Development of a Longitudinal Dataset of Persons With Dementia and Their Caregivers Through End-of-Life: A Statistical Analysis System Algorithm for Joining National Health and Aging Trends Study/National Study of Caregiving.

Background: Alzheimer's disease and related dementias (AD/ADRD) are terminal conditions impacting families and caregivers, particularly at end-of-life. Longitudinal, secondary data analyses present opportunities for insight into dementia caregiving and decision-making over time; however, joining com...

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Publicado en:American Journal of Hospice & Palliative Medicine Vol. 39; no. 9; pp. 1052 - 1061
Autores principales: Sullivan, Suzanne S., Li, Chin-Shang, de Rosa, Cristina, Chang, Yu-Ping
Formato: research tables/charts Journal Article
Publicado: Sage Publications Inc. Sep2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2022
      vid: 39
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        10.1177/10499091211057291
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        atl: Development of a Longitudinal Dataset of Persons With Dementia and Their Caregivers Through End-of-Life: A Statistical Analysis System Algorithm for Joining National Health and Aging Trends Study/National Study of Caregiving.
      aug:
        au:
          Sullivan, Suzanne S.
          Li, Chin-Shang
          de Rosa, Cristina
          Chang, Yu-Ping
        affil: School of Nursinsg, 12292 University at Buffalo - South Campus, Buffalo, NY, USA
      sug:
        subj:
          Dementia Patients Psychosocial Factors
          Caregivers Psychosocial Factors
          Needs Assessment
          Attitude to Death
          Coding
          Algorithms
          Research Personnel
          Human
          Alzheimer's Disease
          Dementia
          Advance Care Planning
          Prospective Studies
          Aged
          Aged, 80 and Over
          Descriptive Statistics
          Interviews
          Male
          Female
          Funding Source
          Patient Attitudes
          Caregiver Attitudes
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: Background: Alzheimer's disease and related dementias (AD/ADRD) are terminal conditions impacting families and caregivers, particularly at end-of-life. Longitudinal, secondary data analyses present opportunities for insight into dementia caregiving and decision-making over time; however, joining complex datasets and preparing them for analysis poses many challenges. Objectives: To describe an approach to linking national survey data of older adults with their primary caregivers to build a prospective, longitudinal dataset, and to share the Statistical Analysis System (SAS) coding statement algorithms with other researchers. Methods: The National Health and Aging Trends Study (NHATS) and National Study of Caregiving (NSOC) are joined using a series of algorithms based on conceptual and operational definitions of dementia, primary caregivers, and the occurrence of death. A series of SAS algorithms resulting in the final longitudinal dataset was created. Results: NHATS/NSOC participants were linked using three preliminary data files (n = 12 427) and one final data join (n = 3305) over nine rounds of data collection. Presence of dementia was defined based on the indicator in the year preceding the last month-of-life (LML) interview. Primary caregivers were defined as the person providing the most frequent care over time. Additional flag variables (LML interview, dementia classification, and cohort (2011 vs 2015)) were created. The SAS algorithms are presented herein. Discussion: The SAS coding statement algorithms provide an opportunity to conduct longitudinal analysis of care for both members of the dyad in the context of dementia and end-of-life. Future research using the proposed dataset can further explore care and caregiving in these populations.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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