Exploring Foot Care Conditions for People Experiencing Homelessness: A Community Participatory Approach
Bibliographic record
Abstract
INTRODUCTION: People experiencing homelessness are faced with complex challenges and are at high risk of illness due to inequities and disparities in access to health care services. OBJECTIVE: To explore the health and foot care problems related to people experiencing homelessness in British Columbia. METHODS: A community participatory research approach was used with a sample of 65 people experiencing homelessness. Data were collected using a survey questionnaire and face-to-face semistructured interviews. RESULTS: Thematic findings shows risk of foot injuries, lack of foot care resources, and absence of family support. Barriers to equitable access to services for most participants experiencing homelessness were lack of housing (76.92%), inability to work (72.31%), and inability to afford the cost of living on their own (63.08%). CONCLUSIONS: There is a pressing need for early screening and detection by health care professionals and enhanced foot care services to reduce foot problems and improve foot care wellness of homeless people. Addressing foot-related care are necessary steps in promoting health, preventing illness, and improving access to health services among people experiencing homelessness.
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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 | 0.022 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 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".