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structural equation modeling of the impact of disease activity on inflammatory bowel disease control: the mediating roles of self-efficacy and self-management behaviors

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BMC GASTROENTEROLOGY 2025年第1期25卷 1-14页

作者： Zhu, Yongli Liu, Ke Jiang, Jinfeng Cheng, Xin Wang, Hao Long, Feiyang Li, Kang Mu, Changping Cui, Lijun North Sichuan Med Coll Affiliated Hosp Dept Nursing Nanchong Peoples R China North Sichuan Med Coll Nanchong Peoples R China Chongqing Univ Chongqing Gen Hosp Chongqing Peoples R China

Background Maintaining effective disease control in patients with inflammatory bowel disease (IBD) is both a significant goal and challenge. Drawing on the Common-Sense Model of Self-Regulation (CSM) and related research, this study investigates how IBD activity status influences disease control through both direct and indirect pathways. Methods A cross-sectional survey was conducted among 310 IBD patients who attended a tertiary general hospital, the leader of the IBD Alliance Group in Chongqing City, between March and August 2024. structural equation modeling (SEM) was utilized to assess the role and magnitude of various influencing factor pathways. Relying on AMOS26 software, the path effects and magnitude of various factors in the disease control process were analyzed using structural equation modeling (SEM) to test hypothetical models. Results A total of 306 valid questionnaires were collected, with a mean IBD-control score of 12.14 +/- 3.665. There was a negative link between disease activity and IBD-control (P < 0.01) and a positive correlation between chronic illness management self-efficacy, IBD self-management behavior, and IBD-control (P < 0.01). Path analysis showed that IBD activity negatively predicted IBD control (beta = -0.715, P = 0.01). Chronic disease management self-efficacy partially mediated this relationship (beta = -0.071, P = 0.012). A significant chain-mediated pathway was identified, where IBD activity affected IBD control via self-efficacy guided by self-management behavior (beta = -0.025, P = 0.007). However, the pathway where IBD activity influenced control through self-efficacy and subsequently self-management behavior showed only marginal significance (P = 0.074). Conclusion Effective self-management behaviors improve IBD control. High disease activity may reduce chronic disease management self-efficacy, impairing IBD control. Positive feedback loops involving self-management behaviors and enhanced self-efficacy are crucial for better

关键词： Inflammatory Bowel Disease (IBD) Disease activity IBD-control Self-efficacy Self-management behaviour structural equation modeling

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structural equation modeling for influencing factors with quality care behavior among nursing assistants: a cross-sectional study

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BMC NURSING 2025年第1期24卷 1-12页

作者： Liao, Lulu Zhang, Yan He, Xiaoxiao Yang, Xiufen Long, Huan Tan, Lei Yang, Linghua Huang, Shenglan Li, Xia Chen, Huijing Huang, Lei Li, Hui Wang, Jieyu Zhang, Lihua Liu, Yilan Huazhong Univ Sci & Technol Union Hosp Tongji Med Coll Dept Nursing Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Tongji Med Coll Sch Nursing Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Med & Hlth Management Wuhan Hubei Peoples R China Southern Univ Sci & Technol Shenzhen Peoples Hosp Affiliated Hosp 1 Dept Geriatr Shenzhen Guangdong Peoples R China Changsha First Social Welf Inst Changsha Hunan Peoples R China Jianghan Dist Social Welf Inst Wuhan Hubei Peoples R China Wuhan Social Welf Inst Wuhan Hubei Peoples R China Yueyang City Social Welf Inst Yueyang Hunan Peoples R China Xinyang City Shengde Nursing Home Xinyang Henan Peoples R China Ping An Pension Insurance Personal Pens Business Dept Head Off Shanghai 200127 Peoples R China Xinxiang Med Coll Sch Nursing Xinxiang Henan Peoples R China Cent South Univ Xiangya Hosp 3 Dept Breast & Nail Surg Changsha 410013 Hunan Peoples R China Huazhong Univ Sci & Technol Union Hosp Tongji Med Coll Dept Neurosurg Wuhan Hubei Peoples R China

Background This study aimed to assess quality care behavior among nursing assistants and investigate potential influencing pathways based on the capability opportunity motivation-behavior (COM-B) model. Nursing assistants are the frontline staff responsible for most residents' daily care, and their care behaviors are closely associated with residents' quality of life. Methods A cross-sectional research methodology was implemented, and data were collected on demographic and sociological information, nursing assistants' quality care behaviors, care knowledge and skills, attitude toward older people, organizational climate, social support, work need satisfaction, and self-efficacy. The quality care behavior of nursing assistants was characterized using means and standard deviations. Key factors of quality care behavior were identified using structural equation modeling (SEM), ANOVA, Pearson's correlation, and the independent sample t-test. Results A total of 1,028 nursing assistants in 18 nursing homes in three central provinces were investigated. The mean total score for quality care behavior was 108.25 +/- 12.33. The findings demonstrated that care knowledge and skills, attitudes toward older people, organizational climate, social support, and work need satisfaction directly and indirectly impacted quality care behavior. The cumulative effect of attitudes toward older people (beta = 0.379, P < 0.001) and organizational climate (beta = 0.295, P < 0.001) on quality care behavior was higher. Conclusion Work need satisfaction and self-efficacy may have significant mediating effects in the link between capability (care knowledge and skills, attitude), opportunity (organization climate, social support) and quality care behavior. Facility managers should foster nursing assistants' professional identities by developing a supportive work environment that encourages their care practices.

关键词： Quality care behavior Nursing assistants Nursing homes Influencing factors structural equation modeling

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structural equation modeling

Structural Equation Modeling

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作者： Kuzminskaya, Kseniya Charles University of Prague

structural equation Models (SEM) - also called Simultaneous equation Models - are used to describe relationships among a set of variables. Similarly as in multivariate regression models, some of the variables are treated as predictors and the others as outcomes. However, unlike in a classical regression model, a variable, which is outcome in one equation, can become a predictor in another equation. SEM are even able to handle variables, which are not measured directly but only through their effects. They are often used in econometrics or socio-economics.

关键词： structural equation modeling simultaneous equation models LISREL

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Predicting College Student Engagement in Physical Education Classes Using Machine Learning and structural equation modeling

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APPLIED SCIENCES-BASEL 2025年第7期15卷 3884-3884页

作者： Zhang, Liguo Gao, Jiarui Zhao, Liangyu Liu, Zetan Guan, Anlin Shandong Univ Sch Phys Educ Jinan 250014 Peoples R China Guangxi Minzu Univ Sch Phys Educ & Hlth Sci Nanning 530006 Peoples R China

Digital technology has become increasingly prevalent in higher education classrooms. However, the impact of different types and use frequencies of digital technology on college students' classroom engagement can vary substantially. This study aims to develop an interpretable machine learning model to predict student classroom engagement based on various digital technologies and construct a structural equation model (SEM) to further investigate the underlying mechanisms involving perceived usefulness (PU), perceived ease of use (PEU), and academic self-efficacy (ASE). Nine machine learning algorithms were employed to develop interpretable predictive models, rank the importance of digital technology tools, and identify the optimal predictive model for student engagement. A total of 1158 eligible Chinese university students participated in this study. The results indicated that subject-specific software, management software, websites, and mobile devices were identified as key factors influencing student engagement. Interaction effect analyses revealed significant synergistic effects between management software and subject-specific software, identifying them as primary determinants of student engagement. SEM results demonstrated that digital technology usage frequency indirectly influenced student engagement through PU, PEU, and ASE, with both PU and ASE as well as PEU and ASE playing chain-mediated roles. The findings underscore the importance of integrating digital tools strategically in PE classrooms to enhance engagement. These insights offer practical implications for higher education institutions and policymakers.

关键词： machine learning structural equation modeling student engagement physical education classes digital technology

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The Effect of Measurement Error on Hypothesis Testing in Small Sample structural equation modeling: A Comparison of Various Estimation Approaches

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structural equation modeling-A MULTIDISCIPLINARY JOURNAL 2025年第2期32卷 215-236页

作者： Bogaert, Jasper Loh, Wen Wei Schuberth, Florian Rosseel, Yves Univ Ghent Ghent Belgium Maastricht Univ Maastricht Netherlands Univ Twente Enschede Netherlands

Researchers seeking valid statistical inference in the presence of measurement error often apply approaches that ignore measurement error. This may result in biased estimates, inflated type I error rates, diminished power, and therefore, increases the risk of drawing erroneous conclusions. However, current advice on accounting for random measurement error is limited to large samples and traditional linear models. This article aims to address this gap for small samples and recent estimation approaches in structural equation modeling. Our results show substantial type I error rate inflation for approaches that ignore measurement error when the model contains correlated latent predictors.

关键词： Factor score regression measurement error partial least squares structural after measurement approach structural equation modeling

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Drivers of aboveground biomass in Quercus wutaishanica Mayr forests based on random forest and structural equation modeling: A cross-scale analysis

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ECOLOGICAL MODELLING 2025年 505卷

作者： Ma, Shuaishuai Zhang, Huayong Wang, Zhongyu Zou, Hengchao Xu, Xiaona North China Elect Power Univ Res Ctr Engn Ecol & Nonlinear Sci Beijing 102206 Peoples R China Shandong Univ Sch Life Sci Theoret Ecol & Engn Ecol Res Grp Qingdao 266237 Shandong Peoples R China

A comprehensive understanding of vegetation biomass is essential to gain deeper insights into the global carbon cycle. Quercus wutaishanica Mayr forests are the dominant and established species in temperate deciduous broadleaved forests in China. They play a significant role in the ecological functions and carbon sequestration of forests. At present, the drivers and influencing mechanisms of aboveground biomass (AGB) of Q. wutaishanica forests have not been clearly quantified across different scales. In this study, we examined the effects of abiotic factors, encompassing climatic conditions and soil properties, and biotic factors that involve grass coverage and forest age, and disturbances on the AGB of Q. wutaishanica forests at overall and 15 vegetation regionalization scales in China using random forest (RF) and piecewise structural equation modeling (piecewiseSEM). The results from the RF model and piecewiseSEM explained 68 % and 47 % of the variance in AGB, respectively, at the overall scale. Climatic factors represented by temperature seasonality (TS) and climate moisture index (CMI) primarily shaped community biomass patterns overall. These factors affected AGB directly and indirectly by influencing edaphic and biotic factors, respectively. In addition, the AGB was mainly constrained by significant seasonal temperature variations or inadequate moisture. The direct effect of biotic factors, specifically forestage and grass coverage, on AGB was more pronounced at the regional than at the overall scale. The dominant factors in the adjacent vegetation zones exhibited a degree of geographical continuity. These findings represented an essential reference for carbon cycling mechanisms within terrestrial ecosystems.

关键词： Aboveground biomass Scale Random forest structural equation modeling Temperature seasonality Climate moisture index

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A study of residents' behavior in participating in smart waste sorting system based on structural equation modeling

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JOURNAL OF MATERIAL CYCLES AND WASTE MANAGEMENT 2025年第1期27卷 354-368页

作者： Wang, Ming Cao, Kewang Khan, Naseer Muhammad Hu, Xiaoman Zhao, Yinuo Dong, Furong Anhui Univ Finance & Econ Sch Econ Bengbu 233030 Peoples R China Natl Univ Sci & Technol Mil Coll Engn Dept Sustainable Adv Geomech Engn Risalpur 23200 Pakistan

Waste classification is vital for addressing the current urban waste crisis. However, existing research on intelligent waste classification systems has limitations compared to traditional methods. This study, grounded in the theory of planned behavior and contextualized within Chinese policy frameworks, surveyed 614 participants from Shanghai, Suzhou, Hangzhou, and other cities. The aim was to analyze residents' willingness to engage with intelligent waste classification systems and to construct a theoretical model. structural equation modeling was employed to examine the influence of system usability, incentives, time costs, social impact, behavioral attitudes, and intentions on residents' participation in intelligent waste classification. The findings reveal that perceived ease of use, perceived motivation, and time cost are significantly positively associated with behavioral attitudes. In addition, time cost, social impact, safety perception, and intelligence perception are strongly linked to residents' behavioral intentions. The ease of use, incentives, and time costs indirectly affect waste classification behavior through behavioral attitudes, while time costs, social impact, safety perception, and intelligence perception exert indirect effects through behavioral intentions. This study offers valuable insights for enhancing urban residents' participation in waste classification initiatives.

关键词： Waste separation Resident structural equation modeling Intelligence Mesomeric influence

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Childhood Pb-induced cognitive dysfunction: structural equation modeling of hot and cold executive functions

JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY

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JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY 2025年 1-10页

作者： Lane, Jamil M. Liu, Shelley H. Midya, Vishal Alcala, Cecilia S. Eggers, Shoshannah Svensson, Katherine Martinez-Medina, Sandra Horton, Megan K. White, Roberta F. Tellez-Rojo, Martha M. Wright, Robert O. Icahn Sch Med Mt Sinai Dept Environm Med New York NY 10029 USA Icahn Sch Med Mt Sinai Dept Populat Hlth Sci & Policy New York NY USA Univ Iowa Coll Publ Hlth Dept Epidemiol Iowa City IA USA Natl Inst Perinatol Dept Dev Neurobiol Mexico City Mexico Inst Expos Res Icahn Sch Med Mt Sinai New York NY USA Boston Univ Dept Environm Hlth & Neurol Sch Publ Hlth & Med Boston MA USA Natl Inst Publ Hlth Ctr Nutr & Hlth Res Cuernavaca Morelos Mexico

BackgroundChildhood lead [Pb] exposure has been consistently linked to neurotoxic effects related to the prefrontal cortex, a critical mediating structure involved in decision-making, planning, problem-solving, and specific aspects of short-term memory, i.e., the components of executive functions [EFs]. Limited studies have taken a deeper phenotyping approach that assess Pb's effects across multiple EF dimensions simultaneously, which can be organized into hot [e.g., reward, motivation] and cold [e.g., primary cognitive processing] *** investigated whether childhood Pb exposure affects hot and cold EF dimensions and assessed any sexually dimorphic *** a longitudinal birth cohort based in Mexico City, children's (n = 602) whole blood Pb levels (mean 23.66 mu g/L) were measured at ages 4-6 and they were administered several EF tasks at ages 6-9. Confirmatory factor analysis confirmed that six EF tests estimated two latent variables representing hot and cold EF dimensions. structural equation modeling [SEM] estimated the neurotoxic effect of childhood Pb exposure on latent variables of hot [higher scores indicate improved performance] and cold [higher scores indicate poorer performance] EFs. Subsequently, a multi-group SEM explored potential effect modifications by child *** exposure was significantly associated with negative impacts on hot EF performance [b = -0.129, p = 0.004]. In both males (b = -0.128, p = 0.032) and females (b = -0.132, p = 0.027), childhood Pb exposure was significantly associated with a reduction in hot EF performance, with no evidence of an interaction with sex. Additionally, we found no association between Pb exposure and cold EF performance [b = 0.063, p = 0.392] and no notable sex *** present study leverages a sophisticated SEM framework as an exploratory tool and a neurotoxic framework to analyze multidimensional cognitive data, aiming to delineate hot and cold EFs. Our fi

关键词： Lead exposure Executive function structural equation modeling Neurotoxicology

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Evaluating Imputation-Based Fit Statistics in structural equation modeling With Ordinal Data: The MI2S Approach

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EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 2025年第1期85卷 82-113页

作者： Sriutaisuk, Suppanut Liu, Yu Chung, Seungwon Kim, Hanjoe Gu, Fei Chulalongkorn Univ Fac Psychol Rama 1 Rd Bangkok 10330 Thailand Univ Houston Houston TX USA US FDA Washington DC USA Yonsei Univ Seoul South Korea

The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two alternative test statistics: the mean-adjusted test statistic (T M ) and the mean- and variance-adjusted test statistic (T MV ). Our results showed that the MI2S-based T MV generally outperformed other test statistics examined in a wide range of conditions. The MI2S-based root mean square error of approximation also exhibited good performance. This article demonstrates the MI2S approach with an empirical data set and provides Mplus and R code for its implementation.

关键词： missing data ordinal data multiple imputation model fit structural equation modeling

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Psychometric analysis of work organization and fatigue instruments and their relationship with occupational accidents: a structural equation modeling approach

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BMC HEALTH SERVICES RESEARCH 2025年第1期25卷 1-11页

作者： Khandan, Mohammad Montazeri, Ali Ebrahimi, Ali Qom Univ Med Sci Sch Publ Hlth Dept Occupat Hlth & Safety Engn Qom Iran Kara Amar Samin Qom Iran

Background Work organization significantly impacts occupational incidents and fatigue in hospital settings, particularly among nurses. This study aimed to evaluate the psychometric properties of instruments measuring work organization and fatigue and to examine their relationship with occupational accidents. Methods A cross-sectional study was conducted in 2019 with 200 nurses working in hospitals in Qom, Iran using the stratified sampling method. Data were collected using three standardized tools: the Work Organization Questionnaire, the Fatigue Checklist, and a demographic information questionnaire. structural equation modeling was employed to analyze the data, while instrument validity and reliability were assessed through Cronbach's alpha, composite reliability, and average variance extracted (AVE). Analysis was performed using Smart PLS and SPSS V20. Results The analysis revealed a significant relationship between work organization and occupational accidents (t = 3.22, p < 0.05). However, the relationships between work organization and fatigue (t = 0.03) and between fatigue and occupational accidents (t = 1.49) were not statistically significant. The Work Organization Questionnaire (WOAQ) demonstrated robust validity and reliability, making it suitable for assessing occupational risks in hospital environments. In contrast, the Fatigue Questionnaire (CIS) exhibited acceptable validity but insufficient reliability (Cronbach's alpha < 0.7), highlighting the need for further refinement. Conclusion This study revealed that the Work Organization Questionnaire has acceptable validity and reliability, making it suitable for hospital settings, while the Fatigue Questionnaire requires further revision. It is recommended that hospital administrators optimize work schedules and provide fatigue management training, and policymakers utilize validated tools to reduce occupational risks and enhance workplace safety.

关键词： Work organization Fatigue Accidents Nurses structural equation modeling

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