Impact of the South Asian Adolescent Diabetes Awareness Program (SAADAP) on diabetes knowledge, risk perception and health behaviour
Bibliographic record
Abstract
Objective: Evidence suggests the increased prevalence of diabetes among South Asian (SA) adolescents is due to their genetic risk profile. The South Asian Adolescent Diabetes Awareness Program (SAADAP) is a pilot intervention for SA youth in Canada with a family history of type 2 diabetes mellitus (T2DM). We sought to investigate changes in (1) diabetes knowledge and associated risk factors, (2) risk perception and (3) health behaviours among adolescents participating in SAADAP. Design: One-group pre-test, post-test design informed by a commitment to community-based participatory research (CBPR). Setting: Sixty-eight adolescents aged 13–17 years with a family history of T2DM participated in SAADAP in a clinical-community setting in Canada. Method: Pre–post questionnaires were administered to evaluate diabetes knowledge and associated risk factors, risk perceptions and health behaviours. Analyses were restricted to 49 participants who attended at least four diabetes education sessions. Results: The mean age of adolescents was 14.5 years, and 57.1% self-identified as girls. The difference in knowledge about the definition, symptoms and complications of T2DM from baseline to post-intervention was 3.32 out of 21 ( p < .001) among SA youth. There was significant increase in learning about diabetes risk factors ( p < .001) from baseline to post-intervention. Almost 60% of participants exhibited no change in their risk perception after intervention. Approximately two-thirds of the participants self-reported positive changes in health behaviours after completing the programme. Conclusion: SAADAP showed promising outcomes in raising knowledge and improving health behaviours in SA adolescents with a family history of diabetes. Larger controlled trials with longer follow-up are recommended to support and expand on the current findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".