BACKGROUND: With the increase in the number of older adults with dementia, research efforts have focused on increasing community-based support service (CBSS) use to improve older adult and caregiver outcomes. However, the research on factors that may explain CBSS use has been focused on individual characteristics, and how the care recipient and caregiver as a pair influence CBSS use has not been accounted for. OBJECTIVE: To classify care recipients with dementia and their caregivers who shared similar patterns of CBSS use and to identify predictors of class membership. METHODS: Participants were 1,813 elders with dementia and their caregivers from the National Longitudinal Caregiver Study, a cross-sectional dataset from 1998. A latent class analysis was used to identify classes of CBSS users by examining use of caregiver support group, home aide, home health, adult day care, and respite care. Multinomial logistic regression analysis was used to examine relationships between predisposing, enabling, and need variables and class membership. RESULTS: Three classes, that is, Low Users, Adult Day Users, and Home-Based Users, comprised 80%, 10%, and 10% of the sample, respectively. Adult Day Users reported significantly more enabling resources and greater service need. Predictors of home-based use included care recipient age, activities of daily living limitations, number of skilled nursing facilities in the local county, and the extent of caregiver physical limitations from comorbid conditions. DISCUSSION: Using latent class analysis allows identification of specific subtypes of CBSS users, prevalence of user subtype, and risk factors for underutilization. Determining the long-term outcomes of class membership may identify specific groups at risk, which could inform the design of interventions to improve assessment for and delivery of CBSS.
BACKGROUND: With the increase in the number of older adults with dementia, research efforts have focused on increasing community-based support service (CBSS) use to improve older adult and caregiver outcomes. However, the research on factors that may explain CBSS use has been focused on individual characteristics, and how the care recipient and caregiver as a pair influence CBSS use has not been accounted for. OBJECTIVE: To classify care recipients with dementia and their caregivers who shared similar patterns of CBSS use and to identify predictors of class membership. METHODS:Participants were 1,813 elders with dementia and their caregivers from the National Longitudinal Caregiver Study, a cross-sectional dataset from 1998. A latent class analysis was used to identify classes of CBSS users by examining use of caregiver support group, home aide, home health, adult day care, and respite care. Multinomial logistic regression analysis was used to examine relationships between predisposing, enabling, and need variables and class membership. RESULTS: Three classes, that is, Low Users, Adult Day Users, and Home-Based Users, comprised 80%, 10%, and 10% of the sample, respectively. Adult Day Users reported significantly more enabling resources and greater service need. Predictors of home-based use included care recipient age, activities of daily living limitations, number of skilled nursing facilities in the local county, and the extent of caregiver physical limitations from comorbid conditions. DISCUSSION: Using latent class analysis allows identification of specific subtypes of CBSS users, prevalence of user subtype, and risk factors for underutilization. Determining the long-term outcomes of class membership may identify specific groups at risk, which could inform the design of interventions to improve assessment for and delivery of CBSS.
Authors: Janis E Campbell; Keith Kleszynski; Amanda E Janitz; Amber S Anderson; Claire Dowers-Nichols; Andrew N Dentino; Laurence Z Rubenstein; Thomas A Teasdale Journal: J Okla State Med Assoc Date: 2018-11
Authors: Henrik Wiegelmann; Karin Wolf-Ostermann; Werner Brannath; Farhad Arzideh; Jan Dreyer; Rene Thyrian; Liane Schirra-Weirich; Lisa Verhaert Journal: BMC Health Serv Res Date: 2021-07-23 Impact factor: 2.655
Authors: Ranak B Trivedi; Brian J Ayotte; Carolyn T Thorpe; David Edelman; Hayden B Bosworth Journal: Patient Prefer Adherence Date: 2010-07-21 Impact factor: 2.711