Occupational needs and priorities of women experiencing homelessness
Bibliographic record
Abstract
BACKGROUND: Women in unstable housing or who are homeless experience disruptions of occupational engagement and performance. Little is known about their perspective on their occupational needs and priorities. PURPOSE: This study aimed to determine how patterns of occupational engagement and performance are facilitated or hindered by personal factors and resources available to sheltered women. METHOD: A participatory, descriptive mixed-methods study design was used. Twenty-one residents were interviewed using the Canadian Occupational Performance Measure, the Goal Attainment Scale, and a time-use inventory. Nineteen residents participated in semistructured qualitative interviews. Qualitative data were analysed using interpretive description. FINDINGS: Participants spent most time on sleep and passive leisure and identified occupational performance issues and goals related to active leisure and employment. Participants' occupational lives were described as transitional journeys comprising five subthemes: seeking safety and stability, being sheltered, shaping one's identity, developing resilience, and engaging in contemplation, contribution, and connectedness through occupation. IMPLICATIONS: Trauma-informed and strengths-based approaches are recommended for this population. Future research should study the implementation of occupation-based interventions in community settings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".