Design Thinking for Health Disparities and Interdisciplinary Knowledge Translation: An LGBTQ+ Youth Health Literacy Project
Bibliographic record
Abstract
This article discusses the use of codesign, design thinking (DT), and design jams in collaboration with interdisciplinary scholars, service providers, and community-based stakeholders as an approach to social work intervention development-specifically, to tackle health inequities and timely knowledge translation (KT). An application of these methods to the problem of sexual health disparities and lack of access to inclusive sexual health education in school-based settings for LGBTQ+ youth is discussed. LGBTQ+ Youth HeLP (Health Literacy Project) is a holistic online sexual health resource providing evidence-based information to LGBTQ+ youth in an accessible and age-appropriate format. This article considers potential opportunities and obstacles for utilizing DT to develop responsive solutions to health inequities and health-related KT learned from the project. Codesign offers effective options for generating collaborations that may increase cross-stakeholder perspective taking in group settings and produce high-quality outputs with increased likelihood of uptake.
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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 | 0.037 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".