Qualitative Evaluation of University Students’ Experience Delivering an Obesity Prevention Programme in Elementary Schools
Bibliographic record
Abstract
The Coordinated Approach to Child Health (CATCH) programme is an accredited obesity prevention programme in the United States, teaching children about nutrition, physical activity, and screen time limits. This study aimed to evaluate the perceptions of undergraduate and graduate student leaders' about their experience delivering the CATCH programme in elementary schools in Northern Illinois school districts during the 2019-2020 school year and its impact on their personal and professional skills and on programme participants. An email questionnaire was sent to eligible students. Grounded theory was used to analyze the students' responses. Two researchers assigned codes to the data and identified themes. Twenty-one students responded (50% response rate). Six identified themes include "purpose of CATCH programme," "school facilities and resources," "university students experience with CATCH lessons and activities," "benefits to university student," "benefits to children and teachers," and "identified weaknesses and suggested improvements to CATCH." University students delivering the CATCH programme appreciated the opportunity to practice in a real-world setting, gained transferable professional skills, increased programme content knowledge, identified CATCH programme benefits/strengths, and planned to apply lessons learned to future practice.
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 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 | 0.017 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".