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Record W4396860511 · doi:10.1080/10530789.2024.2352293

Exploring the role of psychological factors in diabetes management for people experiencing housing instability: a qualitative descriptive study of providers’ perspectives across Canada

2024· article· en· W4396860511 on OpenAlexafffundabout
Saania Tariq, Eshleen Grewal, Rachel Campbell, David J.T. Campbell

Bibliographic record

VenueJournal of Social Distress and the Homeless · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Calgary
FundersAlberta Innovates
KeywordsQualitative researchDescriptive researchDescriptive statisticsPsychologySociology

Abstract

fetched live from OpenAlex

Psychological factors, such as mental health and cognition, are significant contributors to diabetes management, especially for those experiencing housing insecurity. Our aim was to explore the role of psychological factors in diabetes management for people experiencing housing instability from the perspective of providers. We designed a qualitative descriptive study that consisted of a secondary analysis of semi-structured interviews with a range of health and social care providers from programs that addressed the needs of people with diabetes who were also experiencing homelessness. Interviews were recorded, transcribed, and analyzed using inductive thematic analysis. Ninety-six participants completed semi-structured interviews. We identified four themes that showed (i) experiences of stigma and trauma influence clients’ relationships with providers and their diabetes care seeking behaviors, (ii) immediate psychological safety concerns are generally given priority over diabetes in the client’s care, (iii) substance use can create challenges when trying to manage diabetes and lead to diabetic emergencies, and (iv) varying cognitive abilities and social supports compromise a client’s ability to complete self-management tasks. We conclude that providers have a nuanced understanding of psychological factors and the challenges they create for clients with diabetes experiencing housing insecurity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.923

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 integrity0.0000.000
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 head0.114
GPT teacher head0.431
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes3
Has abstractyes

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