Mobilizing Minds: Integrated knowledge translation and youth engagement in the development of mental health information resources
Bibliographic record
Abstract
High rates of highly persistent mental health problems can have significantly damaging effects on young adults’ lives, and young adults are less likely to seek treatment for such problems. This article describes a unique Canadian knowledge translation project called Mobilizing Minds: Pathways to Young Adult Mental Health, which aimed to impact not only the mental health literacy of young adults, but to engage young adults in the entire research process from inception to dissemination of results. Knowledge translation is a process that involves producing and assessing the quality of the knowledge to be translated and tailoring the knowledge to be user friendly for particular segments of the population. The article gives particular attention to the ways in which the Mobilizing Minds project was influenced by youth engagement. We discuss three aspects: 1) structures, processes and communication; 2) project products; and 3) challenges and responses. Lessons learned specific to intergenerational collaboration will be of interest to youth as consumers of mental health information and services, mental health practitioners, researchers, and decision-makers seeking to improve mental health at a systemic level.Keywords: knowledge translation, young adult, mental health, participatory research, youth engagement, youth-adult partnerships
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.050 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".