Laura M Koehly1, Sato Ashida2, Ellen J Schafer2, Amanda Ludden3. 1. Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland. koehlyl@mail.nih.gov. 2. Department of Community and Behavioral Health, College of Public Health, Aging Mind and Brain Initiative, The University of Iowa. 3. Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.
Abstract
OBJECTIVES: This study demonstrates the added value to caregiving research by using a multi-informant social network approach within the context of Alzheimer's disease and related dementia. METHOD: Sixty-six informants from 24 families enumerated caregiving network members in 2012. Comparisons were made between networks based on a single informant versus multiple informants in terms of network composition and caregiving roles, core-periphery structure, and identification of "missed opportunities" in recruitment. RESULTS: On average, each informant beyond the index enumerated 6.2 new members, resulting in about 10 new members per family network when the multiple-informant approach is used. Compared with index informants' networks, multi-informant networks showed an 85% increase in identification of direct care providers (1.71 compared with 3.42) and a 48% increase in identification of those involved in care decision making (3.33 compared with 4.92). Informants from the same network generally showed agreement in reported participation in caregiving activities. However, the reports of non-participation in these roles were less consistent among the informants. Resulting structure indicated a core caregiving network (M = 6.12 members), with semi-peripheral and peripheral members (M = 5.19 and M = 14.83 members, respectively). DISCUSSION: Results suggest that an iterative, targeted sampling approach with at least three informants allows for a more comprehensive assessment of caregiving processes. Applying this approach in future research will greatly enhance our knowledge and better inform future interventions to facilitate family adaptation. Published by Oxford University Press on behalf of the Gerontological Society of America 2014.
OBJECTIVES: This study demonstrates the added value to caregiving research by using a multi-informant social network approach within the context of Alzheimer's disease and related dementia. METHOD: Sixty-six informants from 24 families enumerated caregiving network members in 2012. Comparisons were made between networks based on a single informant versus multiple informants in terms of network composition and caregiving roles, core-periphery structure, and identification of "missed opportunities" in recruitment. RESULTS: On average, each informant beyond the index enumerated 6.2 new members, resulting in about 10 new members per family network when the multiple-informant approach is used. Compared with index informants' networks, multi-informant networks showed an 85% increase in identification of direct care providers (1.71 compared with 3.42) and a 48% increase in identification of those involved in care decision making (3.33 compared with 4.92). Informants from the same network generally showed agreement in reported participation in caregiving activities. However, the reports of non-participation in these roles were less consistent among the informants. Resulting structure indicated a core caregiving network (M = 6.12 members), with semi-peripheral and peripheral members (M = 5.19 and M = 14.83 members, respectively). DISCUSSION: Results suggest that an iterative, targeted sampling approach with at least three informants allows for a more comprehensive assessment of caregiving processes. Applying this approach in future research will greatly enhance our knowledge and better inform future interventions to facilitate family adaptation. Published by Oxford University Press on behalf of the Gerontological Society of America 2014.
Entities:
Keywords:
Alzheimer’s disease; Caregiving; Dementia; Family structure; Social networks.
Authors: Djin L Tay; Katherine A Ornstein; Huong Meeks; Rebecca L Utz; Ken R Smith; Caroline Stephens; Mia Hashibe; Lee Ellington Journal: J Palliat Med Date: 2021-08-27 Impact factor: 2.947