Development of the Strengths, Skills, and Goals Matrix: a tool for facilitating strengths-based adolescent and young adult engagement in research
Bibliographic record
Abstract
BACKGROUND: The involvement of adolescents and young adults (AYAs) with lived experience of health and mental health conditions as partners in research is increasing given the prominence of participatory approaches to research, including patient-oriented research (POR). Much of the relevant research is conducted by graduate students. While guiding AYA engagement frameworks and models exist, the processes of partnering with AYAs in patient-oriented graduate-level research projects have not been well established. Co-developed tools and practices are required to support strengths-based, developmentally appropriate AYA-graduate student partnerships. OBJECTIVES: The objectives of this commentary are: (1) to share the processes of partnership between a graduate student and five Young Adult Research Partners (YARP), (2) to describe the co-design and implementation of the Strengths, Skills, and Goals Matrix (SSGM), a tool for facilitating strengths-based AYA engagement in research, and (3) to outline considerations for applying this tool across a variety of research contexts with patient partners. MAIN BODY: Within the YARP-graduate student partnership, the SSGM offered extensive benefits, including tangible skill development, peer mentorship, and rapport building among all members. This tool offers strategies for strengths-based engagement practices which emphasize AYAs' preferences and goals throughout POR projects. Practical recommendations and considerations for applying the SSGM within graduate-level research and beyond are described, including the importance of connecting AYAs' current (and desired) skills to specific tasks within the research project and resulting outputs. CONCLUSIONS: The SSGM has possible relevance in a variety of settings given its broadly applicable structure. Future research could explore the adaptation, application, and evaluation of the SSGM across research contexts to determine its feasibility and ease of implementation. PATIENT OR PUBLIC CONTRIBUTION: This article was conceived of and co-authored by five young adult research partners. The YARP co-designed the SSGM presented in this article, the figures, and substantially contributed to the preparation of the article.
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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 | 0.034 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.007 |
| 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".