Access to mental health services in urban areas: examine the availability, affordability, and accessibility of mental health services in urban settings, particularly for individuals with intersecting marginalized identities
Bibliographic record
Abstract
PURPOSE OF REVIEW: To offer an integrative overview of mental health services in urban areas across different social groups and underscore the challenges and potential solutions to improve access to mental health services in urban areas. RECENT FINDINGS: The process of urbanization places a lot of toll on the current mental health services system. Challenges to both mental health and mental health services include the elevated risk of some mental and behavioral health issues, the increased demand for mental health services, and the intensification of mental health inequalities. The phenomenon of mental health inequalities is exacerbated in urban areas, with certain disadvantaged population groups more likely to report higher mental health issues and difficulties in accessing mental health services. Targeted and dedicated strategies are warranted to develop and allocate resources to address the mental health services needs among those simultaneously with multiple disadvantaged social and economic characteristics. SUMMARY: Urbanization places a substantive burden on both mental health and mental health services and creates challenges to mental health services access. Integrative and multisectoral initiatives could shed light on effectively addressing the issues of access to mental health services in urban cities.
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.
How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".