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ORIGINAL ARTICLE
Year : 2018  |  Volume : 7  |  Issue : 1  |  Page : 61

Quality of life predictors in physically disabled people


1 Department of Health Education and Promotion, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
2 Department of Biostatistics, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
3 Department of Occupational Health, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
4 Students Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
5 Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran

Correspondence Address:
Mr. Seyed Younes Hosseini
MSc in Occupational Health Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jehp.jehp_115_17

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Background: Physically disabled people experience more restrictions in social activities than healthy people, which are associated with lower level of well-being and poor quality of life (QoL). Study Design: A cross-sectional study was conducted Methods: This study was investigated on among 302 eligible physically disabled people. The predictive role of the demographics and clinical characteristics, anxiety and depression, physical activity, and self-efficacy on the 36-Item Short Form Health Survey (SF-36) was examined. Statistical Analysis Used: Statistical analysis used univariate and multivariate regression models. Results: Gender, self-reported physical activity levels, use of the disability aid tools, and depression were significantly predictors of the physical component summary (PCS) (R2 = 0.20, P < 0.001). We realized that anxiety, depression, and self-efficacy could significantly predict the mental component summary (MCS) (R2 = 0.43, P < 0.001). Conclusions: Study results revealed that four and three variables could predict 20% and 43% of PCS and MCS variations, respectively. These findings warranted the detection of QoL risk factors and establishment of targeted interventions to optimize the health-related QoL among physically disabled people.


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