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Occupational Therapists' Perceptions of Their Role with People Who are Homeless

2009· article· en· W2328395262 on OpenAlexaffabout
Marie Grandisson, Morag Mitchell-Carvalho, Victoria Tang, Nicol Korner‐Bitensky

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsOccupational therapyOutreachFocus groupQualitative researchService delivery frameworkMedicinePerceptionNursingPsychologyService (business)PsychiatrySociology

Abstract

fetched live from OpenAlex

Introduction: The needs of individuals who are homeless are often unmet. This study identifies the potential role of occupational therapy with adults who are homeless. Method: This was a qualitative study of occupational therapists working in Montreal, Québec, Canada, consisting of two survey modes: focus group and self-administered questionnaires. A moderate inductive strategy was used in the analysis of the responses. Findings: Twenty-two occupational therapists participated. The traditional roles of assessing, treating and conducting research were discussed, as well as the emerging role of occupational therapists as case managers, outreach workers and advocates. The challenges to implementing services included health care structures and processes. The potential facilitators included active leadership and advocacy by occupational therapists regarding the needs of those who are homeless. Implications: There is a clear and pertinent role for occupational therapy services with those who are homeless. The traditional process of service delivery presents challenges that must be addressed. The topic of homelessness and role-emerging practice placements with this population should be included in the occupational therapy curriculum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.048
GPT teacher head0.393
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2009
Admission routes2
Has abstractyes

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