Depression in the Iranian Elderly: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Depression can lead to increased medical costs, impaired individual and social functioning, nonadherence to therapeutic proceeding, and even suicide and ultimately affect quality of life. It is important to know the extent of its prevalence for successful planning in this regard. This study was conducted to determine the prevalence of depression in the Iranian elderly. This systematic review and meta-analysis study was done through Medline via PubMed, SCOPUS, Web of Science, ProQuest, SID, Embase, and Magiran with determined keywords. Screening was done on the basis of relevance to the purpose of the study, titles, abstracts, full text, and inclusion and exclusion criteria. The quality of the articles was assessed using the Newcastle-Ottawa standard scale. After primary and secondary screening, 30 articles were finally included in the study. According to the 30 articles reviewed, the prevalence of depression in the Iranian elderly was 52 percent based on the random-effects model (CI 95%: 46-58). According to the results of the present study, depression in the Iranian elderly was moderate to high. Therefore, more exact assessment in terms of depression screening in elderly people seems necessary. Coherent and systematic programs, including psychosocial empowerment counselling for the elderly and workshops for their families, are also needed. Researchers can also use the results of this study for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it