Trajectories of Self-Rated Health Among Industrially Disabled Individuals: A Latent Class Growth Analysis.
Background: Understanding the self-rated health of industrially disabled individuals is an important variable that significantly affects their quality of life, satisfaction, and return to work after an industrial accident. Since the health of people with industrial disabilities is affected by variou...
| Publicado en: | Journal of Occupational Rehabilitation Vol. 34; no. 3; pp. 630 - 644 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179358548&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179358548 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10530487 JOR jtl: Journal of Occupational Rehabilitation issn: 10530487 maglogo: N pubinfo: dt: Sep2024 vid: 34 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 179358548 173835435 179358548 179358548 10.1007/s10926-023-10151-1 179358548 ppf: 630 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Trajectories of Self-Rated Health Among Industrially Disabled Individuals: A Latent Class Growth Analysis. aug: au: Lee, Sujin Park, Han Nah Yoon, Ju Young affil: https://ror.org/04h9pn542 College of Nursing, Seoul National University, Seoul, Republic of Korea sug: subj: Accidents, Occupational Adverse Effects Employees with Disabilities South Korea Occupational Health Evaluation Health Status Evaluation Self Assessment Human Funding Source Structural Equation Modeling South Korea Worker's Compensation Logistic Regression Descriptive Statistics Surveys Chi Square Test Data Analysis Software One-Way Analysis of Variance Male Female Adult Middle Age Aged Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Background: Understanding the self-rated health of industrially disabled individuals is an important variable that significantly affects their quality of life, satisfaction, and return to work after an industrial accident. Since the health of people with industrial disabilities is affected by various environments and variables, interventions and policies that are suitable for their characteristics are needed. Objectives: This study aimed to identify changes in self-rated health among industrially disabled individuals, distinguish between different latent classes, and verify predictive factors for each latent class. Methods: Four time-point datasets from the 2018–2021 panel study of Korean workers' compensation insurance were used. Using the latent growth curve model, an overall trajectory of self-rated health of industrially disabled individuals was confirmed, and the number and characteristics of different trajectories were identified using the latent class growth model. Multinomial logistic regression analysis was used to identify the predictive factors for each class. Results: Four classes of self-rated health trajectories were identified: low-decreasing (21.7%), moderate-increasing (15.7%), high-decreasing (56.1%), and low-stable (6.5%) classes. A multinomial logistic regression analysis revealed that significant determinants (age, capacity, type of industrial accident, grade of disability, mental activity, outdoor activity, and social relationships) were different for each latent class. Capacity level affected all potential class classifications. Conclusions: To improve the self-rated health of industrially disabled individuals, it is necessary to develop an appropriate strategy that considers the characteristics of the latent class. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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