Mean Squared Error Of Approximation Research Articles

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<.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.

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.

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.

Assessment of psychometric performance for the Chinese version of the Brief Inventory of Perceived Stress integrating exploratory graph analysis and confirmatory factor analysis.

This study was to evaluate measurement properties of the Chinese version of the Brief Inventory of Perceived Stress (BIPS-C) and confirm possible solutions for measuring the constructs underlying perceived stress. A total of 1356 community residents enrolled and were randomly split into two halves. The first half was used to explore the underlying constructs of the BIPS-C by exploratory graph analysis (EGA) and the second half was used to compare and confirm the constructs by confirmatory factor analysis (CFA). The EGA identified a one-factor model of the BIPS-C with an accuracy of 99.3%. One-factor, three-factor, second-order, and bifactor models were compared by CFAs. The bifactor model with one general and three specific factors was found to be the most adequate [comparative fit index (CFI) = 0.990; Tucker-Lewis index (TLI) = 0.979; root mean square error of approximation (RMSEA) = 0.058] and was superior to the other models. The related bifactor indices showed a stronger existence of the general factor. The bifactor model of the BIPS-C also showed adequate internal consistency with McDonald's omega and omega subscales ranging from moderate to strong (0.677-0.869). The BIPS-C demonstrates sufficient measurement properties for assessing general perceived stress.

Development and validation of the metaverse perception scale for nursing students

BackgroundThe use of Metaverse applications in nursing education is increasing every day and the evaluation of nursing students' perceptions of this new digital technology may guide interventions related to the use of the Metaverse. However, currently, no standardized instrument specifically designed to measure nursing students' perceptions of the Metaverse exists in Turkey. AimTo develop and validate the Metaverse Perception Scale for Turkish nursing students. MethodThis methodological study was carried out between March 1, 2023 and June 30, 2023 and its sample consisted of 770 nursing students who were enrolled in undergraduate nursing departments of universities in Turkey. The item pool was created based on a literature review and data were analyzed using descriptive statistics, item analysis, exploratory and confirmatory factor analysis, convergent and divergent validity, correlation analysis, internal consistency reliability and test-retest analysis. ResultsThe content validity index for the items ranged between 0.85 – 1.00. According to exploratory factor analysis, the eigenvalue of four factors was greater than one. These four factors explained 77.28 % of the total variance. In the scale model developed for this study, model fit was found to be acceptable for goodness of fit index:.921 and root mean square error of approximation:.064. χ2/sd: 1.659, normalized fit index:.961 and chi-square/degree of freedom revealed that model fit was at a good level and within the recommended value ranges. It was determined that the scale showed convergent and divergent validity and Cronbach's Alpha value ranged between 0.95 and 0.93 in the subscales. The Metaverse Perception Scale in Nursing Students was found to have a high level of test-retest reliability. ConclusionThis study showed that the scale, which consists of 24 items and four subscales, is a valid and reliable measurement tool that can be used to assess nursing students' perceptions of the Metaverse in the Turkish context. This scale can contribute to the evaluation of Turkish nursing students' perceptions of the Metaverse, as well as the effective management of processes related to Metaverse practices.

Development and Validation of the Criminal Aptitude Inventory (Urdu): A Comprehensive Assessment Across Convicted Prisoners and the General Population

Background: Criminal aptitude testing benefits police and other fields of law enforcement. Earlier literature lacked an Urdu-language scale for criminal aptitude. Objectives: The present study developed and validated a new scale to measure criminal aptitude in Urdu speakers. Methods: The development and validation of the Criminal Aptitude Inventory (CAI) unfolded across three distinct phases, involving a total of 1675 participants (51.34% women), including convicted prisoners (37.33%). In the initial phase, the CAI underwent development and preliminary validation through exploratory factor analysis (EFA). Subsequently, the second phase utilized Confirmatory Factor Analysis to further confirm the scale's validity. The third phase focused on analyzing the CAI's convergent and discriminant validity by investigating its relationship with antisocial personality disorder, morality, religiosity, and spirituality. Results: The results demonstrated high reliability and validity of the CAI, affirming its suitability for future applications. The final version of the scale comprises a single factor and consists of 36 items, each utilizing a 5-point Likert-type response format. Indicators such as Kaiser-Meyer-Olkin's values (0.984), Cronbach’s alpha (0.984), average item-total correlation (P &lt; 0.001), comparative fit index (0.936), Tucker-Lewis Index (0.932), Goodness of Fit Index (GFI=.939), root mean square error of approximation (RMSEA = 0.043), convergent validity with antisocial personality disorder (r = 0.458; P &lt; 0.01), and discriminant validity with morality (r = -0.396; P &lt; 0.01), religiosity (r = -.318; P &lt; 0.01), and spirituality (r = -.453; P &lt; 0.01) established the reliability and validity of the CAI. Conclusions: The dual-source data collection strategy employed in this study, drawing from both convicted prisoners and the general population, enhances and operationalizes the scale. This approach ensures its applicability across diverse Urdu-speaking communities in Pakistan and India.

Cross-validation of the Canadian Assessment of Physical Literacy second edition (CAPL-2) for Spanish children

Background/objectiveThis study aimed to explore physical literacy (PL) using the Canadian Assessment of Physical Literacy, second edition (CAPL-2), adapt it to the Spanish context and provide evidence of its validity...

The intensive care unit psychosocial care scale: validity and reliability study in cardiac surgery patients

This study aimed to test the validity and reliability of the ICU Psychosocial Care Scale in Turkish, which was developed to measure the psychosocial care of cardiac critical patients. This study was a methodological design. The study sample consisted of 180 critically ill cardiac patients meeting the inclusion criteria. The study used the ICU-Psychosocial Care (ICU-PC) Scale and The Intensive Care Experiences Scale for data collection. Data were analyzed using SPSS 22.0 and AMOS V 24.0 statistical package programs. Content validity, construct validity, reliability and concurrent validity tests were performed. The sample (n = 180) was predominantly male (66.1%) with a mean age of 65.96 ± 15.46 years. Confirmatory factor analysis was applied to confirm the 3-dimensional and 14-item structure of the scale. The fit indices of the scale were found to be χ2 = 89.24, df = 52, χ2/df = 1.716, goodness of fit index = 0.94, comparative fit index = 0.97, incremental fit index = 0.97, Tucker-Lewis index = 0.95, root mean square error of approximation = 0.05, standardized root mean square residual = 0.05. Cronbach’s alpha coefficient of ICU-PC scale was 0.87. The ICU-PC scale is a valid, reliable and distinctive scale in assessing the psychosocial care of critically ill cardiac patients.

Translation and Validation of Digital Competence Indicators in Greek for Health Professionals: A Cross-Sectional Study.

it is widely accepted that living in the digital transformation era, the need to develop and update new professional skills and tools in health sectors is crucially important. Therefore, this study aimed to explore the reliability and validity of the Digital Competence Indicators tool in assessing the digital skills of Greek health professionals. in this cross-sectional study, 494 health professionals, including doctors (175) and registered nurses (319) working in four Greek hospitals were recruited and willingly participated using a convenience-sampling method. The original framework of Digital Competence Indicators was translated from English to Greek based on guidelines for cross-cultural adaptation of questionnaires. The validity of the tool was explored using confirmatory factor analysis (CFA) to verify the fit of the model using inductive techniques. The instrument reliability was confirmed using Cronbach's alpha (α) and McDonald's Omega coefficients. the reliability was estimated at 0.826 (Cronbach's-α) and 0.850 (McDonald's Omega-ω). The indicators of CFA were all calculated within an ideal range of acceptance. Specifically, the CFA comparative fit index produced the following adjustment indices: x2/df = 1.152 (p = 0.037), CFI = 0.997, Lewis index (TLI) = 0.966, and root mean square error of approximation (RMSEA) = 0.018. The present study demonstrated that the Digital Competence Indicator instrument has high reliability, internal consistency, and construct validity and, therefore, it is suitable for measuring digital skills of health professionals.

Validation of the Greek version of Mother's Autonomy in Decision Making (MADM) scale.

Ensuring expectant mothers have the capacity to make well-informed decisions regarding their prenatal care, encompassing medical interventions, and birthing preferences are crucial for fostering favorable health outcomes for both mother and newborn. The Mother's Autonomy in Decision Making (MADM) scale serves as a commonly utilized tool for evaluating the autonomy of pregnant women in the decision-making processes related to prenatal care and childbirth. The aim of this study is to validate the MADM scale in women who had at least one home childbirth experience in Greece. A retrospective online survey collected data from Greek women with home childbirth experience (January 2010 - December 2023). We utilized a self-administered questionnaire and the Greek version of the MADM scale. The study included 162 women, predominantly of Greek nationality (94.4%) and residing in Attica (54%). The MADM scale showed a median score of 38. The confirmatory factor analysis indicated acceptable fit and reliability (comparative fit index, CFI=0.92; Tucker-Lewis index, TLI=0.91; root mean square error of approximation, RMSEA=0.07; Cronbach's α=0.92). Age correlated weakly negatively with the MADM scale score (Spearman's rho= -0.166, p=0.035). Additionally, women attending antenatal preparation courses with a midwife before their first home birth had higher MADM scores (median 39 vs 35, p=0.037). The study underscores the importance of the MADM scale, demonstrating its reliability and validity for women living in Greece. Younger age and attending antenatal preparation courses with a midwife were associated with higher MADM scores, highlighting education's role in maternal autonomy.

Adventitious Error and Its Implications for Testing Relations Between Variables and for Composite Measurement Outcomes

Wu and Browne (Psychometrika 80(3):571–600, 2015. https://doi.org/10.1007/s11336-015-9451-3; henceforth W &B) introduced the notion of adventitious error to explicitly take into account approximate goodness of fit of covariance structure models (CSMs). Adventitious error supposes that observed covariance matrices are not directly sampled from a theoretical population covariance matrix but from an operational population covariance matrix. This operational matrix is randomly distorted from the theoretical matrix due to differences in study implementations. W &B showed how adventitious error is linked to the root mean square error of approximation (RMSEA) and how the standard errors (SEs) of parameter estimates are augmented. Our contribution is to consider adventitious error as a general phenomenon and to illustrate its consequences. Using simulations, we illustrate that its impact on SEs can be generalized to pairwise relations between variables beyond the CSM context. Using derivations, we conjecture that heterogeneity of effect sizes across studies and overestimation of statistical power can both be interpreted as stemming from adventitious error. We also show that adventitious error, if it occurs, has an impact on the uncertainty of composite measurement outcomes such as factor scores and summed scores. The results of a simulation study show that the impact on measurement uncertainty is rather small although larger for factor scores than for summed scores. Adventitious error is an assumption about the data generating mechanism; the notion offers a statistical framework for understanding a broad range of phenomena, including approximate fit, varying research findings, heterogeneity of effects, and overestimates of power.