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Identification of Stroke Survivors' Perceived Quality of Life: A Latent Profile Analysis Study.

Importance: Identifying quality-of-life (QoL) subgroups can optimize occupational therapy interventions for stroke survivors. Objective: To identify clusters among stroke survivors on the basis of perceived QoL using latent profile analysis (LPA). Design:Cross-sectional study using LPA to classify Q...

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Publicado en:American Journal of Occupational Therapy Vol. 79; no. 6; pp. 1 - 11
Autores principales: Çetin, Binnur, Aran, Orkun Tahir
Formato: research tables/charts Journal Article
Publicado: American Occupational Therapy Association Nov/Dec2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov/Dec2025
      vid: 79
      iid: 6
      pid: 6680
      pub: American Occupational Therapy Association
      place: North Bethesda, Maryland
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        10.5014/ajot.2025.051104
        189032062
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        atl: Identification of Stroke Survivors' Perceived Quality of Life: A Latent Profile Analysis Study.
      aug:
        au:
          Çetin, Binnur
          Aran, Orkun Tahir
        affil: Binnur Çetin, MSc, is Occupational Therapist, Occupational Therapy, Hacettepe Universitesi, Ankara, Türkiye.
      sug:
        subj:
          Stroke Rehabilitation
          Occupational Therapy
          Survivors Psychosocial Factors
          Quality of Life Evaluation
          Human
          Male
          Female
          Middle Age
          Aged
          Cross Sectional Studies
          Academic Medical Centers
          Structural Equation Modeling
          Data Analysis Software
          Post Hoc Analysis
          Inferential Statistics
          One-Way Analysis of Variance
          Multiple Logistic Regression
          Descriptive Statistics
          Questionnaires
          Scales
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Importance: Identifying quality-of-life (QoL) subgroups can optimize occupational therapy interventions for stroke survivors. Objective: To identify clusters among stroke survivors on the basis of perceived QoL using latent profile analysis (LPA). Design:Cross-sectional study using LPA to classify QoL levels among stroke survivors and multinomial logistic regression to identify predictors. Setting: Hospital and university clinic. Participants: A total of 696 adult stroke survivors age 18 yr or older. Eligible participants were literate and had a Mini-Mental State Examination score of 23 or higher, excluding those with speech disorders or additional chronic neurological, psychiatric, or cognitive conditions. Outcomes and Measures: The participants were evaluated with the Stroke Impact Scale (SIS), Barthel Index, and the Impact on Participation and Autonomy Questionnaire (IPA). LPA was applied to the SIS data. Results: Three latent classes were identified: high QoL (n = 232), moderate QoL (n = 322), and low QoL (n = 142). Participants in Class 2 (high QoL) demonstrated higher functional outcomes, whereas those in Class 3 (low QoL) displayed the lowest scores across all scales. Predictors of class membership included age, gender, social relationships, and education level. Conclusions and Relevance: LPA effectively identified subgroups among stroke survivors, supporting tailored interventions in occupational therapy to improve rehabilitation outcomes. Further research is recommended to validate these findings in diverse populations. Plain-Language Summary: This study explored quality of life among stroke survivors. Three groups were identified: those with high, moderate, and low quality of life. Factors such as age, social relationships, and education level influenced quality of life after stroke. These findings can help occupational therapists create personalized care plans to support survivors in recovery, focusing on social connections, autonomy, and daily activities. This study explored quality of life among stroke survivors.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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