Defining youth-centred practice in mental health care
Bibliographic record
Abstract
BACKGROUND: Like many other nations, the rates of mental illness among children and youth have risen. Youth and emerging adults (YEA) between the ages of 16 and 25, in particular, have the highest rate of mental health disorders of any age group leading clinicians and researchers to ponder new and innovative ways to treat mental ill health (1-2). Youth centred practices (YCP) have emerged as possible new approaches in youth mental health care to better treat YEA living with mental illness, but also to empower this population to take control of their wellbeing. Despite the growing use of the term 'youth-centred,' there is little consensus on what this looks like in mental health care for youth. Using research coming out of MINDS of London-Middlesex, we explore how mental health professionals, including clinicians, researchers, administrative staff, and trainees, understand the term YCP and how they implement youth-centredness in practice. METHODS: Using a Youth Participatory Action Research framework as a guide, MINDS' researchers worked alongside YEA research assistants in all phases of research. Participants were selected from a pool of known practitioners and mental health programs utilizing YCP, as identified by YEA research assistants. Qualitative focus group and interviews, developed using an appreciative inquiry approach, were conducted with 13 mental health care professionals, staff, and trainees to ascertain how they understand and practice YCP. Researchers conducted a codebook thematic analysis of the data: five themes and fourteen subthemes were identified. RESULTS: Our analysis identified five main themes: (1) Acknowledging YCP's Role in Supporting YEA Mental Health; (2) Developing Authentic and Meaningful Relationships Between YEA and Care Providers; (3) Collaboration in Care: Engaging YEA as Active Agents in their Treatment; (4) Creation and Maintenance of Accessible Service to Facilitate YEA Engagement; and (5) Moving Beyond Tacit Knowledge to YCP as a Trainable Construct. Underlying each of these key components of YCP was a thread of recognition that systems of care for YEA must be responsive to the unique needs of those the system intends to serve. This process is seen as dynamic and fluid; often representative of societal change and growth, the specific needs of YEA will remain in flux and YCP approaches require continued reflexivity. CONCLUSIONS: When YCPs are used in mental health care, YEA and their lived experiences are respected by trusted adults on their care team. At the core, YCPs are collaborative. There is a shift from the dynamic of "practitioner as expert" to one that provides YEA a sense of agency and autonomy to make informed decisions regarding their care.
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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 | 0.044 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.048 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".