The effects of memory, attention, and executive dysfunction on outcomes of depression in a primary care intervention trial: the PROSPECT study
Bibliographic record
Abstract
OBJECTIVE: To describe the influence of domains of cognition on remission and response of depression in an intervention trial among older primary care patients. METHODS: Twenty primary care practices were randomly assigned to Usual Care or to an Intervention consisting of a depression care manager offering algorithm-based care for depression. In all, 599 adults 60 years and older with a depression diagnosis were included in these analyses. Depression severity and remission of depression were assessed by the 24-item Hamilton Depression Rating Scale. The Mini-Mental State Examination (MMSE) was our global measure of cognitive function. Verbal memory was assessed with the memory subscale of the Dementia Rating Scale. Attention was measured with the digit span from the Weschler Adult Intelligence Test. Response inhibition, one of the executive functions, was assessed with the Stroop Color-Word test. RESULTS: The intervention was associated with improved remission and response rates regardless of cognitive impairment. Response inhibition as measured by the Stroop Color-Word test appeared to significantly modify the intervention versus usual care difference in remission and response at 4 months. Patients in the poorest performance quartile at baseline on the Stroop Color-Word test in the Intervention Condition were more likely to achieve remission of depression at 4 months than comparable patients in Usual Care [odds ratio (OR) = 17.76, 95% Confidence Interval (CI), 3.06, 103.1]. CONCLUSIONS: Depressed older adults in primary care with executive dysfunction have low remission and response rates when receiving usual care but benefit from depression care management.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".