Access to healthcare services and confidence in healthcare professionals’ management of malaria: the views of Francophone sub-Saharan African Immigrants living in western Canada
Bibliographic record
Abstract
BACKGROUND: There is a paucity of knowledge about the healthcare attitudes and practices of French-speaking immigrants originating from Sub-Saharan Africa (FISSA) living in minority settings. The purpose of this study was to characterize FISSA healthcare experiences and confidence in the malaria-related knowledge of health professionals in Edmonton. METHODS: A structured survey was used to examine a cohort of 382 FISSA (48% female; 52% male) living in Edmonton. FISSA general healthcare attitudes, experiences and satisfaction with the Canadian healthcare system were studied. Healthcare Competency Perception (HCP) was characterized by using an index score. Statistical analyses were performed to evaluate the impact of healthcare experiences and other outcomes. RESULTS: Intriguingly, while only 42% of FISSA had a French-speaking family physician, 83% (197/238) of those who had received health care services in Alberta found that access to medical treatment was easy, and 77% (188/243) were satisfied with received care. Although 70% (171/243) of FISSA did not receive services in French, 82% (199/243) surprisingly reported having good levels of comprehension during their visits. Satisfaction with care was associated with having a family physician (p = 0.018) and having health insurance (p = 0.041). Nevertheless, confidence in the healthcare system's ability to treat malaria effectively was significantly lower, with only 39% (148/382) receiving a positive score on the HCP index. CONCLUSION: This study provides an important insight into FISSA experience with and perception of the Alberta's healthcare system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 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".