Process and outcome evaluation of a diabetes prevention education program for community healthcare workers in Thailand.
Bibliographic record
Abstract
OBJECTIVE: To describe the development, process and outcome evaluation of a culturally tailored diabetes prevention education program for community healthcare workers (CHCWs) in Thailand. METHODS: A tailored diabetes prevention education program was designed based on formative research and implemented with 35 CHCWs in semi-urban areas in Chiang Mai province, Thailand. Modules were delivered over eight group classes and eight self-directed E-learning sessions (www.FitThai.org). The program incorporated problem-based learning, discussion, reflection, community-based application, self-evaluation and on-line support. The frequency that students accessed on-line materials, including videotaped lectures, readings, monthly newsletters and community resources, was documented. Participant satisfaction was assessed through three questionnaires. Knowledge was assessed through pre-post testing. RESULTS: Three-quarters of participants attended all eight classes and no participant attended fewer than six. On-line support and materials were accessed 3 to 38 times (median 13). Participants reported that program information and activities were fun, useful, culturally-relevant and applicable to diabetes prevention in their specific communities. Participants also appreciated the innovative technology support for their work. Comfort with E-learning varied among participants. Scores on pre-post knowledge test increased from a mean (sd) of 56.5% (6.26) to 75.5% (6.01) (p < .001). CONCLUSIONS: An innovative diabetes prevention education program was developed for CHCWs in Thailand. Interactive classroom modules and self-directed E-learning were generally well-received and supported better knowledge scores. Ongoing access to web-based materials and expert support may help sustain learning.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".