Depressive symptoms in the entire spectrum of cognitive ageing in Greece: evidence from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD)
Bibliographic record
Abstract
OBJECTIVES: To study (i) the prevalence of mild and moderate-to-severe depressive symptoms in the entire spectrum of cognitive ageing in Greece and (ii) the relationship between these symptoms and demographic and clinical data. METHODS: The study was based on the randomly selected cohort of the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). Depressive symptoms were assessed with the 15-item version of the Geriatric Depression Scale. Participants also received a comprehensive neuropsychological assessment, while the clinical diagnoses of dementia and mild cognitive impairment were established according to international diagnostic criteria. Statistical analyses relied on comparison tests and a logistic (proportional odds) ordinal regression model. RESULTS: Depressive symptoms were detected in 19.5% of the 1936 study participants, while 11.3% of both people with MCI and dementia had moderate-to-severe depressive symptoms. The regression model revealed that older adults with more severe depressive symptoms were more likely female, cognitively impaired, less educated, were treated with psychotropic medication and lived in Attica versus Thessaly. CONCLUSIONS: Since depressive symptoms were detected in almost one in five older adults, healthcare professionals in Greece should safeguard the timely detection and effective treatment of such symptoms and the post-diagnostic care of older adults with 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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".