Building the Next Generation of Researchers: Mentored Training in Dissemination and Implementation Science
Bibliographic record
Abstract
PROBLEM: Dissemination and implementation (D&I) science provides the tools needed to close the gap between known intervention strategies and their effective application. The authors report on the Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC) program-a D&I training program for postdoctoral or early-career cancer prevention and control scholars. APPROACH: MT-DIRC was a 2-year training institute in which fellows attended 2 annual Summer Institutes and other conferences and received didactic, group, and individual instruction; individualized mentoring; and other supports (e.g., pilot funding). A quasi-experimental design compared changes in 3 areas: mentoring, skills, and network composition. To evaluate mentoring and D&I skills, data from fellows on their mentors' mentoring competencies, their perspectives on the importance of and satisfaction with mentoring priority areas, and their self-rated skills in D&I competency domains were collected. Network composition data were collected from faculty and fellows for 3 core social network domains: contact, mentoring, and collaboration. Paired t tests (mentoring), linear mixed models (skills), and descriptive analyses (network composition) were performed. OUTCOMES: Mentors were rated as highly competent across all mentoring competencies, and each mentoring priority area showed reductions in gaps between satisfaction and importance between the 6 and 18 months post-first Summer Institute. Fellows' self-rated skills in D&I competencies improved significantly in all domains over time (range: 42.5%-52.9% increase from baseline to 18 months post-first Summer Institute). Mentorship and collaboration networks grew over time, with the highest number of collaboration network ties for scholarly manuscripts (n = 199) in 2018 and for research projects (n = 160) in 2019. NEXT STEPS: Building on study findings and existing literature, mentored training of scholars is an important approach for building D&I skills and networks, and thus to better applying the vast amount of available intervention evidence to benefit cancer control.
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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 | 0.519 | 0.564 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.020 | 0.040 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".