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Record W4321353047 · doi:10.1353/hpu.2023.0020

The Development of a Conceptual Framework for Providing Tailored Diabetes Care for Individuals Experiencing Homelessness: A Qualitative Study

2023· article· en· W4321353047 on OpenAlexaboutno aff
Hannah M. Yaphe, Rachel Campbell, Nicole L. Mancini, Eshleen Grewal, Tadios Tibebu, Terry Saunders‐Smith, Stephen W. Hwang, David J.T. Campbell

Bibliographic record

VenueJournal of Health Care for the Poor and Underserved · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisSituational ethicsMainstreamQualitative researchMultidisciplinary approachPopulationHealth careNursingBridging (networking)Social workPsychologyConceptual frameworkMedicineSocial psychologySociologyEnvironmental healthPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Homelessness results in barriers to effective diabetes self-management. Programs targeting individuals facing homelessness have refined strategies to address these barriers. We sought to develop a framework to characterize these strategies that could help multidisciplinary providers to better support these individuals. Semi-structured interviews were conducted with a purposive sample of health and social care providers working in diabetes or homelessness in five Canadian cities (n=96). Interview transcripts were analyzed through qualitative thematic analysis. Providers described three groups of approaches that enabled care for this population. Person-centered provider behaviours: This included tailoring care plans to accommodate individuals' situational constraints. Lower-barrier organizational structure: Providers developed specialized organizational processes to increase accessibility. Bridging to larger care systems: Strategies included providing access to support workers. Across diverse program structures, similar approaches are used to enhance diabetes care for individuals who are experiencing homelessness, highlighting tangible opportunities for mainstream services to better engage with this population.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.140
GPT teacher head0.473
Teacher spread0.333 · 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 designQualitative
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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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