Influence of gender and age on cognitive inhibition in late‐onset depression: a case‐control study
Bibliographic record
Abstract
OBJECTIVE: To compare cognitive inhibition performance between people with early-onset (EOD) or late-onset depression (LOD) and controls, and between women and men with LOD. METHODS: On the basis of a case-control design, global executive performance (Frontal Assessment Battery); verbal (Hayling), attention (Stroop), and motor (Go/No-Go) components of cognitive inhibition; mental shifting (Trail Making Test parts A and B); and updating in working memory (Wechsler Adult Intelligence Scale) were assessed in 40 participants (10 depressed women with LOD (i.e., ≥60 years old), 10 depressed women with EOD (i.e., <60 years old), 10 healthy women and 10 depressed men with LOD (i.e., ≥60 years old)). RESULTS: Older depressed women, irrespective of age of depression onset, had greater cognitive inhibition impairments (attention and verbal component) compared with healthy women. LOD was significantly associated with the attention component of cognitive inhibition impairment, unlike EOD (p = 0.026). No executive differences were found regarding age of first-onset depression in older depressed women, and between women and men with LOD. CONCLUSION: Cognitive inhibition impairment, and more specifically its attention component, was the main characteristic of depression in the studied sample of older adults, independently of gender and age of depression onset. It is essential to perform similar studies in both genders in view of future tailor-made therapeutic modalities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".