Co-designing Services for Youth With Mental Health Issues: Novel Elicitation Approaches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Experience-based co-design (EBCD) is an innovative, evidence-based approach to health and social system change based on principles of participatory action research, narrative and learning theory, and design thinking. Unique elicitation strategies such as experience mapping, trigger videos, and prototype development are used in EBCD to engage service users and service providers in a collaborative process of identifying touchpoints and solutions to system-level problems. In this article, we present findings from interviewing a purposeful sample of 18 participants (4 youth, 6 service providers, 6 family members, and 2 employers) across three co-design projects designed to address either mental health or employment services for youth (aged 16–24) with mental health issues in one urban center. Through interviewing participants, perceptions were explored relating to three elicitation techniques: creating experience maps, creating and viewing trigger videos, and co-designing visual “prototype” solutions. Analysis of participants’ comments indicated that these techniques can be powerful tools to foster mutual understanding and collaborative ideas, but they require a social, spatial, and temporal context that optimizes their value. A “safe space” is needed within which the essential elements of elicitation—building trust, finding voice, sharing perspectives, and creating a common vision—can occur. Three core, overlapping processes of co-design elicitation were identified: “building common perspectives,” “building mutual understanding,” and “building innovation.” We present a conceptual framework depicting the interplay of processes and elicitation techniques, essential to building mutual understanding and innovation during the EBCD process.
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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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it