HEARTS Study Protocol: Helping Enable Access and Remove Barriers To Support for Young Adults with Mental Health-Related Disabilities
Bibliographic record
Abstract
Young adults are disproportionally affected by mental illnesses (MIs) and often encounter numerous obstacles to accessing healthcare. Untreated MIs have high chronicity and recurrence and are associated with worse health and life outcomes. The aim of the study described in this protocol is to characterize and better understand the barriers and facilitators to accessing mental healthcare for young adults with mental health-related disabilities (YMHDs), focusing on the impact of functional impairment, determinants of health, and unmet healthcare needs. The study protocol, guided by critical realism, uses a patient-oriented sequential mixed-methods design and involves patient research partners (PRPs) to ensure the voices and perspectives of those directly impacted are central to the research process. This study includes a quantitative analysis of secondary data from the Canadian Community Health Survey and a qualitative analysis of semi-structured interviews with YMHDs. The data will be integrated by themes-by-statistics joint display. The study protocol follows the Tri-Agency Statement of Principles for data collection, storage, retention, sharing, and analysis, adheres to ethical guidelines to ensure participant confidentiality and informed consent, and has received institutional ethics approvals. This study will provide valuable insights into factors that act as barriers or facilitators to accessing care and inform the development of targeted interventions to improve access and support for YMHDs. This study has several strengths, including a participatory research approach that involves PRPs and other relevant stakeholders in the research process, a targeted focus on a specific age group, and the use of mixed-methods research and critical realism. This protocol describes a study that will inform policy, service delivery, and treatment options. This study has the potential to drive systemic change and significantly improve the lives and health of young people with mental health needs.
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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 | 0.076 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.120 | 0.025 |
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".