Mean Squared Error Of Approximation Research Articles

Cultural adaptation and validation of the knee injury and osteoarthritis outcome score into Sinhala language in patients with primary knee osteoarthritis: a cross-sectional study

BackgroundKnee Injury and Osteoarthritis Outcome Score (KOOS) scale is a patient-reported outcome measurement tool. It evaluates both short- and long-term consequences of knee injury and primary osteoarthritis. This study aims to translate and validate the KOOS scale for a Sinhala-speaking Sri Lankan population.MethodsA cross sectional study was conducted in three hospitals. Four hundred and fifteen patients comprising 185 males and 227 females (3 subjects did not reveal their gender) with knee osteoarthritis (KOA) participated in the study. Seventy nine participants without KOA were recruited as controls. The functionality and quality of life level in patients and healthy participants were assessed using translated versions of the KOOS and Short Form-36 (SF-36) scales. Internal consistency of the instrument was assessed by Cronbach alpha. Construct validity and test-retest reliability were examined using the Intraclass Correlation Coefficient (ICC). Confirmatory Factor Analysis (CFA) was used to assess factorial validity.ResultsThe mean age (± sd) of the KOA subjects was 54.9 (± 9.2) years and for the control group was 49.2 (± 8.0) years. Majority of the respondents were female and Sinhalese in both groups. Internal consistency reliability was high (Cronbach’s alpha values ≥ 0.70). The test–retest reliability was excellent with the intraclass correlation coefficient for all subscales being above 0.90. Construct validity was assessed by the magnitude of the correlation coefficient between KOOS and SF-36 subscale scores. KOOS Pain scale moderately correlated with SF-36 bodily pain (Pearson’s r = 0.41). SF-36 physical function scores had a weak positive correlation with all KOOS subscales and SF-36 emotional wellbeing was not significantly correlated with KOOS Quality of Life (QoL) subscale. A five-factor Confirmatory Factor Analysis (CFA) model yielded a Comparative Fit Index (CFI) = 0.950, Tucker Lewis Index (TLI) = 0.946, Root Mean Square Error of Approximation (RMSEA) = 0.082 and Standardised Root Mean squared Residual (SRMR) = 0.072.ConclusionThe Sinhala translation of the KOOS scale is a reliable and valid instrument to assess KOA in a Sinhala-speaking Sri Lankan population. Studies to assess its use as a scale to evaluate responsiveness are recommended.

The Chinese version of patient experience with treatment and self-management (PETS vs. 2.0): translation and validation in patients with multimorbidity in primary care in Hong Kong

BackgroundValidated and comprehensive tools to measure treatment burden are needed for healthcare professionals to understand the treatment burden of patients in China. The study aimed to translate and validate the Chinese version of Patient Experience with Treatment and Self-management (PETS vs. 2.0) in patients with multimorbidity in primary care.MethodologyThe translation process of the 60-item PETS vs. 2.0 followed the Functional Assessment of Chronic Illness Therapy (FACIT) Translation, Formatting, and Testing Guidelines. Computer-assisted assessments were conducted in adult primary care patients with multimorbidity from three general out-patient clinics in Hong Kong. A sample of 502 patients completed the assessments from July to December 2023. Internal reliability was examined using Cronbach’s alphas for each domain of the PETS vs. 2.0. Concurrent validity was assessed through the correlations between different domains of PETS vs. 2.0 with established measures including quality of life, frailty, and depression. Confirmatory Factor Analysis (CFA) with maximum likelihood method was carried out to assess the construct validity.ResultsThe mean age of participants was 64.9 years old and 56.2% were female. Internal consistency reliability was acceptable (alpha ≥ 0.70) for most domains. Higher scores of PETS domains were significantly correlated with worse quality of life, higher level of frailty, and more depressive symptoms (p < 0.05). In CFA, after setting the covariances on the error variances, the adjusted model revealed an acceptable model fit (χ2/df = 1.741; root mean square error of approximation (RMSEA) = 0.038; standardized root mean square residual (SRMR) = 0.058; comparative fit index (CFI) = 0.911; Tucker-Lewis Index (TLI) = 0.903). All standardized factor loadings were 0.30 or above. Significant positive correlations between the latent factors were found for all factor pairs (correlation coefficient < 0.8).ConclusionsThe Chinese version of PETS vs. 2.0 is a reliable and valid tool for assessing the perceived treatment burden in patients with multimorbidity in primary care. All domains and items in the original questionnaires were retained.

Pain Predictors in Patients in the Postanesthesia Care Unit

To analyze the effects of pain-predicting factors on patients in the postanesthesia care unit (PACU). This is an observational and prospective study. This study was conducted at a University Hospital in the state of Minas Gerais (Brazil). To collect data on demographic, clinical, and surgical factors, a collection instrument was devised. The verbal numerical scale was employed to measure pain levels before and after surgery in the PACU. A path analysis was used to assess a predictive model. A total of 226 patients were included in this study. The incidence of pain in the PACU was 31.9%. A model with demographic, clinical, and surgical variables was tested. The final model, after including modification indices, obtained results that indicated an acceptable data fit (comparative fit index=0.996; root mean square error of approximation=0.08). Age (being young), sex (being a woman), oncological diagnosis as an indication for the surgical procedure, type of surgery (surgery of the digestive system), duration of surgery (longer surgeries), and high intraoperative doses of opioids were predictive variables for pain in the PACU. This study's findings provide support for pain management in the PACU. Furthermore, the results of this research can be used to anticipate the occurrence of acute postoperative pain and personalized perioperative analgesia needs.

Psychological distress, health-promoting lifestyle and sociodemographic factors in Honduran university students: a structural equation model.

This study sought to analyze an explanatory model on the relationship among sociodemographic factors, health-promoting lifestyle behaviors and psychological distress (depression, anxiety and stress) in college students. This is an observational, analytical and cross-sectional study conducted on a national sample of 4203 students who entered a macro university in Honduras in 2021, 2022 and 2023. We used a sociodemographic survey, the Health-Promoting Lifestyle Profile (HPLP-II) and the Depression, Anxiety and Stress Scales (DASS-21). Univariate analysis and a multivariate structural equation model were conducted. The average HPLP-II score was 117.45 (± 23.41), and the average DASS-21 score was 20.06 (± 14.16). The multivariate model showed a good data fit (comparative fit index = 0.951; Tucker-Lewis index = 0.957; root mean square error of approximation = 0.067 [90% CI = 0.067-0.068]). Results indicate that being a woman (β = 0.11; p < 0.001) and being enrolled in biological and health sciences (β = 0.09; p < 0.001) significantly predict HPLP-II scores. Furthermore, being a woman (β = 0.17; p < 0.001), age (β = 0.10; p < 0.001) and having pre-existing medical conditions (β = 0.16; p < 0.001) significantly explain part of the variance of DASS-21. A significant reverse relationship between health-promoting behavior and psychological distress was shown (r = -0.36; p < 0.001). This study identifies protective and risky sociodemographic factors linked to health-promoting lifestyle behaviors and psychological distress. Our findings have implications for developing comprehensive intervention policies and strategies to promote health in higher education settings.

Psychometric Properties of the Chinese Version of the Gratitude at Work Scale in Employed Nurses: A Cross-Sectional Study.

The Gratitude at Work Scale, originally developed by American scholars, has been widely administered to mental health professionals and human service workers to explore gratitude in the workplace. No Chinese-language instrument is currently available for assessing workplace gratitude. The aims of this study were to (a) translate the original English version of the Gratitude at Work Scale into a traditional Chinese version (TC-GAWS), confirm its factor structure, and analyze its psychometric properties among newly employed nurses and (b) develop and evaluate the psychometric properties of the TC-GAWS short form. A psychometric study using a cross-sectional web-based design was conducted in Taiwan. Three hundred twenty-two employed nurses completed a battery of self-administered online questionnaires that included a demographic datasheet, the Gratitude Questionnaire-Six-Item Form, the Connor-Davidson Resilience Scale-10, and the Thoughts of Quitting Scale. IBM SPSS 24.0 and AMOS 28.0 were used for data analysis, and Cronbach's alpha and Pearson's correlation were used to assess reliability and concurrent validity. Exploratory factor analysis and confirmatory factor analysis (CFA) were conducted. The internal consistency and stability of the TC-GAWS total scale were .88 and .91, respectively. The exploratory factor analysis showed a satisfactory Kaiser-Meyer-Olkin value of .88 and a Bartlett's test value of 654.01 ( p < .001), suggesting that 64.55% of the total variance was explained by the two-factor TC-GAWS. After item reduction, the CFA of the six remaining items of the TC-GAWS short form revealed adequate fit statistics for a two-factor structure and a second-order factor. Strong correlations were found between the 10-item and six-item TC-GAWS ( r > .94) in the two samples, suggesting good concurrent validity. The overall scores for the 10-item and six-item TC-GAWS had similar convergent validity, with moderate-to-strong correlations for the Gratitude Questionnaire-Six-Item Form ( r = .45 and .540), Connor-Davidson Resilience Scale-10 ( r = .49 and .51), and Thoughts of Quitting Scale ( r = -.57 and -.53). The CFA yielded a two-factor, six-item model that exhibited good fit with the latent constructs of χ 2 / df = 11.06/8 = 1.38, p = .198, comparative fit index = .996, goodness-of-fit index = .979, root mean square error of approximation = .045, root mean square residual = .030, and standardized root mean squared residual = .023. Both the 10- and six-item TC-GAWS instruments demonstrated good reliability and validity in nurse participants. The TC-GAWS may be used to measure gratitude in nurses in the workplace. This instrument has the potential to facilitate a better understanding of gratitude in nurses, which may be applied to the improvement of nursing management, research, and education.

Summary Measure of Health-Related Quality of Life and Its Related Factors Based on the Chinese Version of the Core Healthy Days Measures: Cross-Sectional Study.

The core Healthy Days measures were used to track the population-level health status in the China Chronic Disease and Risk Factor Surveillance; however, they were not easily combined to create a summary of the overall health-related quality of life (HRQOL), limiting this indicator's use. This study aims to develop a summary score based on the Chinese version of the core Healthy Days measures (HRQOL-5) and apply it to estimate HRQOL and its determinants in a Chinese population. From November 2018 to May 2019, a multistage stratified cluster survey was conducted to examine population health status and behavioral risk factors among the resident population older than 15 years in Weifang City, Shandong Province, China. Both exploratory factor analyses and confirmatory factor analyses were performed to reveal the underlying latent construct of HRQOL-5 and then to quantify the overall HRQOL by calculating its summary score. Tobit regression models were finally carried out to identify the influencing factors of the summary score. A total of 26,269 participants (male: n=13,571, 51.7%; mean age 55.9, SD 14.9 years) were included in this study. A total of 71% (n=18,663) of respondents reported that they had excellent or very good general health. One summary factor was extracted to capture overall HRQOL using exploratory factor analysis. The confirmatory factor analysis further confirmed this one-factor model (Tucker-Lewis index, comparative fit index, and goodness-of-fit index >0.90; root mean square error of approximation 0.02). Multivariate Tobit regression analysis showed that age (β=-0.06), educational attainments (primary school: β=0.72; junior middle school: β=1.46; senior middle school or more: β=2.58), average income (≥¥30,000 [US $4200]: β=0.69), physical activity (β=0.75), alcohol use (β=0.46), self-reported disease (β=-6.36), and self-reported injury (β=-5.00) were the major influencing factors on the summary score of the HRQOL-5. This study constructs a summary score from the HRQOL-5, providing a comprehensive representation of population-level HRQOL. Differences in summary scores of different subpopulations may help set priorities for health planning in China to improve population HRQOL.

Synergizing teacher collaboration to foster active learning strategies, student engagement and achievement in physics: a unified analysis across nine countries

This investigation explores the nexus between professional teacher collaboration, active learning methodologies, teaching promoting student engagement in physics classes and physics achievement. Leveraging Trends in International Mathematics and Science Study Advanced 2015 data from 1729 physics instructors across nine countries, it probes the extent to which collaborative practices among teachers influence their teaching to enhance active learning and engagement. Analytical techniques include Spearman correlations, confirmatory factor analysis, and structural equation modeling. Results reveal a robust model, confirmed by a Comparative Fit Index of 0.989 and Tucker–Lewis Index of 0.988, suggesting a good fit with the empirical data, alongside a Root Mean Square Error of Approximation of 0.053. The analysis demonstrates that teacher collaboration (‘Collab’) significantly predicts active learning (‘Active’) with a notable effect (β = 0.344, p < 0.001), which in turn significantly enhances student engagement (‘Engage’) (β = 0.438, p < 0.001). Additionally, ‘Engage’ is also directly influenced by ‘Collab’ (β = 0.174, p < 0.001). Although the relationship between ‘Collab’ and physics achievement (‘Physics’) is weaker, it remains significant (β = 0.063, p = 0.019). These findings support the enhancement of teacher collaboration as a catalyst for active learning and student engagement, which could indirectly foster improvements in physics achievement globally.

Application of an integrated behaviour-change model on grandparental adherence towards childhood domestic injury prevention in Hong Kong: a longitudinal study

Background/purposeEvery year, unintentional injury claims thousands of children’s lives and causes disabilities in many more. For very young children, these injuries often occur at home. The risks of domestic injury...

Translation, cross-cultural adaptation, and psychometric validation of the Malay version of the Assessment of Quality of Life—6 Dimensions (Malay-AQoL-6D) instrument among Malaysians living with chronic heart failure

BackgroundThis study aimed to translate and culturally adapt the Assessment of Quality of Life (AQoL)-6D into Malay (Malay-AQoL-6D), and assesses the instrument’s acceptability, reliability, and validity among Malaysians living with chronic heart failure (HF).MethodsThe translation and cross-cultural adaptation process adhered to international guidelines. The Malay-AQoL-6D underwent content and face validity assessments via expert review, and pretesting among healthy individuals and patients with chronic conditions. Subsequent psychometric validation utilised clinico-sociodemographic data and paired AQoL-6D and EQ-5D-5L data from a health-related quality-of-life (HRQoL) survey involving Malay-speaking patients with HF, which encompassed assessments of Malay-AQoL-6D acceptability, internal consistency and test-retest reliability, as well as its construct, concurrent, convergent and divergent, and known-group validity.ResultsThe Malay-AQoL-6D was deemed acceptable among clinicians and local patients, achieving a 90.8% completion rate among 314 patients surveyed. The instrument demonstrated strong content validity (item-level content validity index [CVI]: 0.83–1.00, average CVI: 0.98), internal consistency (Cronbach’s alpha: 0.72–0.89; MacDonald’s omega: 0.82–0.90, excluding the Senses dimension), and test-retest reliability (average intraclass correlation coefficients: 0.79–0.95). Confirmatory factor analysis confirmed the instrument’s two-level, six-factor structure (Satorra-Bentler [SB]-scaled χ2(df: 164): 283.67, p-value < 0.001; root mean square error of approximation [RMSEA]: 0.051; comparative fix index [CFI]: 0.945, Tucker-Lewis index [TLI]: 0.937; standardised root mean-squared error [SRMR]: 0.058). The Malay-AQoL-6D’s concurrent validity was evident through its good agreement with EQ-5D-5L. Multiple hypothesis tests further affirmed its construct and known-group validity. The Malay-AQoL-6D’s psychometric properties remained consistent across different missing data techniques.ConclusionThe findings suggest that Malay-AQoL-6D could be a culturally acceptable, reliable, and valid HRQoL measure for quantifying HRQoL among the local HF population. Future studies are necessary to further validate the instrument against other measures and confirm the instrument’s test-retest reliability and responsiveness, which are possible with the availability of the Malay-AQoL-6D.

The Parkinson's Disease Composite of Executive Functioning: A Measure for Detecting Cognitive Decline in Clinical Trials.

Executive functioning is one of the first domains to be impaired in Parkinson disease (PD), and the majority of patients with PD eventually develop dementia. Thus, developing a cognitive endpoint measure specifically assessing executive functioning is critical for PD clinical trials. The objective of this study was to develop a cognitive composite measure that is sensitive to decline in executive functioning for use in PD clinical trials. We used cross-sectional and longitudinal follow-up data from PD participants enrolled in the PD Cognitive Genetics Consortium, a multicenter setting focused on PD. All PD participants with Trail Making Test, Digit Symbol, Letter-Number Sequencing, Semantic Fluency, and Phonemic Fluency neuropsychological data collected from March 2010 to February 2020 were included. Baseline executive functioning data were used to create the Parkinson's Disease Composite of Executive Functioning (PaCEF) through confirmatory factor analysis. We examined the changes in the PaCEF over time, how well baseline PaCEF predicts time to cognitive progression, and the required sample size estimates for PD clinical trials. PaCEF results were compared with the Montreal Cognitive Assessment (MoCA), individual tests forming the PaCEF, and tests of visuospatial, language, and memory functioning. A total of 841 participants (251 no cognitive impairment [NCI], 480 mild cognitive impairment [MCI], and 110 dementia) with baseline data were included, of which the mean (SD) age was 67.1 (8.9) years and 270 were women (32%). Five hundred forty five PD participants had longitudinal neuropsychological data spanning 9 years (mean [SD] 4.5 [2.2] years) and were included in analyses examining cognitive decline. A 1-factor model of executive functioning with excellent fit (comparative fit index = 0.993, Tucker-Lewis index = 0.989, and root mean square error of approximation = 0.044) was used to calculate the PaCEF. The average annual change in PaCEF ranged from 0.246 points per year for PD-NCI participants who remained cognitively unimpaired to -0.821 points per year for PD-MCI participants who progressed to dementia. For PD-MCI, baseline PaCEF, but not baseline MoCA, significantly predicted time to dementia. Sample size estimates were 69%-73% smaller for PD-NCI trials and 16%-19% smaller for PD-MCI trials when using the PaCEF rather than MoCA as the endpoint. The PaCEF is a sensitive measure of executive functioning decline in PD and will be especially beneficial for PD clinical trials.

Guidelines for future agricultural technology development to increase productivity in the Agricultural sector

Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.

Validation of the Instructional Materials Motivation Survey among Medicine Resident Physicians

Purpose The Instructional Materials Motivation Survey (IMMS) was developed to measure motivational characteristics of a learning activity, building on Keller's Attention, Relevance, Confidence, Satisfaction (ARCS) motivation model. We aimed to validate IMMS scores using validity evidence of internal structure and relations with other variables. Methods Participants were internal medicine and family medicine residents who completed the IMMS following an online module on outpatient medicine, from 2005 to 2009. We used confirmatory factor analysis (CFA) to examine model fit using half the data (split-sample approach). Finding suboptimal fit, we conducted exploratory factor analysis (EFA) and developed a revised instrument. We evaluated this instrument with CFA using the remaining data. Associations were evaluated between IMMS scores and knowledge and other measures of motivation (Motivated Strategies for Learning Questionnaire, MSLQ). All analyses accounted for repeated measures on subjects. Results There were 242 participants. Although internal consistency reliabilities were good (Cronbach alpha ≥0.70), CFA of the original 36-item, 4-domain instrument revealed poor model fit for data sample 1. EFA found that reverse-scored items clustered strongly together. Further EFA using data sample 1, followed by CFA using data sample 2, found good fit for a 13-item, 4-domain model that omitted reverse-scored items (standardized root mean square residual 0.045, root mean square error of approximation 0.066, comparative fit index 0.96). Linear regression confirmed positive, statistically significant associations for most hypothesized relationships, including IMMS total with knowledge (r=0.19) and MSLQ total (r=0.53; both p&lt;.001). Examination of reverse-scored items suggested participant inattention but not acquiescence. Conclusions IMMS scores show good reliability and relations with other variables. However, the hypothesized and empirical factor structures do not align, and reverse-scored items show particularly poor fit. A 13-item, 4-domain scale omitting reverse-scored items showed good model fit.

A longitudinal examination of the measurement properties and invariance of the Sleep Condition Indicator in Chinese healthcare students

BackgroundThe Sleep Condition Indicator (SCI), an insomnia measurement tool based on the updated Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria with sound psychometric properties when applied in various populations, was evaluated here among healthcare students longitudinally, to demonstrate its measurement properties and invariance in this particularly high-risk population.MethodsHealthcare students of a Chinese university were recruited into this two-wave longitudinal study, completing the simplified Chinese version of the SCI (SCI-SC), Chinese Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration (RU_SATED-C) scale, Chinese Patient Health Questionnaire-4 (PHQ-4-C), and sociodemographic variables questionnaire (Q-SV) between September and November 2022. Structural validity, measurement invariance (MI), convergent and discriminant validity, internal consistency, and test–retest reliability of the SCI-SC were examined. Subgroups of gender, age, home location, part-time job, physical exercise, and stress-coping strategy were surveyed twice to test cross-sectional and longitudinal MI.ResultsWe identified 343 valid responses (62.9% female, mean age = 19.650 ± 1.414 years) with a time interval of seven days. The two-factor structure was considered satisfactory (comparative fit index = 0.953–0.989, Tucker–Lewis index = 0.931–0.984, root means square error of approximation = 0.040–0.092, standardized root mean square residual = 0.039–0.054), which mostly endorsed strict invariance except for part-time job subgroups, hence establishing longitudinal invariance. The SCI-SC presented acceptable convergent validity with the RU_SATED-C scale (r ≥ 0.500), discriminant validity with the PHQ-4-C (0.300 ≤ r < 0.500), internal consistency (Cronbach’s alpha = 0.811–0.835, McDonald’s omega = 0.805–0.832), and test–retest reliability (intraclass correlation coefficient = 0.829).ConclusionThe SCI-SC is an appropriate screening instrument available for assessing insomnia symptoms among healthcare students, and the promising measurement properties provide additional evidence about validity and reliability for detecting insomnia in healthcare students.

Cross-cultural adaptation and psychometric evaluation of the Turkish version of the Smombie Scale for Adolescents.

Smombie has become an important problem especially in terms of adolescent health. The aim of this study was to translate the Smombie Scale for Adolescents (SSA) into Turkish and to examine its psychometric properties. This study has a methodological design. The study was conducted between March and April 2024. The sample of the study consisted of 430 adolescents. The data were collected by using Personal Information Form and SSA. Content Validity Index, Confirmatory Factor Analysis (CFA), test-retest reliability, Cronbach's α coefficient, item-total score correlation, 27% upper-lower group item analysis and Hotelling T2 test were used in data analysis. The four-factor structure of the scale showed a good fit in CFA (chi-square minimum discrepancy [CMIN] = 187.463, degrees of freedo (DF) = 83, CMIN/DF = 2.259, root mean square error of approximation = 0.054, root mean square residual = 0.033, goodness of fit index = 0.947, adjusted goodness of fit index = 0.923, normed fit index = 0.930, tucker-lewis index = 0.949 and comparative fit index = 0.959). Cronbach's α coefficient of the scale was found to be 0.86. The item-total score correlation of the scale was found between 0.212 and 0.721. The test-retest intraclass correlation coefficient of the scale was found to be 0.876. This study shows that the scale is a reliable tool for assessing adolescents' smombie tendencies. It is thought that the scale will contribute to the protection and development of adolescent health.

STRATEGIC PLANNING GUIDELINES FOR SUCCESS IN INDUSTRIAL ENTERPRISES

Objective: The objective of this research is to examine the organizational structure and operational characteristics of industrial businesses, investigate components of strategic planning guidelines, and develop a structural equation model, with the aim of achieving sustainable success for industrial enterprises. Theoretical Framework: Content analysis method is a theoretical framework used to examine the presence and concepts of qualitative data. The framework is used to summarize findings and recommendations, from in-depth interviews and focus group discussions, into frequency values. Survey research framework is a structured approach that guides design, implementation, and analysis of surveys to gather data from targeted populations. The framework is used in quantitative research component, to collect and analyze data using descriptive and inferential statistics Method: Qualitative research involved conducting in-depth interviews with 9 experts and facilitating focus group discussions with 11 qualified individuals. Quantitative research is conducted through surveys to 500 industrial business executives, utilizing descriptive statistics, correlation analysis, and multivariate statistics. Results and Discussion: Findings from developed structural equation model indicated good alignment with observational data, with a Chi-square value of 0.094, Chi-square ratio of 1.115, goodness-of-fit index of 0.954, and a root mean square error of approximation of 0.015. Research Implications: Strategic planning is significant in business operations. Well-formulated business strategies will impact managerial efficiency, creating opportunities and enhancing a competitive advantage for industrial enterprises. Originality/Value: Findings revealed four significant factors contributing to success in industrial enterprises, listed in descending order of importance: 1) adaptive skills, 2) digital technology, 3) collaboration, and 4) organizational support.

Associations Between Sociodemographic Characteristics, eHealth Literacy, and Health-Promoting Lifestyle Among University Students in Taipei: Cross-Sectional Validation Study of the Chinese Version of the eHealth Literacy Scale.

The popularization of the internet and rapid development of mobile devices have led to an increased inclination and opportunities to obtain health-related information online. The eHealth Literacy Scale (eHEALS), widely used for measuring eHealth literacy, assesses an individual's ability to search, understand, appraise, and use eHealth information. However, the Chinese version of the eHEALS multiple-factor model remains to be validated, and the correlation between eHEALS and the health-promoting lifestyle profile (HPLP) among university students is rarely explored in Taiwan. This study aimed to examine the fit, validity, and reliability of the Chinese eHEALS multiple-factor model and to clarify the predictive effects of eHEALS on the HPLP among university students. University students in Taipei, the capital of Taiwan, were recruited, and 406 valid questionnaires including sociodemographic characteristics, eHEALS, and HPLP responses were collected. Confirmatory factor analysis was performed to validate the Chinese eHEALS. Independent sample t test, 1-way ANOVA, and multiple linear regression analyses were conducted to examine the relationship between sociodemographic variables and the HPLP. Pearson product-moment correlation and binary logistic regression analyses were performed to ascertain the predictive effects of eHEALS on the HPLP. The Chinese eHEALS exhibited an optimal fit when delineated into the search, usage, and evaluation 3-factor model (comparative fit index=0.991, Tucker-Lewis index=0.984, root mean square error of approximation=0.062), and its validity and reliability were confirmed. The mean eHEALS score of university students was 3.17/4.00 (SD 0.48) points, and the score for the evaluation subscale was the lowest (mean 3.08, SD 0.56 points). Furthermore, there were significant sex, institution orientation, daily reading time, daily screen time, primary information channel, and perceived health status differences in the HPLP: male participants (t404=2.346, P=.02), participants attending general university (t404=2.564, P=.01), those reading ≥1 hour daily (F2,403=17.618, P<.001), those spending <3 hours on mobile devices or computers daily (F2,403=7.148, P<.001), those acquiring information from others (t404=3.892, P<.001), and those with a good perceived health status (F2,403=24.366, P<.001) had a significantly higher score. After adjusting for sociodemographic variables, the eHEALS score remained an independent predictor of the HPLP. Compared to students with relatively high eHEALS scores, those with relatively low eHEALS scores had a 3.37 times risk of a negative HPLP (adjusted odds ratio [OR]=3.37, 95% CI 1.49-7.61), which could explain 14.7%-24.4% of the variance (Cox-Snell R2=0.147, Nagelkerke R2=0.244, P=.004). There is room for improvement in eHealth literacy among university students in Taipei. eHEALS may be used to screen students who require HPLP improvement, thereby providing appropriate eHealth literacy training programs, particularly those targeting evaluation literacy. Additionally, the 3-factor model of the Chinese eHEALS used in this study results in more definite scale content, thus increasing the practicality and applicability of this scale in health-promoting studies.

Fit Indices in Structural Equation Modeling and Confirmatory Factor Analysis: Reporting Guidelines

This research explores the essential aspects of reporting fit indices in Structural Equation Modeling (SEM), focusing on their significance, methodologies for evaluation, and implications for model validity. The aim is to provide a comprehensive understanding of how fit indices contribute to the rigor and reliability of SEM studies. Methodologically, the study reviews prominent fit indices such as Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Residual (SRMR), and Chi-Square Test of Model Fit (χ²). Each index is defined, and specific threshold values are discussed to guide researchers in interpreting their findings effectively. Originality in this study lies in synthesizing current literature to emphasize the importance of transparent reporting practices in SEM, enhancing methodological clarity and promoting replicable research outcomes. Contributions include a structured approach to understanding fit indices’ roles in model assessment and validation, aiding researchers in advancing theoretical frameworks with robust empirical support.

Empirical Investigation of Multilayered Framework for Predicting Academic Performance in Open and Distance Learning

Integrating artificial intelligence (AI) in open and distance learning (ODL) necessitates comprehensive frameworks to evaluate its educational implications. Existing models lack a robust multilayered analysis of AI’s impact on educational outcomes in ODL. This study introduces a Multilayered Process Framework designed to predict academic performance in ODL and enhance inclusivity, aligning with UNESCO’s 2030 educational goals. The current research employed structural equation modelling (SEM) to analyse the impact of AI adoption, focusing on the initial layers of the process framework. Preliminary validation of the SEM framework showed a good model fit, with a Chi-square/df ratio of 2.34, Root Mean Square Error of Approximation (RMSEA) of 0.045, and Comparative Fit Index (CFI) of 0.97, indicating the model’s effectiveness in capturing the complexities of AI impacts on student outcomes. This framework provides a structured, multilayered approach to understanding AI’s role in education, facilitating the development of equitable and accessible AI-driven educational technologies. It lays the foundational work for expanding research into predictive analytics with a support vector machine (SVM), aiming to universalise quality education and ensure global educational equity. This study highlights the practical implications for integrating AI in educational settings and suggests future research directions to enhance the adaptability and effectiveness of AI-driven educational interventions.

Psychometric Properties of the Persian Version of the Intensive Care Experience Questionnaire (ICE-Q).

Background and Purpose: It is important to assess the experience of patients who have been admitted to an intensive care unit to provide the best treatment and nursing care possible. Therefore, a valid and reliable tool is necessary for measurement. This study aimed to determine the psychometric properties of the Persian version of the Intensive Care Experience Questionnaire (ICEQ) for open-heart surgery patients. Methods: The study was conducted in four steps: translation, face and content validity, confirmatory factor analysis, and reliability assessment. The adapted questionnaire was administered to 200 Iranian cardiac surgery patients who had received treatment in an intensive care unit within the past month. Results: In the final Persian version of ICEQ, there are 4 factors and 21 items. Following the translation and cultural adaptation process, the content validity was evaluated. Three items had content validity ratio < 0.6, so they were deleted. Scale-level content validity index/Average was 0.81 and more than 0.7 for each item on the scale. This scale was validated through confirmatory factor analysis using fit indicators (comparative fit index, normalized fit index, root mean square error of approximation, and chi-square). There was Cronbach's alpha of 0.71-0.85, and intraclass correlation coefficients were 0.82-0.93 for subscales. Conclusions: The Persian version of ICEQ showed appropriate psychometric properties. This scale may be useful to inform the development of effective interventions to improve subsequent outcomes for Iranian open-heart surgery patients.

Validation and Refinement of the Sense of Coherence Scale for a French Population: Observational Study.

Salutogenesis focuses on understanding the factors that contribute to positive health outcomes. At the core of the model lies the sense of coherence (SOC), which plays a crucial role in promoting well-being and resilience. Using the validscale Stata command, we aimed to assess the psychometric properties of the French version of the 3-dimension 13-item SOC questionnaire (SOC-13), encompassing the comprehensibility, manageability, and meaningfulness dimensions. We also aimed to determine if a refined scale, assessed through this method, exhibits superior psychometric properties compared to the SOC-13. A sample of 880 consecutive primary care patients recruited from 35 French practices were asked to complete the SOC-13. We tested for internal consistency and scalability using the Cronbach α and Loevinger H coefficients, respectively, and we tested for construct validity using confirmatory factor analysis and goodness-of-fit indices (root mean square error of approximation [RMSEA] and comparative fit index [CFI]). Of the 880 eligible patients, 804 (91.4%) agreed to participate (n=527, 65.6% women; median age 51 years). Cronbach α and Loevinger H coefficients for the SOC-13 were all <0.70 and <0.30, respectively, indicating poor internal consistency and poor scalability (0.64 and 0.29 for comprehensibility, 0.56 and 0.26 for manageability, and 0.46 and 0.17 for meaningfulness, respectively). The RMSEA and CFI were >0.06 (0.09) and <0.90 (0.83), respectively, indicating a poor fit. By contrast, the psychometric properties of a unidimensional 8-item version of the SOC questionnaire (SOC-8) were excellent (Cronbach α=0.82, Loevinger H=0.38, RMSEA=0.05, and CFI=0.97). The psychometric properties of the 3-dimension SOC-13 were poor, unlike the unidimensional SOC-8. A questionnaire built only with these 8 items could be a good candidate to measure the SOC. However, further validation studies are needed before recommending its use in research.