Evaluations of training programs to improve capacity in K*: a systematic scoping review of methods applied and outcomes assessed
Bibliographic record
Abstract
Abstract This paper examines how frequently K* training programs have been evaluated, synthesizes information on the methods and outcome indicators used, and identifies potential future approaches for evaluation. We conducted a systematic scoping review of publications evaluating K* training programs, including formal and informal training programs targeted toward knowledge brokers, researchers, policymakers, practitioners, and community members. Using broad inclusion criteria, eight electronic databases and Google Scholar were systematically searched using Boolean queries. After independent screening, scientometric and content analysis was conducted to map the literature and provide in-depth insights related to the methodological characteristics, outcomes assessed, and future evaluation approaches proposed by the authors of the included studies. The Kirkpatrick four-level training evaluation model was used to categorize training outcomes. Of the 824 unique resources identified, 47 were eligible for inclusion in the analysis. The number of published articles increased after 2014, with most conducted in the United States and Canada. Many training evaluations were designed to capture process and outcome variables. We found that surveys and interviews of trainees were the most used data collection techniques. Downstream organizational impacts that occurred because of the training were evaluated less frequently. Authors of the included studies cited limitations such as the use of simple evaluative designs, small cohorts/sample sizes, lack of long-term follow-up, and an absence of curriculum evaluation activities. This study found that many evaluations of K* training programs were weak, even though the number of training programs (and the evaluations thereof) have increased steadily since 2014. We found a limited number of studies on K* training outside of the field of health and few studies that assessed the long-term impacts of training. More evidence from well-designed K* training evaluations are needed and we encourage future evaluators and program staff to carefully consider their evaluation design and outcomes to pursue.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".