Bibliographic record
Abstract
Immigrant status, especially a few years post arrival, is a major risk factor for depression in populations that have been adequately studied. While information on depression among Asian migrants, including those from India, China and Philippines, in Canada have been reported in previous studies, there is inadequate information about depression among Nigerian immigrants who make up the largest percentage of African migrants and black population residing in Canada. A cross-sectional study was conducted among 187 Nigerian immigrants in Canada. Participants completed the Patient Health Questionnaire (PHQ-9). Descriptive and multivariate logistic regression analyses were carried out using IBM SPPS. About half (51.7%, n = 91) of the participants screened positive to the PHQ-9. Being female, unmarried, not being at all satisfied with the decision to migrate, and having stayed for more than 10 years in Canada significantly increased the risk of screening positive to depression. More than half of the participants screened positive for depression, suggesting an important mental health concern and the potential need for intervention. This population differed from other immigrant populations from previous studies because the absence of social support, satisfaction with employment status, and perceived discrimination did not significantly predict a positive screen for depression in this study.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".