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Principles and Practice of Structural Equation Modeling

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... A low SRMR (typically values close to 0) suggests that the model's predictions align well with the observed data, indicating a good overall model fit (Hu & Bentler, 1999;Maydeu-Olivares, 2017). Hu and Bentler (1999) suggest SRMR ≤ 0.08 as a benchmark for good overall model fit, although a less strict cut-off value of SRMR < .10 has been put forward (Kline, 2016;Lichti, 2019). While infit MNSQ is sensitive to unexpected behaviour of respondents to whom an item is targeted in terms of difficulty, outfit MNSQ is sensitive to outliers. ...
... The fit indices (Table 3) are acceptable since the values do not greatly exceed the cut-off value and other researchers suggest a less strict cut-off value of SRMR < .10 (Kline, 2016;Lichti, 2019). ...
... Like in the analysis before, the cut-off of SRMR < .08 (Hu & Bentler, 1999) is exceeded but for the two-dimensional model the less strict cut-off of SRMR < .10 (Kline, 2016) is not exceeded in contrast to the one-dimensional model (Table 7). This suggests that the two-dimensional model is preferable. ...
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In chemistry, representational competence is crucial for effective problem-solving and learning. However, the relationship between representational competence and chemical content knowledge, continues to be a matter of discussion. To investigate the connection between representational competence and chemical content knowledge, we developed a new assessment tool known as the Chemical Representation Inventory: Translation, Interpretation, Construction (CRI:TIC), utilizing three lower-level representational skills identified by Kozma and Russell (1997, 2005). This article presents the evaluation of the CRI:TIC and discusses its implications for research in chemistry education and for educators. The instrument was administered to 185 first-year students in a preparatory university chemistry course. Utilizing multidimensional Rasch analysis, we examined the dimensionality of the lower-level representational skills. Based on the results, we suggest that, from a psychometric perspective, lower-level skills should be regarded as a unified construct. Nonetheless, from an educational standpoint, maintaining a conceptual distinction between these skills remains relevant. Further analysis linking the CRI:TIC data to results from a chemical content knowledge assessment indicates that representational competence and content knowledge should be treated as distinct constructs. Although we cannot draw causal conclusions regarding the relationship between these two constructs, our findings underscore the importance of developing students’ representational skills.
... Katılımcılara ait tanımlayıcı istatistiki bilgiler tablo 6'da sunulmuştur. (Byrne, 2010;Kline, 2015). Son olarak GFI değeri 0,88 olarak tespit edilmiştir. ...
... Bu doğrultuda uyum indeks değerleri incelendiğinde, x2/df değerinin 2,74 olduğu tespit edilmiştir. Kline, (2015) bu değerin 3'ün altında olmasının modelin mükemmel uyumu ifade ettiğini belirtmektedir. RMSEA değeri incelendiğinde, 0,060 olarak tespit edilmiştir. ...
... CFI değeri 0,91 olarak tespit edilmiştir. Literatür kapsamında 0,90 ve üstü bir değerin iyi uyum düzeyi olduğu görülmüştür (Byrne, 2010;Kline, 2015). Son olarak GFI değeri 0,88 olarak tespit edilmiştir. ...
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Öz Bu çalışmanın amacı, sporun toplumda meydana getirdiği etkilerin belirlenmesinde geçerliliği ve güvenilirliği kanıtlanmış bir ölçme aracı geliştirmektir. Araştırmanın çalışma grubunu, Ankara ilinde bulunan 2021-2022 eğitim öğretim yılında farklı üniversite ve farklı fakültelerde öğrenim gören en az bir yıllık spor deneyimini halen sürdürmekte olan 833 öğrenci oluşturmaktadır. Araştırmada ölçeğin kapsam geçerliliğini belirlemek amacıyla spor bilimleri alanında uzman akademisyenlerden maddelere ilişkin dönütler alınarak uygun görülmeyen maddeler ölçekten çıkarılmıştır. Maddelerin anlaşılırlığını belirlemek üzere amaca uygun 45 üniversite öğrencisi pilot uygulamaya katkı sağlamıştır. Taslak ölçme aracının yapı geçerliliğini sağlamak için 355 kişi ile açımlayıcı faktör analizi (AFA), yapının doğrulanması için 478 katılımcı ile doğrulayıcı faktör analizi (DFA) yapılmıştır. Yapılan analizler sonucunda; 27 madde ve 4 alt boyuttan (Sosyal sermaye, İyi oluş, Kültürel sermaye ve Sağlık okuryazarlığı) oluşan “sporun sosyal etkisi ölçeği” geliştirilmiştir. Ölçme aracının güvenirliği, Cronbach Alfa ve madde toplam korelasyonu değerleri ile yorumlanmıştır. Analiz sonuçları, geçerlik ve güvenilirlik açısından uygulanabilir olduğunu ortaya koymaktadır.
... We evaluated model fit using the comparative fit index (CFI), incremental fit index (IFI), normed fit index (NFI), goodness of fit index (GFI), and standardized root mean square (SRMR) data. Kline (2016) asserts that values of 0.90 or above for CFI, IFI, NFI, and GFI typically indicate satisfactory model fit, with a value of 0.95 or higher considered preferable for good model fit. Kline (2016) posits that a Standardized Root Mean Square Residual (SRMR) threshold of 0.08 or below signifies a satisfactory model fit. ...
... Kline (2016) asserts that values of 0.90 or above for CFI, IFI, NFI, and GFI typically indicate satisfactory model fit, with a value of 0.95 or higher considered preferable for good model fit. Kline (2016) posits that a Standardized Root Mean Square Residual (SRMR) threshold of 0.08 or below signifies a satisfactory model fit. The AMOS version 24 software performed the mediation analysis for the study. ...
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Adolescence is a crucial time of identity formation, scholastic and social demands, future concerns, and relationship changes. Adolescents are especially susceptible to psychological issues like pessimism, which can hinder their progress and well‐being. Cognitive flexibility may help adolescents adjust to these challenges and improve subjective well‐being. Pessimism, cognitive flexibility, and subjective well‐being have been investigated cross‐sectionally, but their longitudinal association has not. This study examines cognitive flexibility's mediation function in the longitudinal association between pessimism and subjective well‐being in teenagers, taking into account their well‐being development and inadequacies. This study looked at how cognitive flexibility affects the link between pessimism and subjective well‐being. To address the limitations of cross‐sectional mediation analysis, the current study employed an autoregressive cross‐lagged panel model within a half‐longitudinal framework, which allows for a more accurate estimation of directional and temporal relationships among the variables. This model used two 3‐month‐apart data sets. Cognitive flexibility was found to mediate the relationship between pessimism and subjective well‐being (χ2 (3, N = 232) = 11.68, p < 0.001). These findings indicate that cognitive flexibility plays a significant mediating role in weakening the negative impact of pessimism on adolescents’ subjective well‐being, highlighting its importance as a protective cognitive factor during this critical developmental period.
... Model fit for our initial CFA measurement model was below the conventional thresholds for acceptability (Kline, 2016;Little, 2024) with a χ 2 (8) = 1175.844, p < .001, ...
... Future research can benefit from collecting primary data that is inclusive in terms of gender and ethnicity. Also, although the model fit is acceptable ISSN: 1945-7774 CC by-NC 4.0 2025 Financial Therapy Association 73 (Kline, 2016), it is not an ideal fit, due to the use of secondary data. Little (2024) explains that when novel scales are used or scales are created post-hoc from existing items not originally intended to be used as scales, the heuristics of acceptable fit can be relaxed. ...
... For the CFI, conventional cutoff values of 0.90 or greater indicate acceptable fit and 0.95 or greater indicate good fit [29]. RMSEA values between 0.05 and 0.08 represent an acceptable fit [27,29]. Table 2 shows bivariate correlations for study variables. ...
... This comparison the intercept variance and squared slope loadings shows slightly more between-person versus within-person variability across the RSA trajectory (i.e., 0.80/0. 27 Table 3 presents standardized parameter estimates for the associations between between-person differences (intercept) and within-individual variability (slope) in RSA and emotion dysregulation and reactive aggression in daily life, controlling for covariates. There was a significant effect of between-person differences (intercept) and within-individual change (slope) on reactive aggression in daily life. ...
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Individual differences in respiratory sinus arrhythmia (RSA) are linked to emotion and behavior dysregulation, two transdiagnostic indicators of psychopathology youth. However, most research has focused on RSA reactivity to stressors, with little work examining individual differences in RSA following stressors. The current study examined associations between dynamic changes in RSA following parent–child conflict and youth emotion dysregulation and reactive aggression in daily life. In a transdiagnostic sample of clinically referred youth (n = 162; Mage = 12.03 years, SD = 0.92; 47% female; 60% minoritized racial/ethnic status), RSA was assessed during a laboratory-based parent–child interaction task, which included a conflict discussion and four subsequent tasks. Emotion dysregulation and reactive aggression were assessed during a 4-day ecological momentary assessment protocol. Dynamic changes in RSA were modeled using a non-linear growth model (i.e., free curve slope intercept [FCSI] model), and associations with emotion dysregulation and reactive aggression were examined within a multivariate structural equation model. Results from the FCSI model demonstrated significant between-person differences (intercept) and within-individual change (slope) in RSA and predictive associations were specific to reactive aggression. Specifically, youth with higher mean levels of RSA (β = 0.20, p = .02) and those showing decreases in RSA (i.e., continued withdrawal) following parent–child conflict (β = -0.25, p = .03) were more likely to engage in reactive aggression in daily life. No associations wer found with emotion dysregulation. Findings underscore the importance of examining dynamic changes in RSA and suggest prolonged autonomic recovery following a conflict may be an indicator of risk for reactive aggression.
... Furthermore, we adopted a structural equation modeling (SEM) approach. SEM allows for complex modeling of correlated multivariate data, such as individual survey item scores, and hypothetical variables (Kline, 2016;Song & Lee, 2012). The study focuses on direct and indirect effects. ...
... so RH4 was confirmed. Further, because both RH2 and RH4 were confirmed, it was straightforward to conclude that OLR only partially mediates the relationship between DL and SDOL (Kline, 2016). The proposed Bayesian mediation model containing the four research hypotheses explained 64.4% of the variance in OLR and 76.9% of the ...
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Digital literacy encompasses the skills needed to effectively navigate and use the digital tools and resources that are essential in today's educational landscape. Students with higher levels of digital literacy often demonstrate self-directed learning skills, enabling them to manage their study schedules and submit assignments in a timely and effective manner. Integrating digital literacy with preparation for self-directed learning is critical to fostering successful online learning experiences. Research into the impact of students' digital literacy and readiness for online learning on their self-directed learning is crucial to understanding the competencies and skills required for online education. Such competencies in learners may have unique effects, especially in specific online learning processes such as emergency remote teaching. Therefore, this study aimed to explore the potential impact of students' digital literacy on their self-directed online learning, with a particular focus on their online learning readiness. In line with the purpose of the study, a cross-sectional survey design was employed, using a structural equation modeling approach. The results showed that digital literacy has a direct and positive effect on online learning readiness. In addition, online learning readiness has a direct and positive influence on self-directed online learning. The results also highlighted that digital literacy indirectly and positively influences individuals' levels of self-directed online learning through their online learning readiness.
... It is a more reliable method of analysis, and it can be applied to data that does not follow a normal distribution (Hair et al., 2017). According to Kline (2023), a minimum of 100-150 respondents is required to obtain reliable results from structural equation modeling (SEM), indicating that the current study's sample size is sufficient for robust analysis. ...
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This study intends to explore how risk assessments with training programs, personal protective equipment (PPE), and monitoring practices affect the occupational health and safety standards for construction workers in Bangladesh. The study uses quantitative methods with 291 participants to conduct hypothesis tests through SEM. Research results indicate that work health safety significantly benefits from risk determinations, training of employees, personal protective equipment (PPE), and rigid supervision systems. Yet, safety awareness acts as a middle link that binds these components. The research produces field-tested solutions available to be used by governmental agencies and other business partners in construction that enhance worker safety and alleviate on-the-job hazards. The study presents clear and actionable methods that help government officials and organizations within construction, combined with industry participants, defend workers and minimize workplace safety hazards.
... As stated by Hair and colleagues in 2010, for any analyse to be statistically meaningful, it is expected to have a minimum of 200 samples. Whereas Kline (2023) on the other hand, argues that models of similar complexity require samples between 200 to 500. With this number of 351 respondents, there are good chances of being able to explain important inter-relationships among the variables under investigation. ...
... In the study on healthcare management, this method is extensively applied to project how organizational behaviors affect performance [30] Complex routes between DDDM implementation, mediating factors (e.g., efficiency), and financial success were tested using structural equation modeling (SEM). SEM offers a strong test of the conceptual model and helps one understand both direct and indirect interactions [31]. ...
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Amid escalating costs and tightening margins, U.S. healthcare organizations face increasing pressure to enhance profitability while maintaining quality care. Data-Driven Decision-Making (DDDM) has emerged as a transformative approach for improving operational efficiency and financial sustainability. U.S. healthcare companies under growing pressure to improve profitability while keeping excellent treatment among rising expenses and limited margins. Emerging as a transforming strategy for increasing operational efficiency and financial sustainability is DDDM. Primary data from structured polls and interviews with healthcare executives (N = 100+) and secondary data including financial records, electronic health records (HER) system use, and performance measures were combined under a cross-sectional study design. Low, medium, and high DDDM adoption groups were established by organizations. While inferential analysis including regression modeling and correlation matrices evaluated the relationship between DDDM levels and financial performance, descriptive statistics compiled organizational profiles. High-DDDM companies showed notably better average return on investment (9.3%) than medium (8.1%) and low adopters (6.9%). From 8.1% in low adopters to 11.7% in high adopters, operating margins were likewise more robust. Regression study verified that, even after accounting for organizational size, location, and patient volume, DDDM level was a significant predictor of profitability. Strongly favorable correlations between all the financial indicators were identified using correlation analysis. Ultimately, the results showed that better and more consistent financial results are favorably correlated with advanced DDDM acceptance. Healthcare companies that give analytics integration priority get clear benefits in operational profitability and efficiency. These findings highlighted the strategic importance of data maturity and helped to justify more analytics capability funding. Particularly in resource- constrained environments, policymakers should consider encouraging DDDM acceptance to guarantee fair access to data-driven innovation in healthcare.
... for the four-factor AEG construct, as shown in Table 2. Also, all the other model fit indices were within the recommended threshold (CFI AEG , NFI AEG , IFI AEG , and TLI AEG . 0.90; Kline, 2023). Table 3 shows the item loadings, a, v, and AVE of the AEG scale. ...
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Students’ academic engagement in higher education, especially in Economics, is crucial for their success. However, the interaction effect of gender and academic level on the academic engagement of Economics students remains unexplored. This study used a descriptive cross-sectional survey design to examine the academic engagement of Economics students in Ghanaian higher education, with a particular focus on variations based on academic level and gender. Using a census method, the research involved 452 students from different academic levels. This study employs a census method to involve 452 students across various academic levels. Also, a “multidimensional academic engagement scale” was utilized as the data collection instrument. Descriptive (“mean and standard deviation”) and multivariate analysis of variance (“two-way MANOVA”) were used to analyze the research objectives. The study found that Economics students showed high levels of cognitive, emotional, and behavioral engagement. However, their agentic engagement was moderate. Also, the study revealed no significant variations in academic engagement based on gender and academic level. However, at the univariate level, significant differences were found in agentic engagement based on gender. In addition, there were significant differences in both behavioral and agentic engagement based on academic level. It is recommended that higher education educators, especially Economics educators, focus on creating a supportive environment to increase students’ agentic engagement.
... The data's normality was assessed through values of kurtosis (ranging from .00 to -.61) and skewness (ranging from -.25 to -.43)(Seijas-Macias et al., 2023). These values showed that data were normally distributed for each item(Kline, 2005; Xiao & Hua., 2023). ...
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Teachers' emotional literacy involves knowing emotions, acknowledgment of emotions, understanding emotions, expression of emotions, and suitable reflection on emotions. The value of emotional literacy has recently become popularized in educational institutions. Emotional literacy fosters empathy, resilience, social bonding, conflict resolution, and classroom management, empowering teachers to create supportive environments and enabling learners to thrive academically and emotionally. Now this term has become a global trend, more researchers are taking interest in this field of research especially when they came to know that emotional competencies are learnable, improvable, and measurable. For successful implementation of emotional literacy programs in educational institutions. The assessment of teachers' emotional literacy is crucial in Pakistan, where training focuses only on content expertise and pedagogical skills. The study aimed to develop a scale to assess emotional literacy among primary school teachers in Punjab's government institutions. Multistage random sampling technique was used. A sample of three hundred primary teachers was selected from the hundred primary schools from district Sargodha and Hafiz Abad. The construct validity of the scale was established through EFA, and five factors were revealed. The CFA was applied to confirm the results of the EFA. The value of the Cronbach Alpha reliability coefficient was.65 on the scale. The research findings revealed that the Teachers' Emotional Literacy Scale is a valid and reliable tool to measure emotional literacy. The study also confirmed that there are five sub constructs (knowing emotions, showing empathy, managing emotions, emotional resilience, and emotional interactivity) of emotional literacy.
... This approach provides a deeper understanding of model performance by classifying fit indices into percentile-based categories of Very Weak, Weak, Moderate, Strong, and Very Strong fit. Kline (2016) recommends the use of at least four fit indices, although more can be reported. One of the indices that is reported is Chi-Square (χ 2 ); however, given that the χ 2 is sensitive to the sample size and therefore the probability of rejecting the hypothesized model increases when the sample size increases, it is recommended to take into account other indices (Marsh et al., 1996) and for this reason it was reported but not taken into consideration as a fit index. ...
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This study examined the psychometric properties and factor structure of the 6-item Adult ADHD Self-Report Scale Screener (ASRS-6) in a sample of 753 employed adults in Puerto Rico. Confirmatory factor analyses supported a bifactor model featuring a dominant general ADHD factor and two weaker specific dimensions (inattention and hyperactivity). The general factor accounted for a substantial proportion of shared variance (ECV = .520; ωH = .724), supporting the use of a total score as the primary indicator of ADHD symptom burden. However, the hyperactivity subscale demonstrated sufficient unique reliability (ωHS = .561), suggesting it may offer incremental value in select contexts. The ASRS-6 also showed strong internal consistency, and scores were higher among participants with prior ADHD diagnoses. Practical implications include the use of ASRS-6 for brief screening in occupational settings, where undiagnosed ADHD may impact safety and productivity. Findings support the use of the ASRS-6 total score, while recommending cautious interpretation of the hyperactivity subscale only when warranted. Limitations and directions for future research, including the need for longitudinal and cross-cultural validation, are discussed.
... The measurement model validated constructs related to the creative school environment, creative activities at school and outside school, and openness to art and reflection using the lavaan package in R. Model fit was assessed using CFI, Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR), following established guidelines for ordinal data (Hu and Bentler 1999;Kline 2016). According to these criteria, a good model fit is indicated by CFI and TLI values ≥ 0.95, RMSEA ≤ 0.06, and SRMR ≤ 0.08. ...
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Creativity is a critical skill for problem‐solving and innovation, yet its development is influenced by cultural and educational contexts. This study examines pathways to student creativity using data from 15‐year‐old students in Australia and Thailand who participated in PISA 2022. A structural equation modeling (SEM) approach was employed to explore how school environments, creative activities, and openness to art shape student creativity, and to assess measurement and structural invariance across cultural contexts. This study addresses a research gap in cross‐cultural creativity research by validating a theoretically grounded SEM model in two education systems with distinct cultural orientations. Measurement invariance testing confirmed configural and partial metric invariance, allowing for valid comparisons of structural relationships but not direct latent mean comparisons. The results highlight that openness to art significantly predicts student creativity and engagement in both in‐school and out‐of‐school creative activities. Additionally, extracurricular creative engagement strongly influences participation in school‐based creative programs, underscoring the importance of fostering creativity beyond structured school activities. However, structured creative activities within schools negatively predict student creativity, suggesting that rigid school programs may limit creative potential rather than enhance it. These findings underscore the need for more flexible, student‐driven approaches to fostering creativity in education. Australia and Thailand were selected as comparison countries due to their contrasting educational philosophies—one emphasizing student autonomy and the other emphasizing conformity—offering valuable insights into how cultural context shapes creativity. Given the lack of full measurement and structural invariance, within‐group analyses remain essential for understanding creativity across different educational systems. The study contributes to creative education by providing empirical evidence that can guide culturally responsive instructional practices and assessment strategies.
... SEM is a comprehensive statistical method that analyzes complex relationships among multiple variables within a unified framework. It is particularly suitable for models incorporating both latent and observed variables 77 . In this study, SEM is employed to investigate the relationships among students' motivation, satisfaction, behavioral intention, and score. ...
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Heritage education has drawn increasing attention, with digital games and online courses emerging as innovative learning tools. However, the integration of asynchronous digital games and synchronous online courses remains underexplored. This study introduces Bichronous Modes (BMs) in heritage education, combining these two approaches to improve motivation, behavioral intentions for heritage preservation, and learning outcomes. Two experiments investigated the effectiveness of different learning sequences: BMgame-course (asynchronous games followed by synchronous courses) and BMcourse-game (synchronous courses followed by asynchronous games). Results indicated that BMs are more effective than using either approach alone. Specifically, BMgame-course facilitated heritage knowledge acquisition, while BMcourse-game improved student satisfaction. A structural equation model (SEM) revealed that satisfaction mediates the relationship between motivation and behavioral intentions for heritage preservation. This study highlights BMs’ potential in heritage education program design and suggests future avenues for refining learning mechanisms, emphasizing their applicability in schools and museums to promote sustainable heritage education.
... To account for abnormality, CFA-models were estimated with maximum likelihood estimation with robust standard errors (MLR). Model fit was evaluated by means of four standard model fit indices (Kline 2015): (1) the Yuan-Bentler scaled chi-squared should be as small as possible; ...
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Previous research has measured athletic identity by using multiple questionnaires, which mainly tap into the commitment dimension of athletic identity. The aim of the present study was to develop and investigate the psychometric features of a multidimensional measure to assess sport‐specific identity exploration and commitment dimensions. Therefore, we adapted the Dimensions of Identity Development Scale (DIDS) to a sport‐specific context (DIDS‐Athlete or DIDS‐A) to identify three sport‐specific exploration dimensions and two sport‐specific commitment dimensions. Data of the DIDS‐A and other self‐report measures assessing sociodemographic variables, sport‐related variables, and psychological symptoms were collected from 173 competitive athletes (72.1% women; age range: 16–34 years) who are all members of track and field sport clubs in Flanders (Belgium). Confirmatory factor analysis confirmed the five‐factor structure of the DIDS‐A and the scales had sufficient internal consistency. Athletic ruminative exploration, characterized by repeatedly worrying about sport‐identity related choices, was related to being younger, having a higher number of resting days, having one or more sport‐injuries, lower levels of competition, and higher levels of depressive symptoms and more exercise to control weight. The commitment dimensions, on the contrary, showed an opposite—more resilient—pattern. Therefore, it seems indicative to target athletes who score high on ruminative exploration about their role as athlete and to monitor them during their athletic trajectory.
... Model fit was assessed using the most commonly accepted descriptive fit indices and their cut-off values. We report the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA) and the standardized root mean square residual (SRMR) (Kline, 2005). CFI and TLI values above .90 ...
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Introduction Current academic motivation is affected by personal and situational factors. This highlights the dynamic nature of academic motivation, which is shaped by its social contexts, particularly by peers at school. Aims We investigated the relationships between peer interactions and three aspects of students' current academic motivation (positive activation, enjoyment of learning and concentration) in real learning situations in the classroom. We also examined whether and to what extent aspects of the social environment within the class (social classroom climate, the perceptions of peers and teachers as motivators) affected current motivation. Sample The study involved NL2 = 145 fifth graders in secondary schools, who completed a total of NL1 = 3099 (M = 21.4 per student) short questionnaires on tablet computers during class in one school week. Method The Experience Sampling Method was used to simultaneously measure students' aspects of current motivation and their peer interactions in class. In addition, the students reported on their social classroom climate and their perceptions of peers and teachers as motivators using a conventional questionnaire. Multilevel structural equation models were specified. Results Results revealed considerable variability in aspects of current motivation. Students showed higher levels of current academic motivation when they interacted with peers compared to learning situations in which they did not interact with peers (i.e. when they studied alone), when they perceived a positive social classroom climate and when they perceived their peers as supportive. Discussion The study underscores the situational dependence of students' current academic motivation and the central role of peers in aspects of current academic motivation.
... The fit of the raw model and that of the weighted model were compared. The following criteria defined an acceptable model: χ 2 /df less than 3; comparative fit index (CFI) and Tucker -Lewis index (TLI) greater than 0.90 or 0.95; and root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) less than 0.06 and 0.08, respectively (Hu & Bentler, 1999;Kline, 2023). ...
Article
Addressing the lack of high-quality physical literacy instruments for older adults, the goal of this study was to examine the validity and reliability of the Physical Literacy Assessment for Older Adults (PLAOA), which was previously developed through a Delphi study. A sample of 380 older adults completed the Senior Fitness Test, self-reported questionnaires, and accelerometer (ActiGraph) measurements. After removal of misfitting items, the initial PLAOA contained 37 items. Construct validity was supported through (1) Rasch analyses confirming the unidimension-ality of the subdomains (0.1%-14.9% unexplained variance, eigenvalue < 2); (2) a strong correlation with the Senior Perceived Physical Literacy Instrument (r = 0.81, p < .001); (3) satisfactory confirma-tory factor analyses (χ2/df = 1.911, CFI = 0.940, TLI = 0.935, RMSEA = 0.049, SRMR = 0.052); and (4) good internal consistency with Cronbach's alpha of 0.80. Additionally, good test-retest reliability was demonstrated. This study has provided preliminary evidence of the validity and reliability of the PLAOA to better understand physical literacy and active aging in adults.
... Weight and height were analyzed as important components closely related to BMI and nutritional status. This approach aims to obtain a more accurate and comprehensive model of the relationships between factors affecting the quality of life in children with ALL (Kline, 2016). ...
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Background: Acute Lymphoblastic Leukemia (ALL) is the most common type of blood cancer in children. Treatment for ALL may affect the patient's quality of life. Factors such as nutritional status, maternal knowledge of nutrition, and dietary compliance play a role in determining the quality of life of children with ALL. This study aims to analyze the relationship between nutritional status, maternal knowledge, and dietary compliance with health-related quality of life (HRQoL) in children with ALL. Subjects and Method: This study used a cross-sectional design with a sample of 52 children with ALL at the Pediatric Hematology Clinic of Dr. Moewardi Surakarta Hospital in October-November 2024. The independent variables were nutritional status, maternal knowledge, and dietary compliance, while the dependent variable was HRQoL. Data were collected using anthropometric instruments and questionnaires, then analyzed with single logistic regression and path analysis. Results: Single logistic regression analysis showed that nutritional status (OR= 4.60; 95% CI= 1.311 to 16.139; p = 0.017) and dietary compliance (OR= 4.82; 95% CI= 1.39 to 16.78; p= 0.013) were significantly associated with HRQoL. Maternal knowledge had no significant effect (OR= 1.88; 95% CI = 0.35 to 10.18; p = 0.467). Path analysis showed that nutritional status, dietary compliance, and body mass index had a direct positive association with the child's quality of life. The path analysis model showed a good fit with the data (goodness of fit p = 0.594). Conclusion: Nutritional status and dietary compliance are major factors in improving the quality of life of children with ALL. Although maternal knowledge does not have a direct effect, the mother's role remains important through improving the child's dietary compliance. Multidisciplinary interventions that integrate nutrition education and family support are needed to enhance HRQoL in pediatric patients with ALL.
... Finally, for Pilot 4, we conducted confirmatory factor analyses for each scale using Stata version 18. Model parameters were estimated using maximum likelihood estimation. Model fit was evaluated using multiple fit indices, including Comparative Fit Index (CFI; Bentler, 1990), Tucker-Lewis Index (TLI; Tucker & Lewis, 1973), standardized root mean squared residual (SRMR; Kline, 2015), and root mean square error of approximation (RMSEA; Steiger & Lind, 1980). Model fit was assumed to be acceptable if RMSEA values are less than .08 ...
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Teacher well-being is a critical factor influencing educator retention and student outcomes, yet existing measures often fail to capture the nuanced dimensions of this construct. This study addresses this gap by developing and validating four new scales to support teacher well-being: Emotional Exhaustion, Workload, Administrative Support, and Colleague Support. The scales were developed to address the necessity for enhanced instruments to gauge teacher well-being, especially given the heightened demands and stress experienced by teachers. Drawing on previous research and incorporating direct input from practicing teachers, we crafted items that underwent multiple rounds of pilot testing. Psychometric analyses demonstrated strong reliability and validity across diverse samples, highlighting the utility of these scales in identifying specific areas of strength and need within school contexts. These tools offer researchers and practitioners actionable measures to better understand and support the well-being of educators, with implications for professional development, policy, and organizational change.
... This approach is particularly suitable for testing hypotheses (Hair, et al., 2019). Additionally, SEM integrates CFA and path analysis, ensuring that measurement and structural models align with theoretical expectations (Kline, 2023). The analysis demonstrated that the resultant indices, including Chi-square (CMIN = 265.057, ...
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This study investigates influential aspects of students' acceptance of online learning: students' readiness, peer support, and instructional support. Readiness, driven by motivation, technical skills, and self-management, affects online learning participation. This readiness is made up of self-learning and communication abilities in online environments, which influence acceptance and satisfaction. Peer support inspires collaboration and enhances learning gains. It reduces loneliness, boosts motivation, and facilitates teamwork, while instructional support aids learning through organized interaction and feedback. Instructional support (e.g., immediate feedback and well-structured instruction) also improves engagement and perceived accomplishment in online education. The study employed a systematic sampling plan, using 308 students at an American university pursuing online or blended courses. Confirmatory factor analysis was used to validate the measurement model, confirming construct validity and reliability. Structural equation modeling confirmed the tested hypotheses and relationships among the variables. Students who perceive online learning as useful and convenient are more inclined to engage with the learning management system, which aligns with the technology acceptance model. Psychological, technological, and behavioral readiness play a primary role in determining whether self-efficacious and self-regulated learners will adapt. Peer support is important in offsetting the alienating effect of e-learning and facilitating engagement, motivation, and cognitive presence. Interpersonal behavior, such as peer mentoring and group discussion, increases social belonging, reduces anxiety, and develops academic resilience. Instructional support is critical to the acceptance of online learning. Timely scaffolding and immediate feedback increase students' engagement and motivation. Institutional investments in technical and non-technical resources enable active participation. The study's broader implications are multifaceted and require a holistic approach focusing on content delivery, actively preparing students, fostering social connections, and supporting them throughout their journey. Student readiness is not a static trait; rather, it can be intentionally developed over time. Administrators should take pre-emptive measures with course design and focused interventions, like student training that promotes independence and empowerment. Institutional-level policies promoting peer-to-peer cooperation will enable universities to raise the general acceptability of online learning, student involvement, and satisfaction. Instructional support must prioritize clarity and engagement to foster student acceptance of online learning. Institutions can significantly enhance the acceptance of online learning by employing academic and emotional support, integrating technology, and providing comprehensive learning support services. In addition, institutions must constantly build and maintain a solid technology and non-technology support system that includes e-advising, e-tutoring, and mental health counseling for online students. The study advances e-learning practices by reframing student readiness as a dynamic quality that organizations can cultivate with focused instruction and assistance. The results offer practical advice for creating welcoming, stimulating, and encouraging online environments that increase student acceptance of online learning.
... Parallel process growth modelling was utilised to evaluate the mean trajectories of externalizing and internalizing problems from T1 to T8. The base model was identified using relevant fit indices recommended by Kline (2016). The retained base model showed that externalizing scores followed quadratic growth, decreasing in mid-childhood only to increase again in adolescence, while internalizing scores decreased linearly over time. ...
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Adolescent substance use remains a significant public health concern and is associated with future negative outcomes. Risk factors for the development of adolescent substance use behaviours include the presence of externalizing and/or internalizing problems; however, previous studies have not always considered their co-occurring influences. This study aims to better understand the role of externalizing and internalizing problems in the development of adolescent substance use using a person-centred approach. Participants were drawn from an ongoing longitudinal study of children with and without early conduct problems (N = 744). Externalizing and internalizing problems were measured annually using teacher and parent reports from study inception to 7 years later. Substance use outcomes were measured using self-report when participants were approximately 17 years old. Latent class growth analyses identified four trajectory classes: (i) a decreasing externalizing co-occurring trajectory characterised by clinical and at-risk levels of both externalizing and internalizing problems, (ii) a high stable co-occurring trajectory characterised by clinical levels of externalizing problems and at-risk/clinical levels of internalizing problems, (iii) an at-risk externalizing trajectory characterised by at-risk levels of externalizing problems and non-clinical levels of internalizing problems, and (iv) a non-clinical trajectory. Youth in the high stable externalizing co-occurring trajectory were significantly more likely to report substance use behaviours and consequences when compared to other developmental trajectories, including the decreasing externalizing co-occurring trajectory. Our results suggest that the highest risk for substance use remains with those who follow a trajectory with high and stable externalizing problems. Early prevention and intervention efforts targeting externalizing problems could help decrease one’s future risk of engaging in substance use.
... p < .001, goodness of fit index (GFI) = 0.894, adjusted GFI (AGFI) = 0.849, and root mean square error of approximation (RMSEA) =0.093; the GFI was below the threshold of 0.9, which is considered to indicate good fit (Kline, 2016). ...
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Although many scales measure children’s image of older adults, none measure the image that older adults hold of children. This study creates a new scale with reference to previous studies. Using a preliminary survey, we examined whether the Child Image Scale originally designed for teachers could be applied to older adults; however, we found that it was insufficiently reliable. In our primary survey, we administered a questionnaire to individuals aged 65 years and older using newly created scale items. A factor analysis was conducted based on these data. Using exploratory and confirmatory factor analyses, we finally created the “Child Image Assessment Scale for Older Adults” (CIAO), which evaluates older adults’ image of children from three perspectives: purity, self-centeredness, and independence. The scale’s reliability and validity were confirmed using a primary and secondary survey and different samples. The results contribute to the effective evaluation of intergenerational exchange programs in the future.
... In each dimension item, the descriptive test revealed that the skewness was <3 and the kurtosis was <8. This was consistent with the normal distribution and could be further analyzed (Kline, 2023). Table 4 presents the descriptive analysis results. ...
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This study examines artificial intelligence in college students' painting education and their potential impact on students' continuous learning intention. In this study, two surveys were conducted. The first survey included 793 valid samples, and the second survey contained 210 valid samples. Study 1 established the path influence relationship between self-perceived creativity, flow experience, learning interest, and continuous learning intention, confirming gender and educational level as moderators. Study 2 identifies 4 positive factors and 3 negative factors to continuous learning intention through exploratory factor analysis. These findings not only provide a reference for the application of artificial intelligence to art education, but also provide new ideas and approaches for the widespread promotion and application of artificial intelligence to other disciplines of education.
... AVE values ranged from 0.50 (atmosphere) to 0.77 (intention to search the event), exceeding the recommended limit of 0.50 and providing evidence of convergent validity (56). Furthermore, evidence of discriminant validity was accepted since the correlation coefficients were lower than the suggested criterion of 0.85 (61) and none of the squared correlations exceeded the AVE values for each associated factor (56). The correlation matrix for the constructs is presented in Table 2. ...
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Introduction: The current study aims to explore how the physical environment of eSports events can influence fan affective responses and their future behavioural intentions. Following the Stimulus-Organism-Response (S-OR) model, affective response (pleasure) is conceptualized as the organism (mediator) between the physical environment (stimulus) and behavioural intentions (response). Method: The dependent variables were revisit intention and word-of mouth, while demographic factors including age, education level, nationality, and event attendance to describe the sample and examine their potential influence. Data collection was carried out at a "Lisboa Games Week" event (n = 328) by using a self-administered questionnaire. A Confirmatory Factor Analysis analysed the psychometric properties of the constructs and a subsequent Structural Equation Modelling examined the substantive hypotheses tested. Results: Results indicate that the physical environment quality positively influences the affective responses of fans, which motivates them to follow eSports events. Furthermore, fans affectively attached to an eSports event are more intent on revisiting it and making word-of-mouth recommendations about it. Discussion: A high standard service quality is a critical issue for event managers, marketeers, and publishers due to its impact on the behavioural and affective value creation towards the event.
... For evaluating the effects of ACAP, we applied structural equation modelling (SEM) in Mplus 8.6 (Muthén & Muthén, 2021) and used Full Information Maximum Likelihood (FIML) to address missing data (Lei & Shiverdecker, 2020). Preliminary, we checked for multicollinearity by predicting SAMR with the observed independent variables in a linear regression model, and variance inflation factor values were lower than 3.60, which is considered acceptable (Grewal et al., 2004;Kline, 2016). In order to assess the goodness of fit of the models, we used the standardized root mean square residual (SRMR) and the comparative fit index (CFI), with cut-offs of SRMR <0.08 and CFI >0.95 (Schermelleh-Engel et al., 2003;Shi & Maydeu-Olivares, 2020). ...
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This study examines whether and how a school's information and communication technology (ICT) knowledge absorptive capacity (ACAP) affects technology integration in schools. In addition, it investigates the influence of various contextual factors on the degree of contingency of ACAP, such as activation triggers, social integration mechanisms and regimes of appropriability. The study is based on a random sample of N = 411 schools representative of Germany. Structural equation modelling and machine learning were employed. The findings indicate that ICT ACAP has a positive impact on technology integration in schools and serves as a mediator in the relationship between external knowledge and technology integration. The impact of ICT ACAP on technology integration is contingent upon the presence and efficacy of knowledge‐sharing mechanisms within the school, as well as the extent to which schools engage in collaborative efforts with competitors (coopetition). The insights of this study have implications for policymakers and educational leaders, who could prioritize building ACAP and fostering collaborative networks to create more adaptable and innovative school environments. Practitioner notes What is already known about this topic For schools, technology integration is considered an important educational innovation. Acquiring, creating and sharing knowledge are essential for an efficient technology integration. Knowledge absorptive capacity (ACAP) is a critical factor in the acquisition of knowledge. What this paper adds Higher information and communication technology (ICT) ACAP is associated with increased technology integration. ICT ACAP mediates between the depth of external knowledge and technology integration. The efficacy of ACAP is contingent upon a number of contextual variables, in particular, knowledge sharing in schools and coopetition. Implications for practice and/or policy Schools need to identify, integrate and exploit relevant ICT knowledge to integrate technology successfully. Schools must develop systematic knowledge management systems to ensure that newly acquired knowledge is used reasonably. Schools must collaborate, even if they compete, to succeed in technology integration.
... The assessment criteria refer to several goodness-of-fit indicators recommended in the literature. The Chi-square/df index with a value of ≤ 2 indicates a perfect fit, while a value of ≤ 3 is still acceptable as a good fit (Kline, 2016). The RMSEA (Root Mean Square Error of Approximation) value of ≤ 0.05 indicates a perfect fit, while a value of ≤ 0.08 indicates a good fit (Norabuena-Figueroa et al., 2025). ...
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Local wisdom-based approaches are an important strategy in making science learning more contextual and meaningful for students. However, there is no specific instrument available to measure students' cognitive engagement in local culture-based learning. The existing instruments are still general and do not reflect specific cultural dimensions. This study developed the Cognitive Engagement Instrument (CEI), a new measuring instrument that combines the ICAP (Interactive, Constructive, Active, Passive) theory with the context of local wisdom. The aim was to analyze the validity and reliability of the CEI in measuring students' cognitive engagement. A total of 711 junior high school students from various regions in Indonesia participated in an online survey using a 5-point Likert scale. The results showed 37 valid items in four factors. The CFA model showed a good fit, with high reliability (α = 0.756–0.938; ω = 0.764–0.939).
... For the final model, McDonald's ω was estimated to evaluate the subscales' reliability both for the total sample and for Canada, Germany and Switzerland separately. According to Kline (2023), values ≥0.70 indicate a good reliability. ...
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Introduction: While teachers’ individual and collective efficacy has been extensively studied with regard to promoting students’ academic success, teachers’ collective efficacy regarding inclusive practices has been largely neglected thus far, especially from an international perspective. International comparisons are of particular interest to any country or school system, respectively, as they can help to identify alternative approaches and opportunities for inclusive school development. The scale examined in this paper is ascertaining teachers’ collective efficacy with regard to inclusive education (TEIP-C) and is derived from a scale measuring (individual) Teachers’ Efficacy for Inclusive Practices (TEIP). This scale comprises three subscales termed Inclusive Instruction, Managing Behavior and Collaboration. Our major aim was to validate the tripartite structure of the original TEIP scale for the new TEIP-C scale and to demonstrate measurement invariance of the latter employing an international sample. Methods: The sample comprised 897 teachers from Canada, Germany and Switzerland. Different Confirmatory Factor Analysis (CFA) models were combined with Exploratory Structural Equation Models (ESEM). Measurement invariance across countries was examined by means of a multiple group confirmatory factor analysis (MGCFA) approach. Afterwards, the variables gender, age and teaching experience were included simultaneously as predictors of collective teaching efficacy to specify a multiple indicator multiple cause model (MIMIC). Results: We successfully validated the tripartite structure of the original TEIP scale for the new TEIP-C scale and demonstrated its measurement invariance employing samples from Canada, Germany, and Switzerland. Based on similar validations, it now appears possible for researchers to freely combine either of the six subscales focusing on teachers’ individual or collective efficacy with regard to inclusive education in their questionnaires in future studies. While the three country samples did not differ regarding Inclusive Instructions, significant differences in favor of Canadian teachers became apparent for Collaborations (compared to both, Switzerland and Germany) as well as Managing Behavior (Germany). Discussion: Overall, the results underline the comparably high standards of inclusive teaching in Canada. Additional differences on the basis of the two subscales just mentioned pointed to somewhat lower ratings of collective teacher efficacy with respect to inclusive education by female teachers in Canada and Germany and older teachers in Switzerland.
... For validating the developed mediation models as a well-specified model, at least four out of five fit statistics must be satisfied. These include the following: insignificant chi-squared, the Standardized root mean squared residual (SRMR), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and Root mean squared error of approximation (RMSEA) (Kline, 2005). ...
... The first method compares the model fit between one-and two-factor models of the focal construct (secrecy in our case) and another conceptually similar construct, through CFAs and chi-square (χ 2 ) difference test. This test examines whether the items from each measure share a common factor, or whether these items are empirically distinct (Kline 2005). Another approach is the Fornell-Larcker (1981) test. ...
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Although supervisors are expected to interact with their employees in a forthcoming manner, there are many occasions where they deliberately keep secrets from employees. What remains unclear from the literature is how employees respond to their perception of the supervisor's secrecy. To address this question, we develop a theoretical model by drawing on the social uncertainty model and cognitive theories of rumination. We hypothesize that perceived supervisor secrecy triggers rumination, which subsequently prompts employees to seek clarity from the supervisor, solicit gossip from coworkers, and experience heightened emotional exhaustion. Additionally, we propose that these effects are moderated by the quality of the supervisor‐employee relationship, or leader‐member exchange (LMX). We conducted three studies to test our hypotheses, including a vignette experiment (Study 1), a cued recall experiment (Study 2), and a multi‐wave, multi‐source field survey study (Study 3). Study 1 shows that perceived supervisor secrecy triggers rumination, which in turn increases clarity‐seeking, gossip‐seeking, and emotional exhaustion. Studies 2 and 3 largely replicate these findings, while presenting mixed evidence on the moderating role of LMX in the relationship between perceived supervisor secrecy and rumination as well as in the relationships between rumination and the distal outcomes. We conclude by discussing the theoretical and practical implications of our findings.
... According to established research standards, models exhibiting good fit generally display a χ 2 /df ratio less than 3.0, with more stringent criteria recommending thresholds of 2.0 or 1.0 (Byrne, 2013;Hu and Bentler, 1999), which validate the four-factor structure's superiority (M3). Furthermore, a chi-square test p-value greater than 0.05 indicates that differences between the model and empirical data are statistically non-significant (Kline, 2023). ...
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This study investigates the psychometric properties of the Berkeley Expressivity Questionnaire (BEQ) within a cross-cultural framework, specifically among Chinese international students in Malaysia. Exploratory factor analysis identified a four-dimensional structure that diverges from the original three-factor model. This new structure was subsequently validated through confirmatory factor analysis (N = 300), yielding superior model fit indices compared to alternative models, all exceeding conventional benchmarks. The findings highlight significant cross-cultural distinctions, notably in emotional concealment, reflecting the complex interplay between traditional Chinese cultural values and the demands of international educational environments. Detailed analyses indicated that specific adaptations in item wording and context were essential to achieve cross-cultural measurement validity. This research contributes to the methodological discourse on cross-cultural measurement and enriches understanding of emotional expression dynamics among international students. It underscores the importance of culturally responsive adaptations when employing Western-developed assessment tools across diverse populations. The proposed four-dimensional framework offers a refined perspective on emotional expressivity in multicultural educational contexts, providing valuable insights for enhancing the support structures aimed at improving adaptation and psychological well-being for Chinese international students.
... AMOS supports complex model testing, while SPSS aids in regression and other statistical procedures. The combined use of these tools strengthens the analytical rigor and provides a comprehensive understanding of how KM, BDA, technological competence, and innovation interact (Kline, 2015). ...
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The need for strong enterprise resource planning (ERP) software which helps organizations make the right decisions based on real-time data, has become more important as global markets have become more complex and supply chain ecosystems have become more volatile. Yet even the best ERP systems today struggle with agility and advanced predictive analysis. In this paper, we propose a new architecture for AI-enabled data-driven enterprise resource planning (ERP) systems to create efficient systems for marketing operations and resilient supply chain networks. The framework proposal consists of four vertical layers such as data ingestion layer, AI analytics layer (with machine learning, deep learning and natural language processing), ERP integration layer using service-oriented interfaces and business intelligence layer for output as suggestions so that it could promote better decision making. AI contracts (AI modules embedded in the system) allow for advanced capabilities such as customer segmentation based on behavior optimizing value-based marketing campaigns based on sentiment, mix prediction, time-series demand forecasting, inventory optimization and real-time anomaly detection. We implemented and validated the framework through three industrial case studies in the retail, electronics and logistics sectors. The experiments proved a great performance enhancement with 27.05% better forecast accuracy, 19% lower supply chain disruption and 32.15% higher efficiency of marketing campaigns against ordinary ERP deploys. It also talks about the integration challenges such as data quality, model interpretability and compatibility with legacy system. Results bolster believe for potential efficiency of AI-driven ERP to support strategic planning and flexibility of operations. We will analyze the use of explainable AI in combination of federation learning and blockchain-based technology for secure, decentralized ERPs in our future work.
... According to the findings of the power analysis, a minimum sample size of 153 is required for this research to achieve 80% statistical power for a medium effect (0.15) at a level of 5% for the proposed structural framework. Power analysis indicates that a minimum sample size of 153 is needed for this study; hence, the sample size utilized in this study (n = 451) is significantly larger than the minimum and consistent with other general rules of thumb (Haier et el., 2010;Kline 2005;Barclay et al., 1995). ...
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Purpose: Knowledge has emerged as one of the most valuable assets for organizations in recent times. Sharing of such knowledge promotes organizational performance. Drawing on the knowledge-based view theory, this study investigates the antecedents of Knowledge Sharing (KS) on Employee Performance among technology related SMEs, and Clan Culture is used as a moderator in the current study. Design/ Methodology/Approach: Data were gathered from Pakistan through snowball sampling, focusing on professionals employed in the Information Technology based SMEs. A total of 451 valid responses were analyzed using SPSS and smart PLS. Findings: The findings reveal a significant positive relation of all the KS antecedents (Motivation, Self-efficacy, Interpersonal Trust) with KS, and KS has a significant positive relation with Employee Performance. Additionally, Clan Culture moderates the relationship between Motivation and KS, Self-efficacy and KS and Interpersonal Trust and KS respectively. Originality/Value: The novelty of this study is in its comprehensive model, which integrates all the crucial KS antecedents of KS at one place, which previously remain un-tested in totality. Furthermore, the introduction of Clan Culture as a moderator adds fresh insights to the literature. Additionally, the hi-tech sector SMEs like IT based SMEs in Pakistan, are under-researched, thereby filling such gap. Keywords: Knowledge Sharing Antecedents (Motivation, Self-efficacy, Interpersonal Trust), Knowledge Sharing, Employee Performance, Clan Culture, Hi-tech SMEs, KBV Theory.
... The model fit indices were employed to evaluate the structural equation model fit, including a nonsignificant chi-squared statistic ( χ 2 ), the comparative fit index (CFI) exceeding 0.90, the root-mean-square error of approximation (RMSEA) below 0.08, and the standardized root-mean-square residual (SRMR) below 0.08 (Kline 2023). The full information maximum likelihood estimation (FIML) was used to address missing data (justification for the treatment of missing data in Supporting Information: C; Acock 2005). ...
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Numerous studies have supported the positive associations between experiences of early childhood maltreatment (ECM) and subsequent victimization of intimate partner violence (IPV). However, long‐term longitudinal research from childhood through adulthood still remains relatively sparse to elucidate the mechanisms that account for the downstream negative consequences of ECM for later close relationship well‐being. Guided by the Sequential Violence Model and the Social Dysfunction Framework of ECM, this study leveraged five‐wave longitudinal data from early childhood through young adulthood spanning 20 years of life (N = 1032, Mage = 2.98 years old, SD = 0.19, 58.04% females at the initial wave) to examine how experiences of ECM (year 3 and 5) might predict victimization of IPV in young adulthood (year 22) through individuals' disrupted social skills in middle childhood (year 9) as well as elevated behavioral maladaptation in adolescence (year 15). Results, most importantly, revealed two cascading pathways, such that experiences of ECM were positively associated with disrupted social skills in middle childhood, which in turn, predicted elevated levels of behavioral maladaptation in adolescence (especially increased externalizing maladaptation), which ultimately linked with heightened victimization of IPV in young adulthood. Our findings shed light on the developmental cascades linking experiences of ECM with later victimization of IPV. The identified process mechanisms might be important targets for the design of interventions aimed at preventing the transmission of early traumas in families of origin to interpersonal traumas in later romantic relationships.
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Background The transition to university often leads to increased demands and changes in lifestyle habits, which may affect mental health. In particular, loneliness could play a key role in the onset of psychological distress. Although many patterns are consistent across countries, cultural differences may influence students’ mental health and feelings of loneliness. Aims The aim of this study was thus to examine mental health domains and their relationship with loneliness among students from the University of Milano-Bicocca (Italy) and the University of Surrey (United Kingdom). Method Data were from the CAMPUS study, a cross-national survey on students’ mental health. A structural equation modelling (SEM) approach was carried out to simultaneously test the pathways between loneliness and clinical domains in the two populations. Results Anxiety and depressive symptoms were identified as the most common conditions in both the samples. However, Italian students were likely to show a higher degree of anxiety ( t = 7.01, p < .001), while UK undergraduates greater depressive symptoms ( t = −2.50, p = .013) and a higher prevalence of insomnia ( t = −9.55, p < .001). Poor academic performance, along with limited social interactions were associated with worse psychological well-being, despite the likely influence of lifestyle differences among countries. Finally, a significant correlation between loneliness, anxiety and depressive symptoms, as well as insomnia was found both in Italian and UK samples, as confirmed by multivariate analyses. Conclusions Our findings highlight the existence of a cross-nationally, clinically meaningful psychological burden among university students, with a major role played by loneliness. Extensive promotion of healthy social networks, as well as interventions to support academic performance are needed.
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Many companies, in today, technology and dynamic surroundings, have acknowledged knowledge management (KM) and IT tools as valuable resources in addition to other resources for the competitive advantage of organizations. Therefore, this study was conducted with the aim to examine the influence of knowledge storage (KS), knowledge sharing and application (KShA), towards organizational performance (OP). Moreover, to investigate the moderating effect of knowledge management tools (KMT) in the relationship among these variables, in the cruise industry. Data were collected through a questionnaire survey from 283 participants employed on board three Carnival Cruise Lines ships. The Partial Least Squares Structural Equation Modelling (PLS-SEM) technique is adopted to explore relationships among variables. The results showed the significant and positive impact of knowledge storage, sharing and application on OP, as well as the existence of a moderating effect of KMT on the relation between these variables, which was further explained by simple slope analysis. This research contributes to the existing literature by exploring KM and OP specifically in the cruise industry. The practical implications indicate that organizations should integrate KM with technology and provide managerial training, which leads to the delivery of efficient, high-quality services, ultimately enhancing overall performance.
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This study aimed to explore the psychological factors related to stock addiction tendencies among Korean adults with stock investment experience and develop predictive models using psychological variables, demographic profiles, and related characteristics. The participants comprised 400 Korean adults aged 19–68 years. The predictive models were validated using regression and decision-tree analyses. The results indicated that neuroticism, extraversion, agreeableness, the behavioral activation system (BAS), impulsiveness, sensation-seeking, risk-taking, and irrational beliefs in stock investment were positively correlated with stock addiction. To address potential heteroscedasticity identified in residuals from the stepwise regression model, a robust regression analysis using Huber’s M-estimator was conducted based on the predictors selected through stepwise regression. The robust regression analysis revealed that overconfident or illogical reasoning, impulsiveness, and risk-taking were key predictors of stock addiction, with drive also showing a significant effect and BIS demonstrating a marginal effect. These five variables together accounted for a substantial proportion of variance in stock addiction while addressing potential heteroscedasticity. The decision-tree model identified risk-taking, stock balance, overconfident or illogical reasoning, reward responsiveness, impulsiveness, extraversion, and minor investor status (defined by low trading volume rather than investment experience) as predictors of stock addiction among Korean adults. These findings highlight that psychological variables—such as overconfident or illogical reasoning and risk-taking—are crucial factors in the development of stock addiction among Korean adults.
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Individual differences in cognitive abilities and explicit instruction can affect language learning. Understanding how individual differences and instruction interact, however, requires us to determine the points in the language learning process that are open to influence. One hundred and eleven adults were exposed to an artificial language comprising transitive sentences occurring with action scenes and were either instructed or not in the language structure. Learning proceeded by determining the cross-situational correspondences between words and scene features. We found that declarative memory ability related strongly and positively but procedural memory related weakly and negatively to overall immediate learning. Rule-search instruction also positively influenced short-term learning, but not of the structure that was explicitly highlighted, and this was most pronounced in those with high declarative memory. The results highlight which features of language learning are accessible to information about language structure, and how that is affected by the learners' cognitive abilities, with practical implications for personalised design of language learning programmes.
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Particularly, in sub-Saharan Africa, where game-based learning is still in its nascent stages, it is important to understand the factors that shape preservice teachers’ intentions to adopt commercial video games in their teaching-learning practice. A proposed model was tested against online survey data collected from 298 preservice teachers from four colleges of education in the northern region of Ghana, using structural equation modeling (SEM). The results showed that while Preference had a positive but insignificant effect on Intention, Experience and Learning Opportunity demonstrated strong, positive, and significant effects, consistent with existing findings in the acceptance of game-based learning. Subjective Norm, aligned with the Theory of Reasoned Action and Planned Behaviour also showed a strong, positive, and significant effect on Intention, whereas Gender had no significant effect on Experience conflicting findings from the study of parents’ acceptance of video games. The final model with Experience, Learning Opportunity, and Subjective Norms explained 44.5% of the variance in intention to use COTS games. The study implies that to foster successful adoption: (1) there is the need for hands-on workshops and practical sessions, allowing for experimenting with COTS games, (2) the educational benefits of COTS games should be emphasized among preservice teachers, and (3) there should be environments that support peer-mentoring and collaborative learning about COTS games.
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In the context of an increasingly digital economy, firms are rapidly adopting technological innovations to bolster financial resilience and competitiveness. However, the quantitative impact of digital transformation on key financial outcomes—specifically performance, indebtedness, and risk—remains underexplored. This study investigates the extent and pathways through which digital transformation influences financial structures and stability. Employing Structural Equation Modeling (SEM) on firm-level survey data, the analysis reveals that digital transformation significantly enhances financial performance (β = 0.538, p < 0.01). Improved performance, in turn, leads to substantial reductions in firm indebtedness (β = −0.591, p < 0.01) and financial risk (β = −0.124, p = 0.021). While digital transformation does not directly affect indebtedness, it mitigates financial risk indirectly through two mediating variables: financial performance and firm indebtedness (mediated effects: β = −0.221 and β = −0.318, respectively; both p < 0.01). These findings underscore the financial value of digital initiatives, highlighting their role in enhancing performance and reducing financial vulnerabilities. The study offers strategic insights for managers and policymakers aiming to leverage digital transformation for financial optimization.
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Background Body shape concerns have emerged in eating disorders as a public health issue among adolescents worldwide. The psychometric properties of the Body Shape Questionnaire (BSQ) remain underexplored in Chinese university students with eating disorder symptoms. This study aims to evaluate the reliability and validity of the Chinese version of the BSQ in the context of eating disorder symptoms among Chinese university students. Methods A stratified random sample of 858 Chinese university students (age, mean ± SD = 19.91 ± 1.18) participated in the study. The surveys comprised the BSQ and the EDE-QS to assess body shape concerns with eating disorder symptoms. Eating disorder symptoms were defined as scores equal to or greater than 15 on the EDE-QS. Results The Chinese version of the BSQ demonstrated strong internal consistency (Cronbach’s α = 0.92) and robust construct validity. Confirmatory factor analysis supported the original single-factor structure with satisfactory fit indices (Average Variance Extracted = 0.58, Composite Reliability = 0.92, Kaiser-Meyer-Olkin = 0.92, Normed Fit Index = 0.92, Goodness of Fit Index = 0.91, Comparative Fit Index = 0.93, Root Mean Square Error of Approximation = 0.09, Standardized Root Mean Square Residual = 0.03, Tucker-Lewis Index = 0.96). The BSQ showed significant correlations with the EDE-QS (p < 0.01). Conclusion The Chinese version of the BSQ demonstrates strong psychometric properties among university students with eating disorder symptoms, supporting its use as a reliable and valid assessment tool in the Chinese population.
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This study aims to understand citizens’ concerns about the use of artificial intelligence (AI) in policing by applying procedural justice theory. Drawing on data from an online public opinion survey (N = 583) conducted in three northeastern U.S. states (New Jersey, New York, and Pennsylvania), the research examines how perceptions of procedural justice, specifically neutrality, input/voice in decision-making, and trustworthiness, shape public support for AI in law enforcement. Using Structural Equation Modeling (SEM), the analysis reveals that these perceptions significantly influence levels of support for AI technologies in policing. Furthermore, concerns related to procedural justice fully mediate the relationship between knowledge of AI and support for its use. These findings highlight the importance of aligning AI implementation in law enforcement with the public’s expectations of fairness, transparency, and trust. The research findings are discussed, and their policy implications are considered.
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