The perceptions of homeless people regarding their healthcare needs and experiences of receiving health care
Bibliographic record
Abstract
AIMS: To understand the perspective of the homeless about their healthcare encounters and how their experiences of receiving healthcare influence their health-seeking behaviour. BACKGROUND: A phenomenological study was undertaken because of the increasing levels of homelessness in the United Kingdom. Most of the current literature is American or Canadian. DESIGN: An interpretive phenomenological inquiry. METHOD: An opportunistic sample of fourteen single homeless adults was recruited from one male hostel and one non-residential day centre. Data collection was done in 2013. Semi-structured audio-recorded interviews were conducted one-to-one. Colaizzi's method for data analysis was used. FINDINGS: Three major themes were identified. Expressed Health Need, Healthcare Experiences and Attitudes to health care. Health problems are recognized by the homeless but the need for intervention is not always prioritised. Obstacles in access to health care in the UK are both perceived (attitudes towards the homeless; previous bad experience) and actual (difficulty in registering with a general practitioner, difficulty travelling to services, being forced to move to new area). Some homeless people feel that they are treated with prejudice and receive substandard care. Positive healthcare experiences were also reported. CONCLUSIONS: Positive and negative healthcare encounters can profoundly affect the homeless. RECOMMENDATIONS: Address apparent inconsistency of care; promote greater interdisciplinary communication and referrals to homeless services from prisons and hospitals; increase the availability of intermediate services; reduce obligation of homeless to move area; research experiences of homeless families.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".