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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 sur...

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Autores principales: Loke, Seng Cheong, Abdullah, Siti S., Chai, Sen Tyng, Hamid, Tengku A., Yahaya, Nurizan
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3026836/
https://www.ncbi.nlm.nih.gov/pubmed/21283551
http://dx.doi.org/10.1371/journal.pone.0016490
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author Loke, Seng Cheong
Abdullah, Siti S.
Chai, Sen Tyng
Hamid, Tengku A.
Yahaya, Nurizan
author_facet Loke, Seng Cheong
Abdullah, Siti S.
Chai, Sen Tyng
Hamid, Tengku A.
Yahaya, Nurizan
author_sort Loke, Seng Cheong
collection PubMed
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.
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spelling pubmed-30268362011-01-31 Assessment of Factors Influencing Morale in the Elderly Loke, Seng Cheong Abdullah, Siti S. Chai, Sen Tyng Hamid, Tengku A. Yahaya, Nurizan PLoS One Research Article 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 2011-01-25 /pmc/articles/PMC3026836/ /pubmed/21283551 http://dx.doi.org/10.1371/journal.pone.0016490 Text en Loke et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Loke, Seng Cheong
Abdullah, Siti S.
Chai, Sen Tyng
Hamid, Tengku A.
Yahaya, Nurizan
Assessment of Factors Influencing Morale in the Elderly
title 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_short Assessment of Factors Influencing Morale in the Elderly
title_sort assessment of factors influencing morale in the elderly
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3026836/
https://www.ncbi.nlm.nih.gov/pubmed/21283551
http://dx.doi.org/10.1371/journal.pone.0016490
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