Why are African Immigrants in Canada Reluctant to Use Mental Health Services? A Systematic Inventory of Reasons
Bibliographic record
Abstract
Abstract BackgroundStudies suggest that despite a high prevalence of mental health conditions among African immigrants in Western countries, they tend to underuse mental health services, compared with native-born people. This study explored the reasons for underuse of conventional mental health services among African immigrants in Canada.MethodThe study participants were 280 African immigrants who had experienced depressive symptoms but did not use conventional mental health services. They were presented with a questionnaire that contained 50 statements referring to reasons for not using conventional mental health services while experiencing depressive symptoms. They were asked to indicate their degree of agreement with each of the statements on a scale of 0-10. Responses were then analyzed using factor analysis.ResultsA eight-factor structure of reasons was found: "Symptoms underestimation and perceived self-efficacy" (important for 61% of the sample), "Relying on community support" (56% of the sample), "Cost and waiting time" (45% of the sample), "Influence of significant others" (34% of the sample), "Denying competence" (32% of the sample), "Fear of stigmatization" (23% of the sample), "Nature of the consultation" (10% of the sample) and "Social models" (8% of the sample). Scores on these factors were related to participants’ demographics. ConclusionThese findings strongly suggest that strategies to promote the use of mental health services among African immigrants must be multifaceted rather than focused on one single barrier. When implementing these strategies, policymakers should put more emphasis on increasing mental health literacy among African immigrant communities, as well as providing them with culturally sensitive mental healthcare.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".