Bibliographic record
Abstract
Background Depression, anxiety, hopelessness is common among people who live in the Western world, yet little is known about its prevalence in individuals in slum settlements in Latin America. We investigated in the association of scarcity (lack of access to water and food) to depression, anxiety and hopelessness in individuals aged 18–64 years living in slum areas in the Dominican Republic. This is the first study ever which investigates mental health of individuals living in slum areas in the Dominican Republic (DT). Methods A baseline assessment of community based longitudinal survey of adults aged above 18–64 years was carried out in an urban slum and in villages in the DR in 2012. Random sampling by random route was employed to select households, the sampling unit in this study. Depression, anxiety, was measured by using CIDI-based depression and anxiety criteria according to the DSM-IV criteria and overlapping dimensions of depression and anxiety (e.g. hopelessness) were assessed. Association between living conditions and depression and anxiety was investigated with logistic regression analysis. Results A total of 200 individuals were interviewed (n = 119 women, 59.8%). The response rate was excellent (98.5%). The prevalence of depression was 11.3% in women and 16.0% in men. The dimension ‘hopelessness' was the most prevalent mental condition (46.2% among women; 60.5% among men.) Hopelessness was associated with being male and younger. Furthermore, hopelessness was associated with food insecurity (OR = 2.5) and with lack of access to water (OR = 3.0). Conclusion Hopelessness is common in people living in slums, with young males under 30 at greater risk than any other group. This study is the baseline for further research on mental health of people living in slums in the Dominican Republic.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".