Prevalence and correlates of depressive symptoms in older people in the West Bank, Palestine: cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Depressive disorders in elderly people can affect their cognitive and physical abilities and nutritional status. AIMS: This study aimed to determine the prevalence of depressive disorders in older Palestinians and its relationship with nutritional, functional and cognitive status. METHODS: A cross-sectional study was conducted among Palestinians > 60 years living in Hebron, West Bank from September 2017 to March 2018. An interview-based questionnaire was used to obtain information on sociodemographic characteristics, nutritional habits, anthropometric measurements, cognitive function (using the Montreal cognitive assessment tool), and functional status (using activities of daily living and instrumental activities of daily living scales). The presence of depressive symptoms was determined using the geriatric depression scale: a score ≥ 5 indicated depressive symptoms. RESULTS: A total of 291 participants were included in the study. Mean age was 70.4 (SD 7.0) years, range 60-100. The prevalence of depressive symptoms was 51.9%. Depression was significantly associated with marital status (being single), low educational and income level, unemployment, and inability to write and make calculations. The presence of depressive disorders was also significantly associated with lower scores on the instrumental activities of daily living scale and the Montreal cognitive assessment tool, and with hypercholesterolaemia, chewing and swallowing difficulties and lack of appetite. CONCLUSION: A considerable percentage of older Palestinian adults had depressive symptoms. There is a need to screen and treat depressive symptoms among older Palestinian adults to prevent their progression to severe mental health problems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".