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Record W3195352376 · doi:10.1016/j.jamda.2021.07.018

Feasibility of Routine Quality of Life Measurement for People Living With Dementia in Long-Term Care

2021· article· en· W3195352376 on OpenAlexafffundabout
Matthias Hoben, Sube Banerjee, Anna Beeber, Stephanie Chamberlain, Laura Hughes, Hannah M. O’Rourke, Kelli Stajduhar, Shovana Shrestha, Rashmi Devkota, Jenny Lam, Ian Simons, Emily Dymchuk, Kyle Corbett, Carole A. Estabrooks

Bibliographic record

VenueJournal of the American Medical Directors Association · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of VictoriaUniversity of Alberta
FundersEconomic and Social Research CouncilNational Institute for Health and Care ResearchAlzheimer SocietyUniversity of AlbertaUK Research and Innovation
KeywordsMedicineDementiaQuality of life (healthcare)Long-term careGerontologyTerm (time)Assisted livingAssisted Living FacilityPsychiatryNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: Maximizing quality of life (QoL) is the ultimate goal of long-term dementia care. However, routine QoL measurement is rare in nursing home (NH) and assisted living (AL) facilities. Routine QoL measurement might lead to improvements in resident QoL. Our objective was to assess the feasibility of using DEMQOL-CH, completed by long-term care staff in video calls with researchers, to assess health-related quality of life (HrQoL) of NH and AL residents with dementia or other cognitive impairment. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: We included a convenience sample of 5 NHs and 5 AL facilities in the Canadian province of Alberta. Forty-two care staff who had worked in the facility for ≥3 months completed DEMQOL-CH assessments of 183 residents who had lived in the facility for 3 months or more and were aged ≥65 years. Sixteen residents were assessed independently by 2 care staff to assess inter-rater reliability. METHODS: We assessed HrQoL in people with dementia or other cognitive impairment using DEMQOL-CH, and assessed time to complete, inter-rater reliability, internal consistency reliability, and care staff ratings of feasibility of completing the DEMQOL-CH. RESULTS: Average time to complete DEMQOL-CH was <5 minutes. Staff characteristics were not associated with time to complete or DEMQOL-CH scores. Inter-rater reliability [0.735, 95% confidence interval (CI): 0.712-0.780] and internal consistency reliability (0.834, 95% CI: 0.779-0.864) were high. The DEMQOL-CH score varied across residents (mean = 84.8, standard deviation = 11.20, 95% CI: 83.2-86.4). Care aides and managers rated use of the DEMQOL-CH as highly feasible, acceptable, and valuable. CONCLUSIONS AND IMPLICATIONS: This study provides a proof of concept that DEMQOL-CH can be used to assess HrQoL in NH and AL residents and provides initial indications of feasibility and resources required. DEMQOL-CH may be used to support actions to improve the QoL of residents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.399
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2021
Admission routes3
Has abstractyes

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