Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis

Background: Tailoring interventions to the needs of caregivers is an important feature of successful caregiver support programs. To improve cost-effectiveness, group tailoring based on the stage of dementia could be a good alternative. However, existing staging strategies mostly depend on trained pr...

Full description

Saved in:
Bibliographic Details
Main Authors: Yuan, Qi, Tan, Tee Hng, Wang, Peizhi, Devi, Fiona, Ong, Hui Lin, Abdin, Edimansyah, Harish, Magadi, Goveas, Richard, Ng, Li Ling, Chong, Siow Ann, Subramaniam, Mythily
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/145412
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-145412
record_format dspace
spelling sg-ntu-dr.10356-1454122023-03-05T16:43:53Z Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis Yuan, Qi Tan, Tee Hng Wang, Peizhi Devi, Fiona Ong, Hui Lin Abdin, Edimansyah Harish, Magadi Goveas, Richard Ng, Li Ling Chong, Siow Ann Subramaniam, Mythily Lee Kong Chian School of Medicine (LKCMedicine) Science::Medicine Caregiver Dementia Background: Tailoring interventions to the needs of caregivers is an important feature of successful caregiver support programs. To improve cost-effectiveness, group tailoring based on the stage of dementia could be a good alternative. However, existing staging strategies mostly depend on trained professionals. Objective: This study aims to stage dementia based on caregiver reported symptoms of persons with dementia. Methods: Latent class analysis was used. The classes derived were then mapped with disease duration to define the stages. Logistic regression with receiver operating characteristic curve was used to generate the optimal cut-offs. Results: Latent class analysis suggested a 4-class solution, these four classes were named as early (25.9%), mild (25.2%), moderate (16.7%) and severe stage (32.3%). The stages based on the cut-offs generated achieved an overall accuracy of 90.8% compared to stages derived from latent class analysis. Conclusion: The current study confirmed that caregiver reported patient symptoms could be used to classify persons with dementia into different stages. The new staging strategy is a good complement of existing dementia clinical assessment tools in terms of better supporting informal caregivers. Ministry of Health (MOH) National Medical Research Council (NMRC) Published version The study is funded by the Singapore Ministry of Health’s National Medical Research Council under the Center Grant Programme (Grant No.: NMRC/CG/004/2013) and the Institute of Mental Health Bridging Fund (CRCref No.: 545-2016). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. 2020-12-21T05:46:37Z 2020-12-21T05:46:37Z 2020 Journal Article Yuan, Q., Tan, T. H., Wang, P., Devi, F., Ong, H. L., Abdin, E., . . . Subramaniam, M. (2020). Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis. PLOS ONE, 15(1), e0227857-. doi:10.1371/journal.pone.0227857 1932-6203 https://hdl.handle.net/10356/145412 10.1371/journal.pone.0227857 31940419 1 15 en NMRC/CG/004/2013 545-2016 PLOS ONE © 2020 Yuan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Medicine
Caregiver
Dementia
spellingShingle Science::Medicine
Caregiver
Dementia
Yuan, Qi
Tan, Tee Hng
Wang, Peizhi
Devi, Fiona
Ong, Hui Lin
Abdin, Edimansyah
Harish, Magadi
Goveas, Richard
Ng, Li Ling
Chong, Siow Ann
Subramaniam, Mythily
Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
description Background: Tailoring interventions to the needs of caregivers is an important feature of successful caregiver support programs. To improve cost-effectiveness, group tailoring based on the stage of dementia could be a good alternative. However, existing staging strategies mostly depend on trained professionals. Objective: This study aims to stage dementia based on caregiver reported symptoms of persons with dementia. Methods: Latent class analysis was used. The classes derived were then mapped with disease duration to define the stages. Logistic regression with receiver operating characteristic curve was used to generate the optimal cut-offs. Results: Latent class analysis suggested a 4-class solution, these four classes were named as early (25.9%), mild (25.2%), moderate (16.7%) and severe stage (32.3%). The stages based on the cut-offs generated achieved an overall accuracy of 90.8% compared to stages derived from latent class analysis. Conclusion: The current study confirmed that caregiver reported patient symptoms could be used to classify persons with dementia into different stages. The new staging strategy is a good complement of existing dementia clinical assessment tools in terms of better supporting informal caregivers.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Yuan, Qi
Tan, Tee Hng
Wang, Peizhi
Devi, Fiona
Ong, Hui Lin
Abdin, Edimansyah
Harish, Magadi
Goveas, Richard
Ng, Li Ling
Chong, Siow Ann
Subramaniam, Mythily
format Article
author Yuan, Qi
Tan, Tee Hng
Wang, Peizhi
Devi, Fiona
Ong, Hui Lin
Abdin, Edimansyah
Harish, Magadi
Goveas, Richard
Ng, Li Ling
Chong, Siow Ann
Subramaniam, Mythily
author_sort Yuan, Qi
title Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
title_short Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
title_full Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
title_fullStr Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
title_full_unstemmed Staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
title_sort staging dementia based on caregiver reported patient symptoms : implications from a latent class analysis
publishDate 2020
url https://hdl.handle.net/10356/145412
_version_ 1759857195946606592