Knowledge-exchange in the Pacific: outcomes of the TROPIC (translational research for obesity prevention in communities) project
Bibliographic record
Abstract
BACKGROUND: The Pacific TROPIC (Translational Research for Obesity Prevention in Communities) project aimed to design, implement and evaluate a knowledge-broking approach to evidence-informed policy making to address obesity in Fiji. This paper reports on the quantitative evaluation of the knowledge-broking intervention through assessment of participants' perceptions of evidence use and development of policy/advocacy briefs. METHODS: Selected staff from six organizations - four government Ministries and two nongovernment organizations (NGOs) - participated in the project. The intervention comprised workshops and supported development of policy/advocacy briefs. Workshops addressed obesity and policy cycles and developing participants' skills in accessing, assessing, adapting and applying relevant evidence. A knowledge-broking team supported participants individually and/or in small groups to develop evidence-informed policy/advocacy briefs. A questionnaire survey that included workplace and demographic items and the self-assessment tool "Is Research Working for You?" (IRWFY) was administered pre- and post-intervention. RESULTS: Forty nine individuals (55% female, 69% 21-40 years, 69% middle-senior managers) participated in the study. The duration and level of participant engagement with the intervention activities varied - just over half participated for 10+ months, just under half attended most workshops and approximately one third produced one or more policy briefs. There were few reliable changes on the IRWFY scales following the intervention; while positive changes were found on several scales, these effects were small (d < .2) and only one individual scale (assess) was statistically significant (p < .05). Follow up (N = 1) analyses of individual-level change indicated that while 63% of participants reported increased research utilization post-intervention, this proportion was not different to chance levels. Similar analysis using scores aggregated by organization also revealed no organizational-level change post-intervention. CONCLUSIONS: This study empirically evaluated a knowledge-broking program that aimed to extend evidence-informed policy making skills and development of a suite of national policy briefs designed to increase the enactment of obesity-related policies. The findings failed to indicate reliable improvements in research utilization at either the individual or organizational level. Factors associated with fidelity and intervention dose as well as challenges related to organizational support and the measurement of research utilization, are discussed and recommendations for future research presented.
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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 | 0.021 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".