Attending to Mis/matches in Care: a Narrative Inquiry in the Experiences of Youth and Families Waiting to Access Mental Health Services during COVID-19 in Canada
Bibliographic record
Abstract
The mental health of young people has increasingly become the focus of child and youth studies. In Canada, the critical need for improved youth mental health services (MHS) has been exacerbated and exposed by the COVID-19 pandemic. This is particularly evident for BIPOC and 2SLGBTQ + youth. In this paper, we foreground the experiences of young people and their families attempting to access support from child and youth MHS during the COVID-19 pandemic. Employing narrative inquiry, we engaged in research conversations with ten youth participants and their families over an 18-month period. We attended to the experiences of children, youth, and families placed on waiting lists for formalized mental health support. Through a process of analysis of their narrative accounts, we identified several resonant threads that impacted young people’s mental health in relation to their experiences of waiting, systemic challenges, gaps and barriers within child and youth MHS in Canada. Youth and family members described various mis/matches between the MHS needed and those offered, or which were accessible. Our findings highlight participants’ mental health experiences waiting for support and the impact such waiting had on their identities. Young people shared their use of innovative coping resources, strategies, and services they accessed while waiting for formalized mental health supports. Participants’ experiences of mis/matched care foreground the ways in which access to appropriate, empathetic, and timely support is limited. We outline possibilities moving forward which shift focus from a constricted view of children and youth mental health as problems to be solved, towards young people’s understanding of themselves as agentic beings.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.020 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| 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".