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Record W1937904763 · doi:10.5770/cgj.18.134

Psychosocial Risk Factors for Cognitive Decline in Late-Life Depression: Findings from the MTLD-III Study

2015· article· en· W1937904763 on OpenAlexafffundvenue
Soham Rej, Amy Begley, Ariel Gildengers, Mary Amanda Dew, Charles F. Reynolds, Meryl A. Butters

Bibliographic record

VenueCanadian Geriatrics Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchNational Institute of Mental HealthEisaiNational Institutes of HealthPfizerNational Institute on AgingEli Lilly and Company
KeywordsPsychosocialMedicineLate life depressionCognitive declineMarital statusDepression (economics)Socioeconomic statusDementiaGerontologyCognitionPsychiatryClinical psychologyPopulationInternal medicineDiseaseEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive impairment and depression frequently co-occur in late life. There remains a need to better characterize psychosocial risk factors of cognitive decline in older adults with depression. We hypothesized that certain psychosocial factors would be associated with higher risk of cognitive decline in individuals with late-life depression. METHODS: 130 individuals aged ≥ 65 years who had achieved remission from a major depressive episode were randomized to donepezil or placebo and then closely followed for two years. Using Cox proportional hazard models, we examined the association between baseline median household income, education level, race, marital status, and social support and cognitive decline over the follow-up. RESULTS: Lower interpersonal support (OR = 0.86 [0.74-0.99], p = .04) and lower baseline global neuropsychological score (OR = 0.56 [0.36-0.87], p = .001) predicted shorter time to conversion to MCI or dementia in univariate models. These exposures did not remain significant in multivariate analyses. Neither socioeconomic status nor other psychosocial factors independently predicted cognitive diagnostic conversion (p > .05). CONCLUSIONS: We did not find reliable associations between cognitive outcome and any of the psychosocial factors examined. Future large-scale, epidemiological studies, ideally using well-validated subjective measures, should better characterize psychosocial risk factors for cognitive decline in late-life depression.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.341
Teacher spread0.297 · 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 teacher head, 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

Citations15
Published2015
Admission routes3
Has abstractyes

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