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Record W6942466169 · doi:10.14288/1.0440124

Exploring factors affecting attendance in a diabetes prevention program amongst first-generation Afghan immigrants residing in the Okanagan region of British Columbia

2024· article· en· W6942466169 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAcculturationThematic analysisImmigrationAfghanAttendanceQualitative research

Abstract

fetched live from OpenAlex

Background: As global immigration escalates, host nations must adapt to the diverse needs of new arrivals (Chand & Tung, 2019; Hilado et al., 2021; WHO, 2023). Immigrants forced to leave their homes often lack opportunities to learn about healthy behaviours, resources to practice health behaviours, or access proper treatment, compared to those who have not experienced forced resettlement (Hilado et al., 2021; WHO, 2023). The resettlement processes can also deteriorate health, making immigrants particularly vulnerable to non-communicable diseases like Type 2 Diabetes (T2D) (Qureshi et al., 2023; Towne et al., 2021; Wagner et al., 2020). Factors such as low socio-economic status, resettlement stress, acculturation challenges and traumatic life events may contribute to lower participation rates in diabetes prevention programs within host communities (Brown et al., 2023; Joachim-Célestin et al., 2020; Khatri & Assefa, 2022; Nieto-Martínez et al., 2023; van der Boor et al., 2020). This study aimed to understand the barriers and facilitators to attending a diabetes prevention program (DPP) amongst first-generation Afghan immigrants in the Okanagan region of British Columbia (BC) with a social constructivism lens, using the Theoretical Domain Framework (TDF) to identify key domains influencing program attendance. Methodology: 10 participants engaged in semi-structured interviews to explore perceived barriers and facilitators to diabetes prevention program attendance. Data were analysed abductively, with TDF as the deductive framework and Braun and Clarke’s six phases for thematic analysis for inductive analysis (Braun & Clarke, 2006). Results: The analyses identified 146 facilitators and 39 barriers in total. The most frequently reported barriers affecting participant’s decision to attend a diabetes prevention program were coded as TDF domains: Knowledge, Environmental context and resources, and Social influence. Inductive coding resulted in three themes: 1. Deprivation of Life/Growth Opportunities, 2. Sociocultural and Environmental factors, and 3. Reciprocal community support. Conclusion: Findings of this study highlight the need for culturally tailored features in community-based diabetes prevention programs to enhance their acceptability and effectiveness in immigrant populations living in Okanagan, Canada. This study also highlights the importance of such programs in aiding immigrant integration into communities. Applying these findings can enhance program adaptation for newcomers and minorities in Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.193
Teacher spread0.156 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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