Impact of Economic Status on Mental Health in Older Age: A Scoping Review
Bibliographic record
Abstract
The World Health Organization has been raising awareness of the importance of mental health at older age and encouraging policy makers to implement preventive means for better aging. The importance of the economic status of the person in maintaining good mental health at older age is yet to be established. We searched the PubMed and Google Scholar databases for peer reviewed published papers relevant to our scoping review. We limited our search only to recent publications including papers published within the last 5 years. The Rayyan website was used to eliminate duplicates and filter the database based on the titles and abstracts of the papers. We only included studies that identified their participants as older adults. Our search of the international database identified 21 different studies that were included in our scoping review. These studies are mostly located within the Asian continent hence, representing a bias to the representativity of this scoping review on the global level. Economic status is an important determinant of good mental health at older age, but it is not the most crucial factor. Other social determinants like cultural, social, and religious factors play a significant role in mental health status in older adults.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".