Populating the model: the SC2.0 approach to co-design for mental health and substance use health system transformation
Bibliographic record
Abstract
While existing literature describing the use of co-design has focused on its application within individual-level or group-level health interventions, the use of co-design to plan and support the implementation of mental health and substance use health stepped care (MHSUH) models and other MHSUH system transformation initiatives is more limited. In this commentary, the authors describe the Populating the Model Series , a co-design-based, system-level planning intervention specifically developed for sites implementing the Stepped Care 2.0 (SC2.0) model of care. The use of co-design, which is a core component of the SC2.0 model, distributes risk through engagement across the community, broadens the system of care to include and acknowledge informal and formal options, creates person-centricity, and incorporates access points and care modalities that are tailored to the intervention site’s context. Seven steps are identified within the Populating the Model Serie s including assessing intervention site readiness, understanding site context, planning and adjusting engagement of key groups for co-design, learning through workshop sessions and co-design, validation with key groups, understanding findings, and application of findings. This guidance provides an actionable process framework for the application of co-design in the planning and implementation of SC2.0 and other stepped care models.
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 | 0.002 | 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 | 0.002 | 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 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".