Cognitive Changes in Older Adults Following a Stepped Care Intervention for Late-life Depression
Bibliographic record
Abstract
Abstract Older adults with depression may manifest cognitive decline and treating depression may maintain or improve cognition. However, cognitive outcomes could be overlooked in non-pharmacological interventions for depression. This analysis investigated cognitive changes in a stepped-care intervention (Clinical Trial ID: NCT03593889) and the potential association with individual depressive symptom change. The community-dwelling older adults at risk of or with depressive symptoms without significant cognitive impairment (n=802) were assigned to intervention group (n=644) and control group (n=138). Depressive symptoms and cognitive functions were measured using Patient Health Questionnaire-9 and Cognitive Montreal Assessment-5 minutes protocol, respectively. Paired-t-Test showed significant improvements in overall cognition and attention in both intervention and control groups, but the improvements of language fluency (Intervention: MD=-0.51 p<0.01; control: MD=0.14, p=0.500) and orientation (Intervention: MD=-0.22 p<0.05; control: MD=-0.11, p=0.229) only displayed in intervention group. As control group had better cognition at baseline, linear mixed-effects model analysis was used to compare between-group difference. Intervention group had no significant cognitive improvement after adjusting the covariates but a potential improvement in language fluency (Coef. =0.442, SE=0.247, p=0.074). A linear regression analysis in intervention group indicated that reduction of concentration problem (β=0.106, p<0.05) and retardedness (β=0.117, p<0.01) under the symptomatology of depression were associated with the improvement of language fluency. In this group of older persons without significant cognitive impairment, there is no clear evidence of global cognitive benefits in a stepped care depression intervention, although there may be improvements in certain cognitive domains, which may be related to improvements in cognitive aspects of depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".