Dementia and Depression in Older Adults: A Southeast European Perspective: Summary of a Dementia Psychogeriatric Symposium held in Ohrid, Macedonia, 23 May 2013
Bibliographic record
Abstract
We present a report on the recent symposium on dementia and depression in older adults, held in Ohrid, Macedonia and discuss the urgent need for development of psychogeriatric and affiliated services in the Southeast European region. The limited epidemiological data from nine countries in this region suggest high variability of prevalence rates for mental health problems in older adults (>65 years of age). At the moment, there are over 520,000 older adults in the region living with dementia alone. The prevalence rates for dementia (%) are either similar to those of the developed countries (9-9.6% in build-up northern Greece and Albania, respectively) or substantially lower (3.6-4% in rural northern Greece and Montenegro, respectively). The latter may be due to either cultural diversity or lack of adequate medical health service provision and expertise to recognize and diagnose dementia. Indeed, there is a lack of organized specialized services for older adults with mental health problem in the region. The symposium raised the awareness of this problem in the region and called for networking between isolated individuals working in this field to improve the current situation and facilitate further development of adequate clinical services to meet the growing needs of the older adults in the countries of the Southeast Europe.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".