Everyday functioning in treatment-resistant late-life depression: The mediating role of cognition
Bibliographic record
Abstract
OBJECTIVE: Everyday functional capacity in older adults is influenced by several factors, with prior studies finding that cognition mediates the relationship between depression and everyday functioning. However, these studies utilized samples with low depression severity and used only one type of functional assessment. We aimed to examine whether cognition mediates the relationship between depression and functioning in older adults with a history of treatment-resistant depression. METHOD: Data from 383 participants enrolled in the OPTIMUM Neuro study were analyzed. Participants completed a neuropsychological assessment battery, depression severity interview, self-/informant-rated functioning measures and a performance-based functioning measure. Linear regression was used to determine whether depression scores predicted cognitive domain and everyday functioning scores. Cognitive domain scores predicted by depression were then tested as mediators between depression and functioning. RESULTS: Higher depression symptoms predicted poorer performance on all measures of functioning as well as the cognitive domains of attention, executive functioning, and immediate memory. Immediate memory partially mediated the relationship between depression and a performance-based measure of functioning, while attention and executive functioning partially mediated the relationship between a self-report measure of functioning and depression. CONCLUSIONS: The relationship between depression severity and poorer functional performance was partially mediated by attention, executive functioning, and immediate memory, with results differing based on the measure of functioning used. Our findings suggest that there may be additional non-cognitive factors influencing this relationship and highlight the importance of using multiple methods to assess functional performance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".