The value of hackathons in integrated knowledge translation (iKT) research: Waterlupus
Bibliographic record
Abstract
BACKGROUND: Despite a growing movement toward a knowledge-user-driven research process, our understanding of the generation, implementation and evaluation of specific approaches in the integrated knowledge translation (iKT) toolbox that aim to engage health and healthcare knowledge users is limited. Health hackathons offer an innovative approach with potential to generate direct and indirect health-related outcomes benefitting participants, knowledge users and the broader population. In May 2019, our research team hosted Waterlupus, a health hackathon to improve the economic lives of individuals with systemic lupus erythematosus (SLE) in Canada. Waterlupus was held with a multi-stakeholder group of 50 participants that included advocacy organization representatives, policy-makers, researchers, physicians, individuals with lived experience and students. While the hackathon generated viable solutions with the potential to positively impact the lives of individuals with SLE, understanding how participants perceived the hackathon as an iKT tool is critical in the planning and implementation of future iKT research. METHODS: Semi-structured in-depth telephone interviews were conducted with Waterlupus participants (n = 13) between August and November 2019 to (1) explore participant experiences of the hackathon; (2) investigate participant-identified hackathon outcomes; and (3) elicit recommendations for future iKT research using health hackathons. RESULTS: Participants provided feedback on the format and organization of Waterlupus, and identified direct and indirect outcomes to knowledge users, students and researchers beyond the innovations generated at the event. While the majority (n = 11) had never participated in a hackathon prior to Waterlupus, all 13 stated they would participate in future hackathons. Positive outcomes identified include connecting with students and other SLE stakeholders, the formation of professional and support networks, increased awareness of SLE, as well as the innovations generated. Participant recommendations for future health hackathons include the addition of stakeholders from industry or technology, and the need for clear and designated roles for stakeholders to ensure efficient use of resources. CONCLUSIONS: This work contributes to a limited literature regarding the use of health hackathons for social innovation, and offers knowledge-user suggestions relevant to the implementation of future iKT events, and hackathons specifically.
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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: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".