Development of the Cyberchondria Severity Scale in Pregnancy (CSS-P)

Development of the Cyberchondria Severity Scale in Pregnancy (CSS-P) | 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 Development of the Cyberchondria Severity Scale in Pregnancy (CSS-P) Esra ÖZER, Gulten GUVENC This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8386754/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Feb, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 14 You are reading this latest preprint version Abstract Objective With the increase in internet use during pregnancy, many women frequently search for information about their own health and their baby's health from online sources. However, excessive and repetitive online health searches can increase anxiety and lead to cyberchondria. There is no pregnancy-specific measurement tool to assess the severity of cyberchondria in pregnant women. This study was conducted to develop the Pregnancy Cyberchondria Severity Scale (PCSS) and evaluate its psychometric properties. Methods The study was conducted in three phases: (1) creation of the item pool, (2) preliminary evaluation of the items, and (3) refinement of the scale and evaluation of its psychometric properties. Instrument development guidelines were used to assess the content validity, construct validity, internal consistency, and stability over time of the instrument. Data were collected between August 2025 and December 2025 to evaluate the psychometric properties of the CSS-P. Results Exploratory factor analysis revealed that the CSS-P consists of 5 factors and 21 items explaining 65.27% of the total variance. Confirmatory factor analysis revealed that the proposed model showed an excellent level of fit (GFI = 0.943; CFI = 0.994; TLI = 0.993; RMSEA = 0.024; 90% CI: 0.007–0.036). Cronbach's alpha coefficients for the total score and subscales of the scale were above 0.90. The parallel test method was used to evaluate the correlation between the CSS-P and the cyberchondria severity scale. The findings showed that the CSS-P has high internal consistency and stability over time. Conclusion CSS-P is a valid and reliable measure in terms of its psychometric properties. The 21-item scale consists of five factors: Difficulty in Controlling, Impairment in Daily Life, Compulsive Online Searching Behavior, Distrust of Online Information, and Anxiety. Impact CSS-P can be used in clinical practice to identify pregnant women with excessive and maladaptive online health search behavior and to evaluate the effectiveness of interventions aimed at supporting healthier information-seeking behaviors during pregnancy. Pregnancy Maternal Health Information Seeking Behavior Internet Use Psychometrics Cyberchondria Figures Figure 1 Figure 2 Figure 3 Introduction Cyberchondria is defined as a multidimensional phenomenon characterized by an individual's online health information search behavior that increases rather than reduces anxiety and takes on a repetitive, difficult-to-control pattern. This structure includes dimensions such as excessive and compulsive online searching, perceived excessiveness, distress, constant reassurance seeking, and distrust of health professionals [1, 2]. Empirical studies show that higher levels of cyberchondria are positively associated with health anxiety, intolerance of uncertainty, and obsessive-compulsive symptoms; they may also be linked to increased healthcare utilization, impaired functioning, and reduced quality of life [3]. The rapid proliferation of digital technologies and the constant availability of smartphones and the internet have made cyberchondria an increasingly important public health issue [2] . Pregnancy is a special period characterized by intense biological, psychological, and social changes, increased information needs, and heightened susceptibility to anxiety. The literature indicates that pregnant women frequently use the internet for topics such as fetal development, pregnancy complications, lifestyle recommendations, and the birth process; searching for online health information is quite common during pregnancy [4, 5]. While internet use can have positive outcomes in some cases, such as preparedness, increased knowledge, and a strengthened sense of control, exposure to conflicting, unreliable, or alarming content can increase uncertainty and anxiety, and may exacerbate the emotional burden, particularly in high-risk pregnancies [6, 7] . Recent studies have shown that online health information-seeking behavior during pregnancy can reach levels of cyberchondria in some women and may have clinically significant effects on pregnancy-related anxiety, fear of childbirth, and overall mental well-being. Research conducted in different countries has shown that the severity of cyberchondria in pregnant women is positively associated with pregnancy-related anxiety, health anxiety, intolerance of uncertainty, and fear of childbirth [8, 9]. In high-risk pregnancies, cyberchondria has also been found to be associated with symptoms of depression and generalized anxiety; it has been suggested that repetitive and anxiety-laden online searches focused on pregnancy complications may deepen existing psychological vulnerability [6]. Furthermore, it has been determined that health anxiety and e-health literacy in women predict cyberchondria; pregnant women with high health anxiety and low digital information literacy may be particularly prone to interpreting online content in a more threatening manner [10] . However, most existing studies evaluating cyberchondria in pregnancy use the Cyberchondria Severity Scale (CSS) and its short forms, which were initially developed for general adult or student populations [1, 2, 11]. Although the CSS has been adapted into different languages and has demonstrated strong psychometric properties in various samples [12, 13], the original form of the scale was not designed to systematically capture pregnancy-specific themes. Therefore, in studies addressing cyberchondria during pregnancy, CSS scores are mostly used as an indirect indicator of pregnancy-related cyberchondria; however, pregnancy-specific dimensions such as concerns about fetal health, repeated checking for signs of miscarriage or premature birth, overinterpretation of fetal movements, or the impact of online content on obstetric decision-making and interactions with healthcare professionals cannot be clearly distinguished [8, 14] . Theoretical and empirical studies show that cyberchondria is a context-sensitive phenomenon; it is influenced by factors such as perceived disease severity, personal vulnerability, social meaning, and role expectations [2, 15]. Pregnancy is characterized by high perceived risk for the mother and fetus, constant physiological changes, and intense social discourse and information overload regarding "normal" and "risky" conditions, thus presenting a unique context for cyberchondria. Pregnant women frequently compare healthcare professionals' recommendations with online content, compare their symptoms with other women's experiences, and seek a "second opinion" online regarding screening tests, medication use, or mode of delivery [5, 16]. These dynamics may cause repetitive searching, reassurance seeking, and distress patterns during pregnancy to take a different form compared to non-pregnant populations. However, to date, there is no psychometrically valid and reliable measurement tool developed to assess the severity of cyberchondria specific to pregnancy and fetal health. The development of a pregnancy-specific cyberchondria scale could meet an important need in both research and clinical practice. Such an instrument could: (i) more accurately determine the prevalence and risk profiles of cyberchondria in pregnancy according to trimesters, risk groups, and levels of care, (ii) allow for a more detailed examination of relationships with constructs such as pregnancy-related anxiety, fear of childbirth, general health anxiety, and e-health literacy, and (iii) contribute to the development of interventions targeting safe internet use, coping with uncertainty, and digital coping strategies in antenatal care. In this context, this study aims to develop the Cyberchondria Severity Scale in Pregnancy (CSS-P) and examine its psychometric properties in order to assess the severity of cyberchondria specific to pregnancy and fetal health. Methods This study is a methodological tool development research aimed at developing a new scale for measuring levels of cyberchondria during pregnancy, called the Cyberchondria Severity Scale for Pregnancy (CSS-P), and psychometrically evaluating the scale's content validity, factor structure, construct validity, and reliability. Study design The CSS-P scale was developed through a three-stage process: (1) creation of the item pool, (2) preliminary evaluation of the items, and (3) refinement of the scale and assessment of its psychometric properties. In developing the CSS- P, the methodological guidelines proposed by DeVellis (2021) and Carpenter (2018) for scale development were followed [17, 18] (Fig. 1 ). Phase 1. Generating the item pool A comprehensive literature review and interviews were used to prepare the draft form of the Cyberchondria Severity Scale in Pregnancy (CSS-P). In the first phase, a systematic search was conducted in the MEDLINE/PubMed, Scopus, Web of Science, PsycINFO, and Google Scholar databases using the keywords "pregnancy," "cyberchondria," "online health information seeking," "internet use," "health anxiety," and "pregnancy-related anxiety." Frequently used expressions regarding cyberchondria in pregnancy were employed, such as pregnant women searching for health information online, repeatedly checking their symptoms, and the anxiety and uncertainty they experience during this process. In the next phase, in-depth face-to-face interviews were conducted with 20 pregnant women using a semi-structured interview method. The qualitative data collected during the interviews were analyzed using content analysis. The item pool was created based on the interviews and the guidelines suggested in the literatüre [19, 20] . During the item pool creation phase, researchers independently reviewed candidate items, considering the components of cyberchondria defined in the literature: repetitive searching, increased anxiety, seeking reassurance, time loss, and pregnancy-specific themes such as concern about fetal health, exaggerated interpretation of pregnancy symptoms, and fear of childbirth and complications. Key statements directly reflecting the level of cyberchondria were identified, and their explicit and implicit meanings were analyzed; statements representing emotions, thoughts, and behaviors associated with cyberchondria in pregnancy were converted into draft items. The researchers held five meetings to decide on the items to be included in the item pool, and candidate items were evaluated within the framework of the basic definition of situations and behaviors that increase the severity of cyberchondria during pregnancy. Repeated, ambiguous, or statements that did not sufficiently reflect the structure to be measured were eliminated. In the next step of the process, the scope, clarity, and cultural appropriateness of the items were reviewed by experts in the fields of gynecology and obstetrics, midwifery, psychiatry, and measurement and evaluation; accordingly, some items were combined, simplified, or restructured. While developing the items, ambiguous, double-meaning, negative, and leading expressions were avoided; each item was formulated clearly and concisely to reflect a single idea, and a 5-point Likert-type response format was adopted. Phase 2. Preliminary evaluation of the items Expert opinion Expert opinion was obtained from 11 experts in the fields of gynecology and obstetrics nursing, psychiatric nursing, measurement and evaluation, statistics, and linguistics. The Davis method was used to analyze content validity. The item-content validity index (I-CVI) was calculated for each item, and the scale-content validity index (S-CVI) was calculated for the entire instrument. According to this method, I- CVI and S-CVI should be at least 0.80 in newly developed instruments [21]. The experts made minor suggestions for revision, particularly regarding the linguistic fluency and comprehensibility of some items for pregnant women; in line with these suggestions, the wording of several items was simplified, but no items were removed from the scale at this stage. Pilot study The draft form was administered to pregnant women during face-to-face interviews. Participants were asked to first complete the draft form and then evaluate it in terms of comprehensibility, readability, and content of the responses. They were also asked to provide suggestions for improvement, including commenting on any difficulties they encountered in completing the scale and indicating any additional item statements they thought were missing or items that should be deleted [22, 23]. No issues requiring the removal of any items from the scale were identified in the pilot study; the final draft form of the CSS-P at this stage was prepared for use in the psychometric evaluation phase with all items retained. The final form consisted of 31 items. Phase 3. Refining the PREG-QL and evaluating psychometric properties Item reduction The performance of each item was evaluated by calculating the adjusted total item correlation coefficient [24] . Construct Validity Exploratory factor analysis (EFA) ( n = 330) and confirmatory factor analysis (CFA) ( n = 330) were conducted to assess construct validity [25]. The Kaiser-Meyer-Olkin (KMO) coefficient and Bartlett's sphericity test were used to assess the suitability of the data before performing EFA[26]. The number of factors was determined by the scree plot and an eigenvalue greater than 1. Principal Axis Factoring (PAF) and promax rotation were used to determine the factor structure of the CSS-P with EFA [27]. For item selection, items with factor loadings below 0.30, high loadings on more than one factor, cross-loaded items, items with a difference between two factor loadings less than 0.10, and items with eigenvalues less than 0.40 were identified for elimination [17] . The factorial structure obtained from AFA was tested in an independent second sample using DFA. Model fit in DFA was assessed using the chi-square statistic (χ²), degrees of freedom (df), χ²/df ratio, goodness-of-fit index (GFI), comparative fit index (CFI), Tucker–Lewis index (TLI), and root mean square error of approximation (RMSEA 90%Cl). The overall adequacy of the model was examined by considering whether the fit indices met the limits recommended in the construct validity literature. Following DFA, a parallel test method was used to assess the correlation between the CSS-P and CSS-12 scales. As a dimension of construct validity, the correlation between CSS-12, which measures concepts related to CSS-P total and subscale scores, was examined, and convergent validity was supported by relationships in the theoretically expected direction and magnitude. Reliability The internal consistency of the scale was assessed using Cronbach's alpha coefficient. The test-retest method was used to verify the scale's stability over time. Fifteen days after the initial application, the CSS-P was reapplied to 40 pregnant women with similar characteristics to the sample, and the intraclass correlation coefficient (ICC) was calculated. Setting and sample Sample size has been a controversial issue in instrument development studies, and there is no universally accepted idea about the size of the sample population [28]. Insufficient sample size can lead to instability of factors and prevent generalization. A large data set is required to evaluate the factorial structure of instruments [29]. The common view regarding sample size in scale development studies is that approximately 10 participants per item is sufficient. However, there are also recommendations for absolute sample sizes independent of the number of items. Accordingly, 50 participants are considered "very poor," 100 "poor," 200 "moderate," 300 "good," 500 "very good," and a sample size of 1000 or more is considered "excellent" [30]. An appropriate sample size is a prerequisite for developing an instrument with strong psychometric properties. Each stage of our study was conducted on different samples. Twenty pregnant women participated in the pilot study, 330 pregnant women participated in the exploratory factor analysis, and 330 pregnant women participated in the confirmatory factor analysis; a total of 660 pregnant women were included in the study. Data collection The study was conducted at a state university's research and application hospital. In-depth interviews were conducted during the creation of the item pool. Pregnant women were informed about the purpose and scope of the study. The interviews were conducted with volunteer participants at a convenient time and place and were recorded with a voice recorder. The interviews lasted approximately 28 minutes. During the stages where the scale's factorial structure and psychometric properties were evaluated, the researcher visited pregnant women in the obstetrics department, provided information about the purpose and scope of the study, and asked the volunteer participants to complete the CSS-P. The scale administered to participating pregnant women was completed and collected by the researcher in approximately 15–20 minutes. Data were collected between August 2025 and December 2025. Data analysis IBM SPSS version 24.0 was used to evaluate the data obtained from the study, and AMOS version 26 was used for CFA data analysis. Qualitative data obtained from the interviews were evaluated using content analysis. Descriptive analysis used frequency, percentage, mean, and standard deviation. Content validity was assessed using Davis' (1992) method and I-CVI and S-CVI were calculated. Item quality was assessed using the item-total correlation coefficient. Construct validity was assessed using EFA, CFA, and parallel test methods. Factor validity was tested using the chi-square goodness-of-fit test, GFI, RMSEA, TLI, and CFI. Internal consistency was assessed using Cronbach's α coefficient, and the test-retest method (ICC) was calculated to assess the scale's stability over time. Results General characteristics of participants Participants' ages and body mass indices (BMI) ranged from 18 to 43 (mean = 27.3, SD = 4.47) and 18 to 40 (mean = 28.6, SD = 4.12), respectively. Furthermore, 37.9% of participants were in their first trimester, 42.4% had experienced one pregnancy in total, 35.8% were high school graduates, and 36.3% had an income equal to their expenses (Table 1 ). Table 1 General characteristics of the participants Variables Item pool generation (n = 20) M ± SD or n (%) Pilot study (n = 20) M ± SD or n (%) EFA and internal consistency (n = 330) M ± SD or n (%) CFA (n = 230) M ± SD or n (%) Temporal stability (n = 40) M ± SD or n (%) Age 28.6 ± 4.52 27.8 ± 4.23 27.3 ± 4.47 28.4 ± 5.38 28.9 ± 5.78 BMI 27.5 ± 3.81 28.3 ± 4.36 28.6 ± 4.12 28.2 ± 4.31 27.2 ± 4.42 Pregnancy Trimester First Trimester 8 (40) 5 (25) 125 (37.9) 50 (21.5) 10 (25) Second Trimester 5 (20) 7 (35) 90 (27.3) 97 (41.8) 16 (40) Third Trimester 7 (35) 8 (40) 115 (34.8) 83 (36.7) 14 (35) Gravida 1 10 (50) 8 (40) 140 (42.4) 92 (40) 8 (20) 2 5 (25) 6 (30) 100 (30.3) 80 (35) 14 (35) ≥ 3 5 (25) 6 (30) 90 (27.3) 58 (25) 18 (45) Education ≤ Secondary School 3 (15) 4 (20) 102 (30.9) 116 (49.9) 8 (20) High School 6 (30) 6 (30) 118 (35.8) 66 (28.5) 14 (35) University 11 (55) 10 (50) 110 (33.3) 48 (21.6) 18 (45) Income level (monthly) Income lower than expenses 3 (15) 4 (20) 112 (33.9) 92 (39.6) 6 (15) Income equal to expenses 7 (35) 7 (35) 120 (36.3) 56 (25.1) 14 (35) Income higher than expenses 10 (50) 9 (45) 98 (29.8) 82 (35.3) 20 (50) Abbreviations: CFA, confirmatory factor analysis; EFA, exploratory factor analysis; M, mean; SD, standard deviation. Content validity Expert opinions were obtained from 11 experts in the fields of statistics, linguistics, obstetrics and gynecology nursing, psychiatric nursing, and measurement and evaluation using the Davis method. I-CVI scores ranged from 0.91 to 1.00, while S-CVI was found to be 0.98. Item reduction Items with item-total correlation coefficients ≤ 0.30 were re-evaluated [17]. The item-total correlation coefficients of the 21 items ranged from 0.42 to 0.94. Exploratory factor analysis The KMO coefficient (0.90) and Bartlett's sphericity test (χ2 = 10188.19, df = 179, p < .001) indicated that the data were suitable for factor analysis. The scree plot and the criterion of eigenvalues greater than 1 were used to determine the number of factors. The scree plot showed that the eigenvalues of the six factors were greater than 1 and that the eigenvalues decreased significantly after the sixth factor. The findings indicated that the CSS-P had a six-factor model. Nine items with cross-loadings or factor loadings below 0.30 and eigenvalues below 0.30 were removed using AFA to obtain a robust factor structure. After removing these items, the recalculated AFA revealed a five-factor CSS-P consisting of 21 items. The factor loadings of the CSS-P ranged from 0.42 to 0.94. The first factor consisted of 5 items (25, 26, 27, 28, 30), the second factor consists of 4 items (19, 20, 21, 22), the third factor consists of 4 items (1, 2, 3, 4), the fourth factor consists of 4 items (13, 14, 15, 16), and the fifth factor consists of 4 items (7, 8, 9, 10). These five factors explain 65.27% of the total variance. The variances explained by each factor were found to be 28.06%, 11.34%, 9.99%, 9.83%, and 8.81%, respectively (Table 2 ). Table 2 EFA and reliability analysis of CSS-P (n = 330) Factor loadings Mean SD Eigenvalue Explained variance (%) Cronbach's alpha Factor 1: Difficulty in Controlling Item_25: I find it difficult to limit my online research about my pregnancy. 0.91 2.91 1.45 8.42 28.06 0.925 Item_26: I constantly find myself checking my pregnancy symptoms online and cannot stop myself. 0.92 2.92 1.43 Item_27: It is very difficult for me to resist the urge to research my pregnancy online. 0.93 2.88 1.45 Item_28: Even if I try to reduce my research on pregnancy-related information, I lose control. 0.93 2.91 1.42 Item_30: I usually exceed the time limit I set for myself before starting to research pregnancy-related information online. 0.42 3.11 1.40 Factor 2: Disruption in Daily Life Item_19: Researching pregnancy-related health information online interferes with my daily tasks. 0.92 2.99 1.42 3.40 11.34 0.972 Item_20: I waste too much time researching my pregnancy concerns online. 0.92 2.97 1.40 Item_21: Researching pregnancy information online sometimes reduces the time I spend with my spouse or family. 0.92 2.93 1.41 Item_22: When I research pregnancy symptoms online, I neglect other important tasks. 0.91 2.95 1.40 Factor 3: Compulsive Online Searching Behavior Item_1: I can't stop researching health information related to my pregnancy on the internet. 0.92 3.01 1.37 2.99 9.99 0.973 Item_2: I feel the need to check my pregnancy symptoms online several times a day. 0.92 3.03 1.35 Item_3: Searching for health information related to my pregnancy on the internet is a daily routine for me. 0.93 3.03 1.41 Item_4: I feel a strong urge to research every symptom that concerns me about my pregnancy online. 0.92 2.98 1.41 Factor 4: Distrust of Online Information Item_13: I often doubt the accuracy of online health information related to pregnancy. 0.92 3.02 1.38 2.95 9.83 0.974 Item_14: The information I read online about pregnancy seems contradictory to me. 0.92 3.02 1.41 Item_15: When I find different information about my pregnancy on different websites, I don't know what to believe. 0.92 3.03 1.40 Item_16: The information I find online about pregnancy symptoms confuses me rather than reassuring me. 0.94 3.04 1.41 Factor 5: Anxiety Item_7: After researching my pregnancy symptoms online, I usually become more anxious. 0.92 2.91 1.42 2.64 8.81 0.974 Item_8: When I read about a pregnancy issue online, I feel like I have it too. 0.93 2.90 1.43 Item_9: The information I read online about pregnancy complications makes me very anxious. 0.91 2.84 1.43 Item_10: When I research health information related to pregnancy online, I often panic about my baby's health. 0.92 2.92 1.45 TOTAL CSS-P 65.27 0.916 K-MO-= 0.90, Bartlett's Test Statistic = 10188.191, p < 0.001 Confirmatory factor analysis The 5 factors and 21 items proposed by AFA were tested using CFA. Modification indices were evaluated to improve model fit. Bivariate correlations analyzed for bivariate items did not exceed 0.90. Tukey's test of non-aggregability was performed to evaluate the aggregability of the scale. A non-aggregatable p-value below 0.50 ( p < .50) indicates that the scale is not aggregatable. Modification indices were reviewed, and no additional model adjustments were made as the model fit indices met the recommended threshold values. Since cyberchondria in pregnancy is theoretically accepted as a multidimensional construct, a first-order five-factor model was tested for the CSS-P. Considering the content of the items, the factors were named to reflect different dimensions of cyberchondria in pregnancy. These factors are, respectively, difficulty in controlling, disruption in daily life, compulsive online searching behavior, distrust of online information, and anxiety. The fit indices of the five-factor model revealed that the model fit the data perfectly (χ² = 213.89, p = 0.038, χ²/df = 1.20, GFI = 0.943, CFI = 0.994, TLI = 0.993, RMSEA = 0.024, 90% CI: 0.006–0.036) (Table 3 ). Table 3 Factor loadings and indices of fit for the CSS-P (n = 330) Factors CSS-P Factor loadings CSS-P Items 1 2 3 4 5 Factor 1: Difficulty in Controlling CSS-P1: I find it difficult to limit my online research about my pregnancy. 0.84 CSS-P2: I constantly find myself checking my pregnancy symptoms online and cannot stop myself. 0.83 CSS-P3: It is very difficult for me to resist the urge to research my pregnancy online. 0.88 CSS-P4: Even if I try to reduce my research on pregnancy-related information, I lose control. 0.83 CSS-P5: I usually exceed the time limit I set for myself before starting to research pregnancy-related information online. 0.82 Factor 2: Disruption in Daily Life CSS-P6: Researching pregnancy-related health information online interferes with my daily tasks. 0.85 CSS-P7: I waste too much time researching my pregnancy concerns online. 0.87 CSS-P8: Researching pregnancy information online sometimes reduces the time I spend with my spouse or family. 0.88 CSS-P9: When I research pregnancy symptoms online, I neglect other important tasks. 0.84 Factor 3: Compulsive Online Searching Behavior CSS-P10: I can't stop researching health information related to my pregnancy on the internet. 0.83 CSS-P11: I feel the need to check my pregnancy symptoms online several times a day. 0.86 CSS-P12: Searching for health information related to my pregnancy on the internet is a daily routine for me. 0.87 CSS-P13: I feel a strong urge to research every symptom that concerns me about my pregnancy online. 0.86 Factor 4: Distrust of Online Information CSS-P14: I often doubt the accuracy of online health information related to pregnancy. 0.84 CSS-P15: The information I read online about pregnancy seems contradictory to me. 0.84 CSS-P16: When I find different information about my pregnancy on different websites, I don't know what to believe. 0.83 CSS-P17: The information I find online about pregnancy symptoms confuses me rather than reassuring me. 0.87 Factor 5: Anxiety CSS-P18: After researching my pregnancy symptoms online, I usually become more anxious. 0.85 CSS-P19: When I read about a pregnancy issue online, I feel like I have it too. 0.85 CSS-P20: The information I read online about pregnancy complications makes me very anxious. 0.86 CSS-P21: When I research health information related to pregnancy online, I often panic about my baby's health. 0.86 Fit index X 2 df ( p ) X 2 / df GFI CFI RMSEA (%90 CI) TLI Model of CSS-P 213.889 179 (< 0.038) 1.206 0.943 0.994 0.024 0.993 Reference value Acceptable 0.90 > 0.90 0.90 Good 0.95 > 0.95 0.95 Abbreviations: χ², chi-square statistic; df, degrees of freedom; GFI, goodness-of-fit index; CFI, comparative fit index; TLI, Tucker–Lewis index; RMSEA, root mean square error of approximation; CI, confidence interval. Parallel test method The correlation between the CSS-P and CSS scales was calculated using the parallel test method. The analysis showed that the correlation coefficients were statistically significant ( p < .001) and positive at a moderate to high level (Table 4 ). Table 4 Analysis of the relationship between the dimensions of the CSS-P and the CSS-12 Extremism Distress Search for Security Forcing Factor 1: Difficulty in Controlling r .586 .560 .482 .543 p < 0.001 < 0.001 < 0.001 < 0.001 Factor 2: Disruption in Daily Life r .520 .503 .234 .644 p < 0.001 < 0.001 < 0.001 < 0.001 Factor 3: Compulsive Online Searching Behavior r 0.242 .463 .217 .357 p < 0.001 < 0.001 < 0.001 < 0.001 Factor 4: Distrust of Online Information r .253 .238 .213 .542 p < 0.001 < 0.001 < 0.001 < 0.001 Factor 5: Anxiety r .384 .486 .322 .453 p < 0.001 < 0.001 < 0.001 < 0.001 Reliability analysis The Cronbach α coefficients for the five factors were found to be 0.925, 0.972, 0.973, 0.974, and 0.974, respectively. The Cronbach α value for CSS-P was found to be 0.916. The test-retest method was used to evaluate the stability of CSS-P over time. The CSS-P was administered twice to 40 pregnant women at 15-day intervals. The ICC was calculated to compare the scores obtained from the test and retest. The ICC scores for difficulty in controlling, disruption in daily life, compulsive online searching behavior, distrust of online information, and anxiety were 0.93 (95% CI = 0.88–0.95, p < .001), 0.88 (95% CI = 0.81–0.93, p < .001), 0.91 (95% CI = 0.85–0.94, p < .001), 0.85 (95% CI = 0.74–0.90, p < .001), and 0.90 (95% CI = 0.83–0.94, p < .001), respectively (Table 5 ). Table 5 Intraclass correlation coefficient of the CSS-P (n = 40) 95% CI First application M (SD) Second application M (SD) ICC Lower bound Upper bound p value Factor 1: Difficulty in Controlling 2.99 ± 0.92 3.11 ± 0.88 0.930 0.888 0.959 < 0.001 Factor 2: Disruption in Daily Life 3.07 ± 0.78 3.18 ± 0.92 0.886 0.814 0.934 < 0.001 Factor 3: Compulsive Online Searching Behavior 3.04 ± 0.65 3.10 ± 0.72 0.912 0.856 0.949 < 0.001 Factor 4: Distrust of Online Information 2.86 ± 0.52 2.94 ± 0.59 0.856 0.741 0.908 < 0.001 Factor 5: Anxiety 2.85 ± 0.49 2.92 ± 0.52 0.902 0.834 0.941 < 0.001 Abbreviations: CI, Confidence interval; ICC, intraclass correlation coefficient; M, mean; SD, standard deviation Final instrument CSS-P consists of 5 factors comprising 21 items: difficulty in controlling (5 items), disruption in daily life (4 items), compulsive online searching behavior (4 items), distrust of online information (4 items), and anxiety (4 items). The scale was developed to assess the severity of cyberchondria during pregnancy, and items are self-scored on a 5-point Likert-type scale. The scoring system is based on calculating the average scores for each factor, ranging from 1 to 5. High scores on the factors indicate high severity of cyberchondria during pregnancy (Appendix 1). Discussion Mental well-being and health behaviors during pregnancy have long been assessed primarily using pregnancy anxiety, health anxiety, or depression scales; however, these traditional approaches are insufficient to capture the specific dimensions of online health search behaviors related to pregnancy, which are becoming increasingly complex in the digital age [31, 32]. Today, a significant proportion of pregnant women turn to the internet before healthcare professionals for their initial concerns about fetal health and pregnancy; this process can result in information overload, uncertainty, and cycles of increased anxiety, potentially increasing the risk of cyberchondria [33]. Although general scales such as the Cyberchondria Severity Scale (CSS) and its short form CSS-12 exist to assess cyberchondria, they do not adequately reflect pregnancy-specific sources of anxiety, fears about obstetric outcomes, and the pregnancy-specific online information environment [1, 34]. No tool specifically designed to measure the severity of cyberchondria during pregnancy has been identified in the literature. This study provides evidence regarding the validity and reliability of the Cyberchondria Severity Scale in Pregnancy (CSS-P), developed to assess the severity of cyberchondria during pregnancy, thereby making important contributions to the systematic reporting, monitoring, and evaluation of digital health behaviors specific to the pregnancy period. Psychometric properties of the CSS-P The content validity of the CSS-P was assessed using the classification proposed by Davis (1992). I-CVI and S-CVI were above the acceptable lower limit (> 0.80)[35]. The scores indicated that the items adequately represented the construct. Although EFA is recommended first, followed by CFA, when analyzing content validity in scale development studies, conducting parallel tests can strengthen the validity of the measurement instrument [36]. In this study, the KMO coefficient (> 0.70) and Bartlett's sphericity test ( p < 0.001) indicated that the data were normally distributed and that the sample size was adequate for factor analysis [35] . EFA results showed that the total variance explained by the five-factor CSS-P was above the desired range for multi-factor scales (60%-70%) [37]. Eliminating factor loadings below 0.30 in the study improved the representativeness and variance levels of the instrument [17, 27]. CFA was conducted on a different sample, establishing a 5-factor structure (Fig. 2 , Fig. 3 ). Convergent validity, as measured by parallel test results, showed a medium to high level of positive correlation, indicating a statistically significant relationship between CSS-12 and CSS-P factors ( p < .001). These findings indicate that the five-factor structure of CSS-P is adequate. EFA, CFA, and parallel test results demonstrated that CSS-P is a valid instrument. The reliability of the scale was assessed using Cronbach's α coefficient and the test-retest method. Cronbach's α is recommended to be > 0.60 for factors and > 0.70 for the total instrument [28]. The Cronbach's α values for the CSS-P and its factors were above these thresholds. ICC results indicated that the instrument was stable over time [38]. These findings demonstrated that the CSS-P is a valid and reliable instrument. Scale content Scale content Developed to assess the severity of cyberchondria during pregnancy, the CSS-P consists of five factors: control difficulty, disruption to daily life, compulsive online search behavior, distrust of online information, and anxiety. These factors were designed as complementary domains reflecting the cognitive, emotional, and functional dimensions of health information search behavior on the internet during pregnancy and are consistent with the multidimensional structure of existing cyberchondria scales [1, 2] . Factor 1 is called control difficulty; items in this factor describe pregnant women's difficulty in stopping their online health searches, feeling the need to search for the same topics repeatedly, and experiencing a loss of self-control over their search behavior. This factor is consistent with findings from studies using CSS and CSS-12 that show compulsive and excessive online health search behavior is associated with health anxiety, increased distress, and impaired daily functioning [1, 11, 39]. This sub-dimension parallels studies demonstrating the relationship between cyberchondria and increased levels of pregnancy-related anxiety in pregnant women [6, 40] . Factor 2 is termed impairment in daily life. This factor emphasizes how online searches lead to time loss, distraction, and functional impairment in pregnant women's domestic responsibilities, work/school roles, and social relationships. Current studies on cyberchondria show that increased online search behavior is associated with impaired functioning, increased healthcare utilization, and decreased quality of life [2, 3] . Factor 3 is labeled as compulsive online search behavior; items in this domain describe a cyclical search pattern, such as pregnant women constantly browsing different websites and each new piece of information leading to new searches. This structure aligns with theoretical and empirical literature indicating that cyberchondria is characterized by compulsive online search cycles that perpetuate health anxiety rather than alleviating it [2, 11] . Factor 4 is termed distrust of online information. Items in this factor express that pregnant women experience increased confusion and loss of trust as they are exposed to conflicting, dramatized, or unreliable information on the internet. In cyberchondria studies, information overload and uncertainty about the reliability of online sources have been shown to increase health-related cognitive distortions, decision-making difficulties, and maladaptive coping behaviors [2, 41] . Finally, factor 5 is called anxiety; items in this factor describe increased anxiety about pregnancy and fetal health after online searches, fear of discovering new symptoms, and focusing on possible complications. Studies in pregnant women have shown that searching for health information online is associated with increased anxiety levels, pregnancy-specific concerns, and cyberchondria, particularly in complicated or high-risk pregnancies and in the presence of high health anxiety [6, 40] . Limitations This study has several limitations that should be considered when interpreting the findings and using the Pregnancy Cyberchondria Severity Scale (CSS-P). First, although the overall sample size was adequate for scale development and psychometric testing, all participants were selected from a single research and training hospital in Turkey. This single-center, convenience sampling strategy may limit the generalizability of the results to pregnant women receiving care in different geographic regions, health systems, or cultural contexts, and primarily to those using private or community-based services. This study relies solely on self-reported data collected through face-to-face administration. Since women in the perinatal period may be inclined to report 'appropriate' online health behaviors, the data may be subject to recall and social desirability biases. Furthermore, the scope of cyberchondria and related conditions may be limited as they are not validated by objective measures such as digital trace data. Finally, although robust evidence has been obtained for factor structure, internal consistency, test-retest reliability, and convergent validity with the Cyberchondria Severity Scale, some important psychometric properties have not been examined. Measure invariance across key subgroups (e.g., trimester, parity, high-risk and low-risk pregnancy, education level, and e-health literacy) has not been tested. Conclusion This three-phase study demonstrated that the newly developed Pregnancy Cyberchondria Severity Scale (CSS-P) is a valid and reliable tool. This 21-item tool consists of five factors: control difficulties (5 items), disruption in daily life (4 items), compulsive online search behavior (4 items), distrust of online information (4 items), and anxiety (4 items). With its good psychometric properties, the CSS-P can be used in clinical and research settings to assess the severity of cyberchondria during pregnancy in a multidimensional manner and to monitor the digital health behaviors of pregnant women. Abbreviations CSS-P: Pregnancy Cyberchondria Severity Scale χ², chi-square statistic; df, degrees of freedom; p, probability value; χ²/df, chi-square divided by degrees of freedom; GFI, goodness-of-fit index; CFI, comparative fit index; TLI, Tucker–Lewis index; RMSEA, root mean square error of approximation; CI, confidence interval. Declarations Acknowledgements We would like to thank all the pregnant women who participated in this study. Funding The authors declare no financial support. Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Contributions E.Ö. conceived the study, participated in study design, performed data analysis, drafted the manuscript and reviewed the manuscript. G.G. participated in study design and reviewed the manuscript. All authors read and approved the final manuscript. Ethical statements Ethical approval and consent to participate This study was approved by the Non-Interventional Ethics Committee of Ankara Medipol University (decision no: E-85859696-604.01.01-5763, Number: 142). Pregnant women who agreed to participate in the study were included. Informed consent was obtained from all participants. The consent form provided information to the pregnant women about the purpose of the study. All personal information will be kept confidential. The study was conducted in accordance with the Declaration of Human Rights. Consent for publication Not applicable. No identifying images or personal clinical information of participants are included in this manuscript. 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Hansen, M.H., et al., Worries and information seeking during pregnancy: a cross-sectional study among 1402 expectant Norwegian women active on social media platforms. Scandinavian Journal of Primary Health Care, 2025. 43(2): p. 488-499. Yang, X., et al., Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions. Telematics and Informatics, 2025. 97: p. 102225. Additional Declarations No competing interests reported. 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This structure includes dimensions such as excessive and compulsive online searching, perceived excessiveness, distress, constant reassurance seeking, and distrust of health professionals [1, 2]. Empirical studies show that higher levels of cyberchondria are positively associated with health anxiety, intolerance of uncertainty, and obsessive-compulsive symptoms; they may also be linked to increased healthcare utilization, impaired functioning, and reduced quality of life [3]. The rapid proliferation of digital technologies and the constant availability of smartphones and the internet have made cyberchondria an increasingly important public health issue [2] .\u003c/p\u003e \u003cp\u003ePregnancy is a special period characterized by intense biological, psychological, and social changes, increased information needs, and heightened susceptibility to anxiety. The literature indicates that pregnant women frequently use the internet for topics such as fetal development, pregnancy complications, lifestyle recommendations, and the birth process; searching for online health information is quite common during pregnancy [4, 5]. While internet use can have positive outcomes in some cases, such as preparedness, increased knowledge, and a strengthened sense of control, exposure to conflicting, unreliable, or alarming content can increase uncertainty and anxiety, and may exacerbate the emotional burden, particularly in high-risk pregnancies [6, 7] .\u003c/p\u003e \u003cp\u003eRecent studies have shown that online health information-seeking behavior during pregnancy can reach levels of cyberchondria in some women and may have clinically significant effects on pregnancy-related anxiety, fear of childbirth, and overall mental well-being. Research conducted in different countries has shown that the severity of cyberchondria in pregnant women is positively associated with pregnancy-related anxiety, health anxiety, intolerance of uncertainty, and fear of childbirth [8, 9]. In high-risk pregnancies, cyberchondria has also been found to be associated with symptoms of depression and generalized anxiety; it has been suggested that repetitive and anxiety-laden online searches focused on pregnancy complications may deepen existing psychological vulnerability [6]. Furthermore, it has been determined that health anxiety and e-health literacy in women predict cyberchondria; pregnant women with high health anxiety and low digital information literacy may be particularly prone to interpreting online content in a more threatening manner [10] .\u003c/p\u003e \u003cp\u003eHowever, most existing studies evaluating cyberchondria in pregnancy use the Cyberchondria Severity Scale (CSS) and its short forms, which were initially developed for general adult or student populations [1, 2, 11]. Although the CSS has been adapted into different languages and has demonstrated strong psychometric properties in various samples [12, 13], the original form of the scale was not designed to systematically capture pregnancy-specific themes. Therefore, in studies addressing cyberchondria during pregnancy, CSS scores are mostly used as an indirect indicator of pregnancy-related cyberchondria; however, pregnancy-specific dimensions such as concerns about fetal health, repeated checking for signs of miscarriage or premature birth, overinterpretation of fetal movements, or the impact of online content on obstetric decision-making and interactions with healthcare professionals cannot be clearly distinguished [8, 14] .\u003c/p\u003e \u003cp\u003eTheoretical and empirical studies show that cyberchondria is a context-sensitive phenomenon; it is influenced by factors such as perceived disease severity, personal vulnerability, social meaning, and role expectations [2, 15]. Pregnancy is characterized by high perceived risk for the mother and fetus, constant physiological changes, and intense social discourse and information overload regarding \"normal\" and \"risky\" conditions, thus presenting a unique context for cyberchondria. Pregnant women frequently compare healthcare professionals' recommendations with online content, compare their symptoms with other women's experiences, and seek a \"second opinion\" online regarding screening tests, medication use, or mode of delivery [5, 16]. These dynamics may cause repetitive searching, reassurance seeking, and distress patterns during pregnancy to take a different form compared to non-pregnant populations. However, to date, there is no psychometrically valid and reliable measurement tool developed to assess the severity of cyberchondria specific to pregnancy and fetal health.\u003c/p\u003e \u003cp\u003eThe development of a pregnancy-specific cyberchondria scale could meet an important need in both research and clinical practice. Such an instrument could: (i) more accurately determine the prevalence and risk profiles of cyberchondria in pregnancy according to trimesters, risk groups, and levels of care, (ii) allow for a more detailed examination of relationships with constructs such as pregnancy-related anxiety, fear of childbirth, general health anxiety, and e-health literacy, and (iii) contribute to the development of interventions targeting safe internet use, coping with uncertainty, and digital coping strategies in antenatal care. In this context, this study aims to develop the Cyberchondria Severity Scale in Pregnancy (CSS-P) and examine its psychometric properties in order to assess the severity of cyberchondria specific to pregnancy and fetal health.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study is a methodological tool development research aimed at developing a new scale for measuring levels of cyberchondria during pregnancy, called the Cyberchondria Severity Scale for Pregnancy (CSS-P), and psychometrically evaluating the scale's content validity, factor structure, construct validity, and reliability.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThe CSS-P scale was developed through a three-stage process: (1) creation of the item pool, (2) preliminary evaluation of the items, and (3) refinement of the scale and assessment of its psychometric properties. In developing the CSS- P, the methodological guidelines proposed by DeVellis (2021) and Carpenter (2018) for scale development were followed [17, 18] (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePhase 1. Generating the item pool\u003c/h3\u003e\n\u003cp\u003eA comprehensive literature review and interviews were used to prepare the draft form of the Cyberchondria Severity Scale in Pregnancy (CSS-P). In the first phase, a systematic search was conducted in the MEDLINE/PubMed, Scopus, Web of Science, PsycINFO, and Google Scholar databases using the keywords \"pregnancy,\" \"cyberchondria,\" \"online health information seeking,\" \"internet use,\" \"health anxiety,\" and \"pregnancy-related anxiety.\" Frequently used expressions regarding cyberchondria in pregnancy were employed, such as pregnant women searching for health information online, repeatedly checking their symptoms, and the anxiety and uncertainty they experience during this process. In the next phase, in-depth face-to-face interviews were conducted with 20 pregnant women using a semi-structured interview method. The qualitative data collected during the interviews were analyzed using content analysis. The item pool was created based on the interviews and the guidelines suggested in the literat\u0026uuml;re [19, 20] .\u003c/p\u003e \u003cp\u003eDuring the item pool creation phase, researchers independently reviewed candidate items, considering the components of cyberchondria defined in the literature: repetitive searching, increased anxiety, seeking reassurance, time loss, and pregnancy-specific themes such as concern about fetal health, exaggerated interpretation of pregnancy symptoms, and fear of childbirth and complications. Key statements directly reflecting the level of cyberchondria were identified, and their explicit and implicit meanings were analyzed; statements representing emotions, thoughts, and behaviors associated with cyberchondria in pregnancy were converted into draft items. The researchers held five meetings to decide on the items to be included in the item pool, and candidate items were evaluated within the framework of the basic definition of situations and behaviors that increase the severity of cyberchondria during pregnancy. Repeated, ambiguous, or statements that did not sufficiently reflect the structure to be measured were eliminated. In the next step of the process, the scope, clarity, and cultural appropriateness of the items were reviewed by experts in the fields of gynecology and obstetrics, midwifery, psychiatry, and measurement and evaluation; accordingly, some items were combined, simplified, or restructured. While developing the items, ambiguous, double-meaning, negative, and leading expressions were avoided; each item was formulated clearly and concisely to reflect a single idea, and a 5-point Likert-type response format was adopted.\u003c/p\u003e\n\u003ch3\u003ePhase 2. Preliminary evaluation of the items\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eExpert opinion\u003c/h2\u003e \u003cp\u003eExpert opinion was obtained from 11 experts in the fields of gynecology and obstetrics nursing, psychiatric nursing, measurement and evaluation, statistics, and linguistics. The Davis method was used to analyze content validity. The item-content validity index (I-CVI) was calculated for each item, and the scale-content validity index (S-CVI) was calculated for the entire instrument. According to this method, I- CVI and S-CVI should be at least 0.80 in newly developed instruments [21]. The experts made minor suggestions for revision, particularly regarding the linguistic fluency and comprehensibility of some items for pregnant women; in line with these suggestions, the wording of several items was simplified, but no items were removed from the scale at this stage.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePilot study\u003c/h3\u003e\n\u003cp\u003eThe draft form was administered to pregnant women during face-to-face interviews. Participants were asked to first complete the draft form and then evaluate it in terms of comprehensibility, readability, and content of the responses. They were also asked to provide suggestions for improvement, including commenting on any difficulties they encountered in completing the scale and indicating any additional item statements they thought were missing or items that should be deleted [22, 23]. No issues requiring the removal of any items from the scale were identified in the pilot study; the final draft form of the CSS-P at this stage was prepared for use in the psychometric evaluation phase with all items retained. The final form consisted of 31 items.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePhase 3. Refining the PREG-QL and evaluating psychometric properties\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eItem reduction\u003c/h2\u003e \u003cp\u003eThe performance of each item was evaluated by calculating the adjusted total item correlation coefficient [24] .\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eConstruct Validity\u003c/h3\u003e\n\u003cp\u003eExploratory factor analysis (EFA) (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;330) and confirmatory factor analysis (CFA) (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;330) were conducted to assess construct validity [25]. The Kaiser-Meyer-Olkin (KMO) coefficient and Bartlett's sphericity test were used to assess the suitability of the data before performing EFA[26]. The number of factors was determined by the scree plot and an eigenvalue greater than 1. Principal Axis Factoring (PAF) and promax rotation were used to determine the factor structure of the CSS-P with EFA [27]. For item selection, items with factor loadings below 0.30, high loadings on more than one factor, cross-loaded items, items with a difference between two factor loadings less than 0.10, and items with eigenvalues less than 0.40 were identified for elimination [17] .\u003c/p\u003e \u003cp\u003eThe factorial structure obtained from AFA was tested in an independent second sample using DFA. Model fit in DFA was assessed using the chi-square statistic (χ\u0026sup2;), degrees of freedom (df), χ\u0026sup2;/df ratio, goodness-of-fit index (GFI), comparative fit index (CFI), Tucker\u0026ndash;Lewis index (TLI), and root mean square error of approximation (RMSEA 90%Cl). The overall adequacy of the model was examined by considering whether the fit indices met the limits recommended in the construct validity literature. Following DFA, a parallel test method was used to assess the correlation between the CSS-P and CSS-12 scales. As a dimension of construct validity, the correlation between CSS-12, which measures concepts related to CSS-P total and subscale scores, was examined, and convergent validity was supported by relationships in the theoretically expected direction and magnitude.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eReliability\u003c/h2\u003e \u003cp\u003eThe internal consistency of the scale was assessed using Cronbach's alpha coefficient. The test-retest method was used to verify the scale's stability over time. Fifteen days after the initial application, the CSS-P was reapplied to 40 pregnant women with similar characteristics to the sample, and the intraclass correlation coefficient (ICC) was calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSetting and sample\u003c/h2\u003e \u003cp\u003eSample size has been a controversial issue in instrument development studies, and there is no universally accepted idea about the size of the sample population [28]. Insufficient sample size can lead to instability of factors and prevent generalization. A large data set is required to evaluate the factorial structure of instruments [29]. The common view regarding sample size in scale development studies is that approximately 10 participants per item is sufficient. However, there are also recommendations for absolute sample sizes independent of the number of items. Accordingly, 50 participants are considered \"very poor,\" 100 \"poor,\" 200 \"moderate,\" 300 \"good,\" 500 \"very good,\" and a sample size of 1000 or more is considered \"excellent\" [30]. An appropriate sample size is a prerequisite for developing an instrument with strong psychometric properties. Each stage of our study was conducted on different samples. Twenty pregnant women participated in the pilot study, 330 pregnant women participated in the exploratory factor analysis, and 330 pregnant women participated in the confirmatory factor analysis; a total of 660 pregnant women were included in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThe study was conducted at a state university's research and application hospital. In-depth interviews were conducted during the creation of the item pool. Pregnant women were informed about the purpose and scope of the study. The interviews were conducted with volunteer participants at a convenient time and place and were recorded with a voice recorder. The interviews lasted approximately 28 minutes.\u003c/p\u003e \u003cp\u003eDuring the stages where the scale's factorial structure and psychometric properties were evaluated, the researcher visited pregnant women in the obstetrics department, provided information about the purpose and scope of the study, and asked the volunteer participants to complete the CSS-P. The scale administered to participating pregnant women was completed and collected by the researcher in approximately 15\u0026ndash;20 minutes. Data were collected between August 2025 and December 2025.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eIBM SPSS version 24.0 was used to evaluate the data obtained from the study, and AMOS version 26 was used for CFA data analysis. Qualitative data obtained from the interviews were evaluated using content analysis. Descriptive analysis used frequency, percentage, mean, and standard deviation. Content validity was assessed using Davis' (1992) method and I-CVI and S-CVI were calculated. Item quality was assessed using the item-total correlation coefficient. Construct validity was assessed using EFA, CFA, and parallel test methods. Factor validity was tested using the chi-square goodness-of-fit test, GFI, RMSEA, TLI, and CFI. Internal consistency was assessed using Cronbach's α coefficient, and the test-retest method (ICC) was calculated to assess the scale's stability over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eGeneral characteristics of participants\u003c/h2\u003e \u003cp\u003eParticipants' ages and body mass indices (BMI) ranged from 18 to 43 (mean\u0026thinsp;=\u0026thinsp;27.3, SD\u0026thinsp;=\u0026thinsp;4.47) and 18 to 40 (mean\u0026thinsp;=\u0026thinsp;28.6, SD\u0026thinsp;=\u0026thinsp;4.12), respectively. Furthermore, 37.9% of participants were in their first trimester, 42.4% had experienced one pregnancy in total, 35.8% were high school graduates, and 36.3% had an income equal to their expenses (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\u003eGeneral characteristics of the participants\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItem pool generation\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePilot study\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEFA and internal consistency (n\u0026thinsp;=\u0026thinsp;330)\u003c/p\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCFA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;230)\u003c/p\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTemporal stability\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePregnancy Trimester\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst Trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond Trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16 (40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThird Trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGravida\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100 (30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18 (45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le; Secondary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e116 (49.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e118 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18 (45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIncome level (monthly)\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncome lower than expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncome equal to expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56 (25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncome higher than expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20 (50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: CFA, confirmatory factor analysis; EFA, exploratory factor analysis; M, mean; SD, standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eContent validity\u003c/h2\u003e \u003cp\u003eExpert opinions were obtained from 11 experts in the fields of statistics, linguistics, obstetrics and gynecology nursing, psychiatric nursing, and measurement and evaluation using the Davis method. I-CVI scores ranged from 0.91 to 1.00, while S-CVI was found to be 0.98.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eItem reduction\u003c/h2\u003e \u003cp\u003eItems with item-total correlation coefficients\u0026thinsp;\u0026le;\u0026thinsp;0.30 were re-evaluated [17]. The item-total correlation coefficients of the 21 items ranged from 0.42 to 0.94.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eExploratory factor analysis\u003c/h2\u003e \u003cp\u003eThe KMO coefficient (0.90) and Bartlett's sphericity test (χ2\u0026thinsp;=\u0026thinsp;10188.19, df\u0026thinsp;=\u0026thinsp;179, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) indicated that the data were suitable for factor analysis. The scree plot and the criterion of eigenvalues greater than 1 were used to determine the number of factors. The scree plot showed that the eigenvalues of the six factors were greater than 1 and that the eigenvalues decreased significantly after the sixth factor. The findings indicated that the CSS-P had a six-factor model.\u003c/p\u003e \u003cp\u003eNine items with cross-loadings or factor loadings below 0.30 and eigenvalues below 0.30 were removed using AFA to obtain a robust factor structure. After removing these items, the recalculated AFA revealed a five-factor CSS-P consisting of 21 items. The factor loadings of the CSS-P ranged from 0.42 to 0.94. The first factor consisted of 5 items (25, 26, 27, 28, 30), the second factor consists of 4 items (19, 20, 21, 22), the third factor consists of 4 items (1, 2, 3, 4), the fourth factor consists of 4 items (13, 14, 15, 16), and the fifth factor consists of 4 items (7, 8, 9, 10). These five factors explain 65.27% of the total variance. The variances explained by each factor were found to be 28.06%, 11.34%, 9.99%, 9.83%, and 8.81%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eEFA and reliability analysis of CSS-P (n\u0026thinsp;=\u0026thinsp;330)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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 \u003cp\u003eFactor loadings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEigenvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExplained variance (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCronbach's alpha\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eFactor 1: Difficulty in Controlling\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_25: I find it difficult to limit my online research about my pregnancy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_26: I constantly find myself checking my pregnancy symptoms online and cannot stop myself.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.43\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_27: It is very difficult for me to resist the urge to research my pregnancy online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.45\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_28: Even if I try to reduce my research on pregnancy-related information, I lose control.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.42\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_30: I usually exceed the time limit I set for myself before starting to research pregnancy-related information online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.40\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 2: Disruption in Daily Life\u003c/b\u003e\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 \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_19: Researching pregnancy-related health information online interferes with my daily tasks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_20: I waste too much time researching my pregnancy concerns online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.40\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_21: Researching pregnancy information online sometimes reduces the time I spend with my spouse or family.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.41\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_22: When I research pregnancy symptoms online, I neglect other important tasks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.40\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 3: Compulsive Online Searching Behavior\u003c/b\u003e\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 \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_1: I can't stop researching health information related to my pregnancy on the internet.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_2: I feel the need to check my pregnancy symptoms online several times a day.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.35\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_3: Searching for health information related to my pregnancy on the internet is a daily routine for me.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.41\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_4: I feel a strong urge to research every symptom that concerns me about my pregnancy online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.41\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 4: Distrust of Online Information\u003c/b\u003e\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 \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_13: I often doubt the accuracy of online health information related to pregnancy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_14: The information I read online about pregnancy seems contradictory to me.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.41\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_15: When I find different information about my pregnancy on different websites, I don't know what to believe.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.40\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_16: The information I find online about pregnancy symptoms confuses me rather than reassuring me.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.41\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 5: Anxiety\u003c/b\u003e\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 \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_7: After researching my pregnancy symptoms online, I usually become more anxious.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_8: When I read about a pregnancy issue online, I feel like I have it too.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.43\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_9: The information I read online about pregnancy complications makes me very anxious.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.43\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eItem_10: When I research health information related to pregnancy online, I often panic about my baby's health.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.45\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" morerows=\"1\" nameend=\"c9\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTOTAL CSS-P\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e65.27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.916\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eK-MO-= 0.90, Bartlett's Test Statistic\u0026thinsp;=\u0026thinsp;10188.191, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eConfirmatory factor analysis\u003c/h2\u003e \u003cp\u003eThe 5 factors and 21 items proposed by AFA were tested using CFA. Modification indices were evaluated to improve model fit. Bivariate correlations analyzed for bivariate items did not exceed 0.90. Tukey's test of non-aggregability was performed to evaluate the aggregability of the scale. A non-aggregatable p-value below 0.50 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.50) indicates that the scale is not aggregatable. Modification indices were reviewed, and no additional model adjustments were made as the model fit indices met the recommended threshold values. Since cyberchondria in pregnancy is theoretically accepted as a multidimensional construct, a first-order five-factor model was tested for the CSS-P. Considering the content of the items, the factors were named to reflect different dimensions of cyberchondria in pregnancy. These factors are, respectively, difficulty in controlling, disruption in daily life, compulsive online searching behavior, distrust of online information, and anxiety. The fit indices of the five-factor model revealed that the model fit the data perfectly (χ\u0026sup2; = 213.89, p\u0026thinsp;=\u0026thinsp;0.038, χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.20, GFI\u0026thinsp;=\u0026thinsp;0.943, CFI\u0026thinsp;=\u0026thinsp;0.994, TLI\u0026thinsp;=\u0026thinsp;0.993, RMSEA\u0026thinsp;=\u0026thinsp;0.024, 90% CI: 0.006\u0026ndash;0.036) (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\u003eFactor loadings and indices of fit for the CSS-P (n\u0026thinsp;=\u0026thinsp;330)\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eCSS-P Factor loadings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P Items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eFactor 1: Difficulty in Controlling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P1: I find it difficult to limit my online research about my pregnancy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P2: I constantly find myself checking my pregnancy symptoms online and cannot stop myself.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P3: It is very difficult for me to resist the urge to research my pregnancy online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P4: Even if I try to reduce my research on pregnancy-related information, I lose control.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P5: I usually exceed the time limit I set for myself before starting to research pregnancy-related information online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\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\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eFactor 2: Disruption in Daily Life\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P6: Researching pregnancy-related health information online interferes with my daily tasks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85\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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P7: I waste too much time researching my pregnancy concerns online.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P8: Researching pregnancy information online sometimes reduces the time I spend with my spouse or family.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P9: When I research pregnancy symptoms online, I neglect other important tasks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eFactor 3: Compulsive Online Searching Behavior\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P10: I can't stop researching health information related to my pregnancy on the internet.\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 \u003cp\u003e0.83\u003c/p\u003e \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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P11: I feel the need to check my pregnancy symptoms online several times a day.\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 \u003cp\u003e0.86\u003c/p\u003e \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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P12: Searching for health information related to my pregnancy on the internet is a daily routine for me.\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 \u003cp\u003e0.87\u003c/p\u003e \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\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P13: I feel a strong urge to research every symptom that concerns me about my pregnancy online.\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 \u003cp\u003e0.86\u003c/p\u003e \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\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eFactor 4: Distrust of Online Information\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P14: I often doubt the accuracy of online health information related to pregnancy.\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 \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P15: The information I read online about pregnancy seems contradictory to me.\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 \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P16: When I find different information about my pregnancy on different websites, I don't know what to believe.\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 \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P17: The information I find online about pregnancy symptoms confuses me rather than reassuring me.\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 \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eFactor 5: Anxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P18: After researching my pregnancy symptoms online, I usually become more anxious.\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 \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P19: When I read about a pregnancy issue online, I feel like I have it too.\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 \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P20: The information I read online about pregnancy complications makes me very anxious.\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 \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCSS-P21: When I research health information related to pregnancy online, I often panic about my baby's health.\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 \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFit index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRMSEA (%90 CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel of CSS-P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179 (\u0026lt;\u0026thinsp;0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReference value\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcceptable\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 \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\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 \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eAbbreviations: χ\u0026sup2;, chi-square statistic; df, degrees of freedom; GFI, goodness-of-fit index; CFI, comparative fit index; TLI, Tucker\u0026ndash;Lewis index; RMSEA, root mean square error of approximation; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eParallel test method\u003c/h2\u003e \u003cp\u003eThe correlation between the CSS-P and CSS scales was calculated using the parallel test method. The analysis showed that the correlation coefficients were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and positive at a moderate to high level (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of the relationship between the dimensions of the CSS-P and the CSS-12\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExtremism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDistress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSearch for Security\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eForcing\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFactor 1: Difficulty in Controlling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFactor 2: Disruption in Daily Life\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFactor 3: Compulsive Online Searching Behavior\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFactor 4: Distrust of Online Information\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFactor 5: Anxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eReliability analysis\u003c/h2\u003e \u003cp\u003eThe Cronbach α coefficients for the five factors were found to be 0.925, 0.972, 0.973, 0.974, and 0.974, respectively. The Cronbach α value for CSS-P was found to be 0.916. The test-retest method was used to evaluate the stability of CSS-P over time. The CSS-P was administered twice to 40 pregnant women at 15-day intervals. The ICC was calculated to compare the scores obtained from the test and retest. The ICC scores for difficulty in controlling, disruption in daily life, compulsive online searching behavior, distrust of online information, and anxiety were 0.93 (95% CI\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;0.95, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), 0.88 (95% CI\u0026thinsp;=\u0026thinsp;0.81\u0026ndash;0.93, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), 0.91 (95% CI\u0026thinsp;=\u0026thinsp;0.85\u0026ndash;0.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), 0.85 (95% CI\u0026thinsp;=\u0026thinsp;0.74\u0026ndash;0.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and 0.90 (95% CI\u0026thinsp;=\u0026thinsp;0.83\u0026ndash;0.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIntraclass correlation coefficient of the CSS-P (n\u0026thinsp;=\u0026thinsp;40)\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\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst application\u003c/p\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond application\u003c/p\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLower bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUpper bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003cp\u003evalue\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\u003eFactor 1: Difficulty in Controlling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 2: Disruption in Daily Life\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 3: Compulsive Online Searching Behavior\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 4: Distrust of Online Information\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor 5: Anxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: CI, Confidence interval; ICC, intraclass correlation coefficient; M, mean; SD, standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eFinal instrument\u003c/h2\u003e \u003cp\u003eCSS-P consists of 5 factors comprising 21 items: difficulty in controlling (5 items), disruption in daily life (4 items), compulsive online searching behavior (4 items), distrust of online information (4 items), and anxiety (4 items). The scale was developed to assess the severity of cyberchondria during pregnancy, and items are self-scored on a 5-point Likert-type scale. The scoring system is based on calculating the average scores for each factor, ranging from 1 to 5. High scores on the factors indicate high severity of cyberchondria during pregnancy (Appendix 1).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMental well-being and health behaviors during pregnancy have long been assessed primarily using pregnancy anxiety, health anxiety, or depression scales; however, these traditional approaches are insufficient to capture the specific dimensions of online health search behaviors related to pregnancy, which are becoming increasingly complex in the digital age [31, 32]. Today, a significant proportion of pregnant women turn to the internet before healthcare professionals for their initial concerns about fetal health and pregnancy; this process can result in information overload, uncertainty, and cycles of increased anxiety, potentially increasing the risk of cyberchondria [33]. Although general scales such as the Cyberchondria Severity Scale (CSS) and its short form CSS-12 exist to assess cyberchondria, they do not adequately reflect pregnancy-specific sources of anxiety, fears about obstetric outcomes, and the pregnancy-specific online information environment [1, 34]. No tool specifically designed to measure the severity of cyberchondria during pregnancy has been identified in the literature. This study provides evidence regarding the validity and reliability of the Cyberchondria Severity Scale in Pregnancy (CSS-P), developed to assess the severity of cyberchondria during pregnancy, thereby making important contributions to the systematic reporting, monitoring, and evaluation of digital health behaviors specific to the pregnancy period.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003ePsychometric properties of the CSS-P\u003c/h2\u003e \u003cp\u003eThe content validity of the CSS-P was assessed using the classification proposed by Davis (1992). I-CVI and S-CVI were above the acceptable lower limit (\u0026gt;\u0026thinsp;0.80)[35]. The scores indicated that the items adequately represented the construct. Although EFA is recommended first, followed by CFA, when analyzing content validity in scale development studies, conducting parallel tests can strengthen the validity of the measurement instrument [36]. In this study, the KMO coefficient (\u0026gt;\u0026thinsp;0.70) and Bartlett's sphericity test ( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicated that the data were normally distributed and that the sample size was adequate for factor analysis [35] .\u003c/p\u003e \u003cp\u003eEFA results showed that the total variance explained by the five-factor CSS-P was above the desired range for multi-factor scales (60%-70%) [37]. Eliminating factor loadings below 0.30 in the study improved the representativeness and variance levels of the instrument [17, 27]. CFA was conducted on a different sample, establishing a 5-factor structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Convergent validity, as measured by parallel test results, showed a medium to high level of positive correlation, indicating a statistically significant relationship between CSS-12 and CSS-P factors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). These findings indicate that the five-factor structure of CSS-P is adequate. EFA, CFA, and parallel test results demonstrated that CSS-P is a valid instrument.\u003c/p\u003e \u003cp\u003eThe reliability of the scale was assessed using Cronbach's α coefficient and the test-retest method. Cronbach's α is recommended to be \u0026gt;\u0026thinsp;0.60 for factors and \u0026gt;\u0026thinsp;0.70 for the total instrument [28]. The Cronbach's α values for the CSS-P and its factors were above these thresholds. ICC results indicated that the instrument was stable over time [38]. These findings demonstrated that the CSS-P is a valid and reliable instrument.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eScale content\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003eScale content\u003c/h2\u003e \u003cp\u003eDeveloped to assess the severity of cyberchondria during pregnancy, the CSS-P consists of five factors: control difficulty, disruption to daily life, compulsive online search behavior, distrust of online information, and anxiety. These factors were designed as complementary domains reflecting the cognitive, emotional, and functional dimensions of health information search behavior on the internet during pregnancy and are consistent with the multidimensional structure of existing cyberchondria scales [1, 2] .\u003c/p\u003e \u003cp\u003eFactor 1 is called control difficulty; items in this factor describe pregnant women's difficulty in stopping their online health searches, feeling the need to search for the same topics repeatedly, and experiencing a loss of self-control over their search behavior. This factor is consistent with findings from studies using CSS and CSS-12 that show compulsive and excessive online health search behavior is associated with health anxiety, increased distress, and impaired daily functioning [1, 11, 39]. This sub-dimension parallels studies demonstrating the relationship between cyberchondria and increased levels of pregnancy-related anxiety in pregnant women [6, 40] .\u003c/p\u003e \u003cp\u003eFactor 2 is termed impairment in daily life. This factor emphasizes how online searches lead to time loss, distraction, and functional impairment in pregnant women's domestic responsibilities, work/school roles, and social relationships. Current studies on cyberchondria show that increased online search behavior is associated with impaired functioning, increased healthcare utilization, and decreased quality of life [2, 3] .\u003c/p\u003e \u003cp\u003eFactor 3 is labeled as compulsive online search behavior; items in this domain describe a cyclical search pattern, such as pregnant women constantly browsing different websites and each new piece of information leading to new searches. This structure aligns with theoretical and empirical literature indicating that cyberchondria is characterized by compulsive online search cycles that perpetuate health anxiety rather than alleviating it [2, 11] .\u003c/p\u003e \u003cp\u003eFactor 4 is termed distrust of online information. Items in this factor express that pregnant women experience increased confusion and loss of trust as they are exposed to conflicting, dramatized, or unreliable information on the internet. In cyberchondria studies, information overload and uncertainty about the reliability of online sources have been shown to increase health-related cognitive distortions, decision-making difficulties, and maladaptive coping behaviors [2, 41] .\u003c/p\u003e \u003cp\u003eFinally, factor 5 is called anxiety; items in this factor describe increased anxiety about pregnancy and fetal health after online searches, fear of discovering new symptoms, and focusing on possible complications. Studies in pregnant women have shown that searching for health information online is associated with increased anxiety levels, pregnancy-specific concerns, and cyberchondria, particularly in complicated or high-risk pregnancies and in the presence of high health anxiety [6, 40] .\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations that should be considered when interpreting the findings and using the Pregnancy Cyberchondria Severity Scale (CSS-P). First, although the overall sample size was adequate for scale development and psychometric testing, all participants were selected from a single research and training hospital in Turkey. This single-center, convenience sampling strategy may limit the generalizability of the results to pregnant women receiving care in different geographic regions, health systems, or cultural contexts, and primarily to those using private or community-based services.\u003c/p\u003e \u003cp\u003eThis study relies solely on self-reported data collected through face-to-face administration. Since women in the perinatal period may be inclined to report 'appropriate' online health behaviors, the data may be subject to recall and social desirability biases. Furthermore, the scope of cyberchondria and related conditions may be limited as they are not validated by objective measures such as digital trace data.\u003c/p\u003e \u003cp\u003eFinally, although robust evidence has been obtained for factor structure, internal consistency, test-retest reliability, and convergent validity with the Cyberchondria Severity Scale, some important psychometric properties have not been examined. Measure invariance across key subgroups (e.g., trimester, parity, high-risk and low-risk pregnancy, education level, and e-health literacy) has not been tested.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis three-phase study demonstrated that the newly developed Pregnancy Cyberchondria Severity Scale (CSS-P) is a valid and reliable tool. This 21-item tool consists of five factors: control difficulties (5 items), disruption in daily life (4 items), compulsive online search behavior (4 items), distrust of online information (4 items), and anxiety (4 items). With its good psychometric properties, the CSS-P can be used in clinical and research settings to assess the severity of cyberchondria during pregnancy in a multidimensional manner and to monitor the digital health behaviors of pregnant women.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCSS-P: Pregnancy Cyberchondria Severity Scale\u003c/p\u003e\n\u003cp\u003e\u0026chi;\u0026sup2;, chi-square statistic;\u003c/p\u003e\n\u003cp\u003edf, degrees of freedom;\u003c/p\u003e\n\u003cp\u003ep, probability value;\u003c/p\u003e\n\u003cp\u003e\u0026chi;\u0026sup2;/df, chi-square divided by degrees of freedom;\u003c/p\u003e\n\u003cp\u003eGFI, goodness-of-fit index;\u003c/p\u003e\n\u003cp\u003eCFI, comparative fit index;\u003c/p\u003e\n\u003cp\u003eTLI, Tucker\u0026ndash;Lewis index;\u003c/p\u003e\n\u003cp\u003eRMSEA, root mean square error of approximation;\u003c/p\u003e\n\u003cp\u003eCI, confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the pregnant women who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.\u0026Ouml;. conceived the study, participated in study design, performed data analysis, drafted the manuscript and reviewed the manuscript. G.G. participated in study design and reviewed the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Non-Interventional Ethics Committee of Ankara Medipol University (decision no: E-85859696-604.01.01-5763, Number: 142). Pregnant women who agreed to participate in the study were included. Informed consent was obtained from all participants. The consent form provided information to the pregnant women about the purpose of the study. All personal information will be kept confidential. The study was conducted in accordance with the Declaration of Human Rights.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. No identifying images or personal clinical information of participants are included in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMcElroy, E. and M. Shevlin, The development and initial validation of the cyberchondria severity scale (CSS). Journal of anxiety disorders, 2014. 28(2): p. 259-265.\u003c/li\u003e\n\u003cli\u003eStarcevic, V., et al., The assessment of cyberchondria: instruments for assessing problematic online health-related research. Current Addiction Reports, 2020. 7(2): p. 149-165.\u003c/li\u003e\n\u003cli\u003eFergus, T.A., The Cyberchondria Severity Scale (CSS): an examination of structure and relations with health anxiety in a community sample. Journal of anxiety disorders, 2014. 28(6): p. 504-510.\u003c/li\u003e\n\u003cli\u003eDorst, M.T., et al., Health information technologies in the support systems of pregnant women and their caregivers: mixed-methods study. Journal of medical Internet research, 2019. 21(5): p. e10865.\u003c/li\u003e\n\u003cli\u003eJamal, M.E., et al., Internet-based pregnancy information seeking in Lebanon: a cross-sectional study. BMC Pregnancy and Childbirth, 2025. 25(1): p. 697.\u003c/li\u003e\n\u003cli\u003eCoglianese, F., et al., Effect of online health information seeking on anxiety in hospitalized pregnant women: Cohort study. JMIR Medical Informatics, 2020. 8(5): p. e16793.\u003c/li\u003e\n\u003cli\u003eRezaee, R., et al., Healthy lifestyle during pregnancy: Uncovering the role of online health information seeking experience. PLoS One, 2022. 17(8): p. e0271989.\u003c/li\u003e\n\u003cli\u003eAmanak, K. and F. Şule Bilgi\u0026ccedil;, Cyberchondria and pregnancy-related anxiety: multidimensional assessment of Health anxiety, sensitivity, uncertainty, and fear of childbirth in pregnant women. Psychology, Health \u0026amp; Medicine, 2025: p. 1-15.\u003c/li\u003e\n\u003cli\u003eGiacometti, C.F., et al., Internet use by pregnant women during prenatal care. Einstein (S\u0026atilde;o Paulo), 2024. 22: p. eAO0447.\u003c/li\u003e\n\u003cli\u003eGulec Satir, D. and S. Bakir, The relationship between cyberchondria and health anxiety in pregnant women. Journal of Consumer Health on the Internet, 2024. 28(2): p. 91-103.\u003c/li\u003e\n\u003cli\u003eMcElroy, E., et al., The CSS-12: Development and validation of a short-form version of the cyberchondria severity scale. Cyberpsychology, Behavior, and Social Networking, 2019. 22(5): p. 330-335.\u003c/li\u003e\n\u003cli\u003eBarke, A., et al., The Cyberchondria Severity Scale (CSS): German validation and development of a short form. International journal of behavioral medicine, 2016. 23(5): p. 595-605.\u003c/li\u003e\n\u003cli\u003eRahme, C., et al., Cyberchondria severity and quality of life among Lebanese adults: the mediating role of fear of COVID-19, depression, anxiety, stress and obsessive\u0026ndash;compulsive behavior\u0026mdash;a structural equation model approach. BMC psychology, 2021. 9(1): p. 169.\u003c/li\u003e\n\u003cli\u003eKut, M., M. Ogulluk, and D.I. Akbiyik, Cyberchondria Screening in Pregnant Women Applying to The Outpatient Clinics of a Training and Research Hospital. Eurasian Journal of Family Medicine, 2024. 13(4): p. 162-169.\u003c/li\u003e\n\u003cli\u003eBati, A.H., et al., Health anxiety and cyberchondria among Ege University health science students. 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Lee, A first course in factor analysis. 2013: Psychology press.\u003c/li\u003e\n\u003cli\u003eBrown, R.J., N. Skelly, and C.A. Chew-Graham, Online health research and health anxiety: A systematic review and conceptual integration. Clinical psychology: Science and practice, 2020. 27(2): p. 20.\u003c/li\u003e\n\u003cli\u003eMcMullan, R.D., et al., The relationships between health anxiety, online health information seeking, and cyberchondria: Systematic review and meta-analysis. Journal of affective disorders, 2019. 245: p. 270-278.\u003c/li\u003e\n\u003cli\u003eStarcevic, V., D. Berle, and S. Arn\u0026aacute;ez, Recent insights into cyberchondria. Current Psychiatry Reports, 2020. 22(11): p. 56.\u003c/li\u003e\n\u003cli\u003eTerzi, H., A. Akca, and S.A. Alkaya, The Cyberchondria Severity Scale-Short Form: A Psychometric Study. Genel Tıp Dergisi, 2024. 34(4): p. 450-457.\u003c/li\u003e\n\u003cli\u003eAlmanasreh, E., R. Moles, and T.F. Chen, Evaluation of methods used for estimating content validity. Research in social and administrative pharmacy, 2019. 15(2): p. 214-221.\u003c/li\u003e\n\u003cli\u003eNetemeyer, R.G., W.O. Bearden, and S. Sharma, Scaling procedures: Issues and applications. 2003: sage publications.\u003c/li\u003e\n\u003cli\u003eClark, L.A. and D. Watson, Constructing validity: Basic issues in objective scale development. 2016.\u003c/li\u003e\n\u003cli\u003eCortina, J.M., What is coefficient alpha? An examination of theory and applications. Journal of applied psychology, 1993. 78(1): p. 98.\u003c/li\u003e\n\u003cli\u003eRobles-Mari\u0026ntilde;os, R., et al., The short-form of the Cyberchondria Severity Scale (CSS-12): Adaptation and validation of the Spanish version in young Peruvian students. Plos one, 2023. 18(10): p. e0292459.\u003c/li\u003e\n\u003cli\u003eHansen, M.H., et al., Worries and information seeking during pregnancy: a cross-sectional study among 1402 expectant Norwegian women active on social media platforms. Scandinavian Journal of Primary Health Care, 2025. 43(2): p. 488-499.\u003c/li\u003e\n\u003cli\u003eYang, X., et al., Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions. Telematics and Informatics, 2025. 97: p. 102225.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pregnancy, Maternal Health, Information Seeking Behavior, Internet Use, Psychometrics, Cyberchondria","lastPublishedDoi":"10.21203/rs.3.rs-8386754/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8386754/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eWith the increase in internet use during pregnancy, many women frequently search for information about their own health and their baby's health from online sources. However, excessive and repetitive online health searches can increase anxiety and lead to cyberchondria. There is no pregnancy-specific measurement tool to assess the severity of cyberchondria in pregnant women. This study was conducted to develop the Pregnancy Cyberchondria Severity Scale (PCSS) and evaluate its psychometric properties.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study was conducted in three phases: (1) creation of the item pool, (2) preliminary evaluation of the items, and (3) refinement of the scale and evaluation of its psychometric properties. Instrument development guidelines were used to assess the content validity, construct validity, internal consistency, and stability over time of the instrument. Data were collected between August 2025 and December 2025 to evaluate the psychometric properties of the CSS-P.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eExploratory factor analysis revealed that the CSS-P consists of 5 factors and 21 items explaining 65.27% of the total variance. Confirmatory factor analysis revealed that the proposed model showed an excellent level of fit (GFI\u0026thinsp;=\u0026thinsp;0.943; CFI\u0026thinsp;=\u0026thinsp;0.994; TLI\u0026thinsp;=\u0026thinsp;0.993; RMSEA\u0026thinsp;=\u0026thinsp;0.024; 90% CI: 0.007\u0026ndash;0.036). Cronbach's alpha coefficients for the total score and subscales of the scale were above 0.90. The parallel test method was used to evaluate the correlation between the CSS-P and the cyberchondria severity scale. The findings showed that the CSS-P has high internal consistency and stability over time.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCSS-P is a valid and reliable measure in terms of its psychometric properties. The 21-item scale consists of five factors: Difficulty in Controlling, Impairment in Daily Life, Compulsive Online Searching Behavior, Distrust of Online Information, and Anxiety.\u003c/p\u003e\u003ch2\u003eImpact\u003c/h2\u003e \u003cp\u003eCSS-P can be used in clinical practice to identify pregnant women with excessive and maladaptive online health search behavior and to evaluate the effectiveness of interventions aimed at supporting healthier information-seeking behaviors during pregnancy.\u003c/p\u003e","manuscriptTitle":"Development of the Cyberchondria Severity Scale in Pregnancy (CSS-P)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 05:27:22","doi":"10.21203/rs.3.rs-8386754/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-23T09:28:21+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"249003735542780256190544531745516990796","date":"2026-01-23T03:56:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-23T03:05:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324867293595840747953019649019777828494","date":"2026-01-23T02:32:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T08:02:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265920761992218238263247106849633868306","date":"2026-01-22T07:39:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66318171159447515620286721061492981438","date":"2026-01-21T12:41:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-21T06:50:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91029181537749645583568651677155136336","date":"2026-01-21T06:14:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-20T05:52:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-20T05:51:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-08T16:41:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-06T13:26:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2026-01-06T13:16:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7140d921-ff57-471e-b50d-d24429300ab6","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:15:45+00:00","versionOfRecord":{"articleIdentity":"rs-8386754","link":"https://doi.org/10.1186/s12884-026-08833-8","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2026-02-20 15:57:16","publishedOnDateReadable":"February 20th, 2026"},"versionCreatedAt":"2026-01-12 05:27:22","video":"","vorDoi":"10.1186/s12884-026-08833-8","vorDoiUrl":"https://doi.org/10.1186/s12884-026-08833-8","workflowStages":[]},"version":"v1","identity":"rs-8386754","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8386754","identity":"rs-8386754","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}