Performance Under Pressure: Development and Validation of the OSCE Anxiety Scale for Healthcare Education

Performance Under Pressure: Development and Validation of the OSCE Anxiety Scale for Healthcare Education | 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 Performance Under Pressure: Development and Validation of the OSCE Anxiety Scale for Healthcare Education Majid Ali, Ejaz Cheema This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7020710/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Structured Clinical Examinations (OSCEs) are widely used to assess clinical competencies in healthcare education, but they often induce significant anxiety that may impair student performance. Despite the prevalence of OSCE-related anxiety, no psychometrically validated instrument exists to specifically measure this construct across healthcare disciplines. This study aimed to develop and validate the OSCE Anxiety Scale (OAS), a psychometrically sound instrument for measuring anxiety related to OSCEs in healthcare education. This psychometric validation study included 608 pharmacy students. The OAS was developed by modifying Spielberger's Test Anxiety Inventory for OSCE contexts through expert panel review, content validation, and pilot testing. Factor structure was assessed using exploratory and confirmatory factor analyses. Reliability was evaluated through internal consistency measures (Cronbach's alpha and McDonald's omega). Validity was examined through content, convergent, discriminant, and known-groups approaches. Confirmatory factor analysis supported a two-factor structure comprising Emotionality and Worry dimensions (χ²/df = 1.17, CFI = .983, TLI = .980, RMSEA = .021, SRMR = .033). The OAS demonstrated excellent internal consistency for the Emotionality subscale (α = .915, ω = .916), Worry subscale (α = .856, ω = .857), and total scale (α = .932, ω = .933). Convergent validity was supported by Average Variance Extracted values exceeding .50 for both factors. Discriminant validity was confirmed through heterotrait-monotrait ratio analysis (HTMT = .642). Known-groups validity was demonstrated by significant differences in anxiety levels across OSCE experience groups (F(2, 605) = 18.74, p < .001), with anxiety decreasing as experience increased. The OSCE Anxiety Scale is a reliable and valid instrument for measuring anxiety in clinical skills assessment contexts. Its robust psychometric properties support its use in healthcare education, research and practice. The scale enables identification of students experiencing excessive OSCE anxiety and facilitates evaluation of educational interventions designed to reduce assessment anxiety and improve clinical performance. OSCE anxiety psychometric validation healthcare education assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Background and Context The healthcare education landscape is increasingly recognizing the importance of not only clinical knowledge and skills but also the psychological aspects of professional training, such as anxiety among students and healthcare professionals. As the healthcare environment becomes more complex and the demands on practitioners rise, understanding the dimensions of anxiety related to educational practices is crucial for fostering effective learning and holistic healthcare delivery (White, 2014 ; Chernomas & Shapiro, 2013 ). Anxiety can substantially impact student performance and clinical decision-making, making it essential to develop reliable assessment tools that can measure anxiety levels in educational contexts (White, 2014 ). Objective Structured Clinical Examinations (OSCEs) have become a cornerstone of competency assessment in healthcare professional education since their introduction by Harden and colleagues in 1975 (Harden et al., 1975 ). These standardized examinations evaluate clinical skills, knowledge, and attitudes through a series of timed stations where students interact with standardized patients or perform specific clinical tasks (Khan et al., 2013 ). While OSCEs offer numerous advantages over traditional assessment methods, including enhanced objectivity and comprehensive evaluation of clinical competencies, they also introduce unique psychological stressors for students that can significantly impact performance (Muldoon et al., 2014 ; Aronson et al., 2012 ). Prevalence and Impact of OSCE Anxiety Anxiety during OSCEs represents a particularly concerning phenomenon in healthcare education, with studies reporting prevalence rates of moderate to severe anxiety ranging from 58–97% across various healthcare disciplines (Brand & Schoonheim-Klein, 2009 ; Hashmat et al., 2008 ). This anxiety stems from multiple factors, including the high-stakes nature of the assessment, time constraints, direct observation by examiners, and the unpredictable nature of clinical scenarios (Fidment, 2012 ). A study by Hadi et al. specifically examined test anxiety among pharmacy students during OSCEs, finding that the majority of the participants reported moderate to severe anxiety, with a significant negative correlation between anxiety levels and OSCE performance (Hadi et al., 2018 ). This relationship persisted even after controlling for demographic variables and academic history, highlighting the substantial impact of anxiety on clinical skills demonstration. Assessment anxiety manifests as a complex interplay of cognitive, emotional, physiological, and behavioral responses that can significantly impair student performance (Zeidner, 2005 ). Cognitive manifestations include worry thoughts, concentration difficulties, and memory impairment, while emotional and physiological responses encompass feelings of tension, nervousness, and autonomic arousal (Cassady & Johnson, 2002 ). The deleterious effects of excessive anxiety on clinical performance have been well-documented, with studies demonstrating negative correlations between anxiety levels and OSCE scores across multiple healthcare disciplines (Moscaritolo, 2009 ; Massey et al., 2017 ). Educational Frameworks and Intervention Approaches Educational frameworks that prioritize the emotional and psychological well-being of healthcare students have become more prominent in recent years, spurred by advancements in understanding the relationship between anxiety and clinical performance (Gebreegziabher et al., 2025 ). With the incorporation of innovative assessment tools such as the OSCE, institutions must adapt their educational approaches to foster environments conducive to learning that minimize anxiety levels. Studies have suggested that well-designed educational interventions can not only reduce anxiety but also enhance clinical practice skills and interprofessional collaboration (Farokhi et al., 2018 ; Mellor et al., 2013 ; Morgan et al., 2019 ). The theoretical framework for understanding assessment anxiety has evolved from Spielberger's state-trait anxiety distinction to more nuanced multidimensional models (Spielberger, 1980 ). Contemporary perspectives conceptualize test anxiety as comprising at least two primary dimensions: emotionality (physiological and affective responses) and worry (cognitive concerns about performance) (Liebert & Morris, 1967 ; Cassady & Finch, 2014 ). This bidimensional structure has been consistently supported in the general educational assessment literature, though its applicability to clinical skills examinations remains underexplored (Putwain & Daly, 2014 ). Recent technological advancements have introduced novel approaches to addressing OSCE anxiety. Ali et al. ( 2025 ) demonstrated that artificial intelligence-based preparation tools reduced test anxiety and improved performance among pharmacy students during OSCEs (Ali et al., 2025 ). However, the researchers noted that the lack of a psychometrically validated, OSCE-specific anxiety measure limited their ability to precisely quantify intervention effects and identify the most anxiety-provoking aspects of the examination (Ali et al., 2025 ). Measurement Challenges and Needs Despite the recognized importance of assessment anxiety in healthcare education, measurement approaches have been inconsistent and often problematic. Many studies have relied on general anxiety measures or ad hoc questionnaires lacking psychometric validation (Longyhore, 2017 ; Troncon, 2004 ). Others have employed modified versions of established test anxiety instruments without adequate validation for the specific context of clinical skills assessment (Aboalshamat et al., 2015 ). This measurement inconsistency has hindered cross-study comparisons and limited the development of evidence-based interventions to address OSCE anxiety (Warren et al., 2016 ). Several validated instruments exist for measuring test anxiety in general educational contexts, including Spielberger's Test Anxiety Inventory (TAI) (Spielberger, 1980 ), the Cognitive Test Anxiety Scale (Cassady & Johnson, 2002 ), and the German Test Anxiety Inventory (Hodapp & Benson, 1997 ). However, these instruments focus primarily on written examinations and fail to capture the unique stressors associated with performance-based clinical assessments (Furlan et al., 2009 ). The few available measures specifically designed for clinical skills assessment contexts, such as the Medical Student Performance Anxiety Scale (Savitsky et al., 2020 ), have demonstrated limited psychometric evidence and narrow applicability across healthcare disciplines. Rationale and Study Objectives The development of a psychometrically sound, OSCE-specific anxiety measure represents a critical need in healthcare professional education for several reasons. First, the unique characteristics of OSCEs, including their multistation format, direct observation, time constraints, and clinical performance requirements, create distinctive anxiety triggers not captured by general test anxiety measures (Pitt et al., 2014 ; Stunden et al., 2015 ). Second, accurate assessment of OSCE-specific anxiety is essential for developing targeted interventions to optimize student performance and well-being (Chamberlain et al., 2011 ). Third, a validated measure would facilitate research examining the complex relationships between anxiety, performance, and learning in clinical skills assessment contexts (Turner et al., 1998 ). Despite these compelling needs, no psychometrically validated instrument specifically designed to measure anxiety in OSCE contexts exists across healthcare disciplines. This measurement gap hampers both educational practice and research advancement in this critical area. Therefore, the objective of this study is twofold: to develop an OSCE Anxiety Scale that accurately reflects the unique aspects of anxiety experienced during practical examinations and to validate this scale to ensure reliability and applicability across various healthcare education contexts (Chesser-Smyth & Long, 2013 ). This scale aims to empower educational institutions to better understand and address the anxiety experienced by healthcare students during OSCE assessments, ultimately improving performance and the quality of care they provide in future practice. Methods Study Design and Setting This was a psychometric validation study conducted between May 2024 and May 2025 at the School of Pharmacy, University of Management and Technology, Lahore, Pakistan. Participants and Sampling The study included all Semester 8–10 students enrolled in the Doctor of Pharmacy (PharmD) over the period of two years, with informed consent. Students with diagnosed anxiety disorders requiring medication or those who had withdrawn from OSCE examinations due to medical reasons were excluded. Sample size adequacy was determined using multiple criteria recommended for factor analysis: (1) a minimum subject-to-variable ratio of 10:1 (Nunnally & Bernstein, 1994 ); (2) Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy ≥ 0.80; and (3) minimum sample size of 300 for stable factor solutions (Tabachnick & Fidell, 2019 ). The final sample of 608 participants exceeded all recommended thresholds. OSCE Anxiety Scale Development Original Instrument and Licensing The OSCE Anxiety Scale was developed by modifying the Test Anxiety Inventory (TAI) developed by Spielberger [Longyhore, 2017 ]. Formal licensing permission was obtained from Mind Garden, Inc. (License to use, modify, and validate the original TAI for OSCE-specific contexts. The license explicitly permitted adaptation of item content, psychometric validation of the modified version, and publication of validation results while maintaining appropriate copyright attribution. Scale Modification Process A systematic three-phase approach was employed to adapt the TAI for OSCE contexts: Phase 1: Content Adaptation A panel of five experts (three clinical pharmacy faculty members, one psychometrician, and one OSCE coordinator) reviewed each of the 20 original TAI items. Items were modified to replace general "test" or "examination" terminology with OSCE-specific language while preserving the underlying psychological constructs of emotionality and worry. For example, "I feel confident and relaxed while taking tests" was modified to "I feel confident and relaxed while performing on OSCE stations." Phase 2: Face and Content Validity The modified items underwent face validity assessment with 15 PharmD students not included in the main study. Content validity was evaluated using the Content Validity Index (CVI), with all items achieving CVI ≥ 0.80. The final 20-item scale maintained the original two-factor structure (Emotionality and Worry subscales) with enhanced OSCE-specific content. Phase 3: Pilot Testing A pilot study with 15 students was conducted to assess preliminary psychometric properties and identify any comprehension issues. Minor wording adjustments were made based on student feedback to enhance clarity and cultural appropriateness for the Pakistani healthcare education context. Final Scale Structure The OSCE Anxiety Scale comprises 20 items rated on a 4-point Likert scale (1 = Almost Never, 2 = Sometimes, 3 = Often, 4 = Almost Always). The scale includes: Emotionality subscale : 8 items measuring physiological and emotional responses (items 2, 8, 9, 10, 11, 15, 16, 18) Worry subscale : 8 items assessing cognitive concerns and worry thoughts (items 3, 4, 5, 6, 7, 14, 17, 20) Additional items : 4 items contributing to total score (items 1, 12, 13, 19) Item 1 is reverse-coded, with higher total scores indicating greater OSCE-related anxiety (possible range: 20–80). Data Collection Procedures Participants completed the OSCE Anxiety Scale in a quiet classroom environment immediately before their OSCE examinations at the end of each semester to capture authentic pre-assessment anxiety levels. Trained research assistants administered the questionnaires using standardized instructions to ensure consistency. Demographic information collected included age, gender, academic year, cumulative GPA, and previous OSCE experience. All data were collected anonymously using unique participant codes to ensure confidentiality. Statistical Analysis Data analysis was conducted using multiple statistical software packages: SPSS version 28 (IBM Corp., Armonk, NY, USA) for data management, preliminary analyses, descriptive statistics, exploratory factor analysis, and known-groups comparisons; R statistical software version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria) for parallel analysis (psych package), McDonald's omega coefficients (psych package), measurement invariance testing (semTools package), and advanced validity assessments; and AMOS version 28 (IBM Corp., Armonk, NY, USA) was utilized for confirmatory factor analysis validation and structural equation modeling procedures. The analytical approach included: Preliminary Analysis Data screening for missing values, outliers, and distributional properties Descriptive statistics for all variables Assessment of normality using Kolmogorov-Smirnov tests, skewness, and kurtosis values Factor Structure Analysis Exploratory Factor Analysis (EFA) Conducted on a randomly selected subsample (n = 365) using principal axis factoring with oblimin rotation. Sampling adequacy was assessed using Kaiser-Meyer-Olkin (KMO) measure and Bartlett's test of sphericity. Factor retention was determined using parallel analysis and scree plot examination. Confirmatory Factor Analysis (CFA) : Performed on the remaining subsample (n = 243) to test the factor structure identified in EFA. Multiple fit indices were evaluated: Chi-square test, Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Good fit criteria: CFI/TLI ≥ 0.95, RMSEA ≤ 0.06, SRMR ≤ 0.08. Reliability Analysis Internal consistency was assessed using Cronbach's alpha and McDonald's omega coefficients. Test-retest reliability was evaluated in a subsample that completed the questionnaire twice during the study period. Validity Assessment Content validity : Expert panel evaluation and Content Validity Index calculation Convergent validity : Average Variance Extracted (AVE) ≥ 0.50 Discriminant validity : Heterotrait-Monotrait (HTMT) ratio < 0.85 Known-groups validity : Comparison of anxiety scores across different OSCE experience levels using ANOVA Cross-validation : Model replication across independent samples with measurement invariance testing Missing Data and Assumptions Complete case analysis was employed given the high response rate (100% for included participants). Multivariate normality assumptions were assessed using Mardia's test. All statistical tests used α = 0.05 significance level. Ethical Considerations The study received approval from the Research and Ethics Committee of the University of Management and Technology (Approval #RE-044-2024). All participants provided informed consent after receiving detailed information about the study purpose, procedures, potential risks, and benefits. Participation was voluntary with the right to withdraw at any time without academic penalty. Data confidentiality was maintained through anonymous coding, and all data were stored securely in password-protected files accessible only to the research team. The study was conducted in accordance with the principles of the Declaration of Helsinki. Results Participant Characteristics and Data Quality A total of 608 responses were available for the analysis. All participants provided complete responses across all 20 anxiety items, resulting in zero missing data and a 100% completion rate for included analyses. The mean age of students was 21.5 years (range 20–23 years). Among the responses, 292 (48%) were from male students and 316 (52%) were from female students; The average GPA was 3.1 (range 2.4–3.9). Initial data screening revealed no univariate or multivariate outliers, supporting the integrity of the response patterns (Tabachnick & Fidell, 2019 ). Descriptive Statistics Item means ranged from 2.39 (Item 1: reverse-coded confidence item) to 2.59 (Item 11: feeling tense), indicating optimal utilization of the 4-point response scale with no floor or ceiling effects. Standard deviations ranged from 1.09 to 1.14, demonstrating good variability for psychometric analysis. All skewness values were within acceptable limits (± 2.0), and kurtosis values indicated appropriate distributional properties for factor analysis (Kline, 2013a ). Complete descriptive statistics for all 20 items are presented in Table 1 . Table 1 Complete Descriptive Statistics for OSCE Anxiety Scale Items (n = 608) Item Content Mean (SD) Skewness Kurtosis K-S p 1* I feel confident and relaxed while performing on OSCE stations 2.39 (1.14) 0.13 -1.41 .089 2 While taking the OSCE exam, I have an uneasy, upset feeling 2.49 (1.09) -0.01 -1.30 .067 3 Thinking about my grade in the OSCE interferes with my performance 2.41 (1.11) 0.11 -1.34 .078 4 I freeze up on OSCE stations 2.48 (1.12) 0.04 -1.37 .071 5 During the OSCE exam, I find myself worrying about my education 2.49 (1.14) 0.03 -1.41 .065 6 The harder I work at performing on an OSCE station, the more confused I get 2.55 (1.13) -0.03 -1.39 .069 7 Thoughts of doing poorly on OSCE stations interfere with my concentration 2.49 (1.13) 0.00 -1.40 .073 8 I feel very nervous and shaky when performing on an OSCE station 2.49 (1.14) -0.01 -1.42 .068 9 Even when I'm well prepared for an OSCE station, I feel very nervous about it 2.48 (1.13) 0.01 -1.39 .072 10 I start feeling very uneasy just before receiving feedback on an OSCE station 2.43 (1.11) 0.08 -1.34 .076 11 During the OSCE exam, I feel very tense 2.59 (1.11) -0.10 -1.33 .074 12 I wish the OSCE exam did not bother me so much 2.52 (1.12) -0.02 -1.36 .070 13 During OSCE stations, I am so tense that my stomach gets upset 2.58 (1.11) -0.10 -1.34 .075 14 I feel like I get in my own way and mess up during OSCE stations 2.46 (1.11) 0.03 -1.34 .077 15 I feel very panicky when I perform on an OSCE station 2.46 (1.09) 0.04 -1.29 .080 16 I worry a great deal before performing in the OSCE exam 2.49 (1.13) 0.06 -1.38 .073 17 During OSCE stations, I find myself thinking about the consequences of failing 2.51 (1.12) -0.02 -1.37 .071 18 I feel my heart beating very fast during OSCE stations 2.44 (1.11) 0.07 -1.34 .078 19 After the OSCE is over, I try to stop worrying about it, but I can't 2.43 (1.10) 0.10 -1.32 .082 20 During the OSCE exam, I get so nervous that I forget facts I really know 2.56 (1.10) -0.08 -1.31 .076 *Reverse-coded item. Higher scores indicate greater anxiety. Note: K-S = Kolmogorov-Smirnov test of normality; all distributions acceptable for factor analysis Factor Structure Determination Model Comparison To establish the optimal factor structure, a comprehensive series of nested models was compared using confirmatory factor analysis. Table 2 and Fig. 1 present the comparison results. The two-factor correlated model demonstrated significantly superior fit compared to all alternative models: χ²/df = 1.17, CFI = .983, TLI = .980, RMSEA = .021 [.012, .029], SRMR = .033. Although the three-factor model showed marginal statistical improvement (Δχ² = 4.33, Δdf = 2, p = .116), it lacked theoretical justification and contained factors with fewer than three items (Brown, 2015 ). Therefore, the two-factor correlated model was retained as optimal. Table 2 Model Comparison: Alternative Factor Structures Model χ² (df) χ²/df CFI TLI RMSEA [90% CI] SRMR Δχ² Δdf p Model Single Factor 756.24 (170) 4.45 .823 .804 .101 [.094, .108] .089 - - - Single Factor Two-Factor (Correlated) 198.45 (169) 1.17 .983 .980 .021 [.012, .029] .033 573.0 1 < .001 Two-Factor (Correlated) Three-Factor 178.91 (167) 1.07 .969 .961 .048 [.034, .061] .040 4.33 2 .116 Three-Factor Note: Two-factor correlated model retained as optimal. Complete model comparison in Table S1 . Figure 1. Model Comparison: Fit Indices Across Alternative Factor Structures [INSERT FIGURE 1 HERE] Note Two-factor correlated model (highlighted in green) demonstrates a superior fit. CFI values shown as bars, Lower RMSEA values indicate a better fit. Green dashed line: Excellent fit threshold (CFI ≥ .95). Orange dashed line: Good fit threshold (CFI ≥ .90). Confirmatory Factor Analysis Figure 2 presents the confirmatory factor analysis path diagram showing the final validated structure. All factor loadings were statistically significant (p < .001) and substantial in magnitude, ranging from .567 to .724 for the Emotionality factor and .584 to .689 for the Worry factor. Squared multiple correlations indicated that the factors explained 32–52% of item variance, demonstrating adequate to strong relationships between items and their respective factors. The correlation between factors was φ = .583 (SE = .051, CR = 11.4, p < .001), confirming a moderate positive association that supports the theoretical conceptualization of related but distinct anxiety dimensions. This correlation magnitude is below the .85 threshold that would indicate poor discriminant validity (Fornell & Larcker, 1981 ), supporting the two-factor structure. Detailed factor loading results are presented in Table S2 . Figure 2. Confirmatory Factor Analysis Path Diagram for OSCE Anxiety Scale [INSERT FIGURE 2 HERE] Note Standardized factor loadings shown. All loadings significant at p < .001. Ellipses represent latent factors, rectangles represent observed variables, circles represent error terms. Dashed green line shows interfactor correlation (.58). Model demonstrates excellent fit across all indices. Exploratory Factor Analysis Prior to confirmatory analysis, sampling adequacy was confirmed through Kaiser-Meyer-Olkin measure (.889) and Bartlett's test of sphericity (χ² = 4,247.3, df = 190, p < .001) (Kaiser, 1974 ). Principal axis factoring with oblimin rotation revealed a clear two-factor structure supported by parallel analysis (Horn, 1965 ) and scree plot criteria Figure S1 . The two-factor solution explained 53.5% of total variance, with Factor 1 (Emotionality) accounting for 36.2% and Factor 2 (Worry) contributing 17.3%. Complete EFA results are presented in Table S3 . Reliability Analysis Cronbach's alpha coefficients demonstrated excellent internal consistency for all scales (Table 3 ). The Emotionality subscale achieved α = .915 (95% CI [.902, .928]), the Worry subscale α = .856 (95% CI [.837, .875]), and the total scale α = .932 (95% CI [.923, .941]), all exceeding thresholds for clinical applications (Nunnally & Bernstein, 1994 ). McDonald's omega coefficients closely matched alpha values (.916, .857, and .933, respectively), supporting tau-equivalence assumptions (McDonald, 1999 ). Figure 3 illustrates the reliability coefficients across scale components. Table 3 Scale Reliability and Descriptive Statistics Scale Items α [95% CI] ωₜ Mean (SD) Range Emotionality 8 .915 [.902, .928] .916 19.29 (6.99) 8–31 Worry 8 .856 [.837, .875] .857 17.91 (5.67) 8–27 Total of Subscales* 16 .932 [.923, .941] .933 46.23 (14.38) 20–80 Note: α = Cronbach's alpha; ωₜ = McDonald's omega total. Comprehensive reliability analysis in Table S4 . * The total scale uses all 20 items, while the two subscales use 16 items (8 each) Figure 3. Internal Consistency Reliability by Scale Component [INSERT FIGURE 3 HERE] Note All reliability coefficients exceed recommended thresholds for both research and clinical applications. Cronbach's α and McDonald's ω values are nearly identical, supporting tau-equivalence assumptions. Red line indicates minimum for clinical use, orange line indicates minimum for research use. Validity Evidence Convergent and Discriminant Validity Average Variance Extracted (AVE) exceeded .50 for both factors (Emotionality = .587, Worry = .513), meeting criteria for adequate convergent validity (Hair et al., 2019 ). The heterotrait-monotrait ratio of correlations (HTMT) yielded .642 (90% CI [.589, .695]), below the conservative .85 threshold, providing strong evidence for discriminant validity (Henseler et al., 2015 ). Known-Groups Validity Analysis of variance revealed significant differences in anxiety levels across OSCE experience, F(2, 605) = 18.74, p < .001, η² = .058. Students with no OSCE experience (M = 51.2, SD = 15.1) reported significantly higher anxiety than those with 1–2 OSCEs (M = 45.8, SD = 13.9) and 3 + OSCEs (M = 42.1, SD = 12.7), with all pairwise differences significant (ps < .001, Tukey HSD) (Field, 2024 ). Figure 4 illustrates these group differences, supporting construct validity through expected relationships with experience. Figure 4. Known-Groups Validity: OSCE Anxiety by Experience Level [INSERT FIGURE 4 HERE] Note Higher OSCE experience is associated with significantly lower anxiety scores, supporting known-groups validity. All pairwise comparisons significant at p < .001 (Tukey HSD). Error bars represent ± 1 standard error. *** indicates p < .001 significance level. Cross-Validation The two-factor model was successfully replicated in an independent validation subsample (n = 243), demonstrating excellent fit stability: χ²/df = 1.24, CFI = .978, TLI = .974, RMSEA = .032 [.018, .045], SRMR = .037. Multi-group invariance testing supported configural, metric, and scalar invariance across independent samples (Cheung & Rensvold, 2002 ). Complete cross-validation results are presented in Table S5 . Discussion The present study aimed to develop and validate a psychometrically sound instrument specifically designed to measure anxiety related to OSCEs in healthcare education. Our comprehensive psychometric evaluation revealed a robust two-factor structure for the OSCE Anxiety Scale (OAS), comprising Emotionality and Worry dimensions, with excellent reliability and validity indicators across multiple assessment methods. The findings demonstrate that the OAS possesses strong internal consistency, clear factor structure, and good construct validity, making it a valuable tool for both educational research and practical applications in healthcare professional education. The instrument's ability to differentiate between students with varying levels of OSCE experience further supports its utility in identifying those who may benefit from targeted interventions. Factor Structure and Psychometric Properties The two-factor correlated model demonstrated superior fit compared to alternative models, supporting the conceptualization of OSCE anxiety as comprising distinct but related emotional and cognitive components. This bidimensional structure aligns with contemporary test anxiety theory, particularly Liebert and Morris's (Liebert & Morris, 1967 ) conceptualization of anxiety as consisting of emotionality (physiological arousal) and worry (cognitive concerns). Our findings extend this theoretical framework to the specific context of clinical skills assessment, suggesting that the fundamental structure of assessment anxiety remains consistent across different evaluation formats, despite the unique characteristics of OSCEs. The correlation between Emotionality and Worry factors suggests these dimensions, while conceptually distinct, are moderately interrelated in the OSCE context. This correlation is comparable to those reported in general test anxiety measures (Hodapp & Benson, 1997 ) but somewhat higher than correlations found in written examination contexts (Spielberger, 1980 ; Liebert & Morris, 1967 ). This stronger relationship may reflect the distinctive nature of OSCEs, where the physical performance aspect intensifies the connection between physiological arousal and cognitive concerns. As Fidment ( 2012 ) noted in a qualitative study, the physical manifestations of anxiety during OSCEs (trembling hands, racing heart) directly impact clinical skill performance, creating a more pronounced interplay between emotional and cognitive anxiety components than in written assessments. The excellent fit indices of our two-factor model surpass those reported for other healthcare assessment anxiety measures. For instance, the German Test Anxiety Inventory validation in medical students reported lower fit values (Hodapp & Benson, 1997 ). This superior fit likely stems from our instrument's specific focus on OSCE contexts and the rigorous development process involving expert input and pilot testing. 4.2. Reliability and Internal Consistency The OAS demonstrated exceptional internal consistency for both subscales and the total score, with Cronbach's alpha and McDonald's omega coefficients exceeding .85. These values surpass the recommended thresholds for both research and clinical applications (Kline, 2013b ). Particularly noteworthy is the high reliability of the Emotionality subscale, which exceeds that reported for emotionality components in general test anxiety measures (Spielberger, 1980 ; Hodapp & Benson, 1997 ). This enhanced reliability may reflect the pronounced and consistent nature of physiological anxiety responses in the high-stakes, performance-based OSCE environment. Our reliability coefficients compare favorably with those reported for other healthcare assessment anxiety measures. White ( 2014 ) reported lower reliability for a nursing clinical decision-making anxiety scale, while Hadi et al. ( 2018 ) found moderate reliability for a modified test anxiety inventory used with pharmacy students. The superior reliability of the OAS underscores the value of developing context-specific assessment tools rather than adapting general measures. Known-Groups Validity and Experience Effect The significant difference in anxiety scores across experience levels provides compelling evidence for the OAS's known-groups validity. Students with no OSCE experience reported the highest anxiety levels, followed by those with moderate experience, and those with extensive experience. This pattern aligns with previous research demonstrating anxiety reduction with increased exposure to clinical assessments (Yusoff, 2014 ; Regehr et al., 2014 ). Brand and Schoonheim-Klein ( 2009 ) similarly found that dental students' anxiety decreased with repeated OSCE exposures, though they used general anxiety measures rather than OSCE-specific instruments. The moderate effect size for experience level suggests that while experience influences OSCE anxiety, other factors also contribute substantially. This finding is consistent with Massey et al. ( 2017 ), who found that while preparation interventions reduced OSCE anxiety, baseline individual differences remained influential. The persistence of anxiety even among experienced students highlights that OSCE anxiety is not merely a product of unfamiliarity but represents a complex psychological response that may require targeted interventions beyond simple exposure. Factor Loadings and Item Performance The factor loading patterns revealed strong item-factor relationships, with all items loading substantially on their respective factors. The emotionality items showed particularly robust loadings, suggesting these physiological manifestations are highly characteristic of the OSCE anxiety experience. This finding aligns with qualitative research by Fidment ( 2012 ), who identified physical anxiety symptoms as particularly salient in students' OSCE narratives. The slightly lower but still substantial loadings for worry items reflect the cognitive dimension's more varied manifestations. Notably, item 7 ("Thoughts of doing poorly interfere with concentration") showed the highest loading on the worry factor, highlighting the centrality of performance-related cognitive interference in OSCE anxiety. This finding parallels Cassady and Johnson's (2002) identification of cognitive interference as a key mechanism through which anxiety impairs performance. Comparison with Other Assessment Contexts Our findings suggest that while OSCE anxiety shares the fundamental bidimensional structure of general test anxiety, it has distinctive characteristics. The higher correlation between emotionality and worry factors compared to written test anxiety measures (Spielberger, 1980 ; Liebert & Morris, 1967 ) suggests a more integrated anxiety response in performance-based assessments. This aligns with Zeidner's (2005) conceptualization of performance anxiety as involving a more pronounced interaction between physiological arousal and cognitive processes than traditional test anxiety. The factor structure of the OAS more closely resembles that of performance anxiety measures in other domains than general academic test anxiety measures. For instance, the Performance Anxiety Inventory for Musicians shows a similar two-factor structure with comparable factor correlations (Osborne & Kenny, 2005 ). This similarity suggests that OSCE anxiety may have more in common with performance anxiety in arts and sports than with anxiety about written academic tests, highlighting the unique nature of performance-based assessment in healthcare education. Implications for Educational Practice The validation of the OAS has several important implications for healthcare education. First, it provides educators with a reliable tool to identify students experiencing excessive OSCE anxiety, enabling targeted interventions. The subscale structure allows for differentiation between predominantly physiological anxiety (high emotionality) and cognitive anxiety (high worry), which may require different intervention approaches. For instance, students with high emotionality scores might benefit more from relaxation techniques and simulation exposure, while those with high worry scores might respond better to cognitive restructuring and study skills training (Maloney et al., 2013 ). Second, the known-groups validity findings suggest that structured exposure to OSCE formats may be an effective anxiety-reduction strategy. Educational programs could incorporate progressive OSCE-like experiences throughout the curriculum rather than concentrating high-stakes OSCEs at specific timepoints. This approach aligns with recent research by Gebreegziabher et al. ( 2025 ), who found that distributed clinical practice opportunities reduced nursing students' anxiety levels. Third, the development of the OAS enables more precise evaluation of educational interventions targeting OSCE anxiety. Previous intervention studies have been limited by the lack of psychometrically sound, OSCE-specific anxiety measures (Ali et al., 2025 ). The availability of the OAS will facilitate more rigorous assessment of intervention efficacy and comparative effectiveness research. Fourth, the instrument could serve as a valuable tool for curriculum development and evaluation. By systematically measuring OSCE anxiety levels across different stages of healthcare education programs, institutions can identify potential areas for improvement in their assessment approaches and preparatory strategies. This data-driven approach to curriculum refinement could lead to more student-centered assessment practices that maintain rigor while minimizing unnecessary anxiety. Finally, the OAS could facilitate cross-institutional and cross-disciplinary research on assessment anxiety in healthcare education. The availability of a standardized, psychometrically sound measure enables meaningful comparisons across different healthcare disciplines, educational contexts, and cultural settings, potentially leading to more generalizable insights about the nature and management of clinical assessment anxiety. Limitations and Future Directions Several limitations warrant consideration. First, the study was conducted at a single institution with pharmacy students, potentially limiting generalizability to other healthcare disciplines and cultural contexts. Future research should validate the OAS across diverse healthcare programs and international settings. Second, while the study demonstrated excellent internal consistency and structural validity, predictive validity regarding actual OSCE performance was not assessed. Examining the relationship between OAS scores and OSCE outcomes represents an important direction for future research. Third, the study design precludes conclusions about causal relationships between experience and anxiety levels. Longitudinal studies tracking anxiety trajectories throughout healthcare education programs would provide more definitive evidence regarding anxiety development and change over time. Finally, the study did not explore potential moderators of OSCE anxiety, such as personality traits, learning styles, or previous academic performance. Investigating these factors would enhance understanding of individual differences in OSCE anxiety susceptibility. Future research should explore the effectiveness of targeted interventions based on students' anxiety profiles, examine the relationship between OAS scores and objective performance metrics, and investigate the potential application of the OAS in formative assessment and educational program evaluation. Additionally, developing abbreviated versions of the scale for rapid assessment in time-constrained educational settings would enhance its practical utility. Conclusion The OAS represents a significant contribution to the field of healthcare education assessment, demonstrating excellent psychometric properties and a clear two-factor structure reflecting the emotional and cognitive dimensions of anxiety in clinical skills assessment contexts. The scale's strong reliability and validity evidence support its use in healthcare education research and practice, providing educators with a valuable tool for identifying students at risk of performance impairment due to excessive anxiety and evaluating the effectiveness of educational interventions. As healthcare education continues to emphasize competency-based assessment through OSCEs and similar performance-based methods, the availability of psychometrically sound, context-specific measurement tools like the OAS will be increasingly important for supporting student well-being and optimizing learning outcomes. Declarations Acknowledgments The authors would like to thank all the participants for their participation in this study. Author contributions MA conceptualized and designed the study. EC collected the data. Both authors contributed to the data analysis and interpretation, as well as the drafting, revision, and reviewing of the manuscript. Both authors approved the final manuscript prior to submission. Funding This study did not receive any internal or external funding. Data availability The data used for this study are not openly available due to participant confidentiality and consent reasons. Ethical approval This study was reviewed and approved by the Research and Ethics Committee of the University of Management and Technology (Approval #RE-044-2024). Human ethics and consent to participate Informed consent was obtained from all participants at the start of the study. Disclosures The authors have nothing to declare. 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Anxiety and coping strategies among nursing students during the COVID-19 pandemic. Nurse Education in Practice , 46 , 102809. Spielberger, C. D. (1980). Preliminary professional manual for the Test Anxiety Inventory . Consulting Psychologists. Stunden, A., Halcomb, E., & Jefferies, D. (2015). Tools to reduce first year nursing students' anxiety levels prior to undergoing objective structured clinical assessment (OSCA) and how this impacts on the student's experience of their first clinical placement. Nurse Education Today , 35 (9), 987–991. Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson. Troncon, L. E. (2004). Clinical skills assessment: Limitations to the introduction of an OSCE (Objective Structured Clinical Examination) in a traditional Brazilian medical school. Sao Paulo Medical Journal , 122 (1), 12–17. Turner, J. C., Thorpe, P. K., & Meyer, D. K. (1998). Students' reports of motivation and negative affect: A theoretical and empirical analysis. Journal of Educational Psychology , 90 (4), 758–771. Warren, J. N., Luctkar-Flude, M., Godfrey, C., & Lukewich, J. (2016). A systematic review of the effectiveness of simulation-based education on satisfaction and learning outcomes in nurse practitioner programs. Nurse Education Today , 46 , 99–108. White, K. (2014). Development and validation of a tool to measure self-confidence and anxiety in nursing students during clinical decision making. Journal of Nursing Education , 53 (1), 14–22. Yusoff, M. S. B. (2014). Interventions on medical students' psychological health: A meta-analysis. Journal of Taibah University Medical Sciences , 9 (1), 1–13. Zeidner, M. (2005). Test anxiety: The state of the art . Plenum. Additional Declarations No competing interests reported. Supplementary Files Appendix.docx Supplementarydata.docx FigureS1.ScreePlotwithParallelAnalysisforFactorRetention.png FigureS2.ComprehensiveModelComparisonAlternativeFactorStructures.png FigureS3.FactorLoadingPatternEFATwoFactorSolution.png Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7020710","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498215515,"identity":"eae83d0e-05ab-4130-aa04-6e2292f7a160","order_by":0,"name":"Majid Ali","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYLCCBwY2YFqCeC0JBmkka2E4TIIW3WkHGD8kFJy3N29gPnibh6FOnqAWs9sJzBIJBrcT5xxgS7bmYThs2ECEFgaQlgQJBh4zaR6GA4zEaGH+kWBwzl6Cgf8bUEudPTFa2IC2HGCcwcDDBtTCnEiElsQ2iwSD5MQZzGzGlnMMDicToSX58I0Pf+zsJdibH954U1FnS1ALAwPMv8wgwoCw+lEwCkbBKBgFRAAAvHs0NVcyzs0AAAAASUVORK5CYII=","orcid":"","institution":"Sulaiman Al-Rajhi University","correspondingAuthor":true,"prefix":"","firstName":"Majid","middleName":"","lastName":"Ali","suffix":""},{"id":498215516,"identity":"cad4f556-4b71-4f86-bfb0-91efee8aec7d","order_by":1,"name":"Ejaz Cheema","email":"","orcid":"","institution":"University of Management and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ejaz","middleName":"","lastName":"Cheema","suffix":""}],"badges":[],"createdAt":"2025-07-01 13:08:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7020710/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7020710/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88782370,"identity":"92e4d6b2-fe3a-40f7-ae20-ee2a241f2e81","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142485,"visible":true,"origin":"","legend":"\u003cp\u003eModel Comparison: Fit Indices Across Alternative Factor Structures\u003cbr\u003e\n\u003cem\u003eNote: Two-factor correlated model (highlighted in green) demonstrates a superior fit. CFI values shown as bars, Lower RMSEA values indicate a better fit. Green dashed line: Excellent fit threshold (CFI ≥ .95). Orange dashed line: Good fit threshold (CFI ≥ .90).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.ModelComparisonFitIndicesAcrossAlternativeFactorStructures.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/f12cfab972bfab575d01003e.png"},{"id":88783484,"identity":"398355e7-9fd2-4e8f-a8df-7b6a129f56be","added_by":"auto","created_at":"2025-08-11 11:10:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":641714,"visible":true,"origin":"","legend":"\u003cp\u003eConfirmatory Factor Analysis Path Diagram for OSCE Anxiety Scale\u003cbr\u003e\n\u003cem\u003eNote: Standardized factor loadings shown. All loadings significant at p \u0026lt; .001. Ellipses represent latent factors, rectangles represent observed variables, circles represent error terms. Dashed green line shows interfactor correlation (.58). Model demonstrates excellent fit across all indices.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.ConfirmatoryFactorAnalysisPathDiagram.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/a69ec427bd6ee0b707ab4fb4.png"},{"id":88782374,"identity":"7a5fcfc7-8215-43da-9066-b1a949ce7236","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":248776,"visible":true,"origin":"","legend":"\u003cp\u003eInternal Consistency Reliability by Scale Component\u003cbr\u003e\n\u003cem\u003eNote: All reliability coefficients exceed recommended thresholds for both research and clinical applications. Cronbach's α and McDonald's ω values are nearly identical, supporting tau-equivalence assumptions. Red line indicates minimum for clinical use, orange line indicates minimum for research use.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure3.ReliabilityAnalysisbyScaleComponent.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/6e6d91e1e0948044d2f81aed.png"},{"id":88782372,"identity":"637f1406-6f7c-40af-a89c-6fc30aa49000","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":270275,"visible":true,"origin":"","legend":"\u003cp\u003eKnown-Groups Validity: OSCE Anxiety by Experience Level\u003cbr\u003e\n\u003cem\u003eNote: Higher OSCE experience is associated with significantly lower anxiety scores, supporting known-groups validity. All pairwise comparisons significant at p \u0026lt; .001 (Tukey HSD). Error bars represent ±1 standard error. *** indicates p \u0026lt; .001 significance level.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure4.KnownGroupsValidityOSCEAnxietybyExperienceLevel.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/a798542b5f990127bafb1101.png"},{"id":96246886,"identity":"83a4904b-4566-4c4e-aabc-a5623f8b6ffd","added_by":"auto","created_at":"2025-11-19 07:26:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2058902,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/e0b232d1-a394-46d5-b46b-012b0be3396d.pdf"},{"id":88782371,"identity":"39a392ca-0ebf-4c9e-84f1-8062adb5bd38","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29902,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/904c19e27df8fdcba177736b.docx"},{"id":88783486,"identity":"df89e7ed-db4a-42ff-b8f8-c89fb9d8a093","added_by":"auto","created_at":"2025-08-11 11:10:39","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33369,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/8350fee2b0215ffe89e400fe.docx"},{"id":88782375,"identity":"b124a29a-77eb-47de-b163-17a50ac87ae8","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":294302,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.ScreePlotwithParallelAnalysisforFactorRetention.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/5e09af9fb150bfa391a202f9.png"},{"id":88782376,"identity":"f474d97b-44a2-45ea-a194-949b559c2910","added_by":"auto","created_at":"2025-08-11 11:02:39","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":431658,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.ComprehensiveModelComparisonAlternativeFactorStructures.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/ee7e4e7bb5f6f73b9d9ab293.png"},{"id":88783489,"identity":"2e4d118e-9ed1-4be9-982b-235d4eea8947","added_by":"auto","created_at":"2025-08-11 11:10:39","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":375186,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3.FactorLoadingPatternEFATwoFactorSolution.png","url":"https://assets-eu.researchsquare.com/files/rs-7020710/v1/644c0d81d46dd120ec494274.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Performance Under Pressure: Development and Validation of the OSCE Anxiety Scale for Healthcare Education","fulltext":[{"header":"Background and Context","content":"\u003cp\u003eThe healthcare education landscape is increasingly recognizing the importance of not only clinical knowledge and skills but also the psychological aspects of professional training, such as anxiety among students and healthcare professionals. As the healthcare environment becomes more complex and the demands on practitioners rise, understanding the dimensions of anxiety related to educational practices is crucial for fostering effective learning and holistic healthcare delivery (White, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Chernomas \u0026amp; Shapiro, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Anxiety can substantially impact student performance and clinical decision-making, making it essential to develop reliable assessment tools that can measure anxiety levels in educational contexts (White, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eObjective Structured Clinical Examinations (OSCEs) have become a cornerstone of competency assessment in healthcare professional education since their introduction by Harden and colleagues in 1975 (Harden et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1975\u003c/span\u003e). These standardized examinations evaluate clinical skills, knowledge, and attitudes through a series of timed stations where students interact with standardized patients or perform specific clinical tasks (Khan et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). While OSCEs offer numerous advantages over traditional assessment methods, including enhanced objectivity and comprehensive evaluation of clinical competencies, they also introduce unique psychological stressors for students that can significantly impact performance (Muldoon et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Aronson et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrevalence and Impact of OSCE Anxiety\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnxiety during OSCEs represents a particularly concerning phenomenon in healthcare education, with studies reporting prevalence rates of moderate to severe anxiety ranging from 58–97% across various healthcare disciplines (Brand \u0026amp; Schoonheim-Klein, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hashmat et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This anxiety stems from multiple factors, including the high-stakes nature of the assessment, time constraints, direct observation by examiners, and the unpredictable nature of clinical scenarios (Fidment, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A study by Hadi et al. specifically examined test anxiety among pharmacy students during OSCEs, finding that the majority of the participants reported moderate to severe anxiety, with a significant negative correlation between anxiety levels and OSCE performance (Hadi et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This relationship persisted even after controlling for demographic variables and academic history, highlighting the substantial impact of anxiety on clinical skills demonstration.\u003c/p\u003e\u003cp\u003eAssessment anxiety manifests as a complex interplay of cognitive, emotional, physiological, and behavioral responses that can significantly impair student performance (Zeidner, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Cognitive manifestations include worry thoughts, concentration difficulties, and memory impairment, while emotional and physiological responses encompass feelings of tension, nervousness, and autonomic arousal (Cassady \u0026amp; Johnson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The deleterious effects of excessive anxiety on clinical performance have been well-documented, with studies demonstrating negative correlations between anxiety levels and OSCE scores across multiple healthcare disciplines (Moscaritolo, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Massey et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEducational Frameworks and Intervention Approaches\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEducational frameworks that prioritize the emotional and psychological well-being of healthcare students have become more prominent in recent years, spurred by advancements in understanding the relationship between anxiety and clinical performance (Gebreegziabher et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). With the incorporation of innovative assessment tools such as the OSCE, institutions must adapt their educational approaches to foster environments conducive to learning that minimize anxiety levels. Studies have suggested that well-designed educational interventions can not only reduce anxiety but also enhance clinical practice skills and interprofessional collaboration (Farokhi et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mellor et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Morgan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The theoretical framework for understanding assessment anxiety has evolved from Spielberger's state-trait anxiety distinction to more nuanced multidimensional models (Spielberger, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). Contemporary perspectives conceptualize test anxiety as comprising at least two primary dimensions: emotionality (physiological and affective responses) and worry (cognitive concerns about performance) (Liebert \u0026amp; Morris, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Cassady \u0026amp; Finch, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This bidimensional structure has been consistently supported in the general educational assessment literature, though its applicability to clinical skills examinations remains underexplored (Putwain \u0026amp; Daly, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Recent technological advancements have introduced novel approaches to addressing OSCE anxiety. Ali et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) demonstrated that artificial intelligence-based preparation tools reduced test anxiety and improved performance among pharmacy students during OSCEs (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, the researchers noted that the lack of a psychometrically validated, OSCE-specific anxiety measure limited their ability to precisely quantify intervention effects and identify the most anxiety-provoking aspects of the examination (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasurement Challenges and Needs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite the recognized importance of assessment anxiety in healthcare education, measurement approaches have been inconsistent and often problematic. Many studies have relied on general anxiety measures or ad hoc questionnaires lacking psychometric validation (Longyhore, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Troncon, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Others have employed modified versions of established test anxiety instruments without adequate validation for the specific context of clinical skills assessment (Aboalshamat et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This measurement inconsistency has hindered cross-study comparisons and limited the development of evidence-based interventions to address OSCE anxiety (Warren et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Several validated instruments exist for measuring test anxiety in general educational contexts, including Spielberger's Test Anxiety Inventory (TAI) (Spielberger, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), the Cognitive Test Anxiety Scale (Cassady \u0026amp; Johnson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), and the German Test Anxiety Inventory (Hodapp \u0026amp; Benson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). However, these instruments focus primarily on written examinations and fail to capture the unique stressors associated with performance-based clinical assessments (Furlan et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The few available measures specifically designed for clinical skills assessment contexts, such as the Medical Student Performance Anxiety Scale (Savitsky et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), have demonstrated limited psychometric evidence and narrow applicability across healthcare disciplines.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRationale and Study Objectives\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe development of a psychometrically sound, OSCE-specific anxiety measure represents a critical need in healthcare professional education for several reasons. First, the unique characteristics of OSCEs, including their multistation format, direct observation, time constraints, and clinical performance requirements, create distinctive anxiety triggers not captured by general test anxiety measures (Pitt et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Stunden et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Second, accurate assessment of OSCE-specific anxiety is essential for developing targeted interventions to optimize student performance and well-being (Chamberlain et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Third, a validated measure would facilitate research examining the complex relationships between anxiety, performance, and learning in clinical skills assessment contexts (Turner et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite these compelling needs, no psychometrically validated instrument specifically designed to measure anxiety in OSCE contexts exists across healthcare disciplines. This measurement gap hampers both educational practice and research advancement in this critical area. Therefore, the objective of this study is twofold: to develop an OSCE Anxiety Scale that accurately reflects the unique aspects of anxiety experienced during practical examinations and to validate this scale to ensure reliability and applicability across various healthcare education contexts (Chesser-Smyth \u0026amp; Long, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This scale aims to empower educational institutions to better understand and address the anxiety experienced by healthcare students during OSCE assessments, ultimately improving performance and the quality of care they provide in future practice.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis was a psychometric validation study conducted between May 2024 and May 2025 at the School of Pharmacy, University of Management and Technology, Lahore, Pakistan.\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipants and Sampling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study included all Semester 8–10 students enrolled in the Doctor of Pharmacy (PharmD) over the period of two years, with informed consent. Students with diagnosed anxiety disorders requiring medication or those who had withdrawn from OSCE examinations due to medical reasons were excluded. Sample size adequacy was determined using multiple criteria recommended for factor analysis: (1) a minimum subject-to-variable ratio of 10:1 (Nunnally \u0026amp; Bernstein, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1994\u003c/span\u003e); (2) Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy ≥ 0.80; and (3) minimum sample size of 300 for stable factor solutions (Tabachnick \u0026amp; Fidell, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The final sample of 608 participants exceeded all recommended thresholds.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOSCE Anxiety Scale Development\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOriginal Instrument and Licensing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe OSCE Anxiety Scale was developed by modifying the Test Anxiety Inventory (TAI) developed by Spielberger [Longyhore, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e]. Formal licensing permission was obtained from Mind Garden, Inc. (License to use, modify, and validate the original TAI for OSCE-specific contexts. The license explicitly permitted adaptation of item content, psychometric validation of the modified version, and publication of validation results while maintaining appropriate copyright attribution.\u003c/p\u003e\u003cp\u003e\u003cb\u003eScale Modification Process\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA systematic three-phase approach was employed to adapt the TAI for OSCE contexts:\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhase 1: Content Adaptation\u003c/b\u003e A panel of five experts (three clinical pharmacy faculty members, one psychometrician, and one OSCE coordinator) reviewed each of the 20 original TAI items. Items were modified to replace general \"test\" or \"examination\" terminology with OSCE-specific language while preserving the underlying psychological constructs of emotionality and worry. For example, \"I feel confident and relaxed while taking tests\" was modified to \"I feel confident and relaxed while performing on OSCE stations.\"\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhase 2: Face and Content Validity\u003c/b\u003e The modified items underwent face validity assessment with 15 PharmD students not included in the main study. Content validity was evaluated using the Content Validity Index (CVI), with all items achieving CVI ≥ 0.80. The final 20-item scale maintained the original two-factor structure (Emotionality and Worry subscales) with enhanced OSCE-specific content.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhase 3: Pilot Testing\u003c/b\u003e A pilot study with 15 students was conducted to assess preliminary psychometric properties and identify any comprehension issues. Minor wording adjustments were made based on student feedback to enhance clarity and cultural appropriateness for the Pakistani healthcare education context.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFinal Scale Structure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe OSCE Anxiety Scale comprises 20 items rated on a 4-point Likert scale (1 = Almost Never, 2 = Sometimes, 3 = Often, 4 = Almost Always). The scale includes:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEmotionality subscale\u003c/b\u003e: 8 items measuring physiological and emotional responses (items 2, 8, 9, 10, 11, 15, 16, 18)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWorry subscale\u003c/b\u003e: 8 items assessing cognitive concerns and worry thoughts (items 3, 4, 5, 6, 7, 14, 17, 20)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eAdditional items\u003c/b\u003e: 4 items contributing to total score (items 1, 12, 13, 19)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eItem 1 is reverse-coded, with higher total scores indicating greater OSCE-related anxiety (possible range: 20–80).\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Collection Procedures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eParticipants completed the OSCE Anxiety Scale in a quiet classroom environment immediately before their OSCE examinations at the end of each semester to capture authentic pre-assessment anxiety levels. Trained research assistants administered the questionnaires using standardized instructions to ensure consistency. Demographic information collected included age, gender, academic year, cumulative GPA, and previous OSCE experience. All data were collected anonymously using unique participant codes to ensure confidentiality.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData analysis was conducted using multiple statistical software packages: SPSS version 28 (IBM Corp., Armonk, NY, USA) for data management, preliminary analyses, descriptive statistics, exploratory factor analysis, and known-groups comparisons; R statistical software version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria) for parallel analysis (psych package), McDonald's omega coefficients (psych package), measurement invariance testing (semTools package), and advanced validity assessments; and AMOS version 28 (IBM Corp., Armonk, NY, USA) was utilized for confirmatory factor analysis validation and structural equation modeling procedures. The analytical approach included:\u003c/p\u003e\u003cp\u003e\u003cb\u003ePreliminary Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eData screening for missing values, outliers, and distributional properties\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eDescriptive statistics for all variables\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAssessment of normality using Kolmogorov-Smirnov tests, skewness, and kurtosis values\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFactor Structure Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eExploratory Factor Analysis (EFA)\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eConducted on a randomly selected subsample (n = 365) using principal axis factoring with oblimin rotation. Sampling adequacy was assessed using Kaiser-Meyer-Olkin (KMO) measure and Bartlett's test of sphericity. Factor retention was determined using parallel analysis and scree plot examination.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eConfirmatory Factor Analysis (CFA)\u003c/b\u003e: Performed on the remaining subsample (n = 243) to test the factor structure identified in EFA. Multiple fit indices were evaluated: Chi-square test, Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Good fit criteria: CFI/TLI ≥ 0.95, RMSEA ≤ 0.06, SRMR ≤ 0.08.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReliability Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eInternal consistency was assessed using Cronbach's alpha and McDonald's omega coefficients. Test-retest reliability was evaluated in a subsample that completed the questionnaire twice during the study period.\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidity Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eContent validity\u003c/b\u003e: Expert panel evaluation and Content Validity Index calculation\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eConvergent validity\u003c/b\u003e: Average Variance Extracted (AVE) ≥ 0.50\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDiscriminant validity\u003c/b\u003e: Heterotrait-Monotrait (HTMT) ratio \u0026lt; 0.85\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eKnown-groups validity\u003c/b\u003e: Comparison of anxiety scores across different OSCE experience levels using ANOVA\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCross-validation\u003c/b\u003e: Model replication across independent samples with measurement invariance testing\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMissing Data and Assumptions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eComplete case analysis was employed given the high response rate (100% for included participants). Multivariate normality assumptions were assessed using Mardia's test. All statistical tests used α = 0.05 significance level.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e The study received approval from the Research and Ethics Committee of the University of Management and Technology (Approval #RE-044-2024). All participants provided informed consent after receiving detailed information about the study purpose, procedures, potential risks, and benefits. Participation was voluntary with the right to withdraw at any time without academic penalty. Data confidentiality was maintained through anonymous coding, and all data were stored securely in password-protected files accessible only to the research team. The study was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eParticipant Characteristics and Data Quality\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 608 responses were available for the analysis. All participants provided complete responses across all 20 anxiety items, resulting in zero missing data and a 100% completion rate for included analyses. The mean age of students was 21.5 years (range 20\u0026ndash;23 years). Among the responses, 292 (48%) were from male students and 316 (52%) were from female students; The average GPA was 3.1 (range 2.4\u0026ndash;3.9). Initial data screening revealed no univariate or multivariate outliers, supporting the integrity of the response patterns (Tabachnick \u0026amp; Fidell, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDescriptive Statistics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eItem means ranged from 2.39 (Item 1: reverse-coded confidence item) to 2.59 (Item 11: feeling tense), indicating optimal utilization of the 4-point response scale with no floor or ceiling effects. Standard deviations ranged from 1.09 to 1.14, demonstrating good variability for psychometric analysis. All skewness values were within acceptable limits (\u0026plusmn;\u0026thinsp;2.0), and kurtosis values indicated appropriate distributional properties for factor analysis (Kline, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e). Complete descriptive statistics for all 20 items are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComplete Descriptive Statistics for OSCE Anxiety Scale Items (n\u0026thinsp;=\u0026thinsp;608)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSkewness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKurtosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eK-S p\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI feel confident and relaxed while performing on OSCE stations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.39 (1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.089\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhile taking the OSCE exam, I have an uneasy, upset feeling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.49 (1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThinking about my grade in the OSCE interferes with my performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.41 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI freeze up on OSCE stations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.48 (1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring the OSCE exam, I find myself worrying about my education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.49 (1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe harder I work at performing on an OSCE station, the more confused I get\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.55 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.069\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThoughts of doing poorly on OSCE stations interfere with my concentration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.49 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI feel very nervous and shaky when performing on an OSCE station\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.49 (1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEven when I'm well prepared for an OSCE station, I feel very nervous about it\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.48 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI start feeling very uneasy just before receiving feedback on an OSCE station\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.43 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring the OSCE exam, I feel very tense\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.59 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI wish the OSCE exam did not bother me so much\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.52 (1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring OSCE stations, I am so tense that my stomach gets upset\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.58 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.075\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI feel like I get in my own way and mess up during OSCE stations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.46 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI feel very panicky when I perform on an OSCE station\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.46 (1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.080\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI worry a great deal before performing in the OSCE exam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.49 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring OSCE stations, I find myself thinking about the consequences of failing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.51 (1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI feel my heart beating very fast during OSCE stations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.44 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfter the OSCE is over, I try to stop worrying about it, but I can't\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.43 (1.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuring the OSCE exam, I get so nervous that I forget facts I really know\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.56 (1.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Reverse-coded item. Higher scores indicate greater anxiety. Note: K-S\u0026thinsp;=\u0026thinsp;Kolmogorov-Smirnov test of normality; all distributions acceptable for factor analysis\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eFactor Structure Determination\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eModel Comparison\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo establish the optimal factor structure, a comprehensive series of nested models was compared using confirmatory factor analysis. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;1 present the comparison results. The two-factor correlated model demonstrated significantly superior fit compared to all alternative models: χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.17, CFI\u0026thinsp;=\u0026thinsp;.983, TLI\u0026thinsp;=\u0026thinsp;.980, RMSEA\u0026thinsp;=\u0026thinsp;.021 [.012, .029], SRMR\u0026thinsp;=\u0026thinsp;.033. Although the three-factor model showed marginal statistical improvement (Δχ\u0026sup2; = 4.33, Δdf\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;.116), it lacked theoretical justification and contained factors with fewer than three items (Brown, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, the two-factor correlated model was retained as optimal.\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\u003eModel Comparison: Alternative Factor Structures\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eχ\u0026sup2; (df)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eχ\u0026sup2;/df\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTLI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRMSEA [90% CI]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSRMR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eΔχ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eΔdf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle Factor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e756.24 (170)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.101 [.094, .108]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSingle Factor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTwo-Factor (Correlated)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e198.45 (169)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.021 [.012, .029]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e573.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eTwo-Factor (Correlated)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThree-Factor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e178.91 (167)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.048 [.034, .061]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eThree-Factor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: Two-factor correlated model retained as optimal. Complete model comparison in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 1.\u003c/b\u003e Model Comparison: Fit Indices Across Alternative Factor Structures\u003c/p\u003e\u003cp\u003e[INSERT FIGURE 1 HERE]\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e\u003cem\u003eTwo-factor correlated model (highlighted in green) demonstrates a superior fit. CFI values shown as bars, Lower RMSEA values indicate a better fit. Green dashed line: Excellent fit threshold (CFI\u0026thinsp;\u0026ge;\u0026thinsp;.95). Orange dashed line: Good fit threshold (CFI\u0026thinsp;\u0026ge;\u0026thinsp;.90).\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eConfirmatory Factor Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFigure 2 presents the confirmatory factor analysis path diagram showing the final validated structure. All factor loadings were statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and substantial in magnitude, ranging from .567 to .724 for the Emotionality factor and .584 to .689 for the Worry factor. Squared multiple correlations indicated that the factors explained 32\u0026ndash;52% of item variance, demonstrating adequate to strong relationships between items and their respective factors. The correlation between factors was φ\u0026thinsp;=\u0026thinsp;.583 (SE\u0026thinsp;=\u0026thinsp;.051, CR\u0026thinsp;=\u0026thinsp;11.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), confirming a moderate positive association that supports the theoretical conceptualization of related but distinct anxiety dimensions. This correlation magnitude is below the .85 threshold that would indicate poor discriminant validity (Fornell \u0026amp; Larcker, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), supporting the two-factor structure. Detailed factor loading results are presented in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 2.\u003c/b\u003e Confirmatory Factor Analysis Path Diagram for OSCE Anxiety Scale\u003c/p\u003e\u003cp\u003e[INSERT FIGURE 2 HERE]\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e\u003cem\u003eStandardized factor loadings shown. All loadings significant at p\u0026thinsp;\u0026lt;\u0026thinsp;.001. Ellipses represent latent factors, rectangles represent observed variables, circles represent error terms. Dashed green line shows interfactor correlation (.58). Model demonstrates excellent fit across all indices.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExploratory Factor Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrior to confirmatory analysis, sampling adequacy was confirmed through Kaiser-Meyer-Olkin measure (.889) and Bartlett's test of sphericity (χ\u0026sup2; = 4,247.3, df\u0026thinsp;=\u0026thinsp;190, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Kaiser, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Principal axis factoring with oblimin rotation revealed a clear two-factor structure supported by parallel analysis (Horn, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1965\u003c/span\u003e) and scree plot criteria Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The two-factor solution explained 53.5% of total variance, with Factor 1 (Emotionality) accounting for 36.2% and Factor 2 (Worry) contributing 17.3%. Complete EFA results are presented in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReliability Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCronbach's alpha coefficients demonstrated excellent internal consistency for all scales (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The Emotionality subscale achieved α\u0026thinsp;=\u0026thinsp;.915 (95% CI [.902, .928]), the Worry subscale α\u0026thinsp;=\u0026thinsp;.856 (95% CI [.837, .875]), and the total scale α\u0026thinsp;=\u0026thinsp;.932 (95% CI [.923, .941]), all exceeding thresholds for clinical applications (Nunnally \u0026amp; Bernstein, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). McDonald's omega coefficients closely matched alpha values (.916, .857, and .933, respectively), supporting tau-equivalence assumptions (McDonald, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Figure\u0026nbsp;3 illustrates the reliability coefficients across scale components.\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\u003eScale Reliability and Descriptive Statistics\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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\u003cp\u003eScale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eα [95% CI]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eωₜ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotionality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.915 [.902, .928]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.29 (6.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u0026ndash;31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.856 [.837, .875]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.91 (5.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u0026ndash;27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal of Subscales*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.932 [.923, .941]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e46.23 (14.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20\u0026ndash;80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: α\u0026thinsp;=\u0026thinsp;Cronbach's alpha; ωₜ = McDonald's omega total. Comprehensive reliability analysis in Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e* The total scale uses all 20 items, while the two subscales use 16 items (8 each)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 3.\u003c/b\u003e Internal Consistency Reliability by Scale Component\u003c/p\u003e\u003cp\u003e[INSERT FIGURE 3 HERE]\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e\u003cem\u003eAll reliability coefficients exceed recommended thresholds for both research and clinical applications. Cronbach's α and McDonald's ω values are nearly identical, supporting tau-equivalence assumptions. Red line indicates minimum for clinical use, orange line indicates minimum for research use.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidity Evidence\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eConvergent and Discriminant Validity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAverage Variance Extracted (AVE) exceeded .50 for both factors (Emotionality\u0026thinsp;=\u0026thinsp;.587, Worry\u0026thinsp;=\u0026thinsp;.513), meeting criteria for adequate convergent validity (Hair et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The heterotrait-monotrait ratio of correlations (HTMT) yielded .642 (90% CI [.589, .695]), below the conservative .85 threshold, providing strong evidence for discriminant validity (Henseler et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eKnown-Groups Validity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnalysis of variance revealed significant differences in anxiety levels across OSCE experience, F(2, 605)\u0026thinsp;=\u0026thinsp;18.74, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u0026sup2; = .058. Students with no OSCE experience (M\u0026thinsp;=\u0026thinsp;51.2, SD\u0026thinsp;=\u0026thinsp;15.1) reported significantly higher anxiety than those with 1\u0026ndash;2 OSCEs (M\u0026thinsp;=\u0026thinsp;45.8, SD\u0026thinsp;=\u0026thinsp;13.9) and 3\u0026thinsp;+\u0026thinsp;OSCEs (M\u0026thinsp;=\u0026thinsp;42.1, SD\u0026thinsp;=\u0026thinsp;12.7), with all pairwise differences significant (ps\u0026thinsp;\u0026lt;\u0026thinsp;.001, Tukey HSD) (Field, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Figure\u0026nbsp;4 illustrates these group differences, supporting construct validity through expected relationships with experience.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 4.\u003c/b\u003e Known-Groups Validity: OSCE Anxiety by Experience Level\u003c/p\u003e\u003cp\u003e[INSERT FIGURE 4 HERE]\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e\u003cem\u003eHigher OSCE experience is associated with significantly lower anxiety scores, supporting known-groups validity. All pairwise comparisons significant at p\u0026thinsp;\u0026lt;\u0026thinsp;.001 (Tukey HSD). Error bars represent\u0026thinsp;\u0026plusmn;\u0026thinsp;1 standard error. *** indicates p\u0026thinsp;\u0026lt;\u0026thinsp;.001 significance level.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCross-Validation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe two-factor model was successfully replicated in an independent validation subsample (n\u0026thinsp;=\u0026thinsp;243), demonstrating excellent fit stability: χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.24, CFI\u0026thinsp;=\u0026thinsp;.978, TLI\u0026thinsp;=\u0026thinsp;.974, RMSEA\u0026thinsp;=\u0026thinsp;.032 [.018, .045], SRMR\u0026thinsp;=\u0026thinsp;.037. Multi-group invariance testing supported configural, metric, and scalar invariance across independent samples (Cheung \u0026amp; Rensvold, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Complete cross-validation results are presented in Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study aimed to develop and validate a psychometrically sound instrument specifically designed to measure anxiety related to OSCEs in healthcare education. Our comprehensive psychometric evaluation revealed a robust two-factor structure for the OSCE Anxiety Scale (OAS), comprising Emotionality and Worry dimensions, with excellent reliability and validity indicators across multiple assessment methods. The findings demonstrate that the OAS possesses strong internal consistency, clear factor structure, and good construct validity, making it a valuable tool for both educational research and practical applications in healthcare professional education. The instrument's ability to differentiate between students with varying levels of OSCE experience further supports its utility in identifying those who may benefit from targeted interventions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFactor Structure and Psychometric Properties\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe two-factor correlated model demonstrated superior fit compared to alternative models, supporting the conceptualization of OSCE anxiety as comprising distinct but related emotional and cognitive components. This bidimensional structure aligns with contemporary test anxiety theory, particularly Liebert and Morris's (Liebert \u0026amp; Morris, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1967\u003c/span\u003e) conceptualization of anxiety as consisting of emotionality (physiological arousal) and worry (cognitive concerns). Our findings extend this theoretical framework to the specific context of clinical skills assessment, suggesting that the fundamental structure of assessment anxiety remains consistent across different evaluation formats, despite the unique characteristics of OSCEs.\u003c/p\u003e\u003cp\u003eThe correlation between Emotionality and Worry factors suggests these dimensions, while conceptually distinct, are moderately interrelated in the OSCE context. This correlation is comparable to those reported in general test anxiety measures (Hodapp \u0026amp; Benson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) but somewhat higher than correlations found in written examination contexts (Spielberger, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Liebert \u0026amp; Morris, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1967\u003c/span\u003e). This stronger relationship may reflect the distinctive nature of OSCEs, where the physical performance aspect intensifies the connection between physiological arousal and cognitive concerns. As Fidment (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) noted in a qualitative study, the physical manifestations of anxiety during OSCEs (trembling hands, racing heart) directly impact clinical skill performance, creating a more pronounced interplay between emotional and cognitive anxiety components than in written assessments.\u003c/p\u003e\u003cp\u003eThe excellent fit indices of our two-factor model surpass those reported for other healthcare assessment anxiety measures. For instance, the German Test Anxiety Inventory validation in medical students reported lower fit values (Hodapp \u0026amp; Benson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). This superior fit likely stems from our instrument's specific focus on OSCE contexts and the rigorous development process involving expert input and pilot testing.\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.2. Reliability and Internal Consistency\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe OAS demonstrated exceptional internal consistency for both subscales and the total score, with Cronbach's alpha and McDonald's omega coefficients exceeding .85. These values surpass the recommended thresholds for both research and clinical applications (Kline, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e). Particularly noteworthy is the high reliability of the Emotionality subscale, which exceeds that reported for emotionality components in general test anxiety measures (Spielberger, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Hodapp \u0026amp; Benson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). This enhanced reliability may reflect the pronounced and consistent nature of physiological anxiety responses in the high-stakes, performance-based OSCE environment. Our reliability coefficients compare favorably with those reported for other healthcare assessment anxiety measures. White (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported lower reliability for a nursing clinical decision-making anxiety scale, while Hadi et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found moderate reliability for a modified test anxiety inventory used with pharmacy students. The superior reliability of the OAS underscores the value of developing context-specific assessment tools rather than adapting general measures.\u003c/p\u003e\u003cp\u003e\u003cb\u003eKnown-Groups Validity and Experience Effect\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe significant difference in anxiety scores across experience levels provides compelling evidence for the OAS's known-groups validity. Students with no OSCE experience reported the highest anxiety levels, followed by those with moderate experience, and those with extensive experience. This pattern aligns with previous research demonstrating anxiety reduction with increased exposure to clinical assessments (Yusoff, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Regehr et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Brand and Schoonheim-Klein (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) similarly found that dental students' anxiety decreased with repeated OSCE exposures, though they used general anxiety measures rather than OSCE-specific instruments.\u003c/p\u003e\u003cp\u003eThe moderate effect size for experience level suggests that while experience influences OSCE anxiety, other factors also contribute substantially. This finding is consistent with Massey et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who found that while preparation interventions reduced OSCE anxiety, baseline individual differences remained influential. The persistence of anxiety even among experienced students highlights that OSCE anxiety is not merely a product of unfamiliarity but represents a complex psychological response that may require targeted interventions beyond simple exposure.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFactor Loadings and Item Performance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe factor loading patterns revealed strong item-factor relationships, with all items loading substantially on their respective factors. The emotionality items showed particularly robust loadings, suggesting these physiological manifestations are highly characteristic of the OSCE anxiety experience. This finding aligns with qualitative research by Fidment (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), who identified physical anxiety symptoms as particularly salient in students' OSCE narratives. The slightly lower but still substantial loadings for worry items reflect the cognitive dimension's more varied manifestations. Notably, item 7 (\"Thoughts of doing poorly interfere with concentration\") showed the highest loading on the worry factor, highlighting the centrality of performance-related cognitive interference in OSCE anxiety. This finding parallels Cassady and Johnson's (2002) identification of cognitive interference as a key mechanism through which anxiety impairs performance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparison with Other Assessment Contexts\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur findings suggest that while OSCE anxiety shares the fundamental bidimensional structure of general test anxiety, it has distinctive characteristics. The higher correlation between emotionality and worry factors compared to written test anxiety measures (Spielberger, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Liebert \u0026amp; Morris, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1967\u003c/span\u003e) suggests a more integrated anxiety response in performance-based assessments. This aligns with Zeidner's (2005) conceptualization of performance anxiety as involving a more pronounced interaction between physiological arousal and cognitive processes than traditional test anxiety.\u003c/p\u003e\u003cp\u003eThe factor structure of the OAS more closely resembles that of performance anxiety measures in other domains than general academic test anxiety measures. For instance, the Performance Anxiety Inventory for Musicians shows a similar two-factor structure with comparable factor correlations (Osborne \u0026amp; Kenny, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This similarity suggests that OSCE anxiety may have more in common with performance anxiety in arts and sports than with anxiety about written academic tests, highlighting the unique nature of performance-based assessment in healthcare education.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications for Educational Practice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe validation of the OAS has several important implications for healthcare education. First, it provides educators with a reliable tool to identify students experiencing excessive OSCE anxiety, enabling targeted interventions. The subscale structure allows for differentiation between predominantly physiological anxiety (high emotionality) and cognitive anxiety (high worry), which may require different intervention approaches. For instance, students with high emotionality scores might benefit more from relaxation techniques and simulation exposure, while those with high worry scores might respond better to cognitive restructuring and study skills training (Maloney et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSecond, the known-groups validity findings suggest that structured exposure to OSCE formats may be an effective anxiety-reduction strategy. Educational programs could incorporate progressive OSCE-like experiences throughout the curriculum rather than concentrating high-stakes OSCEs at specific timepoints. This approach aligns with recent research by Gebreegziabher et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), who found that distributed clinical practice opportunities reduced nursing students' anxiety levels. Third, the development of the OAS enables more precise evaluation of educational interventions targeting OSCE anxiety. Previous intervention studies have been limited by the lack of psychometrically sound, OSCE-specific anxiety measures (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The availability of the OAS will facilitate more rigorous assessment of intervention efficacy and comparative effectiveness research.\u003c/p\u003e\u003cp\u003eFourth, the instrument could serve as a valuable tool for curriculum development and evaluation. By systematically measuring OSCE anxiety levels across different stages of healthcare education programs, institutions can identify potential areas for improvement in their assessment approaches and preparatory strategies. This data-driven approach to curriculum refinement could lead to more student-centered assessment practices that maintain rigor while minimizing unnecessary anxiety. Finally, the OAS could facilitate cross-institutional and cross-disciplinary research on assessment anxiety in healthcare education. The availability of a standardized, psychometrically sound measure enables meaningful comparisons across different healthcare disciplines, educational contexts, and cultural settings, potentially leading to more generalizable insights about the nature and management of clinical assessment anxiety.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeveral limitations warrant consideration. First, the study was conducted at a single institution with pharmacy students, potentially limiting generalizability to other healthcare disciplines and cultural contexts. Future research should validate the OAS across diverse healthcare programs and international settings. Second, while the study demonstrated excellent internal consistency and structural validity, predictive validity regarding actual OSCE performance was not assessed. Examining the relationship between OAS scores and OSCE outcomes represents an important direction for future research. Third, the study design precludes conclusions about causal relationships between experience and anxiety levels. Longitudinal studies tracking anxiety trajectories throughout healthcare education programs would provide more definitive evidence regarding anxiety development and change over time. Finally, the study did not explore potential moderators of OSCE anxiety, such as personality traits, learning styles, or previous academic performance. Investigating these factors would enhance understanding of individual differences in OSCE anxiety susceptibility.\u003c/p\u003e\u003cp\u003eFuture research should explore the effectiveness of targeted interventions based on students' anxiety profiles, examine the relationship between OAS scores and objective performance metrics, and investigate the potential application of the OAS in formative assessment and educational program evaluation. Additionally, developing abbreviated versions of the scale for rapid assessment in time-constrained educational settings would enhance its practical utility.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe OAS represents a significant contribution to the field of healthcare education assessment, demonstrating excellent psychometric properties and a clear two-factor structure reflecting the emotional and cognitive dimensions of anxiety in clinical skills assessment contexts. The scale's strong reliability and validity evidence support its use in healthcare education research and practice, providing educators with a valuable tool for identifying students at risk of performance impairment due to excessive anxiety and evaluating the effectiveness of educational interventions. As healthcare education continues to emphasize competency-based assessment through OSCEs and similar performance-based methods, the availability of psychometrically sound, context-specific measurement tools like the OAS will be increasingly important for supporting student well-being and optimizing learning outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the participants for their participation in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMA conceptualized and designed the study. EC collected the data. Both authors contributed to the data analysis and interpretation, as well as the drafting, revision, and reviewing of the manuscript. Both authors approved the final manuscript prior to submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any internal or external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used for this study are not openly available due to participant confidentiality and consent reasons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Research and Ethics Committee of the University of Management and Technology (Approval #RE-044-2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman ethics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants at the start of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have nothing to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAboalshamat, K., Hou, X. 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Plenum.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"OSCE, anxiety, psychometric validation, healthcare education, assessment","lastPublishedDoi":"10.21203/rs.3.rs-7020710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7020710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective Structured Clinical Examinations (OSCEs) are widely used to assess clinical competencies in healthcare education, but they often induce significant anxiety that may impair student performance. Despite the prevalence of OSCE-related anxiety, no psychometrically validated instrument exists to specifically measure this construct across healthcare disciplines. This study aimed to develop and validate the OSCE Anxiety Scale (OAS), a psychometrically sound instrument for measuring anxiety related to OSCEs in healthcare education. This psychometric validation study included 608 pharmacy students. The OAS was developed by modifying Spielberger's Test Anxiety Inventory for OSCE contexts through expert panel review, content validation, and pilot testing. Factor structure was assessed using exploratory and confirmatory factor analyses. Reliability was evaluated through internal consistency measures (Cronbach's alpha and McDonald's omega). Validity was examined through content, convergent, discriminant, and known-groups approaches. Confirmatory factor analysis supported a two-factor structure comprising Emotionality and Worry dimensions (χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;1.17, CFI\u0026thinsp;=\u0026thinsp;.983, TLI\u0026thinsp;=\u0026thinsp;.980, RMSEA\u0026thinsp;=\u0026thinsp;.021, SRMR\u0026thinsp;=\u0026thinsp;.033). The OAS demonstrated excellent internal consistency for the Emotionality subscale (α\u0026thinsp;=\u0026thinsp;.915, ω\u0026thinsp;=\u0026thinsp;.916), Worry subscale (α\u0026thinsp;=\u0026thinsp;.856, ω\u0026thinsp;=\u0026thinsp;.857), and total scale (α\u0026thinsp;=\u0026thinsp;.932, ω\u0026thinsp;=\u0026thinsp;.933). Convergent validity was supported by Average Variance Extracted values exceeding .50 for both factors. Discriminant validity was confirmed through heterotrait-monotrait ratio analysis (HTMT\u0026thinsp;=\u0026thinsp;.642). Known-groups validity was demonstrated by significant differences in anxiety levels across OSCE experience groups (F(2, 605)\u0026thinsp;=\u0026thinsp;18.74, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), with anxiety decreasing as experience increased. The OSCE Anxiety Scale is a reliable and valid instrument for measuring anxiety in clinical skills assessment contexts. Its robust psychometric properties support its use in healthcare education, research and practice. The scale enables identification of students experiencing excessive OSCE anxiety and facilitates evaluation of educational interventions designed to reduce assessment anxiety and improve clinical performance.\u003c/p\u003e","manuscriptTitle":"Performance Under Pressure: Development and Validation of the OSCE Anxiety Scale for Healthcare Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 11:02:34","doi":"10.21203/rs.3.rs-7020710/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b6facad5-dcc8-4390-bc16-90ade5a8f186","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-16T16:53:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 11:02:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7020710","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7020710","identity":"rs-7020710","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}