The Factor Structure of a Written English Proficiency Test: A Structural Equation Modeling Approach

Position effects may occur in both paper–pencil tests and computerized assessments when examinees respond to the same test items located in different positions on the test. To examine position effects in large-scale assessments, previous studies often used multilevel item response models within the generalized linear mixed modeling framework. Using the equivalence of the item response theory and binary factor analysis frameworks when modeling dichotomous item responses, this study introduces a structural equation modeling (SEM) approach that is capable of estimating various types of position effects. Using real data from a large-scale reading assessment, the SEM approach is demonstrated for investigating form, passage position, and item position effects for reading items. The results from a simulation study are also presented to evaluate the accuracy of the SEM approach in detecting item position effects. The implications of using the SEM approach are discussed in the context of large-scale assessments.

Nursing students’ nomophobia, social media use, attention, motivation, and academic performance: A structural equation modeling approach

Gross manual dexterity is an important part of human factors and ergonomics. The purpose of the current study was to investigate factors affecting gross manual dexterity. Gender, palm length, grip strength, hand skin temperature, room temperature, and room humidity were analyzed simultaneously to predict gross manual dexterity by utilizing Structural Equation Modeling (SEM) approach. SEM showed that hand skin temperature was the most important factor for predicting gross manual dexterity, followed by several other factors such as grip strength, gender, and room temperature. In addition, room humidity, age, and hand size were also had significant indirect effects on gross manual dexterity. The SEM derived in this study could be a very valuable theoretical foundation which could be very beneficial for human factors engineer, physical therapist, and even medical doctors.

Factors affecting response actions of the 2020 Taal Volcano eruption among Filipinos in Luzon, Philippines: A structural equation modeling approach

This paper concerns the divisibility of comprehension subskills measured in L2 listening and reading tests. Motivated by the administration of the new Web-based English as a Second Language Placement Exam (WB-ESLPE) at UCLA, this study addresses the following research questions: first, to what extent do the WB-ESLPE listening and reading items measure different comprehension subskills? Second, to what extent can L2 listening and reading be considered similar or different, with regard to the divisibility of comprehension subskills? Employing a structural equation modeling (SEM) approach, the factor structures of 110 test takers' scores on the WB-ESLPE listening and reading items were examined with regard to three types of subskills, that is, `understanding main/topical ideas', `understanding supporting/specific details', and `making inferences'. The results of the analyses indicated that the WB-ESLPE listening and reading items measure two or three kinds of subskills, and that while L2 listening and reading might share a common comprehension process, they may be distinct in the decoding processes involved due to the difference in mode of presentation. It is suggested that this divisibility of subskills in L2 comprehension tests might depend on the test takers' L2 proficiency as well as on the task characteristics of the test administered to them.

Purpose This study used extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the effect of personal expectancy (PE), efforts expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) and habit (H) on behavioural intention (BI) to use Chat Generative Pre-Trained Transformer (ChatGPT) in higher education for an Indian context. The study also examined moderating effects of students’ self-innovativeness (SIN) and integrity (INT) on the relationship between BI and use behaviour (UB) for ChatGPT. Design/methodology/approach A sample of 311 students has been selected from Northern states of India by applying stratified proportionate random sampling method and four disciplines – engineering, business administration, science and fine arts were used as different strata in the sample selection process. Partial least squares structural equation modelling (PLS-SEM) approach has been used in data analysis to assess proposed theoretical model. Findings The study found PE, FC, PV and H significantly account for students’ BI and actual use of ChatGPT, whereas EE, SI and HM showed a negligible impact on BI. The BI was also found non-significant in predicting the usage behaviour for ChatGPT. The moderation effects of SIN and INT of students were also found non-significant on the relationship between BI and UB. Research limitations/implications A limited sample size of study and its focus on Northern states of India constrain the generalizability of findings to the other parts of world. Originality/value The study helps to understand the nuances associated with advanced artificial intelligence (AI)-driven tool such as ChatGPT in higher education for the application of best-practices. Therefore, this study aims to bridge this gap by examining determinants of ChatGPT usage with extended version of UTAUT model in Indian context by using additional constructs such as SIN and INT.

<p style="text-align: justify;">This study used the structural equation modeling (SEM) approach to test a model that hypothesized the influence of self-efficacy, self-control, emotion, and engagement on student academic performance. The structural equation modeling model was developed to link all the study variables with a literature review to describe the interrelationship. Data collected were from 413 college students in their second year. The results show that self-efficacy, self-control, emotion, and engagement predict student academic performance. And through emotion and student engagement, both self-efficacy and self-control predict student academic performance indirectly. Practically the measures used in this study give more information about the learning environment in higher education settings than those usually come from traditional practices faculty received in the classroom, such as student rating forms and feedback. The main findings of this study have some implications for higher education, theory development, measurement, and future research.</p>

Limitations record on a variable which have continuous variable changes make the 'time' attached to the data is discrete. That underlies development of continuous time model. Compared to discrete time model, the continuous time model has advantages that can make prediction at different lag. In addition, it still can perform continuous time model parameter estimation, although the objects observations do not always have the same time interval (irregular time). Thus, the purpose of this study is to examine the consistency of continuous time model coefficient parameter with structural equation model (SEM) approach in irregular time data. The method used is the Exact Discrete Model (EDM) with SEM approach. EDM is a model that connects the parameter to value which is underlying parameter of the continuous time model with non-linear relationships. The result analysis of the research indicated that the coefficients of continuous time model parameter are still consistent until 20% of irregular time with 5% consistency limits.

This paper aims to identify the major significant dimensions that contribute to the overall quality of life (QOL) of wage workers in Egypt. As the QOL is a complex, multidimensional, and interdisciplinary concept, forty-seven indicators under five domains were chosen to investigate the QOL determinants of wage workers in Egypt, namely job characteristics, job satisfaction, ICT access, gender equality and women empowerment, and neighborhood services and utilities. Using data from the 2018 wave of the Egypt Labor Market Panel Survey, the paper employed structural equation modelling (SEM) approach to investigate the impact of proposed dimensions on the overall QOL. In addition, multi-group SEM analysis was implemented to measure how people differ in the way they assess their QOL on the basis of various moderating variables such as the geographical region of residence, age group, and years of schooling. The findings showed the significant impact of the chosen dimensions on the overall QOL. Moreover, the multi-group models showed a significant variation among compared groups, in which the weights of dimensions vary due to the differences in socio-cultural characteristics and the surrounding environment, confirming the complexity of such a concept. As people usually differ in the way they assess their QOL, which is affected by their characteristics and priorities.

Public transportation in Phnom Penh, Cambodia has undergone significant changes in recent years, with daily ridership increasing from 7,000 at its reintroduction in 2014 to about 20,000 passengers by 2023. Despite this progress, a considerable portion of the buses operate at around 50% of their total capacity, presenting a challenge to the system’s efficiency and sustainability. In order to shift Phnom Penh towards a more sustainable transportation future, an examination of transit loyalty emerges as a strategy to retain and attract more users. This study aims to contribute to the understanding of urban public mobility in the context of a developing country, by investigating the relationships among accessibility, perceived value, satisfaction, service quality, and loyalty, as well as exploring the perceptions of loyal users of the public buses. Data collection was conducted through in-person and questionnaire-based interviews at bus stops and on the buses. Out of the 220 responses gathered, 186 were deemed suitable for further factor and reliability analyses. Finally, the data were analyzed using a Structural Equation Modelling (SEM) approach, and the best fitting model was developed to illustrate the relationship among the constructs of transit loyalty. Findings suggest that loyalty is primarily influenced by satisfaction, which is driven by perceived value and accessibility. Furthermore, service quality was found to have an impact on perceived value. This study suggests that there is a strong possibility for more demand for public transportation for non-bus users, provided the system offers better coverage and frequency. Consequently, this presents as an opportunity for policymakers and stakeholders to leverage these insights in shaping policies that would enhance the sustainability and appeal of public transportation in Phnom Penh.

Rail transportation is crucial for any strategy aiming to increase the use of public transportation at the expense of private travel. This chapter aims to contribute to the discussion by describing and comparing two different methods for analysing rail service quality, both based on user perceptions, in the context of the rail services offered by Italian operators in the north of the country. These methods are the Classification and Regression Tree Approach (CART) and the Structural Equation Modelling (SEM) approach. The CART approach suggests that factors such as cleanliness, availability of information, comfort and quality of service are most important. These results were confirmed by the SEM approach, according to which aspects regarding information, cleanliness and service have the highest positive effects on overall service quality.

ABSTRACTIn the present study, we used latent variable structural equation modeling to investigate relations between oral language, decoding, and two components of executive function (cognitive flexibility and working memory) and reading comprehension in a sample of 271 native English-speaking 9.00- to 14.83-year-olds. Results of the mediation analyses indicated that both oral language and decoding fully mediated the relations between working memory and cognitive flexibility and reading comprehension. These findings suggest that executive function is likely associated with reading comprehension through its relation with decoding and oral language and provide additional support for the role of executive function in reading comprehension as a potentially crucial precursor to skilled reading.

Purpose This study examined hope, meaning in life (MIL), and religious/spiritual struggle (RSS) as predictors of the quality of life (QOL) in cancer patients. We hypothesized a positive association of QOL with hope and MIL, whereas a negative association with RSS. The stage of cancer was hypothesized as a moderator variable between QOL and hope. Hope and MIL were assumed as positive predictors and RSS as negative predictor of QOL. Methods Data stem from the cross-sectional survey study of 300 cancer patients (Mean age = 50.97 ± 13.50 SD). Herth Hope Index, Meaning in Life Scale, Religious Spiritual Struggle Scale and WHO-QOL-BRIEF were used. The correlation coefficient and partial least square structural equation modeling approach (PLS-SEM) were used for assessing the measurement model and the structural model. Results As hypothesized, QOL was found positively associated with Hope and MIL, but negatively associated with RSS. The stage of cancer was hypothesized as a negative moderator. The three predictors significantly predicted QOL in cancer patients and explained 75.3% of the variance in QOL, and the overall model fit was adequate (SRMR = 0.075). Hope and MIL had a positive impact on QOL (β = .356, p < 0.01; β = .355 p < 0.01, respectively), whereas RSS had a negative impact (β = –.102, p < .05). The Stage of cancer did not moderate the path coefficient between the hope and QOL to a significant degree (β = .097, p > 0.01). Conclusion In cancer patients, hope and MIL are facilitators of QOL. Addressing religious and spiritual concerns and struggles is critical to overall QOL improvement.

HIV disclosure continues to be a key consideration among people living with HIV (PLWH). However, there is a lack of studies assessing factors associated with HIV disclosure among PLWH in the Southern U.S. Therefore, the aim of this study was to assess the association between sociodemographic risk factors and HIV disclosure using a structural equation modeling approach among PLWH in South Carolina. Exploratory factor analysis was used to operationalize HIV disclosure. Structural equation models were used to determine the associations between sociodemographic factors and HIV disclosure among PLWH. Two latent variables were obtained for HIV disclosure: partners (stable partners, spouses, casual partners), and family/friends (parents, grandparents, siblings, children, adult children, friends, and coworkers). After adjusting for confounders, Black populations were less likely to disclose their HIV status to both partners (β = −0.250, p = 0.006) and family/friends (β = −0.246, p < 0.001) compared to non-Black populations. As yearly income increased, the likelihood of HIV disclosure to family/friends decreased (β = −0.300, p = <0.001). As time since diagnosis increased, the likelihood of HIV disclosure to family/friends increased (β = 0.266, p = 0.001). Future research can assess the feasibility of implementing disclosure interventions that are geared towards Black, high income and newly diagnosed PLWH and the associations of psychosocial factors and HIV disclosure.

&#x0D; Backgroung. In public health one debated issue is related to consequences of improper self-management in health care. Some theoretical models have been proposed in Health Communication theory which highlight how components such general literacy and specific knowledge of the disease might be very important for effective actions in healthcare system. &#x0D; Methods. This paper aims at investigating the consistency of Health Empowerment Model by means of both graphical models approach, which is a “data driven” method and a Structural Equation Modeling (SEM) approach, which is instead “theory driven”, showing the different information pattern that can be revealed in a health care research context.&#x0D; The analyzed dataset provides data on the relationship between the Health Empowerment Model constructs and the behavioral and health status in 263 chronic low back pain (cLBP) patients. We used the graphical models approach to evaluate the dependence structure in a “blind” way, thus learning the structure from the data.&#x0D; Results. From the estimation results dependence structure confirms links design assumed in SEM approach directly from researchers, thus validating the hypotheses which generated the Health Empowerment Model constructs.&#x0D; Conclusions. This models comparison helps in avoiding confirmation bias. In Structural Equation Modeling, we used SPSS AMOS 21 software. Graphical modeling algorithms were implemented in a R software environment.&#x0D;