Navigating Mental Health Services Barriers for Transitional-Aged Youth with Co-occurring Conditions
Bibliographic record
Abstract
Purpose: Canadian youth with neurodevelopmental disabilities (NDDs) are three to five times more likely to develop mental health and/or addictions (MHA) concerns compared to the general population. When accessing MHA care, these youth often face barriers such as long wait lists, uncoordinated transitions, and a lack of specialized services. Patient navigation, a model focused on connecting patients to appropriate resources, may improve access to MHA care. The purpose of this study was to examine and contrast the outcomes and experiences of receiving navigation services vs. self-navigating for caregivers of youth with co-occurring NDDs and MHA concerns over time.Methods: A pragmatic randomized controlled trial was conducted where 158 caregivers of youth (ages 13 to 26) with MHA concerns were randomized to receive navigation services or self-navigate. The current study is a secondary mixed methods analysis, with an embedded design, examining a subset of 67 caregivers of youth with co-occurring NDDs and MHA concerns. Quantitative outcomes (caregiver strain, family functioning, youth symptoms and functioning, quality of life, service utilization and satisfaction) were examined between groups over a six-month period using MANOVA and Mann-Whitney U tests. Thematic analysis of qualitative interviews was used to examine the experiences of families finding and accessing MHA care. Lastly, a statistics-by-themes joint display was used to visualize integrated findings of each strand. Results: Multivariate effects for the interaction between the randomization groups and time were non-significant (p= .20, η² = .042). Four qualitative themes emerged: 1) Neurodiverse-Affirming Care and Specialized Navigation, 2) MHA System Complexities and Inaccessibility for Neurodiverse Youth, 3) Navigation Restoring Balance to Strained Family Systems, and 4) Stigmatizing Care Experiences of Youth with Co-occurring Conditions. Integrated findings provided both convergent and divergent findings between strands and provided nuanced understandings of caregivers' experiences accessing services in the MHA care system. Conclusion: Integrated findings extend understandings of navigation services as a relational and systemic intervention, with implications for design and improvement.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".