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The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis

The purposes of this study were to identify the patterns of caregiving activities among family caregivers in Hong Kong and to examine their associations with characteristic factors and caregiver burden. The data was from the cross-sectional survey on the profiles of family caregivers of older adults...

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Autores principales: Huang, Jing, Chau, Pui Hing, Choi, Edmond Pui Hang, Wu, Bei, Lou, Vivian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7740121/
http://dx.doi.org/10.1093/geroni/igaa057.1141
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author Huang, Jing
Chau, Pui Hing
Choi, Edmond Pui Hang
Wu, Bei
Lou, Vivian
author_facet Huang, Jing
Chau, Pui Hing
Choi, Edmond Pui Hang
Wu, Bei
Lou, Vivian
author_sort Huang, Jing
collection PubMed
description The purposes of this study were to identify the patterns of caregiving activities among family caregivers in Hong Kong and to examine their associations with characteristic factors and caregiver burden. The data was from the cross-sectional survey on the profiles of family caregivers of older adults in Hong Kong. 932 family caregivers were classified into different classes by using the Latent class analysis (LCA) according to their engagements in the 17 daily caregiving activities: 6 activities of daily living (ADLs), 8 instrumental activities of daily living activities (IADLs), emotional support, decision-making, and financial support. Five classes were revealed and labeled “Total All-round Caregiving” (Class I: 19.5%), “Partial All-round Caregiving” (Class II: 8.2%), “ADLs Free Caregiving” (Class III: 23.8%), “ADLs & Partial IADLs Free Caregiving” (Class IV: 32.5%), “Financial Caregiving” (Class V: 16.0%), respectively. Results from multinomial logistic regression found that the following factors were associated with the class membership: care recipients’ age, medical diagnoses, and caregivers’ gender, job status, marital status, self-rated economic status, living with care recipients, and caring for ≥40 hours per week. Findings from multiple linear regression showed caregivers with different patterns of caregiving activities reported different levels of caregiver burden. Caregivers in Class I have been found with the highest caregiver burden. This is the first study that has applied LCA to capture the patterns of caregiving activities among family caregivers. Identification of caregiving activity patterns and examination of their characteristics and caregiver burden can help healthcare providers to shift to prioritized and targeted caregiver support.
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spelling pubmed-77401212020-12-21 The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis Huang, Jing Chau, Pui Hing Choi, Edmond Pui Hang Wu, Bei Lou, Vivian Innov Aging Abstracts The purposes of this study were to identify the patterns of caregiving activities among family caregivers in Hong Kong and to examine their associations with characteristic factors and caregiver burden. The data was from the cross-sectional survey on the profiles of family caregivers of older adults in Hong Kong. 932 family caregivers were classified into different classes by using the Latent class analysis (LCA) according to their engagements in the 17 daily caregiving activities: 6 activities of daily living (ADLs), 8 instrumental activities of daily living activities (IADLs), emotional support, decision-making, and financial support. Five classes were revealed and labeled “Total All-round Caregiving” (Class I: 19.5%), “Partial All-round Caregiving” (Class II: 8.2%), “ADLs Free Caregiving” (Class III: 23.8%), “ADLs & Partial IADLs Free Caregiving” (Class IV: 32.5%), “Financial Caregiving” (Class V: 16.0%), respectively. Results from multinomial logistic regression found that the following factors were associated with the class membership: care recipients’ age, medical diagnoses, and caregivers’ gender, job status, marital status, self-rated economic status, living with care recipients, and caring for ≥40 hours per week. Findings from multiple linear regression showed caregivers with different patterns of caregiving activities reported different levels of caregiver burden. Caregivers in Class I have been found with the highest caregiver burden. This is the first study that has applied LCA to capture the patterns of caregiving activities among family caregivers. Identification of caregiving activity patterns and examination of their characteristics and caregiver burden can help healthcare providers to shift to prioritized and targeted caregiver support. Oxford University Press 2020-12-16 /pmc/articles/PMC7740121/ http://dx.doi.org/10.1093/geroni/igaa057.1141 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Huang, Jing
Chau, Pui Hing
Choi, Edmond Pui Hang
Wu, Bei
Lou, Vivian
The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title_full The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title_fullStr The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title_full_unstemmed The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title_short The Patterns of Caregiving Activities for Family Caregivers of Older Adults: A Latent Class Analysis
title_sort patterns of caregiving activities for family caregivers of older adults: a latent class analysis
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7740121/
http://dx.doi.org/10.1093/geroni/igaa057.1141
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