Immigrant women’s experiences of receiving care in a mobile health clinic
Bibliographic record
Abstract
AIM: This paper is a report of a study of the experiences of Portuguese-speaking immigrant women who used a mobile health clinic for their reproductive health care. BACKGROUND: Upon arrival in Canada, immigrant women often are in better health than their Canadian-born counterparts; however, this health status tends to deteriorate over time. One reason for this change is limited access to services. METHOD: Data collection during 2004 and 2005 involved individual interviews with seven Portuguese-speaking women who received care in a mobile health clinic in Toronto, Canada, and with four clinic care providers. Non-participant observation of the interaction between clients and care providers was also conducted. Interviews conducted in Portuguese were translated into English and transcribed, along with those conducted in English. Interview transcripts were read and re-read in the context of observational notes to develop codes. Emerging codes were grouped together to develop subcategories and categories. FINDINGS: Participants' experiences of accessing and receiving care in the mobile health clinic were shaped by their perceptions of health, which included physical, mental, social and spiritual aspects, and their pre- and postmigration care experiences. As an alternative model of care delivery, the mobile health clinic was perceived by participants to address their care needs and to help overcome postmigration barriers by providing accessible, holistic, and linguistically and culturally appropriate care. CONCLUSION: Mobile health clinics should be considered as an alternative care delivery model for immigrant women who may be at a disadvantage because of their socio-economic, cultural, and racialized statuses.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".