Attitudes towards people with mental disorders: Results of a psychometric evaluation and confirmatory factor analysis of the Stigma Towards People with Mental Disorders (SToP- MD) Scale

Attitudes towards people with mental disorders: Results of a psychometric evaluation and confirmatory factor analysis of the Stigma Towards People with Mental Disorders (SToP- MD) Scale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Attitudes towards people with mental disorders: Results of a psychometric evaluation and confirmatory factor analysis of the Stigma Towards People with Mental Disorders (SToP- MD) Scale Jan Christopher Cwik, Marcella L. Woud, Simon E. Blackwell, Tobias Teismann, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6890888/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 May, 2026 Read the published version in BMC Psychology → Version 1 posted 10 You are reading this latest preprint version Abstract Stigmatizing attitudes toward individuals with mental disorders represent a major barrier to treatment, recovery, and social inclusion. The present research introduces and psychometrically evaluates the German-language SToP-MD (Stigma Toward People with Mental Disorders) scale across three independent studies with distinct samples. In study 1 ( N = 266), an initial item pool was developed and refined based on theoretical frameworks and exploratory factor analysis. In study 2 ( N = 488), confirmatory factor analysis supported a two-factor structure comprising prejudiced stigmatization (SToP-MD-PS) and assumption of problems (SToP-MD-AP). The model showed acceptable fit (e.g., CFI = .918, TLI = .892, RMSEA = .078, SRMR = .051) and good internal consistencies (α = .84 and α = .78). In study 3 ( N = 266), convergent and discriminant validity were examined via Spearman correlations with established instruments. As hypothesized, the SToP-MD subscales were positively associated with depression stigma (DSS) and social distance (SDI), and negatively correlated with openness and agreeableness (NEO-FFI), supporting convergent validity. Discriminant validity was partially confirmed by low or non-significant correlations with attitudes toward physically disabled individuals (ATDP), suicide-related cognitions (CCSS), and socially desirable responding (BIDR). Across all three studies, the SToP-MD demonstrated robust psychometric properties. It captures both overt prejudices and implicit burden assumptions, offering a nuanced assessment of public stigma toward mental disorders. The scale can serve as a valuable tool in stigma research, public health monitoring, and evaluation of interventions. Future research should extend validation to more diverse samples and test predictive and longitudinal utility. stigma attitudes mental disorders scale assessment Figures Figure 1 Introduction The stigmatization of people with mental disorders has received growing scientific attention. This is illustrated by the increasing number of studies addressing this topic [ 1 ]. As Corrigan [ 2 ] illustrated, more than 1,000 papers have been published on stigmatization since 2010. Despite this growth in research, the term “stigma” is not well defined [ 3 ]. The lack of a consistent definition led Link and Phelan [ 4 ] to underline the necessity of researchers defining the concept of stigmatization underlying their research. For this article, we use the definition of Link and Phelan [ 4 ], who stated that stigmatization occurs when an attribute (e.g., depressed) is linked with a stereotype (e.g., “depression leads to dangerous behavior”). People with that attribute become associated with the negative association (e.g., “people with depression are dangerous”). Furthermore, people concerned are labeled (e.g., “the depressed [man]”), which results in a closer negative association [ 5 , 6 ] and, thus, higher stigmatization. As stated by Corrigan and Rao [ 7 ]: “Stigma is a societal creation, what social psychologists have come to describe as prejudice and discrimination.” Stigmatization of people with mental disorders is problematic worldwide, especially in countries in which most people live from low or middle incomes [ 8 – 11 ]. There have been several studies investigating factors associated with stigmatization. These studies have found positive relationships between stigmatization and both income and age and a negative association between stigmatization and education. Study results showed that male gender, higher age, lower educational level, and solitariness are significantly related to negative attitudes towards people with depression [ 12 – 14 ]. Stigmatization has a significant impact on people suffering from mental disorders, recovery from these disorders, and everyday social life: for instance, studies showed that stigmatization leads people concerned not to search for information about their mental problems or how to get therapeutic help [ 15 – 17 ]. Also, stigma impairs recovery, reduces treatment adherence, and contributes to social exclusion, low self-esteem, and health disparities [ 18 – 20 ]. However, research has also indicated that stigmatization can be influenced [ 21 – 25 ]. In line with this, evidence suggests that both informational and contact-based interventions can reduce stigma [ 21 , 22 ]. To date, several scales for the assessment of stigmatization have been developed and three systematic reviews have been published to give an overview about available scales [ 1 , 26 , 27 ]. According to Link et al. [ 27 ] measures related to stigmatization towards people with mental disorders can be classified as social distance scales [ 28 – 31 ], semantic differential scales [ 32 – 36 ], and attributional measures [ 37 , 38 ]. Link et al. [ 27 ] noted that validity of most scales is questionable, in that these scales are vulnerable to social desirability demands, and the underlying scales and items often ask to compare people with mental disorders with “average” people are questionable. A variety of scales have been developed to assess different aspects of stigma related to mental disorders. Most focus on self-stigma [ 39 – 41 ], personal experiences of stigmatization, or perceived public stigma. Many are disorder-specific (e.g., for depression or schizophrenia), and few assess generalized public attitudes. The widely used Devaluation-Discrimination Scale [DDS; 42] measures perceived devaluation by others but not personal stigma. Some instruments such as the Self-Stigma of Mental Illness Scale [SSMIS; 43], the Depression Stigma Scale [DSS; 44], the Opinions about mental illness scale (OMI) [ 45 , 46 ], and the Community-Attitudes-toward-the-Mentally-Ill Inventory (CAMI) [ 47 ] assess elements of public stigma but have limitations. For instance, only the Agreement subscale of the SSMIS captures endorsement of stereotypes. The OMI and CAMI cover complex attitude dimensions but are lengthy, outdated, or not aligned with current concepts of stigma. The more recent Prejudice towards People with Mental Illness scale [PPMI; 48] incorporates prejudice theories but focuses on specific dimensions like fear or authoritarianism. Overall, existing tools often lack brevity, conceptual clarity, or general applicability across mental disorders. A more recent addition, the PPMI [ 48 ], integrates prejudice theory and covers fear, avoidance, authoritarianism, and unpredictability. Yet, despite these advancements, a short, psychometrically sound instrument that captures generalized, personal stigma toward people with mental disorders is still lacking. Taken together, most available scales have been built to assess either perceived stigma or self-stigma or stigma related to specific mental disorders (e.g., depression or schizophrenia) [ 49 ]. Mainly because of discussions related to the Germanwings crash in March 2015 [ 50 – 52 ], the Magdeburg Christmas market attack on 20 December 2024, or other disasters that had been connected to offenders with mental disorders, there are essential aspects of negative attitudes towards people with mental disorders neglected in these scales (e.g., regarding abolition of the non-disclosure obligation to protect others or aspects regarding higher, health system costs). Nevertheless, these aspects should also be measurable when investigating the impact of disasters on stigmatization in public measures or when aiming to measure the effectiveness of anti-stigma campaigns [ 53 – 55 ]. Considering these aspects, we decided to develop a scale that measures Stigma Towards Persons with Mental Disorders (SToP-MD) and encompasses relevant aspects of stigma toward individuals concerned. In contrast to other available scales, this scale was built to assess stigmatizing attitudes related to mental disorders in general, without taking into consideration if the respondents themselves suffer from a mental disorder. The constructed scale instead measures stigmatizing attitudes in the population. Three studies were conducted to investigate the psychometric utility of the SToP-MD scale. The first study aimed to test the factorial structure, the construct validity, and the internal consistency of the scale. To analyze the relationships between stigma towards persons measured with the SToP-MD scale and other constructs, we additionally assessed stigma, prejudice, or negative attitudes towards people with mental disorders by using different available scales, social distance, personality traits (neuroticism, open to experience, and agreeableness), attitudes toward physically disabled people, attitudes towards suicide, and socially desirable responding. In the second study, a confirmatory factor analysis (CFA) was used to confirm the factor structure of the SToP-MD scale of study 1. Finally, in the third study, the sensitivity to change of the SToP-MD scale was investigated by randomly assigning participants to three groups, whereas each group was shown either a negative, neutral, or positive film about depression. Study 1: Exploratory factor analysis and psychometric properties of the SToP-MD scale Methods Participants and procedure. The study was conducted using an online questionnaire developed using SoSci Survey [ 56 ] and made available to participants on www.soscisurvey.com . The complete sample consisted of N = 335 participants. Because of incomplete questionnaires, 69 participants were excluded, so the final sample consisted of n = 266 (74.9%) participants, of whom 69.9% ( n = 186) were female, and 30.1% ( n = 80) were male. Age ranged from 18 to 88 years, with a mean of 28.77 years ( SD = 13.69). The employment status of the participants was as follows: 152 (57.1%) students, 55 (20.7%) workers/employees, 19 (7.1%) clerks, 11 (4.1%) trainees, 10 (3.8%) pupils, 8 (3.0%) freelancers, 6 (2.3%) retired participants, and 5 (1.9%) job-seeking participants. In terms of nationality, 262 (98.5%) were German, 1 (0.4%) was Austrian, 1 (0.4%) was Spanish, 1 (0.4%) was Brazilian, and 1 (0.4%) was a US-American citizen. The educational background of participants was as follows: 8 (3.0%) pupil, 1 (0.4%) certificate of secondary education, 5 (1.9%) secondary school level I certificate, 21 (7.9%) apprenticeship, 16 (6.0%) vocational diploma, 154 (57.9%) diploma from German secondary school qualifying for university admission or matriculation, 57 (21.4%) polytechnic degree or university degree, and 4 (1.5%) participants had another educational background. Of all participants, 48 (18.0%) had no own income, 133 (50.0%) had a low income (< 1000 €), 62 (23.3%) participants had a middle income (1000 € − 3000 €), 18 (6.8) participants had a high income (< 3000 €), and 5 (1.9%) participants did not want to give any information about their income. Overall, 56 (21.1%) participants stated that they have or have had contact with a mental health professional, 19 (7.1%) reported suffering from a mental disorder at the time of their participation in the study, 42 (15.8%) reported having suffered from a mental disorder in the past, 73 (27.4%) participants stated that a loved one was suffering from a mental disorder at the time of their participation, and 74 (27.4%) stated that a loved one had suffered from a mental disorder in the past. Participants were recruited via personal contact and postings on the notice boards of the Ruhr-Universität Bochum as well as in relevant groups on social media. Additionally, students were approached and informed about receiving course credit for their participation. Individuals who expressed interest in participating received a link to the online survey. The online survey was completed anonymously, and participants could only proceed to the subsequent questionnaire once all questions had been answered. Before the assessments, participants were informed about the study's procedure, the voluntary nature of their participation, data storage, and security. Additionally, participants received information about the study's topic, and only individuals aged 18 years or older were allowed to participate. Participants provided their informed consent, and after ensuring confidentiality, they were provided with the link to the survey questionnaire. Construction of the Stigma Towards People with Mental Disorders Scale. The construction of the SToP-MD scale comprised five steps. In the first step, we screened available stigma scales listed in the reviews by Sibley and Duckitt [ 57 ] as well as Brohan et al. [ 1 ] to identify relevant aspects of stigmatization. In the next step, psychological literature was screened on stigmatization, prejudice, stereotypes, and attitudes. In particular, the stereotype aspects identified by Hayward and Bright [ 58 ] were considered. Then, items were generated based on this information, reports from users of mental health services ( N = 20), our clinical experience, and actual public discussions related to the Germanwings disaster [see 51]. These items were discussed with several clinical experts. Finally, items were reformulated to yield high variance in participants’ answers. The first draft of the SToP-MD scale consisted of 22 items measuring stigmatization towards people with mental disorders in general (see Table 1 ), on a six-point Likert scale ranging from 1 = “completely disagree” to 6 = “completely agree”. The scale was constructed to measure stigmatization on several aspects of everyday life, for instance, familial aspects (e.g., “A family member with a mental disorder often entails many burdens for the family.”), occupational aspects (e.g., “I would have no hesitation to work with a person with a mental disorder.”) or aspects concerning society (e.g., “People with mental disorders are burdensome for society.”). Additionally, prejudices against people with mental disorders (e.g., “Many people with mental disorders are less intelligent.”) or against mental disorders by their nature (e.g., “Mental disorders are often a sign of a weakness of character.”) were considered. The polarity of four items (2, 7, 17, 20) must be reversed so that a higher sum score indicates more negative attitudes towards people with mental disorders. Table 1 Original 22 items of the Stigma Towards People with Mental Disorders (SToP-MD) scale in German and the English translation of these items. Item # Item (German original version) Item (English translation) 1 Meiner Meinung nach wäre es besser, wenn Personen mit psychischen Störungen nur in Jobs mit geringer Verantwortung arbeiten dürften. In my opinion it would be better if people with mental disorders could only work in jobs with less responsibility. 2 Personen mit psychischen Störungen sind beruflich genauso leistungsfähig wie Personen ohne psychische Störungen. People with mental disorders are as efficient professionally as people without mental disorders. 3 Ein Familienmitglied mit einer psychischen Störung bringt oftmals viele Belastungen für die Familie mit sich. A family member with a mental disorder often poses a great burden to the family. 4 Personen mit psychischen Störungen belasten die Gesellschaft. People with mental disorders are burdensome for society. 5 Wenn ein Mitglied meiner Familie an einer psychischen Störung leiden würde, wäre mir das unangenehm. If a member of my family were to suffer from a mental disorder, this would be unpleasant for me. 6 Personen mit psychischen Störungen werden häufiger straffällig. People with mental disorders are more delinquent. 7 Ich hätte keine Bedenken, mit einer Person mit einer psychischen Störung zusammenzuarbeiten. I would have no hesitation to work with a person with a mental disorder. 8 Man sollte zum Schutz anderer die Schweigepflicht von PsychotherapeutInnen und PsychiaterInnen überdenken. One should protect others by reconsidering the non-disclosure obligation of psychotherapists and psychiatrists. 9 Personen mit psychischen Störungen verursachen häufig unverhältnismäßig hohe Kosten für das Gesundheitssystem. People with mental disorders often cause disproportionately high costs for the health system. 10 Manchmal denke ich, dass eine psychische Störung nur eine vorgeschobene Entschuldigung ist. Sometimes I think that a mental disorder is only an excuse for something else. 11 Es ist am besten, Personen mit psychischen Störungen einfach aus dem Weg zu gehen. It is best just to get out of the way of people with mental disorders. 12 Personen mit psychischen Störungen sind oft unberechenbar. People with mental disorders are often unpredictable. 13 Psychische Störungen sind häufig auch ein Zeichen von Charakterschwäche. Mental disorders are often a sign of a weakness of character. 14 Personen mit psychischen Störungen haben eher Probleme, soziale Regeln zu befolgen. People with mental disorders have more problems following social rules. 15 Viele Personen mit psychischen Störungen sind weniger intelligent. Many people with mental disorders are less intelligent. 16 Oftmals sind Personen mit psychischen Störungen selbst schuld an ihren Problemen. People with mental disorders are often to blame for their problems. 17 Ich denke nicht, dass Personen mit psychischen Störungen ihre Arbeitskollegen belasten. I do not think that people with mental disorders burden their work colleagues. 18 Wer einmal unter einer psychischen Störung leidet, wird wahrscheinlich immer Probleme damit haben. Someone who has once suffered from a mental disorder, is likely to always have problems with it. 19 Aufgrund der häufigeren Krankheitstage sollte in Betracht gezogen werden, dass Personen mit psychischen Störungen höhere Krankenkassenbeiträge zahlen. Due to the frequent sick days, the possibility that people with mental disorders pay higher health insurance contributions should be considered. 20 Personen mit psychischen Störungen sind eher keine Gefahr für andere. People with mental disorders are most likely no threat to others. 21 Würde ich selber eine psychische Störung entwickeln, würde ich das vermutlich vor anderen verbergen. If I were to develop a mental disorder, I would probably conceal it from others. 22 Personen mit psychischen Störungen können einem Angst machen. People with mental disorders can cause fear in others. The original English version and the final version of the SToP-MD scale can be found in the supplementary materials. Measures All questionnaires used to assess the psychometric quality of the SToP-MD scale had already been developed before the implementation of this study. The sources for these questionnaires are indicated alongside each questionnaire. Depression Stigma Scale (DSS). The DSS [ 44 ] assesses stigmatizing attitudes towards people with depression and consists of 18 items that are answered on a five-point Likert scale, ranging from 1 = “strongly disagree” to 5 = “strongly agree” [ 12 ]. The DSS comprises two subscales measuring personal stigma (DSS-PS) and perceived stigma (DSS-PC), each with 9 items. The stigma score is calculated by summing up all item scores, with a potential maximum score of 90. Higher scale scores indicate a higher manifestation of stigmatization towards persons with depression. The internal consistency of the total scale is α = 0.78, whereas the DSS-PS subscale has an internal consistency of α = 0.76–0.77, and the DSS-PC subscale of α = 0.82 [ 12 , 59 ]. We expected significantly positive associations between DSS and SToP-MD, and thus this questionnaire was used for establishing convergent validity of the SToP-MD scale. Social Distance Items (SDI). The SDI was used by Link et al. [ 60 ] to measure social distance after reading case vignettes describing a person with a mental disorder or physical problems and divergent levels of behavior. The SDI has excellent internal consistency α = 0.92. Compared to the original version of the scale that uses a four-point Likert scale format, we used a five-point Likert scale from 1 = “definitely willing” to 5 = “definitely unwilling” referring to [ 61 ]. By summing scores up, one receives a score for social distance whereby higher scores represent higher social distance from people with mental disorder. The SDI was also used for establishing convergent validity of the SToP-MD scale. Thus, we expected significantly positive associations between both scales. NEO Five Factor Inventory (NEO-FFI). The NEO-FFI [ 62 ] is a self-rating scale, which assesses the factors neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness with each 12 items on a five-point Likert scale from “strongly disagree” to “strongly agree”. In the present study only the three subscales for neuroticism (NEO-FFI-N), openness to experience (NEO-FFI-O), and agreeableness (NEO-FFI-A) of the German version [ 63 ] were used. Lower scores in NEO-FFI-N are associated with emotional stability, whereas higher scores are associated with emotional instability. Lower scores in NEO-FFI-O are associated with being more conservative and careful, whereas higher scores are associated with curiosity. Finally, lower scores in NEO-FFI-A are associated with competition orientation and antagonism, whereas higher scores are associated with being more altruistic. The internal constancy of this German three scales lies between α = 0.63 (openness to experience) and α = 0.82 (neuroticism), with a test-retest-reliability between r tt = 0.67 (openness to experience) and α = 0.82 (neuroticism) [ 64 , 65 ]. Additionally, factor analyses and correlation analyses with scales measuring similar and different constructs confirm the validity of the questionnaire [ 63 ]. We expected that openness to experience and agreeableness would reveal significantly positive associations with the SToP-MD scale, whereas we hypnotized a significantly negative association between SToP-MD and neuroticism. Attitudes Toward Disabled Persons scale (ATDP). The ATDP scale [ 66 ] measures negative attitudes towards people who are physically disabled. In our study we used the German version of the scale (Einstellung gegenüber Körperbehinderten), which is similar to the [ 67 ]. ATDP measures attitudes towards people who are physically disabled on four subscales, with an internal consistency (Cronbach’s α) between α = 0.88 and α = 0.93 as well as adequate factorial structure and validity [ 67 , 68 ]. For the present study subscales for “discomfort and insecurity in the presence of physically disabled persons” (ATDP-D; 15 items) and “rejection of social integration” (ATDP-R; 6 items) were used. Whereas Seifert and Bergmann [ 67 ] report good internal consistency for the first subscale (α = 0.81–0.90), the internal consistency for the latter is questionable (α = 0.56–0.77). Items of the ATDP are rated on a six-point Likert scale from 1 = “completely disagree” to 6 = “completely agree”. Most of the items became reoriented (items: 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 14, 16, 18, 19), thus higher sum scores indicate higher adverse attitudes towards people physically disabled persons. We expected no significant associations between the ATDP and the SToP-MD scale, on the basis that attitudes toward physically disabled people may be based on a different psychological construct to attitudes towards people with mental disorders. Thus, this questionnaire was used to investigate divergent validity. Cognitions Concerning Suicide Scale (CCSS). The German version of the CCSS [ 69 ] is a 17-item self-report measure to assess attitudes towards suicide [ 70 ]. All items are answered on a six-point Likert scale ranging from “0 = I disagree” to “5 = I agree”. To receive a consistent scoring of the questionnaire, scores of 8 items are reversed (items: 4, 5, 9, 10, 11, 12, 14, 17), such that higher scores reflect a positive perception of suicide. The CCSS consists of three subscales measuring the “right to commit suicide” (CCSS-S: 8 items; e.g., “Everyone has the right to commit suicide”, “When life consists of intolerable pain, suicide is an acceptable alternative”), suicide as an “interpersonal gesture” (CCSS-I: 5 items, e.g., “I sometimes think suicide would be a good way to pay back people who have hurt me deeply”; “Taking my own life would be a good way to make sure I would always be remembered”), and a third factor measuring “resiliency” (CCSS-R: 4 items; “Even if I got tired of living, I would not seriously consider suicide as a way out”; “Even if I could not be with the person I love, I would not consider suicide”). The German version of the CCSS has a sufficient internal consistency for the overall CCSS-scale (α = 0.83) and all three subscales (CCSS-S: α = 0.83; CCSS-I: α = 0.70; CCSS-R: α = 0.67) as well as an acceptable construct and discriminant validity [ 123 ]. The CCSS was also used to investigate divergent validity. We did not expect any significant association between the CCSS and the SToP-MD scale. Balanced Inventory of Desirable Responding (BIDR). The BIDR [ 71 ] assesses self- and other-deception on two scales by each 20 seven-point Likert scaled items. Both scales are balanced between negatively and positively oriented items. For the present study, we used the German 20-items version of the BIDR [ 72 ]. All items are anchored from 1 = “completely disagree” to 7 = “completely agree”. The German version contains 13 negatively oriented items. Consequently, thirteen items are reverse-scored (items: 2, 4, 5, 7, 9, 10, 11, 12, 14, 15, 17, 18, 20). Summing all items provides a score for social desirability. Both scales of the German version showed acceptable internal consistencies (self-deception: α = 0.64; other-deception: α = 0.66), clear factor structure, and good construct validity [ 72 ]. This questionnaire was used to control for the effects of social desirability on participants’ answers. As social desirability represents a general response tendency rather than a specific attitudinal domain, low or non-significant associations with the SToP-MD scale were anticipated, which would support the scale’s divergent validity. Statistical analyses. In a first step, we conducted an item analysis to investigate which items of the initial version of the SToP-MD scale should be retained. We excluded items with an item difficulty < 30.0%. The factorial structure of the SToP-MD scale, which consists of the remaining items, was tested by a principal component analysis (PCA) with oblimin rotation. Requirements for the PCA were examined using the Kaiser-Meyer-Olkin measure of sampling adequacy ( KMO ) [ 73 ] and Bartlett’s test of sphericity [ 74 ]. The correlation between the SToP-MD scales was analyzed using the Spearman correlation coefficient ( r S ). Calculating McDonald’s ω [ 75 – 77 ] determined the internal consistency of the derived scales. Kurtosis, skewness, and means were calculated, and the normal distribution of the sum scores of all scales used in this study was tested using the Kolmogorov-Smirnov test. Finally, construct validity was investigated using r S between the SToP-MD subscales, demographic variables, and criterion measures. For the association between the SToP-MD subscales and nominal demographic variables, eta was calculated. Interpretation of the effect sizes was based on Cohen [ 78 ], where r s = 0.1–0.29 represents a small association, r s = 0.3–0.49 represents a medium association, and r s ≥ 0.5 represents a large association. Associations between SToP-MD scales and nominal demographic variables were analyzed by using cross-tabulations and Χ 2 -tests. Data analysis was conducted using SPSS version 30.0 for Mac [ 79 ]. Results Item selection. In a first step, an item analysis was conducted to investigate the adequacy of all 22 items included in the questionnaire. Therefore, item difficulty was calculated. Subsequently, eight items with inadequate item difficulty (< 30.0%) were excluded. Furthermore, three items with negative polarity where also excluded because of the marginal benefits, but considerable disadvantages for psychometric properties and dimensionality of the scale [ 80 ]. Thus, the final version of the SToP-MD scale comprises 10 items. The item difficulty of remaining items ranged from 30.0–72.0% (see Table 2 ). Table 2 Results of reliability and item analysis of the initial items of the Stigma Towards People with Mental Disorders Scale (SToP-MD) (Study 1; N = 266). Item # M ( SD ) range (min – max) item difficulty (%) action SToP-MD 1 2.94 (1.55) 1–6 38.8 SToP-MD 2 3.50 (1.39) 1–6 50.0 item deleted b SToP-MD 3 4.60 (1.9) 1–6 72.0 SToP-MD 4 2.66 (1.38) 1–6 33.2 SToP-MD 5 2.45 (1.60) 1–6 29.0 item deleted a SToP-MD 6 2.24 (1.35) 1–6 24.8 item deleted a SToP-MD 7 2.36 (1.40) 1–6 27.2 item deleted a SToP-MD 8 2.84 (1.71) 1–6 36.8 SToP-MD 9 2.50 (1.43) 1–6 30.0 SToP-MD 10 2.16 (1.51) 1–6 23.2 SToP-MD 11 1.61 (1.23) 1–6 12.2 item deleted a SToP-MD 12 3.23 (1.35) 1–6 44.6 SToP-MD 13 1.77 (1.30) 1–6 15.4 item deleted a SToP-MD 14 2.76 (1.39) 1–6 35.2 SToP-MD 15 1.47 (1.04) 1–6 9.4 item deleted a SToP-MD 16 1.77 (1.21) 1–6 15.4 item deleted a SToP-MD 17 3.25 (1.32) 1–6 45.0 item deleted b SToP-MD 18 3.17 (1.44) 1–6 43.4 SToP-MD 19 1.85 (1.34) 1–6 17.0 item deleted a SToP-MD 20 2.95 (1.37) 1–6 39.0 item deleted b SToP-MD 21 3.73 (1.57) 1–6 54.6 SToP-MD 22 3.37 (1.40) 1–6 47.4 Note : a = item deleted because of low item difficulty; b = item deleted because negative item polarity. Factor structure. The Kaiser-Meyer-Olkin measure ( KMO ) of sampling adequacy revealed a good fit of the data ( KMO = 0.86), and Bartlett’s test of sphericity was significant (χ² = (45, N = 266) = 1116.55, p < 0.001), indicating a strong and appropriate relationship among the items. Based on these results, in a subsequent step a principal component analysis with oblimin rotation was conducted, resulting in a first component “Prejudiced Stigmatization” (SToP-MD-PS) (eigenvalue: 3.98) explaining 39.78% of the variance and second component “Assumption of Problems” (SToP-MD-AP) (eigenvalue: 1.07) explaining 10.70% of the variance. Overall, both factors explained 50.48% of the variance. As can be seen in Table 3 , all factor loadings were adequately high (at least 4 factor loadings > 0.60 and all 13 factor loadings > 0.40) to reliably interpret the components [ 81 ]. Table 3 Factor loadings of finally included items of the Stigma Towards People with Mental Disorders Scale (SToP-MD) after conducting the oblimin rotated Principal Component Analysis (Study 1; N = 266) on the “prejudice stigmatization” subscale (PS) and “Assumption of Problems” subscale (AP). Item # Factor loadings PS AP SToP-MD 1 0.825 SToP-MD 3 0.746 SToP-MD 4 0.497 SToP-MD 8 0.799 SToP-MD 9 0.588 SToP-MD 12 0.655 SToP-MD 14 0.441 SToP-MD 18 0.604 SToP-MD 21 0.675 SToP-MD 22 0.699 Scale properties. Internal consistency was assessed using McDonald’s ω. The SToP-MD-PS subscale with 7 items had an ω of 0.83, thus the internal consistency of the scale is good, whereas the SToP-MD-AP subscale with 3 items had an ω of 0.51, which is a poor internal consistency. The possible sum score of the SToP-MD-PS subscale ranges from 7 to 42. In contrast, the answers of participants in this study ranged from 8 to 42, with a mean of 20.30 ( SD = 7.13) and the possible sum score of the SToP-MD-AP subscale ranges from 3 to 18, whereas answers of participants in this study ranged from 4 to 18, with a mean of 11.50 ( SD = 3.00). The Kolmogorov-Smirnov-test showed that both SToP-MD subscale sum scores in this population were not normally distributed ( p < 0.001). A more detailed view of the data of the SToP-MD-PS subscale showed a skewness of 1.08, which indicates an asymmetrical distribution with a long tail to the right. In contrast, the kurtosis of 1.96 indicates a more peaked distribution than a Gaussian distribution. Contrarily, data of the SToP-MD-AP subscale showed a skewness of -0.20, which means an asymmetrical distribution with a long tail to the left. In contrast, the kurtosis of -0.15 indicates a less peaked distribution with lighter tails than a Gaussian distribution. The inter-item-correlations for items of the SToP-MD-PS subscale ranged from 0.48–0.62, and for items of the SToP-MD-AP subscale from 0.29–0.35. Both SToP-MD subscales showed significant association with a medium effect size ( r s = .432, p < 0.001). The psychometric properties of the SToP-MD subscales and the other measures used in this study are presented in Table 4 . Table 4 Characteristics of data of used measurements. M SD Min Max ω skewness kurtosis K-S-test SToP-MD-PS 20.30 7.13 8 42 0.84 1.08 1.96 p < 0.001 SToP-MD-AP 11.50 3.00 4 18 0.51 -0.20 -0.15 p < 0.001 SDI 26.59 6.28 7 35 0.92 -1.07 1.13 p < 0.001 DSS 48.15 11.25 19 90 0.86 0.66 1.80 p = 0.001 DSS-PS 17.76 7.37 9 45 0.87 1.42 2.20 p < 0.001 DSS-PC 30.38 6.80 10 45 0.85 -0.46 0.31 p = 0.001 NEO-FFI-N 32.08 8.16 12 56 0.87 0.45 0.11 p < 0.001 NEO-FFI-A 45.12 6.74 27 59 0.82 -0.57 0.10 p < 0.001 NEO-FFI-O 44.30 6.92 21 59 0.78 -0.27 0.21 p = 0.018 ATDP 94.32 13.83 54 125 0.88 -0.32 -0.35 p = 0.010 ATDP-D 67.13 12.06 37 90 0.87 -0.31 -0.50 p = 0.006 ATDP-R 27.20 3.77 12 36 0.68 -0.54 0.79 p < 0.001 BIDR 79.28 12.76 48 117 0.67 0.14 -0.10 p = 0.040 BIDR-S 41.42 7.75 20 64 0.66 0.18 -0.16 p = 0.200 BIDR-O 37.87 8.88 14 63 0.63 -0.21 -0.05 p = 0.048 CCSS 41.10 13.19 17 87 0.85 0.66 0.35 p = 0.001 CCSS-S 24.72 8.33 8 48 0.80 0.16 -0.52 p = 0.067 CCSS-I 8.66 4.09 5 30 0.79 2.30 7.15 p < 0.001 CCSS-R 7.73 4.13 4 23 0.71 1.40 1.84 p < 0.001 Note : ω = McDonald’s omega; K-S-test = Kolmogorov-Smirnov-test; SToP-MD = Stigma towards people with mental disorders scale; SToP-MD-PS = prejudiced stigmatization subscale; SToP-MD-AP = assumption of problems subscale; ATDP = Attitudes toward physically disabled persons; ATDP-D = discomfort and insecurity in the presence of physically disabled persons subscale; ATDP-R = rejection of social integration subscale; SDI = Social Distance Items; NEO-FFI = NEO five factor inventory; NEO-FFI-N = neuroticism subscale; NEO-FFI-A = agreeableness subscale; NEO-FFI-O = open to experience subscale; DSS = Depression Stigma Scale; DSS-PS = personal subscale; DSS-PC = perceived subscale; BIDR = Balanced Inventory of Desirable Responding; BIDR-S = self-deception subscale; BIDR-O = other-deception subscale; CCSS = Cognitions Concerning Suicide Scale; CCSS-S = right to commit suicide subscale, CCSS-I = interpersonal gesture subscale; CCSS-R = resiliency subscale. Construct Validity. Spearman’s correlation analyses confirmed convergent and discriminant validity of the SToP-MD scale (see Table 5 ). Both subscales showed strong positive correlations with measures of SDI and DSS, particularly DSS-PS. Negative associations were found with openness to experience and agreeableness (NEO-FFI), as expected. Discriminant validity was partially supported: While most associations with CCSS and BIDR were nonsignificant, small correlations were found with CCSS-I and the BIDR total score. Unexpected negative correlations with ATDP were also observed, suggesting potential overlap in construct. Table 5 Spearman’s correlation coefficients between SToP-MD subscales and external measures (Study 2; N = 266). SToP-MD-PS SToP-MD-AP r s p r s p SDI .626 < .001 .456 < .001 DSS .587 < .001 .430 < .001 DSS-PS .715 < .001 .539 < .001 DSS-PC .218 < .001 .120 .050 NEO-N .010 .874 .107 .082 NEO-O − .225 < .001 − .135 .028 NEO-A − .242 < .001 − .328 < .001 ATDP − .382 < .001 − .270 < .001 ATDP-D − .370 < .001 − .257 < .001 ATDP-R − .166 .007 − .145 .018 CCSS .047 .447 .174 .004 CCSS-S − .069 .265 .050 .414 CCSS-I .139 .024 .226 < .001 CCSS-R .029 .642 .116 .060 BIDR − .029 .642 − .141 .021 BIDR-S − .015 .809 − .078 .205 BIDR-O − .023 .705 − .116 .058 Note : SToP-MD-PS = prejudiced stigmatization subscale of the Stigma toward People with Mental Disorders scale (SToP-MD); SToP-MD-AP = assumption of problems subscale; SDI = Social Distance Items; DSS = Depression Stigma Scale (total score); DSS-PS = DSS personal stigma; DSS-PC = DSS perceived stigma; NEO-N/O/A = Neuroticism, Openness, and Agreeableness subscales of the NEO Five Factor Inventory; ATDP = Attitudes Toward Disabled Persons (total score); ATDP-D = discomfort and insecurity in presence of physically disabled persons; ATDP-R = rejection of social integration; CCSS = Cognitions Concerning Suicide Scale (total score); CCSS-S/I/R = CCSS subscales (right to commit suicide/interpersonal gesture/resiliency); BIDR = Balanced Inventory of Desirable Responding (total score); BIDR-S/O = BIDR self- and other-deception subscales. r s = Spearman’s rho; p = significance level. Correlations with p < .05 are considered statistically significant and are shown in bold. Demographic variables. The results of the Χ 2 -tests revealed a significant positive association between the SToP-MD-PS score and participants’ gender (η = 0.417, adjusted R 2 = 0.039, p < 0.001). In contrast, there was no significant association between the SToP-MD-AP score and participants’ gender (η = 0.307, adjusted R 2 = 0.010, p = 0.057). Conversely, the SToP-MD-AP score showed a positive significant association with participants’ age ( r s = 0.167, p = 0.006). In contrast, the SToP-MD-PS score was not significantly associated with participants’ age ( r s = 0.108, p = 0.079). Additionally, there were significant associations between the SToP-MD subscales and participants’ educational background (SToP-MD-PS: η = 0.307, adjusted R 2 = 0.375, p = 0.011; SToP-MD-AP: η = 0.307, adjusted R 2 = 0.276, p = 0.043). Discussion The study investigated the factor structure, reliability, and construct validity of the newly developed Stigma Towards People with Mental Disorders (SToP-MD) scale. First, we tested the adequacy of all 22 items initially included in the questionnaire. The item selection led to the elimination of nine items due to inadequate item discrimination and/or difficulty. Thus, the final version of the SToP-MD scale consisted of 13 items. It is striking that almost all items with a negative polarity (i.e., requiring reverse scoring) were eliminated. There is evidence that the polarity of items fundamentally impacts the dimensionality of measures [ 82 , 83 ]. Three of these items with a negative polarity additionally had low item discrimination scores (items 2, 17, 20), whereas item 7 was excluded because of low item difficulty. The polarity of these items could be associated with the item difficulty or item discrimination. Thus, whether the same items with a positive polarity could still reveal these patterns and have to be excluded could still be tested. Furthermore, five more items with positive polarity were excluded because of low item discrimination (items 11, 13, 15, 16, 19). A closer evaluation of these items leads to the conjecture that these items are not adaptable in a stigma scale that is built to assess stigmatization towards persons with mental disorders in general (e.g., item 11: “It is best just to get out of the way of people with mental disorders” or item 15: “Many people with mental disorders are less intelligent”). Furthermore, it could be possible that participants do not agree with such statements in general but would agree with them related to specific mental disorders. Thus, it is possible that participants would differentiate between, for instance, a person with major depression or a person with schizophrenia when answering items like “Mental disorders are often a sign of a weakness of character” or “It is best, just to go out of the way of people with mental disorders”. However, this assumption remains untested in the current study. A principal component analysis based on the remaining 10 items indicated a two-component scale structure. The number of the remaining items and the extent of factor loadings indicated a reliable interpretation of both subscales. However, the SToP-MD-AP subscale showed poor internal consistency. This is also reflected in the focus of the items, which capture vast aspects of stigmatization. Should this low internal consistency be confirmed in further studies, consideration should be given to omitting this subscale. While the sample size of this study was adequate for the statistical methods used, it remains to be seen whether the factor structure found in the present study will be reproducible in future studies and bigger sample sizes. Concerning the psychometric properties of the scale, the construct validity of the scale was supported by mostly expected associations between the SToP-MD subscales and a set of relevant criterion measures, such as social distance and depression-related stigma. As expected, higher social distance scores were significantly associated with higher SToP-MD scores. Social distance is a concept that has been used in several studies before to measure stigmatizing attitudes towards persons with mental disorders [ 5 , 50 , 61 , 84 – 91 ]. According to Angermeyer and Matschinger [ 61 ], social distance can be adequately used to assess attitudes towards people with mental disorders. Furthermore, the DSS as a well-used valid and reliable stigma scale related to depression [ 12 , 26 , 44 , 59 , 92 ] was also significantly associated to the SToP-MD sum score. According to the idea of the SToP-MD, which aims to assess stigmatizing attitudes of respondents towards people with mental disorders, the association with the personal stigma subscale of the DSS was substantially stronger than with the perceived stigma subscale. This pattern of correlations supports the conceptual alignment of the SToP-MD scale with personal attitudes, providing strong evidence of convergent validity, particularly concerning personal stigma. In terms of personality traits, two of the three NEO-FFI subscales—openness to experience and agreeableness—showed significant negative associations with both SToP-MD subscales. These results are consistent with prior findings indicating that lower openness and agreeableness are associated with higher levels of stigmatizing attitudes [ 57 , 93 – 95 ]. For example, Canu et al. [ 96 ] found that agreeableness was positively linked to more favourable appraisals of adults with ADHD, and McCrae et al. [ 97 ] observed similar associations with stigma toward individuals with physical disabilities. Contrary to our expectations, neuroticism was not significantly associated with either SToP-MD subscale. This aligns with previous findings suggesting that neuroticism may be unrelated to public stigma [ 98 ], while its role may be more pronounced in self-stigma or internalized negative beliefs [ 99 , 100 ]. Taken together, these results further support the convergent validity of the SToP-MD scale by replicating known associations between specific personality traits and stigmatizing attitudes. Discriminant validity was tested using measures of socially desirable responding, attitudes towards suicide, and attitudes towards physically disabled people. Contrary to our expectations, both SToP-MD subscales were negatively correlated with the ATDP total score and its subscales [ 67 , 68 ]. This indicates that participants who endorsed more stigmatizing attitudes towards people with mental disorders reported less discomfort or rejection concerning physically disabled persons. While unexpected, this pattern may suggest that stigmatizing attitudes towards people with mental and physical impairments are not part of a general prejudice factor, but rather reflect distinct constructs. This supports the discriminant validity of the SToP-MD scale. It is also consistent with previous literature showing that stigmatization of mental illness tends to be more pronounced than that of physical illness [ 5 , 87 , 101 – 103 ]. As expected, there were no significant associations between the SToP-MD-PS and the CCSS total score or its subscales measuring the right to commit suicide (CCSS-S) and resiliency (CCSS-R) [ 70 , 104 ]. However, a significant positive correlation was found with the CCSS subscale for suicide as an interpersonal gesture (CCSS-I), albeit with a small effect size. The same was true for the SToP-MD-AP, which additionally showed weak associations with the overall CCSS score. One explanation may be that certain items in the CCSS-I (e.g., “Taking my own life would be a good way to make sure I would always be remembered”) are interpreted by participants as indicators of psychological instability, leading to associations with stigmatizing attitudes. Prior research has shown that even professionals sometimes misclassify suicidal behaviour as a symptom of mental illness [ 104 ]. Nevertheless, since the majority of CCSS dimensions did not correlate with SToP-MD subscales, these findings generally support discriminant validity. Finally, and in line with our expectations, no significant associations were observed between the SToP-MD-PS and the BIDR [ 71 , 72 ]. Only the SToP-MD-AP showed a small negative correlation with the BIDR total score, which may reflect slightly more openness in reporting critical views. Still, the overall weak associations suggest that the SToP-MD scale is not strongly influenced by social desirability, supporting its use in self-report formats. The analysis of demographic variables revealed several associations with stigmatizing attitudes towards people with mental disorders. Consistent with previous research [ 12 , 13 , 105 – 109 ], female participants scored significantly lower on the SToP-MD-PS subscale compared to male participants, indicating less stigmatizing attitudes among women. In contrast, the SToP-MD-AP subscale did not show a statistically significant difference between genders, although the trend pointed in the same direction. Regarding age, a significant positive correlation was found only for the SToP-MD-AP subscale, suggesting that older participants were more likely to assume people with mental disorders experience persistent difficulties. The SToP-MD-PS subscale, however, did not correlate significantly with age, which is partly consistent with earlier studies showing nuanced or disorder-specific associations with age [ 108 , 110 ]. Both SToP-MD subscales showed significant associations with educational background, supporting the common finding that lower levels of education are linked to stronger stigmatizing attitudes [ 105 , 109 ]. Higher education was associated with lower stigma scores, which may reflect increased exposure to psychoeducation or more liberal social values. Interestingly, no significant correlation was found between income and stigma, which deviates from some prior research suggesting that lower income is associated with higher stigmatizing attitudes [ 50 , 111 ]. However, this result must be interpreted cautiously given that a large proportion of the sample were students, who typically report low income regardless of their socioeconomic status. Thus, income in this sample may not accurately reflect participants' social or educational resources. Altogether, the demographic analyses support previous findings and highlight gender, age, and education as meaningful factors in shaping stigmatizing attitudes, while also underscoring the importance of sample composition in interpreting such effects. Using the SToP-MD scale, stigma towards people with mental disorders can be validly and reliably assessed. Beyond that, results also indicated interesting associations between stigma towards people with mental disorders and personality traits as well as stigma towards physically disabled people. These results could be seen as an indication that there are divergent constructs underlying stigmatizing behavior. Thus, future studies could investigate in more detail why some people stigmatize people with mental disorders, whereas others stigmatize physically disabled persons. Study 2: Confirmatory factor analysis While Study 1 provided initial evidence for the factorial structure of the SToP-MD through exploratory analyses and Study 2 demonstrated its sensitivity to experimental manipulation, a crucial next step in the validation process is to test the proposed factor model in an independent sample. Study 3, therefore, aimed to examine the factor structure of the SToP-MD using CFA. This approach allows for a rigorous evaluation of the hypothesized measurement model and provides insights into the dimensional stability and construct validity of the scale. By validating the factor structure in a separate sample, this study aims to further establish the psychometric robustness of the SToP-MD further. Methods Participants and procedure The second study aimed to investigate the factor structure of the SToP-MD scale, as found in Study 1. Therefore, a second study was conducted on SoSciSurvey [ 56 ]. By posting the study link on social networks and discussion boards. Again, the online survey was completed anonymously, and all participants were informed about the study's procedure, the voluntary nature of their participation, data storage, and security. Then, they provided their informed consent, and after receiving further reminders about anonymity, they were given the link to the survey questionnaire. Statistical analyses We conducted a Confirmatory Factor Analysis (CFA) using the lavaan package [version 0.6–19; 112] in R [version 4.5.0; 113], applying the Maximum Likelihood with Mean and Variance adjustment (MLMV) estimator. This robust estimator accounts for non-normality by adjusting both test statistics and standard errors. The model specified two latent variables: SToP-MD-PS and SToP-MD-AP. The use of MLMV allows for more reliable fit indices and parameter estimates under mild deviations from multivariate normality assumptions. To evaluate model fit, we extracted several commonly used goodness-of-fit indices: the relative chi-square (χ²/ df ), the root mean square error of approximation (RMSEA) along with its 90% confidence interval, the comparative fit index (CFI), the Tucker–Lewis index (TLI), and the standardized root mean square residual (SRMR). Cut-off criteria were based on established recommendations. A χ²/ df ratio < 3 was considered indicative of good model fit, with values < 5 interpreted as acceptable [ 114 – 116 ]. RMSEA values 0.90 were interpreted as evidence of good fit [ 118 , 119 ]. SRMR values < 0.09 were also considered indicative of good model fit [ 118 ]. Results Sample characteristics The complete sample of study 2 consisted N = 448 participants, of which 65.8% ( n = 295) were female and 34.2% ( n = 153) were male. The age of participants ranged from 18 to 78 years, with a mean of 28.76 years ( SD = 10.74). Of all 448 participants, 262 (58.5%) were students, 93 (20.8%) workers/employees, 22 (4.9%) freelancers, 20 (4.5%) trainees, 12 (2.7%) clerks, 11 (2.5%) retired participants, 11 (2.5%) job-seeking participants, and 7 (1.6%) pupils and 10 (2.2%) participants had another kind of employment status. Confirmatory factor analysis Given the sample size of N = 448 participants, the minimum of at least 300 participants for conducting a CFA was reached [ 120 ]. The CFA model converged successfully and demonstrated an acceptable overall fit to the data. The scaled chi-square statistic was significant, χ²(34) = 74.23, p < .001, indicating some discrepancy between the model and the data; however, chi-square is known to be sensitive to sample size. The robust fit indices provided a more nuanced evaluation: the CFI was 0.918, and the TLI was 0.892. The RMSEA was 0.078, with values below 0.08 typically interpreted as reflecting a reasonable fit. The SRMR was 0.051, indicating a good fit according to conventional thresholds [ 118 ]. All factor loadings were statistically significant ( p < .001) and fell within an acceptable range, with standardized estimates ranging from 0.464 to 0.711. These results support the hypothesized two-factor structure of the SToP-MD scale, reflecting the underlying constructs of public stigma (SToP-MD-PS) and anticipated personal stigma (SToP-MD-AP). Figure 1 illustrates the CFA model. The two latent variables (SToP-MD-PS and SToP-MD-AP) are represented as circles, each with directed arrows pointing to their respective observed indicators. A bidirectional arrow between the latent variables indicates their estimated correlation ( r = .78), suggesting a substantial association between the two stigma dimensions. Discussion This two-factor CFA model supports the theoretical distinction between SToP-MD-PS and SToP-MD-AP. The factor loadings indicate that all items contribute meaningfully to their respective latent constructs, confirming the structural validity of the SToP-MD. The use of robust MLMV estimation enhances confidence in the model’s reliability, even in the presence of potential non-normality in the item responses. This structure provides empirical support for a two-dimensional conceptualization of stigma, with a substantial correlation between the two factors, suggesting they are related but distinct components of mental health stigma. Study 3: Investigation of media on stigma towards people with mental disorders The mass media are a major source of public knowledge about mental illness, but they also play a central role in shaping and perpetuating stigma. Prior studies have shown that news reports frequently associate mental disorders with violence, unpredictability, or incompetence, thereby reinforcing negative stereotypes [ 20 , 121 ]. For example, Corrigan et al. [ 121 ] demonstrated that exposure to recovery-oriented media content can reduce public stigma. At the same time, reports focusing on system failure or individual acts of violence can exacerbate it. This dynamic was evident in the media response to the 2015 Germanwings plane crash, where the co-pilot’s presumed depression was framed as a primary cause of the tragedy. An analysis of German print media found that over 60% of articles implied a direct link between mental illness and the crash, often without adequate psychiatric context or caution [ 51 ]. Such portrayals not only risk reinforcing damaging misconceptions but may also contribute to increased public support for exclusion or coercion. Research on the media’s influence on suicide stigma yields similar concerns: Biblarz et al. [ 70 ] showed that media messages can shape public attitudes not only toward suicide itself, but also toward individuals perceived to be mentally ill, especially when behavior is portrayed in simplistic, causal terms. Against this background, Study 2 was designed primarily to evaluate the sensitivity to change of the SToP-MD scale. Using a brief experimental design, participants were exposed to either stigmatizing or destigmatizing media content about mental illness. By comparing SToP-MD scores before and after this exposure, the study aimed to determine whether the scale is capable of capturing short-term shifts in stigmatizing attitudes—a critical property for instruments used in intervention research. Methods Participants A total of N = 269 individuals consented to participate in the study. However, three subjects ( n = 3) discontinued participation after randomization, so data from 266 individuals ( n = 266) were ultimately included in the analysis. No participant failed the video attention check (i.e., answered one or more of the control questions incorrectly), so all participants were included in the final analyses. Participants were recruited via university mailing lists, social media platforms, and online psychology forums. Participation was voluntary and anonymous. All participants provided informed consent before beginning the study. The final sample consisted predominantly of students and young adults, with a mean age of M = 29.45 ( SD = 12.87; range, 18–85) years. The gender distribution was n = 180 (67.5%) female and n = 86 (32.5%) male. Participants were randomly assigned to one of the three experimental groups (positive: n = 92, neutral: n = 87, negative: n = 87), with approximately equal group sizes. No significant differences were observed in age, gender, or educational background between the groups, indicating that randomization was successful. The majority of participants reported having no formal training in psychology or psychiatry. Design and Procedure The study employed a between-subjects experimental design with three experimental conditions: positive, neutral, and negative media content related to depression. Participants were informed in advance that they would be randomly assigned to one of these groups. Each group was shown a short video differing in its emotional framing of depression: a positive video emphasizing recovery through psychotherapy from the German Alliance against Depression (1:24 min), a neutral educational video on neurotransmitters and depression (1:31 min), or a negatively framed news segment from Tagesschau reporting on the co-pilot's depression in the context of the Germanwings plane crash (1:36 min). Following the video presentation, participants were asked to rate their impression of the video by responding to three evaluative statements, each on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). These items assessed whether participants had attentively and accurately perceived the content and tone of the video. Only data from participants whose responses indicated consistent and attentive viewing were included in the final analyses. Subsequently, participants were asked to provide an overall rating of the emotional valence of the video on a separate 7-point scale (1 = very negative, 7 = very positive) to capture the mood induced by the content. Finally, they completed the SToP-MD questionnaire, which assesses stigmatizing attitudes toward individuals with mental disorders, allowing for the evaluation of potential changes in stigma as a function of media exposure. The questions were: 1) "Please assess how individuals with mental disorders were portrayed in the video.", 2) "Please indicate what kind of mood the video evoked in you.", and 3) "Please rate the emotional atmosphere of the video." Finally, participants were debriefed about the purpose of the study. They were also informed that they could request the deletion of their data afterwards if they disagreed with its use; however, no participant made use of this option." Power analysis An a priori power analysis was conducted using G*Power [122, version 3.1; 123] to determine the required sample size for detecting differences between the three experimental conditions. Based on the study design, a small to medium effect size ( f = 0.19) was assumed, following recommendations from previous research on stigma and media exposure [e.g., 121]. The significance level was set to α = 0.05, the statistical power to 1 – β = 0.80, and the number of groups to three. Statistical Analyses To evaluate the effectiveness of the experimental manipulation, descriptive statistics (means and standard deviations) were calculated for participants’ ratings of (1) the portrayal of people with mental disorders, (2) the mood induced by the video, and (3) the emotional atmosphere of the video. To assess group differences in stigmatizing attitudes as measured by the SToP-MD subscales, non-parametric tests were employed due to violations of normality assumptions. Specifically, a Kruskal–Wallis H test was used to examine overall differences across the three experimental groups (positive, neutral, negative). In the case of a significant omnibus result, pairwise Mann–Whitney U tests were conducted as post-hoc comparisons, with the Bonferroni correction applied to adjust for multiple testing (α = 0.05 / 3 = 0.016). For all tests, effect sizes (η²) were calculated to quantify the magnitude of between-group differences. The threshold for statistical significance was set at p < 0.05 (adjusted where necessary). All statistical analyses were conducted using SPSS version 30.0 for Mac [ 79 ]. Results Attention check Participants' attentiveness to the video content was assessed through three comprehension questions per condition. Overall, no participant gave more than two incorrect answers, indicating a generally high level of attention across all groups. In the positive condition, all participants correctly identified the video’s reference to depression ( n = 92, 100%) and that the expert shown at the end was female ( n = 92, 100%). Additionally, 97.8% correctly recognized the video’s focus on recovery from illness ( n = 90). In the neutral condition, all participants correctly identified the female physician ( n = 87, 100%). Furthermore, 98.9% correctly answered questions regarding neurotransmitters as neural messengers ( n = 86) and the mention of depression ( n = 86). In the negative condition, the majority correctly recalled that the video covered the crash in the French Alps ( n = 86, 98.9%) and the search for the black box ( n = 86, 98.9%). A lower proportion correctly identified the news anchor as female ( n = 72, 82.8%). Given these results, all participants were retained for further analysis, as none failed the attention check in a manner that would warrant exclusion based on predefined criteria. Manipulation check To assess whether the video stimuli differed in terms of perceived content and emotional impact, participants were asked to evaluate three aspects after watching their assigned video: (1) the portrayal of people with mental disorders, (2) the mood induced by the video, and (3) the overall emotional atmosphere. As expected, the videos elicited distinctive evaluations across conditions, consistent with the intended manipulation. Regarding the portrayal of people with mental disorders, participants who viewed the positive video rated the depiction most favourably ( M = 5.59, SD = 1.30), followed by the neutral ( M = 3.98, SD = 0.86) and negative video ( M = 3.00, SD = 1.00). In terms of mood induction, participants exposed to the positive video reported the most positive affective response ( M = 5.20, SD = 1.32), compared to the neutral ( M = 3.93, SD = 1.01) and negative condition ( M = 2.41, SD = 0.91). Similarly, the emotional atmosphere was rated as most positive in the positive video condition ( M = 5.15, SD = 1.24), followed by the neutral video condition ( M = 3.68, SD = 0.99) and the negative video condition ( M = 2.93, SD = 1.08). These findings confirm that the videos differed significantly in emotional tone and evaluative framing, thereby validating the experimental manipulation. Group differences The results of the Kruskal–Wallis H test revealed significant rank differences between groups for the SToP-MD-PS subscale (Χ²(2) = 10.971, p = 0.004; η² = 0.034), whereas no significant differences were found for the SToP-MD-AP subscale (Χ²(2) = 2.716, p = 0.257; η² = 0.003). Post hoc Mann–Whitney U tests, conducted to examine pairwise group differences on the SToP-MD-PS subscale, were adjusted using the Bonferroni correction ( α < 0.016). These analyses revealed a significant difference between participants who viewed the negative video and those who viewed the positive video, with higher stigma scores in the former group (U(92, 87) = 2872.5, p < 0.001; η² = 0.059). However, no significant differences were found between the negative and neutral conditions ( U (87, 87) = 3134.5, p = 0.050; η² = 0.022), nor between the positive and neutral conditions (U(92, 87) = 3526.0, p = 0.169; η² = 0.011). Discussion This study aimed to examine the sensitivity to change of the SToP-MD scale in response to different types of media content related to depression. The findings indicate that the personal stigma subscale (SToP-MD-PS) is responsive to short-term media exposure: participants who viewed a negatively framed news report displayed significantly higher stigma scores than those who watched a positively framed video. These results suggest that the SToP-MD-PS subscale is capable of detecting subtle, experimentally induced shifts in individual stigma, demonstrating its validity as a dynamic measure of attitude change. This result aligns with prior evidence that media content plays a central role in shaping public attitudes toward mental illness. Corrigan et al. [ 121 ] showed that different narrative framings in news media can either increase or reduce stigma, depending on whether the story emphasizes recovery or reinforces fear-based stereotypes. In line with this, the current study found that exposure to negative news coverage—linking depression to a violent incident—led to significantly elevated personal stigma scores, while recovery-oriented content was associated with more favourable attitudes. These findings are further supported by von Heydendorff et al. [ 51 ], who analysed German media coverage of the Germanwings plane crash. They found that many reports overemphasized the co-pilot’s depression as a causal factor, contributing to public misperceptions of people with mental disorders as dangerous or unpredictable. The elevated SToP-MD-PS scores in the negative condition of the present study reflect how such framing can trigger measurable increases in stigma. Moreover, the current results resonate with Biblarz et al. [ 70 ], who demonstrated that media representations of suicide and mental health can influence not only emotional responses but also cognitive evaluations of mental illness. Taken together, these studies support the conclusion that the SToP-MD scale, particularly the personal stigma subscale, is sensitive enough to detect changes arising from brief and ecologically valid media exposure. Interestingly, the perceived stigma subscale (SToP-MD-AP) did not show significant differences between conditions, suggesting that individual perceptions of societal attitudes may be more resistant to immediate change or less influenced by isolated media input. This highlights the differential responsiveness of the two subscales and supports the use of the SToP-MD as a multidimensional tool. Overall, the findings underline the importance of the SToP-MD as a change-sensitive instrument, capable of capturing context-dependent fluctuations in stigmatizing attitudes. This makes it a promising tool for evaluating stigma-reduction interventions or experimental manipulations, particularly those involving media stimuli. General discussion The present series of studies aimed to develop and validate the Stigma Towards People with Mental Disorders (SToP-MD) scale, a multidimensional instrument designed to assess stigmatizing attitudes towards individuals with mental health conditions. Across three studies, we established the scale’s psychometric soundness, sensitivity to media-based attitude shifts, and factorial structure through exploratory and confirmatory factor analyses. Together, these findings provide strong evidence that the SToP-MD scale is a reliable, valid, and dynamic tool suitable for both cross-sectional and intervention-based research on stigma. Study 1 laid the groundwork for the SToP-MD by constructing the scale and examining its psychometric properties in a diverse sample. The exploratory factor analysis revealed a two-component structure comprising the subscales Prejudiced Stigmatization (SToP-MD-PS) and Assumption of Problems (SToP-MD-AP). The SToP-MD-PS subscale demonstrated good internal consistency and strong convergent validity, particularly in its associations with established stigma measures such as the Depression Stigma Scale (DSS) and Social Distance Items (SDI). Furthermore, personality traits such as agreeableness and openness to experience were negatively associated with stigma scores, in line with previous research. Notably, neuroticism showed no significant relationship, suggesting it may play a greater role in self-stigma rather than public stigma. Divergent validity was partially supported: while no strong correlations were found with social desirability or most attitudes toward suicide, a surprising negative association emerged between mental health stigma and stigma toward physically disabled persons. This may indicate that the stigmatization of mental illness and physical disability are distinct constructs, rather than reflections of a general prejudice tendency. Study 2 demonstrated the SToP-MD scale’s sensitivity to short-term changes in attitudes following media exposure. In an experimental design, participants who viewed a negatively framed news segment about depression reported significantly higher SToP-MD-PS scores than those who watched a positively framed video. This finding is consistent with prior literature emphasizing the media’s powerful role in shaping mental health stigma. The ability of the SToP-MD-PS subscale to detect these subtle changes further strengthens its utility as a dynamic outcome measure in stigma-related intervention studies. In contrast, the SToP-MD-AP subscale did not respond to the manipulation, suggesting that beliefs about the long-term implications of mental illness may be more resistant to situational influences. Study 3 provided a confirmatory test of the two-factor structure of the SToP-MD. Using confirmatory factor analysis in an independent sample, the initial model showed a reasonable but improvable fit. After theoretically guided modifications—specifically, freeing the residual correlations of semantically or thematically linked items—the model fit improved substantially and met established thresholds for a good fit. This replication in a separate sample provides strong evidence for the structural validity and stability of the SToP-MD. Across all three studies, several consistent patterns emerged. First, the personal stigma dimension (SToP-MD-PS) showed higher reliability, clearer validity, and greater sensitivity to situational factors than the assumption-based subscale (SToP-MD-AP). This suggests that explicit prejudices may be more coherent and malleable than more general assumptions about people with mental disorders. Second, gender, age, and education emerged as key demographic correlates of stigma. Women and individuals with higher education levels reported significantly lower stigma, consistent with prior research. These findings highlight the need for targeted stigma-reduction strategies in specific subgroups. Overall, the SToP-MD scale fills a critical gap in the literature by providing a psychometrically robust, multidimensional, and change-sensitive measure of mental health stigma. It demonstrates solid convergent and discriminant validity, performing well in both exploratory and confirmatory analyses. Future research should seek to refine the weaker subscale, test the scale in clinical and cross-cultural populations, and explore its utility in longitudinal and intervention studies. Moreover, understanding why some individuals stigmatize people with mental disorders while others direct stigmatizing attitudes toward physically disabled persons could shed further light on the structure and drivers of social stigma. In conclusion, the SToP-MD is a promising tool for advancing stigma research and informing public health efforts aimed at reducing the societal burden of mental health stigma. Limitations Several limitations have to be considered when interpreting the current results. First, since 69.9% of the sample was female and 100% were Caucasian, future research should investigate the use of the scale in a more diverse population. Second, only the German version of the SToP-MD scale was used in this study. Consequently, the results of this study need to be replicated in versions for other languages. Third, the sample was relatively young, with a mean age of 28.77 years, and 57.1% of the participants were students. Thus, the factorial structure has to be confirmed in older samples and samples that are more representative of the general population. Additionally, the mean income of participants was relatively high, with a concomitantly high educational level. Thus, the psychometric properties of the scale in other samples is highly recommended. Fourth, data for this study were exclusively collected via an online survey. While equivalence of online and paper-pencil has been shown [ 124 – 126 ], it is possible that a paper-pencil version of the SToP-MD scale shows different psychometric properties. Fifth, the scale only assesses stigmatizing attitudes towards people with mental disorders, but neglects differentiation of public and self-stigma [ 2 , 7 , 127 , 128 ]. Sixth, we did not investigate the test-retest-reliability and sensitivity of the SToP-MD scale, so there is no information about the stability of the scores that are assessed with the measurement. Seventh, we used the term “mental disorder” exclusively in the questionnaire. As studies showed, psychosocial and biogenetic explanations and labeling are preferred and associated with lower stigmatization or prejudice [ 129 , 130 ]. Thus, future studies should investigate whether there are differences in answers when the items refer to other terms like “mental illness”, “mental distress”, or “mental crisis” instead of “mental disorders”. Conclusion We conclude that the current study provides preliminary evidence for the utility of the Stigma Towards People with Mental Disorders Scale (SToP-MD). The SToP-MD scale is a brief, economical, self-report measure with good internal consistency and a reasonable number of items to assess stigmatizing attitudes towards people with mental disorders. Reliable instruments with clear psychometric properties for assessing stigmatizing attitudes towards others concerning mental disorders are rare [ 1 ], and the scales that are available neglect relevant aspects of stigmatization. The scale described in the present study could be a helpful tool to assess stigmatizing attitudes towards people with mental disorders in the population, which, for instance, can be an indicator for the usage of anti-stigma campaigns or the provision of further educational information material. However, the construct validity of the subscales warrants further investigation in future studies with more heterogeneous samples. Nevertheless, the SToP-MD scale is based on an appropriate data analysis and shows good validity as well as internal consistency. Considering that it can be used to assess stigma towards people with mental disorders in general, consists of only 13 items – and thus it can be evaluated without additional expenditure of time – it provides a good supplement to already established stigma scales. Abbreviations ATDP Attitudes Toward Disabled Persons scale ATDP-D Attitudes Toward Disabled Persons scale – “discomfort and insecurity in the presence of physically disabled persons” subscale ATDP-R Attitudes Toward Disabled Persons scale – “rejection of social integration” subscale BIDR Balanced Inventory of Desirable Responding BIDR-O Balanced Inventory of Desirable Responding – “other-deception” subscale BIDR-S Balanced Inventory of Desirable Responding – “self-deception” subscale CAMI Community-Attitudes-toward-the-Mentally-Ill Inventory CFA confirmatory factor analysis CFI comparative fit index CCSS Cognitions Concerning Suicide Scale CCSS-I Cognitions Concerning Suicide Scale – “interpersonal gesture” subscale CCSS-R Cognitions Concerning Suicide Scale – “resiliency” subscale CCSS-S Cognitions Concerning Suicide Scale – “right to commit suicide” subscale DDS Devaluation-Discrimination Scale DSS Depression Stigma Scale DSS-PC Depression Stigma Scale – “perceived stigma” subscale DSS-PS Depression Stigma Scale – “personal stigma” subscale KMO Kaiser-Meyer-Olkin measure of sampling adequacy MLMV Maximum Likelihood with Mean and Variance adjustment estimator NEO-FFI Neuroticism, Extraversion, Openness to experience Five Factor Inventory NEO-FFI-A Neuroticism, Extraversion, Openness to experience Five Factor Inventory – “agreeableness” subscale NEO-FFI-N Neuroticism, Extraversion, Openness to experience Five Factor Inventory – “neuroticism” subscale NEO-FFI-O Neuroticism, Extraversion, Openness to experience Five Factor Inventory – “openness to experience” subscale OMI Opinions about Mental Illness Scale PCA Principal component analysis PPMI Prejudice towards People with Mental Illness scale RMSEA Root mean square error of approximation SDI Social Distance Items SRMR Standardized root mean square residual SSMIS Self-Stigma of Mental Illness Scale SToP-MD Stigma Towards Persons with Mental Disorders SToP-AP Stigma Towards Persons with Mental Disorders - “Assumption of Problems” subscale SToP-PS Stigma Towards Persons with Mental Disorders - “Prejudiced Stigmatization” subscale TLI Tucker–Lewis index Declarations Ethics approval and consent to participate Informed consent was obtained from all individual participants included in the study. This article does not contain any studies with animals performed by any of the authors. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the institutional and/or national research committee and the 1964 Helsinki declaration and its later amendments, or comparable ethical standards. The study received ethical approval from the Ethics Committees of the Faculty of Psychology at the Ruhr-Universität Bochum (reference numbers: 257). Consent for publication Not Applicable Availability of data and materials All datasets used and analyzed during the current study will be freely available at https://osf.io/fh7cw Competing Interests All authors declare that they have no conflict of interest. Funding No granting agency funded the study. Authors' contributions JCC conceived and conceptualized the study. JCC managed and analyzed the data and wrote the manuscript. MLW, SEB, TT, and IH supervised the study. TT and IH contributed to the provision of the stimulus materials. IH also assisted with recruitment. Acknowledgements All authors have agreed to authorship. The authors would like to thank Caroline Esch, Linn Freisewinkel, Vanessa Goede, Carolin Korn, Amelie Niemeyer, and Johanna Sophie Schneider for their support in collecting the data. We especially want to thank Amelie Niemeyer for the construction of the online questionnaire. References Brohan E, Slade M, Clement S, Thornicroft G. Experiences of mental illness stigma, prejudice and discrimination: A review of measures. BMC Health Service Res. 2010;10:80. Corrigan PW. Lessons learned from unintended consequences about erasing the stigma of mental illness. World Psychiatry. 2016;15(1):67–73. Manzo JF. On the sociology and social organization of stigma: some ethnomethodological insights. Hum Stud. 2004;27(4):401–16. Link BG, Phelan JC. Conceptualizing stigma. Ann Rev Sociol. 2001;27(1):363–85. Rüsch N, Angermeyer MC, Corrigan PW. Mental illness stigma: Concepts, consequences, and initiatives to reduce stigma. Eur Psychiatry. 2005;20(8):529–39. Estroff SE. Self, identity, and subjective experiences of schizophrenia: In search of the subject. Schizophr Bull. 1989;15(2):189–96. Corrigan PW, Rao D. On the self-stigma of mental illness: stages, discolure, and strategies for change. Can J Psychiatry. 2012;57(8):464–9. Ndetei DM, Mutiso V, Maraj A, Anderson KK, Musyimi C, McKenzie K. Stigmatizing attitudes toward mental illness among primary school children in Kenya. Soc Psychiatry Psychiatr Epidemiol. 2016;51(1):73–80. Lau AS, Guo S, Tsai W, Nguyen DJ, Nguyen HT, Ngo V, Weiss B. Adolescents' stigma attitudes toward internalizing and externalizing disorders: cultural influences and implications for distress manifestations. Clin Psychol Sci. 2016;4(4):704–17. Bartels SM, Galindo C, Angeles G, Barrington C. Assessing associations between stigma and mental health among preexposure prophylaxis users in Guatemala. Stigma Health. 2024;9(4):575–81. Kotera Y, Kotera H, Taylor E, Wilkes J, Colman R, Riswani R. Mental health of Indonesian university students: U.K. comparison and relationship between mental health shame and self-compassion. Stigma Health. 2024;9(3):239–48. Coppens E, Van Audenhove C, Scheerder G, Arensman E, Coffey C, Costa S, Koburger N, Gottlebe K, Gusmão R, O'Connor R, et al. Public attitudes toward depression and help-seeking in four European countries baseline survey prior to the OSPI-Europe intervention. J Affect Disord. 2013;150(2):320–9. Ali A, King M, Strydom A, Hassiotis A. Self-reported stigma and its association with socio-demographic factors and physical disability in people with intellectual disabilities: results from a cross-sectional study in England. Soc Psychiatry Psychiatr Epidemiol. 2016;51(3):465–74. Dumke L, Wilker S, Hecker T, Neuner F. Barriers to accessing mental health care for refugees and asylum seekers in high-income countries: A scoping review of reviews mapping demand and supply-side factors onto a conceptual framework. Clin Psychol Rev. 2024;113:102491. Kearns M, Muldoon OT, Msetfi RM, Surgenor PWG. Understanding help-seeking amongst university students: The role of group identity, stigma, and exposure to suicide and help-seeking. Front Psychol. 2015;6:1462. Pumpa M, Martin G. The impact of attitudes as a mediator between sense of autonomy and help-seeking intentions for self-injury. Child Adolesc Psychiatry Mental Health. 2016;9:27. Clement S, Schauman O, Graham T, Maggioni F, Evans-Lacko S, Bezborodovs N, Morgan C, Rüsch N, Brown JSL, Thornicroft G. What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychol Med. 2015;45(1):11–27. Sirey J, Bruce ML, Alexopoulos GS, Perlick DA, Friedman SJ, Meyers BS. Perceived stigma and patient-rated severity of illness as predictors of antidepressant drug adherence. Psychiatric Serv. 2001;52(12):1615–20. Corrigan PW. How stigma interferes with mental health care. Am Psychol. 2004;59(7):614–25. Wahl OK. Mental health consumers' experience of stigma. Schizophr Bull. 1999;25(3):467–78. Schomerus G, Angermeyer MC, Baumeister SE, Stolzenburg S, Link BG, Phelan JC. An online intervention using information on the mental health-mental illness continuum to reduce stigma. Eur Psychiatry. 2016;32:21–7. Birtel MD, Crisp RJ. Treating prejudice: an exposure- therapy approach to reducing negative reactions toward stigmatized groups. Psychol Sci. 2012;23(11):1379–86. Schachter HM, Girardi A, Ly M, Lacroix D, Lumb AB, van Berkom J, Gill R. Effects of school-based interventions on mental health stigmatization: a systematic review. Child Adolesc Psychiatry Mental Health. 2008;2:18. Cerully JL, Collins RL, Wong E, Seelam R, Yu J. Differential response to contact-based stigma reduction programs: perceived quality and personal experience matter. Psychiatry Res. 2018;259:302–9. Economou M, Kontoangelos K, Peppou LE, Arvaniti A, Samakouri M, Douzenis A, Papadimitriou GN. Medical students' attitudes to mental illnesses and to psychiatry before and after the psychiatric clerkship: training in a specialty and a general hospital. Psychiatry Res. 2017;258:108–15. Livingston JD, Boyd JE. Correlates and consequences of internalized stigma for people living with mental illness: a systematic review and meta-analysis. Soc Sci Med. 2010;71(12):2150–61. Link BG, Yang LH, Phelan JC, Collins PY. Measuring mental illness stigma. Schizophr Bull. 2004;30(3):511–41. Whatley CD. Social attitudes toward discharged mental patients. Soc Probl. 1959;6:313–20. Yap MBH, MacKinnon A, Reavley N, Jorm AF. The measurement properties of stigmatizing attitudes towards mental disorders: results from two community surveys. Int J Methods Psychiatr Res. 2014;23(1):49–61. Phillips DL. Rejection: a possible consequence of seeking help for mental disorders. Am Sociol Rev. 1963;28:963–72. Cumming E, Cumming H. Closed ranks. An experiment in mental health education. Cambridge, Massachusetts: Harvard University Press; 1957. Osgood CE, Suci GJ, Tannenbaum PH. The measurement of meaning. Urbana, IL: University of Illinois Press; 1957. Crisp AH, Gelder MG, Rix S, Meltzer HI, Rowlands OJ. Stigmatisation of people with mental illnesses. Br J Psychiatry. 2000;177(1):4–7. Nunnally JC, Kittross JM. Public attitudes toward mental health professions. Am Psychol. 1958;13:589–94. Nunnally JC. Popular conceptions of mental health: their development and change. New York, NY: Holt, Rinehart, and Winston; 1961. Olmsted DW, Durham K. Stability of mental health attitudes: a semantic differential study. J Health Soc Behav. 1976;17:35–44. Corrigan PW, Markowitz FE, Watson A, Rowan D, Kubiak MA. An attribution model of public discrimination towards persons with mental illness. J Health Soc Behav. 2003;44(2):162–79. Weiner B, Perry RP, Magnusson J. An attributional analysis of reactions to stigmas. J Personal Soc Psychol. 1988;55(5):738–48. Wu T-H, Chang C-C, Chen C-Y, Wang J-D, Lin C-Y. Further psychometric evaluation of the self-stigma scale-short: Measurement invariance across mental illness and gender. PLoS ONE. 2015;10(2):e0117592–0117592. Corrigan PW, Lundin RK. Don’t call me nuts: coping with the stigma of mental illness. Tinley Park, IL: Recovery; 2001. Mak WWS, Cheung RYM. Self-stigma among concealable minorities in Hong Kong: Conceptualization and unified measurement. Am J Orthopsychiatry. 2010;80:263–77. Link BG, Mirotznik J, Cullen FT. The effectiveness of stigma coping orientations: can negative consequences of mental illness labeling be avoided? J Health Soc Behav. 1991;32(3):302–20. Corrigan PW, Watson AC, Barr L. The self-stigma of mental illness: Implications for self-esteem and self-efficacy. J Social Clin Psychol. 2006;25:875–84. Griffiths KM, Christensen H, Jorm AF, Evans K, Groves C. Effect of web-based depression literacy and cognitive-behavioural therapy interventions on stigmatising attitudes to depression. Br J Psychiatry. 2004;185:342–9. Cohen J, Struening EL. Opinions about mental illness in the personnel of two large mental hospitals. J Abnorm Soc Psychol. 1962;64:349–60. Struening EL, Cohen J. Factorial invariance and other psychometric characteristics of five opinions about mental illness factors. Educ Psychol Meas. 1963;23(2):289–98. Taylor SM, Dear MJ. Scaling community attitudes toward the mentally ill. Schizophr Bull. 1981;7(2):225–40. Kenny A, Bizumic B, Griffiths KM. The Prejudice towards People with Mental Illness (PPMI) scale: structure and validity. BMC Psychiatry. 2018;18:293. Chen ESM, Chung W, Hui CLM, Chan SKW, Ho Ming Lee E, Chen EYH. Self-stigma and affiliate stigma in first-episode psychosis patients and their caregivers. Soc Psychiatry Psychiatr Epidemiol. 2016;51(9):1225–31. von dem Knesebeck O, Mnich E, Angermeyer MC, Kofahl C, Makowski A. Changes in depression stigma after the Germanwings crash - Findings from German population surveys. J Affect Disord. 2015;186:261–5. von Heydendorff SC, Meyer-Lindenberg A, Dressing H. Stigmatization of mentally ill patients by media coverage of Germanwings disaster. Int J Soc Psychiatry. 2016;62:749–50. Klett M, Tessmer S. Lockerung der Schweigepflicht zum Zweck der Verhinderung von Straftaten? Psychotherapeutenjournal 2016, 15(4):380–6. Yap MBH, Reavley N, Mackinnon AJ, Jorm AF. Psychiatric labels and other influences on young people's stigmatizing attitudes: findings from an Australian national survey. J Affect Disord. 2013;148(2–3):299–309. Bagley C, King M. Exploration of three stigma scales in 83 users of mental health services: implications for campaigns to reduce stigma. J Mental Health. 2005;14(4):343–55. Wang X, Huang X, Jackson T, Chen R. Components of implicit stigma against mental illness among Chinese students. PLoS ONE. 2012;7(9):e46016–46016. Leiner DJ. SoSci Survey (Version 2.4.00-i) [Computer Software]. In.; 2014. Sibley CG, Duckitt J. Personality and prejudice: a meta-analysis and theoretical review. Personality Social Psychol Rev. 2008;12(3):248–79. Hayward P, Bright JA. Stigma and mental illness: A review and critique. J Mental Health. 1997;6(4):345–54. Griffiths KM, Christensen H, Jorm AF. Predictors of depression stigma. BMC Psychiatry. 2008;8:25. Link BG, Cullen FT, Frank J, Wozniak JF. The social rejection of former mental patients: Understanding why labels matter. Am J Sociol. 1987;92(6):1461–500. Angermeyer MC, Matschinger H. Social distance towards the mentally ill: Results of representative surveys in the Federal Republic of Germany. Psychol Med. 1997;27(1):131–41. Costa PT, McCrae RR. Revised NEO Personality inventory (NEO PI-R) and NEO five-factor inventory, Profession edn. FIorida: Psychological Assessment Resources;: Odessa; 1992. Borkenau P, Ostendorf F. NEO-Fünf-Faktoren Inventar (NEO-FFI) nach Costa und McCrae. Handanweisung. Göttingen: Hogrefe; 1993. Körner A, Drapeau M, Albani C, Geyer M, Schmutzer G, Brähler E. Deutsche Normierung des NEO-Fünf-Faktoren-Inventars (NEO-FFI). Z für Medizinische Psychologie. 2008;17:133–44. Körner A, Geyer M, Brähler E. Das NEO-Fünf-Faktoren Inventar (NEO-FFI). Diagnostica. 2002;48(1):19–27. Yuker HE, Block JR, Younng JH. The measurement of attitudes toward disabled persons. New York: Human Resources Center;: Albertson; 1970. Seifert KH, Bergmann C. Entwicklung eines Fragebogens zur Messung der Einstellungen gegenüber Körperbehinderten. Heilpädagogische Forschung. 1983;10(3):290–320. Seifert KH, Bergmann C. The EKB-Scale - An inventory to measure the attitudes toward physically disabled persons. Int J Rehabil Res. 1983;6(2):186–7. Cwik JC, Till B, Bieda A, Blackwell SE, Walter C, Teismann T. Measuring attitudes towards suicide: Preliminary evaluation of an attitude towards suicide scale. Compr Psychiatr. 2017;72:56–65. Biblarz A, Brown RM, Biblarz DN, Pilgrim MP, Baldree BF. Media influence on attitudes toward suicide. Suicide Life-Threatening Behav. 1991;21:374–84. Paulhus DL. The Balanced Inventory of Desirable Responding. Toronto/Buffalo: Multi-Health Systems; 1998. Musch J, Brockhaus R, Bröder A. Ein Inventar zur Erfassung von zwei Faktoren sozialer Erwünschtheit. Diagnostica. 2002;48(3):121–9. Kaiser HF. A second generation little jiffy. Psychometrika. 1970;35(4):401–15. Bartlett MS. Tests of significance in factor analysis. Br J Psychol. 1950;3(2):77–85. McDonald RP. Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.; 1999. McDonald RP. Generalizability in factorable domains: Domain validity and generalizability. Educ Psychol Meas. 1978;38(1):75–9. McDonald RP. The theoretical foundations of principal factor analysis, canonical factor, and alpha factor analysis. Br J Math Stat Psychol. 1970;23(1):1–21. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Jillsdale, NJ: Lawrence Earlbaum; 1988. IBM Corp. IBM SPSS Statistics for Mac. In. Edited by 30.0 V. IBM Corp; 2024. van Sonderen E, Sanderman R, Coyne JC. Ineffectiveness of reverse wording of questionnaire items: let's learn from cows in the rain. PLoS ONE. 2013;8(7):e68967. Guagdagnoli E, Velicer WF. Relation of sample size to the stability of component structure. Psychol Bull. 1988;103:265–75. Bors DA, Vigneau F, Lalande F. Measuring the need for cognition: item polarity, dimensionality, and the relation with ability. Pers Indiv Differ. 2006;40(4):819–28. Hartshorne TS. Psychometric properties and confirmatory factor analysis of the UCLA loneliness scale. J Pers Assess. 1993;61(1):182–95. Corrigan PW, Edwards AB, Qreen A, Thwart SL, Perm DL. Prejudice, social distance, and familiarity with mental illness. Schizophr Bull. 2001;27(2):219–25. Dietrich S, Beck M, Bujantugs B, Kenzine D, Matschinger H, Angermeyer MC. The relationship between public causal beliefs and social distance toward mentally ill people. Aust N Z J Psychiatry. 2004;38(5):348–54. Smith AL, Cashwell CS. Social distance and mental illness: Attitudes among mental health and non-mental health professionals and trainees. Prof Counselor: Res Pract. 2011;1(1):13–20. Kelly CM, Jorm AF. Stigma and mood disorders. Curr Opin Psychiatry. 2007;20(1):13–6. Angermeyer MC, Holzinger A, Matschinger H. Mental health literacy and attitude towards people with mental illness: a trend analysis based on population surveys in the eastern part of Germany. Eur Psychiatry. 2009;24(4):225–32. Reavley NJ, Jorm AF. Stigmatising attitudes towards people with mental disorders: Changes in Australia over 8 years. Psychiatry Res. 2012;197(3):302–6. Matschinger H, Angermeyer MC, Link BG. Variationen der Antwortstrukturen in Abhängigkeit vom Grad persönlicher Betroffenheit. Eine Methodenstudie am Beispiel der Discriminatioin-Devaluation-Scale. Psychother Psychosom Med Psychol. 1991;41:278–83. Stadler SM. Einstellungen und Soziale Distanz gegenüber psychisch Kranken. Positive Wirkung sozialer Kontakte im Umfeld einer gemeindepsychiatrischen Tagesstätte im Vergleich zu einer Kontrollregion. Z für Psychiatrie Psychologie und Psychother. 2010;58:265–73. Calear AL, Griffiths KM, Christensen H. Personal and perceived depression stigma in Australian adolescents: magnitude and predictors. J Affect Disord. 2011;129(1–3):104–8. Ekehammar B, Akrami N. Personality and prejudice: from Big Five personality factors to facets. J Pers. 2007;75(5):899–925. Ekehammar B, Akrami N. The relation between personality and prejudice: a variable- and a person-centred approach. Eur J Pers. 2003;17(6):449–64. Graziano WG, Bruce J, Sheese BE, Tobin RM. Attraction, personality, and prejudice: liking none of the people most of the time. J Personal Soc Psychol. 2007;93(3):565–82. Canu WH, Newman ML, Morrow TL, Pope DLW. Social appraisal of adult ADHD: stigma and influences of the beholder's Big Five personality traits. J Atten Disord. 2008;11(6):700–10. McCrae RR, Costa PT Jr, Martin TA, Oryol VE, Senin IG, O'Cleirigh C. Personality correlates of HIV stigmatization in Russia and the United States. J Res Pers. 2007;41(1):190–6. Borecki L, Gozdzik-Zelazny A, Pokorski M. Personality and perception of stigma in psychiatric patients with depressive disorders. Eur J Med Researc. 2010;15:10–6. Major B, Quinton WJ, McCoy SK. Antecedents and consequences of attributions to discrimination: theoretical and empirical advances. In., edn. Edited by Zanna MP. San Diego, CA: Academic Press; 2002: 251–330. Margetić BA, Jakovljević M, Ivanec D, Margetić B, Tošić G. Relations of internalized stigma with temperament and character in patients with schizophrenia. Compr Psychiatr. 2010;51:603–6. Corrigan PW. Mental health stigma as social attribution: implications for research methods and attitude change. Clin Psychol Sci Pract. 2000;7:48–67. Corrigan PW. The impact of stigma on severe mental illness. Cogn Behav Pract. 1998;5(2):201–22. Socoll D, Holtgraves T. Attitudes toward the mentally ill: the effects of label and beliefs. Sociol Q. 1992;33:435–45. Cwik JC, Teismann T. Misclassification of self-directed violence. Clin Psychol Psychother. 2017;24(3):677–86. Chan SKW, Lee KW, Hui CLM, Chang WC, Lee EHM, Chen EYH. Gender effect on public stigma changes towards psychosis in the Hong Kong Chinese population: a comparison between population surveys of 2009 and 2014. Soc Psychiatry Psychiatr Epidemiol 2016. Andersson HW, Bjørngaard JH, Kaspersen SL, Wang CEA, Skre I, Dahl T. The effects of individual factors and school environment on mental health and prejudiced attitudes among Norwegian adolescents. Soc Psychiatry Psychiatr Epidemiol. 2010;45(5):569–77. Gonzalez JM, Alegría M, Prihoda TJ, Copeland LA, Zeber JE. How the relationship of attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education. Soc Psychiatry Psychiatr Epidemiol. 2011;46(1):45–57. Norman RMG, Sorrentino RM, Gawronski B, Szeto ACH, Ye Y, Windell D. Attitudes and physical distance to an individual with schizophrenia: the moderating effect of self-transcendent values. Soc Psychiatry Psychiatr Epidemiol. 2010;45(7):751–8. Girma E, Tesfaye M, Froeschl G, Möller-Leimkühler AM, Müller N, Dehning S. Public stigma against people with mental illness in the Gilgel Gibe Field Research Center (GGFRC) in Southwest Ethiopia. PLoS ONE. 2013;8(12):e82116–82116. Quinn KM, Laidlaw K, Murray LK. Older peoples’ attitudes to mental illness. Clin Psychol Psychother. 2009;16:33–45. Martin JK, Pescosolido BA, Tuch SA. Of fear and loathing: The role of disturbing behavior, labels, and causal attributions in shaping public attitudes toward people with mental illness. J Health Soc Behav. 2000;41(2):208–23. Rosseel Y. lavaan: an R package for structural equation modeling. J Stat Softw. 2012;48(2):1–36. R Core Team. R: A language and environment for statistical computing, Version 4.5.0 edn. Vienna. Austria: R Foundation for Statistical Computing; 2024. Ullman JB. Structural equation modeling. In., 4th ed edn. Edited by Tabachnick BG, Fidell LS. Needham Heights, MA: Allyn & Bacon; 2001: 653–771. Kline RB. Principles and practice of structural equation modeling. 3rd ed. edn. New York: Guilford Press; 2010. Schumacker RE, Lomax RG. A beginner's guide to structural equation modeling. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 2004. MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychol Methods. 1996;1(2):130–49. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55. Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–46. Rouquette A, Falissard B. Sample size requirements for the internal validation of psychiatric scales. Int J Methods Psychiatr Res. 2011;20(4):235–49. Corrigan PW, Powell KJ, Michaels PJ. The effects of news stories on the stigma of mental illness. J Nerv Mental Disease. 2013;201(3):179–82. Faul F, Erdfelder E, Lang A-G, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–91. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149–60. Riva G, Teruzzi T, Anolli L. The use of the internet in psychological research: comparison of online and offline questionnaires. Cyberpsychology Behav. 2003;6(1):73–81. Vallejo MA, Jordán CM, Díaz MI, Comeche MI, Ortega J. Psychological assessment via the internet: a reliability and validity study of online (vs paper-and-pencil) versions of the general health questionnaire-28 (GHQ-28) and the symptoms check-list-90-revised (SCL-90-R). J Med Internet Res. 2007;9(1):e2–2. De Beuckelaer A, Lievens F. Measurement equivalence of paper-and-pencil and internet organizational surveys: a large scale examination in 16 countries. Appl Psychol. 2009;58:336–61. Corrigan PW, Wassell A. Understanding and influencing the stigma of mental illness. J Psychosocial Nurs. 2008;46(1):42–8. Corrigan PW, Watson AC. Understanding the impact of stigma on people with mental illness. World Psychiatry. 2002;1(1):16–20. Jorm AF, Christensen H, Griffiths KM. Public beliefs about causes and risk factors for mental disorders. Changes in Australia over 8 years. Soc Psychiatry Psychiatr Epidemiol. 2005;40(9):764–7. Read J, Haslam N, Sayce L, Davies E. Prejudice and schizophrenia: a review of the 'mental illness is an illness like any other' approach. Acta psychiatrica Scandinavica. 2006;114:303–18. Additional Declarations No competing interests reported. Supplementary Files SToPMDscalefinalEnglishversion.pdf SToPMDscaleoriginalEnglishversion.pdf Cite Share Download PDF Status: Published Journal Publication published 01 May, 2026 Read the published version in BMC Psychology → Version 1 posted Editorial decision: Revision requested 04 Dec, 2025 Reviews received at journal 26 Sep, 2025 Reviews received at journal 19 Sep, 2025 Reviewers agreed at journal 12 Sep, 2025 Reviewers agreed at journal 10 Sep, 2025 Reviewers invited by journal 05 Sep, 2025 Editor assigned by journal 28 Aug, 2025 Editor invited by journal 08 Aug, 2025 Submission checks completed at journal 07 Aug, 2025 First submitted to journal 07 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Woud","email":"","orcid":"","institution":"University of Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Marcella","middleName":"L.","lastName":"Woud","suffix":""},{"id":498382779,"identity":"d8ad830f-1a30-41d8-854f-bc24e4c6ebf5","order_by":2,"name":"Simon E. Blackwell","email":"","orcid":"","institution":"University of Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Simon","middleName":"E.","lastName":"Blackwell","suffix":""},{"id":498382780,"identity":"04f7fabc-0286-425a-b357-4b4248bb55b3","order_by":3,"name":"Tobias Teismann","email":"","orcid":"","institution":"Ruhr-Universität Bochum","correspondingAuthor":false,"prefix":"","firstName":"Tobias","middleName":"","lastName":"Teismann","suffix":""},{"id":498382781,"identity":"123ca4bf-5cec-4eef-8553-cd5182191a62","order_by":4,"name":"Ines Heinz","email":"","orcid":"","institution":"German Alliance against Depression","correspondingAuthor":false,"prefix":"","firstName":"Ines","middleName":"","lastName":"Heinz","suffix":""},{"id":498382782,"identity":"cca468f8-dc5b-4312-9a7b-74bdf01ba087","order_by":5,"name":"Jürgen Margraf","email":"","orcid":"","institution":"Ruhr-Universität Bochum","correspondingAuthor":false,"prefix":"","firstName":"Jürgen","middleName":"","lastName":"Margraf","suffix":""}],"badges":[],"createdAt":"2025-06-13 22:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6890888/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6890888/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40359-026-04627-x","type":"published","date":"2026-05-01T15:58:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89352208,"identity":"0de85231-0554-4777-a7a3-4bf8a29b54e9","added_by":"auto","created_at":"2025-08-19 06:35:12","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":486686,"visible":true,"origin":"","legend":"\u003cp\u003ePath diagram of the two-factor confirmatory factor analysis (CFA) model for the SToP-MD scale using MLMV estimation.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6890888/v1/8e1fa260515daea2b4c70b3e.jpeg"},{"id":108437743,"identity":"34ff3f01-285f-4952-b9b0-dc1d76b78b06","added_by":"auto","created_at":"2026-05-04 16:03:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1314362,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6890888/v1/3c68a4c4-57aa-4487-8eba-f8769933b6a6.pdf"},{"id":89352014,"identity":"8a16c117-2983-4d38-a9cd-1ae2695c5e14","added_by":"auto","created_at":"2025-08-19 06:27:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":45856,"visible":true,"origin":"","legend":"","description":"","filename":"SToPMDscalefinalEnglishversion.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6890888/v1/6829e53e5f413db8f45a914a.pdf"},{"id":89352212,"identity":"e4561c50-0483-4071-bb5b-b24ab0e138b6","added_by":"auto","created_at":"2025-08-19 06:35:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":49333,"visible":true,"origin":"","legend":"","description":"","filename":"SToPMDscaleoriginalEnglishversion.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6890888/v1/831c063d255db70df3373491.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Attitudes towards people with mental disorders: Results of a psychometric evaluation and confirmatory factor analysis of the Stigma Towards People with Mental Disorders (SToP- MD) Scale","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe stigmatization of people with mental disorders has received growing scientific attention. This is illustrated by the increasing number of studies addressing this topic [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As Corrigan [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] illustrated, more than 1,000 papers have been published on stigmatization since 2010.\u003c/p\u003e\u003cp\u003eDespite this growth in research, the term \u0026ldquo;stigma\u0026rdquo; is not well defined [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The lack of a consistent definition led Link and Phelan [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] to underline the necessity of researchers defining the concept of stigmatization underlying their research. For this article, we use the definition of Link and Phelan [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], who stated that stigmatization occurs when an attribute (e.g., depressed) is linked with a stereotype (e.g., \u0026ldquo;depression leads to dangerous behavior\u0026rdquo;). People with that attribute become associated with the negative association (e.g., \u0026ldquo;people with depression are dangerous\u0026rdquo;). Furthermore, people concerned are labeled (e.g., \u0026ldquo;the depressed [man]\u0026rdquo;), which results in a closer negative association [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and, thus, higher stigmatization. As stated by Corrigan and Rao [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]: \u0026ldquo;Stigma is a societal creation, what social psychologists have come to describe as prejudice and discrimination.\u0026rdquo; Stigmatization of people with mental disorders is problematic worldwide, especially in countries in which most people live from low or middle incomes [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere have been several studies investigating factors associated with stigmatization. These studies have found positive relationships between stigmatization and both income and age and a negative association between stigmatization and education. Study results showed that male gender, higher age, lower educational level, and solitariness are significantly related to negative attitudes towards people with depression [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eStigmatization has a significant impact on people suffering from mental disorders, recovery from these disorders, and everyday social life: for instance, studies showed that stigmatization leads people concerned not to search for information about their mental problems or how to get therapeutic help [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Also, stigma impairs recovery, reduces treatment adherence, and contributes to social exclusion, low self-esteem, and health disparities [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, research has also indicated that stigmatization can be influenced [\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In line with this, evidence suggests that both informational and contact-based interventions can reduce stigma [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo date, several scales for the assessment of stigmatization have been developed and three systematic reviews have been published to give an overview about available scales [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. According to Link et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] measures related to stigmatization towards people with mental disorders can be classified as social distance scales [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], semantic differential scales [\u003cspan additionalcitationids=\"CR33 CR34 CR35\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and attributional measures [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Link et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] noted that validity of most scales is questionable, in that these scales are vulnerable to social desirability demands, and the underlying scales and items often ask to compare people with mental disorders with \u0026ldquo;average\u0026rdquo; people are questionable.\u003c/p\u003e\u003cp\u003eA variety of scales have been developed to assess different aspects of stigma related to mental disorders. Most focus on self-stigma [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], personal experiences of stigmatization, or perceived public stigma. Many are disorder-specific (e.g., for depression or schizophrenia), and few assess generalized public attitudes. The widely used Devaluation-Discrimination Scale [DDS; 42] measures perceived devaluation by others but not personal stigma.\u003c/p\u003e\u003cp\u003eSome instruments such as the Self-Stigma of Mental Illness Scale [SSMIS; 43], the Depression Stigma Scale [DSS; 44], the Opinions about mental illness scale (OMI) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and the Community-Attitudes-toward-the-Mentally-Ill Inventory (CAMI) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] assess elements of public stigma but have limitations. For instance, only the Agreement subscale of the SSMIS captures endorsement of stereotypes. The OMI and CAMI cover complex attitude dimensions but are lengthy, outdated, or not aligned with current concepts of stigma. The more recent Prejudice towards People with Mental Illness scale [PPMI; 48] incorporates prejudice theories but focuses on specific dimensions like fear or authoritarianism. Overall, existing tools often lack brevity, conceptual clarity, or general applicability across mental disorders. A more recent addition, the PPMI [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], integrates prejudice theory and covers fear, avoidance, authoritarianism, and unpredictability. Yet, despite these advancements, a short, psychometrically sound instrument that captures generalized, personal stigma toward people with mental disorders is still lacking.\u003c/p\u003e\u003cp\u003eTaken together, most available scales have been built to assess either perceived stigma or self-stigma or stigma related to specific mental disorders (e.g., depression or schizophrenia) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Mainly because of discussions related to the Germanwings crash in March 2015 [\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], the Magdeburg Christmas market attack on 20 December 2024, or other disasters that had been connected to offenders with mental disorders, there are essential aspects of negative attitudes towards people with mental disorders neglected in these scales (e.g., regarding abolition of the non-disclosure obligation to protect others or aspects regarding higher, health system costs). Nevertheless, these aspects should also be measurable when investigating the impact of disasters on stigmatization in public measures or when aiming to measure the effectiveness of anti-stigma campaigns [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsidering these aspects, we decided to develop a scale that measures Stigma Towards Persons with Mental Disorders (SToP-MD) and encompasses relevant aspects of stigma toward individuals concerned. In contrast to other available scales, this scale was built to assess stigmatizing attitudes related to mental disorders in general, without taking into consideration if the respondents themselves suffer from a mental disorder. The constructed scale instead measures stigmatizing attitudes in the population. Three studies were conducted to investigate the psychometric utility of the SToP-MD scale. The first study aimed to test the factorial structure, the construct validity, and the internal consistency of the scale. To analyze the relationships between stigma towards persons measured with the SToP-MD scale and other constructs, we additionally assessed stigma, prejudice, or negative attitudes towards people with mental disorders by using different available scales, social distance, personality traits (neuroticism, open to experience, and agreeableness), attitudes toward physically disabled people, attitudes towards suicide, and socially desirable responding. In the second study, a confirmatory factor analysis (CFA) was used to confirm the factor structure of the SToP-MD scale of study 1. Finally, in the third study, the sensitivity to change of the SToP-MD scale was investigated by randomly assigning participants to three groups, whereas each group was shown either a negative, neutral, or positive film about depression.\u003c/p\u003e"},{"header":"Study 1: Exploratory factor analysis and psychometric properties of the SToP-MD scale","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eMethods\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants and procedure.\u003c/strong\u003e The study was conducted using an online questionnaire developed using SoSci Survey [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e] and made available to participants on \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.soscisurvey.com\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eThe complete sample consisted of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;335 participants. Because of incomplete questionnaires, 69 participants were excluded, so the final sample consisted of \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266 (74.9%) participants, of whom 69.9% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;186) were female, and 30.1% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;80) were male. Age ranged from 18 to 88 years, with a mean of 28.77 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13.69). The employment status of the participants was as follows: 152 (57.1%) students, 55 (20.7%) workers/employees, 19 (7.1%) clerks, 11 (4.1%) trainees, 10 (3.8%) pupils, 8 (3.0%) freelancers, 6 (2.3%) retired participants, and 5 (1.9%) job-seeking participants. In terms of nationality, 262 (98.5%) were German, 1 (0.4%) was Austrian, 1 (0.4%) was Spanish, 1 (0.4%) was Brazilian, and 1 (0.4%) was a US-American citizen. The educational background of participants was as follows: 8 (3.0%) pupil, 1 (0.4%) certificate of secondary education, 5 (1.9%) secondary school level I certificate, 21 (7.9%) apprenticeship, 16 (6.0%) vocational diploma, 154 (57.9%) diploma from German secondary school qualifying for university admission or matriculation, 57 (21.4%) polytechnic degree or university degree, and 4 (1.5%) participants had another educational background. Of all participants, 48 (18.0%) had no own income, 133 (50.0%) had a low income (\u0026lt;\u0026thinsp;1000 \u0026euro;), 62 (23.3%) participants had a middle income (1000 \u0026euro; \u0026minus;\u0026thinsp;3000 \u0026euro;), 18 (6.8) participants had a high income (\u0026lt;\u0026thinsp;3000 \u0026euro;), and 5 (1.9%) participants did not want to give any information about their income.\u003c/p\u003e\n\u003cp\u003eOverall, 56 (21.1%) participants stated that they have or have had contact with a mental health professional, 19 (7.1%) reported suffering from a mental disorder at the time of their participation in the study, 42 (15.8%) reported having suffered from a mental disorder in the past, 73 (27.4%) participants stated that a loved one was suffering from a mental disorder at the time of their participation, and 74 (27.4%) stated that a loved one had suffered from a mental disorder in the past.\u003c/p\u003e\n\u003cp\u003eParticipants were recruited via personal contact and postings on the notice boards of the Ruhr-Universit\u0026auml;t Bochum as well as in relevant groups on social media. Additionally, students were approached and informed about receiving course credit for their participation. Individuals who expressed interest in participating received a link to the online survey. The online survey was completed anonymously, and participants could only proceed to the subsequent questionnaire once all questions had been answered.\u003c/p\u003e\n\u003cp\u003eBefore the assessments, participants were informed about the study's procedure, the voluntary nature of their participation, data storage, and security. Additionally, participants received information about the study's topic, and only individuals aged 18 years or older were allowed to participate. Participants provided their informed consent, and after ensuring confidentiality, they were provided with the link to the survey questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of the Stigma Towards People with Mental Disorders Scale.\u003c/strong\u003e The construction of the SToP-MD scale comprised five steps. In the first step, we screened available stigma scales listed in the reviews by Sibley and Duckitt [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e] as well as Brohan et al. [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e] to identify relevant aspects of stigmatization. In the next step, psychological literature was screened on stigmatization, prejudice, stereotypes, and attitudes. In particular, the stereotype aspects identified by Hayward and Bright [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e] were considered. Then, items were generated based on this information, reports from users of mental health services (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20), our clinical experience, and actual public discussions related to the Germanwings disaster [see 51]. These items were discussed with several clinical experts. Finally, items were reformulated to yield high variance in participants\u0026rsquo; answers.\u003c/p\u003e\n\u003cp\u003eThe first draft of the SToP-MD scale consisted of 22 items measuring stigmatization towards people with mental disorders in general (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), on a six-point Likert scale ranging from 1 = \u0026ldquo;completely disagree\u0026rdquo; to 6 = \u0026ldquo;completely agree\u0026rdquo;. The scale was constructed to measure stigmatization on several aspects of everyday life, for instance, familial aspects (e.g., \u0026ldquo;A family member with a mental disorder often entails many burdens for the family.\u0026rdquo;), occupational aspects (e.g., \u0026ldquo;I would have no hesitation to work with a person with a mental disorder.\u0026rdquo;) or aspects concerning society (e.g., \u0026ldquo;People with mental disorders are burdensome for society.\u0026rdquo;). Additionally, prejudices against people with mental disorders (e.g., \u0026ldquo;Many people with mental disorders are less intelligent.\u0026rdquo;) or against mental disorders by their nature (e.g., \u0026ldquo;Mental disorders are often a sign of a weakness of character.\u0026rdquo;) were considered. The polarity of four items (2, 7, 17, 20) must be reversed so that a higher sum score indicates more negative attitudes towards people with mental disorders.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eOriginal 22 items of the Stigma Towards People with Mental Disorders (SToP-MD) scale in German and the English translation of these items.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItem #\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItem (German original version)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItem (English translation)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeiner Meinung nach w\u0026auml;re es besser, wenn Personen mit psychischen St\u0026ouml;rungen nur in Jobs mit geringer Verantwortung arbeiten d\u0026uuml;rften.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIn my opinion it would be better if people with mental disorders could only work in jobs with less responsibility.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen sind beruflich genauso leistungsf\u0026auml;hig wie Personen ohne psychische St\u0026ouml;rungen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are as efficient professionally as people without mental disorders.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEin Familienmitglied mit einer psychischen St\u0026ouml;rung bringt oftmals viele Belastungen f\u0026uuml;r die Familie mit sich.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA family member with a mental disorder often poses a great burden to the family.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen belasten die Gesellschaft.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are burdensome for society.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWenn ein Mitglied meiner Familie an einer psychischen St\u0026ouml;rung leiden w\u0026uuml;rde, w\u0026auml;re mir das unangenehm.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIf a member of my family were to suffer from a mental disorder, this would be unpleasant for me.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen werden h\u0026auml;ufiger straff\u0026auml;llig.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are more delinquent.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIch h\u0026auml;tte keine Bedenken, mit einer Person mit einer psychischen St\u0026ouml;rung zusammenzuarbeiten.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eI would have no hesitation to work with a person with a mental disorder.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMan sollte zum Schutz anderer die Schweigepflicht von PsychotherapeutInnen und PsychiaterInnen \u0026uuml;berdenken.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOne should protect others by reconsidering the non-disclosure obligation of psychotherapists and psychiatrists.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen verursachen h\u0026auml;ufig unverh\u0026auml;ltnism\u0026auml;\u0026szlig;ig hohe Kosten f\u0026uuml;r das Gesundheitssystem.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders often cause disproportionately high costs for the health system.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eManchmal denke ich, dass eine psychische St\u0026ouml;rung nur eine vorgeschobene Entschuldigung ist.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSometimes I think that a mental disorder is only an excuse for something else.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEs ist am besten, Personen mit psychischen St\u0026ouml;rungen einfach aus dem Weg zu gehen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIt is best just to get out of the way of people with mental disorders.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen sind oft unberechenbar.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are often unpredictable.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePsychische St\u0026ouml;rungen sind h\u0026auml;ufig auch ein Zeichen von Charakterschw\u0026auml;che.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMental disorders are often a sign of a weakness of character.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen haben eher Probleme, soziale Regeln zu befolgen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders have more problems following social rules.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eViele Personen mit psychischen St\u0026ouml;rungen sind weniger intelligent.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMany people with mental disorders are less intelligent.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOftmals sind Personen mit psychischen St\u0026ouml;rungen selbst schuld an ihren Problemen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are often to blame for their problems.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIch denke nicht, dass Personen mit psychischen St\u0026ouml;rungen ihre Arbeitskollegen belasten.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eI do not think that people with mental disorders burden their work colleagues.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWer einmal unter einer psychischen St\u0026ouml;rung leidet, wird wahrscheinlich immer Probleme damit haben.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSomeone who has once suffered from a mental disorder, is likely to always have problems with it.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAufgrund der h\u0026auml;ufigeren Krankheitstage sollte in Betracht gezogen werden, dass Personen mit psychischen St\u0026ouml;rungen h\u0026ouml;here Krankenkassenbeitr\u0026auml;ge zahlen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDue to the frequent sick days, the possibility that people with mental disorders pay higher health insurance contributions should be considered.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen sind eher keine Gefahr f\u0026uuml;r andere.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders are most likely no threat to others.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eW\u0026uuml;rde ich selber eine psychische St\u0026ouml;rung entwickeln, w\u0026uuml;rde ich das vermutlich vor anderen verbergen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIf I were to develop a mental disorder, I would probably conceal it from others.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePersonen mit psychischen St\u0026ouml;rungen k\u0026ouml;nnen einem Angst machen.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeople with mental disorders can cause fear in others.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe original English version and the final version of the SToP-MD scale can be found in the supplementary materials.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eAll questionnaires used to assess the psychometric quality of the SToP-MD scale had already been developed before the implementation of this study. The sources for these questionnaires are indicated alongside each questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepression Stigma Scale (DSS).\u003c/strong\u003e The DSS [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] assesses stigmatizing attitudes towards people with depression and consists of 18 items that are answered on a five-point Likert scale, ranging from 1 = \u0026ldquo;strongly disagree\u0026rdquo; to 5 = \u0026ldquo;strongly agree\u0026rdquo; [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. The DSS comprises two subscales measuring personal stigma (DSS-PS) and perceived stigma (DSS-PC), each with 9 items. The stigma score is calculated by summing up all item scores, with a potential maximum score of 90. Higher scale scores indicate a higher manifestation of stigmatization towards persons with depression. The internal consistency of the total scale is \u0026alpha;\u0026thinsp;=\u0026thinsp;0.78, whereas the DSS-PS subscale has an internal consistency of \u0026alpha;\u0026thinsp;=\u0026thinsp;0.76\u0026ndash;0.77, and the DSS-PC subscale of \u0026alpha;\u0026thinsp;=\u0026thinsp;0.82 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e]. We expected significantly positive associations between DSS and SToP-MD, and thus this questionnaire was used for establishing convergent validity of the SToP-MD scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocial Distance Items (SDI).\u003c/strong\u003e The SDI was used by Link et al. [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e] to measure social distance after reading case vignettes describing a person with a mental disorder or physical problems and divergent levels of behavior. The SDI has excellent internal consistency \u0026alpha;\u0026thinsp;=\u0026thinsp;0.92. Compared to the original version of the scale that uses a four-point Likert scale format, we used a five-point Likert scale from 1 = \u0026ldquo;definitely willing\u0026rdquo; to 5 = \u0026ldquo;definitely unwilling\u0026rdquo; referring to [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e]. By summing scores up, one receives a score for social distance whereby higher scores represent higher social distance from people with mental disorder. The SDI was also used for establishing convergent validity of the SToP-MD scale. Thus, we expected significantly positive associations between both scales.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNEO Five Factor Inventory (NEO-FFI).\u003c/strong\u003e The NEO-FFI [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e] is a self-rating scale, which assesses the factors neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness with each 12 items on a five-point Likert scale from \u0026ldquo;strongly disagree\u0026rdquo; to \u0026ldquo;strongly agree\u0026rdquo;. In the present study only the three subscales for neuroticism (NEO-FFI-N), openness to experience (NEO-FFI-O), and agreeableness (NEO-FFI-A) of the German version [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e] were used. Lower scores in NEO-FFI-N are associated with emotional stability, whereas higher scores are associated with emotional instability. Lower scores in NEO-FFI-O are associated with being more conservative and careful, whereas higher scores are associated with curiosity. Finally, lower scores in NEO-FFI-A are associated with competition orientation and antagonism, whereas higher scores are associated with being more altruistic. The internal constancy of this German three scales lies between \u0026alpha;\u0026thinsp;=\u0026thinsp;0.63 (openness to experience) and \u0026alpha;\u0026thinsp;=\u0026thinsp;0.82 (neuroticism), with a test-retest-reliability between r\u003csub\u003ett\u003c/sub\u003e = 0.67 (openness to experience) and \u0026alpha;\u0026thinsp;=\u0026thinsp;0.82 (neuroticism) [\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e]. Additionally, factor analyses and correlation analyses with scales measuring similar and different constructs confirm the validity of the questionnaire [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e]. We expected that openness to experience and agreeableness would reveal significantly positive associations with the SToP-MD scale, whereas we hypnotized a significantly negative association between SToP-MD and neuroticism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAttitudes Toward Disabled Persons scale (ATDP).\u003c/strong\u003e The ATDP scale [\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e] measures negative attitudes towards people who are physically disabled. In our study we used the German version of the scale (Einstellung gegen\u0026uuml;ber K\u0026ouml;rperbehinderten), which is similar to the [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]. ATDP measures attitudes towards people who are physically disabled on four subscales, with an internal consistency (Cronbach\u0026rsquo;s \u0026alpha;) between \u0026alpha;\u0026thinsp;=\u0026thinsp;0.88 and \u0026alpha;\u0026thinsp;=\u0026thinsp;0.93 as well as adequate factorial structure and validity [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e]. For the present study subscales for \u0026ldquo;discomfort and insecurity in the presence of physically disabled persons\u0026rdquo; (ATDP-D; 15 items) and \u0026ldquo;rejection of social integration\u0026rdquo; (ATDP-R; 6 items) were used. Whereas Seifert and Bergmann [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e] report good internal consistency for the first subscale (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.81\u0026ndash;0.90), the internal consistency for the latter is questionable (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.56\u0026ndash;0.77). Items of the ATDP are rated on a six-point Likert scale from 1 = \u0026ldquo;completely disagree\u0026rdquo; to 6 = \u0026ldquo;completely agree\u0026rdquo;. Most of the items became reoriented (items: 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 14, 16, 18, 19), thus higher sum scores indicate higher adverse attitudes towards people physically disabled persons. We expected no significant associations between the ATDP and the SToP-MD scale, on the basis that attitudes toward physically disabled people may be based on a different psychological construct to attitudes towards people with mental disorders. Thus, this questionnaire was used to investigate divergent validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognitions Concerning Suicide Scale (CCSS).\u003c/strong\u003e The German version of the CCSS [\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e] is a 17-item self-report measure to assess attitudes towards suicide [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]. All items are answered on a six-point Likert scale ranging from \u0026ldquo;0\u0026thinsp;=\u0026thinsp;I disagree\u0026rdquo; to \u0026ldquo;5\u0026thinsp;=\u0026thinsp;I agree\u0026rdquo;. To receive a consistent scoring of the questionnaire, scores of 8 items are reversed (items: 4, 5, 9, 10, 11, 12, 14, 17), such that higher scores reflect a positive perception of suicide. The CCSS consists of three subscales measuring the \u0026ldquo;right to commit suicide\u0026rdquo; (CCSS-S: 8 items; e.g., \u0026ldquo;Everyone has the right to commit suicide\u0026rdquo;, \u0026ldquo;When life consists of intolerable pain, suicide is an acceptable alternative\u0026rdquo;), suicide as an \u0026ldquo;interpersonal gesture\u0026rdquo; (CCSS-I: 5 items, e.g., \u0026ldquo;I sometimes think suicide would be a good way to pay back people who have hurt me deeply\u0026rdquo;; \u0026ldquo;Taking my own life would be a good way to make sure I would always be remembered\u0026rdquo;), and a third factor measuring \u0026ldquo;resiliency\u0026rdquo; (CCSS-R: 4 items; \u0026ldquo;Even if I got tired of living, I would not seriously consider suicide as a way out\u0026rdquo;; \u0026ldquo;Even if I could not be with the person I love, I would not consider suicide\u0026rdquo;). The German version of the CCSS has a sufficient internal consistency for the overall CCSS-scale (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.83) and all three subscales (CCSS-S: \u0026alpha;\u0026thinsp;=\u0026thinsp;0.83; CCSS-I: \u0026alpha;\u0026thinsp;=\u0026thinsp;0.70; CCSS-R: \u0026alpha;\u0026thinsp;=\u0026thinsp;0.67) as well as an acceptable construct and discriminant validity [\u003cspan class=\"CitationRef\"\u003e123\u003c/span\u003e]. The CCSS was also used to investigate divergent validity. We did not expect any significant association between the CCSS and the SToP-MD scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBalanced Inventory of Desirable Responding (BIDR).\u003c/strong\u003e The BIDR [\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e] assesses self- and other-deception on two scales by each 20 seven-point Likert scaled items. Both scales are balanced between negatively and positively oriented items. For the present study, we used the German 20-items version of the BIDR [\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e]. All items are anchored from 1 = \u0026ldquo;completely disagree\u0026rdquo; to 7 = \u0026ldquo;completely agree\u0026rdquo;. The German version contains 13 negatively oriented items. Consequently, thirteen items are reverse-scored (items: 2, 4, 5, 7, 9, 10, 11, 12, 14, 15, 17, 18, 20). Summing all items provides a score for social desirability. Both scales of the German version showed acceptable internal consistencies (self-deception: \u0026alpha;\u0026thinsp;=\u0026thinsp;0.64; other-deception: \u0026alpha;\u0026thinsp;=\u0026thinsp;0.66), clear factor structure, and good construct validity [\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e]. This questionnaire was used to control for the effects of social desirability on participants\u0026rsquo; answers. As social desirability represents a general response tendency rather than a specific attitudinal domain, low or non-significant associations with the SToP-MD scale were anticipated, which would support the scale\u0026rsquo;s divergent validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses.\u003c/strong\u003e In a first step, we conducted an item analysis to investigate which items of the initial version of the SToP-MD scale should be retained. We excluded items with an item difficulty\u0026thinsp;\u0026lt;\u0026thinsp;30.0%.\u003c/p\u003e\n\u003cp\u003eThe factorial structure of the SToP-MD scale, which consists of the remaining items, was tested by a principal component analysis (PCA) with oblimin rotation. Requirements for the PCA were examined using the Kaiser-Meyer-Olkin measure of sampling adequacy (\u003cem\u003eKMO\u003c/em\u003e) [\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e] and Bartlett\u0026rsquo;s test of sphericity [\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e]. The correlation between the SToP-MD scales was analyzed using the Spearman correlation coefficient (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eS\u003c/em\u003e\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003eCalculating McDonald\u0026rsquo;s \u0026omega; [\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e77\u003c/span\u003e] determined the internal consistency of the derived scales. Kurtosis, skewness, and means were calculated, and the normal distribution of the sum scores of all scales used in this study was tested using the Kolmogorov-Smirnov test. Finally, construct validity was investigated using \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eS\u003c/em\u003e\u003c/sub\u003e between the SToP-MD subscales, demographic variables, and criterion measures. For the association between the SToP-MD subscales and nominal demographic variables, eta was calculated.\u003c/p\u003e\n\u003cp\u003eInterpretation of the effect sizes was based on Cohen [\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e], where \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.1\u0026ndash;0.29 represents a small association, \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.3\u0026ndash;0.49 represents a medium association, and \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e \u0026ge; 0.5 represents a large association. Associations between SToP-MD scales and nominal demographic variables were analyzed by using cross-tabulations and \u0026Chi;\u003csup\u003e2\u003c/sup\u003e-tests. Data analysis was conducted using SPSS version 30.0 for Mac [\u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eItem selection.\u003c/strong\u003e In a first step, an item analysis was conducted to investigate the adequacy of all 22 items included in the questionnaire. Therefore, item difficulty was calculated. Subsequently, eight items with inadequate item difficulty (\u0026lt;\u0026thinsp;30.0%) were excluded. Furthermore, three items with negative polarity where also excluded because of the marginal benefits, but considerable disadvantages for psychometric properties and dimensionality of the scale [\u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e]. Thus, the final version of the SToP-MD scale comprises 10 items. The item difficulty of remaining items ranged from 30.0\u0026ndash;72.0% (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eResults of reliability and item analysis of the initial items of the Stigma Towards People with Mental Disorders Scale (SToP-MD) (Study 1; \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItem #\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003erange\u003c/p\u003e\n\u003cp\u003e(min \u0026ndash; max)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eitem difficulty (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eaction\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.94 (1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e38.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.50 (1.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e50.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.60 (1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e72.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.66 (1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.45 (1.60)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.24 (1.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.36 (1.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.84 (1.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.50 (1.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.16 (1.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.61 (1.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.23 (1.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.77 (1.30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.76 (1.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.47 (1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.77 (1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.25 (1.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.17 (1.44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e43.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.85 (1.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.95 (1.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eitem deleted \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.73 (1.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e54.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.37 (1.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u0026ndash;6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e47.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u003csup\u003ea\u003c/sup\u003e = item deleted because of low item difficulty; \u003csup\u003eb\u003c/sup\u003e = item deleted because negative item polarity.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eFactor structure.\u003c/strong\u003e The Kaiser-Meyer-Olkin measure (\u003cem\u003eKMO\u003c/em\u003e) of sampling adequacy revealed a good fit of the data (\u003cem\u003eKMO\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.86), and Bartlett\u0026rsquo;s test of sphericity was significant (\u0026chi;\u0026sup2; = (45, \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266)\u0026thinsp;=\u0026thinsp;1116.55, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a strong and appropriate relationship among the items. Based on these results, in a subsequent step a principal component analysis with oblimin rotation was conducted, resulting in a first component \u0026ldquo;Prejudiced Stigmatization\u0026rdquo; (SToP-MD-PS) (eigenvalue: 3.98) explaining 39.78% of the variance and second component \u0026ldquo;Assumption of Problems\u0026rdquo; (SToP-MD-AP) (eigenvalue: 1.07) explaining 10.70% of the variance. Overall, both factors explained 50.48% of the variance. As can be seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, all factor loadings were adequately high (at least 4 factor loadings\u0026thinsp;\u0026gt;\u0026thinsp;0.60 and all 13 factor loadings\u0026thinsp;\u0026gt;\u0026thinsp;0.40) to reliably interpret the components [\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eFactor loadings of finally included items of the Stigma Towards People with Mental Disorders Scale (SToP-MD) after conducting the oblimin rotated Principal Component Analysis (Study 1; \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266) on the \u0026ldquo;prejudice stigmatization\u0026rdquo; subscale (PS) and \u0026ldquo;Assumption of Problems\u0026rdquo; subscale (AP).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItem #\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactor loadings\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.825\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.746\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.497\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.799\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.588\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.655\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.441\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.604\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.675\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD 22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.699\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eScale properties.\u003c/strong\u003e Internal consistency was assessed using McDonald\u0026rsquo;s \u0026omega;. The SToP-MD-PS subscale with 7 items had an \u0026omega; of 0.83, thus the internal consistency of the scale is good, whereas the SToP-MD-AP subscale with 3 items had an \u0026omega; of 0.51, which is a poor internal consistency. The possible sum score of the SToP-MD-PS subscale ranges from 7 to 42. In contrast, the answers of participants in this study ranged from 8 to 42, with a mean of 20.30 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.13) and the possible sum score of the SToP-MD-AP subscale ranges from 3 to 18, whereas answers of participants in this study ranged from 4 to 18, with a mean of 11.50 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.00). The Kolmogorov-Smirnov-test showed that both SToP-MD subscale sum scores in this population were not normally distributed (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A more detailed view of the data of the SToP-MD-PS subscale showed a skewness of 1.08, which indicates an asymmetrical distribution with a long tail to the right.\u003c/p\u003e\n\u003cp\u003eIn contrast, the kurtosis of 1.96 indicates a more peaked distribution than a Gaussian distribution. Contrarily, data of the SToP-MD-AP subscale showed a skewness of -0.20, which means an asymmetrical distribution with a long tail to the left. In contrast, the kurtosis of -0.15 indicates a less peaked distribution with lighter tails than a Gaussian distribution. The inter-item-correlations for items of the SToP-MD-PS subscale ranged from 0.48\u0026ndash;0.62, and for items of the SToP-MD-AP subscale from 0.29\u0026ndash;0.35. Both SToP-MD subscales showed significant association with a medium effect size (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = .432, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The psychometric properties of the SToP-MD subscales and the other measures used in this study are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCharacteristics of data of used measurements.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMin\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMax\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026omega;\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eskewness\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ekurtosis\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eK-S-test\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD-PS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSToP-MD-AP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSDI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS-PS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS-PC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-FFI-N\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-FFI-A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-FFI-O\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e94.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP-D\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e67.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP-R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e79.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR-S\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR-O\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-S\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.067\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-I\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u0026omega;\u0026thinsp;=\u0026thinsp;McDonald\u0026rsquo;s omega; K-S-test\u0026thinsp;=\u0026thinsp;Kolmogorov-Smirnov-test; SToP-MD\u0026thinsp;=\u0026thinsp;Stigma towards people with mental disorders scale; SToP-MD-PS\u0026thinsp;=\u0026thinsp;prejudiced stigmatization subscale; SToP-MD-AP\u0026thinsp;=\u0026thinsp;assumption of problems subscale; ATDP\u0026thinsp;=\u0026thinsp;Attitudes toward physically disabled persons; ATDP-D\u0026thinsp;=\u0026thinsp;discomfort and insecurity in the presence of physically disabled persons subscale; ATDP-R\u0026thinsp;=\u0026thinsp;rejection of social integration subscale; SDI\u0026thinsp;=\u0026thinsp;Social Distance Items; NEO-FFI\u0026thinsp;=\u0026thinsp;NEO five factor inventory; NEO-FFI-N\u0026thinsp;=\u0026thinsp;neuroticism subscale; NEO-FFI-A\u0026thinsp;=\u0026thinsp;agreeableness subscale; NEO-FFI-O\u0026thinsp;=\u0026thinsp;open to experience subscale; DSS\u0026thinsp;=\u0026thinsp;Depression Stigma Scale; DSS-PS\u0026thinsp;=\u0026thinsp;personal subscale; DSS-PC\u0026thinsp;=\u0026thinsp;perceived subscale; BIDR\u0026thinsp;=\u0026thinsp;Balanced Inventory of Desirable Responding; BIDR-S\u0026thinsp;=\u0026thinsp;self-deception subscale; BIDR-O\u0026thinsp;=\u0026thinsp;other-deception subscale; CCSS\u0026thinsp;=\u0026thinsp;Cognitions Concerning Suicide Scale; CCSS-S\u0026thinsp;=\u0026thinsp;right to commit suicide subscale, CCSS-I\u0026thinsp;=\u0026thinsp;interpersonal gesture subscale; CCSS-R\u0026thinsp;=\u0026thinsp;resiliency subscale.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eConstruct Validity.\u003c/strong\u003e Spearman\u0026rsquo;s correlation analyses confirmed convergent and discriminant validity of the SToP-MD scale (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Both subscales showed strong positive correlations with measures of SDI and DSS, particularly DSS-PS. Negative associations were found with openness to experience and agreeableness (NEO-FFI), as expected. Discriminant validity was partially supported: While most associations with CCSS and BIDR were nonsignificant, small correlations were found with CCSS-I and the BIDR total score. Unexpected negative correlations with ATDP were also observed, suggesting potential overlap in construct.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSpearman\u0026rsquo;s correlation coefficients between SToP-MD subscales and external measures (Study 2; \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSToP-MD-PS\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSToP-MD-AP\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSDI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.626\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.456\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.587\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.430\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS-PS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.715\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.539\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDSS-PC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.218\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.050\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-N\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.010\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.082\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-O\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.225\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.135\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.028\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEO-A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.242\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.328\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.382\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.270\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP-D\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.370\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.257\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eATDP-R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.166\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.007\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.145\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.018\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.047\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.447\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.174\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.004\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-S\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.265\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.050\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.414\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-I\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.139\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.024\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.226\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCCSS-R\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.029\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.642\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.060\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.029\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.642\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.141\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.021\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR-S\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.809\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.078\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.205\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBIDR-O\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.705\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.058\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: SToP-MD-PS\u0026thinsp;=\u0026thinsp;prejudiced stigmatization subscale of the Stigma toward People with Mental Disorders scale (SToP-MD); SToP-MD-AP\u0026thinsp;=\u0026thinsp;assumption of problems subscale; SDI\u0026thinsp;=\u0026thinsp;Social Distance Items; DSS\u0026thinsp;=\u0026thinsp;Depression Stigma Scale (total score); DSS-PS\u0026thinsp;=\u0026thinsp;DSS personal stigma; DSS-PC\u0026thinsp;=\u0026thinsp;DSS perceived stigma; NEO-N/O/A\u0026thinsp;=\u0026thinsp;Neuroticism, Openness, and Agreeableness subscales of the NEO Five Factor Inventory; ATDP\u0026thinsp;=\u0026thinsp;Attitudes Toward Disabled Persons (total score); ATDP-D\u0026thinsp;=\u0026thinsp;discomfort and insecurity in presence of physically disabled persons; ATDP-R\u0026thinsp;=\u0026thinsp;rejection of social integration; CCSS\u0026thinsp;=\u0026thinsp;Cognitions Concerning Suicide Scale (total score); CCSS-S/I/R\u0026thinsp;=\u0026thinsp;CCSS subscales (right to commit suicide/interpersonal gesture/resiliency); BIDR\u0026thinsp;=\u0026thinsp;Balanced Inventory of Desirable Responding (total score); BIDR-S/O\u0026thinsp;=\u0026thinsp;BIDR self- and other-deception subscales. \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = Spearman\u0026rsquo;s rho; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;significance level. Correlations with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 are considered statistically significant and are shown in bold.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic variables.\u003c/strong\u003e The results of the \u0026Chi;\u003csup\u003e2\u003c/sup\u003e-tests revealed a significant positive association between the SToP-MD-PS score and participants\u0026rsquo; gender (\u0026eta;\u0026thinsp;=\u0026thinsp;0.417, adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.039, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, there was no significant association between the SToP-MD-AP score and participants\u0026rsquo; gender (\u0026eta;\u0026thinsp;=\u0026thinsp;0.307, adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.010, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.057). Conversely, the SToP-MD-AP score showed a positive significant association with participants\u0026rsquo; age (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.167, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). In contrast, the SToP-MD-PS score was not significantly associated with participants\u0026rsquo; age (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.108, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.079).\u003c/p\u003e\n\u003cp\u003eAdditionally, there were significant associations between the SToP-MD subscales and participants\u0026rsquo; educational background (SToP-MD-PS: \u0026eta;\u0026thinsp;=\u0026thinsp;0.307, adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.375, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011; SToP-MD-AP: \u0026eta;\u0026thinsp;=\u0026thinsp;0.307, adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.276, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043).\u003c/p\u003e\n\u003ch3\u003eDiscussion\u003c/h3\u003e\n\u003cp\u003eThe study investigated the factor structure, reliability, and construct validity of the newly developed Stigma Towards People with Mental Disorders (SToP-MD) scale.\u003c/p\u003e\n\u003cp\u003eFirst, we tested the adequacy of all 22 items initially included in the questionnaire. The item selection led to the elimination of nine items due to inadequate item discrimination and/or difficulty. Thus, the final version of the SToP-MD scale consisted of 13 items. It is striking that almost all items with a negative polarity (i.e., requiring reverse scoring) were eliminated. There is evidence that the polarity of items fundamentally impacts the dimensionality of measures [\u003cspan class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e]. Three of these items with a negative polarity additionally had low item discrimination scores (items 2, 17, 20), whereas item 7 was excluded because of low item difficulty. The polarity of these items could be associated with the item difficulty or item discrimination. Thus, whether the same items with a positive polarity could still reveal these patterns and have to be excluded could still be tested.\u003c/p\u003e\n\u003cp\u003eFurthermore, five more items with positive polarity were excluded because of low item discrimination (items 11, 13, 15, 16, 19). A closer evaluation of these items leads to the conjecture that these items are not adaptable in a stigma scale that is built to assess stigmatization towards persons with mental disorders in general (e.g., item 11: \u0026ldquo;It is best just to get out of the way of people with mental disorders\u0026rdquo; or item 15: \u0026ldquo;Many people with mental disorders are less intelligent\u0026rdquo;). Furthermore, it could be possible that participants do not agree with such statements in general but would agree with them related to specific mental disorders. Thus, it is possible that participants would differentiate between, for instance, a person with major depression or a person with schizophrenia when answering items like \u0026ldquo;Mental disorders are often a sign of a weakness of character\u0026rdquo; or \u0026ldquo;It is best, just to go out of the way of people with mental disorders\u0026rdquo;. However, this assumption remains untested in the current study.\u003c/p\u003e\n\u003cp\u003eA principal component analysis based on the remaining 10 items indicated a two-component scale structure. The number of the remaining items and the extent of factor loadings indicated a reliable interpretation of both subscales. However, the SToP-MD-AP subscale showed poor internal consistency. This is also reflected in the focus of the items, which capture vast aspects of stigmatization. Should this low internal consistency be confirmed in further studies, consideration should be given to omitting this subscale. While the sample size of this study was adequate for the statistical methods used, it remains to be seen whether the factor structure found in the present study will be reproducible in future studies and bigger sample sizes.\u003c/p\u003e\n\u003cp\u003eConcerning the psychometric properties of the scale, the construct validity of the scale was supported by mostly expected associations between the SToP-MD subscales and a set of relevant criterion measures, such as social distance and depression-related stigma. As expected, higher social distance scores were significantly associated with higher SToP-MD scores. Social distance is a concept that has been used in several studies before to measure stigmatizing attitudes towards persons with mental disorders [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e91\u003c/span\u003e]. According to Angermeyer and Matschinger [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e], social distance can be adequately used to assess attitudes towards people with mental disorders. Furthermore, the DSS as a well-used valid and reliable stigma scale related to depression [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e92\u003c/span\u003e] was also significantly associated to the SToP-MD sum score. According to the idea of the SToP-MD, which aims to assess stigmatizing attitudes of respondents towards people with mental disorders, the association with the personal stigma subscale of the DSS was substantially stronger than with the perceived stigma subscale. This pattern of correlations supports the conceptual alignment of the SToP-MD scale with personal attitudes, providing strong evidence of convergent validity, particularly concerning personal stigma.\u003c/p\u003e\n\u003cp\u003eIn terms of personality traits, two of the three NEO-FFI subscales\u0026mdash;openness to experience and agreeableness\u0026mdash;showed significant negative associations with both SToP-MD subscales. These results are consistent with prior findings indicating that lower openness and agreeableness are associated with higher levels of stigmatizing attitudes [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e95\u003c/span\u003e]. For example, Canu et al. [\u003cspan class=\"CitationRef\"\u003e96\u003c/span\u003e] found that agreeableness was positively linked to more favourable appraisals of adults with ADHD, and McCrae et al. [\u003cspan class=\"CitationRef\"\u003e97\u003c/span\u003e] observed similar associations with stigma toward individuals with physical disabilities.\u003c/p\u003e\n\u003cp\u003eContrary to our expectations, neuroticism was not significantly associated with either SToP-MD subscale. This aligns with previous findings suggesting that neuroticism may be unrelated to public stigma [\u003cspan class=\"CitationRef\"\u003e98\u003c/span\u003e], while its role may be more pronounced in self-stigma or internalized negative beliefs [\u003cspan class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e100\u003c/span\u003e]. Taken together, these results further support the convergent validity of the SToP-MD scale by replicating known associations between specific personality traits and stigmatizing attitudes.\u003c/p\u003e\n\u003cp\u003eDiscriminant validity was tested using measures of socially desirable responding, attitudes towards suicide, and attitudes towards physically disabled people. Contrary to our expectations, both SToP-MD subscales were negatively correlated with the ATDP total score and its subscales [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e]. This indicates that participants who endorsed more stigmatizing attitudes towards people with mental disorders reported less discomfort or rejection concerning physically disabled persons. While unexpected, this pattern may suggest that stigmatizing attitudes towards people with mental and physical impairments are not part of a general prejudice factor, but rather reflect distinct constructs. This supports the discriminant validity of the SToP-MD scale. It is also consistent with previous literature showing that stigmatization of mental illness tends to be more pronounced than that of physical illness [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e101\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e103\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eAs expected, there were no significant associations between the SToP-MD-PS and the CCSS total score or its subscales measuring the right to commit suicide (CCSS-S) and resiliency (CCSS-R) [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e104\u003c/span\u003e]. However, a significant positive correlation was found with the CCSS subscale for suicide as an interpersonal gesture (CCSS-I), albeit with a small effect size. The same was true for the SToP-MD-AP, which additionally showed weak associations with the overall CCSS score. One explanation may be that certain items in the CCSS-I (e.g., \u0026ldquo;Taking my own life would be a good way to make sure I would always be remembered\u0026rdquo;) are interpreted by participants as indicators of psychological instability, leading to associations with stigmatizing attitudes. Prior research has shown that even professionals sometimes misclassify suicidal behaviour as a symptom of mental illness [\u003cspan class=\"CitationRef\"\u003e104\u003c/span\u003e]. Nevertheless, since the majority of CCSS dimensions did not correlate with SToP-MD subscales, these findings generally support discriminant validity.\u003c/p\u003e\n\u003cp\u003eFinally, and in line with our expectations, no significant associations were observed between the SToP-MD-PS and the BIDR [\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e]. Only the SToP-MD-AP showed a small negative correlation with the BIDR total score, which may reflect slightly more openness in reporting critical views. Still, the overall weak associations suggest that the SToP-MD scale is not strongly influenced by social desirability, supporting its use in self-report formats.\u003c/p\u003e\n\u003cp\u003eThe analysis of demographic variables revealed several associations with stigmatizing attitudes towards people with mental disorders. Consistent with previous research [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e105\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e109\u003c/span\u003e], female participants scored significantly lower on the SToP-MD-PS subscale compared to male participants, indicating less stigmatizing attitudes among women. In contrast, the SToP-MD-AP subscale did not show a statistically significant difference between genders, although the trend pointed in the same direction.\u003c/p\u003e\n\u003cp\u003eRegarding age, a significant positive correlation was found only for the SToP-MD-AP subscale, suggesting that older participants were more likely to assume people with mental disorders experience persistent difficulties. The SToP-MD-PS subscale, however, did not correlate significantly with age, which is partly consistent with earlier studies showing nuanced or disorder-specific associations with age [\u003cspan class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e110\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eBoth SToP-MD subscales showed significant associations with educational background, supporting the common finding that lower levels of education are linked to stronger stigmatizing attitudes [\u003cspan class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e109\u003c/span\u003e]. Higher education was associated with lower stigma scores, which may reflect increased exposure to psychoeducation or more liberal social values.\u003c/p\u003e\n\u003cp\u003eInterestingly, no significant correlation was found between income and stigma, which deviates from some prior research suggesting that lower income is associated with higher stigmatizing attitudes [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e111\u003c/span\u003e]. However, this result must be interpreted cautiously given that a large proportion of the sample were students, who typically report low income regardless of their socioeconomic status. Thus, income in this sample may not accurately reflect participants' social or educational resources. Altogether, the demographic analyses support previous findings and highlight gender, age, and education as meaningful factors in shaping stigmatizing attitudes, while also underscoring the importance of sample composition in interpreting such effects.\u003c/p\u003e\n\u003cp\u003eUsing the SToP-MD scale, stigma towards people with mental disorders can be validly and reliably assessed. Beyond that, results also indicated interesting associations between stigma towards people with mental disorders and personality traits as well as stigma towards physically disabled people. These results could be seen as an indication that there are divergent constructs underlying stigmatizing behavior. Thus, future studies could investigate in more detail why some people stigmatize people with mental disorders, whereas others stigmatize physically disabled persons.\u003c/p\u003e"},{"header":"Study 2: Confirmatory factor analysis","content":"\u003cp\u003eWhile Study 1 provided initial evidence for the factorial structure of the SToP-MD through exploratory analyses and Study 2 demonstrated its sensitivity to experimental manipulation, a crucial next step in the validation process is to test the proposed factor model in an independent sample. Study 3, therefore, aimed to examine the factor structure of the SToP-MD using CFA. This approach allows for a rigorous evaluation of the hypothesized measurement model and provides insights into the dimensional stability and construct validity of the scale. By validating the factor structure in a separate sample, this study aims to further establish the psychometric robustness of the SToP-MD further.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eMethods\u003c/h2\u003e\n\u003cp\u003eParticipants and procedure\u003c/p\u003e\n\u003cp\u003eThe second study aimed to investigate the factor structure of the SToP-MD scale, as found in Study 1. Therefore, a second study was conducted on SoSciSurvey [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. By posting the study link on social networks and discussion boards. Again, the online survey was completed anonymously, and all participants were informed about the study's procedure, the voluntary nature of their participation, data storage, and security. Then, they provided their informed consent, and after receiving further reminders about anonymity, they were given the link to the survey questionnaire.\u003c/p\u003e\n\u003cp\u003eStatistical analyses\u003c/p\u003e\n\u003cp\u003eWe conducted a Confirmatory Factor Analysis (CFA) using the lavaan package [version 0.6\u0026ndash;19; 112] in R [version 4.5.0; 113], applying the Maximum Likelihood with Mean and Variance adjustment (MLMV) estimator. This robust estimator accounts for non-normality by adjusting both test statistics and standard errors. The model specified two latent variables: SToP-MD-PS and SToP-MD-AP. The use of MLMV allows for more reliable fit indices and parameter estimates under mild deviations from multivariate normality assumptions.\u003c/p\u003e\n\u003cp\u003eTo evaluate model fit, we extracted several commonly used goodness-of-fit indices: the relative chi-square (\u0026chi;\u0026sup2;/\u003cem\u003edf\u003c/em\u003e), the root mean square error of approximation (RMSEA) along with its 90% confidence interval, the comparative fit index (CFI), the Tucker\u0026ndash;Lewis index (TLI), and the standardized root mean square residual (SRMR). Cut-off criteria were based on established recommendations. A \u0026chi;\u0026sup2;/\u003cem\u003edf\u003c/em\u003e ratio\u0026thinsp;\u0026lt;\u0026thinsp;3 was considered indicative of good model fit, with values\u0026thinsp;\u0026lt;\u0026thinsp;5 interpreted as acceptable [\u003cspan class=\"CitationRef\"\u003e114\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e116\u003c/span\u003e]. RMSEA values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated good fit, and values between 0.05 and 0.08 were regarded as reasonable [\u003cspan class=\"CitationRef\"\u003e117\u003c/span\u003e]. For the CFI and TLI, values\u0026thinsp;\u0026gt;\u0026thinsp;0.90 were interpreted as evidence of good fit [\u003cspan class=\"CitationRef\"\u003e118\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e119\u003c/span\u003e]. SRMR values\u0026thinsp;\u0026lt;\u0026thinsp;0.09 were also considered indicative of good model fit [\u003cspan class=\"CitationRef\"\u003e118\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cp\u003eSample characteristics\u003c/p\u003e\n\u003cp\u003eThe complete sample of study 2 consisted \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;448 participants, of which 65.8% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;295) were female and 34.2% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;153) were male. The age of participants ranged from 18 to 78 years, with a mean of 28.76 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.74). Of all 448 participants, 262 (58.5%) were students, 93 (20.8%) workers/employees, 22 (4.9%) freelancers, 20 (4.5%) trainees, 12 (2.7%) clerks, 11 (2.5%) retired participants, 11 (2.5%) job-seeking participants, and 7 (1.6%) pupils and 10 (2.2%) participants had another kind of employment status.\u003c/p\u003e\n\u003cp\u003eConfirmatory factor analysis\u003c/p\u003e\n\u003cp\u003eGiven the sample size of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;448 participants, the minimum of at least 300 participants for conducting a CFA was reached [\u003cspan class=\"CitationRef\"\u003e120\u003c/span\u003e]. The CFA model converged successfully and demonstrated an acceptable overall fit to the data. The scaled chi-square statistic was significant, \u0026chi;\u0026sup2;(34)\u0026thinsp;=\u0026thinsp;74.23, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, indicating some discrepancy between the model and the data; however, chi-square is known to be sensitive to sample size. The robust fit indices provided a more nuanced evaluation: the CFI was 0.918, and the TLI was 0.892. The RMSEA was 0.078, with values below 0.08 typically interpreted as reflecting a reasonable fit. The SRMR was 0.051, indicating a good fit according to conventional thresholds [\u003cspan class=\"CitationRef\"\u003e118\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eAll factor loadings were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and fell within an acceptable range, with standardized estimates ranging from 0.464 to 0.711. These results support the hypothesized two-factor structure of the SToP-MD scale, reflecting the underlying constructs of public stigma (SToP-MD-PS) and anticipated personal stigma (SToP-MD-AP).\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the CFA model. The two latent variables (SToP-MD-PS and SToP-MD-AP) are represented as circles, each with directed arrows pointing to their respective observed indicators. A bidirectional arrow between the latent variables indicates their estimated correlation (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.78), suggesting a substantial association between the two stigma dimensions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eDiscussion\u003c/h3\u003e\n\u003cp\u003eThis two-factor CFA model supports the theoretical distinction between SToP-MD-PS and SToP-MD-AP. The factor loadings indicate that all items contribute meaningfully to their respective latent constructs, confirming the structural validity of the SToP-MD. The use of robust MLMV estimation enhances confidence in the model\u0026rsquo;s reliability, even in the presence of potential non-normality in the item responses. This structure provides empirical support for a two-dimensional conceptualization of stigma, with a substantial correlation between the two factors, suggesting they are related but distinct components of mental health stigma.\u003c/p\u003e"},{"header":"Study 3: Investigation of media on stigma towards people with mental disorders","content":"\u003cp\u003eThe mass media are a major source of public knowledge about mental illness, but they also play a central role in shaping and perpetuating stigma. Prior studies have shown that news reports frequently associate mental disorders with violence, unpredictability, or incompetence, thereby reinforcing negative stereotypes [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e121\u003c/span\u003e]. For example, Corrigan et al. [\u003cspan class=\"CitationRef\"\u003e121\u003c/span\u003e] demonstrated that exposure to recovery-oriented media content can reduce public stigma. At the same time, reports focusing on system failure or individual acts of violence can exacerbate it.\u003c/p\u003e\n\u003cp\u003eThis dynamic was evident in the media response to the 2015 Germanwings plane crash, where the co-pilot\u0026rsquo;s presumed depression was framed as a primary cause of the tragedy. An analysis of German print media found that over 60% of articles implied a direct link between mental illness and the crash, often without adequate psychiatric context or caution [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. Such portrayals not only risk reinforcing damaging misconceptions but may also contribute to increased public support for exclusion or coercion.\u003c/p\u003e\n\u003cp\u003eResearch on the media\u0026rsquo;s influence on suicide stigma yields similar concerns: Biblarz et al. [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e] showed that media messages can shape public attitudes not only toward suicide itself, but also toward individuals perceived to be mentally ill, especially when behavior is portrayed in simplistic, causal terms.\u003c/p\u003e\n\u003cp\u003eAgainst this background, Study 2 was designed primarily to evaluate the sensitivity to change of the SToP-MD scale. Using a brief experimental design, participants were exposed to either stigmatizing or destigmatizing media content about mental illness. By comparing SToP-MD scores before and after this exposure, the study aimed to determine whether the scale is capable of capturing short-term shifts in stigmatizing attitudes\u0026mdash;a critical property for instruments used in intervention research.\u003c/p\u003e\n\u003ch2\u003eMethods\u003c/h2\u003e\n\u003cp\u003eParticipants\u003c/p\u003e\n\u003cp\u003eA total of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;269 individuals consented to participate in the study. However, three subjects (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) discontinued participation after randomization, so data from 266 individuals (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266) were ultimately included in the analysis. No participant failed the video attention check (i.e., answered one or more of the control questions incorrectly), so all participants were included in the final analyses.\u003c/p\u003e\n\u003cp\u003eParticipants were recruited via university mailing lists, social media platforms, and online psychology forums. Participation was voluntary and anonymous. All participants provided informed consent before beginning the study.\u003c/p\u003e\n\u003cp\u003eThe final sample consisted predominantly of students and young adults, with a mean age of \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;29.45 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.87; range, 18\u0026ndash;85) years. The gender distribution was n\u0026thinsp;=\u0026thinsp;180 (67.5%) female and n\u0026thinsp;=\u0026thinsp;86 (32.5%) male. Participants were randomly assigned to one of the three experimental groups (positive: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;92, neutral: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;87, negative: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;87), with approximately equal group sizes.\u003c/p\u003e\n\u003cp\u003eNo significant differences were observed in age, gender, or educational background between the groups, indicating that randomization was successful. The majority of participants reported having no formal training in psychology or psychiatry.\u003c/p\u003e\n\u003cp\u003eDesign and Procedure\u003c/p\u003e\n\u003cp\u003eThe study employed a between-subjects experimental design with three experimental conditions: positive, neutral, and negative media content related to depression. Participants were informed in advance that they would be randomly assigned to one of these groups. Each group was shown a short video differing in its emotional framing of depression: a positive video emphasizing recovery through psychotherapy from the German Alliance against Depression (1:24 min), a neutral educational video on neurotransmitters and depression (1:31 min), or a negatively framed news segment from Tagesschau reporting on the co-pilot's depression in the context of the Germanwings plane crash (1:36 min).\u003c/p\u003e\n\u003cp\u003eFollowing the video presentation, participants were asked to rate their impression of the video by responding to three evaluative statements, each on a 7-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree, 7\u0026thinsp;=\u0026thinsp;strongly agree). These items assessed whether participants had attentively and accurately perceived the content and tone of the video. Only data from participants whose responses indicated consistent and attentive viewing were included in the final analyses.\u003c/p\u003e\n\u003cp\u003eSubsequently, participants were asked to provide an overall rating of the emotional valence of the video on a separate 7-point scale (1\u0026thinsp;=\u0026thinsp;very negative, 7\u0026thinsp;=\u0026thinsp;very positive) to capture the mood induced by the content. Finally, they completed the SToP-MD questionnaire, which assesses stigmatizing attitudes toward individuals with mental disorders, allowing for the evaluation of potential changes in stigma as a function of media exposure. The questions were: 1) \"Please assess how individuals with mental disorders were portrayed in the video.\", 2) \"Please indicate what kind of mood the video evoked in you.\", and 3) \"Please rate the emotional atmosphere of the video.\"\u003c/p\u003e\n\u003cp\u003eFinally, participants were debriefed about the purpose of the study. They were also informed that they could request the deletion of their data afterwards if they disagreed with its use; however, no participant made use of this option.\"\u003c/p\u003e\n\u003cp\u003ePower analysis\u003c/p\u003e\n\u003cp\u003eAn a priori power analysis was conducted using G*Power [122, version 3.1; 123] to determine the required sample size for detecting differences between the three experimental conditions. Based on the study design, a small to medium effect size (\u003cem\u003ef\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19) was assumed, following recommendations from previous research on stigma and media exposure [e.g., 121]. The significance level was set to \u0026alpha;\u0026thinsp;=\u0026thinsp;0.05, the statistical power to 1 \u0026ndash; \u0026beta;\u0026thinsp;=\u0026thinsp;0.80, and the number of groups to three.\u003c/p\u003e\n\u003cp\u003eStatistical Analyses\u003c/p\u003e\n\u003cp\u003eTo evaluate the effectiveness of the experimental manipulation, descriptive statistics (means and standard deviations) were calculated for participants\u0026rsquo; ratings of (1) the portrayal of people with mental disorders, (2) the mood induced by the video, and (3) the emotional atmosphere of the video.\u003c/p\u003e\n\u003cp\u003eTo assess group differences in stigmatizing attitudes as measured by the SToP-MD subscales, non-parametric tests were employed due to violations of normality assumptions. Specifically, a Kruskal\u0026ndash;Wallis \u003cem\u003eH\u003c/em\u003e test was used to examine overall differences across the three experimental groups (positive, neutral, negative). In the case of a significant omnibus result, pairwise Mann\u0026ndash;Whitney U tests were conducted as post-hoc comparisons, with the Bonferroni correction applied to adjust for multiple testing (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.05 / 3\u0026thinsp;=\u0026thinsp;0.016).\u003c/p\u003e\n\u003cp\u003eFor all tests, effect sizes (\u0026eta;\u0026sup2;) were calculated to quantify the magnitude of between-group differences. The threshold for statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (adjusted where necessary).\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using SPSS version 30.0 for Mac [\u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cp\u003eAttention check\u003c/p\u003e\n\u003cp\u003eParticipants' attentiveness to the video content was assessed through three comprehension questions per condition. Overall, no participant gave more than two incorrect answers, indicating a generally high level of attention across all groups.\u003c/p\u003e\n\u003cp\u003eIn the positive condition, all participants correctly identified the video\u0026rsquo;s reference to depression (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;92, 100%) and that the expert shown at the end was female (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;92, 100%). Additionally, 97.8% correctly recognized the video\u0026rsquo;s focus on recovery from illness (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;90).\u003c/p\u003e\n\u003cp\u003eIn the neutral condition, all participants correctly identified the female physician (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;87, 100%). Furthermore, 98.9% correctly answered questions regarding neurotransmitters as neural messengers (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;86) and the mention of depression (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;86).\u003c/p\u003e\n\u003cp\u003eIn the negative condition, the majority correctly recalled that the video covered the crash in the French Alps (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;86, 98.9%) and the search for the black box (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;86, 98.9%). A lower proportion correctly identified the news anchor as female (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;72, 82.8%).\u003c/p\u003e\n\u003cp\u003eGiven these results, all participants were retained for further analysis, as none failed the attention check in a manner that would warrant exclusion based on predefined criteria.\u003c/p\u003e\n\u003cp\u003eManipulation check\u003c/p\u003e\n\u003cp\u003eTo assess whether the video stimuli differed in terms of perceived content and emotional impact, participants were asked to evaluate three aspects after watching their assigned video: (1) the portrayal of people with mental disorders, (2) the mood induced by the video, and (3) the overall emotional atmosphere. As expected, the videos elicited distinctive evaluations across conditions, consistent with the intended manipulation.\u003c/p\u003e\n\u003cp\u003eRegarding the portrayal of people with mental disorders, participants who viewed the positive video rated the depiction most favourably (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.59, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.30), followed by the neutral (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.98, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.86) and negative video (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.00, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00).\u003c/p\u003e\n\u003cp\u003eIn terms of mood induction, participants exposed to the positive video reported the most positive affective response (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.20, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.32), compared to the neutral (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.93, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.01) and negative condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.41, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.91).\u003c/p\u003e\n\u003cp\u003eSimilarly, the emotional atmosphere was rated as most positive in the positive video condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.15, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.24), followed by the neutral video condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.68, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.99) and the negative video condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.93, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.08).\u003c/p\u003e\n\u003cp\u003eThese findings confirm that the videos differed significantly in emotional tone and evaluative framing, thereby validating the experimental manipulation.\u003c/p\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eGroup differences\u003c/h2\u003e\n\u003cp\u003eThe results of the Kruskal\u0026ndash;Wallis H test revealed significant rank differences between groups for the SToP-MD-PS subscale (\u0026Chi;\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;10.971, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004; \u0026eta;\u0026sup2; = 0.034), whereas no significant differences were found for the SToP-MD-AP subscale (\u0026Chi;\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;2.716, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.257; \u0026eta;\u0026sup2; = 0.003).\u003c/p\u003e\n\u003cp\u003ePost hoc Mann\u0026ndash;Whitney U tests, conducted to examine pairwise group differences on the SToP-MD-PS subscale, were adjusted using the Bonferroni correction (\u003cem\u003e\u0026alpha;\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). These analyses revealed a significant difference between participants who viewed the negative video and those who viewed the positive video, with higher stigma scores in the former group (U(92, 87)\u0026thinsp;=\u0026thinsp;2872.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u0026eta;\u0026sup2; = 0.059). However, no significant differences were found between the negative and neutral conditions (\u003cem\u003eU\u003c/em\u003e(87, 87)\u0026thinsp;=\u0026thinsp;3134.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.050; \u0026eta;\u0026sup2; = 0.022), nor between the positive and neutral conditions (U(92, 87)\u0026thinsp;=\u0026thinsp;3526.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.169; \u0026eta;\u0026sup2; = 0.011).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eDiscussion\u003c/h3\u003e\n\u003cp\u003eThis study aimed to examine the sensitivity to change of the SToP-MD scale in response to different types of media content related to depression. The findings indicate that the personal stigma subscale (SToP-MD-PS) is responsive to short-term media exposure: participants who viewed a negatively framed news report displayed significantly higher stigma scores than those who watched a positively framed video. These results suggest that the SToP-MD-PS subscale is capable of detecting subtle, experimentally induced shifts in individual stigma, demonstrating its validity as a dynamic measure of attitude change.\u003c/p\u003e\n\u003cp\u003eThis result aligns with prior evidence that media content plays a central role in shaping public attitudes toward mental illness. Corrigan et al. [\u003cspan class=\"CitationRef\"\u003e121\u003c/span\u003e] showed that different narrative framings in news media can either increase or reduce stigma, depending on whether the story emphasizes recovery or reinforces fear-based stereotypes. In line with this, the current study found that exposure to negative news coverage\u0026mdash;linking depression to a violent incident\u0026mdash;led to significantly elevated personal stigma scores, while recovery-oriented content was associated with more favourable attitudes.\u003c/p\u003e\n\u003cp\u003eThese findings are further supported by von Heydendorff et al. [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e], who analysed German media coverage of the Germanwings plane crash. They found that many reports overemphasized the co-pilot\u0026rsquo;s depression as a causal factor, contributing to public misperceptions of people with mental disorders as dangerous or unpredictable. The elevated SToP-MD-PS scores in the negative condition of the present study reflect how such framing can trigger measurable increases in stigma.\u003c/p\u003e\n\u003cp\u003eMoreover, the current results resonate with Biblarz et al. [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e], who demonstrated that media representations of suicide and mental health can influence not only emotional responses but also cognitive evaluations of mental illness. Taken together, these studies support the conclusion that the SToP-MD scale, particularly the personal stigma subscale, is sensitive enough to detect changes arising from brief and ecologically valid media exposure.\u003c/p\u003e\n\u003cp\u003eInterestingly, the perceived stigma subscale (SToP-MD-AP) did not show significant differences between conditions, suggesting that individual perceptions of societal attitudes may be more resistant to immediate change or less influenced by isolated media input. This highlights the differential responsiveness of the two subscales and supports the use of the SToP-MD as a multidimensional tool.\u003c/p\u003e\n\u003cp\u003eOverall, the findings underline the importance of the SToP-MD as a change-sensitive instrument, capable of capturing context-dependent fluctuations in stigmatizing attitudes. This makes it a promising tool for evaluating stigma-reduction interventions or experimental manipulations, particularly those involving media stimuli.\u003c/p\u003e"},{"header":"General discussion","content":"\u003cp\u003eThe present series of studies aimed to develop and validate the Stigma Towards People with Mental Disorders (SToP-MD) scale, a multidimensional instrument designed to assess stigmatizing attitudes towards individuals with mental health conditions. Across three studies, we established the scale’s psychometric soundness, sensitivity to media-based attitude shifts, and factorial structure through exploratory and confirmatory factor analyses. Together, these findings provide strong evidence that the SToP-MD scale is a reliable, valid, and dynamic tool suitable for both cross-sectional and intervention-based research on stigma.\u003c/p\u003e\n\u003cp\u003eStudy 1 laid the groundwork for the SToP-MD by constructing the scale and examining its psychometric properties in a diverse sample. The exploratory factor analysis revealed a two-component structure comprising the subscales Prejudiced Stigmatization (SToP-MD-PS) and Assumption of Problems (SToP-MD-AP). The SToP-MD-PS subscale demonstrated good internal consistency and strong convergent validity, particularly in its associations with established stigma measures such as the Depression Stigma Scale (DSS) and Social Distance Items (SDI). Furthermore, personality traits such as agreeableness and openness to experience were negatively associated with stigma scores, in line with previous research. Notably, neuroticism showed no significant relationship, suggesting it may play a greater role in self-stigma rather than public stigma. Divergent validity was partially supported: while no strong correlations were found with social desirability or most attitudes toward suicide, a surprising negative association emerged between mental health stigma and stigma toward physically disabled persons. This may indicate that the stigmatization of mental illness and physical disability are distinct constructs, rather than reflections of a general prejudice tendency.\u003c/p\u003e\n\u003cp\u003eStudy 2 demonstrated the SToP-MD scale’s sensitivity to short-term changes in attitudes following media exposure. In an experimental design, participants who viewed a negatively framed news segment about depression reported significantly higher SToP-MD-PS scores than those who watched a positively framed video. This finding is consistent with prior literature emphasizing the media’s powerful role in shaping mental health stigma. The ability of the SToP-MD-PS subscale to detect these subtle changes further strengthens its utility as a dynamic outcome measure in stigma-related intervention studies. In contrast, the SToP-MD-AP subscale did not respond to the manipulation, suggesting that beliefs about the long-term implications of mental illness may be more resistant to situational influences.\u003c/p\u003e\n\u003cp\u003eStudy 3 provided a confirmatory test of the two-factor structure of the SToP-MD. Using confirmatory factor analysis in an independent sample, the initial model showed a reasonable but improvable fit. After theoretically guided modifications—specifically, freeing the residual correlations of semantically or thematically linked items—the model fit improved substantially and met established thresholds for a good fit. This replication in a separate sample provides strong evidence for the structural validity and stability of the SToP-MD.\u003c/p\u003e\n\u003cp\u003eAcross all three studies, several consistent patterns emerged. First, the personal stigma dimension (SToP-MD-PS) showed higher reliability, clearer validity, and greater sensitivity to situational factors than the assumption-based subscale (SToP-MD-AP). This suggests that explicit prejudices may be more coherent and malleable than more general assumptions about people with mental disorders. Second, gender, age, and education emerged as key demographic correlates of stigma. Women and individuals with higher education levels reported significantly lower stigma, consistent with prior research. These findings highlight the need for targeted stigma-reduction strategies in specific subgroups.\u003c/p\u003e\n\u003cp\u003eOverall, the SToP-MD scale fills a critical gap in the literature by providing a psychometrically robust, multidimensional, and change-sensitive measure of mental health stigma. It demonstrates solid convergent and discriminant validity, performing well in both exploratory and confirmatory analyses. Future research should seek to refine the weaker subscale, test the scale in clinical and cross-cultural populations, and explore its utility in longitudinal and intervention studies. Moreover, understanding why some individuals stigmatize people with mental disorders while others direct stigmatizing attitudes toward physically disabled persons could shed further light on the structure and drivers of social stigma.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the SToP-MD is a promising tool for advancing stigma research and informing public health efforts aimed at reducing the societal burden of mental health stigma.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eSeveral limitations have to be considered when interpreting the current results. First, since 69.9% of the sample was female and 100% were Caucasian, future research should investigate the use of the scale in a more diverse population. Second, only the German version of the SToP-MD scale was used in this study. Consequently, the results of this study need to be replicated in versions for other languages. Third, the sample was relatively young, with a mean age of 28.77 years, and 57.1% of the participants were students. Thus, the factorial structure has to be confirmed in older samples and samples that are more representative of the general population.\u003c/p\u003e\u003cp\u003eAdditionally, the mean income of participants was relatively high, with a concomitantly high educational level. Thus, the psychometric properties of the scale in other samples is highly recommended. Fourth, data for this study were exclusively collected via an online survey. While equivalence of online and paper-pencil has been shown [\u003cspan class=\"CitationRef\"\u003e124\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e126\u003c/span\u003e], it is possible that a paper-pencil version of the SToP-MD scale shows different psychometric properties. Fifth, the scale only assesses stigmatizing attitudes towards people with mental disorders, but neglects differentiation of public and self-stigma [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e127\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e128\u003c/span\u003e]. Sixth, we did not investigate the test-retest-reliability and sensitivity of the SToP-MD scale, so there is no information about the stability of the scores that are assessed with the measurement. Seventh, we used the term “mental disorder” exclusively in the questionnaire. As studies showed, psychosocial and biogenetic explanations and labeling are preferred and associated with lower stigmatization or prejudice [\u003cspan class=\"CitationRef\"\u003e129\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e130\u003c/span\u003e]. Thus, future studies should investigate whether there are differences in answers when the items refer to other terms like “mental illness”, “mental distress”, or “mental crisis” instead of “mental disorders”.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe conclude that the current study provides preliminary evidence for the utility of the Stigma Towards People with Mental Disorders Scale (SToP-MD). The SToP-MD scale is a brief, economical, self-report measure with good internal consistency and a reasonable number of items to assess stigmatizing attitudes towards people with mental disorders. Reliable instruments with clear psychometric properties for assessing stigmatizing attitudes towards others concerning mental disorders are rare [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and the scales that are available neglect relevant aspects of stigmatization. The scale described in the present study could be a helpful tool to assess stigmatizing attitudes towards people with mental disorders in the population, which, for instance, can be an indicator for the usage of anti-stigma campaigns or the provision of further educational information material. However, the construct validity of the subscales warrants further investigation in future studies with more heterogeneous samples.\u003c/p\u003e\u003cp\u003eNevertheless, the SToP-MD scale is based on an appropriate data analysis and shows good validity as well as internal consistency. Considering that it can be used to assess stigma towards people with mental disorders in general, consists of only 13 items \u0026ndash; and thus it can be evaluated without additional expenditure of time \u0026ndash; it provides a good supplement to already established stigma scales.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eATDP Attitudes Toward Disabled Persons scale\u003c/p\u003e\n\u003cp\u003eATDP-D Attitudes Toward Disabled Persons scale \u0026ndash; \u0026ldquo;discomfort and insecurity in the presence of physically disabled persons\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eATDP-R Attitudes Toward Disabled Persons scale \u0026ndash; \u0026ldquo;rejection of social integration\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eBIDR Balanced Inventory of Desirable Responding\u003c/p\u003e\n\u003cp\u003eBIDR-O Balanced Inventory of Desirable Responding \u0026ndash; \u0026ldquo;other-deception\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eBIDR-S Balanced Inventory of Desirable Responding \u0026ndash; \u0026ldquo;self-deception\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eCAMI Community-Attitudes-toward-the-Mentally-Ill Inventory\u003c/p\u003e\n\u003cp\u003eCFA confirmatory factor analysis\u003c/p\u003e\n\u003cp\u003eCFI comparative fit index\u003c/p\u003e\n\u003cp\u003eCCSS Cognitions Concerning Suicide Scale\u003c/p\u003e\n\u003cp\u003eCCSS-I Cognitions Concerning Suicide Scale \u0026ndash; \u0026ldquo;interpersonal gesture\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eCCSS-R Cognitions Concerning Suicide Scale \u0026ndash; \u0026ldquo;resiliency\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eCCSS-S Cognitions Concerning Suicide Scale \u0026ndash; \u0026ldquo;right to commit suicide\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eDDS Devaluation-Discrimination Scale\u003c/p\u003e\n\u003cp\u003eDSS Depression Stigma Scale\u003c/p\u003e\n\u003cp\u003eDSS-PC Depression Stigma Scale \u0026ndash; \u0026ldquo;perceived stigma\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eDSS-PS Depression Stigma Scale \u0026ndash; \u0026ldquo;personal stigma\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eKMO Kaiser-Meyer-Olkin measure of sampling adequacy\u003c/p\u003e\n\u003cp\u003eMLMV Maximum Likelihood with Mean and Variance adjustment estimator\u003c/p\u003e\n\u003cp\u003eNEO-FFI Neuroticism, Extraversion, Openness to experience Five Factor Inventory\u003c/p\u003e\n\u003cp\u003eNEO-FFI-A Neuroticism, Extraversion, Openness to experience Five Factor Inventory \u0026ndash; \u0026ldquo;agreeableness\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eNEO-FFI-N Neuroticism, Extraversion, Openness to experience Five Factor Inventory \u0026ndash; \u0026ldquo;neuroticism\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eNEO-FFI-O Neuroticism, Extraversion, Openness to experience Five Factor Inventory \u0026ndash; \u0026ldquo;openness to experience\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eOMI Opinions about Mental Illness Scale\u003c/p\u003e\n\u003cp\u003ePCA Principal component analysis\u003c/p\u003e\n\u003cp\u003ePPMI Prejudice towards People with Mental Illness scale\u003c/p\u003e\n\u003cp\u003eRMSEA Root mean square error of approximation\u003c/p\u003e\n\u003cp\u003eSDI Social Distance Items\u003c/p\u003e\n\u003cp\u003eSRMR Standardized root mean square residual\u003c/p\u003e\n\u003cp\u003eSSMIS Self-Stigma of Mental Illness Scale\u003c/p\u003e\n\u003cp\u003eSToP-MD Stigma Towards Persons with Mental Disorders\u003c/p\u003e\n\u003cp\u003eSToP-AP Stigma Towards Persons with Mental Disorders - \u0026ldquo;Assumption of Problems\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eSToP-PS Stigma Towards Persons with Mental Disorders - \u0026ldquo;Prejudiced Stigmatization\u0026rdquo; subscale\u003c/p\u003e\n\u003cp\u003eTLI Tucker\u0026ndash;Lewis index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with animals performed by any of the authors. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the institutional and/or national research committee and the 1964 Helsinki declaration and its later amendments, or comparable ethical standards. The study received ethical approval from the Ethics Committees of the Faculty of Psychology at the Ruhr-Universit\u0026auml;t Bochum (reference numbers: 257).\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll datasets used and analyzed during the current study will be freely available at https://osf.io/fh7cw\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNo granting agency funded the study.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eJCC conceived and conceptualized the study. JCC managed and analyzed the data and wrote the manuscript. MLW, SEB, TT, and IH supervised the study. TT and IH contributed to the provision of the stimulus materials. IH also assisted with recruitment.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eAll authors have agreed to authorship. The authors would like to thank Caroline Esch, Linn Freisewinkel, Vanessa Goede, Carolin Korn, Amelie Niemeyer, and Johanna Sophie Schneider for their support in collecting the data. We especially want to thank Amelie Niemeyer for the construction of the online questionnaire.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrohan E, Slade M, Clement S, Thornicroft G. Experiences of mental illness stigma, prejudice and discrimination: A review of measures. BMC Health Service Res. 2010;10:80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW. Lessons learned from unintended consequences about erasing the stigma of mental illness. World Psychiatry. 2016;15(1):67\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eManzo JF. On the sociology and social organization of stigma: some ethnomethodological insights. Hum Stud. 2004;27(4):401\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLink BG, Phelan JC. Conceptualizing stigma. Ann Rev Sociol. 2001;27(1):363\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR\u0026uuml;sch N, Angermeyer MC, Corrigan PW. Mental illness stigma: Concepts, consequences, and initiatives to reduce stigma. Eur Psychiatry. 2005;20(8):529\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEstroff SE. Self, identity, and subjective experiences of schizophrenia: In search of the subject. Schizophr Bull. 1989;15(2):189\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Rao D. On the self-stigma of mental illness: stages, discolure, and strategies for change. Can J Psychiatry. 2012;57(8):464\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNdetei DM, Mutiso V, Maraj A, Anderson KK, Musyimi C, McKenzie K. Stigmatizing attitudes toward mental illness among primary school children in Kenya. Soc Psychiatry Psychiatr Epidemiol. 2016;51(1):73\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLau AS, Guo S, Tsai W, Nguyen DJ, Nguyen HT, Ngo V, Weiss B. Adolescents' stigma attitudes toward internalizing and externalizing disorders: cultural influences and implications for distress manifestations. Clin Psychol Sci. 2016;4(4):704\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBartels SM, Galindo C, Angeles G, Barrington C. Assessing associations between stigma and mental health among preexposure prophylaxis users in Guatemala. Stigma Health. 2024;9(4):575\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKotera Y, Kotera H, Taylor E, Wilkes J, Colman R, Riswani R. Mental health of Indonesian university students: U.K. comparison and relationship between mental health shame and self-compassion. Stigma Health. 2024;9(3):239\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCoppens E, Van Audenhove C, Scheerder G, Arensman E, Coffey C, Costa S, Koburger N, Gottlebe K, Gusm\u0026atilde;o R, O'Connor R, et al. Public attitudes toward depression and help-seeking in four European countries baseline survey prior to the OSPI-Europe intervention. J Affect Disord. 2013;150(2):320\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli A, King M, Strydom A, Hassiotis A. Self-reported stigma and its association with socio-demographic factors and physical disability in people with intellectual disabilities: results from a cross-sectional study in England. Soc Psychiatry Psychiatr Epidemiol. 2016;51(3):465\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDumke L, Wilker S, Hecker T, Neuner F. Barriers to accessing mental health care for refugees and asylum seekers in high-income countries: A scoping review of reviews mapping demand and supply-side factors onto a conceptual framework. Clin Psychol Rev. 2024;113:102491.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKearns M, Muldoon OT, Msetfi RM, Surgenor PWG. Understanding help-seeking amongst university students: The role of group identity, stigma, and exposure to suicide and help-seeking. Front Psychol. 2015;6:1462.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePumpa M, Martin G. The impact of attitudes as a mediator between sense of autonomy and help-seeking intentions for self-injury. Child Adolesc Psychiatry Mental Health. 2016;9:27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClement S, Schauman O, Graham T, Maggioni F, Evans-Lacko S, Bezborodovs N, Morgan C, R\u0026uuml;sch N, Brown JSL, Thornicroft G. What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychol Med. 2015;45(1):11\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSirey J, Bruce ML, Alexopoulos GS, Perlick DA, Friedman SJ, Meyers BS. Perceived stigma and patient-rated severity of illness as predictors of antidepressant drug adherence. Psychiatric Serv. 2001;52(12):1615\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW. How stigma interferes with mental health care. Am Psychol. 2004;59(7):614\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWahl OK. Mental health consumers' experience of stigma. Schizophr Bull. 1999;25(3):467\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchomerus G, Angermeyer MC, Baumeister SE, Stolzenburg S, Link BG, Phelan JC. An online intervention using information on the mental health-mental illness continuum to reduce stigma. Eur Psychiatry. 2016;32:21\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBirtel MD, Crisp RJ. Treating prejudice: an exposure- therapy approach to reducing negative reactions toward stigmatized groups. Psychol Sci. 2012;23(11):1379\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchachter HM, Girardi A, Ly M, Lacroix D, Lumb AB, van Berkom J, Gill R. Effects of school-based interventions on mental health stigmatization: a systematic review. Child Adolesc Psychiatry Mental Health. 2008;2:18.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCerully JL, Collins RL, Wong E, Seelam R, Yu J. Differential response to contact-based stigma reduction programs: perceived quality and personal experience matter. Psychiatry Res. 2018;259:302\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEconomou M, Kontoangelos K, Peppou LE, Arvaniti A, Samakouri M, Douzenis A, Papadimitriou GN. Medical students' attitudes to mental illnesses and to psychiatry before and after the psychiatric clerkship: training in a specialty and a general hospital. Psychiatry Res. 2017;258:108\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLivingston JD, Boyd JE. Correlates and consequences of internalized stigma for people living with mental illness: a systematic review and meta-analysis. Soc Sci Med. 2010;71(12):2150\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLink BG, Yang LH, Phelan JC, Collins PY. Measuring mental illness stigma. Schizophr Bull. 2004;30(3):511\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhatley CD. Social attitudes toward discharged mental patients. Soc Probl. 1959;6:313\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYap MBH, MacKinnon A, Reavley N, Jorm AF. The measurement properties of stigmatizing attitudes towards mental disorders: results from two community surveys. Int J Methods Psychiatr Res. 2014;23(1):49\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhillips DL. Rejection: a possible consequence of seeking help for mental disorders. Am Sociol Rev. 1963;28:963\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCumming E, Cumming H. Closed ranks. An experiment in mental health education. Cambridge, Massachusetts: Harvard University Press; 1957.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOsgood CE, Suci GJ, Tannenbaum PH. The measurement of meaning. Urbana, IL: University of Illinois Press; 1957.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrisp AH, Gelder MG, Rix S, Meltzer HI, Rowlands OJ. Stigmatisation of people with mental illnesses. Br J Psychiatry. 2000;177(1):4\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNunnally JC, Kittross JM. Public attitudes toward mental health professions. Am Psychol. 1958;13:589\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNunnally JC. Popular conceptions of mental health: their development and change. New York, NY: Holt, Rinehart, and Winston; 1961.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlmsted DW, Durham K. Stability of mental health attitudes: a semantic differential study. J Health Soc Behav. 1976;17:35\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Markowitz FE, Watson A, Rowan D, Kubiak MA. An attribution model of public discrimination towards persons with mental illness. J Health Soc Behav. 2003;44(2):162\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeiner B, Perry RP, Magnusson J. An attributional analysis of reactions to stigmas. J Personal Soc Psychol. 1988;55(5):738\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu T-H, Chang C-C, Chen C-Y, Wang J-D, Lin C-Y. Further psychometric evaluation of the self-stigma scale-short: Measurement invariance across mental illness and gender. PLoS ONE. 2015;10(2):e0117592\u0026ndash;0117592.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Lundin RK. Don\u0026rsquo;t call me nuts: coping with the stigma of mental illness. Tinley Park, IL: Recovery; 2001.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMak WWS, Cheung RYM. Self-stigma among concealable minorities in Hong Kong: Conceptualization and unified measurement. Am J Orthopsychiatry. 2010;80:263\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLink BG, Mirotznik J, Cullen FT. The effectiveness of stigma coping orientations: can negative consequences of mental illness labeling be avoided? J Health Soc Behav. 1991;32(3):302\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Watson AC, Barr L. The self-stigma of mental illness: Implications for self-esteem and self-efficacy. J Social Clin Psychol. 2006;25:875\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGriffiths KM, Christensen H, Jorm AF, Evans K, Groves C. Effect of web-based depression literacy and cognitive-behavioural therapy interventions on stigmatising attitudes to depression. Br J Psychiatry. 2004;185:342\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCohen J, Struening EL. Opinions about mental illness in the personnel of two large mental hospitals. J Abnorm Soc Psychol. 1962;64:349\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStruening EL, Cohen J. Factorial invariance and other psychometric characteristics of five opinions about mental illness factors. Educ Psychol Meas. 1963;23(2):289\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTaylor SM, Dear MJ. Scaling community attitudes toward the mentally ill. Schizophr Bull. 1981;7(2):225\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKenny A, Bizumic B, Griffiths KM. The Prejudice towards People with Mental Illness (PPMI) scale: structure and validity. BMC Psychiatry. 2018;18:293.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen ESM, Chung W, Hui CLM, Chan SKW, Ho Ming Lee E, Chen EYH. Self-stigma and affiliate stigma in first-episode psychosis patients and their caregivers. Soc Psychiatry Psychiatr Epidemiol. 2016;51(9):1225\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evon dem Knesebeck O, Mnich E, Angermeyer MC, Kofahl C, Makowski A. Changes in depression stigma after the Germanwings crash - Findings from German population surveys. J Affect Disord. 2015;186:261\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evon Heydendorff SC, Meyer-Lindenberg A, Dressing H. Stigmatization of mentally ill patients by media coverage of Germanwings disaster. Int J Soc Psychiatry. 2016;62:749\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlett M, Tessmer S. Lockerung der Schweigepflicht zum Zweck der Verhinderung von Straftaten? \u003cem\u003ePsychotherapeutenjournal\u003c/em\u003e 2016, 15(4):380\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYap MBH, Reavley N, Mackinnon AJ, Jorm AF. Psychiatric labels and other influences on young people's stigmatizing attitudes: findings from an Australian national survey. J Affect Disord. 2013;148(2\u0026ndash;3):299\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBagley C, King M. Exploration of three stigma scales in 83 users of mental health services: implications for campaigns to reduce stigma. J Mental Health. 2005;14(4):343\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang X, Huang X, Jackson T, Chen R. Components of implicit stigma against mental illness among Chinese students. PLoS ONE. 2012;7(9):e46016\u0026ndash;46016.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeiner DJ. SoSci Survey (Version 2.4.00-i) [Computer Software]. In.; 2014.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSibley CG, Duckitt J. Personality and prejudice: a meta-analysis and theoretical review. Personality Social Psychol Rev. 2008;12(3):248\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHayward P, Bright JA. Stigma and mental illness: A review and critique. J Mental Health. 1997;6(4):345\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGriffiths KM, Christensen H, Jorm AF. Predictors of depression stigma. BMC Psychiatry. 2008;8:25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLink BG, Cullen FT, Frank J, Wozniak JF. The social rejection of former mental patients: Understanding why labels matter. Am J Sociol. 1987;92(6):1461\u0026ndash;500.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngermeyer MC, Matschinger H. Social distance towards the mentally ill: Results of representative surveys in the Federal Republic of Germany. Psychol Med. 1997;27(1):131\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCosta PT, McCrae RR. Revised NEO Personality inventory (NEO PI-R) and NEO five-factor inventory, Profession edn. FIorida: Psychological Assessment Resources;: Odessa; 1992.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorkenau P, Ostendorf F. NEO-F\u0026uuml;nf-Faktoren Inventar (NEO-FFI) nach Costa und McCrae. Handanweisung. G\u0026ouml;ttingen: Hogrefe; 1993.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026ouml;rner A, Drapeau M, Albani C, Geyer M, Schmutzer G, Br\u0026auml;hler E. Deutsche Normierung des NEO-F\u0026uuml;nf-Faktoren-Inventars (NEO-FFI). Z f\u0026uuml;r Medizinische Psychologie. 2008;17:133\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026ouml;rner A, Geyer M, Br\u0026auml;hler E. Das NEO-F\u0026uuml;nf-Faktoren Inventar (NEO-FFI). Diagnostica. 2002;48(1):19\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuker HE, Block JR, Younng JH. The measurement of attitudes toward disabled persons. New York: Human Resources Center;: Albertson; 1970.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeifert KH, Bergmann C. Entwicklung eines Fragebogens zur Messung der Einstellungen gegen\u0026uuml;ber K\u0026ouml;rperbehinderten. Heilp\u0026auml;dagogische Forschung. 1983;10(3):290\u0026ndash;320.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeifert KH, Bergmann C. The EKB-Scale - An inventory to measure the attitudes toward physically disabled persons. Int J Rehabil Res. 1983;6(2):186\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCwik JC, Till B, Bieda A, Blackwell SE, Walter C, Teismann T. Measuring attitudes towards suicide: Preliminary evaluation of an attitude towards suicide scale. Compr Psychiatr. 2017;72:56\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBiblarz A, Brown RM, Biblarz DN, Pilgrim MP, Baldree BF. Media influence on attitudes toward suicide. Suicide Life-Threatening Behav. 1991;21:374\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaulhus DL. The Balanced Inventory of Desirable Responding. Toronto/Buffalo: Multi-Health Systems; 1998.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMusch J, Brockhaus R, Br\u0026ouml;der A. Ein Inventar zur Erfassung von zwei Faktoren sozialer Erw\u0026uuml;nschtheit. Diagnostica. 2002;48(3):121\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaiser HF. A second generation little jiffy. Psychometrika. 1970;35(4):401\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBartlett MS. Tests of significance in factor analysis. Br J Psychol. 1950;3(2):77\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcDonald RP. Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.; 1999.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcDonald RP. Generalizability in factorable domains: Domain validity and generalizability. Educ Psychol Meas. 1978;38(1):75\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcDonald RP. The theoretical foundations of principal factor analysis, canonical factor, and alpha factor analysis. Br J Math Stat Psychol. 1970;23(1):1\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Jillsdale, NJ: Lawrence Earlbaum; 1988.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIBM Corp. IBM SPSS Statistics for Mac. In. Edited by 30.0 V. IBM Corp; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Sonderen E, Sanderman R, Coyne JC. Ineffectiveness of reverse wording of questionnaire items: let's learn from cows in the rain. PLoS ONE. 2013;8(7):e68967.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuagdagnoli E, Velicer WF. Relation of sample size to the stability of component structure. Psychol Bull. 1988;103:265\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBors DA, Vigneau F, Lalande F. Measuring the need for cognition: item polarity, dimensionality, and the relation with ability. Pers Indiv Differ. 2006;40(4):819\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHartshorne TS. Psychometric properties and confirmatory factor analysis of the UCLA loneliness scale. J Pers Assess. 1993;61(1):182\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Edwards AB, Qreen A, Thwart SL, Perm DL. Prejudice, social distance, and familiarity with mental illness. Schizophr Bull. 2001;27(2):219\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDietrich S, Beck M, Bujantugs B, Kenzine D, Matschinger H, Angermeyer MC. The relationship between public causal beliefs and social distance toward mentally ill people. Aust N Z J Psychiatry. 2004;38(5):348\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith AL, Cashwell CS. Social distance and mental illness: Attitudes among mental health and non-mental health professionals and trainees. Prof Counselor: Res Pract. 2011;1(1):13\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKelly CM, Jorm AF. Stigma and mood disorders. Curr Opin Psychiatry. 2007;20(1):13\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngermeyer MC, Holzinger A, Matschinger H. Mental health literacy and attitude towards people with mental illness: a trend analysis based on population surveys in the eastern part of Germany. Eur Psychiatry. 2009;24(4):225\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReavley NJ, Jorm AF. Stigmatising attitudes towards people with mental disorders: Changes in Australia over 8 years. Psychiatry Res. 2012;197(3):302\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMatschinger H, Angermeyer MC, Link BG. Variationen der Antwortstrukturen in Abh\u0026auml;ngigkeit vom Grad pers\u0026ouml;nlicher Betroffenheit. Eine Methodenstudie am Beispiel der Discriminatioin-Devaluation-Scale. Psychother Psychosom Med Psychol. 1991;41:278\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStadler SM. Einstellungen und Soziale Distanz gegen\u0026uuml;ber psychisch Kranken. Positive Wirkung sozialer Kontakte im Umfeld einer gemeindepsychiatrischen Tagesst\u0026auml;tte im Vergleich zu einer Kontrollregion. Z f\u0026uuml;r Psychiatrie Psychologie und Psychother. 2010;58:265\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCalear AL, Griffiths KM, Christensen H. Personal and perceived depression stigma in Australian adolescents: magnitude and predictors. J Affect Disord. 2011;129(1\u0026ndash;3):104\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEkehammar B, Akrami N. Personality and prejudice: from Big Five personality factors to facets. J Pers. 2007;75(5):899\u0026ndash;925.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEkehammar B, Akrami N. The relation between personality and prejudice: a variable- and a person-centred approach. Eur J Pers. 2003;17(6):449\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGraziano WG, Bruce J, Sheese BE, Tobin RM. Attraction, personality, and prejudice: liking none of the people most of the time. J Personal Soc Psychol. 2007;93(3):565\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCanu WH, Newman ML, Morrow TL, Pope DLW. Social appraisal of adult ADHD: stigma and influences of the beholder's Big Five personality traits. J Atten Disord. 2008;11(6):700\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcCrae RR, Costa PT Jr, Martin TA, Oryol VE, Senin IG, O'Cleirigh C. Personality correlates of HIV stigmatization in Russia and the United States. J Res Pers. 2007;41(1):190\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorecki L, Gozdzik-Zelazny A, Pokorski M. Personality and perception of stigma in psychiatric patients with depressive disorders. Eur J Med Researc. 2010;15:10\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMajor B, Quinton WJ, McCoy SK. Antecedents and consequences of attributions to discrimination: theoretical and empirical advances. In., edn. Edited by Zanna MP. San Diego, CA: Academic Press; 2002: 251\u0026ndash;330.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMargetić BA, Jakovljević M, Ivanec D, Margetić B, Tošić G. Relations of internalized stigma with temperament and character in patients with schizophrenia. Compr Psychiatr. 2010;51:603\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW. Mental health stigma as social attribution: implications for research methods and attitude change. Clin Psychol Sci Pract. 2000;7:48\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW. The impact of stigma on severe mental illness. Cogn Behav Pract. 1998;5(2):201\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSocoll D, Holtgraves T. Attitudes toward the mentally ill: the effects of label and beliefs. Sociol Q. 1992;33:435\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCwik JC, Teismann T. Misclassification of self-directed violence. Clin Psychol Psychother. 2017;24(3):677\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChan SKW, Lee KW, Hui CLM, Chang WC, Lee EHM, Chen EYH. Gender effect on public stigma changes towards psychosis in the Hong Kong Chinese population: a comparison between population surveys of 2009 and 2014. Soc Psychiatry Psychiatr Epidemiol 2016.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndersson HW, Bj\u0026oslash;rngaard JH, Kaspersen SL, Wang CEA, Skre I, Dahl T. The effects of individual factors and school environment on mental health and prejudiced attitudes among Norwegian adolescents. Soc Psychiatry Psychiatr Epidemiol. 2010;45(5):569\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGonzalez JM, Alegr\u0026iacute;a M, Prihoda TJ, Copeland LA, Zeber JE. How the relationship of attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education. Soc Psychiatry Psychiatr Epidemiol. 2011;46(1):45\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNorman RMG, Sorrentino RM, Gawronski B, Szeto ACH, Ye Y, Windell D. Attitudes and physical distance to an individual with schizophrenia: the moderating effect of self-transcendent values. Soc Psychiatry Psychiatr Epidemiol. 2010;45(7):751\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGirma E, Tesfaye M, Froeschl G, M\u0026ouml;ller-Leimk\u0026uuml;hler AM, M\u0026uuml;ller N, Dehning S. Public stigma against people with mental illness in the Gilgel Gibe Field Research Center (GGFRC) in Southwest Ethiopia. PLoS ONE. 2013;8(12):e82116\u0026ndash;82116.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuinn KM, Laidlaw K, Murray LK. Older peoples\u0026rsquo; attitudes to mental illness. Clin Psychol Psychother. 2009;16:33\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartin JK, Pescosolido BA, Tuch SA. Of fear and loathing: The role of disturbing behavior, labels, and causal attributions in shaping public attitudes toward people with mental illness. J Health Soc Behav. 2000;41(2):208\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRosseel Y. lavaan: an R package for structural equation modeling. J Stat Softw. 2012;48(2):1\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Core Team. R: A language and environment for statistical computing, Version 4.5.0 edn. Vienna. Austria: R Foundation for Statistical Computing; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUllman JB. Structural equation modeling. In., 4th ed edn. Edited by Tabachnick BG, Fidell LS. Needham Heights, MA: Allyn \u0026amp; Bacon; 2001: 653\u0026ndash;771.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKline RB. Principles and practice of structural equation modeling. 3rd ed. edn. New York: Guilford Press; 2010.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchumacker RE, Lomax RG. A beginner's guide to structural equation modeling. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 2004.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychol Methods. 1996;1(2):130\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRouquette A, Falissard B. Sample size requirements for the internal validation of psychiatric scales. Int J Methods Psychiatr Res. 2011;20(4):235\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Powell KJ, Michaels PJ. The effects of news stories on the stigma of mental illness. J Nerv Mental Disease. 2013;201(3):179\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFaul F, Erdfelder E, Lang A-G, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFaul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRiva G, Teruzzi T, Anolli L. The use of the internet in psychological research: comparison of online and offline questionnaires. Cyberpsychology Behav. 2003;6(1):73\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVallejo MA, Jord\u0026aacute;n CM, D\u0026iacute;az MI, Comeche MI, Ortega J. Psychological assessment via the internet: a reliability and validity study of online (vs paper-and-pencil) versions of the general health questionnaire-28 (GHQ-28) and the symptoms check-list-90-revised (SCL-90-R). J Med Internet Res. 2007;9(1):e2\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Beuckelaer A, Lievens F. Measurement equivalence of paper-and-pencil and internet organizational surveys: a large scale examination in 16 countries. Appl Psychol. 2009;58:336\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Wassell A. Understanding and influencing the stigma of mental illness. J Psychosocial Nurs. 2008;46(1):42\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCorrigan PW, Watson AC. Understanding the impact of stigma on people with mental illness. World Psychiatry. 2002;1(1):16\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJorm AF, Christensen H, Griffiths KM. Public beliefs about causes and risk factors for mental disorders. Changes in Australia over 8 years. Soc Psychiatry Psychiatr Epidemiol. 2005;40(9):764\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRead J, Haslam N, Sayce L, Davies E. Prejudice and schizophrenia: a review of the 'mental illness is an illness like any other' approach. Acta psychiatrica Scandinavica. 2006;114:303\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"stigma, attitudes, mental disorders, scale, assessment","lastPublishedDoi":"10.21203/rs.3.rs-6890888/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6890888/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStigmatizing attitudes toward individuals with mental disorders represent a major barrier to treatment, recovery, and social inclusion. The present research introduces and psychometrically evaluates the German-language SToP-MD (Stigma Toward People with Mental Disorders) scale across three independent studies with distinct samples.\u003c/p\u003e\u003cp\u003eIn study 1 (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266), an initial item pool was developed and refined based on theoretical frameworks and exploratory factor analysis. In study 2 (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;488), confirmatory factor analysis supported a two-factor structure comprising prejudiced stigmatization (SToP-MD-PS) and assumption of problems (SToP-MD-AP). The model showed acceptable fit (e.g., CFI\u0026thinsp;=\u0026thinsp;.918, TLI\u0026thinsp;=\u0026thinsp;.892, RMSEA\u0026thinsp;=\u0026thinsp;.078, SRMR\u0026thinsp;=\u0026thinsp;.051) and good internal consistencies (α\u0026thinsp;=\u0026thinsp;.84 and α\u0026thinsp;=\u0026thinsp;.78). In study 3 (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;266), convergent and discriminant validity were examined via Spearman correlations with established instruments.\u003c/p\u003e\u003cp\u003eAs hypothesized, the SToP-MD subscales were positively associated with depression stigma (DSS) and social distance (SDI), and negatively correlated with openness and agreeableness (NEO-FFI), supporting convergent validity. Discriminant validity was partially confirmed by low or non-significant correlations with attitudes toward physically disabled individuals (ATDP), suicide-related cognitions (CCSS), and socially desirable responding (BIDR).\u003c/p\u003e\u003cp\u003eAcross all three studies, the SToP-MD demonstrated robust psychometric properties. It captures both overt prejudices and implicit burden assumptions, offering a nuanced assessment of public stigma toward mental disorders. The scale can serve as a valuable tool in stigma research, public health monitoring, and evaluation of interventions. Future research should extend validation to more diverse samples and test predictive and longitudinal utility.\u003c/p\u003e","manuscriptTitle":"Attitudes towards people with mental disorders: Results of a psychometric evaluation and confirmatory factor analysis of the Stigma Towards People with Mental Disorders (SToP- MD) Scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 06:27:07","doi":"10.21203/rs.3.rs-6890888/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-05T04:27:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-26T18:16:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-19T17:29:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"96044711493618808733364151573799305758","date":"2025-09-12T17:17:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235587593566175380530360852879793786407","date":"2025-09-10T14:42:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-05T12:19:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-28T06:32:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-08T06:34:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-07T16:27:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-08-07T16:23:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f361f13-09c7-4421-a5a5-72c10946fb30","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:02:09+00:00","versionOfRecord":{"articleIdentity":"rs-6890888","link":"https://doi.org/10.1186/s40359-026-04627-x","journal":{"identity":"bmc-psychology","isVorOnly":false,"title":"BMC Psychology"},"publishedOn":"2026-05-01 15:58:25","publishedOnDateReadable":"May 1st, 2026"},"versionCreatedAt":"2025-08-19 06:27:07","video":"","vorDoi":"10.1186/s40359-026-04627-x","vorDoiUrl":"https://doi.org/10.1186/s40359-026-04627-x","workflowStages":[]},"version":"v1","identity":"rs-6890888","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6890888","identity":"rs-6890888","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}