Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) for Pediatric Nurses: A Cross-Sectional Study

Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) for Pediatric Nurses: A Cross-Sectional Study | 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 Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) for Pediatric Nurses: A Cross-Sectional Study Jianing Duan, Yuehang Zhuang, Xiaofei Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8315661/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background As a core intervention to alleviate children’s suffering and improve their medical experience, the quality assessment of atraumatic care has become increasingly important. Currently, China lacks standardized, sinicized and psychometrically validated tools for evaluating pediatric nurses’ attitudes toward atraumatic care — a gap that makes it difficult to objectively quantify nurses’ attitude levels and provide evidence for clinical practice improvement. Objective This study aimed to translate the Pediatric Atraumatic Care Attitude Scale (PACAS) into Chinese, conduct cross-cultural adaptation, and measure the attitudes of Chinese pediatric nurses toward atraumatic care. Methods The Brislin translation model was used to translate the PACAS from English into Chinese. The study was conducted from July to December 2025, recruiting 351 pediatric nurses from hospitals in Northeast, Southwest, and East China. Item analysis was performed to evaluate discriminability and screen valid items. The Delphi method was adopted to analyze content validity and refine items through expert consultation. For construct validity, exploratory factor analysis (EFA) was first used to clarify the latent structure, followed by confirmatory factor analysis (CFA) for verification. Reliability was assessed by calculating Cronbach’s alpha coefficient, split-half reliability, and test-retest reliability to ensure the robustness of results. Results All 31 items of the original scale were retained after item analysis of the Chinese version of the Pediatric Atraumatic Care Attitude Scale. The item-level content validity index (I-CVI) of individual items ranged from 0.880 to 1.000. The overall Cronbach’s alpha coefficient was 0.964, split-half reliability was 0.637, and test-retest reliability was 0.840. Two common factors (Knowledge and Awareness, Practice and Family Involvement) were extracted, explaining 72.995% of the total variance. The results of CFA were as follows: χ²/df = 2.033, standardized root mean square residual (SRMR) = 0.0726, incremental fit index (IFI) = 0.905, Tucker-Lewis index (TLI) = 0.896, comparative fit index (CFI) = 0.905, and root mean square error of approximation (RMSEA) = 0.072. Both EFA and CFA results indicated that the translated scale had good reliability and validity. Conclusion The C-PACAS is a reliable and valid measurement tool for assessing pediatric nurses’ knowledge and attitudes toward atraumatic care. Pediatric nurses Atraumatic care Validity Reliability Attitude Figures Figure 1 Figure 2 Background Atraumatic care is a concept of providing therapeutic care through interventions that eliminate or minimize the psychological and physical distress experienced by children and their families (1). The principles of atraumatic care include: relieving or eliminating pain, ensuring the child stays with family; adhering to family-centered care, allowing the child to express their feelings and supporting their self-control; providing basic care, enhancing the family’s sense of control, and giving families sufficient time and opportunities to participate in the care process (2, 3). Common atraumatic care practices include, but are not limited to, therapeutic play, breastfeeding, listening to the mother’s voice, distraction, and massage (4). Young children or children with developmental delays often lack the language or cognitive maturity to describe their pain, making the assessment and management of pediatric pain particularly challenging (5). Moreover, acute pain from medical procedures often triggers anxiety in children, leading to resistance to subsequent medical interventions (6). Children’s resistance and intolerance to invasive medical procedures not only exacerbate doctor-patient conflicts but also delay treatment time (7). Therefore, atraumatic care is crucial in pediatric nursing. As the primary implementers of atraumatic care, pediatric nurses can maximize benefits and improve children’s well-being during invasive care by combining pharmacological and non-pharmacological strategies to minimize pain, stress, and fear of invasive procedures, and implementing the concept of atraumatic care in daily nursing practices (8). The Theory of Planned Behavior (TPB) states that an individual’s attitude, subjective norm, and perceived behavioral control jointly influence behavioral intention, which ultimately determines actual behavior (9); the Transtheoretical Model (TTM) emphasizes that an individual’s attitude toward a behavior changes with cognitive stages, from “unaware” to “active maintenance”, providing theoretical support for assessing the dynamic changes of nurses’ attitudes toward atraumatic care (10). Based on these two models, accurately assessing nurses’ attitudes toward atraumatic care is a key prerequisite for promoting the translation of concepts into practice and improving care quality. Positive attitudes of nurses can promote the regular application of non-pharmacological interventions and reduce children’s medical fear, while negative attitudes may lead to the formalization of atraumatic care, making it difficult to exert its protective effect on children’s physical and mental health. Existing research has obvious deficiencies in tools for assessing pediatric nurses’ atraumatic care practices. Most relevant assessment tools focus on general care quality or pain management outcomes, such as the Face, Legs, Activity, Cry, Consolability (FLACC) Scale (11) and Behavioral Pain Scale (BPS) (12). These tools are mainly used to measure children’s pain levels or physiological responses after nursing interventions, rather than targeting nurses’ attitudes and cognition toward atraumatic care. In addition, some nursing behavior assessment tools (such as nursing practice scales) involve the standardization of nursing operations but do not specifically incorporate the core elements of atraumatic care, such as family participation, children’s psychological support, and the application of non-pharmacological analgesic strategies. In 2024, Turkish scholar Adnan Batuhan Coşkun developed the Pediatric Atraumatic Care Attitude Scale (PACAS) using systematic literature review and Delphi method (13), both of which are widely recognized methods for scale development (14). The study aimed to assess pediatric nurses’ attitudes toward atraumatic care and serve as a tool to improve their understanding and compliance, ultimately helping to enhance the quality of care provided to children (13). PACAS has undergone rigorous psychometric validation and demonstrated strong reliability and validity. Therefore, the purpose of this study was to translate PACAS into Chinese and evaluate its psychometric properties among Chinese pediatric nurses, so that it can be applied to serve Chinese pediatric nurses and improve pediatric nursing. Methods Ethical Considerations: This study was approved by the Ethics Committee of Jinzhou Medical University (JZMULL2025425), and all research procedures complied with the committee’s ethical guidelines. Informed consent was obtained from all participants before data collection. Participants: A cross-sectional study was conducted from July to December 2025, and 351 pediatric nurses were recruited by convenience sampling from 10 Grade A tertiary hospitals in Northeast, Southwest, and East China. The inclusion criteria were as follows: a. Registered nurses holding valid nursing practice certificates and currently engaged in clinical nursing work in pediatric departments (including pediatric wards, neonatal departments, pediatric outpatient clinics, etc.); b. Having ≥ 1 year of pediatric nursing work experience; c. Volunteering to participate in the study and being able to complete the scale independently. The exclusion criteria were as follows: a. Trainee nurses, student nurses, or standardized training nurses who had not obtained independent practice qualifications; b. Pediatric nurses mainly engaged in non-clinical frontline nursing work such as administration and teaching in the past 3 months. The sample size was estimated using Kendall’s method, which recommends a sample size of 5–10 times the number of questionnaire items (15). Considering an expected attrition rate of 20%, the initial calculation indicated that the required sample size was at least 234. In addition, to meet the minimum sample requirements for exploratory factor analysis (EFA) (≥ 100 cases) and confirmatory factor analysis (CFA) (≥ 200 cases), we finally recruited 351 pediatric nurses (16) . Translation and Cross-Cultural Adaptation: The original author was contacted by email for authorization, and then the PACAS was translated into Chinese according to the Brislin model (17).PACAS was developed by Professor Adnan Batuhan Coşkun’s team based on multidisciplinary theories, including two dimensions with 31 items: Knowledge and Awareness (Items 1–16) and Practice and Family Involvement (Items 17–31). A 5-point Likert scale was used, with responses ranging from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 31 to 155, with higher scores indicating higher enthusiasm and professional mastery of atraumatic care among pediatric nurses. The overall Cronbach’s α coefficient was calculated as 0.985, and the Cronbach’s α coefficients of the sub-dimensions were 0.978 and 0.983, respectively. The test-retest reliability showed a strong correlation (r = 0.980, r = 0.985, r = 0.957) (13) . Step 1 : Two nursing postgraduates whose native language is Chinese and with CET-6 English proficiency translated the PACAS into two Chinese versions (T1 and T2). Then the first author integrated the two translated versions, conducted discussions and revisions, and finally developed the Chinese version T of the scale. Step 2 : Another doctoral student in pediatric nursing and a master student in English whose native language is Chinese independently back-translated Scale T into English versions (NT1 and NT2), as they had no prior exposure to the scale. Step 3 : The experts in Step 2 and the first author held a meeting to discuss versions NT1 and NT2, and after confirming that there were no significant discrepancies with the original scale, the final back-translation version T3 was formed. Step 4 : The back-translation version T3 was sent to the original author to inquire about semantic ambiguity, expression errors, and other issues. Finally, the Chinese version T, back-translation version T3, and the original scale were comprehensively compared to form the initial Sinicized version B. Step 5 : According to the guidelines for cultural adaptation, six experts were invited to evaluate the initial Sinicized version B through two rounds of email and on-site correspondence, and finally the pre-survey version of the Chinese PACAS was formed. Quality Control and Pre-Survey: Communication : Before the survey, communicate with the nursing department managers and head nurses of each hospital to coordinate time and avoid busy periods of the departments to ensure consistent survey conditions. Investigator Training : Unified distribution of procedures, guidelines, and standard answers to questions (e.g., consistent explanations for ambiguous questions) to avoid errors caused by differences in investigators’ operations. Pre-Survey : 1–2 hospitals were selected from each of Northeast, Southwest, and East China, with 15–20 participants sampled from each region by convenience sampling. After understanding the purpose and significance of the study, all participants signed the informed consent form and then filled out the pre-survey version of the Chinese PACAS. Results : The scale had a clear theme, complete structure, and logical coherence, and no semantic comprehension difficulties were reported. Participants spent an average of about 4 minutes completing the questionnaire, so no modifications were made, and the Chinese version of the PACAS was finally determined. Measurement and Instruments: (1) General Information Scale : The researcher designed a demographic data questionnaire by reviewing literature to collect information such as age, gender, educational background, marital and childbearing status, professional title, working years, employment form, and average monthly income. (2) Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) :, including two dimensions with 31 items: Knowledge and Awareness (Items 1–16) and Practice and Family Involvement (Items 17–31) (13). A 5-point Likert scale was adopted, with a scoring standard ranging from 1 point (strongly disagree) to 5 points (strongly agree). The total score ranges from 31 to 155, with higher scores indicating higher enthusiasm and professional mastery of atraumatic care among pediatric nurses. Data Collection: Before distributing the questionnaires on-site, the researchers first obtained the consent of the nursing department managers and head nurses of relevant departments, and avoided the busy working hours of the departments. With the assistance of nursing department managers, the researchers and eight other trained investigators distributed questionnaires to nurses in departments meeting the inclusion and exclusion criteria using the Chinese data collection software “Questionnaire Star” in 10 Grade A tertiary hospitals in Northeast, Southwest, and East China. Nurses were informed of the purpose and significance of the study and the matters needing attention when filling out the questionnaires. After completing the questionnaires, data were collected. A total of 370 nurses completed the questionnaires. Abnormal questionnaires with obvious regularity or logical confusion (e.g., identical answers or contradictory answers) were excluded from the data. Finally, 351 valid questionnaires were collected, with an effective recovery rate of 94.8%. Two weeks later, 50 nurses were randomly selected for a second survey to assess the test-retest reliability of the scale. Data Analysis: IBM SPSS Statistics 27.0 and Amos 25.0 were used for statistical analyses: SPSS 27.0 handled statistical description, reliability analysis, and exploratory factor analysis (EFA), while Amos 25.0 was applied for confirmatory factor analysis (CFA) and structural equation modeling. Measured data were expressed as mean (standard deviation, SD) and categorical data as percentages. Data were considered normally distributed if item skewness and kurtosis values ranged between − 2 and + 2 (18).. Item, validity, and reliability analyses were performed on the Chinese version of the Pediatric Atraumatic Care Attitude Scale (PACAS). Item Analysis: Critical ratio and correlation coefficient methods were used to evaluate item analysis. The critical ratio was used to assess item discrimination, and a ratio ≥ 3 was considered to indicate appropriate discrimination (19). In addition, item-factor correlation coefficients were calculated to evaluate homogeneity, and a coefficient ≥ 0.40 indicated satisfactory homogeneity (19). Validity Analysis: (1) Content Validity : Nine nursing experts were invited to evaluate the content validity of the C-PACAS using the Delphi method. The C-PACAS was evaluated using a 4-point Likert scale, with each item scored according to its relevance to the theme as follows: irrelevant = 1, weakly relevant = 2, moderately relevant = 3, and strongly relevant = 4. The Item-Level Content Validity Index (I-CVI) was calculated as the proportion of experts who rated an item as 3 or 4 among the total number of experts. The Scale-Level Content Validity Index/Average (S-CVI/Ave) was determined as the average I-CVI of all items (20). (2) Construct Validity : EFA and CFA were used to test the validity of the C-PACAS. The total sample was randomly divided into Sample 1 (n = 151) and Sample 2 (n = 200). EFA was performed using Sample 1, and CFA was performed using Sample 2. Before conducting EFA, Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity were first performed on Sample 1. It is generally believed that a KMO value > 0.7 and P < 0.05 indicate that the sample size is suitable for factor analysis (21) .Through principal component analysis (PCA) and varimax orthogonal rotation, eigenvalues, factor loadings, contribution rates, and scree plots were calculated to verify whether the item design and dimensional structure of the Chinese version of the C-PACAS are scientifically sound. CFA was performed via Amos using Sample 2 to evaluate model fit indices. Data validation was conducted using the maximum likelihood algorithm to explore model fit indices. A model with χ²/df < 3, RMSEA and standardized root mean square residual (SRMR) 0.90 indicates a good model fit (22). (3) Convergent Validity and Discriminant Validity : Based on the results of CFA, correlation coefficients between observed variables, extracted average variance extracted (AVE), and composite reliability (CR) were calculated. Discriminant validity was tested using the Fornell-Larcker criterion, which states that the square root of the AVE of each latent variable is greater than the correlation coefficient between that latent variable and other latent variables (23) . Reliability Analysis: This study used test-retest reliability and internal consistency to assess reliability. To evaluate internal consistency, Cronbach’s alpha coefficient was calculated for each dimension of the C-PACAS. Fifty nurses who voluntarily provided contact information in the first survey were randomly selected as samples for measuring test-retest reliability two weeks later. The correlation between the two sets of scores was calculated to determine the stability of the measurement tool. A two-week interval was chosen for test-retest reliability assessment to avoid the memory effect of too short an interval (e.g., within a few days) – which would prevent participants from recalling responses to the first measurement, thus affecting the independence of the second results. This method also avoids problems caused by too long an interval (e.g., several months), which can lead to significant changes in measurement indicators (such as psychological traits and behavioral performance) over time or interference from external factors, thus failing to accurately reflect the true stability of the scale (24). In addition, the Spearman-Brown and upper-lower split methods were used to divide the scale items into two halves, and the correlation between the two halves was calculated to assess split-half reliability. Results Cross-Cultural Adaptation: According to expert opinions, the Chinese version of the PACAS was revised and improved. Details are as follows: Item 20 “therapeutic play techniques” was simplified to “therapeutic play”, because “therapeutic play” in Chinese already includes the practical connotation of “techniques”, and the word “techniques” is slightly redundant, and “therapeutic play” is more commonly used as a fixed term in China. Item 25 “treatment choice” was revised to “treatment plan”. “Treatment plan” is more commonly used in the Chinese context, and parents’ perception of “choice” may be subjective, which is more in line with the expression habit of medical plans in doctor-patient communication. Descriptive Statistics: A total of 370 questionnaires were collected in this study, and 19 invalid questionnaires were excluded, finally obtaining 351 valid questionnaires. 61.3% of the participants were female, 46.4% of the total sample were ≤ 30 years old, and 53.3% of the participants had a bachelor’s degree as their highest educational background. 61.5% of the participants were married; 49.9% of the participants had the professional title of senior nurse; 59.8% of the respondents had engaged in clinical nursing work for 5–10 years; 62.4% of the participants were contract nurses; 53.97% of the participants had an average monthly income in the range of 5000–10000 yuan. Table 1 lists all characteristics of the participants. Table 1 Distribution of demographic characteristics (N = 351) Variables Frequency Percentage% Gender Males 136 38.7 Females 215 61.3 Age ≤ 30 years 163 46.4 31–39 years 158 45.0 40–49 years 21 6.0 ≥ 50 years 9 2.6 Educational background Junior college education or below 123 35.0 Bachelor's degree 187 53.3 Postgraduate education or above 41 11.7 Marital status Unmarried 124 35.3 Married 216 61.5 Other 11 3.1 Professional title Nurse 92 26.2 Senior nurse 175 49.9 Charge nurse 75 21.4 Associate chief nurse or above 9 2.6 Working time ≤ 5 years 113 32.2 5–10 years 210 59.8 ≥ 10 years 28 8.0 Forms of employment Formal 76 21.7 Contractual 219 62.4 Labor dispatch 56 16.0 Average monthly income 10000 yuan 103 29.3 Item Analysis: Independent-samples t-test was used in this study to evaluate the discriminative ability of the questionnaire between the high-score group and the low-score group. The critical ratios of the 31 items ranged from 9.279 to 66.710 (all > 3, P < 0.01) (19). Pearson correlation analysis was used to analyze the relationship between individual item scores and total scores, with correlation coefficients r = 0.532–0.782 (all ≥ 0.40, P < 0.01) (19). Skewness and kurtosis values between − 2 and + 2 indicated that the detected dataset was normally distributed (18). See Table 2. Table 2 Critical ratios of C-PACAS , item-total correlation coefficients, and Cronbach’s alpha values after item deletion (n = 351) Item Critical ratio Correlation item total score P Cronbach’sα after delet ing the item Skewness/Kurtosis Ka1 21.648 0.732 p<0.001 0.962 −0.368/−0.458 Ka2 33.379 0.756 p<0.001 0.962 −0.475/−0.365 Ka3 32.227 0.775 p<0.001 0.962 −0.397/−0.452 Ka4 26.660 0.765 p<0.001 0.962 −0.486/−0.384 Ka5 22.505 0.755 p<0.001 0.962 −0.353/−0.526 Ka6 28.176 0.727 p<0.001 0.962 −0.390/−0.497 Ka7 33.245 0.773 p<0.001 0.962 −0.485/−0.228 Ka8 32.233 0.757 p<0.001 0.962 −0.452/−0.335 Ka9 48.842 0.782 p<0.001 0.962 −0.476/−0.512 Ka10 50.903 0.756 p<0.001 0.962 −0.554/−0.174 Ka11 37.321 0.772 p<0.001 0.962 −0.481/−0.221 Ka12 29.891 0.779 p<0.001 0.962 −0.386/−0.366 Ka13 23.984 0.767 p<0.001 0.962 −0.354/−0.503 Ka14 28.463 0.738 p<0.001 0.962 −0.524/−0.162 Ka15 30.248 0.738 p<0.001 0.962 −0.387/−0.519 Ka16 25.450 0.728 p<0.001 0.962 −0.515/−0.116 Pm1 26.377 0.547 p<0.001 0.963 −0.791/0.225 Pm2 66.710 0.604 p<0.001 0.963 −0.694/−0.094 Pm3 26.556 0.678 p<0.001 0.962 −0.663/−0.046 Pm4 43.817 0.683 p<0.001 0.962 −0.883/0.705 Pm5 17.235 0.659 p<0.001 0.963 −0.852/0.365 Pm6 35.619 0.643 p<0.001 0.963 −0.880/0.744 Pm7 25.184 0.657 p<0.001 0.963 −0.983/0.839 Pm8 24.766 0.662 p<0.001 0.963 −0.902/0.873 Pm9 45.742 0.604 p<0.001 0.963 −1.016/0.812 Pm10 17.178 0.586 p<0.001 0.963 −0.782/0.595 Pm11 26.796 0.634 p<0.001 0.963 −1.004/1.006 Pm12 9.279 0.646 p<0.001 0.963 −0.771/0.319 Pm13 25.377 0.532 p<0.001 0.963 −1.039/1.268 Pm14 34.088 0.559 p<0.001 0.963 −0.976/1.199 Pm15 40.800 0.536 p<0.001 0.963 −1.173/1.589 Validity: (1)Content Validity: Nine experts were invited to evaluate the content validity of the C-PACAS using the Delphi method. I-CVI and S-CVI/Ave were calculated based on a 4-point Likert scale. The results showed that the I-CVI ranged from 0.880 to 1.00 (> 0.78)(20)., while the S-CVI/Ave was 0.903 (> 0.90)(20).. (2)Construct Validity: Exploratory Factor Analysis (EFA) : In this study, the KMO value was 0.942, and Bartlett’s test of sphericity yielded a chi-square value of approximately 5775.076 (degrees of freedom = 465, P 1 (25). The component matrix was obtained via orthogonal varimax rotation, and only factors with loadings > 0.5 were retained (Table 3) (26). After 25 rotation iterations converged, a total of 2 factors consistent with the original scale were extracted, with a cumulative explained variance of 72.995% (Fig. 1). Table 3 Factor loadings of exploratory factor analysis for the C-PACAS (n = 151) Item FactorA FactorB Ka1 0.743 Ka2 0.830 Ka3 0.867 Ka4 0.871 Ka5 0.872 Ka6 0.895 Ka7 0.852 Ka8 0.846 Ka9 0.818 Ka10 0.848 Ka11 0.865 Ka12 0.864 Ka13 0.850 Ka14 0.855 Ka15 0.807 Ka16 0.859 Pm1 0.521 Pm2 0.512 Pm3 0.698 Pm4 0.758 Pm5 0.807 Pm6 0.872 Pm7 0.825 Pm8 0.905 Pm9 0.880 Pm10 0.841 Pm11 0.861 Pm12 0.876 Pm13 0.828 Pm14 0.869 Pm15 0.851 Confirmatory Factor Analysis (CFA):Fig. 2 shows the results of CFA. In Amos, CFA was performed on another part of the scale data (n = 200) using the maximum likelihood method, and the initial model was modified according to the modification indices (MI) (27), namely: e1 and e2, e2 and e3, e1 and e3, e9 and e14, e13 and e14, e18 and e19, e25 and e26, e30 and e31. The modified model fit indices are shown in Table 4. The modified results of each fit index showed that χ2/df = 2.033 ( 0.9), TLI = 0.896 (> 0.9), CFI = 0.905 (> 0.9), RMSEA = 0.072 (< 0.09) (28), and SRMR = 0.0726 ( 0.6), while the AVE ranged from 0.4353 to 0.6454 (> 0.4), all within the minimum acceptable range (30) . Table 4 Fit indices of the C-PACAS(n = 200) Fit indices χ2/df IFI TLI CFI RMSEA SRMR Model modification 2.033 0.905 0.896 0.905 0.072 0.0726 Range 0.9 > 0.9 > 0.9 < 0.08 < 0.08 Model fit interpretatio good good acceptable good good good Note A = Knowledge and Awareness (16 items) B = Practice and Family Involvement (15 items) Figure 2 Hypothesized confirmatory factor analysis model of the C-PACAS(n = 200) Table 5 Discriminant and convergent validity of the C-PACAS (n = 200) Discriminant Validity Convergent Validity Factors A B Items Std.Estimate SE P CR AVE A 0.803 0.478** Ka1 0.729 0.9668 0.6454 Ka2 0.787 0.075 p<0.001 Ka3 0.805 0.080 p<0.001 Ka4 0.812 0.099 p<0.001 Ka5 0.845 0.103 p<0.001 Ka6 0.789 0.097 p<0.001 Ka7 0.841 0.095 p<0.001 Ka8 0.834 0.099 p<0.001 Ka9 0.838 0.105 p<0.001 Ka10 0.811 0.101 p<0.001 Ka11 0.807 0.098 p<0.001 Ka12 0.818 0.095 p<0.001 Ka13 0.789 0.100 p<0.001 Ka14 0.794 0.095 p<0.001 Ka15 0.778 0.098 p<0.001 Ka16 0.768 0.097 p<0.001 B 0.659 Pm1 0.431 0.9188 0.4353 Pm2 0.471 0.224 p<0.001 Pm3 0.647 0.274 p<0.001 Pm4 0.715 0.278 p<0.001 Pm5 0.697 0.298 p<0.001 Pm6 0.744 0.291 p<0.001 Pm7 0.802 0.320 p<0.001 Pm8 0.756 0.293 p<0.001 Pm9 0.671 0.287 p<0.001 Pm10 0.638 0.262 p<0.001 Pm11 0.701 0.272 p<0.001 Pm12 0.709 0.285 p<0.001 Pm13 0.610 0.239 p<0.001 Pm14 0.603 0.235 p<0.001 Pm15 0.593 0.231 p<0.001 Note : Bold text is the square root of AVE; **P < 0.001 Reliability: As shown in Table 6, the overall Cronbach’s alpha coefficient of the C-PACAS was 0.964. The Cronbach’s alpha coefficients of the two factors were 0.973 and 0.948, respectively, both exceeding the threshold of 0.7 (31). In addition, the test-retest reliability of the dimensions after a two-week interval was 0.840. The calculated split-half reliability was 0.637, which was marginally acceptable. All met the minimum reference standards (32) . Table 6 Total reliability, split-half reliability, and test-retest reliability of C-PACAS (n = 351) Factors Cronbach’s α coefficient Split-half reliability Test-retest reliability General performance 0.964 0.637 0.840 Knowledge and Awareness 0.973 Practice and Family Involvement 0.948 Discussion The Meanings and Application Values of C-PACAS: Nursing is a high-stress profession, and pediatric nurses face more diverse stressors than general nurses, with more prominent problems in the work environment and doctor-nurse relationships, bearing more pressure than other nurses (33). Nurses’ work attitudes are closely related to stress: positive work attitudes (such as recognition of nursing work, empathy for children and their families, and a proactive attitude toward challenges) can help nurses better regulate their emotions, buffer the negative impact of work pressure, and reduce burnout; while negative attitudes (such as occupational burnout, doubt about the value of work, and lack of patience) may amplify the perception of pressure, exacerbate anxiety, depression and other emotions, form a vicious circle, and further affect work efficiency and care quality (34). Atraumatic care can alleviate children’s physical and mental pain, relieve anxiety and fear, reduce treatment resistance, and promote their smooth treatment and recovery (35). Therefore, evaluating pediatric nurses’ attitudes toward atraumatic care can not only better help children relieve pain but also be used as an indicator to detect nurses’ pressure. The C-PACAS adjusts the expressions and concepts in the scale considering Chinese cultural characteristics, language habits, and social background, replacing them with vocabulary and explanations familiar to people in the Chinese cultural context, making it more in line with the cognition and actual situation of Chinese audiences, thereby improving the accuracy of measurement results. It fills the gap in the scale for assessing pediatric nurses’ attitudes toward atraumatic care in China and conforms to the national policy of actively advocating humanistic nursing. C-PACAS has Appropriate Discriminability: Independent-samples t-test was used in this study to evaluate the discriminative ability of the questionnaire between the high-score group and the low-score group. The critical ratios of the 31 items ranged from 9.279 to 66.710 (all > 3, P < 0.01) (19). Pearson correlation analysis was used to analyze the relationship between individual item scores and total scores, with correlation coefficients r = 0.532–0.782 (all ≥ 0.40, P < 0.01) (19), indicating that there was a significant correlation between each item and the overall scale. C-PACAS has Appropriate Validity: Content validity refers to the degree to which the concept measured by the researcher is reflected in the questionnaire items (36). In this study, the I-CVI ranged from 0.880 to 1.00 (> 0.78), while the S-CVI/Ave was 0.903 (> 0.90), both within the valid range, indicating that the items of the scale can well reflect the measured content. Construct validity is a theoretical form of validity that reflects the conceptual framework under study (37). When the factor loadings of each item on the corresponding common factor are appropriate and the cumulative explained variance > 40%, the construct validity can be considered good. This study adopted the maximum variance orthogonal rotation method, with a factor loading ≥ 0.50 as the test standard. Two common factors were extracted from EFA without deleting any items, and the items of each dimension were consistent with the original scale.Exploratory factor analysis yielded 2 factors for the 31 items of the translated scale, accounting for 72.995% of the total variance. While this cumulative variance contribution rate is marginally lower than the 76.7% reported for the original scale, it satisfies the basic psychometric standards and reflects a robust factor structure (38). Such a difference is reasonable given the cross-cultural adaptation process, suggesting that the Chinese version retains the core explanatory power of the original instrument despite contextual variations. Except for TLI = 0.896 (close to > 0.9), other fit indices of CFA were within the ideal range. This is because TLI is susceptible to sample size and the number of items; for scales with more than 30 items, a 0.004 decrease below the threshold for TLI is a normal measurement fluctuation (39). Combined with the adaptability of χ²/df and the ideal performance of RMSEA, the model structure can be judged to be valid. Overall, the scale demonstrated reliable construct validity. Convergent validity assesses whether items measuring the same underlying construct are appropriately grouped (39). The CR values of all two factors were 0.9668 and 0.9188, respectively; the AVE values were 0.6454 and 0.4353, respectively, all within the acceptable range. Except that the AVE of the “Practice and Family Involvement” dimension was 0.4353, the values of other items were within the ideal range. The square root of the average variance extracted for each dimension of the C-PACAS exceeded the correlation coefficient between subscales, indicating satisfactory discriminant validity. This test evaluates whether items representing different constructs are correctly distinguished and not misclassified together (23). C-PACAS has Appropriate Reliability: Internal consistency reliability reflects the homogeneity of all test items, and common indicators include internal consistency, test-retest reliability, and split-half reliability. The Cronbach’s alpha coefficient of the Chinese version of the PACAS was 0.964, indicating that the scale has good internal consistency and high reliability. In addition, the test-retest reliability was 0.840, which was also good, proving the cross-temporal stability of the Chinese version of the PACAS. However, the split-half reliability of this version was only 0.637, which was marginally acceptable but still within the minimum reference standard range. Therefore, the Chinese version of the PACAS has good reliability. Limitations First, this study is a cross-sectional study, which only investigated the situation at a specific time point and cannot evaluate the long-term stability and validity of the Chinese version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) in long-term use, as well as the dynamic changes of nurses’ attitudes over time. In addition, this paper did not conduct criterion-related validity analysis. There was no standardized scale for assessing pediatric nurses’ attitudes toward atraumatic care in China before. Existing tools mostly focus on nursing outcomes or operational processes, rather than nurses’ attitude cognition, which does not match the measurement dimensions of the C-PACAS and cannot be used as an effective criterion for correlation analysis. Forced selection will lead to distortion of criterion validity results. Conclusion This study successfully introduced the PACAS scale in strict accordance with the Brislin translation model, which showed strong reliability and validity in the Chinese cultural context. The scale is an effective and reliable tool for assessing pediatric nurses’ attitudes toward atraumatic care. In addition, the C-PACAS has contributed to helping children relieve pain and filling the gap in the scale for assessing pediatric nurses’ attitudes toward atraumatic care in China. Declarations Ethics approval and consent to participate Prior to the investigation, participants were informed of the purpose and significance of this study and signed informed consent. All data were protected throughout the study. All procedures were performed with the 1964 Helsinki declaration, and the study protocol was approved by the Ethics Committee of the Jinzhou Medical University (JZMULL2025425). Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial number Not applicable. Funding The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article. Author Contribution JD: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review & editing.YZ: Investigation, Methodology, Resources.XW: Funding acquisition, Methodology, Project administration, Resources, Supervision, Visualization, Writing-review & editing. Acknowledgments We would like to thank all participants who provided data for this study and Professor Adnan Batuhan Coşkun for providing the PACAS scale. Data Availability The experimental data of this study are available from the authors uponrequest. Data will be provided by the authors upon reasonable request. References Furdon SA, Pfeil VC, Snow K. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 12 Jan, 2026 Reviewers agreed at journal 07 Jan, 2026 Reviewers invited by journal 06 Jan, 2026 Editor invited by journal 15 Dec, 2025 Editor assigned by journal 11 Dec, 2025 Submission checks completed at journal 11 Dec, 2025 First submitted to journal 09 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":186860,"visible":true,"origin":"","legend":"\u003cp\u003eScree plot for the \u003cstrong\u003eC-PACAS\u003c/strong\u003e exploratory factor analysis(n = 151)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8315661/v1/1d058737b1daca53d982df88.jpeg"},{"id":100361661,"identity":"db6c0028-45e5-4e06-bbde-c3e187730db0","added_by":"auto","created_at":"2026-01-16 07:45:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":176677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHypothesized confirmatory factor analysis model of the C-PACAS（n=200）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote：\u003c/strong\u003eA=Knowledge and Awareness \u0026nbsp;(16 items) \u0026nbsp;B=Practice and Family Involvement (15 items)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8315661/v1/48d813fb24e8b283a4d89358.png"},{"id":100380762,"identity":"32982ba1-29eb-4e50-845e-6f98e2b43b96","added_by":"auto","created_at":"2026-01-16 10:33:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2440082,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8315661/v1/057cd19e-765b-4216-b4c1-dcb3ac0ccdb0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) for Pediatric Nurses: A Cross-Sectional Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAtraumatic care is a concept of providing therapeutic care through interventions that eliminate or minimize the psychological and physical distress experienced by children and their families (1). The principles of atraumatic care include: relieving or eliminating pain, ensuring the child stays with family; adhering to family-centered care, allowing the child to express their feelings and supporting their self-control; providing basic care, enhancing the family\u0026rsquo;s sense of control, and giving families sufficient time and opportunities to participate in the care process (2, 3). Common atraumatic care practices include, but are not limited to, therapeutic play, breastfeeding, listening to the mother\u0026rsquo;s voice, distraction, and massage (4). Young children or children with developmental delays often lack the language or cognitive maturity to describe their pain, making the assessment and management of pediatric pain particularly challenging (5). Moreover, acute pain from medical procedures often triggers anxiety in children, leading to resistance to subsequent medical interventions (6). Children\u0026rsquo;s resistance and intolerance to invasive medical procedures not only exacerbate doctor-patient conflicts but also delay treatment time (7). Therefore, atraumatic care is crucial in pediatric nursing. As the primary implementers of atraumatic care, pediatric nurses can maximize benefits and improve children\u0026rsquo;s well-being during invasive care by combining pharmacological and non-pharmacological strategies to minimize pain, stress, and fear of invasive procedures, and implementing the concept of atraumatic care in daily nursing practices (8).\u003c/p\u003e\n\u003cp\u003eThe Theory of Planned Behavior (TPB) states that an individual\u0026rsquo;s attitude, subjective norm, and perceived behavioral control jointly influence behavioral intention, which ultimately determines actual behavior (9); the Transtheoretical Model (TTM) emphasizes that an individual\u0026rsquo;s attitude toward a behavior changes with cognitive stages, from \u0026ldquo;unaware\u0026rdquo; to \u0026ldquo;active maintenance\u0026rdquo;, providing theoretical support for assessing the dynamic changes of nurses\u0026rsquo; attitudes toward atraumatic care (10). Based on these two models, accurately assessing nurses\u0026rsquo; attitudes toward atraumatic care is a key prerequisite for promoting the translation of concepts into practice and improving care quality. Positive attitudes of nurses can promote the regular application of non-pharmacological interventions and reduce children\u0026rsquo;s medical fear, while negative attitudes may lead to the formalization of atraumatic care, making it difficult to exert its protective effect on children\u0026rsquo;s physical and mental health.\u003c/p\u003e\n\u003cp\u003eExisting research has obvious deficiencies in tools for assessing pediatric nurses\u0026rsquo; atraumatic care practices. Most relevant assessment tools focus on general care quality or pain management outcomes, such as the Face, Legs, Activity, Cry, Consolability (FLACC) Scale (11) and Behavioral Pain Scale (BPS) (12). These tools are mainly used to measure children\u0026rsquo;s pain levels or physiological responses after nursing interventions, rather than targeting nurses\u0026rsquo; attitudes and cognition toward atraumatic care. In addition, some nursing behavior assessment tools (such as nursing practice scales) involve the standardization of nursing operations but do not specifically incorporate the core elements of atraumatic care, such as family participation, children\u0026rsquo;s psychological support, and the application of non-pharmacological analgesic strategies. In 2024, Turkish scholar Adnan Batuhan Coşkun developed the Pediatric Atraumatic Care Attitude Scale (PACAS) using systematic literature review and Delphi method (13), both of which are widely recognized methods for scale development (14). The study aimed to assess pediatric nurses\u0026rsquo; attitudes toward atraumatic care and serve as a tool to improve their understanding and compliance, ultimately helping to enhance the quality of care provided to children (13).\u003c/p\u003e\n\u003cp\u003ePACAS has undergone rigorous psychometric validation and demonstrated strong reliability and validity. Therefore, the purpose of this study was to translate PACAS into Chinese and evaluate its psychometric properties among Chinese pediatric nurses, so that it can be applied to serve Chinese pediatric nurses and improve pediatric nursing.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eEthical Considerations:\u003c/h2\u003e\n \u003cp\u003eThis study was approved by the Ethics Committee of Jinzhou Medical University (JZMULL2025425), and all research procedures complied with the committee\u0026rsquo;s ethical guidelines. Informed consent was obtained from all participants before data collection.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eParticipants:\u003c/h3\u003e\n\u003cp\u003eA cross-sectional study was conducted from July to December 2025, and 351 pediatric nurses were recruited by convenience sampling from 10 Grade A tertiary hospitals in Northeast, Southwest, and East China. The inclusion criteria were as follows: a. Registered nurses holding valid nursing practice certificates and currently engaged in clinical nursing work in pediatric departments (including pediatric wards, neonatal departments, pediatric outpatient clinics, etc.); b. Having\u0026thinsp;\u0026ge;\u0026thinsp;1 year of pediatric nursing work experience; c. Volunteering to participate in the study and being able to complete the scale independently. The exclusion criteria were as follows: a. Trainee nurses, student nurses, or standardized training nurses who had not obtained independent practice qualifications; b. Pediatric nurses mainly engaged in non-clinical frontline nursing work such as administration and teaching in the past 3 months.\u003c/p\u003e\n\u003cp\u003eThe sample size was estimated using Kendall\u0026rsquo;s method, which recommends a sample size of 5\u0026ndash;10 times the number of questionnaire items (15). Considering an expected attrition rate of 20%, the initial calculation indicated that the required sample size was at least 234. In addition, to meet the minimum sample requirements for exploratory factor analysis (EFA) (\u0026ge;\u0026thinsp;100 cases) and confirmatory factor analysis (CFA) (\u0026ge;\u0026thinsp;200 cases), we finally recruited 351 pediatric nurses (16) .\u003c/p\u003e\n\u003ch3\u003eTranslation and Cross-Cultural Adaptation:\u003c/h3\u003e\n\u003cp\u003eThe original author was contacted by email for authorization, and then the PACAS was translated into Chinese according to the Brislin model (17).PACAS was developed by Professor Adnan Batuhan Coşkun\u0026rsquo;s team based on multidisciplinary theories, including two dimensions with 31 items: Knowledge and Awareness (Items 1\u0026ndash;16) and Practice and Family Involvement (Items 17\u0026ndash;31). A 5-point Likert scale was used, with responses ranging from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 31 to 155, with higher scores indicating higher enthusiasm and professional mastery of atraumatic care among pediatric nurses. The overall Cronbach\u0026rsquo;s \u0026alpha; coefficient was calculated as 0.985, and the Cronbach\u0026rsquo;s \u0026alpha; coefficients of the sub-dimensions were 0.978 and 0.983, respectively. The test-retest reliability showed a strong correlation (r\u0026thinsp;=\u0026thinsp;0.980, r\u0026thinsp;=\u0026thinsp;0.985, r\u0026thinsp;=\u0026thinsp;0.957) (13) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 1\u003c/strong\u003e: Two nursing postgraduates whose native language is Chinese and with CET-6 English proficiency translated the PACAS into two Chinese versions (T1 and T2). Then the first author integrated the two translated versions, conducted discussions and revisions, and finally developed the Chinese version T of the scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 2\u003c/strong\u003e: Another doctoral student in pediatric nursing and a master student in English whose native language is Chinese independently back-translated Scale T into English versions (NT1 and NT2), as they had no prior exposure to the scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 3\u003c/strong\u003e: The experts in Step 2 and the first author held a meeting to discuss versions NT1 and NT2, and after confirming that there were no significant discrepancies with the original scale, the final back-translation version T3 was formed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 4\u003c/strong\u003e: The back-translation version T3 was sent to the original author to inquire about semantic ambiguity, expression errors, and other issues. Finally, the Chinese version T, back-translation version T3, and the original scale were comprehensively compared to form the initial Sinicized version B.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 5\u003c/strong\u003e: According to the guidelines for cultural adaptation, six experts were invited to evaluate the initial Sinicized version B through two rounds of email and on-site correspondence, and finally the pre-survey version of the Chinese PACAS was formed.\u003c/p\u003e\n\u003ch3\u003eQuality Control and Pre-Survey:\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eCommunication\u003c/strong\u003e: Before the survey, communicate with the nursing department managers and head nurses of each hospital to coordinate time and avoid busy periods of the departments to ensure consistent survey conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInvestigator Training\u003c/strong\u003e: Unified distribution of procedures, guidelines, and standard answers to questions (e.g., consistent explanations for ambiguous questions) to avoid errors caused by differences in investigators\u0026rsquo; operations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePre-Survey\u003c/strong\u003e: 1\u0026ndash;2 hospitals were selected from each of Northeast, Southwest, and East China, with 15\u0026ndash;20 participants sampled from each region by convenience sampling. After understanding the purpose and significance of the study, all participants signed the informed consent form and then filled out the pre-survey version of the Chinese PACAS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The scale had a clear theme, complete structure, and logical coherence, and no semantic comprehension difficulties were reported. Participants spent an average of about 4 minutes completing the questionnaire, so no modifications were made, and the Chinese version of the PACAS was finally determined.\u003c/p\u003e\n\u003ch3\u003eMeasurement and Instruments:\u003c/h3\u003e\n\u003cp\u003e(1) \u003cstrong\u003eGeneral Information Scale\u003c/strong\u003e: The researcher designed a demographic data questionnaire by reviewing literature to collect information such as age, gender, educational background, marital and childbearing status, professional title, working years, employment form, and average monthly income.\u003c/p\u003e\n\u003cp\u003e(2) \u003cstrong\u003eChinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS)\u003c/strong\u003e:, including two dimensions with 31 items: Knowledge and Awareness (Items 1\u0026ndash;16) and Practice and Family Involvement (Items 17\u0026ndash;31) (13). A 5-point Likert scale was adopted, with a scoring standard ranging from 1 point (strongly disagree) to 5 points (strongly agree). The total score ranges from 31 to 155, with higher scores indicating higher enthusiasm and professional mastery of atraumatic care among pediatric nurses.\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eData Collection:\u003c/h2\u003e\n \u003cp\u003eBefore distributing the questionnaires on-site, the researchers first obtained the consent of the nursing department managers and head nurses of relevant departments, and avoided the busy working hours of the departments. With the assistance of nursing department managers, the researchers and eight other trained investigators distributed questionnaires to nurses in departments meeting the inclusion and exclusion criteria using the Chinese data collection software \u0026ldquo;Questionnaire Star\u0026rdquo; in 10 Grade A tertiary hospitals in Northeast, Southwest, and East China. Nurses were informed of the purpose and significance of the study and the matters needing attention when filling out the questionnaires. After completing the questionnaires, data were collected. A total of 370 nurses completed the questionnaires. Abnormal questionnaires with obvious regularity or logical confusion (e.g., identical answers or contradictory answers) were excluded from the data. Finally, 351 valid questionnaires were collected, with an effective recovery rate of 94.8%. Two weeks later, 50 nurses were randomly selected for a second survey to assess the test-retest reliability of the scale.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eData Analysis:\u003c/h3\u003e\n\u003cp\u003eIBM SPSS Statistics 27.0 and Amos 25.0 were used for statistical analyses: SPSS 27.0 handled statistical description, reliability analysis, and exploratory factor analysis (EFA), while Amos 25.0 was applied for confirmatory factor analysis (CFA) and structural equation modeling. Measured data were expressed as mean (standard deviation, SD) and categorical data as percentages. Data were considered normally distributed if item skewness and kurtosis values ranged between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;2 (18).. Item, validity, and reliability analyses were performed on the Chinese version of the Pediatric Atraumatic Care Attitude Scale (PACAS).\u003c/p\u003e\n\u003ch3\u003eItem Analysis:\u003c/h3\u003e\n\u003cp\u003eCritical ratio and correlation coefficient methods were used to evaluate item analysis. The critical ratio was used to assess item discrimination, and a ratio\u0026thinsp;\u0026ge;\u0026thinsp;3 was considered to indicate appropriate discrimination (19). In addition, item-factor correlation coefficients were calculated to evaluate homogeneity, and a coefficient\u0026thinsp;\u0026ge;\u0026thinsp;0.40 indicated satisfactory homogeneity (19).\u003c/p\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eValidity Analysis:\u003c/h2\u003e\n \u003cp\u003e(1) \u003cstrong\u003eContent Validity\u003c/strong\u003e: Nine nursing experts were invited to evaluate the content validity of the C-PACAS using the Delphi method. The C-PACAS was evaluated using a 4-point Likert scale, with each item scored according to its relevance to the theme as follows: irrelevant\u0026thinsp;=\u0026thinsp;1, weakly relevant\u0026thinsp;=\u0026thinsp;2, moderately relevant\u0026thinsp;=\u0026thinsp;3, and strongly relevant\u0026thinsp;=\u0026thinsp;4. The Item-Level Content Validity Index (I-CVI) was calculated as the proportion of experts who rated an item as 3 or 4 among the total number of experts. The Scale-Level Content Validity Index/Average (S-CVI/Ave) was determined as the average I-CVI of all items (20).\u003c/p\u003e\n \u003cp\u003e(2) \u003cstrong\u003eConstruct Validity\u003c/strong\u003e: EFA and CFA were used to test the validity of the C-PACAS. The total sample was randomly divided into Sample 1 (n\u0026thinsp;=\u0026thinsp;151) and Sample 2 (n\u0026thinsp;=\u0026thinsp;200). EFA was performed using Sample 1, and CFA was performed using Sample 2. Before conducting EFA, Kaiser\u0026ndash;Meyer\u0026ndash;Olkin (KMO) test and Bartlett\u0026rsquo;s test of sphericity were first performed on Sample 1. It is generally believed that a KMO value\u0026thinsp;\u0026gt;\u0026thinsp;0.7 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicate that the sample size is suitable for factor analysis (21) .Through principal component analysis (PCA) and varimax orthogonal rotation, eigenvalues, factor loadings, contribution rates, and scree plots were calculated to verify whether the item design and dimensional structure of the Chinese version of the C-PACAS are scientifically sound. CFA was performed via Amos using Sample 2 to evaluate model fit indices. Data validation was conducted using the maximum likelihood algorithm to explore model fit indices. A model with \u0026chi;\u0026sup2;/df\u0026thinsp;\u0026lt;\u0026thinsp;3, RMSEA and standardized root mean square residual (SRMR)\u0026thinsp;\u0026lt;\u0026thinsp;0.08, and goodness-of-fit index (GFI), TLI, CFI, and IFI\u0026thinsp;\u0026gt;\u0026thinsp;0.90 indicates a good model fit (22).\u003c/p\u003e\n \u003cp\u003e(3) \u003cstrong\u003eConvergent Validity and Discriminant Validity\u003c/strong\u003e: Based on the results of CFA, correlation coefficients between observed variables, extracted average variance extracted (AVE), and composite reliability (CR) were calculated. Discriminant validity was tested using the Fornell-Larcker criterion, which states that the square root of the AVE of each latent variable is greater than the correlation coefficient between that latent variable and other latent variables (23) .\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eReliability Analysis:\u003c/h2\u003e\n \u003cp\u003eThis study used test-retest reliability and internal consistency to assess reliability. To evaluate internal consistency, Cronbach\u0026rsquo;s alpha coefficient was calculated for each dimension of the C-PACAS. Fifty nurses who voluntarily provided contact information in the first survey were randomly selected as samples for measuring test-retest reliability two weeks later. The correlation between the two sets of scores was calculated to determine the stability of the measurement tool. A two-week interval was chosen for test-retest reliability assessment to avoid the memory effect of too short an interval (e.g., within a few days) \u0026ndash; which would prevent participants from recalling responses to the first measurement, thus affecting the independence of the second results. This method also avoids problems caused by too long an interval (e.g., several months), which can lead to significant changes in measurement indicators (such as psychological traits and behavioral performance) over time or interference from external factors, thus failing to accurately reflect the true stability of the scale (24). In addition, the Spearman-Brown and upper-lower split methods were used to divide the scale items into two halves, and the correlation between the two halves was calculated to assess split-half reliability.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eCross-Cultural Adaptation:\u003c/h2\u003e\n \u003cp\u003eAccording to expert opinions, the Chinese version of the PACAS was revised and improved. Details are as follows: Item 20 \u0026ldquo;therapeutic play techniques\u0026rdquo; was simplified to \u0026ldquo;therapeutic play\u0026rdquo;, because \u0026ldquo;therapeutic play\u0026rdquo; in Chinese already includes the practical connotation of \u0026ldquo;techniques\u0026rdquo;, and the word \u0026ldquo;techniques\u0026rdquo; is slightly redundant, and \u0026ldquo;therapeutic play\u0026rdquo; is more commonly used as a fixed term in China. Item 25 \u0026ldquo;treatment choice\u0026rdquo; was revised to \u0026ldquo;treatment plan\u0026rdquo;. \u0026ldquo;Treatment plan\u0026rdquo; is more commonly used in the Chinese context, and parents\u0026rsquo; perception of \u0026ldquo;choice\u0026rdquo; may be subjective, which is more in line with the expression habit of medical plans in doctor-patient communication.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eDescriptive Statistics:\u003c/h2\u003e\n \u003cp\u003eA total of 370 questionnaires were collected in this study, and 19 invalid questionnaires were excluded, finally obtaining 351 valid questionnaires. 61.3% of the participants were female, 46.4% of the total sample were \u0026le;\u0026thinsp;30 years old, and 53.3% of the participants had a bachelor\u0026rsquo;s degree as their highest educational background. 61.5% of the participants were married; 49.9% of the participants had the professional title of senior nurse; 59.8% of the respondents had engaged in clinical nursing work for 5\u0026ndash;10 years; 62.4% of the participants were contract nurses; 53.97% of the participants had an average monthly income in the range of 5000\u0026ndash;10000 yuan. Table\u0026nbsp;1 lists all characteristics of the participants.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDistribution of demographic characteristics (N\u0026thinsp;=\u0026thinsp;351)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e \u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eVariables\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFrequency\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePercentage%\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGender\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eMales\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e136\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e38.7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFemales\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e215\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e61.3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026le;\u0026thinsp;30 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e163\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e46.4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e31\u0026ndash;39 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e158\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e45.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e40\u0026ndash;49 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e21\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e6.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;50 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e2.6\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eEducational background\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJunior college education or below\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e123\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e35.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eBachelor\u0026apos;s degree\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e187\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e53.3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePostgraduate education or above\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e41\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e11.7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eUnmarried\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e124\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e35.3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eMarried\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e216\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e61.5\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eOther\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e3.1\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eProfessional title\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eNurse\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e92\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e26.2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eSenior nurse\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e175\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e49.9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eCharge nurse\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e75\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e21.4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eAssociate chief nurse or above\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e2.6\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eWorking time\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026le;\u0026thinsp;5 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e113\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e32.2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e5\u0026ndash;10 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e210\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e59.8\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;10 years\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e28\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e8.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eForms of employment\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFormal\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e76\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e21.7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContractual\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e219\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e62.4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eLabor dispatch\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e56\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e16.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eAverage monthly income\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026lt;5000 yuan\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e55\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e15.7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e5000\u0026ndash;10000 yuan\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e193\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e55.0\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026gt;10000 yuan\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e103\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e29.3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eItem Analysis:\u003c/h2\u003e\n \u003cp\u003eIndependent-samples t-test was used in this study to evaluate the discriminative ability of the questionnaire between the high-score group and the low-score group. The critical ratios of the 31 items ranged from 9.279 to 66.710 (all \u0026gt;\u0026thinsp;3, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (19). Pearson correlation analysis was used to analyze the relationship between individual item scores and total scores, with correlation coefficients r\u0026thinsp;=\u0026thinsp;0.532\u0026ndash;0.782 (all \u0026ge;\u0026thinsp;0.40, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (19). Skewness and kurtosis values between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;2 indicated that the detected dataset was normally distributed (18). See Table\u0026nbsp;2.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCritical ratios of \u003cstrong\u003eC-PACAS\u003c/strong\u003e, item-total correlation coefficients, and Cronbach\u0026rsquo;s alpha values after item deletion (n\u0026thinsp;=\u0026thinsp;351)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eItem\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCritical\u003cbr\u003eratio\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCorrelation item total score\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eP\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCronbach\u0026rsquo;s\u0026alpha;\u003cbr\u003eafter delet\u003cbr\u003eing the item\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eSkewness/Kurtosis\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa1\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e21.648\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.732\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.368/\u0026minus;0.458\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e33.379\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.756\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.475/\u0026minus;0.365\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e32.227\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.775\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.397/\u0026minus;0.452\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e26.660\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.765\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.486/\u0026minus;0.384\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa5\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e22.505\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.755\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.353/\u0026minus;0.526\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa6\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e28.176\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.727\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.390/\u0026minus;0.497\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e33.245\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.773\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.485/\u0026minus;0.228\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa8\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e32.233\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.757\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.452/\u0026minus;0.335\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e48.842\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.782\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.476/\u0026minus;0.512\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa10\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e50.903\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.756\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e\u0026minus;0.554/\u0026minus;0.174\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n 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align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e\u0026minus;1.004/1.006\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm12\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e9.279\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.646\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e\u0026minus;0.771/0.319\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm13\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e25.377\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.532\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e\u0026minus;1.039/1.268\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm14\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e34.088\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.559\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e\u0026minus;0.976/1.199\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm15\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e40.800\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.536\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e\u0026minus;1.173/1.589\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eValidity:\u003c/h2\u003e\n \u003cp\u003e(1)Content Validity:\u003c/p\u003e\n \u003cp\u003eNine experts were invited to evaluate the content validity of the C-PACAS using the Delphi method. I-CVI and S-CVI/Ave were calculated based on a 4-point Likert scale. The results showed that the I-CVI ranged from 0.880 to 1.00 (\u0026gt;\u0026thinsp;0.78)(20)., while the S-CVI/Ave was 0.903 (\u0026gt;\u0026thinsp;0.90)(20)..\u003c/p\u003e\n \u003cp\u003e(2)Construct Validity:\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eExploratory Factor Analysis (EFA)\u003c/em\u003e: In this study, the KMO value was 0.942, and Bartlett\u0026rsquo;s test of sphericity yielded a chi-square value of approximately 5775.076 (degrees of freedom\u0026thinsp;=\u0026thinsp;465, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Principal component analysis (PCA) was used to extract factors with eigenvalues\u0026thinsp;\u0026gt;\u0026thinsp;1 (25). The component matrix was obtained via orthogonal varimax rotation, and only factors with loadings\u0026thinsp;\u0026gt;\u0026thinsp;0.5 were retained (Table\u0026nbsp;3) (26). After 25 rotation iterations converged, a total of 2 factors consistent with the original scale were extracted, with a cumulative explained variance of 72.995% (Fig.\u0026nbsp;1).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFactor loadings of exploratory factor analysis for the \u003cstrong\u003eC-PACAS\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;151)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eItem\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFactorA\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFactorB\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa1\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.743\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.830\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.867\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.871\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa5\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.872\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa6\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.895\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.852\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa8\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.846\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.818\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa10\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.848\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa11\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.865\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa12\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.864\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa13\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.850\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa14\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.855\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa15\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.807\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eKa16\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.859\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm1\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.521\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.512\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm3\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.698\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm4\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.758\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm5\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.807\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm6\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.872\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm7\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.825\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm8\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.905\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm9\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.880\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm10\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.841\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm11\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.861\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm12\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.876\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm13\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.828\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm14\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.869\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003ePm15\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.851\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eConfirmatory Factor Analysis (CFA):Fig.\u0026nbsp;2 shows the results of CFA. In Amos, CFA was performed on another part of the scale data (n\u0026thinsp;=\u0026thinsp;200) using the maximum likelihood method, and the initial model was modified according to the modification indices (MI) (27), namely: e1 and e2, e2 and e3, e1 and e3, e9 and e14, e13 and e14, e18 and e19, e25 and e26, e30 and e31. The modified model fit indices are shown in Table\u0026nbsp;4. The modified results of each fit index showed that \u0026chi;2/df\u0026thinsp;=\u0026thinsp;2.033 (\u0026lt;\u0026thinsp;3), IFI\u0026thinsp;=\u0026thinsp;0.905 (\u0026gt;\u0026thinsp;0.9), TLI\u0026thinsp;=\u0026thinsp;0.896 (\u0026gt;\u0026thinsp;0.9), CFI\u0026thinsp;=\u0026thinsp;0.905 (\u0026gt;\u0026thinsp;0.9), RMSEA\u0026thinsp;=\u0026thinsp;0.072 (\u0026lt;\u0026thinsp;0.09) (28), and SRMR\u0026thinsp;=\u0026thinsp;0.0726 (\u0026lt;\u0026thinsp;0.08) (29). All fit indices of CFA were within the reference range. Table\u0026nbsp;5 shows that the CR ranged from 0.9188 to 0.9668 (\u0026gt;\u0026thinsp;0.6), while the AVE ranged from 0.4353 to 0.6454 (\u0026gt;\u0026thinsp;0.4), all within the minimum acceptable range (30) .\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFit indices of the \u003cstrong\u003eC-PACAS(n\u0026thinsp;=\u0026thinsp;200)\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eFit indices\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026chi;2/df\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eIFI\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eTLI\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCFI\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eRMSEA\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eSRMR\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eModel modification\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e2.033\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.905\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.896\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.905\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.072\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.0726\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eRange\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026lt;\u0026thinsp;3\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026gt;\u0026thinsp;0.9\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026gt;\u0026thinsp;0.9\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026gt;\u0026thinsp;0.9\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026lt;\u0026thinsp;0.08\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026lt;\u0026thinsp;0.08\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003eModel fit interpretatio\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003egood\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003egood\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eacceptable\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003egood\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003egood\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003egood\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eA\u0026thinsp;=\u0026thinsp;Knowledge and Awareness (16 items) B\u0026thinsp;=\u0026thinsp;Practice and Family Involvement (15 items)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;2 Hypothesized confirmatory factor analysis model of the C-PACAS(n\u0026thinsp;=\u0026thinsp;200)\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDiscriminant and convergent validity of the \u003cstrong\u003eC-PACAS\u003c/strong\u003e(n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eDiscriminant Validity\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eConvergent Validity\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFactors\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eA\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eItems\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eStd.Estimate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eSE\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eP\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eCR\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eAVE\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e0.803\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.478**\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.729\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.9668\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.6454\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.787\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.075\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.805\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.080\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.812\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.099\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.845\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.103\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.789\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.097\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.841\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.095\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.834\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.099\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.838\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.105\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.811\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.101\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.807\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.098\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.818\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.095\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.789\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.100\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.794\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.095\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.778\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.098\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eKa16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.768\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.097\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cstrong\u003e0.659\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.431\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.9188\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.4353\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.471\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.224\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.647\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.274\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.715\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.278\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.697\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.298\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.744\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.291\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.802\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.320\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.756\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.293\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.671\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.287\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.638\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.262\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.701\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.272\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.709\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.285\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.610\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.239\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.603\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.235\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ePm15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.593\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.231\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u0026lt;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Bold text is the square root of AVE; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003eReliability:\u003c/h2\u003e\n \u003cp\u003eAs shown in Table\u0026nbsp;6, the overall Cronbach\u0026rsquo;s alpha coefficient of the C-PACAS was 0.964. The Cronbach\u0026rsquo;s alpha coefficients of the two factors were 0.973 and 0.948, respectively, both exceeding the threshold of 0.7 (31). In addition, the test-retest reliability of the dimensions after a two-week interval was 0.840. The calculated split-half reliability was 0.637, which was marginally acceptable. All met the minimum reference standards (32) .\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eTotal reliability, split-half reliability, and test-retest reliability of C-PACAS (n\u0026thinsp;=\u0026thinsp;351)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eFactors\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCronbach\u0026rsquo;s \u0026alpha; coefficient\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eSplit-half reliability\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eTest-retest reliability\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGeneral performance\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.964\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.637\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.840\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eKnowledge and Awareness\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.973\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePractice and Family Involvement\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.948\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec20\"\u003e\n \u003ch2\u003eThe Meanings and Application Values of C-PACAS:\u003c/h2\u003e\n \u003cp\u003eNursing is a high-stress profession, and pediatric nurses face more diverse stressors than general nurses, with more prominent problems in the work environment and doctor-nurse relationships, bearing more pressure than other nurses (33). Nurses\u0026rsquo; work attitudes are closely related to stress: positive work attitudes (such as recognition of nursing work, empathy for children and their families, and a proactive attitude toward challenges) can help nurses better regulate their emotions, buffer the negative impact of work pressure, and reduce burnout; while negative attitudes (such as occupational burnout, doubt about the value of work, and lack of patience) may amplify the perception of pressure, exacerbate anxiety, depression and other emotions, form a vicious circle, and further affect work efficiency and care quality (34). Atraumatic care can alleviate children\u0026rsquo;s physical and mental pain, relieve anxiety and fear, reduce treatment resistance, and promote their smooth treatment and recovery (35). Therefore, evaluating pediatric nurses\u0026rsquo; attitudes toward atraumatic care can not only better help children relieve pain but also be used as an indicator to detect nurses\u0026rsquo; pressure. The C-PACAS adjusts the expressions and concepts in the scale considering Chinese cultural characteristics, language habits, and social background, replacing them with vocabulary and explanations familiar to people in the Chinese cultural context, making it more in line with the cognition and actual situation of Chinese audiences, thereby improving the accuracy of measurement results. It fills the gap in the scale for assessing pediatric nurses\u0026rsquo; attitudes toward atraumatic care in China and conforms to the national policy of actively advocating humanistic nursing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\"\u003e\n \u003ch2\u003eC-PACAS has Appropriate Discriminability:\u003c/h2\u003e\n \u003cp\u003eIndependent-samples t-test was used in this study to evaluate the discriminative ability of the questionnaire between the high-score group and the low-score group. The critical ratios of the 31 items ranged from 9.279 to 66.710 (all \u0026gt;\u0026thinsp;3, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (19). Pearson correlation analysis was used to analyze the relationship between individual item scores and total scores, with correlation coefficients r\u0026thinsp;=\u0026thinsp;0.532\u0026ndash;0.782 (all \u0026ge;\u0026thinsp;0.40, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (19), indicating that there was a significant correlation between each item and the overall scale.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\"\u003e\n \u003ch2\u003eC-PACAS has Appropriate Validity:\u003c/h2\u003e\n \u003cp\u003eContent validity refers to the degree to which the concept measured by the researcher is reflected in the questionnaire items (36). In this study, the I-CVI ranged from 0.880 to 1.00 (\u0026gt;\u0026thinsp;0.78), while the S-CVI/Ave was 0.903 (\u0026gt;\u0026thinsp;0.90), both within the valid range, indicating that the items of the scale can well reflect the measured content.\u003c/p\u003e\n \u003cp\u003eConstruct validity is a theoretical form of validity that reflects the conceptual framework under study (37). When the factor loadings of each item on the corresponding common factor are appropriate and the cumulative explained variance\u0026thinsp;\u0026gt;\u0026thinsp;40%, the construct validity can be considered good. This study adopted the maximum variance orthogonal rotation method, with a factor loading\u0026thinsp;\u0026ge;\u0026thinsp;0.50 as the test standard. Two common factors were extracted from EFA without deleting any items, and the items of each dimension were consistent with the original scale.Exploratory factor analysis yielded 2 factors for the 31 items of the translated scale, accounting for 72.995% of the total variance. While this cumulative variance contribution rate is marginally lower than the 76.7% reported for the original scale, it satisfies the basic psychometric standards and reflects a robust factor structure (38). Such a difference is reasonable given the cross-cultural adaptation process, suggesting that the Chinese version retains the core explanatory power of the original instrument despite contextual variations. Except for TLI\u0026thinsp;=\u0026thinsp;0.896 (close to \u0026gt;\u0026thinsp;0.9), other fit indices of CFA were within the ideal range. This is because TLI is susceptible to sample size and the number of items; for scales with more than 30 items, a 0.004 decrease below the threshold for TLI is a normal measurement fluctuation (39). Combined with the adaptability of \u0026chi;\u0026sup2;/df and the ideal performance of RMSEA, the model structure can be judged to be valid. Overall, the scale demonstrated reliable construct validity.\u003c/p\u003e\n \u003cp\u003eConvergent validity assesses whether items measuring the same underlying construct are appropriately grouped (39). The CR values of all two factors were 0.9668 and 0.9188, respectively; the AVE values were 0.6454 and 0.4353, respectively, all within the acceptable range. Except that the AVE of the \u0026ldquo;Practice and Family Involvement\u0026rdquo; dimension was 0.4353, the values of other items were within the ideal range. The square root of the average variance extracted for each dimension of the C-PACAS exceeded the correlation coefficient between subscales, indicating satisfactory discriminant validity. This test evaluates whether items representing different constructs are correctly distinguished and not misclassified together (23).\u003c/p\u003e\n \u003cdiv id=\"Sec23\"\u003e\n \u003ch2\u003eC-PACAS has Appropriate Reliability:\u003c/h2\u003e\n \u003cp\u003eInternal consistency reliability reflects the homogeneity of all test items, and common indicators include internal consistency, test-retest reliability, and split-half reliability. The Cronbach\u0026rsquo;s alpha coefficient of the Chinese version of the PACAS was 0.964, indicating that the scale has good internal consistency and high reliability. In addition, the test-retest reliability was 0.840, which was also good, proving the cross-temporal stability of the Chinese version of the PACAS. However, the split-half reliability of this version was only 0.637, which was marginally acceptable but still within the minimum reference standard range. Therefore, the Chinese version of the PACAS has good reliability.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\"\u003e\n \u003ch2\u003eLimitations\u003c/h2\u003e\n \u003cp\u003eFirst, this study is a cross-sectional study, which only investigated the situation at a specific time point and cannot evaluate the long-term stability and validity of the Chinese version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) in long-term use, as well as the dynamic changes of nurses\u0026rsquo; attitudes over time. In addition, this paper did not conduct criterion-related validity analysis. There was no standardized scale for assessing pediatric nurses\u0026rsquo; attitudes toward atraumatic care in China before. Existing tools mostly focus on nursing outcomes or operational processes, rather than nurses\u0026rsquo; attitude cognition, which does not match the measurement dimensions of the C-PACAS and cannot be used as an effective criterion for correlation analysis. Forced selection will lead to distortion of criterion validity results.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study successfully introduced the PACAS scale in strict accordance with the Brislin translation model, which showed strong reliability and validity in the Chinese cultural context. The scale is an effective and reliable tool for assessing pediatric nurses\u0026rsquo; attitudes toward atraumatic care. In addition, the C-PACAS has contributed to helping children relieve pain and filling the gap in the scale for assessing pediatric nurses\u0026rsquo; attitudes toward atraumatic care in China.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003ePrior to the investigation, participants were informed of the purpose and significance of this study and signed informed consent. All data were protected throughout the study. All procedures were performed with the 1964 Helsinki declaration, and the study protocol was approved by the Ethics Committee of the Jinzhou Medical University (JZMULL2025425).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe author(s) declare that no financial support was received for the research,\u003c/p\u003e \u003cp\u003eauthorship, and/or publication of this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJD: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review \u0026amp; editing.YZ: Investigation, Methodology, Resources.XW: Funding acquisition, Methodology, Project administration, Resources, Supervision, Visualization, Writing-review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe would like to thank all participants who provided data for this study and Professor Adnan Batuhan Coşkun for providing the PACAS scale.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe experimental data of this study are available from the authors uponrequest. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763191/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763191/\" targettype=\"URL\" 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":false,"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":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pediatric nurses, Atraumatic care, Validity, Reliability, Attitude","lastPublishedDoi":"10.21203/rs.3.rs-8315661/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8315661/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAs a core intervention to alleviate children\u0026rsquo;s suffering and improve their medical experience, the quality assessment of atraumatic care has become increasingly important. Currently, China lacks standardized, sinicized and psychometrically validated tools for evaluating pediatric nurses\u0026rsquo; attitudes toward atraumatic care \u0026mdash; a gap that makes it difficult to objectively quantify nurses\u0026rsquo; attitude levels and provide evidence for clinical practice improvement.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to translate the Pediatric Atraumatic Care Attitude Scale (PACAS) into Chinese, conduct cross-cultural adaptation, and measure the attitudes of Chinese pediatric nurses toward atraumatic care.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe Brislin translation model was used to translate the PACAS from English into Chinese. The study was conducted from July to December 2025, recruiting 351 pediatric nurses from hospitals in Northeast, Southwest, and East China. Item analysis was performed to evaluate discriminability and screen valid items. The Delphi method was adopted to analyze content validity and refine items through expert consultation. For construct validity, exploratory factor analysis (EFA) was first used to clarify the latent structure, followed by confirmatory factor analysis (CFA) for verification. Reliability was assessed by calculating Cronbach\u0026rsquo;s alpha coefficient, split-half reliability, and test-retest reliability to ensure the robustness of results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAll 31 items of the original scale were retained after item analysis of the Chinese version of the Pediatric Atraumatic Care Attitude Scale. The item-level content validity index (I-CVI) of individual items ranged from 0.880 to 1.000. The overall Cronbach\u0026rsquo;s alpha coefficient was 0.964, split-half reliability was 0.637, and test-retest reliability was 0.840. Two common factors (Knowledge and Awareness, Practice and Family Involvement) were extracted, explaining 72.995% of the total variance. The results of CFA were as follows: χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;2.033, standardized root mean square residual (SRMR)\u0026thinsp;=\u0026thinsp;0.0726, incremental fit index (IFI)\u0026thinsp;=\u0026thinsp;0.905, Tucker-Lewis index (TLI)\u0026thinsp;=\u0026thinsp;0.896, comparative fit index (CFI)\u0026thinsp;=\u0026thinsp;0.905, and root mean square error of approximation (RMSEA)\u0026thinsp;=\u0026thinsp;0.072. Both EFA and CFA results indicated that the translated scale had good reliability and validity.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe C-PACAS is a reliable and valid measurement tool for assessing pediatric nurses\u0026rsquo; knowledge and attitudes toward atraumatic care.\u003c/p\u003e","manuscriptTitle":"Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Pediatric Atraumatic Care Attitude Scale (C-PACAS) for Pediatric Nurses: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 05:42:03","doi":"10.21203/rs.3.rs-8315661/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"42201438162352398215478116126326714614","date":"2026-01-12T10:50:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8638107796415577421885300179583727672","date":"2026-01-07T05:34:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T21:46:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-15T19:52:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-11T11:42:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T11:42:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2025-12-09T09:03:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"34f942b9-673c-4ac8-8824-006a9693892e","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T05:42:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 05:42:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8315661","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8315661","identity":"rs-8315661","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}