Primary health care: applying the principles within a community-based participatory health research project that began in a Canadian women’s prison
Bibliographic record
Abstract
OBJECTIVES: the purpose of this research was to determine the feasibility of engaging incarcerated women in community-based participatory research and to identify, by and with the women, the health concerns to be addressed. DESIGN: the integration of primary health care, community-based participatory research, a settings approach to health promotion and transformative action research guided the overall design of this study. PARTICIPANTS: Incarcerated women, correctional centre staff and academic researchers participated collaboratively. Setting. The study was conducted in the main short sentence (two years or less) minimum/medium security women's correctional centre in a Canadian province. RESULTS: In-depth interviews were conducted with 16 incarcerated women; in-depth group interviews were facilitated with 16 correctional centre staff. Twenty-one themes, which emerged from participatory, inductive and content analysis of the data, were presented at a face-to-face meeting attended by 120 incarcerated women, 10 correctional centre staff and 5 academic researchers. Underlying values and principles for the project were identified prior to a discussion of the results. During the course of this meeting, the themes were converged into five major categories: addictions and mental health; HIV, hepatitis and infections; health care in prison; life skills and re-entry into society (including homelessness and housing); and children, family and relationships. Numerous suggestions for health interventions and participatory projects were generated, each relating to one of the five major categories. CONCLUSIONS: this study was unique in that, to our knowledge, no other studies have utilized community-based participatory research methods in which incarcerated women played a role in designing the research questions and tools, collecting the data, analyzing the data, interpreting the data and authoring the publications and presentations. This study demonstrated that it is feasible for incarcerated women to engage in developing and utilizing community-based participatory research methods and that these methods can be grounded in a settings approach to whole prison health promotion.
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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 | 0.033 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".