Mentored training and its association with dissemination and implementation research output: a quasi-experimental evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is a continued need to evaluate training programs in dissemination and implementation (D&I) research. Scientific products yielded from trainees are an important and objective measure to understand the capacity growth within the D&I field. This study evaluates our mentored training program in terms of scientific productivity among applicants. METHODS: Post-doctoral and early-career cancer researchers were recruited and applied to the R25 Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC) between 2014 and 2017. Using application details and publicly available bibliometric and funding data, we compared selected fellows with unsuccessful applicants (nonfellows). We extracted Scopus citations and US federal grant funding records for all applicants (N = 102). Funding and publication abstracts were de-identified and coded for D&I focus and aggregated to the applicant level for analysis. Logistic regression models were explored separately for the odds of (1) a D&I publication and (2) US federal grant funding post year of application among fellows (N = 55) and nonfellows (N = 47). Additional models were constructed to include independent variables that attenuated the program's association by 5% or more. Only US-based applicants (N = 87) were included in the grant funding analysis. RESULTS: Fellows and nonfellows were similar across several demographic characteristics. Fellows were more than 3 times more likely than nonfellows to have grant funding after MT-DIRC application year (OR 3.2; 95% CI 1.1-11.0) while controlling for time since application year; the association estimate was 3.1 (95% CI 0.98-11.0) after adjusting for both cancer research area and previous grant funding. For publications, fellows were almost 4 times more likely to publish D&I-focused work adjusting for time (OR 3.8; 95% CI 1.7-9.0). This association lessened after adjusting for previous D&I publication and years since undergraduate degree (OR 2.9; 95% CI 1.2-7.5). CONCLUSIONS: We document the association of a mentored training approach with built-in networks of peers to yield productive D&I researchers. Future evaluation efforts could be expanded to include other forms of longer-term productivity such as policy or practice change as additional objective measures. D&I research trainings in the USA and internationally should consider common evaluation measures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it