Construct validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS)

Construct validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS) | 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 Construct validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS) Mesadeh Irak-Suárez, Claudio-Alberto Rodríguez-Suárez, Candelaria de la Merced Díaz-González, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7155035/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Currently, there is no gold standard scale for assessing academic satisfaction among undergraduate nursing students. The aim of this study was to evaluate the construct-structural validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS), as well as to assess the academic satisfaction of undergraduate nursing students at the University of Las Palmas de Gran Canaria (ULPGC). Methods A cross-sectional study was conducted among nursing students at ULPGC, Spain. Model fit indicators were examined using confirmatory factor analysis (CFA) for both the original four-factor model and a unidimensional model. Additionally, a new three-factor model was tested through exploratory factor analysis (EFA). Internal consistency reliability was evaluated. Bivariate analysis was performed using chi-square, U-Mann-Whitney, and Kruskal-Wallis tests. For each association, effect sizes were calculated using biserial rank correlation and Kelley’s squared Epsilon measure. Descriptive and inferential analyses (p < 0.05) were performed using Jamovi (v.2.3.28). Factor analysis and model reliability were carried out using FACTOR© (Release 12.06.08, x64). The study was approved by the Research Ethics Committee (No. 2023-499-1). Results A total of 226 students participated (n = 226), showing a high level of satisfaction (M = 163.30 [156.70–163.90]; SD = 27.24). Sample adequacy for factor analysis was excellent (KMO = 0.925 [95%CI: 0.868–0.932]; Bartlett’s test: p < 0.001). The unidimensional model showed poor fit (RMSEA = 0.100 [95%CI: 0.094–0.101]). The three-factor model yielded RMSEA = 0.050 [95%CI: 0.047–0.050] and the four-factor model RMSEA = 0.049 [95%CI: 0.047–0.051]; however, the three-factor model was closer to Kelley’s criterion (RMSR = 0.0533 [95%CI: 0.053–0.053], expected RMSR = 0.066). Internal consistency reliability was excellent for the three-factor model (F1: α = 0.948, ω = 0.949; F2: α = 0.910, ω = 0.911; F3: α = 0.900, ω = 0.899) and good for the four-factor model (F1: α = 0.905, ω = 0.906; F2: α = 0.948, ω = 0.949; F3: α = 0.897, ω = 0.897; F4: α = 0.718, ω = 0.610). Conclusions The Spanish version of the UNSASS scale demonstrated multidimensionality, with the three-factor model showing a better fit and excellent internal consistency. ULPGC students reported high levels of satisfaction, with “Clinical Teaching” being the most highly rated factor. Personal Satisfaction Students Nursing Education Nursing Education Nursing Diploma Programs Academic Success 1 Background The training of students during the Undergraduate Nursing Degree (UND) includes a curriculum designed to organize both content and professional competencies [ 1 ] with the goal of providing knowledge, skills, and abilities necessary for professional practice. It also aims to develop competencies for problem-solving, effective communication, critical thinking, and adherence to ethical principles and professional responsibilities [ 2 , 3 ]. However, the key element for achieving professional excellence lies in students’ academic engagement, understood as a multidimensional process that encompasses behavioral, emotional, cognitive, motivational [ 4 ], and affective aspects through a dynamic pursuit of deep learning [ 5 ]. Likewise, social support has a positive effect on students by enhancing their academic engagement through motivation [ 6 ], without overlooking the role of instructors as facilitators who provide feedback aimed at increasing educational involvement and fostering professional autonomy [ 7 ]. On the other hand, the university support network is not limited to faculty alone, but also includes administrative staff and personnel from other general services. Although the curriculum and social support influence students’ academic engagement during their academic training related to theoretical learning, limitations in the availability of teaching resources may also negatively affect their learning process. For instance, inadequate classroom furniture, lack of technical and simulation materials in laboratory settings, limited space, and high student-to-tutor ratios are all factors that may hinder the study environment and reduce academic satisfaction during theoretical instruction [ 8 ]. In addition, clinical training in healthcare institutions can vary greatly depending on the characteristics of different clinical environments, the variability in working dynamics, and the shifting work conditions of nursing staff—all of which can also significantly impact students’ satisfaction with their nursing education. Satisfaction is a psychological state derived from the comparison between expectations and actual experiences [ 9 ], which includes pleasurable responses from clients regarding the services provided by an organization. It is a key element in assessing service quality [ 10 ]. In the context of higher education, students are considered clients and universities are the organizations responsible for ensuring their satisfaction [ 11 ]. Accordingly, academic satisfaction can be understood as the students’ personal perspective on the educational content of the program, available resources, and the support received from both academic and administrative staff [ 1 , 12 ]. However, satisfaction is also influenced by other factors such as the learning environment, the responsibilities of both instructors and students, assessment approaches, student motivation, and classroom diversity [ 13 ]. Despite numerous studies linking these factors with academic satisfaction, there is no clear consensus on which ones have the greatest influence, highlighting the need for further research into this educational experience [ 1 ]. Despite the diversity between countries, nursing curricula typically include theoretical classes, laboratory practice—including simulation activities—and clinical placements in real healthcare settings. These modalities require the reorganization of students into smaller groups, and in the case of clinical practice, the presence of a supervising tutor responsible for personalized oversight of student performance in small groups [ 13 , 14 ]. Therefore, academic satisfaction in nursing programs should be evaluated comprehensively, differentiating between theoretical teaching, lab-based learning, and clinical practice—without neglecting the academic program, institutional resources, and the support provided by the university, faculty, and administrative personnel [ 15 ]. All of these elements, when properly integrated, promote educational excellence [ 1 ] and foster greater student participation and engagement [ 13 , 16 ]. Various tools have been developed in the literature to assess the learning environment of nursing students [ 16 ]. For example, Chen et al. developed the Nursing Student Satisfaction Scale (NSSS), composed of four subscales: “Curriculum” (9 items), “Faculty” (8 items), “Social Interaction” (6 items), and “Learning Environment” (7 items), using a 6-point Likert scale ranging from 1 (not satisfied) to 6 (very satisfied), with excellent reliability (α = 0.96) [ 17 ]. However, the NSSS does not assess other relevant aspects related to the clinical setting, resources, or institutional support, which are also important for a comprehensive evaluation of nursing students’ satisfaction. In contrast, Asadizaker et al. developed the First Clinical Practical Education (SFCPE) instrument, which focuses solely on the clinical domain and lacks items related to classroom teaching [ 18 ]. Other authors have used alternative approaches, such as Barraza and Ortiz, who employed the Quality of Life and Satisfaction (Q-LES-Q) instrument to assess quality of life in undergraduate nursing students [ 19 ]. Because existing instruments do not cover all factors influencing nursing students’ satisfaction with their undergraduate education, several authors have attempted to develop new tools that allow for more complete and specific assessments. In 2012, Dennison and El-Masri developed the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS), structured into four subscales: “In-Class Teaching,” “Clinical Teaching,” “Program Design and Delivery,” and “Support and Resources,” with excellent internal consistency (α = 0.96) [ 15 ], and validated in several international contexts [ 20 , 21 ]. Guerra-Martín et al. [ 22 ] translated, culturally adapted, and conducted a confirmatory factor analysis (CFA) of the Spanish version of the UNSASS, naming it the Escala de Satisfacción Académica del Estudiante de Enfermería (ESAEE). They reported high reliability values, with Cronbach’s alpha coefficients above α = 0.90 for each of the four subscales. However, these authors did not report model fit indices or the sample size used for the CFA. For this reason, and in order to clarify the structure of the Spanish version of the UNSASS (ESAEE) and provide additional evidence of its reliability and validity, the main objective of this study was to evaluate the construct validity and reliability of the Spanish version of the UNSASS. A secondary objective was to assess the academic satisfaction of nursing students at the University of Las Palmas de Gran Canaria (ULPGC). 2 Method 2.1. Design A cross-sectional descriptive observational study was conducted to obtain a validation sample, following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 23 ]. 2.2. Study Population and Context The population consisted of third- and fourth-year nursing students enrolled in the Undergraduate Nursing Degree (UND) program across the three campuses of the University of Las Palmas de Gran Canaria (ULPGC). A total of 430 students were enrolled in the 2023/2024 academic year (n = 430), distributed as follows: 268 students at the Gran Canaria campus, 82 at the Fuerteventura campus, and 80 at the Lanzarote campus. 2.3. Inclusion and Exclusion Criteria The inclusion criterion was being enrolled as a third- or fourth-year UND student during the 2023/2024 academic year. Students participating in academic mobility programs (e.g., SICUE, Erasmus) during the study period were excluded. 2.4. Sample Size Based on the recommendations of Ferrando et al. [ 24 ] and Hair et al. [ 25 ], a minimum sample size of 200 participants was established to ensure the feasibility of conducting a factor analysis (FA). 2.5. Study Variables, Instruments, and Data Collection The following sociodemographic variables were collected: Gender (female, male, prefer not to answer), Campus (Gran Canaria, Fuerteventura, Lanzarote), Academic year (third, fourth), and Age (in years, quantitative variable). The administered instrument was the Spanish version of the ESAEE scale [ 20 ], which contains 48 items organized into four subscales: In-Class Teaching (items nº 1 to nº 16), Clinical Teaching (items nº 17 to nº 31), “Program Design and Delivery” (items nº 32 to nº 43) y “Support & Resources” (items nº 44 to nº 48). Each item uses a five-point Likert scale, where a score of 1 indicates “strongly disagree” and a score of 5 indicates “strongly agree.” Thus, higher scores reflect greater levels of satisfaction. The total score ranges from 48 (minimum satisfaction) to 240 (maximum satisfaction). Subscales-specific scores can also be calculated by summing the scores of the corresponding items. The instrument was administered via an online questionnaire using the Google Forms® platform, distributed through the institutional email addresses of eligible students. The data collection period extended from December 2023 to March 2024. 2.6. Statistical Analysis Strategy 2.6.1. Descriptive Analysis A descriptive statistical analysis was performed. Categorical variables were expressed as frequencies and percentages, and quantitative variables using means and standard deviations. Based on the total score of the scale, five levels of satisfaction were established: very low (48–86), low (87–124), moderate (125–162), high (163–200), and very high (201–240). To allow comparisons across dimensions, scores were normalized using the Min-Max scaling technique with the formula: Xnorm = (X – Xmin) / (Xmax – Xmin). 2.6.2. Structural Construct Validity and Internal Consistency Reliability To assess the structural construct validity of the ESAEE instrument, a factor analysis (FA) was conducted. Means, standard deviations, skewness, and kurtosis were calculated for each item. According to Mardia’s test, a Pearson correlation matrix was used for the FA. After evaluating the Measure of Sampling Adequacy (MSA) (values of MSA below 0.500 suggest that the item does not measure the same domain as the remaining items in the pool), overall data adequacy was assessed using the Kaiser-Meyer-Olkin (KMO) index and Bartlett’s test of sphericity. Values above 0.75 for KMO and p ≤ 0.05 for Bartlett’s test were considered acceptable [ 24 – 26 ]. Factor extraction was performed using Unweighted Least Squares (ULS) with PROMIN oblique rotation. Bootstrapping was used to calculate 95% confidence intervals for item scores and model measures. Model fit was evaluated using the Root Mean Square of Residuals (RMSR), Root Mean Square Error of Approximation (RMSEA), Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), and Goodness of Fit Index (GFI). An RMSR value of 0.05 was considered an acceptable fit, and RMSEA values below 0.05 were considered a good fit, while values between 0.05–0.08 were considered a reasonable fit. NNFI and CFI values ≥ 0.95, and GFI values > 0.90 were regarded as indicators of good model fit. For RMSR, Kelley’s criterion was used, in which the RMSR is compared to the typical error of a correlation of 0 in the population [ 24 , 27 ]. The Bayesian Information Criterion (BIC) was also used to compare model solutions. The analysis strategy involved performing a confirmatory factor analysis (CFA) of the initial four-factor model proposed by Guerra-Martín et al. [ 22 ] (using a semi-specified matrix) and a unidimensional model. Additionally, to assess unidimensionality, the following indices were used: Unidimensional Congruence (UniCo), Explained Common Variance (ECV), and Mean of Item Residual Absolute Loadings (MIREAL). UniCo values above 0.95, ECV values above 0.85, and MIREAL values below 0.30 indicate that the data may be considered essentially unidimensional [ 28 ]. Since parallel analysis suggested a possible three-factor solution, an exploratory factor analysis (EFA) was conducted to assess the fit of this proposed three-factor model. The consistency of the factors in each model was assessed using the Overall Reliability of fully-Informative prior Oblique N-EAP scores (ORION) and the Factor Determinacy Index (FDI) [ 29 ]. The Sensitivity Ratio (SR) and Expected Percentage of True Differences (EPTD) were also calculated. SR reflects the number of distinct factor levels that can be differentiated based on the estimated factor scores. EPTD refers to the estimated percentage of differences between observed and true factor scores that are in the same direction. Recommended values are FDI > 0.90, Oblique N-EAP scores > 0.80, SR > 2, and EPTD > 90% [ 28 ]. Finally, reliability (internal consistency) was assessed using McDonald's Omega and Cronbach’s Alpha coefficients, with 95% confidence intervals calculated for both. 2.6.3. Bivariate Analysis The Kolmogorov-Smirnov test indicated non-normal distribution for quantitative variables; therefore, the non-parametric Mann-Whitney U test was used to compare means between two groups, and the Kruskal-Wallis test for comparisons involving more than two groups. In the latter case, Dwass-Steel-Critchlow-Fligner (DSCF) post hoc tests were applied. To assess differences between categorical variables, the Chi-square test (χ²) was used. For each association examined, the effect size was calculated: for the Mann-Whitney U test, it was measured using the rank-biserial correlation, and for the Kruskal-Wallis test, Kelley’s squared epsilon was applied. Coefficients between 0.10 and 0.30 were interpreted as small effect sizes, between 0.30 and 0.50 as medium, and values greater than 0.50 as large effect sizes [ 30 ]. Descriptive and inferential analyses were conducted using Jamovi software (version 2.3.28), with statistical significance set at p < 0.05. Factor analysis and model reliability assessments were performed using FACTOR© software (Release 12.06.08, x64). 2.7. Ethical Considerations Authorization was obtained from the original authors (Date: October 31, 2023) to use the Spanish version of the ESAEE scale, as well as from the corresponding Dean’s Office at the University of Las Palmas de Gran Canaria (ULPGC). The study was conducted in accordance with the Declaration of Helsinki. Although the questionnaire was anonymous, participants were informed about the general aspects of the study, including its aims and characteristics. Prior to accessing the questionnaire, participants had to accept an informed consent form. This research was approved by the Research Ethics Committee (CEI/CEIm) of Hospital Dr. Negrín, Las Palmas (approval number: 2023-499-1). 3 Results 3.1. Sample Description The response rate was 52.5%. A total of 226 students (n = 226), with a mean age of 24.03 years (SD = 7.09), participated in the study. Among the participants, 82.3% (n = 186) identified as female and 17.7% (n = 40) as male. Of the total, 58.0% (n = 131) were in their third year of study, and 42.0% (n = 95) were in their fourth year. Regarding campus affiliation, 73.9% (n = 167) were from the Gran Canaria campus, 16.8% (n = 38) from the Fuerteventura campus, and 9.3% (n = 21) from the Lanzarote campus. Table 1 shows the frequencies and percentages of the variables considered by campus. Statistically significant differences were found between campuses for the academic year variable (p = 0.010), as well as for age (Table 1 ). Table 1 Socio-demographic variables and differences between groups according to the campuses. Variable Total n = 226 (100%) Campus Gran Canaria n = 167 (73.9%) Campus Fuerteventura n = 38 (16.8%) Campus Lanzarote n = 21 (9.3%) n (%) n (%) n (%) n (%) p-value 1 Gender p = 0.588 Women 186 (82.3%) 136 (60.2%) 31 (13.7%) 19 (8.4%) Men 40 (17.7%) 31 (13.7%) 7 (3.1%) 2 (0.9%) Academic year p = 0.010* 3rd year 131 (58%) 99 (43.8%) 26 (11.5%) 6 (2.7%) 4th year 95 (42%) 68 (30.1%) 12 (5.3%) 15 (6.6%) p-value 3 Age 2 M (SD) M (SD) M (SD) M (SD) p = 0.120 24.03 (7.09) 23.7 (6.66) 26.5 (9.76) 22 (1.97) 1 p-value obtained with Chi-Square; 2 expressed in means and standard deviations; 3 p-value obtained with Kruskall Wallis * Statistically significant p-value. 3.2 Structural Construct Validity and Internal Consistency Reliability Descriptive item analysis is shown in Table 2 . Table 2 Descriptive analysis of the items and values of Measure of Sampling Adequacy Variable M [CI95%] 1 SD 2 Skewness Kurtosis Normed MSA 3 [CI95%] Item 1. I can freely express my academic and other concerns to faculty members 3.29 [3.12–3.46] 1.01 -0.129 -0.500 0.876 [0.697–0.904] Item 2. Faculty members are easily approachable 3.23 [3.07–3.38] 0.90 -0.163 -0.237 0.933 [0.837–0.939] Item 3. Faculty members make every effort to assist students when asked 3.21 [3.05–3.37] 0.93 -0.534 0.167 0.951 [0.837–0.944] Item 4. Faculty members make an effort to understand difficulties I might be having with my course work 2.88 [2.73–3.03] 0.86 -0.267 -0.144 0.934 [0.818–0.937] Item 5. Faculty members are usually available after class and during office hours 3.39 [3.23–3.54] 0.91 -0.532 0.293 0.949 [0.808–0.943] Item 6. I can freely express my academic and other concerns to the administration 3.26 [3.08–3.44] 1.08 -0.192 -0.501 0.948 [0.839–0.949] Item 7. Faculty are fair and unbiased in their treatment of individual students 3.00 [2.82–3.19] 1.08 -0.267 -0.686 0.868 [0.627–0.901] Item 8. Faculty members provide adequate feedback about students’ progress in a course 2.98 [2.82–3.14] 0.94 -0.225 -0.342 0.923 [0.791–0.928] Item 9. I receive detailed feedback from faculty members on my work and written assignments 2.81 [2.64–2.99] 1.02 0.051 -0.723 0.880 [0.666–0.901] Item 10. Channels for expressing students’ complaints are readily available 2.71 [2.52–2.89] 1.08 0.134 -0.717 0.920 [0.735–0.918] Item 11. Faculty members are good role models and motivate me to do my best 2.99 [2.83–3.15] 0.96 -0.284 -0.282 0.923 [0.824–0.936] Item 12. The administration shows concern for students as individuals 2.44 [2.24–2.64] 1.17 0.651 -0.334 0.896 [0.696–0.905] Item 13. Faculty members demonstrate a high level of knowledge in their subject area 4.00 [3.85–4.15] 0.88 -0.931 1.104 0.938 [0.824–0.940] Item 14. Faculty members take the time to listen/discuss issues that may impact my academic performance 2.82 [2.66–2.99] 0.96 0.056 -0.504 0.955 [0.859–0.951] Item 15. Faculty members create a good overall impression 3.55 [3.40–3.70] 0.88 -0.736 0.739 0.957 [0.865–0.953] Item 16. I am generally given enough time to understand the things I have to learn 3.06 [2.89–3.22] 0.98 -0.491 -0.240 0.932 [0.814–0.938] Item 17. Clinical instructors are approachable and make students feel comfortable about asking questions 3.77 [3.59–3.95] 1.03 -0.745 0.239 0.907 [0.816–0.925] Item 18. Clinical instructors provide feedback at appropriate times, and do not embarrass me in front of others (classmates, staff, patients and family members) 3.64 [3.46–3.82] 1.07 -0.759 0.182 0.936 [0.841–0.940] Item 19. Clinical instructors are open to discussions and difference in opinions 3.61 [3.43–3.79] 1.05 -0.673 0.067 0.942 [0.862–0.949] Item 20. Clinical instructors give me sufficient guidance before I perform technical skills 3.63 [3.45–3.80] 1.03 -0.729 0.133 0.920 [0.817–0.936] Item 21. Clinical instructors view my mistakes as part of my learning 3.69 [3.50–3.89] 1.12 0.873 0.138 0.941 [0.859–0.940] Item 22. Clinical instructors give me clear ideas of what is expected from me during a clinical rotation 3.73 [3.54–3.91] 1.11 -0.712 -0.182 0.950 [0.860–0.949] Item 23. Clinical instructors facilitate my ability to critically assess my client’s needs 3.61 [3.43–3.79] 1.04 -0.714 0.205 0.935 [0.841–0.941] Item 24. Clinical instructors assign me to patients that are appropriate for my level of competence 3.53 [3.33–3.73] 1.17 -0.614 -0.298 0.945 [0.826–0.944] Item 25. Clinical instructors give me verbal and written feedback concerning my clinical experience 3.65 [3.46–3.83] 1.07 -0.630 -0.115 0.930 [0.827–0.935] Item 26. Clinical instructors demonstrate a high level of knowledge and clinical expertise 4.03 [3.87–4.19] 0.94 -1.160 1.616 0.949 [0.839–0.949] Item 27. Clinical instructors are available when needed 3.58 [3.41–3.75] 1.00 -0.690 0.441 0.935 [0.828–0.941] Item 28. Clinical instructors provide enough opportunities for independent practice in the lab and clinical sites 3.59 [3.41–3.77] 1.06 -0.663 0.024 0.940 [0.829–0.940] Item 29. Clinical instructors encourage me to link theory to practice 3.79 [3.64–3.94] 0.88 -0.675 0.585 0.955 [0.855–0.949] Item 30. Instructions are consistent among different clinical and lab instructors 3.33 [3.14–3.51] 1.08 -0.403 -0.419 0.951 [0.842–0.949] Item 31. Faculty members behave professionally 3.93 [3.78–4.07] 0.86 -1.062 2.001 0.964 [0.867–0.958] Item 32. This program provides a variety of good and relevant courses 3.04 [2.88–3.19] 0.92 -0.446 -0.346 0.911 [0.771–0.919] Item 33. The program enhances my analytical skills 3.30 [3.15–3.44] 0.87 -0.531 0.220 0.927 [0.816–0.933] Item 34. Most courses in this program are beneficial and contribute to my overall professional development 3.43 [3.29–3.57] 0.82 -0.490 0.295 0.930 [0.779–0.931] Item 35. The quality of instruction I receive in my classes is good and helpful 3.28 [3.14–3.42] 0.84 -0.608 0.599 0.950 [0.837–0.953] Item 36. I usually have a clear idea of what is expected of me in this program 3.40 [3.26–3.55] 0.86 -0.624 0.429 0.918 [0.786–0.931] Item 37. The program is designed to facilitate team work among students 3.43 [3.27–3.60] 0.96 -0.624 0.179 0.902 [0.760–0.920] Item 38. The program enhances my problem solving or critical thinking skills 3.31 [3.17–3.46] 0.85 -0.559 0.274 0.903 [0.773–0.924] Item 39. There is a commitment to academic excellence in this program 3.27 [3.11–3.44] 0.95 -0.416 -0.033 0.904 [0.750–0.920] Item 40. As a result of my courses, I feel confident about dealing with clinical nursing problems 3.01 [2.83–3.18] 1.03 -0.240 -0.643 0.908 [0.771–0.923] Item 41. Going to class helps me better understand the material 3.47 [3.27–3.67] 1.17 -0.471 -0.591 0.911 [0.768–0.923] Item 42. I am able to experience intellectual growth in the program 3.59 [3.43–3.75] 0.96 -0.772 0.602 0.914 [0.807–0.923] Item 43. Overall, the program requirements are reasonable and achievable 3.52 [3.38–3.66] 0.81 -0.763 1.138 0.947 [0.847–0.948] Item 44. The secretaries are caring and helpful 2.94 [2.74–3.13] 1.15 0.015 -0.679 0.829 [0.675–0.862] Item 45. The secretaries behave professionally 3.59 [3.42–3.75] 0.98 -0.481 0.109 0.865 [0.720–0.893] Item 46. Support at the clinical and computer labs is readily available 2.96 [2.78–3.13] 1.02 -0.216 -0.477 0.857 [0.684–0.885] Item 47. Computer and clinical labs are well equipped, adequately staffed, and are readily accessible to meet 2.80 [2.61–2.98] 1.09 -0.046 -0.757 0.797 [0.591–0.843] Item 48. The facilities (class rooms, clinical and computer labs) facilitate my learning 3.23 [3.06–3.41] 1.05 -0.177 -0.343 0.885 [0.659–0.903] 1: Mean [Confident Inteval 95%]/ 2: Standard Deviation/ 3: Measure of Sampling Adequacy All MSA values were above the 0.500 threshold. The KMO index and Bartlett’s test of sphericity (n = 226) indicated excellent sampling adequacy (KMO = 0.925 [95%CI: 0.868–0.932]; Bartlett’s test p ≤ 0.001). The expected RMSR according to Kelley’s criterion for an acceptable model was 0.066. The unidimensionality analysis produced the following results: UniCo = 0.958 [95%CI: 0.945–0.978], ECV = 0.790 [95%CI: 0.740–0.850], MIREAL = 0.272 [95%CI: 0.235–0.300], indicating that the results were inconclusive regarding essential unidimensionality. Two CFAs were initially performed (a four-factor model and a unidimensional model). Since the parallel analysis suggested a three-factor solution, an EFA was also conducted to assess the fit of this model. Fit indices for the three models tested through FA are presented in Table 3 , along with reliability indices for the factors in each model. Table 3 Fit and reliability indices of the factors of the models tested EFA Three Factor Model CFA Four Factor Model CFA One Factor Model RMSEA[95%CI] 1 0.050 [0.047–0.050] 0.049 [0.047–0.051] 0.100 [0.094–0.101] X 2 (p) 2 1543.532 (P = 0.000010) 1452.597 (p = 0.000010) 3527.202 (p = 0.000010) NNFI [95%CI] 3 0.978 [0.975–0.987] 0.979 [0.972–0.987] 0.910 [0.908–0.933] CFI [95%CI] 4 0.980 [0.978–0.989] 0.982 [0.976–0.989] 0.914 [0.912–0.935] GFI [95%CI] 5 0.979 [0.956–0.981] 0.985 [0.966–0.987] 0.921 [0.857–0.943] BIC[95%CI] 6 2584.275 [2525.265- 2590.831] 2753.526 [2715.601-2797.043] 4047.573 [3854.761- 4068.997] RMSR [95%CI] 7 0.0533 [0.053–0.053] 0.0461 [0.036–0.036] 0.1046 [0.092 0.111] F1 Satisfaction with Clinical Teaching F2 Satisfaction with Faculty and Human Resources F3 Satisfaction with Academic Program and Support Resources F1 In-Class Teaching F2 Clinical Teaching F3 Program Design and Delivery F4 Support & Resources F1 Proportion of Variance 33.92% 9.24% 5,14% 33.92% 9.24% 5,14% 3.84% 33.92% % Cumulative Proportion of Variance 33.92% 43.16% 48.30% 33.92% 43.16% 48.30% 52.14% 33.92% Factor Determinacy Index (FDI) 0.977 0.965 0.955 0.961 0.977 0.962 0.914 0.980 ORION marginal reliability 0.954 0.930 0.912 0.924 0.954 0.926 0.835 0.961 Sensitivity ratio (SR) a 4.554 3.656 3.213 3.483 4.567 3.548 2.253 4.943 Expected percentage of true differences (EPTD) b 95.6% 94.1% 93.1% 61.7% 64.7% 61.9% 58.1% 96.1% [Confident Inteval 95%] 1:Root Mean Square Error of Approximation/2:LOSEFER empirically corrected Chi-square/3:Non-Normed Fit Index/4: Comparative Fit Index/5: Goodness of Fit Index/6: Schwarz s Bayesian Information Criterion/7: Root Mean Square of Residuals a = The sensitivity ratio (SR) can be interpreted as the number of different factor levels than can be differentiated on the basis of the factor score estimates. b = expected percentage of true differences (EPTD) is the estimated percentage of differences between the observed factor score estimates that are in the same direction as the corresponding true differences. If factor scores are to be used for individual assessment, FDI values above 0.90, marginal reliabilities above 0.80, SR above 2, and EPTDs above 90% are recommended. Fit coefficients for the three- and four-factor models were very similar, with RMSEA values of 0.050 [95%CI: 0.047–0.050] and 0.049 [95%CI: 0.047–0.051], respectively. However, the three-factor model had a slightly lower BIC and a RMSR value closer to Kelley’s criterion (RMSR = 0.0533 [95%CI: 0.053–0.053] versus RMSR = 0.0461 [95%CI: 0.036–0.036]). Although reliability coefficients (FDI, ORION, and SR) were adequate for both models, the three-factor model showed clearly superior values in terms of EPTD. In contrast, the unidimensional model showed poor fit indices (RMSEA = 0.100 [95%CI: 0.094–0.101]), supporting the suitability of adopting a multidimensional model, consistent with the unidimensionality analysis. The rotated matrix with the factor loadings for the newly proposed three-factor model is shown in Table 4 . Table 4 Factor loadings of the matrix after rotation of the three-factor model Items Factor 1 Satisfaction with Clinical Teaching Factor 2 Satisfaction with Faculty and Human Resources Factor 3 Satisfaction with Academic Program and Support Resources Item 1 0.514 [0.284–0.698] Item 2 0.711 [0.593–0.856] Item 3 0.679 [0.532–0.830] Item 4 0.722 [0.550–0.902] Item 5 0.537 [0.371–0.743] Item 6 0.744 [0.597–0.920] Item 7 0.411 [0.078–0.633] Item 8 0.584 [0.451–0.781] Item 9 0.530 [0.340–0.699] Item 10 0.441 [0.225–0.616] Item 11 0.544 [0.330–0.719] Item 12 0.685 [0.446-0.900] Item 13 0.395 [0.095–0.603] Item 14 0.653 [0.522–0.814] Item 15 0.421 [0.171–0.592] Item 16 0.697 [0.550–0.902] Item 17 0.754 [0.653–0.857] Item 18 0.796 [0.687–0.894] Item 19 0.840 [0.773–0.921] Item 20 0.743 [0.629–0.836] Item 21 0.867 [0.801–0.952] Item 22 0.766 [0.670–0.850] Item 23 0.807 [0.708–0.891] Item 24 0.663 [0.495–0.788] Item 25 0.775 [0.559–0.871] Item 26 0.759 [0.666–0.865] Item 27 0.757 [0.643–0.857] Item 28 0.693 [0.554–0.802] Item 29 0.640 [0.520–0.749] Item 30 0.553 [0.419–0.697] Item 31 0.575 [0.368–0.714] Item 32 0.597 [0.387–0.813] Item 33 0.685 [0.499–0.892] Item 34 0.804 [0.656–0.977] Item 35 0.580 [0.408–0.784] Item 36 0.484 [0.272–0.692] Item 37 0.344 [0.139–0.518] Item 38 0.642 [0.489–0.872] Item 39 0.565 [0.375–0.783] Item 40 0.497 [0.344–0.750] Item 41 0.409 [0.178–0.635] Item 42 0.521 [0.205–0.755] Item 43 0.437 [0.194–0.622] Item 44 0.739 [0.474–1.001] Item 45 0.623 [0.330–0.861] Item 46 0.425 [0.252–0.572] Item 47 0.425 [0.252–0.572] Item 48 0.425 [0.252–0.572] [Confident Inteval 95%] This model retains all items from the original Clinical Teaching dimension (items 17–31) within Factor 1. Factor 2 includes all items from In-Class Teaching (items 1–16), plus items 44 and 45, excluding item 13. Factor 3 incorporates the remaining items, originally from Program Design and Delivery and Support & Resources. In this model, no item had cross-loadings above 0.400 in more than one factor, except for item 13, which had a loading of 0.395. Based on item distribution, the factors were renamed as follows: Factor 1 – Satisfaction with Clinical Teaching (items 17–31); Factor 2 – Satisfaction with Faculty and Human Resources (items 1–12, 14–16, 44, and 45); Factor 3 – Satisfaction with Academic Program and Support Resources (item 13, items 32–43, 46–48). Finally, regarding internal consistency reliability, Table 5 presents the values of Cronbach’s Alpha and McDonald’s Omega coefficients for both the three- and four-factor models. Table 5 Values of cronbach's alpha and omega coefficients of the three- and four-factor models. Three Factor Model Four Factor Model Factor 1 Satisfaction with Clinical Teaching Factor 2 Satisfaction with Faculty and Human Resources Factor 3 Satisfaction with Academic Program and Support Resources Factor 1 In-Class Teaching Factor 2 Clinical Teaching Factor 3 Program Design and Delivery Factor 4 Support & Resources Coeficiente Alfa de Cronbach (α) α = 0.948 [0.935–0.961] α = 0.910 [0.889–0.931] α = 0.900 [0.874–0.927] α = 0.905 [0.883–0.927] α = 0.948 [0.935–0.961] α = 0.897 [0.869–0.924] α = 0.718 [0.647–0.789] Coeficiente Omega de MacDonald (Ω) ω = 0.949 [0.939 − 0.938] ω = 0.911 [0.894–0.928] ω = 0.899 [0.880–0.919] ω = 0.906 [0.888–0.924] ω = 0.949 [0.939–0.958] ω = 0.897 [0.877–0.917] ω = 0.610 [0.537–0.682] [Confident Inteval 95%] 3.3 Analysis of Nursing Students’ Satisfaction at ULPGC The overall mean score on the ESAEE scale indicated a high level of satisfaction (M = 163.30 [156.70–163.90]; SD = 27.24). The scores obtained for each factor were as follows: Factor 1 (M = 55.10 [53.50–56.60]; SD = 11.81), Factor 2 (M = 52.20 [50.70–53.60]; SD = 10.85), and Factor 3 (M = 53.00 [51.80–54.30]; SD = 9.59). The normalized mean values were Xnorm = 1.00 for Factor 1, Xnorm = 0.00 for Factor 2, and Xnorm = 0.28 for Factor 3. Bivariate analysis revealed statistically significant differences according to gender in Item 8 (p = 0.023) and Item 16 (p = 0.002), as shown in Supplementary File 1. Regarding the academic year, statistically significant differences were found in Item 8 (p = 0.021), Item 13 (p = 0.043), Item 24 (p = 0.040), Item 33 (p = 0.001), Item 39 (p = 0.004), and in Factor 3 (p = 0.049), as shown in Supplementary File 2. As for the campus variable, significant differences were found in the following comparisons: Item 2 GC–FTV (p < 0.001); Item 3 GC–FTV (p = 0.016); Item 6 GC–FTV (p < 0.001), GC–LNZ (p = 0.037), FTV–LNZ (p = 0.007); Item 7 FTV–LNZ (p = 0.047); Item 11 GC–FTV (p = 0.043); Item 12 GC–FTV (p < 0.001), FTV–LNZ (p = 0.013); Item 14 GC–FTV (p = 0.008), GC–LNZ (p = 0.012); Item 16 GC–FTV (p = 0.005); Item 44 GC–FTV (p < 0.001), FTV–LNZ (p < 0.001); Item 45 GC–FTV (p < 0.001), FTV–LNZ (p < 0.001); Item 46 GC–FTV (p < 0.001), FTV–LNZ (p = 0.022); Item 47 GC–FTV (p < 0.001); Item 48 GC–FTV (p = 0.015), GC–LNZ (p = 0.010); and Factor 2 GC–FTV (p < 0.001), as detailed in Supplementary File 3. 4 Discussion A large number of scales have been developed to assess nursing students’ satisfaction [ 16 , 21 ]. However, according to Rahmatpour et al. [ 21 ], these instruments do not meet “excellent” quality standards across all psychometric properties, as defined by the COSMIN initiative [ 31 ]. Therefore, no single robust and valid instrument currently exists that is considered the gold standard for measuring student satisfaction [ 21 ]. This is applicable to the UNSASS scale. Although it was one of the first instruments developed to assess nursing student satisfaction, we believe that the information provided on its structure and psychometric properties in both the original and subsequent validation studies has been insufficient. For example, in the original study by Dennison and El-Masri, the initial development of the scale was presented, and face, content, and construct validity, as well as internal consistency reliability, were assessed in a sample of 313 Canadian students [ 15 ]. However, construct validity was only examined through exploratory factor analysis (EFA), meaning the originally proposed four-factor structure—subsequently adopted in other studies [ 20 , 22 ]—was not formally tested using confirmatory factor analysis (CFA), and no fit indices were reported. Victor et al. [ 20 ], in their study conducted in Pakistan, directly adopted this model without formally validating it for their context, performing only a pretest with 10 students. More recently, the study by Guerra-Martín et al. [ 22 ] in Spain attempted to confirm this four-factor model via CFA, but again no fit indices were reported. The claim of good model fit was based solely on factor loadings above 0.4, which is an oversimplified interpretation [ 32 ]. Perhaps the most rigorous validation of the UNSASS to date is the Iranian version by Rahmatpour et al. [ 21 ], which provided more detailed evidence on its structure, using a sample of 237 students for EFA and 200 for CFA. Their three-factor model (named “University factors”, “Clinical factors”, and “Faculty factors”) yielded acceptable fit indices (RMSEA = 0.052; CFI = 0.918). Although we did not perform a CFA in our study, our results are aligned in indicating better fit for a three-factor model over the four-factor version, and we also observed greater reliability for the factors. Regarding item clustering, our findings also closely resemble those reported by Rahmatpour et al. [ 21 ]. Two key considerations must be acknowledged when evaluating the various factor analyses conducted with UNSASS. First, most validations used methodological approaches that are now considered outdated. For instance, the original study by Dennison and El-Masri [ 15 ] used the common but discouraged method of principal component extraction and Varimax rotation—an approach also employed by Guerra-Martín et al. [ 22 ]. This methodology does not adequately distinguish between common and specific variance, which may compromise the construct validity of scales, although it remains widely used [ 24 , 32 ]. Second, the influence of sample size on factor analysis results must be considered. While most validations—including the present study—have been conducted with sample sizes ranging from sufficient (n = 200) to very good (n = 500) [ 33 , 34 ], factors such as sample variability, ambiguous items, or restricted response ranges should be considered when determining adequate sample size for factor analysis [ 24 , 32 , 35 ]. In our case, although the sample size was considered sufficient and sampling adequacy was excellent (KMO > 0.90), it did not allow us to perform a CFA, following the recommendation to use different samples for EFA and CFA [ 24 ]. Therefore, a CFA remains pending to confirm the proposed three-factor structure of the Spanish version of UNSASS. In our study, factor reliability was assessed using multiple coefficients, including ORION Marginal Reliability (Overall Reliability of fully Informative prior Oblique N-EAP scores), Sensitivity Ratio (SR), and Expected Percentage of True Differences (EPTD) [ 28 ]. The ORION coefficient, an IRT-based alternative to Cronbach’s alpha, measures the precision of estimated latent scores for each factor. Values close to 1.00 indicate very high reliability, with values above 0.80 considered acceptable. Unlike Cronbach’s alpha, ORION does not require assumptions of tau-equivalence or factor independence [ 28 ]. SR (ratio of true score variance to measurement error) assesses the instrument’s ability to discriminate between individuals with different true scores; values above 2 indicate good sensitivity. EPTD estimates the proportion of observed score differences that reflect true differences rather than measurement error. Values above 90% are desirable, indicating strong discriminative fidelity. Although not yet widely used, these indices should be considered standard practice for high-quality psychometric evaluations. We also calculated classic internal consistency indicators such as Cronbach’s alpha and McDonald’s omega [ 36 ]. Although Cronbach’s alpha has been increasingly criticized, it remains the most commonly used index for internal consistency. McDonald’s omega is now recognized as a more robust alternative [ 37 – 39 ]. In our study, both coefficients were calculated to allow comparison with previous validations. Only Rahmatpour et al. [ 21 ] reported omega in their study, and similarly to our results, they obtained coefficients above 0.900 for the three model dimensions, supporting strong internal consistency. With regard to the application of the instrument, our students’ overall satisfaction was high (M = 163.30; SD = 27.24), although lower than that observed in Canada [ 15 ] (M = 175.12; SD = 25.88). Global results could not be compared with other applications of UNSASS [ 20 – 22 ] due to the absence of total and subscale scores in those studies. After normalizing the means, the highest satisfaction was found in Factor 1 “Satisfaction with Clinical Teaching” (Xnorm = 1.00), while the lowest was in Factor 2 “Satisfaction with Faculty and Human Resources” (Xnorm = 0.00). Normalized means could not be compared due to our restructured three-factor model. However, in the Canadian study [ 15 ], the highest satisfaction was for “In-Class Teaching” (Xnorm = 1.00), and the lowest for “Support and Resources” (Xnorm = 0.00). In this regard, mentoring programs have been shown to enhance educational outcomes and increase satisfaction among both students and faculty [ 40 , 41 ]. The highest-rated items were Item 26 “Clinical instructors demonstrate a high level of knowledge and clinical expertise” (M = 4.03; SD = 0.94) and Item 13 “Faculty members demonstrate a high level of knowledge in their subject area” (M = 4.00; SD = 0.88), reflecting students’ high appreciation of faculty knowledge [ 41 ]. Nonetheless, improvements in curriculum structure, evaluation strategies, teaching resources, and alumni follow-up systems are needed to improve educational quality [ 42 ]. The lowest-rated item was Item 12 “The administration shows concern for students as individuals” (M = 2.44; SD = 1.17). Transformational leadership experiences in organizational culture have shown promise in promoting significant changes in institutional systems and staff dynamics, which are crucial for effective transformation [ 43 , 44 ]. Although some statistically significant differences were observed based on gender and academic year, the most relevant influence was that of the ULPGC campus. This variable is relevant because, for example, the GC campus has a larger student-to-classroom ratio. As noted by Walker et al. [ 41 ], smaller class sizes improve faculty-student interaction and enhance the learning process. Likewise, the smaller clinical hospitals associated with the FTV campus are linked to reduced faculty workload and fewer assigned students, allowing for more personalized teaching, more effective learning, and greater student motivation [ 8 ]. According to Cant and Gazula [ 1 ], student interaction with peers and university staff—especially faculty—directly influences motivation and engagement in learning. Among the limitations of this study, the most significant was the sample size used for the analysis of construct validity. Although the KMO index indicated excellent sampling adequacy, the sample did not allow for a CFA, following the recommendation to use separate samples for EFA and CFA. A CFA using an independent sample remains necessary to confirm the proposed three-factor structure of the Spanish version of the UNSASS instrument. One of the strengths of this study lies in the rigorous analysis of structural construct validity, employing fit indices and statistical tests that provide evidence of the instrument’s multidimensionality and support the proposal of a new three-factor model. Additionally, the estimation of reliability through internal consistency using McDonald’s omega—considered a more robust alternative to Cronbach’s alpha—is noteworthy, along with the calculation of additional reliability coefficients for the model’s factors. 5 Conclusions This study contributes to improving the understanding of the psychometric properties of the Spanish version of the UNSASS scale, confirming it as a valid and reliable instrument for assessing nursing students' satisfaction in the Spanish context. A multidimensional model is proposed for the Spanish version of the UNSASS scale, showing a better fit for a three-factor model compared to the classic four-factor structure, along with excellent internal consistency. The satisfaction of ULPGC students was high, with the “Clinical Teaching” factor standing out as the most highly rated subscale. Declarations Ethics approval and consent to participate. Participants provided informed consent before completing the questionnaire. The study was approved by the Research Ethics Committee of Hospital Dr. Negrín, Las Palmas (approval number: 2023-499-1). Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Clinical trial declaration Not applicable. Authors' contributions Conceptualization: M.IS, CA.RS, H.GT; Data curation; M.IS, CA.RS; Formal analysis: CA.RS, H.GT; Investigation: M.IS, CM.DG, M.RH; Methodology: M.IS, CA.RS, H.GT; Software: CA.RS, H.GT; Supervision: CA.RS; Validation: H.GT; Visualization: M.IS, CM.DG, M.RH; Writing – original draft: M.IS, CA.RS, H.GT, CM.DG, M.RH; Writing – review & editing; CA.RS, H.GT, CM.DG. Acknowledgements The authors thank all the students for their participation in this study. References Cant R, Gazula S, Ryan C. Predictors of nursing student satisfaction as a key quality indicator of tertiary student’s education experience: An integrative review. Nurse Educ Today. 2023;126:1–9. https://doi.org/10.1016/j.nedt.2023.105806 . Alhassan A, Duke M, Phillips NM. Nursing students’ satisfaction with the quality of clinical placement and their perceptions of preceptors competence: A prospective longitudinal study. Nurse Educ Today. 2024;133:1–3. https://doi.org/10.1016/j.nedt.2023.106081 . 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[A journey around alpha and omega to estimate internal consistency reliability]. Anal Psicol. 2017;33(3):755–82. https://dx.doi.org/10.6018/analesps.33.3.268401 . Sijtsma K, Pfadt J, Part II. On the use, the misuse, and the very limited usefulness of Cronbach’s alpha: discussing lower bounds and correlated errors. Psychometrika. 2021;86(4):843–60. https://doi.org/10.1007/s11336-021-09789-8 . Lim S, Xin Min L, Chan CJW, Dong Y, Mikkonen K, Zhou W. Peer mentoring programs for nursing students: A mixed methods systematic review. Nurse Educ Today. 2022;119:105577. https://doi.org/10.1016/j.nedt.2022.105577 . Walker S, Rossi D, Anastasi J, Gray-Ganter G, Tennent R. Indicators of undergraduate nursing students’ satisfaction with their learning journey: An integrative review. Nurse Educ Today. 2016;43:40–8. http://dx.doi.org/10.1016/j.nedt.2016.04.011 . Yildirim M, Sahin M. Evaluating undergraduate nursing education and student competencies: a mixed-methods study using the input-process-output framework. BMC Nurs. 2025;24(1):760. https://doi.org/10.1186/s12912-025-03358-5 . Springer PJ, Clark CM, Strohfus P, Belcheir M. Using transformational change to improve organizational culture and climate in a school of nursing. J Nurs Educ. 2012;51(2):81–8. https://doi.org/10.3928/01484834-20111230-02 . Amin SM, El-Sayed AAI, Othman AA, Ali AS, ELfeshawy NI, El-Sherbini HH, Mahmoud AAF, Atta MHR. Transforming nursing education: the power of educational leadership in optimizing time management and competency. BMC Nurs. 2025;24(1):870. https://doi.org/10.1186/s12912-025-03420-2 . Additional Declarations No competing interests reported. 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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-7155035","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":490373221,"identity":"17a807e3-6cad-44d1-b2b4-5aaae418204c","order_by":0,"name":"Mesadeh Irak-Suárez","email":"","orcid":"","institution":"Hospital Universitario Insular de Gran Canaria","correspondingAuthor":false,"prefix":"","firstName":"Mesadeh","middleName":"","lastName":"Irak-Suárez","suffix":""},{"id":490373222,"identity":"cef2cc28-0197-49b1-9ec8-48d76692c8b8","order_by":1,"name":"Claudio-Alberto Rodríguez-Suárez","email":"data:image/png;base64,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","orcid":"","institution":"Hospital Universitario Insular de Gran Canaria","correspondingAuthor":true,"prefix":"","firstName":"Claudio-Alberto","middleName":"","lastName":"Rodríguez-Suárez","suffix":""},{"id":490373223,"identity":"352371ce-79be-48d1-935f-bff1f86f3b44","order_by":2,"name":"Candelaria de la Merced Díaz-González","email":"","orcid":"","institution":"University of Las Palmas de Gran Canaria","correspondingAuthor":false,"prefix":"","firstName":"Candelaria","middleName":"de la Merced","lastName":"Díaz-González","suffix":""},{"id":490373224,"identity":"667e5fc7-3caa-4467-ad53-8b077aca56cc","order_by":3,"name":"Milagros De la Rosa-Hormiga","email":"","orcid":"","institution":"University of Las Palmas de Gran Canaria","correspondingAuthor":false,"prefix":"","firstName":"Milagros","middleName":"De la","lastName":"Rosa-Hormiga","suffix":""},{"id":490373226,"identity":"b5b7cbb5-597e-4926-b642-9a2d4bd2ccb1","order_by":4,"name":"Héctor González-de la Torre","email":"","orcid":"","institution":"University of Las Palmas de Gran Canaria","correspondingAuthor":false,"prefix":"","firstName":"Héctor","middleName":"González-de la","lastName":"Torre","suffix":""}],"badges":[],"createdAt":"2025-07-18 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16:11:32","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":30107,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7155035/v1/9322cb1f4f6508822b94cae5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Construct validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS)","fulltext":[{"header":"1 Background","content":"\u003cp\u003eThe training of students during the Undergraduate Nursing Degree (UND) includes a curriculum designed to organize both content and professional competencies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] with the goal of providing knowledge, skills, and abilities necessary for professional practice. It also aims to develop competencies for problem-solving, effective communication, critical thinking, and adherence to ethical principles and professional responsibilities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, the key element for achieving professional excellence lies in students\u0026rsquo; academic engagement, understood as a multidimensional process that encompasses behavioral, emotional, cognitive, motivational [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and affective aspects through a dynamic pursuit of deep learning [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Likewise, social support has a positive effect on students by enhancing their academic engagement through motivation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], without overlooking the role of instructors as facilitators who provide feedback aimed at increasing educational involvement and fostering professional autonomy [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOn the other hand, the university support network is not limited to faculty alone, but also includes administrative staff and personnel from other general services. Although the curriculum and social support influence students\u0026rsquo; academic engagement during their academic training related to theoretical learning, limitations in the availability of teaching resources may also negatively affect their learning process. For instance, inadequate classroom furniture, lack of technical and simulation materials in laboratory settings, limited space, and high student-to-tutor ratios are all factors that may hinder the study environment and reduce academic satisfaction during theoretical instruction [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition, clinical training in healthcare institutions can vary greatly depending on the characteristics of different clinical environments, the variability in working dynamics, and the shifting work conditions of nursing staff\u0026mdash;all of which can also significantly impact students\u0026rsquo; satisfaction with their nursing education.\u003c/p\u003e\u003cp\u003eSatisfaction is a psychological state derived from the comparison between expectations and actual experiences [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], which includes pleasurable responses from clients regarding the services provided by an organization. It is a key element in assessing service quality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the context of higher education, students are considered clients and universities are the organizations responsible for ensuring their satisfaction [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Accordingly, academic satisfaction can be understood as the students\u0026rsquo; personal perspective on the educational content of the program, available resources, and the support received from both academic and administrative staff [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, satisfaction is also influenced by other factors such as the learning environment, the responsibilities of both instructors and students, assessment approaches, student motivation, and classroom diversity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite numerous studies linking these factors with academic satisfaction, there is no clear consensus on which ones have the greatest influence, highlighting the need for further research into this educational experience [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the diversity between countries, nursing curricula typically include theoretical classes, laboratory practice\u0026mdash;including simulation activities\u0026mdash;and clinical placements in real healthcare settings. These modalities require the reorganization of students into smaller groups, and in the case of clinical practice, the presence of a supervising tutor responsible for personalized oversight of student performance in small groups [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, academic satisfaction in nursing programs should be evaluated comprehensively, differentiating between theoretical teaching, lab-based learning, and clinical practice\u0026mdash;without neglecting the academic program, institutional resources, and the support provided by the university, faculty, and administrative personnel [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. All of these elements, when properly integrated, promote educational excellence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and foster greater student participation and engagement [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eVarious tools have been developed in the literature to assess the learning environment of nursing students [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For example, Chen et al. developed the \u003cem\u003eNursing Student Satisfaction Scale\u003c/em\u003e (NSSS), composed of four subscales: \u0026ldquo;Curriculum\u0026rdquo; (9 items), \u0026ldquo;Faculty\u0026rdquo; (8 items), \u0026ldquo;Social Interaction\u0026rdquo; (6 items), and \u0026ldquo;Learning Environment\u0026rdquo; (7 items), using a 6-point Likert scale ranging from 1 (not satisfied) to 6 (very satisfied), with excellent reliability (α\u0026thinsp;=\u0026thinsp;0.96) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, the NSSS does not assess other relevant aspects related to the clinical setting, resources, or institutional support, which are also important for a comprehensive evaluation of nursing students\u0026rsquo; satisfaction. In contrast, Asadizaker et al. developed the \u003cem\u003eFirst Clinical Practical Education\u003c/em\u003e (SFCPE) instrument, which focuses solely on the clinical domain and lacks items related to classroom teaching [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Other authors have used alternative approaches, such as Barraza and Ortiz, who employed the \u003cem\u003eQuality of Life and Satisfaction\u003c/em\u003e (Q-LES-Q) instrument to assess quality of life in undergraduate nursing students [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBecause existing instruments do not cover all factors influencing nursing students\u0026rsquo; satisfaction with their undergraduate education, several authors have attempted to develop new tools that allow for more complete and specific assessments. In 2012, Dennison and El-Masri developed the \u003cem\u003eUndergraduate Nursing Student Academic Satisfaction Scale\u003c/em\u003e (UNSASS), structured into four subscales: \u0026ldquo;In-Class Teaching,\u0026rdquo; \u0026ldquo;Clinical Teaching,\u0026rdquo; \u0026ldquo;Program Design and Delivery,\u0026rdquo; and \u0026ldquo;Support and Resources,\u0026rdquo; with excellent internal consistency (α\u0026thinsp;=\u0026thinsp;0.96) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and validated in several international contexts [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGuerra-Mart\u0026iacute;n et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] translated, culturally adapted, and conducted a confirmatory factor analysis (CFA) of the Spanish version of the UNSASS, naming it the \u003cem\u003eEscala de Satisfacci\u0026oacute;n Acad\u0026eacute;mica del Estudiante de Enfermer\u0026iacute;a\u003c/em\u003e (ESAEE). They reported high reliability values, with Cronbach\u0026rsquo;s alpha coefficients above α\u0026thinsp;=\u0026thinsp;0.90 for each of the four subscales. However, these authors did not report model fit indices or the sample size used for the CFA.\u003c/p\u003e\u003cp\u003eFor this reason, and in order to clarify the structure of the Spanish version of the UNSASS (ESAEE) and provide additional evidence of its reliability and validity, the main objective of this study was to evaluate the construct validity and reliability of the Spanish version of the UNSASS. A secondary objective was to assess the academic satisfaction of nursing students at the University of Las Palmas de Gran Canaria (ULPGC).\u003c/p\u003e"},{"header":"2 Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Design\u003c/h2\u003e\u003cp\u003eA cross-sectional descriptive observational study was conducted to obtain a validation sample, following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Study Population and Context\u003c/h2\u003e\u003cp\u003eThe population consisted of third- and fourth-year nursing students enrolled in the Undergraduate Nursing Degree (UND) program across the three campuses of the University of Las Palmas de Gran Canaria (ULPGC). A total of 430 students were enrolled in the 2023/2024 academic year (n\u0026thinsp;=\u0026thinsp;430), distributed as follows: 268 students at the Gran Canaria campus, 82 at the Fuerteventura campus, and 80 at the Lanzarote campus.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Inclusion and Exclusion Criteria\u003c/h2\u003e\u003cp\u003eThe inclusion criterion was being enrolled as a third- or fourth-year UND student during the 2023/2024 academic year. Students participating in academic mobility programs (e.g., SICUE, Erasmus) during the study period were excluded.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Sample Size\u003c/h2\u003e\u003cp\u003eBased on the recommendations of Ferrando et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Hair et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], a minimum sample size of 200 participants was established to ensure the feasibility of conducting a factor analysis (FA).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Study Variables, Instruments, and Data Collection\u003c/h2\u003e\u003cp\u003eThe following sociodemographic variables were collected: Gender (female, male, prefer not to answer), Campus (Gran Canaria, Fuerteventura, Lanzarote), Academic year (third, fourth), and Age (in years, quantitative variable).\u003c/p\u003e\u003cp\u003eThe administered instrument was the Spanish version of the ESAEE scale [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which contains 48 items organized into four subscales: In-Class Teaching (items n\u0026ordm; 1 to n\u0026ordm; 16), Clinical Teaching (items n\u0026ordm; 17 to n\u0026ordm; 31), \u0026ldquo;Program Design and Delivery\u0026rdquo; (items n\u0026ordm; 32 to n\u0026ordm; 43) y \u0026ldquo;Support \u0026amp; Resources\u0026rdquo; (items n\u0026ordm; 44 to n\u0026ordm; 48). Each item uses a five-point Likert scale, where a score of 1 indicates \u0026ldquo;strongly disagree\u0026rdquo; and a score of 5 indicates \u0026ldquo;strongly agree.\u0026rdquo; Thus, higher scores reflect greater levels of satisfaction. The total score ranges from 48 (minimum satisfaction) to 240 (maximum satisfaction). Subscales-specific scores can also be calculated by summing the scores of the corresponding items.\u003c/p\u003e\u003cp\u003eThe instrument was administered via an online questionnaire using the Google Forms\u0026reg; platform, distributed through the institutional email addresses of eligible students. The data collection period extended from December 2023 to March 2024.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Statistical Analysis Strategy\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.6.1. Descriptive Analysis\u003c/h2\u003e\u003cp\u003eA descriptive statistical analysis was performed. Categorical variables were expressed as frequencies and percentages, and quantitative variables using means and standard deviations. Based on the total score of the scale, five levels of satisfaction were established: very low (48\u0026ndash;86), low (87\u0026ndash;124), moderate (125\u0026ndash;162), high (163\u0026ndash;200), and very high (201\u0026ndash;240). To allow comparisons across dimensions, scores were normalized using the Min-Max scaling technique with the formula: Xnorm = (X \u0026ndash; Xmin) / (Xmax \u0026ndash; Xmin).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.6.2. Structural Construct Validity and Internal Consistency Reliability\u003c/h2\u003e\u003cp\u003eTo assess the structural construct validity of the ESAEE instrument, a factor analysis (FA) was conducted. Means, standard deviations, skewness, and kurtosis were calculated for each item. According to Mardia\u0026rsquo;s test, a Pearson correlation matrix was used for the FA. After evaluating the Measure of Sampling Adequacy (MSA) (values of MSA below 0.500 suggest that the item does not measure the same domain as the remaining items in the pool), overall data adequacy was assessed using the Kaiser-Meyer-Olkin (KMO) index and Bartlett\u0026rsquo;s test of sphericity. Values above 0.75 for KMO and p\u0026thinsp;\u0026le;\u0026thinsp;0.05 for Bartlett\u0026rsquo;s test were considered acceptable [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Factor extraction was performed using Unweighted Least Squares (ULS) with PROMIN oblique rotation. Bootstrapping was used to calculate 95% confidence intervals for item scores and model measures.\u003c/p\u003e\u003cp\u003eModel fit was evaluated using the Root Mean Square of Residuals (RMSR), Root Mean Square Error of Approximation (RMSEA), Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), and Goodness of Fit Index (GFI). An RMSR value of 0.05 was considered an acceptable fit, and RMSEA values below 0.05 were considered a good fit, while values between 0.05\u0026ndash;0.08 were considered a reasonable fit. NNFI and CFI values\u0026thinsp;\u0026ge;\u0026thinsp;0.95, and GFI values\u0026thinsp;\u0026gt;\u0026thinsp;0.90 were regarded as indicators of good model fit. For RMSR, Kelley\u0026rsquo;s criterion was used, in which the RMSR is compared to the typical error of a correlation of 0 in the population [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The Bayesian Information Criterion (BIC) was also used to compare model solutions.\u003c/p\u003e\u003cp\u003eThe analysis strategy involved performing a confirmatory factor analysis (CFA) of the initial four-factor model proposed by Guerra-Mart\u0026iacute;n et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] (using a semi-specified matrix) and a unidimensional model. Additionally, to assess unidimensionality, the following indices were used: Unidimensional Congruence (UniCo), Explained Common Variance (ECV), and Mean of Item Residual Absolute Loadings (MIREAL). UniCo values above 0.95, ECV values above 0.85, and MIREAL values below 0.30 indicate that the data may be considered essentially unidimensional [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Since parallel analysis suggested a possible three-factor solution, an exploratory factor analysis (EFA) was conducted to assess the fit of this proposed three-factor model.\u003c/p\u003e\u003cp\u003eThe consistency of the factors in each model was assessed using the Overall Reliability of fully-Informative prior Oblique N-EAP scores (ORION) and the Factor Determinacy Index (FDI) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The Sensitivity Ratio (SR) and Expected Percentage of True Differences (EPTD) were also calculated. SR reflects the number of distinct factor levels that can be differentiated based on the estimated factor scores. EPTD refers to the estimated percentage of differences between observed and true factor scores that are in the same direction. Recommended values are FDI\u0026thinsp;\u0026gt;\u0026thinsp;0.90, Oblique N-EAP scores\u0026thinsp;\u0026gt;\u0026thinsp;0.80, SR\u0026thinsp;\u0026gt;\u0026thinsp;2, and EPTD\u0026thinsp;\u0026gt;\u0026thinsp;90% [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFinally, reliability (internal consistency) was assessed using McDonald's Omega and Cronbach\u0026rsquo;s Alpha coefficients, with 95% confidence intervals calculated for both.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.6.3. Bivariate Analysis\u003c/h2\u003e\u003cp\u003eThe Kolmogorov-Smirnov test indicated non-normal distribution for quantitative variables; therefore, the non-parametric Mann-Whitney U test was used to compare means between two groups, and the Kruskal-Wallis test for comparisons involving more than two groups. In the latter case, Dwass-Steel-Critchlow-Fligner (DSCF) post hoc tests were applied. To assess differences between categorical variables, the Chi-square test (χ\u0026sup2;) was used. For each association examined, the effect size was calculated: for the Mann-Whitney U test, it was measured using the rank-biserial correlation, and for the Kruskal-Wallis test, Kelley\u0026rsquo;s squared epsilon was applied. Coefficients between 0.10 and 0.30 were interpreted as small effect sizes, between 0.30 and 0.50 as medium, and values greater than 0.50 as large effect sizes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDescriptive and inferential analyses were conducted using Jamovi software (version 2.3.28), with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Factor analysis and model reliability assessments were performed using FACTOR\u0026copy; software (Release 12.06.08, x64).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.7. Ethical Considerations\u003c/h2\u003e\u003cp\u003e Authorization was obtained from the original authors (Date: October 31, 2023) to use the Spanish version of the ESAEE scale, as well as from the corresponding Dean\u0026rsquo;s Office at the University of Las Palmas de Gran Canaria (ULPGC).\u003c/p\u003e\u003cp\u003e The study was conducted in accordance with the Declaration of Helsinki. Although the questionnaire was anonymous, participants were informed about the general aspects of the study, including its aims and characteristics. Prior to accessing the questionnaire, participants had to accept an informed consent form. This research was approved by the Research Ethics Committee (CEI/CEIm) of Hospital Dr. Negr\u0026iacute;n, Las Palmas (approval number: 2023-499-1).\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Sample Description\u003c/h2\u003e\u003cp\u003eThe response rate was 52.5%. A total of 226 students (n\u0026thinsp;=\u0026thinsp;226), with a mean age of 24.03 years (SD\u0026thinsp;=\u0026thinsp;7.09), participated in the study. Among the participants, 82.3% (n\u0026thinsp;=\u0026thinsp;186) identified as female and 17.7% (n\u0026thinsp;=\u0026thinsp;40) as male. Of the total, 58.0% (n\u0026thinsp;=\u0026thinsp;131) were in their third year of study, and 42.0% (n\u0026thinsp;=\u0026thinsp;95) were in their fourth year. Regarding campus affiliation, 73.9% (n\u0026thinsp;=\u0026thinsp;167) were from the Gran Canaria campus, 16.8% (n\u0026thinsp;=\u0026thinsp;38) from the Fuerteventura campus, and 9.3% (n\u0026thinsp;=\u0026thinsp;21) from the Lanzarote campus. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the frequencies and percentages of the variables considered by campus. Statistically significant differences were found between campuses for the academic year variable (p\u0026thinsp;=\u0026thinsp;0.010), as well as for age (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\u003eSocio-demographic variables and differences between groups according to the campuses.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;226 (100%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCampus\u003c/p\u003e\u003cp\u003eGran Canaria\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;167 (73.9%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCampus\u003c/p\u003e\u003cp\u003eFuerteventura\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;38 (16.8%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCampus\u003c/p\u003e\u003cp\u003eLanzarote\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;21 (9.3%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.588\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e186 (82.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136 (60.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19 (8.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40 (17.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcademic year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.010*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e131 (58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99 (43.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (2.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95 (42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68 (30.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eM (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eM (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.120\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.03 (7.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.7 (6.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.5 (9.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22 (1.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e1 p-value obtained with Chi-Square; 2 expressed in means and standard deviations; 3 p-value obtained with Kruskall Wallis * Statistically significant p-value.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Structural Construct Validity and Internal Consistency Reliability\u003c/h2\u003e\u003cp\u003eDescriptive item analysis is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive analysis of the items and values of Measure of Sampling Adequacy\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eM [CI95%]\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003csup\u003e2\u003c/sup\u003e\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\u003eNormed MSA\u003csup\u003e3\u003c/sup\u003e [CI95%]\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 1. I can freely express my academic and other concerns to faculty members\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.29 [3.12\u0026ndash;3.46]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.876 [0.697\u0026ndash;0.904]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 2. Faculty members are easily approachable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.23 [3.07\u0026ndash;3.38]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.933 [0.837\u0026ndash;0.939]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 3. Faculty members make every effort to assist students when asked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.21 [3.05\u0026ndash;3.37]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.534\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.951 [0.837\u0026ndash;0.944]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 4. Faculty members make an effort to understand difficulties I might be having with my course work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.88 [2.73\u0026ndash;3.03]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.934 [0.818\u0026ndash;0.937]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 5. Faculty members are usually available after class and during office hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.39 [3.23\u0026ndash;3.54]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.949 [0.808\u0026ndash;0.943]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 6. I can freely express my academic and other concerns to the administration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.26 [3.08\u0026ndash;3.44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.948 [0.839\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 7. Faculty are fair and unbiased in their treatment of individual students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.00 [2.82\u0026ndash;3.19]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.686\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.868 [0.627\u0026ndash;0.901]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 8. Faculty members provide adequate feedback about students\u0026rsquo; progress in a course\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.98 [2.82\u0026ndash;3.14]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.923 [0.791\u0026ndash;0.928]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 9. I receive detailed feedback from faculty members on my work and written assignments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.81 [2.64\u0026ndash;2.99]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.880 [0.666\u0026ndash;0.901]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 10. Channels for expressing students\u0026rsquo; complaints are readily available\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.71 [2.52\u0026ndash;2.89]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.920 [0.735\u0026ndash;0.918]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 11. Faculty members are good role models and motivate me to do my best\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.99 [2.83\u0026ndash;3.15]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.923 [0.824\u0026ndash;0.936]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 12. The administration shows concern for students as individuals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.44 [2.24\u0026ndash;2.64]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.896 [0.696\u0026ndash;0.905]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 13. Faculty members demonstrate a high level of knowledge in their subject area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00 [3.85\u0026ndash;4.15]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.938 [0.824\u0026ndash;0.940]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 14. Faculty members take the time to listen/discuss issues that may impact my academic performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.82 [2.66\u0026ndash;2.99]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.504\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.955 [0.859\u0026ndash;0.951]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 15. Faculty members create a good overall impression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.55 [3.40\u0026ndash;3.70]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.957 [0.865\u0026ndash;0.953]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 16. I am generally given enough time to understand the things I have to learn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.06 [2.89\u0026ndash;3.22]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.491\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.932 [0.814\u0026ndash;0.938]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 17. Clinical instructors are approachable and make students feel comfortable about asking questions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.77 [3.59\u0026ndash;3.95]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.907 [0.816\u0026ndash;0.925]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 18. Clinical instructors provide feedback at appropriate times, and do not embarrass me in front of others (classmates, staff, patients and family members)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.64 [3.46\u0026ndash;3.82]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.936 [0.841\u0026ndash;0.940]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 19. Clinical instructors are open to discussions and difference in opinions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.61 [3.43\u0026ndash;3.79]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.673\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.942 [0.862\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 20. Clinical instructors give me sufficient guidance before I perform technical skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.63 [3.45\u0026ndash;3.80]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.920 [0.817\u0026ndash;0.936]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 21. Clinical instructors view my mistakes as part of my learning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.69 [3.50\u0026ndash;3.89]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.941 [0.859\u0026ndash;0.940]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 22. Clinical instructors give me clear ideas of what is expected from me during a clinical rotation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.73 [3.54\u0026ndash;3.91]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.950 [0.860\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 23. Clinical instructors facilitate my ability to critically assess my client\u0026rsquo;s needs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.61 [3.43\u0026ndash;3.79]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.935 [0.841\u0026ndash;0.941]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 24. Clinical instructors assign me to patients that are appropriate for my level of competence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.53 [3.33\u0026ndash;3.73]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.945 [0.826\u0026ndash;0.944]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 25. Clinical instructors give me verbal and written feedback concerning my clinical experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.65 [3.46\u0026ndash;3.83]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.930 [0.827\u0026ndash;0.935]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 26. Clinical instructors demonstrate a high level of knowledge and clinical expertise\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.03 [3.87\u0026ndash;4.19]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.949 [0.839\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 27. Clinical instructors are available when needed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.58 [3.41\u0026ndash;3.75]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.690\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.441\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.935 [0.828\u0026ndash;0.941]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 28. Clinical instructors provide enough opportunities for independent practice in the lab and clinical sites\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.59 [3.41\u0026ndash;3.77]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.663\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.940 [0.829\u0026ndash;0.940]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 29. Clinical instructors encourage me to link theory to practice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.79 [3.64\u0026ndash;3.94]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.955 [0.855\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 30. Instructions are consistent among different clinical and lab instructors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.33 [3.14\u0026ndash;3.51]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.951 [0.842\u0026ndash;0.949]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 31. Faculty members behave professionally\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.93 [3.78\u0026ndash;4.07]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.964 [0.867\u0026ndash;0.958]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 32. This program provides a variety of good and relevant courses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.04 [2.88\u0026ndash;3.19]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.911 [0.771\u0026ndash;0.919]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 33. The program enhances my analytical skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.30 [3.15\u0026ndash;3.44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.927 [0.816\u0026ndash;0.933]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 34. Most courses in this program are beneficial and contribute to my overall\u003c/p\u003e\u003cp\u003eprofessional development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.43 [3.29\u0026ndash;3.57]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.930 [0.779\u0026ndash;0.931]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 35. The quality of instruction I receive in my classes is good and helpful\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.28 [3.14\u0026ndash;3.42]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.950 [0.837\u0026ndash;0.953]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 36. I usually have a clear idea of what is expected of me in this program\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.40 [3.26\u0026ndash;3.55]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.918 [0.786\u0026ndash;0.931]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 37. The program is designed to facilitate team work among students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.43 [3.27\u0026ndash;3.60]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.902 [0.760\u0026ndash;0.920]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 38. The program enhances my problem solving or critical thinking skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.31 [3.17\u0026ndash;3.46]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.903 [0.773\u0026ndash;0.924]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 39. There is a commitment to academic excellence in this program\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.27 [3.11\u0026ndash;3.44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.904 [0.750\u0026ndash;0.920]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 40. As a result of my courses, I feel confident about dealing with clinical nursing problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.01 [2.83\u0026ndash;3.18]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.908 [0.771\u0026ndash;0.923]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 41. Going to class helps me better understand the material\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.47 [3.27\u0026ndash;3.67]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.911 [0.768\u0026ndash;0.923]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 42. I am able to experience intellectual growth in the program\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.59 [3.43\u0026ndash;3.75]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.914 [0.807\u0026ndash;0.923]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 43. Overall, the program requirements are reasonable and achievable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.52 [3.38\u0026ndash;3.66]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.947 [0.847\u0026ndash;0.948]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 44. The secretaries are caring and helpful\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.94 [2.74\u0026ndash;3.13]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.679\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.829 [0.675\u0026ndash;0.862]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 45. The secretaries behave professionally\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.59 [3.42\u0026ndash;3.75]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.481\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.865 [0.720\u0026ndash;0.893]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 46. Support at the clinical and computer labs is readily available\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.96 [2.78\u0026ndash;3.13]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.857 [0.684\u0026ndash;0.885]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 47. Computer and clinical labs are well equipped, adequately staffed, and are readily accessible to meet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.80 [2.61\u0026ndash;2.98]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.797 [0.591\u0026ndash;0.843]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 48. The facilities (class rooms, clinical and computer labs) facilitate my learning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.23 [3.06\u0026ndash;3.41]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.885 [0.659\u0026ndash;0.903]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003e1: Mean [Confident Inteval 95%]/ 2: Standard Deviation/ 3: Measure of Sampling Adequacy\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAll MSA values were above the 0.500 threshold. The KMO index and Bartlett\u0026rsquo;s test of sphericity (n\u0026thinsp;=\u0026thinsp;226) indicated excellent sampling adequacy (KMO\u0026thinsp;=\u0026thinsp;0.925 [95%CI: 0.868\u0026ndash;0.932]; Bartlett\u0026rsquo;s test p\u0026thinsp;\u0026le;\u0026thinsp;0.001). The expected RMSR according to Kelley\u0026rsquo;s criterion for an acceptable model was 0.066. The unidimensionality analysis produced the following results: UniCo\u0026thinsp;=\u0026thinsp;0.958 [95%CI: 0.945\u0026ndash;0.978], ECV\u0026thinsp;=\u0026thinsp;0.790 [95%CI: 0.740\u0026ndash;0.850], MIREAL\u0026thinsp;=\u0026thinsp;0.272 [95%CI: 0.235\u0026ndash;0.300], indicating that the results were inconclusive regarding essential unidimensionality.\u003c/p\u003e\u003cp\u003eTwo CFAs were initially performed (a four-factor model and a unidimensional model). Since the parallel analysis suggested a three-factor solution, an EFA was also conducted to assess the fit of this model. Fit indices for the three models tested through FA are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, along with reliability indices for the factors in each model.\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\u003eFit and reliability indices of the factors of the models tested\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eEFA\u003c/p\u003e\u003cp\u003eThree Factor Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003eCFA\u003c/p\u003e\u003cp\u003eFour Factor Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCFA\u003c/p\u003e\u003cp\u003eOne Factor Model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSEA[95%CI]\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.050 [0.047\u0026ndash;0.050]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e0.049 [0.047\u0026ndash;0.051]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.100 [0.094\u0026ndash;0.101]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e (p)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e1543.532 (P\u0026thinsp;=\u0026thinsp;0.000010)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e1452.597 (p\u0026thinsp;=\u0026thinsp;0.000010)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3527.202 (p\u0026thinsp;=\u0026thinsp;0.000010)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNNFI [95%CI]\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.978 [0.975\u0026ndash;0.987]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e0.979 [0.972\u0026ndash;0.987]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.910 [0.908\u0026ndash;0.933]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFI [95%CI]\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.980 [0.978\u0026ndash;0.989]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e0.982 [0.976\u0026ndash;0.989]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.914 [0.912\u0026ndash;0.935]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGFI [95%CI]\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.979 [0.956\u0026ndash;0.981]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e0.985 [0.966\u0026ndash;0.987]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.921 [0.857\u0026ndash;0.943]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBIC[95%CI]\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e2584.275 [2525.265- 2590.831]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e2753.526 [2715.601-2797.043]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4047.573 [3854.761- 4068.997]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSR [95%CI]\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.0533 [0.053\u0026ndash;0.053]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e0.0461 [0.036\u0026ndash;0.036]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1046 [0.092 0.111]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF1\u003c/p\u003e\u003cp\u003eSatisfaction with Clinical Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF2\u003c/p\u003e\u003cp\u003eSatisfaction with Faculty and Human Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF3\u003c/p\u003e\u003cp\u003eSatisfaction with Academic Program and Support Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF1\u003c/p\u003e\u003cp\u003eIn-Class Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF2\u003c/p\u003e\u003cp\u003eClinical Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eF3\u003c/p\u003e\u003cp\u003eProgram Design and Delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF4\u003c/p\u003e\u003cp\u003eSupport \u0026amp; Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eF1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProportion of Variance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.24%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5,14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.24%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% Cumulative Proportion of Variance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.30%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e43.16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48.30%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e52.14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e33.92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactor Determinacy Index (FDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.980\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eORION marginal reliability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.930\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity ratio (SR)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.483\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.548\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.943\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExpected percentage of true differences (EPTD)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e61.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e58.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e96.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003e[Confident Inteval 95%]\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e1:Root Mean Square Error of Approximation/2:LOSEFER empirically corrected Chi-square/3:Non-Normed Fit Index/4: Comparative Fit Index/5: Goodness of Fit Index/6: Schwarz s Bayesian Information Criterion/7: Root Mean Square of Residuals\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003ea\u0026thinsp;=\u0026thinsp;The sensitivity ratio (SR) can be interpreted as the number of different factor levels than can be differentiated on the basis of the factor score estimates.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eb\u0026thinsp;=\u0026thinsp;expected percentage of true differences (EPTD) is the estimated percentage of differences between the observed factor score estimates that are in the same direction as the corresponding true differences.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eIf factor scores are to be used for individual assessment, FDI values above 0.90, marginal reliabilities above 0.80, SR above 2, and EPTDs above 90% are recommended.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFit coefficients for the three- and four-factor models were very similar, with RMSEA values of 0.050 [95%CI: 0.047\u0026ndash;0.050] and 0.049 [95%CI: 0.047\u0026ndash;0.051], respectively. However, the three-factor model had a slightly lower BIC and a RMSR value closer to Kelley\u0026rsquo;s criterion (RMSR\u0026thinsp;=\u0026thinsp;0.0533 [95%CI: 0.053\u0026ndash;0.053] versus RMSR\u0026thinsp;=\u0026thinsp;0.0461 [95%CI: 0.036\u0026ndash;0.036]). Although reliability coefficients (FDI, ORION, and SR) were adequate for both models, the three-factor model showed clearly superior values in terms of EPTD. In contrast, the unidimensional model showed poor fit indices (RMSEA\u0026thinsp;=\u0026thinsp;0.100 [95%CI: 0.094\u0026ndash;0.101]), supporting the suitability of adopting a multidimensional model, consistent with the unidimensionality analysis.\u003c/p\u003e\u003cp\u003eThe rotated matrix with the factor loadings for the newly proposed three-factor model is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFactor loadings of the matrix after rotation of the three-factor model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFactor 1\u003c/p\u003e\u003cp\u003eSatisfaction with Clinical Teaching\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFactor 2\u003c/p\u003e\u003cp\u003eSatisfaction with Faculty and Human Resources\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFactor 3\u003c/p\u003e\u003cp\u003eSatisfaction with Academic Program and Support Resources\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.514 [0.284\u0026ndash;0.698]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.711 [0.593\u0026ndash;0.856]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.679 [0.532\u0026ndash;0.830]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.722 [0.550\u0026ndash;0.902]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.537 [0.371\u0026ndash;0.743]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.744 [0.597\u0026ndash;0.920]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.411 [0.078\u0026ndash;0.633]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.584 [0.451\u0026ndash;0.781]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.530 [0.340\u0026ndash;0.699]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.441 [0.225\u0026ndash;0.616]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.544 [0.330\u0026ndash;0.719]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.685 [0.446-0.900]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.395 [0.095\u0026ndash;0.603]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.653 [0.522\u0026ndash;0.814]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.421 [0.171\u0026ndash;0.592]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.697 [0.550\u0026ndash;0.902]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.754 [0.653\u0026ndash;0.857]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.796 [0.687\u0026ndash;0.894]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.840 [0.773\u0026ndash;0.921]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.743 [0.629\u0026ndash;0.836]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.867 [0.801\u0026ndash;0.952]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.766 [0.670\u0026ndash;0.850]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.807 [0.708\u0026ndash;0.891]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.663 [0.495\u0026ndash;0.788]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.775 [0.559\u0026ndash;0.871]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.759 [0.666\u0026ndash;0.865]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.757 [0.643\u0026ndash;0.857]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.693 [0.554\u0026ndash;0.802]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.640 [0.520\u0026ndash;0.749]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.553 [0.419\u0026ndash;0.697]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.575 [0.368\u0026ndash;0.714]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.597 [0.387\u0026ndash;0.813]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.685 [0.499\u0026ndash;0.892]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.804 [0.656\u0026ndash;0.977]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.580 [0.408\u0026ndash;0.784]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.484 [0.272\u0026ndash;0.692]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.344 [0.139\u0026ndash;0.518]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.642 [0.489\u0026ndash;0.872]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.565 [0.375\u0026ndash;0.783]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.497 [0.344\u0026ndash;0.750]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.409 [0.178\u0026ndash;0.635]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.521 [0.205\u0026ndash;0.755]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.437 [0.194\u0026ndash;0.622]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.739 [0.474\u0026ndash;1.001]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.623 [0.330\u0026ndash;0.861]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.425 [0.252\u0026ndash;0.572]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.425 [0.252\u0026ndash;0.572]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem 48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.425 [0.252\u0026ndash;0.572]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003e[Confident Inteval 95%]\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis model retains all items from the original Clinical Teaching dimension (items 17\u0026ndash;31) within Factor 1. Factor 2 includes all items from In-Class Teaching (items 1\u0026ndash;16), plus items 44 and 45, excluding item 13. Factor 3 incorporates the remaining items, originally from Program Design and Delivery and Support \u0026amp; Resources. In this model, no item had cross-loadings above 0.400 in more than one factor, except for item 13, which had a loading of 0.395. Based on item distribution, the factors were renamed as follows: Factor 1 \u0026ndash; Satisfaction with Clinical Teaching (items 17\u0026ndash;31); Factor 2 \u0026ndash; Satisfaction with Faculty and Human Resources (items 1\u0026ndash;12, 14\u0026ndash;16, 44, and 45); Factor 3 \u0026ndash; Satisfaction with Academic Program and Support Resources (item 13, items 32\u0026ndash;43, 46\u0026ndash;48).\u003c/p\u003e\u003cp\u003eFinally, regarding internal consistency reliability, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the values of Cronbach\u0026rsquo;s Alpha and McDonald\u0026rsquo;s Omega coefficients for both the three- and four-factor models.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eValues of cronbach's alpha and omega coefficients of the three- and four-factor models.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eThree Factor Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003eFour Factor Model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFactor 1\u003c/p\u003e\u003cp\u003eSatisfaction with Clinical Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFactor 2\u003c/p\u003e\u003cp\u003eSatisfaction with Faculty and Human Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFactor 3\u003c/p\u003e\u003cp\u003eSatisfaction with Academic Program and Support Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFactor 1\u003c/p\u003e\u003cp\u003eIn-Class Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFactor 2\u003c/p\u003e\u003cp\u003eClinical Teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFactor 3\u003c/p\u003e\u003cp\u003eProgram Design and Delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eFactor 4\u003c/p\u003e\u003cp\u003eSupport \u0026amp; Resources\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoeficiente Alfa de Cronbach (α)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.948\u003c/p\u003e\u003cp\u003e[0.935\u0026ndash;0.961]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.910\u003c/p\u003e\u003cp\u003e[0.889\u0026ndash;0.931]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.900\u003c/p\u003e\u003cp\u003e[0.874\u0026ndash;0.927]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.905 [0.883\u0026ndash;0.927]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.948 [0.935\u0026ndash;0.961]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.897 [0.869\u0026ndash;0.924]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.718 [0.647\u0026ndash;0.789]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoeficiente Omega de MacDonald (Ω)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.949\u003c/p\u003e\u003cp\u003e[0.939\u0026thinsp;\u0026minus;\u0026thinsp;0.938]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.911\u003c/p\u003e\u003cp\u003e[0.894\u0026ndash;0.928]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.899\u003c/p\u003e\u003cp\u003e[0.880\u0026ndash;0.919]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.906 [0.888\u0026ndash;0.924]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.949 [0.939\u0026ndash;0.958]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.897 [0.877\u0026ndash;0.917]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eω\u0026thinsp;=\u0026thinsp;0.610 [0.537\u0026ndash;0.682]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003e[Confident Inteval 95%]\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Analysis of Nursing Students\u0026rsquo; Satisfaction at ULPGC\u003c/h2\u003e\u003cp\u003eThe overall mean score on the ESAEE scale indicated a high level of satisfaction (M\u0026thinsp;=\u0026thinsp;163.30 [156.70\u0026ndash;163.90]; SD\u0026thinsp;=\u0026thinsp;27.24). The scores obtained for each factor were as follows: Factor 1 (M\u0026thinsp;=\u0026thinsp;55.10 [53.50\u0026ndash;56.60]; SD\u0026thinsp;=\u0026thinsp;11.81), Factor 2 (M\u0026thinsp;=\u0026thinsp;52.20 [50.70\u0026ndash;53.60]; SD\u0026thinsp;=\u0026thinsp;10.85), and Factor 3 (M\u0026thinsp;=\u0026thinsp;53.00 [51.80\u0026ndash;54.30]; SD\u0026thinsp;=\u0026thinsp;9.59). The normalized mean values were Xnorm\u0026thinsp;=\u0026thinsp;1.00 for Factor 1, Xnorm\u0026thinsp;=\u0026thinsp;0.00 for Factor 2, and Xnorm\u0026thinsp;=\u0026thinsp;0.28 for Factor 3.\u003c/p\u003e\u003cp\u003eBivariate analysis revealed statistically significant differences according to gender in Item 8 (p\u0026thinsp;=\u0026thinsp;0.023) and Item 16 (p\u0026thinsp;=\u0026thinsp;0.002), as shown in Supplementary File 1.\u003c/p\u003e\u003cp\u003eRegarding the academic year, statistically significant differences were found in Item 8 (p\u0026thinsp;=\u0026thinsp;0.021), Item 13 (p\u0026thinsp;=\u0026thinsp;0.043), Item 24 (p\u0026thinsp;=\u0026thinsp;0.040), Item 33 (p\u0026thinsp;=\u0026thinsp;0.001), Item 39 (p\u0026thinsp;=\u0026thinsp;0.004), and in Factor 3 (p\u0026thinsp;=\u0026thinsp;0.049), as shown in Supplementary File 2.\u003c/p\u003e\u003cp\u003eAs for the campus variable, significant differences were found in the following comparisons: Item 2 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); Item 3 GC\u0026ndash;FTV (p\u0026thinsp;=\u0026thinsp;0.016); Item 6 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), GC\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.037), FTV\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.007); Item 7 FTV\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.047); Item 11 GC\u0026ndash;FTV (p\u0026thinsp;=\u0026thinsp;0.043); Item 12 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FTV\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.013); Item 14 GC\u0026ndash;FTV (p\u0026thinsp;=\u0026thinsp;0.008), GC\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.012); Item 16 GC\u0026ndash;FTV (p\u0026thinsp;=\u0026thinsp;0.005); Item 44 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FTV\u0026ndash;LNZ (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); Item 45 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FTV\u0026ndash;LNZ (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); Item 46 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FTV\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.022); Item 47 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); Item 48 GC\u0026ndash;FTV (p\u0026thinsp;=\u0026thinsp;0.015), GC\u0026ndash;LNZ (p\u0026thinsp;=\u0026thinsp;0.010); and Factor 2 GC\u0026ndash;FTV (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as detailed in Supplementary File 3.\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eA large number of scales have been developed to assess nursing students\u0026rsquo; satisfaction [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, according to Rahmatpour et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], these instruments do not meet \u0026ldquo;excellent\u0026rdquo; quality standards across all psychometric properties, as defined by the COSMIN initiative [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, no single robust and valid instrument currently exists that is considered the gold standard for measuring student satisfaction [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis is applicable to the UNSASS scale. Although it was one of the first instruments developed to assess nursing student satisfaction, we believe that the information provided on its structure and psychometric properties in both the original and subsequent validation studies has been insufficient. For example, in the original study by Dennison and El-Masri, the initial development of the scale was presented, and face, content, and construct validity, as well as internal consistency reliability, were assessed in a sample of 313 Canadian students [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, construct validity was only examined through exploratory factor analysis (EFA), meaning the originally proposed four-factor structure\u0026mdash;subsequently adopted in other studies [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u0026mdash;was not formally tested using confirmatory factor analysis (CFA), and no fit indices were reported. Victor et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], in their study conducted in Pakistan, directly adopted this model without formally validating it for their context, performing only a pretest with 10 students. More recently, the study by Guerra-Mart\u0026iacute;n et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] in Spain attempted to confirm this four-factor model via CFA, but again no fit indices were reported. The claim of good model fit was based solely on factor loadings above 0.4, which is an oversimplified interpretation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePerhaps the most rigorous validation of the UNSASS to date is the Iranian version by Rahmatpour et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], which provided more detailed evidence on its structure, using a sample of 237 students for EFA and 200 for CFA. Their three-factor model (named \u0026ldquo;University factors\u0026rdquo;, \u0026ldquo;Clinical factors\u0026rdquo;, and \u0026ldquo;Faculty factors\u0026rdquo;) yielded acceptable fit indices (RMSEA\u0026thinsp;=\u0026thinsp;0.052; CFI\u0026thinsp;=\u0026thinsp;0.918). Although we did not perform a CFA in our study, our results are aligned in indicating better fit for a three-factor model over the four-factor version, and we also observed greater reliability for the factors. Regarding item clustering, our findings also closely resemble those reported by Rahmatpour et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTwo key considerations must be acknowledged when evaluating the various factor analyses conducted with UNSASS. First, most validations used methodological approaches that are now considered outdated. For instance, the original study by Dennison and El-Masri [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] used the common but discouraged method of principal component extraction and Varimax rotation\u0026mdash;an approach also employed by Guerra-Mart\u0026iacute;n et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This methodology does not adequately distinguish between common and specific variance, which may compromise the construct validity of scales, although it remains widely used [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Second, the influence of sample size on factor analysis results must be considered. While most validations\u0026mdash;including the present study\u0026mdash;have been conducted with sample sizes ranging from sufficient (n\u0026thinsp;=\u0026thinsp;200) to very good (n\u0026thinsp;=\u0026thinsp;500) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], factors such as sample variability, ambiguous items, or restricted response ranges should be considered when determining adequate sample size for factor analysis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In our case, although the sample size was considered sufficient and sampling adequacy was excellent (KMO\u0026thinsp;\u0026gt;\u0026thinsp;0.90), it did not allow us to perform a CFA, following the recommendation to use different samples for EFA and CFA [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, a CFA remains pending to confirm the proposed three-factor structure of the Spanish version of UNSASS.\u003c/p\u003e\u003cp\u003eIn our study, factor reliability was assessed using multiple coefficients, including ORION Marginal Reliability (Overall Reliability of fully Informative prior Oblique N-EAP scores), Sensitivity Ratio (SR), and Expected Percentage of True Differences (EPTD) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The ORION coefficient, an IRT-based alternative to Cronbach\u0026rsquo;s alpha, measures the precision of estimated latent scores for each factor. Values close to 1.00 indicate very high reliability, with values above 0.80 considered acceptable. Unlike Cronbach\u0026rsquo;s alpha, ORION does not require assumptions of tau-equivalence or factor independence [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. SR (ratio of true score variance to measurement error) assesses the instrument\u0026rsquo;s ability to discriminate between individuals with different true scores; values above 2 indicate good sensitivity. EPTD estimates the proportion of observed score differences that reflect true differences rather than measurement error. Values above 90% are desirable, indicating strong discriminative fidelity. Although not yet widely used, these indices should be considered standard practice for high-quality psychometric evaluations. We also calculated classic internal consistency indicators such as Cronbach\u0026rsquo;s alpha and McDonald\u0026rsquo;s omega [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Although Cronbach\u0026rsquo;s alpha has been increasingly criticized, it remains the most commonly used index for internal consistency. McDonald\u0026rsquo;s omega is now recognized as a more robust alternative [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In our study, both coefficients were calculated to allow comparison with previous validations. Only Rahmatpour et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported omega in their study, and similarly to our results, they obtained coefficients above 0.900 for the three model dimensions, supporting strong internal consistency.\u003c/p\u003e\u003cp\u003eWith regard to the application of the instrument, our students\u0026rsquo; overall satisfaction was high (M\u0026thinsp;=\u0026thinsp;163.30; SD\u0026thinsp;=\u0026thinsp;27.24), although lower than that observed in Canada [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] (M\u0026thinsp;=\u0026thinsp;175.12; SD\u0026thinsp;=\u0026thinsp;25.88). Global results could not be compared with other applications of UNSASS [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] due to the absence of total and subscale scores in those studies. After normalizing the means, the highest satisfaction was found in Factor 1 \u0026ldquo;Satisfaction with Clinical Teaching\u0026rdquo; (Xnorm\u0026thinsp;=\u0026thinsp;1.00), while the lowest was in Factor 2 \u0026ldquo;Satisfaction with Faculty and Human Resources\u0026rdquo; (Xnorm\u0026thinsp;=\u0026thinsp;0.00). Normalized means could not be compared due to our restructured three-factor model. However, in the Canadian study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the highest satisfaction was for \u0026ldquo;In-Class Teaching\u0026rdquo; (Xnorm\u0026thinsp;=\u0026thinsp;1.00), and the lowest for \u0026ldquo;Support and Resources\u0026rdquo; (Xnorm\u0026thinsp;=\u0026thinsp;0.00). In this regard, mentoring programs have been shown to enhance educational outcomes and increase satisfaction among both students and faculty [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The highest-rated items were Item 26 \u0026ldquo;Clinical instructors demonstrate a high level of knowledge and clinical expertise\u0026rdquo; (M\u0026thinsp;=\u0026thinsp;4.03; SD\u0026thinsp;=\u0026thinsp;0.94) and Item 13 \u0026ldquo;Faculty members demonstrate a high level of knowledge in their subject area\u0026rdquo; (M\u0026thinsp;=\u0026thinsp;4.00; SD\u0026thinsp;=\u0026thinsp;0.88), reflecting students\u0026rsquo; high appreciation of faculty knowledge [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Nonetheless, improvements in curriculum structure, evaluation strategies, teaching resources, and alumni follow-up systems are needed to improve educational quality [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The lowest-rated item was Item 12 \u0026ldquo;The administration shows concern for students as individuals\u0026rdquo; (M\u0026thinsp;=\u0026thinsp;2.44; SD\u0026thinsp;=\u0026thinsp;1.17). Transformational leadership experiences in organizational culture have shown promise in promoting significant changes in institutional systems and staff dynamics, which are crucial for effective transformation [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough some statistically significant differences were observed based on gender and academic year, the most relevant influence was that of the ULPGC campus. This variable is relevant because, for example, the GC campus has a larger student-to-classroom ratio. As noted by Walker et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], smaller class sizes improve faculty-student interaction and enhance the learning process. Likewise, the smaller clinical hospitals associated with the FTV campus are linked to reduced faculty workload and fewer assigned students, allowing for more personalized teaching, more effective learning, and greater student motivation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. According to Cant and Gazula [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], student interaction with peers and university staff\u0026mdash;especially faculty\u0026mdash;directly influences motivation and engagement in learning.\u003c/p\u003e\u003cp\u003eAmong the limitations of this study, the most significant was the sample size used for the analysis of construct validity. Although the KMO index indicated excellent sampling adequacy, the sample did not allow for a CFA, following the recommendation to use separate samples for EFA and CFA. A CFA using an independent sample remains necessary to confirm the proposed three-factor structure of the Spanish version of the UNSASS instrument.\u003c/p\u003e\u003cp\u003eOne of the strengths of this study lies in the rigorous analysis of structural construct validity, employing fit indices and statistical tests that provide evidence of the instrument\u0026rsquo;s multidimensionality and support the proposal of a new three-factor model. Additionally, the estimation of reliability through internal consistency using McDonald\u0026rsquo;s omega\u0026mdash;considered a more robust alternative to Cronbach\u0026rsquo;s alpha\u0026mdash;is noteworthy, along with the calculation of additional reliability coefficients for the model\u0026rsquo;s factors.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study contributes to improving the understanding of the psychometric properties of the Spanish version of the UNSASS scale, confirming it as a valid and reliable instrument for assessing nursing students' satisfaction in the Spanish context. A multidimensional model is proposed for the Spanish version of the UNSASS scale, showing a better fit for a three-factor model compared to the classic four-factor structure, along with excellent internal consistency. The satisfaction of ULPGC students was high, with the \u0026ldquo;Clinical Teaching\u0026rdquo; factor standing out as the most highly rated subscale.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate.\u003c/p\u003e\n\u003cp\u003eParticipants provided informed consent before completing the questionnaire. The study was approved by the Research Ethics Committee of Hospital Dr. Negr\u0026iacute;n, Las Palmas (approval number: 2023-499-1).\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eClinical trial declaration\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eConceptualization: M.IS, CA.RS, H.GT; Data curation; M.IS, CA.RS; Formal analysis: CA.RS, \u0026nbsp;H.GT; Investigation: M.IS, CM.DG, M.RH; Methodology: M.IS, CA.RS, H.GT; Software: CA.RS, H.GT; Supervision: CA.RS; Validation: H.GT; Visualization: M.IS, CM.DG, M.RH; Writing \u0026ndash; original draft: M.IS, CA.RS, H.GT, CM.DG, M.RH; Writing \u0026ndash; review \u0026amp; editing; CA.RS, H.GT, CM.DG.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank all the students for their participation in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCant R, Gazula S, Ryan C. 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J Nurs Educ. 2012;51(2):81\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3928/01484834-20111230-02\u003c/span\u003e\u003cspan address=\"10.3928/01484834-20111230-02\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmin SM, El-Sayed AAI, Othman AA, Ali AS, ELfeshawy NI, El-Sherbini HH, Mahmoud AAF, Atta MHR. Transforming nursing education: the power of educational leadership in optimizing time management and competency. BMC Nurs. 2025;24(1):870. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12912-025-03420-2\u003c/span\u003e\u003cspan address=\"10.1186/s12912-025-03420-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":"Personal Satisfaction, Students, Nursing, Education, Nursing, Education, Nursing, Diploma Programs, Academic Success","lastPublishedDoi":"10.21203/rs.3.rs-7155035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7155035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCurrently, there is no gold standard scale for assessing academic satisfaction among undergraduate nursing students. The aim of this study was to evaluate the construct-structural validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS), as well as to assess the academic satisfaction of undergraduate nursing students at the University of Las Palmas de Gran Canaria (ULPGC).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted among nursing students at ULPGC, Spain. Model fit indicators were examined using confirmatory factor analysis (CFA) for both the original four-factor model and a unidimensional model. Additionally, a new three-factor model was tested through exploratory factor analysis (EFA). Internal consistency reliability was evaluated. Bivariate analysis was performed using chi-square, U-Mann-Whitney, and Kruskal-Wallis tests. For each association, effect sizes were calculated using biserial rank correlation and Kelley\u0026rsquo;s squared Epsilon measure. Descriptive and inferential analyses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were performed using Jamovi (v.2.3.28). Factor analysis and model reliability were carried out using FACTOR\u0026copy; (Release 12.06.08, x64). The study was approved by the Research Ethics Committee (No. 2023-499-1).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 226 students participated (n\u0026thinsp;=\u0026thinsp;226), showing a high level of satisfaction (M\u0026thinsp;=\u0026thinsp;163.30 [156.70\u0026ndash;163.90]; SD\u0026thinsp;=\u0026thinsp;27.24). Sample adequacy for factor analysis was excellent (KMO\u0026thinsp;=\u0026thinsp;0.925 [95%CI: 0.868\u0026ndash;0.932]; Bartlett\u0026rsquo;s test: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The unidimensional model showed poor fit (RMSEA\u0026thinsp;=\u0026thinsp;0.100 [95%CI: 0.094\u0026ndash;0.101]). The three-factor model yielded RMSEA\u0026thinsp;=\u0026thinsp;0.050 [95%CI: 0.047\u0026ndash;0.050] and the four-factor model RMSEA\u0026thinsp;=\u0026thinsp;0.049 [95%CI: 0.047\u0026ndash;0.051]; however, the three-factor model was closer to Kelley\u0026rsquo;s criterion (RMSR\u0026thinsp;=\u0026thinsp;0.0533 [95%CI: 0.053\u0026ndash;0.053], expected RMSR\u0026thinsp;=\u0026thinsp;0.066). Internal consistency reliability was excellent for the three-factor model (F1: α\u0026thinsp;=\u0026thinsp;0.948, ω\u0026thinsp;=\u0026thinsp;0.949; F2: α\u0026thinsp;=\u0026thinsp;0.910, ω\u0026thinsp;=\u0026thinsp;0.911; F3: α\u0026thinsp;=\u0026thinsp;0.900, ω\u0026thinsp;=\u0026thinsp;0.899) and good for the four-factor model (F1: α\u0026thinsp;=\u0026thinsp;0.905, ω\u0026thinsp;=\u0026thinsp;0.906; F2: α\u0026thinsp;=\u0026thinsp;0.948, ω\u0026thinsp;=\u0026thinsp;0.949; F3: α\u0026thinsp;=\u0026thinsp;0.897, ω\u0026thinsp;=\u0026thinsp;0.897; F4: α\u0026thinsp;=\u0026thinsp;0.718, ω\u0026thinsp;=\u0026thinsp;0.610).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe Spanish version of the UNSASS scale demonstrated multidimensionality, with the three-factor model showing a better fit and excellent internal consistency. ULPGC students reported high levels of satisfaction, with \u0026ldquo;Clinical Teaching\u0026rdquo; being the most highly rated factor.\u003c/p\u003e","manuscriptTitle":"Construct validity and reliability of the Spanish version of the Undergraduate Nursing Student Academic Satisfaction Scale (UNSASS)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 16:10:27","doi":"10.21203/rs.3.rs-7155035/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":"055249ed-b290-44c6-8039-20626fe41a1c","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Withdrawn","date":"2026-05-20T07:58:11+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T08:12:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 16:10:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7155035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7155035","identity":"rs-7155035","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}