Supporting At-Risk Youth and Their Families to Manage and Prevent Diabetes: Developing a National Partnership of Medical Residency Programs and High Schools
Bibliographic record
Abstract
BACKGROUND: The Stanford Youth Diabetes Coaches Program (SYDCP) is a school based health program in which Family Medicine residents train healthy at-risk adolescents to become diabetes self-management coaches for family members with diabetes. This study evaluates the impact of the SYDCP when disseminated to remote sites. Additionally, this study aims to assess perceived benefit of enhanced curriculum. METHODS: From 2012-2015, 10 high schools and one summer camp in the US and Canada and five residency programs were selected to participate. Physicians and other health providers implemented the SYDCP with racial/ethnic-minority students from low-income communities. Student coaches completed pre- and posttest surveys which included knowledge, health behavior, and psychosocial asset questions (i.e., worth and resilience), as well as open-ended feedback questions. T-test pre-post comparisons were used to determine differences in knowledge and psychosocial assets, and open and axial coding methods were used to analyze qualitative data. RESULTS: A total of 216 participating high school students completed both pre-and posttests, and 96 nonparticipating students also completed pre- and posttests. Student coaches improved from pre- to posttest significantly on knowledge (p<0.005 in 2012-13, 2014 camp, and 2014-15); worth (p<0.1 in 2014-15); problem solving (p<0.005 in 2014 camp and p<0.1 in 2014-15); and self-efficacy (p<0.05 in 2014 camp). Eighty-two percent of student coaches reported that they considered making a behavior change to improve their own health as a result of program participation. Qualitative feedback themes included acknowledgment of usefulness and relevance of the program, appreciation for physician instructors, knowledge gain, pride in helping family members, improved relationships and connectedness with family members, and lifestyle improvements. CONCLUSION: Overall, when disseminated, this program can increase health knowledge and some psychosocial assets of at-risk youth and holds promise to empower these youth with health literacy and encourage them to adopt healthy behaviors.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".