Shared Decision Making in a Youth Mental Health Service Design and Research Project: Insights From the Pan-Canadian ACCESS Open Minds Network
Bibliographic record
Abstract
Shared decision making (SDM) is the process by which health care providers and patients collaborate to make health care decisions. This collaboration leads to informed decision making and improved outcomes. However, research on SDM specific to the field of youth mental health is scarce. ACCESS Open Minds (ACCESS OM) is a youth mental health research and evaluation project that implemented and evaluated SDM practices within its various activities and operations. The ACCESS OM network spans a diversity of youth mental health settings across Canada, and includes various stakeholders such as youth, family members and carers, clinicians, researchers, and policy makers. The project values all types of knowledge (specifically, experiential, cultural, clinical, and scientific knowledge) as necessary to lead to better health research, care delivery, and outcomes for patients and their communities. Similarly, it acknowledges the lived experience of patients and, family and carers as expertise. Through the integration of SDM practices, ACCESS OM has formulated valuable insights that can be applied to other health problems and settings. This paper, written by youth and family council members, operational staff, and researchers from the project, will share challenges and solutions that arose in the integration of SDM practices within ACCESS OM’s knowledge translation strategy, governance structures, clinical contexts, and capacity-building initiatives. This paper describes how ACCESS Open Minds (ACCESS OM) uses shared decision making (SDM) strategies. ACCESS OM is a pan-Canadian youth mental health project, which is improving youth mental health services across Canada. Often, health care systems are not set up to prioritize patients’ expertise when it comes to decisions about care and services. SDM means that patients, service providers, and other relevant individuals collaborate to make decisions about health care. SDM strategies are important in how ACCESS OM is working to improve youth mental health services. This paper provides examples of how the ACCESS OM project has implemented SDM processes, and discusses challenges encountered in this regard, with the aim of helping other projects and organizations implement SDM strategies.
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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 | 0.078 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.052 | 0.039 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.007 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".