NorthBEAT: exploring the service needs of youth experiencing early psychosis in Northern Ontario
Bibliographic record
Abstract
Introduction: Early Psychosis Intervention (EPI) is critical for best outcomes. Among 369 diseases, psychosis is among those causing the greatest disability. Evidence-based interventions for youth in early stages of psychosis (EPI programs) have prevented chronic disability. Yet, EPI is frequently inaccessible for youth living in rural communities. Moreover, Indigenous youth often face more precipitous situations given inadequate staffing, and culturally unsafe care. The NorthBEAT (Barriers to Early Assessment and Treatment) project sought to understand the service needs of youth with psychosis in Northern Ontario. The goals were: (1) to describe the mental health of a subset of adolescents receiving EPI care; (2) examine Indigenous youth as a significant and vulnerable population; (3) to understand the barriers and facilitators for Indigenous and non-Indigenous youth receiving EPI. Methods: Mixed methods (structured and narrative interviews) included: psychometric scales interviews with youth, and narrative interviews with youth, their family, and service providers Data validation workshops were held with participants. Results: = 26 months). No significant differences were found in functioning or duration of psychosis between Indigenous and non-Indigenous youth. Narrative interviews were conducted with 18 youth, 11 family members, and 14 service providers. Identified barriers were a lack of knowledge about psychosis among service providers, a disconnected system leading to delays in treatment, help not wanted by youth, expansive geographical context. Service needs were: finding the right point of access, support for families, pre-crisis intervention, reduced stigma for youth and their families, and an EPI approach to care. Discussion: Rural and northern youth face similar barriers to accessing EPI as urban youth. However, northern youth face additional unique challenges due to expansive geographical context, limited resources and lack of knowledge about services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".