The role of family support in preventing type 2 diabetes in rural and remote British Columbia
Bibliographic record
Abstract
Rural and remote populations in Canada face health disparities that increase their risk for developing type 2 diabetes (T2D; Public Health Agency of Canada, 2011; Roche et al., 2014). Locating, accessing, and being supported in making behaviour changes in line with T2D prevention guidelines are barriers for rural and remote populations in British Columbia (Keating et al., 2011; Locke et al., 2021 & Public Health Agency of Canada, 2011). A feasible form of support that may be available to these populations is family members as most self-management activities occur at home and are within the family network. Family involvement has been shown to influence adherence to diet and exercise; two health behaviours critical for preventing T2D (Mayberry et al., 2016; Johnson et al., 2013). The aim of this project was to understand how family involvement facilitates and discourages diet and physical activity behaviours among individuals at risk of developing T2D living in rural and remote communities in British Columbia. Ten individuals (five family members and five individuals at risk of T2D) participated in separate semi-structured interviews exploring perceived supportive and unsupportive family behaviours related to diet and physical activity participation. Interviews were analyzed using the adapted Framework Method for dyadic analysis (Collaco et al., 2021) using an abductive approach. Perceived supportive and unsupportive behaviours were coded to the Theoretical Domains Framework (TDF; Michie et al., 2008) and Self and Family Management Framework (SFMF; Grey et al., 2015), and dyadic perspectives were thematically analyzed. Participants reported perceived supportive behaviours (129) and unsupportive behaviours (55). The most frequently coded TDF domains were social influence (199), and environmental context and resources (109). Motivation (114) was most frequently coded from the SFMF. Themes arising from the dyadic analysis included a need for partnership, modelling of healthy behaviours by family members, and differing views on helpful environments. These findings highlight the iv prevalence of family influence on health behaviours and suggest a need to involve family members in diabetes prevention programs. Addressing the most frequently coded domains from the TDF and concepts from the SFMF could improve the quality of family support in diet and physical activity participation leading to better health outcomes and diabetes prevention practices in rural and remote areas in British Columbia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".