The Four-Item Mentalising Index (FIMI): A multinational validation of the Arabic version in 12 countries

The Four-Item Mentalising Index (FIMI): A multinational validation of the Arabic version in 12 countries | 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 The Four-Item Mentalising Index (FIMI): A multinational validation of the Arabic version in 12 countries Feten Fekih-Romdhane, Amira Mohammed Ali, Amthal Alhuwailah, Fouad Sakr, and 22 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4870250/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The lack of sound measures to assess mentalising in Arabic-speaking adults is a significant gap that can substantially constrain understanding of the expression and difficulties in the mentalising processes across the lifespan in the Arab world, and of the cross-cultural. Therefore, this study aimed to investigate the psychometric properties of an Arabic translation of the FIMI in a multi-national sample of non-clinical adults. Methods: A sample of 8,408 adults (74.5% females, mean age 24.70 ± 8.44 years) from the general population of twelve Arab countries was surveyed to examine the psychometric properties of the Arabic FIMI. Results: CFA indicated that fit of the one-factor model of FIMI scores was excellent: RMSEA = .035 (90% CI .023, .048), SRMR = .012, CFI = .996, TLI = .989, and had adequate internal consistency reliability (ω = .68; α = .65). Indices suggested that configural, metric, and scalar invariance was supported across sex and country groups. Finally, correlational analyses provided support for construct validity of the Arabic-language version of the FIMI, by showing significant positive correlations between mentalising and self-reported autistic traits scores. Conclusion: Findings suggest that the Arabic FIMI is valid, reliable ad suitable for use among Arabic-speaking adults. The scale may raise awareness among clinicians and researchers of the possibilities to easily and accurately assess mentalising in order to enable the development, testing and monitoring of tailored Mentalising-based treatments aimed at addressing impaired mentalising and managing a range of mental disorders in Arab settings. Mentalising Four-Item Mentalising Index FIMI Psychometric properties Validation Arabic. Figures Figure 1 INTRODUCTION Mentalising (or mentalisation) refers to “the ability to understand one’s own and others’ mental states, thereby comprehending one’s own and others’ intentions and affects” ([ 1 ], p.1). This ability can be regarded as a metacognitive process [ 2 ] which enables an individual to interpret one own’s or others’ behaviors through attributions of mental states (i.e., emotions, thoughts, beliefs, intentions, wishes) that might underlie these behaviors [ 3 ]. Mentalizing is thought to be related to, but potentially distinct from, the concept of “theory of mind”, as the former focuses more specifically on affective and cognitive mental states in the context of emotional arousal [ 2 , 4 ], whereas the latter reflects “epistemic states” such as intentions, beliefs and persuasions ([ 2 ], p.730). Mentalizing constitutes an important determinant of mental health [ 5 ]. It is recognized as a core element for healthy personality development and social cognition, as it plays a major role in one’s ability to feel/express empathy, to communicate, to regulate emotions and impulse control, to experience well-being, as well as in entertaining relationships and overall interpersonal functioning [ 3 , 5 , 6 ]. As such, a lack or deficiency in mentalizing ability was shown to be significantly linked to a range of psychopathology, such as psychotic disorders [ 7 ] - including at the early stages of disease progression [ 8 ]-, bipolar disorders [ 9 ], Major depressive disorders [ 10 ], eating disorders [ 11 ], borderline personality disorder [ 12 ], and substance use disorders [ 13 ]. Mentalising deficits has also been found to be involved in the psychological functioning within a range of psychiatric conditions, including autism and psychosis [ 14 ]. In light of these findings, researchers have recently turned to mentalising in an attempt to provide a better understanding and more efficacious treatments for severe, yet poorly understood and inadequately managed diseases such as schizophrenia [ 15 ], or dual diagnosis personality disorder and substance use disorder [ 16 ]. Therefore, measuring and exploring mentalising abilities should be considered a growing need for both clinicians and researchers involved in these psychiatric disorders’ diagnosis, management and rehabilitation. Measurement tools of mentalising Several measurement instruments are currently available to assess mentalising, but no benchmark or gold standard measure exists. The existing measures can be classified based on their nature and the targeted population group. For instance, there are interview-based tools specifically designed for use among older adolescents (aged 16 years and over) and adults, such as the Metacognition Assessment Scale [ 17 ] and the Reflective Functioning Scale [ 18 ]. Other tools consist of narrative-based or task-based measures that were developed to be used among children and/or young adolescents, such as the Mentalizing Stories for Adolescents [ 19 ] or the Affect Task [ 20 ]. Although these measures have proven to be psychometrically sound, their administration requires dedicated time and trained personnel during a clinical session [ 20 ]. A good alternative to overcome these limitations could be mentalising measures based on self-report. Examples of self-administered measures include the 33-item Multidimensional Mentalizing Questionnaire [ 21 ], the 22-item Mentalising Imbalances Scale [ 22 ], the 20-item Interactive Mentalizing Questionnaire [ 23 ], and the 15-item Mentalising Questionnaire [ 24 ]. While these measures have the major advantage of being self-report without the problems inherent in interviewer-administered measures, they can be time-consuming to administer with their many items, making them less suitable for use in highly specialized clinical contexts and large-scale, multi-time-point studies involving large samples. In addition, most of them were mainly designed as clinical screening instruments to be used in clinical rather than community populations [ 21 ]. Furthermore, several previous mentalising measures were of questionable validity, as they often had untested or poor psychometric characteristics. Moreover, there have been concerns about what construct it is really meant to be evaluated, as some tools claim to measure mentalising, whereas other concepts such as emotion processing are actually being measured [ 25 ]. Other tools combined and conflated many constructs, including mentalising, empathy and emotion perception [ 26 ]. In an effort to address these limitations, Clutterbuck et al. [ 27 ] developed the Four-Item Mentalising Index (FIMI), a self-report scale aimed specifically assessing the mentalising construct while simplifying its conceptual complexity, and enabling its use in applied clinical and research settings. The FIMI The FIMI was designed to selectively measure mentalising abilities in community adults [ 27 ]. The FIMI is composed of the following four items: (1) “I find it easy to put myself in somebody else’s shoes”, (2) “I sometimes find it difficult to see things from other people’s point of view”, (3) “I sometimes try to understand my friends better by imagining how things look from their perspective”, and (4) “I can usually understand another person’s viewpoint, even if it differs from my own ‘’. Through a series of studies investigating its psychometric properties in both clinical (i.e. autistic) and non-clinical English-speaking adults from the US and UK, the FIMI was demonstrated to be methodologically and conceptually a robust measure to assess mentalising abilities in the adult population. In particular, the FIMI showed a solid unidimensional factor structure, and data supported its internal consistency reliability, measurement invariance by sex, test-retest reliability, and construct validity of its scores against autistic traits, a cognitive mentalising task, and comparing scores in non-autistic and autistic individuals [ 27 ]. More recently, the FIMI was adapted, translated and validated to the German language in 283 German-speaking adults from Germany, Austria, and Switzerland [ 28 ]. The German version showed adequate psychometric properties in terms of factor structure, inner consistency, and relationships with relevant validity criteria (including autistic traits) [ 28 ]. However, no previous studies examining the psychometric properties of the FIMI in the Arabic language could be found in the literature. Rationale and aim of this study Our study was motivated by some key needs. First, despite a sizeable amount of research literature has been undertaken on mentalising in children, much less attention has been devoted to exploring mentalising in adulthood [ 29 ]. Second, no studies have yet examined mentalising in adults from Arab countries as far as we know, which may be explained by the lack of locally validated instrument to measure this construct in the Arabic-speaking adult population. Studying mentalising in general population adults is crucial to the understanding of social-cognitive changes that occur as one ages [ 30 ], and to gain knowledge on clinical phenomena that are characterised by mentalising problems, such as autism [ 31 ]. Third, a meta-analysis showed that the conceptualization of mentalising can differ between cultures (e.g., self other mentalising in individualistic cultures such as Western societies) [ 32 ], which emphasizes the strong need to make available mentalising measures that are appropriate for different cultural contexts. Therefore, this study aimed to investigate the psychometric properties of an Arabic translation of the FIMI in a multi-national sample of non-clinical adults. Following the English and German versions of the FIMI, we hypothesise that the Arabic FIMI will yield a single-factor solution, as well a good internal consistency reliability and adequate construct validity. In addition, it is anticipated that the factor structure will show measurement invariance across sex and country. Methods Participants and procedure The current study is part of the M ultinational A utism P roject (“MAP”) of the Arab world (more details about the project can be found in [ 33 ]). The study has a cross-sectional design. An online anonymous questionnaire was launched during the period from February to April 2024. Invitations to take part in the study were sent to potential participants via several social media platforms, such as Facebook, WhatsApp, Instagram and TikTok, using snowball sampling. Eligible participants were adults aged 18 years and over from the general population of 12 Arab countries: Algeria, Bahrain, Egypt, Iraq, Jordan, Kingdom of Saudi Arabia, Kuwait, Lebanon, Morocco, Oman, Palestine, Tunisia. Participation was on a voluntary basis and no compensation was offered. Those who gave their informed consent to participate in the first section of the questionnaire were then redirected to the rest of the questionnaire. Measures Sociodemographic information Sociodemographic data collected included sex (male, female), age, educational level (elementary, middle, secondary, university), household crowding index (i.e. the number of persons divided by the number of rooms in the house except the kitchen and bathrooms; with higher scores reflecting worse socioeconomic status). The FIMI The FIMI was rigorously translated and culturally adapted for the Arabic environment and language. The translation and adaptation processes ensured that the meaning of the four items remained consistent with that of the original version according to the international norms [ 34 ]. The forward translation and backward translation of the FIMI was performed. Initially, the FIMI was translated from English to Arabic by a translator who was not involved in the research. Then, the backward translation was completed by a health professional who is fluent in English and familiar with the terminology of the area covered by the instrument. This approach was adopted to ensure the conceptual equivalence of each item. Afterwards, both the original and the back-translated English versions were compared by a panel of experts composed of the translators, the research team, two psychiatrists, and one psychologist, in order to resolve any inconsistencies and confirm the accuracy of the translation [ 35 ]. A pilot study was then conducted to ensure that items are clear and easily interpreted. No further adjustments were required, and the translation was examined and confirmed by one of the original authors of the instrument (Professor Punit Shah). The Autism-Spectrum Quotient-28 (AQ-28) The Arabic validated version of the AQ-28 was used in this study [52], which conceptually replicated one of the validation studies conducted by Clutterbuck et al. in the original development of the FIMI. The AQ-28 showed a Cronbach α of .91 in the present sample. The AQ-28 is a self-report scale which measures ATs via 28 items and five factors : (1) Difficulties with imagination (e.g., “I find it difficult to work out people’s intentions”), (2) Difficulties with social skills (e.g., “I find it hard to make new friends”), (3) Preference for routine (e.g., “New situations make me anxious”), (4) Attention switching difficulties (e.g., “I find it easy to do more than one thing at once”), and (5) Fascination for numbers/patterns (e.g., “I notice patterns in things all the time”) [61]. Items are scored on a 4-point Likert scale, with “Slightly agree”/ “Definitely agree” scoring 1 and “Slightly disagree”/ “Definitely disagree” scoring 0. Fifteen items are reverse scored. Total scores range from 0 to 28, with greater scores reflecting higher levels of ATs. Analytic Strategy Data treatment. There were no missing responses in the dataset. To examine the factor structure of the FIMI, we conducted a Confirmatory Factor Analysis using the data from the total sample via SPSS AMOS v.29 software. A minimum sample varying between 12–80 participants was deemed necessary to conduct a confirmatory factor analysis following a recommendation between 3–20 times the number of the scale’s variables [ 36 ]. Parameter estimates were obtained using the maximum likelihood method. Calculated fit indices were the root mean square error of approximation (RMSEA), the Tucker-Lewis Index (TLI) and the comparative fit index (CFI). Values ≤ .08 for RMSEA, and .95 for CFI and TLI indicate good fit of the model to the data [ 37 ]. Multivariate normality was not verified at first (Critical ratio > 5; Bollen-Stine p = .002); therefore, we performed non-parametric bootstrapping procedure. Measurement invariance. To examine gender and country invariance of FIMI scores, we conducted multi-group CFA [ 38 ] using the total sample. Measurement invariance was assessed at the configural, metric, and scalar levels [ 39 ]. We accepted ΔCFI ≤ .010 and ΔRMSEA ≤ .015 or ΔSRMR ≤ .010 as evidence of invariance [ 38 ], Comparison between males and females was done using the Student t -test only if scalar or partial scalar invariance. ANOVA test was used to compare scores between countries. Composite reliability in both subsamples was assessed using McDonald’s ω and Cronbach’s alpha, with values greater than .70 reflecting adequate composite reliability. Normality of the FIMI score was verified since the skewness and kurtosis values for each item of the scale varied between − 1 and + 1 [ 40 ]. To assess concurrent validity, Pearson test was used to correlate FIMI scores with the other scales. Results Of potential participants contacted, 8,408 successfully answered the survey questionnaire and were included in the final analysis. Participants’ mean age was 24.70 ± 8.44 years, and 74.5% were females. The description of participants’ characteristics by country can be found in Table 1 . Table 1 Sociodemographic characteristics of the participants. Oman (n = 433) Iraq (n = 488) Saudi Arabia (n = 342) Jordan (n = 452) Palestine (n = 455) Egypt (n = 1177) Algeria (n = 534) Lebanon (n = 1076) Morocco (n = 456) Bahrain (n = 419) Tunisia (n = 1119) Kuwait (n = 1448) Total (n = 8408) Age (years) 26.31 ± 7.98 20.23 ± 3.10 27.23 ± 9.45 26.85 ± 8.58 21.90 ± 5.68 20.74 ± 3.81 26.79 ± 8.51 27.90 ± 11.81 23.48 ± 11.47 23.50 ± 6.47 27.03 ± 7.38 24.34 ± 7.70 24.70 ± 8.44 Sex Male 108 (24.9%) 148 (30.3%) 75 (21.9%) 160 (35.4%) 82 (18.0%) 146 (12.4%) 135 (25.3%) 389 (36.2%) 119 (25.6%) 102 (24.3%) 324 (29.0%) 357 (24.7%) 2145 (25.5%) Female 325 (75.1%) 340 (69.7%) 267 (78.1%) 292 (64.6%) 373 (82.0%) 1031 (87.6%) 399 (74.7%) 687 (63.8%) 346 (74.4%) 317 (75.7%) 795 (71.0%) 1091 (75.3%) 6263 (74.5%) Education Secondary or less 42 (9.7%) 7 (1.4%) 56 (16.4%) 31 (6.9%) 20 (4.4%) 17 (1.4%) 123 (23.0%) 190 (17.7%) 60 (12.9%) 68 (16.2%) 80 (7.1%) 154 (10.6%) 848 (10.1%) University 391 (90.3%) 481 (98.6%) 286 (83.6%) 421 (93.1%) 435 (95.6%) 1160 (98.6%) 411 (77.0%) 886 (82.3%) 405 (87.1%) 351 (83.8%) 1039 (92.9%) 1294 (89.4%) 7560 (89.9%) HCI 1.63 ± 1.17 1.76 ± 1.05 1.01 ± .62 1.28 ± .62 1.65 ± .94 1.77 ± .82 1.54 ± .77 1.15 ± .94 1.75 ± 1.02 1.45 ± .74 1.15 ± .68 1.22 ± .84 1.41 ± .90 FIMI 10.23 ± 1.93 10.58 ± 2.28 10.63 ± 2.37 10.25 ± 2.18 10.64 ± 2.08 10.75 ± 2.06 10.76 ± 2.05 10.18 ± 2.02 10.88 ± 2.25 10.56 ± 2.39 11.85 ± 2.21 10.11 ± 2.32 10.64 ± 2.24 HCI = Household Crowding Index Confirmatory Factor Analysis of the FIMI scale CFA indicated that fit of the one-factor model of FIMI scores was excellent: RMSEA = .035 (90% CI .023, .048), SRMR = .012, CFI = .996, TLI = .989. The standardised estimates of factor loadings were all adequate (Fig. 1 ). Internal reliability was good (ω = .68; α = .65). Measurement invariance by sex and countries Indices suggested that configural, metric, and scalar invariance was supported across sex (Table 2 ). A significantly higher mean FIMI score was found in females ( M = 10.73, SD = 2.22) compared to males ( M = 10.37, SD = 2.27) in the total sample, t (8406) = -6.48, p < .001. A significant difference in terms of FIMI scores was found between countries, F(11, 8396) = 47.44, p < .001 (Table 1 ). The post-hoc Bonferroni analysis showed a significant difference between Oman and Egypt (p = .001), Oman and Algeria (p = .011), Oman and Morocco (p < .001), Oman and Tunisia (p < .001), Iraq and Tunisia (p < .001), Iraq and Kuwait (p = .002), Saudi Arabia and Tunisia (p < .001), Saudi Arabia and Kuwait (p = .004), Jordan and Egypt (p = .002), Jordan and Algeria (p = .015), Jordan and Tunisia (p < .001), Palestine and Lebanon (p = .010), Palestine and Tunisia (p < .001), Palestine and Kuwait (p < .001), Egypt and Lebanon (p < .001), Egypt and Tunisia (p < .001), Egypt and Kuwait (p < .001), Algeria and Lebanon (p < .001), Algeria and Tunisia (p < .001), Algeria and Kuwait (p < .001), Lebanon and Morocco (p < .001), Lebanon and Tunisia (p < .001), Morocco and Jordan (p = .001), Morocco and Tunisia (p < .001), Morocco and Kuwait (p < .001), Bahrain and Tunisia (p < .001), Bahrain and Kuwait (p = .011), and Tunisia and Kuwait (p < .001). Table 2 Measurement Invariance across sex and countries in the total sample. Model CFI RMSEA SRMR Model Comparison ΔCFI ΔRMSEA ΔSRMR Model 1: sex Configural .994 .031 .022 Metric .993 .026 .034 Configural vs metric .001 .005 .012 Scalar .992 .023 .034 Metric vs scalar .001 .003 < .001 Model 2: Countries Configural .981 .022 .024 Metric .927 .029 .068 Configural vs metric .054 .007 .044 Scalar .892 .028 .076 Metric vs scalar .035 .001 .008 Note. CFI = Comparative fit index; RMSEA = Steiger-Lind root mean square error of approximation; SRMR = Standardised root mean square residual. Concurrent validity Higher total autism scores (r = − .21), difficulties with social skills (r = − .03), preference for routine (r = − .10), difficulties with imagination (r = − .25) and fascination for numbers/patterns (r = − .10) were significantly associated with lower FIMI scores (Table 3 ). Table 3 Pearson correlation matrix. 1. FIMI scores 1 2. AQ-28 - Difficulties with social skills − .03** 1 3. AQ-28 - Preference for routine − .10*** .20*** 1 4. AQ-28 - Attention switching difficulties .001 .28*** .15*** 1 5. AQ-28 - Difficulties with imagination − .25*** .11*** .13*** .16*** 1 6. AQ-28 - Fascination for numbers/patterns − .10*** − .08*** .09*** − .20*** − .09*** 1 7. AQ-28 total scores − .21*** .63*** .51*** .46*** .54*** .36*** FIMI: the Four-Item Mentalising Index; AQ-28: the Autism-Spectrum Quotient-28. **p < .01; ***p < .001. DISCUSSION The lack of sound measures to assess mentalising in Arabic-speaking adults is a significant gap that can substantially constrain understanding of the expression and difficulties in the mentalising processes across the lifespan in the Arab world, and of the cross-cultural. This also can hinder the current understanding of the cross-cultural validity and generalizability of the mentalising concept. This study proposes to validate the Arabic version of the FIMI in a multicountry sample of community adults. The FIMI was chosen to be validated into the Arabic language because of its briefness, conceptual clarity and psychometric validity [ 41 ]. Findings showed that the scale is unidimensional, valid and reliable. This study also tested and supported the measurement invariance of the Arabic FIMI across both sex and country groups. Structurally, our finding strengthens support for the unidimensional model of the mentalising construct initially proposed by Clutterbuck et al. [ 27 ], and supported later in the German validation study by Bertrams et al. [ 28 ]. The investigation of factorial structure in our sample allows to ensure that the interpretation of total FIMI scores is appropriate and meaningful, and that the scale genuinely assesses the mentalising ability construct it intends to assess. Altogether, previous findings along with our results suggest that the factor structure of the FIMI is not much under cross-cultural variations, but is rather universal. Additionally, internal consistency reliability of the Arabic FIMI was satisfactory, with a Cronbach’s alpha of .65 and a McDonald’s omega of .68. Likewise, both the English-language [ 27 ] and the German-language [ 28 ] versions of the FIMI showed acceptable-to-good internal consistency, with a McDonald’s omega of .75 and .82, respectively. Furthermore, the results of the CFA indicated that the FIMI fit the data well and in similar ways across the twelve countries, as well as for both males and females. Measurement invariance is considered a prerequisite to soundness comparisons of mean levels across the sexes, and across individuals originating from and residing in different countries and cultural backgrounds. This finding can help to address the relevant question of whether clinical (e.g., with social anxiety disorder [ 42 ] or autism [ 43 ]) and non-clinical males and females are subject to differences in social cognition and behaviors. Similarly, the developers of the original English version of the FIMI were able to establish measurement invariance across sex in both a large community sample of adults and in university students [ 27 ]. Also, the German version of the FIMI was found to be invariant to sex. It is of note that the German validation did not investigate this psychometric property, and that, overall, there is only very little evidence available on sex-based measurement invariance of mentalising measures [ 27 ]. Higher mean FIMI scores were found in females compared to males, which is consistent with previous findings among both English-speaking [ 27 ] and German-speaking [ 28 ] adults. The measurement invariance of the FIMI across country groups is an especially important and valuable result of the current study, as the majority (or all) previous measures of mentalising lack such cross-cultural validity. Given that mentalising processes can be susceptible to cultural and contextual variation [ 32 ], establishing psychometric equivalence of the FIMI across various Arab countries may enable accurate comparisons of the concept between individuals from different nations and help further understanding of how profiles of mentalising can vary across cultures. Finally, correlational analyses provided support for construct validity of the Arabic-language version of the FIMI, by showing significant positive correlations between mentalising and self-reported autistic traits scores. This result concurs with the strong theoretical and empirical evidence indicating that mentalising difficulties represent a consistent feature of autism [ 44 ], and further supports the utility and relevance of the FIMI for clinical and research practices. The original validation study of the FIMI also observed significant links between the FIMI and autism, and showed the ability of the scale to measure clinically meaningful mentalising differences, as well as to discriminate between autistic and non-autistic individuals [ 27 ]. Additionally, Bertrams et al. [ 28 ] found significant correlations between the German version of the FIMI and different aspects of autistics traits as measured using the AQ-28. Overall, we report a coherent pattern of validation results that aligns with previous research in multiple languages. Strengths and limitations The main strengths of our study are that it included a very large sample of community adults from 12 Arab nations of different regions (e.g., North Africa versus Middle East) and cultural backgrounds (e.g., Gulf versus non-Gulf), and it used a validated measure (the Arabic AQ-28) to assess construct validity. At the same time however, there are some limitations in this study’s methodology that could have affected the interpretation and generalizability of findings. First, only community adults were involved. The validity, reliability and applicability of the Arabic FIMI should be further evaluated in clinical samples with various psychiatric conditions and across different settings. Second, the study did not assess the test-retest reliability of the Arabic FIMI, which would have provided additional information about the stability of the measure over time. Third, future research may incorporate other measures, such as other “objective” mentalising tasks, to further examine validity of the Arabic FIMI. Practical implications There has been an increasing acknowledgement within the scientific community of the importance of the value of assessing mentalizing through a succinct, valid, reliable, and cost-effective tool such as the FIMI in clinical and research settings. In the present study, we demonstrate that the Arabic version of the FIMI has good psychometric qualities allowing to reliably assess ‘subjective’ mentalising in Arabic-speaking adults. The FIMI is concise enough to be administered alongside other survey instruments, and yet sufficiently robust to be used as an independent measurement of mentalising. These are major assets that can have important practical implications, especially in the low-middle income Arab countries where clinicians and researchers often work under time pressure and resources constraints. Offering a psychometrically sound measure of mentalising may raise awareness among clinicians and researchers of the possibilities to easily, reliably and accurately assess mentalising in order to enable the development, testing and monitoring of tailored Mentalising-based treatments aimed at addressing impaired mentalising and managing a range of mental disorders in Arab settings. Finally, the Arabic FIMI will hopefully prompt future research on quantifying individual differences in mentalising difficulties in Arabic-speaking populations, which can further our understanding of how mentalising ability may overlap with other social-cognitive constructs, such as empathy. CONCLUSION This study is the first to our knowledge to validate a measure of mentalising, i.e. the FIMI, in the Arabic language. Clinicians and researchers working in Arab settings would benefit from the Arabic version of the FIMI as a brief, valid, reliable and easy-to-administer self-report measure of mentalising. Beyond its practical usefulness in Arab contexts, such a measure could also provide important theoretical impetus for understanding the expression and clinical correlates of mentalising strengths and difficulties in adults across different cultures. Declarations Ethics Approval and Consent to Participate. The protocol was approved by the home institutions of the study's principal investigators (FFR and SH), namely the ethics committee of Razi Psychiatric Hospital, Manouba, Tunisia (ECRPH-2024-032) and the Lebanese International University's School of Pharmacy ethics committee (2024ERC-025-LIUSOP). When filling out the online form, each participant provided written informed consent. All methods were performed in accordance with the relevant guidelines and regulations (in accordance with the Declaration of Helsinki). Consent for publication:Not applicable. Availability of data and materials : Because of ethical committee constraints, none of the data collected or analyzed during this study are publicly available. However, the corresponding author (SH) may make the data available upon reasonable request. Competing interests: The authors have nothing to disclose. Funding:None. 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Morken KT, Binder P-E, Molde H, Arefjord N, Karterud S: Mentalization-based treatment for female patients with comorbid personality disorder and substance use disorder: A pilot study . Scandinavian Psychologist 2017, 4 . Semerari A, Carcione A, Dimaggio G, Falcone M, Nicolò G, Procacci M, Alleva G: How to evaluate metacognitive functioning in psychotherapy? The metacognition assessment scale and its applications . Clinical Psychology & Psychotherapy 2003, 10 (4):238-261. Fonagy P, Target M, Steele H, Steele M: Reflective Functioning Scale (RF)[Database record]. APA PsycTests . In . ; 1998. Vrouva I, Fonagy P: Development of the mentalizing stories for adolescents (MSA) . Journal of the American Psychoanalytic Association 2009, 57 (5):1174-1179. Vrouva I, Target M, Ensink K: Measuring mentalization in children and young people . In: Minding the child. edn.: Routledge; 2013: 54-76. Gori A, Arcioni A, Topino E, Craparo G, Lauro Grotto R: Development of a new measure for assessing mentalizing: The multidimensional mentalizing questionnaire (MMQ) . Journal of Personalized Medicine 2021, 11 (4):305. Gagliardini G, Gullo S, Caverzasi E, Boldrini A, Blasi S, Colli A: Assessing mentalization in psychotherapy: First validation of the Mentalization Imbalances Scale . Research in Psychotherapy: Psychopathology, Process, and Outcome 2018, 21 (3). Wu H, Fung BJ, Mobbs D: Mentalizing during social interaction: The development and validation of the interactive mentalizing questionnaire . Frontiers in Psychology 2022, 12 :791835. Hausberg MC, Schulz H, Piegler T, Happach CG, Klöpper M, Brütt AL, Sammet I, Andreas S: Is a self-rated instrument appropriate to assess mentalization in patients with mental disorders? Development and first validation of the Mentalization Questionnaire (MZQ) . Psychotherapy Research 2012, 22 (6):699-709. Olderbak S, Geiger M, Wilhelm O: A call for revamping socio-emotional ability research in autism . Behavioral and Brain Sciences 2019, 42 . Quesque F, Rossetti Y: What do theory-of-mind tasks actually measure? Theory and practice . Perspectives on Psychological Science 2020, 15 (2):384-396. Clutterbuck RA, Callan MJ, Taylor EC, Livingston LA, Shah P: Development and validation of the Four-Item Mentalising Index . Psychological Assessment 2021, 33 (7):629. Bertrams A, Blaise M, Krispenz A: German Translation of the Four-Item Mentalising Index (FIMI-G) . Measurement Instruments for the Social Sciences 2024, 6 :1-14. Livingston L, Happe F: Understanding Atypical Social Behaviour Using Social Cognitive Theory: Lessons from Autism . In: The Cognitive Basis of Social Interaction Across the Lifespan. edn.: Oxford University Press (OUP); 2021. Henry JD, Phillips LH, Ruffman T, Bailey PE: A meta-analytic review of age differences in theory of mind . Psychology and aging 2013, 28 (3):826. Lever AG, Geurts HM: Age‐related differences in cognition across the adult lifespan in autism spectrum disorder . Autism Research 2016, 9 (6):666-676. Aival-Naveh E, Rothschild-Yakar L, Kurman J: Keeping culture in mind: A systematic review and initial conceptualization of mentalizing from a cross-cultural perspective . Clinical Psychology: Science and Practice 2019, 26 (4):e12300. Fekih-Romdhane F, Alhuwailah A, Sakr F, Chaibi LS, Helmy M, Shuwiekh HAM, Boudouda NE, Zarrouq B, Naser AY, Jebreen K: A twelve-country population-based psychometric validation study of the Arabic version of the Social Pain Questionnaire (SPQ) . 2024. Van Widenfelt BM, Treffers PD, De Beurs E, Siebelink B, Koudijs E, Siebelink BM: Translation and cross-cultural adaptation of assessment instruments used in psychological research with children and families . Clinical Child & Family Psychology Review 2005, 8 (2). Fenn J, Tan C-S, George S: Development, validation and translation of psychological tests . BJPsych Advances 2020, 26 (5):306-315. Mundfrom DJ, Shaw DG, Ke TL: Minimum sample size recommendations for conducting factor analyses . International journal of testing 2005, 5 (2):159-168. Hu Lt, Bentler PM: Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives . Structural equation modeling: a multidisciplinary journal 1999, 6 (1):1-55. Chen FF: Sensitivity of goodness of fit indexes to lack of measurement invariance . Structural equation modeling: a multidisciplinary journal 2007, 14 (3):464-504. Vadenberg R, Lance C: A review and synthesis of the measurement in variance literature: Suggestions, practices, and recommendations for organizational research . Organ Res Methods 2000, 3 :4-70. Hair Jr JF, Sarstedt M, Ringle CM, Gudergan SP: Advanced issues in partial least squares structural equation modeling : saGe publications; 2017. Clutterbuck RA, Livingston LA, Shah P: The Four-Item Mentalising Index (FIMI) is a valid, reliable, and practical way to assess mentalising: Reply to Murphy et al.(2022) . 2022. Asher M, Asnaani A, Aderka IM: Gender differences in social anxiety disorder: A review . Clinical psychology review 2017, 56 :1-12. Loomes R, Hull L, Mandy WPL: What is the male-to-female ratio in autism spectrum disorder? A systematic review and meta-analysis . Journal of the American Academy of Child & Adolescent Psychiatry 2017, 56 (6):466-474. Livingston LA, Carr B, Shah P: Recent advances and new directions in measuring theory of mind in autistic adults . Journal of Autism and Developmental Disorders 2019, 49 :1738-1744. Additional Declarations No competing interests reported. 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18:16:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4870250/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4870250/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63514807,"identity":"9c3518ed-99e1-4a46-bd18-b514589aa260","added_by":"auto","created_at":"2024-08-29 04:15:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53141,"visible":true,"origin":"","legend":"\u003cp\u003eStandardised estimates of factor loadings of the Four-Item Mentalising Index\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4870250/v1/871963371afde013544fc09f.png"},{"id":67493387,"identity":"eb603e1a-090b-421d-8dac-81752c86f9c2","added_by":"auto","created_at":"2024-10-25 15:17:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1800955,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4870250/v1/43982a5a-6cdf-4b8a-bddf-1928640510a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Four-Item Mentalising Index (FIMI): A multinational validation of the Arabic version in 12 countries","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMentalising (or mentalisation) refers to \u0026ldquo;the ability to understand one\u0026rsquo;s own and others\u0026rsquo; mental states, thereby comprehending one\u0026rsquo;s own and others\u0026rsquo; intentions and affects\u0026rdquo; ([\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], p.1). This ability can be regarded as a metacognitive process [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] which enables an individual to interpret one own\u0026rsquo;s or others\u0026rsquo; behaviors through attributions of mental states (i.e., emotions, thoughts, beliefs, intentions, wishes) that might underlie these behaviors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Mentalizing is thought to be related to, but potentially distinct from, the concept of \u0026ldquo;theory of mind\u0026rdquo;, as the former focuses more specifically on affective and cognitive mental states in the context of emotional arousal [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], whereas the latter reflects \u0026ldquo;epistemic states\u0026rdquo; such as intentions, beliefs and persuasions ([\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], p.730). Mentalizing constitutes an important determinant of mental health [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It is recognized as a core element for healthy personality development and social cognition, as it plays a major role in one\u0026rsquo;s ability to feel/express empathy, to communicate, to regulate emotions and impulse control, to experience well-being, as well as in entertaining relationships and overall interpersonal functioning [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As such, a lack or deficiency in mentalizing ability was shown to be significantly linked to a range of psychopathology, such as psychotic disorders [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] - including at the early stages of disease progression [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]-, bipolar disorders [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], Major depressive disorders [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], eating disorders [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], borderline personality disorder [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and substance use disorders [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Mentalising deficits has also been found to be involved in the psychological functioning within a range of psychiatric conditions, including autism and psychosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In light of these findings, researchers have recently turned to mentalising in an attempt to provide a better understanding and more efficacious treatments for severe, yet poorly understood and inadequately managed diseases such as schizophrenia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], or dual diagnosis personality disorder and substance use disorder [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, measuring and exploring mentalising abilities should be considered a growing need for both clinicians and researchers involved in these psychiatric disorders\u0026rsquo; diagnosis, management and rehabilitation.\u003c/p\u003e\n\u003ch3\u003eMeasurement tools of mentalising\u003c/h3\u003e\n\u003cp\u003eSeveral measurement instruments are currently available to assess mentalising, but no benchmark or gold standard measure exists. The existing measures can be classified based on their nature and the targeted population group. For instance, there are interview-based tools specifically designed for use among older adolescents (aged 16 years and over) and adults, such as the Metacognition Assessment Scale [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and the Reflective Functioning Scale [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Other tools consist of narrative-based or task-based measures that were developed to be used among children and/or young adolescents, such as the Mentalizing Stories for Adolescents [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] or the Affect Task [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Although these measures have proven to be psychometrically sound, their administration requires dedicated time and trained personnel during a clinical session [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A good alternative to overcome these limitations could be mentalising measures based on self-report. Examples of self-administered measures include the 33-item Multidimensional Mentalizing Questionnaire [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the 22-item Mentalising Imbalances Scale [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the 20-item Interactive Mentalizing Questionnaire [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and the 15-item Mentalising Questionnaire [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile these measures have the major advantage of being self-report without the problems inherent in interviewer-administered measures, they can be time-consuming to administer with their many items, making them less suitable for use in highly specialized clinical contexts and large-scale, multi-time-point studies involving large samples. In addition, most of them were mainly designed as clinical screening instruments to be used in clinical rather than community populations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Furthermore, several previous mentalising measures were of questionable validity, as they often had untested or poor psychometric characteristics. Moreover, there have been concerns about what construct it is really meant to be evaluated, as some tools claim to measure mentalising, whereas other concepts such as emotion processing are actually being measured [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Other tools combined and conflated many constructs, including mentalising, empathy and emotion perception [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In an effort to address these limitations, Clutterbuck et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] developed the Four-Item Mentalising Index (FIMI), a self-report scale aimed specifically assessing the mentalising construct while simplifying its conceptual complexity, and enabling its use in applied clinical and research settings.\u003c/p\u003e\n\u003ch3\u003eThe FIMI\u003c/h3\u003e\n\u003cp\u003eThe FIMI was designed to selectively measure mentalising abilities in community adults [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The FIMI is composed of the following four items: (1) \u0026ldquo;I find it easy to put myself in somebody else\u0026rsquo;s shoes\u0026rdquo;, (2) \u0026ldquo;I sometimes find it difficult to see things from other people\u0026rsquo;s point of view\u0026rdquo;, (3) \u0026ldquo;I sometimes try to understand my friends better by imagining how things look from their perspective\u0026rdquo;, and (4) \u0026ldquo;I can usually understand another person\u0026rsquo;s viewpoint, even if it differs from my own \u0026lsquo;\u0026rsquo;. Through a series of studies investigating its psychometric properties in both clinical (i.e. autistic) and non-clinical English-speaking adults from the US and UK, the FIMI was demonstrated to be methodologically and conceptually a robust measure to assess mentalising abilities in the adult population. In particular, the FIMI showed a solid unidimensional factor structure, and data supported its internal consistency reliability, measurement invariance by sex, test-retest reliability, and construct validity of its scores against autistic traits, a cognitive mentalising task, and comparing scores in non-autistic and autistic individuals [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. More recently, the FIMI was adapted, translated and validated to the German language in 283 German-speaking adults from Germany, Austria, and Switzerland [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The German version showed adequate psychometric properties in terms of factor structure, inner consistency, and relationships with relevant validity criteria (including autistic traits) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, no previous studies examining the psychometric properties of the FIMI in the Arabic language could be found in the literature.\u003c/p\u003e\n\u003ch3\u003eRationale and aim of this study\u003c/h3\u003e\n\u003cp\u003eOur study was motivated by some key needs. First, despite a sizeable amount of research literature has been undertaken on mentalising in children, much less attention has been devoted to exploring mentalising in adulthood [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Second, no studies have yet examined mentalising in adults from Arab countries as far as we know, which may be explained by the lack of locally validated instrument to measure this construct in the Arabic-speaking adult population. Studying mentalising in general population adults is crucial to the understanding of social-cognitive changes that occur as one ages [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and to gain knowledge on clinical phenomena that are characterised by mentalising problems, such as autism [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Third, a meta-analysis showed that the conceptualization of mentalising can differ between cultures (e.g., self\u0026thinsp;\u0026lt;\u0026thinsp;other mentalising in collectivistic cultures such as Arab societies, self\u0026thinsp;\u0026gt;\u0026thinsp;other mentalising in individualistic cultures such as Western societies) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which emphasizes the strong need to make available mentalising measures that are appropriate for different cultural contexts. Therefore, this study aimed to investigate the psychometric properties of an Arabic translation of the FIMI in a multi-national sample of non-clinical adults. Following the English and German versions of the FIMI, we hypothesise that the Arabic FIMI will yield a single-factor solution, as well a good internal consistency reliability and adequate construct validity. In addition, it is anticipated that the factor structure will show measurement invariance across sex and country.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and procedure\u003c/h2\u003e \u003cp\u003eThe current study is part of the \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eM\u003c/span\u003eultinational \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003eutism \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eP\u003c/span\u003eroject (\u0026ldquo;MAP\u0026rdquo;) of the Arab world (more details about the project can be found in [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]). The study has a cross-sectional design. An online anonymous questionnaire was launched during the period from February to April 2024. Invitations to take part in the study were sent to potential participants via several social media platforms, such as Facebook, WhatsApp, Instagram and TikTok, using snowball sampling. Eligible participants were adults aged 18 years and over from the general population of 12 Arab countries: Algeria, Bahrain, Egypt, Iraq, Jordan, Kingdom of Saudi Arabia, Kuwait, Lebanon, Morocco, Oman, Palestine, Tunisia. Participation was on a voluntary basis and no compensation was offered. Those who gave their informed consent to participate in the first section of the questionnaire were then redirected to the rest of the questionnaire.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic information\u003c/h2\u003e \u003cp\u003eSociodemographic data collected included sex (male, female), age, educational level (elementary, middle, secondary, university), household crowding index (i.e. the number of persons divided by the number of rooms in the house except the kitchen and bathrooms; with higher scores reflecting worse socioeconomic status).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eThe FIMI\u003c/h2\u003e \u003cp\u003eThe FIMI was rigorously translated and culturally adapted for the Arabic environment and language. The translation and adaptation processes ensured that the meaning of the four items remained consistent with that of the original version according to the international norms [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The forward translation and backward translation of the FIMI was performed. Initially, the FIMI was translated from English to Arabic by a translator who was not involved in the research. Then, the backward translation was completed by a health professional who is fluent in English and familiar with the terminology of the area covered by the instrument. This approach was adopted to ensure the conceptual equivalence of each item. Afterwards, both the original and the back-translated English versions were compared by a panel of experts composed of the translators, the research team, two psychiatrists, and one psychologist, in order to resolve any inconsistencies and confirm the accuracy of the translation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A pilot study was then conducted to ensure that items are clear and easily interpreted. No further adjustments were required, and the translation was examined and confirmed by one of the original authors of the instrument (Professor Punit Shah).\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eThe Autism-Spectrum Quotient-28 (AQ-28)\u003c/h2\u003e \u003cp\u003eThe Arabic validated version of the AQ-28 was used in this study [52], which conceptually replicated one of the validation studies conducted by Clutterbuck et al. in the original development of the FIMI. The AQ-28 showed a Cronbach α of .91 in the present sample. The AQ-28 is a self-report scale which measures ATs via 28 items and five factors : (1) Difficulties with imagination (e.g., \u0026ldquo;I find it difficult to work out people\u0026rsquo;s intentions\u0026rdquo;), (2) Difficulties with social skills (e.g., \u0026ldquo;I find it hard to make new friends\u0026rdquo;), (3) Preference for routine (e.g., \u0026ldquo;New situations make me anxious\u0026rdquo;), (4) Attention switching difficulties (e.g., \u0026ldquo;I find it easy to do more than one thing at once\u0026rdquo;), and (5) Fascination for numbers/patterns (e.g., \u0026ldquo;I notice patterns in things all the time\u0026rdquo;) [61]. Items are scored on a 4-point Likert scale, with \u0026ldquo;Slightly agree\u0026rdquo;/ \u0026ldquo;Definitely agree\u0026rdquo; scoring 1 and \u0026ldquo;Slightly disagree\u0026rdquo;/ \u0026ldquo;Definitely disagree\u0026rdquo; scoring 0. Fifteen items are reverse scored. Total scores range from 0 to 28, with greater scores reflecting higher levels of ATs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalytic Strategy\u003c/h2\u003e \u003cp\u003e \u003cb\u003eData treatment.\u003c/b\u003e There were no missing responses in the dataset. To examine the factor structure of the FIMI, we conducted a Confirmatory Factor Analysis using the data from the total sample via SPSS AMOS v.29 software. A minimum sample varying between 12\u0026ndash;80 participants was deemed necessary to conduct a confirmatory factor analysis following a recommendation between 3\u0026ndash;20 times the number of the scale\u0026rsquo;s variables [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Parameter estimates were obtained using the maximum likelihood method. Calculated fit indices were the root mean square error of approximation (RMSEA), the Tucker-Lewis Index (TLI) and the comparative fit index (CFI). Values\u0026thinsp;\u0026le;\u0026thinsp;.08 for RMSEA, and .95 for CFI and TLI indicate good fit of the model to the data [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Multivariate normality was not verified at first (Critical ratio\u0026thinsp;\u0026gt;\u0026thinsp;5; Bollen-Stine \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.002); therefore, we performed non-parametric bootstrapping procedure.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurement invariance.\u003c/b\u003e To examine gender and country invariance of FIMI scores, we conducted multi-group CFA [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] using the total sample. Measurement invariance was assessed at the configural, metric, and scalar levels [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. We accepted ΔCFI\u0026thinsp;\u0026le;\u0026thinsp;.010 and ΔRMSEA\u0026thinsp;\u0026le;\u0026thinsp;.015 or ΔSRMR\u0026thinsp;\u0026le;\u0026thinsp;.010 as evidence of invariance [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], Comparison between males and females was done using the Student \u003cem\u003et\u003c/em\u003e-test only if scalar or partial scalar invariance. ANOVA test was used to compare scores between countries.\u003c/p\u003e \u003cp\u003eComposite reliability in both subsamples was assessed using McDonald\u0026rsquo;s ω and Cronbach\u0026rsquo;s alpha, with values greater than .70 reflecting adequate composite reliability. Normality of the FIMI score was verified since the skewness and kurtosis values for each item of the scale varied between \u0026minus;\u0026thinsp;1 and +\u0026thinsp;1 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. To assess concurrent validity, Pearson test was used to correlate FIMI scores with the other scales.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf potential participants contacted, 8,408 successfully answered the survey questionnaire and were included in the final analysis. Participants\u0026rsquo; mean age was 24.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.44 years, and 74.5% were females. The description of participants\u0026rsquo; characteristics by country can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics of the participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOman (n\u0026thinsp;=\u0026thinsp;433)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIraq (n\u0026thinsp;=\u0026thinsp;488)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSaudi Arabia (n\u0026thinsp;=\u0026thinsp;342)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJordan (n\u0026thinsp;=\u0026thinsp;452)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePalestine (n\u0026thinsp;=\u0026thinsp;455)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEgypt (n\u0026thinsp;=\u0026thinsp;1177)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAlgeria (n\u0026thinsp;=\u0026thinsp;534)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLebanon (n\u0026thinsp;=\u0026thinsp;1076)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMorocco (n\u0026thinsp;=\u0026thinsp;456)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBahrain (n\u0026thinsp;=\u0026thinsp;419)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eTunisia (n\u0026thinsp;=\u0026thinsp;1119)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eKuwait (n\u0026thinsp;=\u0026thinsp;1448)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;8408)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.31\u0026thinsp;\u0026plusmn;\u0026thinsp;7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.23\u0026thinsp;\u0026plusmn;\u0026thinsp;9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.85\u0026thinsp;\u0026plusmn;\u0026thinsp;8.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.90\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.79\u0026thinsp;\u0026plusmn;\u0026thinsp;8.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.90\u0026thinsp;\u0026plusmn;\u0026thinsp;11.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23.48\u0026thinsp;\u0026plusmn;\u0026thinsp;11.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24.34\u0026thinsp;\u0026plusmn;\u0026thinsp;7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e24.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (24.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82 (18.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e135 (25.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e389 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e119 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e102 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e324 (29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e357 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2145 (25.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325 (75.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e340 (69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e267 (78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e292 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e373 (82.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1031 (87.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e399 (74.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e687 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e346 (74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e317 (75.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e795 (71.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1091 (75.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6263 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e123 (23.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e190 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e60 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e68 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e80 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e154 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e848 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e391 (90.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e481 (98.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e286 (83.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e421 (93.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e435 (95.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1160 (98.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e411 (77.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e886 (82.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e405 (87.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e351 (83.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1039 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1294 (89.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7560 (89.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.77\u0026thinsp;\u0026plusmn;\u0026thinsp;.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e10.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003eHCI\u0026thinsp;=\u0026thinsp;Household Crowding Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eConfirmatory Factor Analysis of the FIMI scale\u003c/h2\u003e \u003cp\u003eCFA indicated that fit of the one-factor model of FIMI scores was excellent: RMSEA\u0026thinsp;=\u0026thinsp;.035 (90% CI .023, .048), SRMR\u0026thinsp;=\u0026thinsp;.012, CFI\u0026thinsp;=\u0026thinsp;.996, TLI\u0026thinsp;=\u0026thinsp;.989. The standardised estimates of factor loadings were all adequate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Internal reliability was good (ω\u0026thinsp;=\u0026thinsp;.68; α\u0026thinsp;=\u0026thinsp;.65).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement invariance by sex and countries\u003c/h2\u003e \u003cp\u003eIndices suggested that configural, metric, and scalar invariance was supported across sex (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A significantly higher mean FIMI score was found in females (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.73, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.22) compared to males (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.37, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.27) in the total sample, \u003cem\u003et\u003c/em\u003e(8406) = -6.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e \u003cp\u003eA significant difference in terms of FIMI scores was found between countries, F(11, 8396)\u0026thinsp;=\u0026thinsp;47.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The post-hoc Bonferroni analysis showed a significant difference between Oman and Egypt (p\u0026thinsp;=\u0026thinsp;.001), Oman and Algeria (p\u0026thinsp;=\u0026thinsp;.011), Oman and Morocco (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Oman and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Iraq and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Iraq and Kuwait (p\u0026thinsp;=\u0026thinsp;.002), Saudi Arabia and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Saudi Arabia and Kuwait (p\u0026thinsp;=\u0026thinsp;.004), Jordan and Egypt (p\u0026thinsp;=\u0026thinsp;.002), Jordan and Algeria (p\u0026thinsp;=\u0026thinsp;.015), Jordan and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Palestine and Lebanon (p\u0026thinsp;=\u0026thinsp;.010), Palestine and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Palestine and Kuwait (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Egypt and Lebanon (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Egypt and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Egypt and Kuwait (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Algeria and Lebanon (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Algeria and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Algeria and Kuwait (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Lebanon and Morocco (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Lebanon and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Morocco and Jordan (p\u0026thinsp;=\u0026thinsp;.001), Morocco and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Morocco and Kuwait (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Bahrain and Tunisia (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Bahrain and Kuwait (p\u0026thinsp;=\u0026thinsp;.011), and Tunisia and Kuwait (p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eMeasurement Invariance across sex and countries in the total sample.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel Comparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eΔCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eΔRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eΔSRMR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1: sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConfigural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConfigural vs metric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMetric vs scalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 2: Countries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConfigural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConfigural vs metric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMetric vs scalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e CFI\u0026thinsp;=\u0026thinsp;Comparative fit index; RMSEA\u0026thinsp;=\u0026thinsp;Steiger-Lind root mean square error of approximation; SRMR\u0026thinsp;=\u0026thinsp;Standardised root mean square residual.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eConcurrent validity\u003c/h2\u003e \u003cp\u003eHigher total autism scores (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.21), difficulties with social skills (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.03), preference for routine (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.10), difficulties with imagination (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.25) and fascination for numbers/patterns (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.10) were significantly associated with lower FIMI scores (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson correlation matrix.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. FIMI scores\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. AQ-28 - Difficulties with social skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.03**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. AQ-28 - Preference for routine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.10***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.20***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. AQ-28 - Attention switching difficulties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.28***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.15***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. AQ-28 - Difficulties with imagination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.25***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.11***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.13***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.16***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. AQ-28 - Fascination for numbers/patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.10***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.08***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.09***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.20***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.09***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. AQ-28 total scores\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.21***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.63***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.51***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.46***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.54***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.36***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFIMI: the Four-Item Mentalising Index; AQ-28: the Autism-Spectrum Quotient-28.\u003c/p\u003e \u003cp\u003e**p\u0026thinsp;\u0026lt;\u0026thinsp;.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe lack of sound measures to assess mentalising in Arabic-speaking adults is a significant gap that can substantially constrain understanding of the expression and difficulties in the mentalising processes across the lifespan in the Arab world, and of the cross-cultural. This also can hinder the current understanding of the cross-cultural validity and generalizability of the mentalising concept. This study proposes to validate the Arabic version of the FIMI in a multicountry sample of community adults. The FIMI was chosen to be validated into the Arabic language because of its briefness, conceptual clarity and psychometric validity [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Findings showed that the scale is unidimensional, valid and reliable. This study also tested and supported the measurement invariance of the Arabic FIMI across both sex and country groups.\u003c/p\u003e \u003cp\u003eStructurally, our finding strengthens support for the unidimensional model of the mentalising construct initially proposed by Clutterbuck et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and supported later in the German validation study by Bertrams et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The investigation of factorial structure in our sample allows to ensure that the interpretation of total FIMI scores is appropriate and meaningful, and that the scale genuinely assesses the mentalising ability construct it intends to assess. Altogether, previous findings along with our results suggest that the factor structure of the FIMI is not much under cross-cultural variations, but is rather universal. Additionally, internal consistency reliability of the Arabic FIMI was satisfactory, with a Cronbach\u0026rsquo;s alpha of .65 and a McDonald\u0026rsquo;s omega of .68. Likewise, both the English-language [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and the German-language [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] versions of the FIMI showed acceptable-to-good internal consistency, with a McDonald\u0026rsquo;s omega of .75 and .82, respectively.\u003c/p\u003e \u003cp\u003eFurthermore, the results of the CFA indicated that the FIMI fit the data well and in similar ways across the twelve countries, as well as for both males and females. Measurement invariance is considered a prerequisite to soundness comparisons of mean levels across the sexes, and across individuals originating from and residing in different countries and cultural backgrounds. This finding can help to address the relevant question of whether clinical (e.g., with social anxiety disorder [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] or autism [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]) and non-clinical males and females are subject to differences in social cognition and behaviors. Similarly, the developers of the original English version of the FIMI were able to establish measurement invariance across sex in both a large community sample of adults and in university students [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Also, the German version of the FIMI was found to be invariant to sex. It is of note that the German validation did not investigate this psychometric property, and that, overall, there is only very little evidence available on sex-based measurement invariance of mentalising measures [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Higher mean FIMI scores were found in females compared to males, which is consistent with previous findings among both English-speaking [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and German-speaking [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] adults. The measurement invariance of the FIMI across country groups is an especially important and valuable result of the current study, as the majority (or all) previous measures of mentalising lack such cross-cultural validity. Given that mentalising processes can be susceptible to cultural and contextual variation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], establishing psychometric equivalence of the FIMI across various Arab countries may enable accurate comparisons of the concept between individuals from different nations and help further understanding of how profiles of mentalising can vary across cultures.\u003c/p\u003e \u003cp\u003eFinally, correlational analyses provided support for construct validity of the Arabic-language version of the FIMI, by showing significant positive correlations between mentalising and self-reported autistic traits scores. This result concurs with the strong theoretical and empirical evidence indicating that mentalising difficulties represent a consistent feature of autism [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and further supports the utility and relevance of the FIMI for clinical and research practices. The original validation study of the FIMI also observed significant links between the FIMI and autism, and showed the ability of the scale to measure clinically meaningful mentalising differences, as well as to discriminate between autistic and non-autistic individuals [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Additionally, Bertrams et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found significant correlations between the German version of the FIMI and different aspects of autistics traits as measured using the AQ-28. Overall, we report a coherent pattern of validation results that aligns with previous research in multiple languages.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe main strengths of our study are that it included a very large sample of community adults from 12 Arab nations of different regions (e.g., North Africa versus Middle East) and cultural backgrounds (e.g., Gulf versus non-Gulf), and it used a validated measure (the Arabic AQ-28) to assess construct validity. At the same time however, there are some limitations in this study\u0026rsquo;s methodology that could have affected the interpretation and generalizability of findings. First, only community adults were involved. The validity, reliability and applicability of the Arabic FIMI should be further evaluated in clinical samples with various psychiatric conditions and across different settings. Second, the study did not assess the test-retest reliability of the Arabic FIMI, which would have provided additional information about the stability of the measure over time. Third, future research may incorporate other measures, such as other \u0026ldquo;objective\u0026rdquo; mentalising tasks, to further examine validity of the Arabic FIMI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePractical implications\u003c/h2\u003e \u003cp\u003eThere has been an increasing acknowledgement within the scientific community of the importance of the value of assessing mentalizing through a succinct, valid, reliable, and cost-effective tool such as the FIMI in clinical and research settings. In the present study, we demonstrate that the Arabic version of the FIMI has good psychometric qualities allowing to reliably assess \u0026lsquo;subjective\u0026rsquo; mentalising in Arabic-speaking adults. The FIMI is concise enough to be administered alongside other survey instruments, and yet sufficiently robust to be used as an independent measurement of mentalising. These are major assets that can have important practical implications, especially in the low-middle income Arab countries where clinicians and researchers often work under time pressure and resources constraints. Offering a psychometrically sound measure of mentalising may raise awareness among clinicians and researchers of the possibilities to easily, reliably and accurately assess mentalising in order to enable the development, testing and monitoring of tailored Mentalising-based treatments aimed at addressing impaired mentalising and managing a range of mental disorders in Arab settings. Finally, the Arabic FIMI will hopefully prompt future research on quantifying individual differences in mentalising difficulties in Arabic-speaking populations, which can further our understanding of how mentalising ability may overlap with other social-cognitive constructs, such as empathy.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study is the first to our knowledge to validate a measure of mentalising, i.e. the FIMI, in the Arabic language. Clinicians and researchers working in Arab settings would benefit from the Arabic version of the FIMI as a brief, valid, reliable and easy-to-administer self-report measure of mentalising. Beyond its practical usefulness in Arab contexts, such a measure could also provide important theoretical impetus for understanding the expression and clinical correlates of mentalising strengths and difficulties in adults across different cultures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate.\u0026nbsp;\u003c/strong\u003eThe protocol was approved by the home institutions of the study's principal investigators (FFR and SH), namely the ethics committee of Razi Psychiatric Hospital, Manouba, Tunisia (ECRPH-2024-032) and the Lebanese International University's School of Pharmacy ethics committee (2024ERC-025-LIUSOP). When filling out the online form, each participant provided written informed consent. All methods were performed in accordance with the relevant guidelines and regulations (in accordance with the Declaration of Helsinki).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication:Not applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eBecause of ethical committee constraints, none of the data collected or analyzed during this study are publicly available. However, the corresponding author (SH) may make the data available upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u0026nbsp;The authors have nothing to disclose.\u003c/p\u003e\n\u003cp\u003eFunding:None.\u003c/p\u003e\n\u003cp\u003eAuthor contributions:FFR and SH designed the study; FFR drafted the manuscript; SH carried out the analysis and interpreted the results; FS, AA, LSC, MH, HAMS, NEB, BZ, AYN, KJ, MLR, NM, RA, BARH, AHM, SSF, OAA, and MD collected the data; MC, DM, SO, PS and AMA reviewed the paper for intellectual content; all authors reviewed the final manuscript and gave their consent.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:The authors would like to thank all participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eVandenBos GR: \u003cstrong\u003eAPA dictionary of psychology\u003c/strong\u003e: American Psychological Association; 2018.\u003c/li\u003e\n \u003cli\u003eWyl A: \u003cstrong\u003eMentalisierung und Theory of Mind\u003c/strong\u003e. \u003cem\u003ePraxis der Kinderpsychologie und Kinderpsychiatrie\u0026nbsp;\u003c/em\u003e2014, \u003cstrong\u003e63\u003c/strong\u003e(9):730-737.\u003c/li\u003e\n \u003cli\u003eFonagy P, Allison E: \u003cstrong\u003eWhat is mentalization?: The concept and its foundations in developmental research\u003c/strong\u003e. 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A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eJournal of the American Academy of Child \u0026amp; Adolescent Psychiatry\u0026nbsp;\u003c/em\u003e2017, \u003cstrong\u003e56\u003c/strong\u003e(6):466-474.\u003c/li\u003e\n \u003cli\u003eLivingston LA, Carr B, Shah P: \u003cstrong\u003eRecent advances and new directions in measuring theory of mind in autistic adults\u003c/strong\u003e. \u003cem\u003eJournal of Autism and Developmental Disorders\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e49\u003c/strong\u003e:1738-1744.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mentalising, Four-Item Mentalising Index, FIMI, Psychometric properties, Validation, Arabic.","lastPublishedDoi":"10.21203/rs.3.rs-4870250/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4870250/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The lack of sound measures to assess mentalising in Arabic-speaking adults is a significant gap that can substantially constrain understanding of the expression and difficulties in the mentalising processes across the lifespan in the Arab world, and of the cross-cultural. Therefore, this study aimed to investigate the psychometric properties of an Arabic translation of the FIMI in a multi-national sample of non-clinical adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA sample of 8,408 adults (74.5% females, mean age 24.70 ± 8.44 years) from the general population of twelve Arab countries was surveyed to examine the psychometric properties of the Arabic FIMI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e CFA indicated that fit of the one-factor model of FIMI scores was excellent: RMSEA = .035 (90% CI .023, .048), SRMR = .012, CFI = .996, TLI = .989, and had adequate internal consistency reliability (ω = .68; α = .65). Indices suggested that configural, metric, and scalar invariance was supported across sex and country groups. Finally, correlational analyses provided support for construct validity of the Arabic-language version of the FIMI, by showing significant positive correlations between mentalising and self-reported autistic traits scores.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Findings suggest that the Arabic FIMI is valid, reliable ad suitable for use among Arabic-speaking adults. The scale may raise awareness among clinicians and researchers of the possibilities to easily and accurately assess mentalising in order to enable the development, testing and monitoring of tailored Mentalising-based treatments aimed at addressing impaired mentalising and managing a range of mental disorders in Arab settings.\u003c/p\u003e","manuscriptTitle":"The Four-Item Mentalising Index (FIMI): A multinational validation of the Arabic version in 12 countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-29 04:15:19","doi":"10.21203/rs.3.rs-4870250/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e006af4a-4651-48be-92b3-f1f6e1660d47","owner":[],"postedDate":"August 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-25T15:08:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-29 04:15:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4870250","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4870250","identity":"rs-4870250","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}