MétaCan
Menu
Back to cohort
Record W4402973131 · doi:10.1002/gps.6153

Mild Behavioral Impairment and Quality of Life in Community Dwelling Older Adults

2024· article· en· W4402973131 on OpenAlexafffundabout
Ibadat Warring, Dylan X. Guan, Clive Ballard, Byron Creese, Anne Corbett, Ellie Pickering, Pamela Roach, Eric E. Smith, Zahinoor Ismail

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersCanadian Institutes of Health ResearchKillam TrustsNational Institute for Health and Care ResearchAlzheimer SocietyUniversity of Calgary
KeywordsQuality of life (healthcare)Marital statusAnxietyDementiaGerontologyActivities of daily livingModerationPsychologyClinical psychologyMedicineDiseasePhysical therapyPsychiatryPopulationInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Mild behavioral impairment (MBI) is a dementia risk indicator in older adults characterized by later-life emergent and persistent neuropsychiatric symptoms. Quality of life (QoL) is a multi-dimensional concept encompassing physical, spiritual, and emotional well-being. QoL aims to measure and quantify perceptions of individual health, well-being, standard of living, personal fulfillment, and satisfaction. As MBI symptoms may arise from early-stage neurodegenerative disease, MBI may contribute to declining QoL before dementia onset. In this study, we investigated the relationship between symptoms of MBI and QoL in older adults. METHODS: The sample comprised 1107 individuals aged ≥ 50 years from the Canadian Platform for Research Online to Investigate Health, Quality of Life, Cognition, Behavior, Function, and Caregiving in Aging (CAN-PROTECT). Multivariable linear regressions were used to model the associations between MBI symptom severity (exposure), measured using the MBI Checklist (MBI-C), and QoL (outcome) assessed by the EuroQol-5D (EQ-5D, higher score = poorer QoL) and the novel Quality of Life and Function Five Domain Scale (QFS-5) (QFS-5, lower score = poorer QoL). Covariates were age, sex, cognition, education, ethnocultural origin, marital status, employment status, high blood pressure, heart disease, and diabetes. Moderation analysis explored potential sex differences. A sensitivity analysis was performed removing anxiety/depression items from the EQ-5D score. RESULTS: Across the sample (mean age = 64.4 ± 7.2, 79.4% female) every 1-point increase in MBI-C score was associated with a 0.06-point standard deviation (SD) increase in EQ-5D score (95% confidence interval (CI): 0.05-0.06, p < 0.001) and 0.08 SD decrease in QFS-5 score (95% CI: -0.09 to -0.08, p < 0.001). Neither association depended on sex (p = 0.59 and p = 0.41, respectively). The association remained significant after removing anxiety/depression items from the EQ-5D score (β = 0.04, 95% CI: 0.03- 0.04, p < 0.001). CONCLUSIONS: The study shows that MBI is associated with poorer QoL, independent of sex, on two QoL scales. We addressed depression/anxiety items in the EQ-5D as a potential confounder for the observed MBI-QoL association by conducting a sensitivity analysis that excluded those items from the EQ-5D total score and by employing a novel measure of QoL (QFS-5) that excludes psychiatric symptoms from measurement of QoL. Associations of MBI with the novel QFS-5 were similar to associations between MBI and the EQ-5D. Finding interventions to reduce the burden of MBI symptoms might improve quality of life.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.098
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.385
Teacher spread0.354 · 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

Citations10
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Geriatric PsychiatrySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207