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Assessment of factors influencing morale in the elderly

Background: We examined the relationship between morale measured by the Philadelphia Geriatric Morale Scale (PGC) and disability, social support, religiosity, and personality traits. Instruments predicting morale were then tested against PGC domains. Methods: The study utilized a cross-sectional su...

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Main Authors: Loke, Seng Cheong, Abdullah, Siti Suhailah, Chai, Sen Tyng, Tengku Abdul Hamid, Tengku Aizan, Yahaya, Nurizan
Format: Article
Language:English
Published: Public Library of Science 2011
Online Access:http://psasir.upm.edu.my/id/eprint/22584/1/22584.PDF
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spelling oai:psasir.upm.edu.my:22584 http://psasir.upm.edu.my/id/eprint/22584/ Assessment of factors influencing morale in the elderly Loke, Seng Cheong Abdullah, Siti Suhailah Chai, Sen Tyng Tengku Abdul Hamid, Tengku Aizan Yahaya, Nurizan Background: We examined the relationship between morale measured by the Philadelphia Geriatric Morale Scale (PGC) and disability, social support, religiosity, and personality traits. Instruments predicting morale were then tested against PGC domains. Methods: The study utilized a cross-sectional survey with a multistage cluster sampling design. Instruments used were disability (disease burden; WHO Disability Score-II, WHODAS-II), social support (Duke Social Support Scale, DUSOCS; Lubben Social Network Scale, LSNS-6; Medical Outcomes Study Social Support Survey, MOS-SSS), religiosity (Revised Intrinsic-Extrinsic Religious Orientation Scale, I/E-R), and personality (Ten-Item Personality Inventory, TIPI). These were plotted as bar charts against PGC, resolved with one-way ANOVA and Kruskal-Wallis tests, then corrected for multiple comparisons. This process was repeated with PGC domains. Contribution of factors was modeled using population attributable risk (PAR) and odds ratios. Effect of confounders such as gender, age, and ethnicity were checked using binary logistic regression. Results: All instruments showed clear relationships with PGC, with WHODAS-II and DUSOCS performing well (ANOVA p<0.001). For PGC domains, attitude toward aging and lonely dissatisfaction trended together, while agitation did not. PAR, odds ratios, and Exp(β) were disability (WHODAS-II: 28.5%, 3.8, 2.8), social support (DUSOCS: 28.0%, 3.4, 2.2), religiosity (I/E-R: 21.6%, 3.2, 2.1), and personality (TIPI: 27.9%, 3.6, 2.4). Combined PAR was 70.9%. Conclusions: Disability, social support, religiosity, and personality strongly influence morale in the elderly. WHODAS-II and DUSOCS perform best in measuring disability and social support respectively. Public Library of Science 2011 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/22584/1/22584.PDF Loke, Seng Cheong and Abdullah, Siti Suhailah and Chai, Sen Tyng and Tengku Abdul Hamid, Tengku Aizan and Yahaya, Nurizan (2011) Assessment of factors influencing morale in the elderly. PLOS ONE, 6 (1). art. no. e16490. pp. 1-8. ISSN 1932-6203 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0016490 10.1371/journal.pone.0016490
institution UPM IR
collection UPM IR
language English
description Background: We examined the relationship between morale measured by the Philadelphia Geriatric Morale Scale (PGC) and disability, social support, religiosity, and personality traits. Instruments predicting morale were then tested against PGC domains. Methods: The study utilized a cross-sectional survey with a multistage cluster sampling design. Instruments used were disability (disease burden; WHO Disability Score-II, WHODAS-II), social support (Duke Social Support Scale, DUSOCS; Lubben Social Network Scale, LSNS-6; Medical Outcomes Study Social Support Survey, MOS-SSS), religiosity (Revised Intrinsic-Extrinsic Religious Orientation Scale, I/E-R), and personality (Ten-Item Personality Inventory, TIPI). These were plotted as bar charts against PGC, resolved with one-way ANOVA and Kruskal-Wallis tests, then corrected for multiple comparisons. This process was repeated with PGC domains. Contribution of factors was modeled using population attributable risk (PAR) and odds ratios. Effect of confounders such as gender, age, and ethnicity were checked using binary logistic regression. Results: All instruments showed clear relationships with PGC, with WHODAS-II and DUSOCS performing well (ANOVA p<0.001). For PGC domains, attitude toward aging and lonely dissatisfaction trended together, while agitation did not. PAR, odds ratios, and Exp(β) were disability (WHODAS-II: 28.5%, 3.8, 2.8), social support (DUSOCS: 28.0%, 3.4, 2.2), religiosity (I/E-R: 21.6%, 3.2, 2.1), and personality (TIPI: 27.9%, 3.6, 2.4). Combined PAR was 70.9%. Conclusions: Disability, social support, religiosity, and personality strongly influence morale in the elderly. WHODAS-II and DUSOCS perform best in measuring disability and social support respectively.
format Article
author Loke, Seng Cheong
Abdullah, Siti Suhailah
Chai, Sen Tyng
Tengku Abdul Hamid, Tengku Aizan
Yahaya, Nurizan
spellingShingle Loke, Seng Cheong
Abdullah, Siti Suhailah
Chai, Sen Tyng
Tengku Abdul Hamid, Tengku Aizan
Yahaya, Nurizan
Assessment of factors influencing morale in the elderly
author_facet Loke, Seng Cheong
Abdullah, Siti Suhailah
Chai, Sen Tyng
Tengku Abdul Hamid, Tengku Aizan
Yahaya, Nurizan
author_sort Loke, Seng Cheong
title Assessment of factors influencing morale in the elderly
title_short Assessment of factors influencing morale in the elderly
title_full Assessment of factors influencing morale in the elderly
title_fullStr Assessment of factors influencing morale in the elderly
title_full_unstemmed Assessment of factors influencing morale in the elderly
title_sort assessment of factors influencing morale in the elderly
publisher Public Library of Science
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/22584/1/22584.PDF
_version_ 1782719802408697856
score 12.933938

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