Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12202/5279
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dc.contributor.advisorHoltzer, Roee-
dc.contributor.authorBelser-Ehrlich, Janna-
dc.date.accessioned2020-03-30T22:41:18Z-
dc.date.available2020-03-30T22:41:18Z-
dc.date.issued2017-
dc.identifier.citationSource: Dissertations Abstracts International, Volume: 80-01, Section: B.;Publisher info.: Dissertation/Thesis.;Advisors: Holtzer, Roee.en_US
dc.identifier.isbn978-0-438-19115-0-
dc.identifier.urihttps://hdl.handle.net/20.500.12202/5279-
dc.identifier.urihttps://ezproxy.yu.edu/login?url=http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10907700en_US
dc.description.abstractHealth Related Quality of Life and Cognitive Functioning in Older Adults Health-related quality of life (HRQoL) is a multidimensional concept that examines aspects of health contributing to quality of life (QoL). A theoretical framework was proposed by Wilson & Cleary (1995) to describe specific relationships among the factors important in conceptualizing HRQoL. Despite its acceptance in the literature, whether this model of HRQoL is conceptually and statistically sound in an aging population has not yet been explored. Furthermore, the relationship between cognitive functioning and HRQoL is not well understood within the context of the model. The current study aimed to establish good model fit for the Wilson & Cleary Model and explore the contribution of cognitive functioning in a sample of non-demented older adults. Participants were community-dwelling older adults (N = 444, age range = 65-95, female = 58%) who completed measures used to represent factors of the HRQoL model. Factors of the HRQoL model included biological functioning, symptom status.. functional status, general health perceptions. overall quality of life and individual and environmental characteristics. Structural equation modeling was the primary statistical method utilized. Results indicated that although the measurement variables chosen represented HRQoL factors, the overall model fit was poor for both physical HRQoL X2(140)= 565.38, p<0.001; CFI= 0.867: RF1= 0.793: GF1= 0.870; RMSEA= 0.081 and mental HRQoL X2(140)= 543.78. p<0.001: CFI= 0.867:; RFI= 0.793: GFI= 0.867: RMSEA= 0.081. Incorporating cognitive functioning into the model also yielded poor model tit for both physical X 2(158)= 701.84. p<0.001: CFI= 0.839: RFI= 0.764: GFI= 0.853; RMSEA= 0.088 and mental HRQoL X2(158)= 678.80. p<0.001: CFI= 0.836: RFI= 0.757: GFI= 0.852: RMSEA= 0.086. Modifications that were statistically and theoretically justified did not improve model fit. Thus, the assumption of the model that the measured variables represented only one factor of HRQoL. as well the linear progression of factors is not supported in a sample of community-dwelling older adults. This is likely due to the associations among aspects of physical, psychological, social. and functional abilities in the aging population.en_US
dc.language.isoen_USen_US
dc.publisherProQuest Dissertations & Theses Globalen_US
dc.subjectGerontologyen_US
dc.subjectAgingen_US
dc.subjectPsychologyen_US
dc.titleHealth Related Quality of Life and Cognitive Functioning in Older Adultsen_US
dc.typeDissertationen_US
dc.typeThesisen_US
Appears in Collections:Ferkauf Graduate School of Psychology: Doctoral Dissertations

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