Demographic and Clinical Presentations of Youth using Enhanced Mental Health Services in Six Indigenous Communities from the ACCESS Open Minds Network
Bibliographic record
Abstract
OBJECTIVE: In many Indigenous communities, youth mental health services are inadequate. Six Indigenous communities participating in the ACCESS Open Minds (AOM) network implemented strategies to transform their youth mental health services. This report documents the demographic and clinical presentations of youth accessing AOM services at these Indigenous sites. METHODS: Four First Nations and two Inuit communities contributed to this study. Youth presenting for mental health services responded to a customized sociodemographic questionnaire and presenting concerns checklist, and scales assessing distress, self-rated health and mental health, and suicidal thoughts and behaviors. RESULTS: Combined data from the First Nations sites indicated that youth across the range of 11-29 years accessed services. More girls/women than boys/men accessed services; 17% identified as LBGTQ+. Most (83%) youth indicated having access to at least one reliable adult and getting along well with the people living with them. Twenty-five percent of youth reported difficulty meeting basic expenses. Kessler (K10) distress scores indicated that half likely had a moderate mental health problem and a fourth had severe problems. Fifty-five percent of youth rated their mental health as fair or poor, while 50% reported suicidal thoughts in the last month. Anxiety, stress, depression and sleep issues were the most common presenting problems. Fifty-one percent of youth either accessed services themselves or were referred by family members. AOM was the first mental health service accessed that year for 68% of youth. CONCLUSIONS: This report is the first to present a demographic and clinical portrait of youth presenting at mental health services in multiple Indigenous settings in Canada. It illustrates the acceptability and feasibility of transforming youth mental health services using core principles tailored to meet communities' unique needs, resources, and cultures, and evaluating these using a common protocol. Data obtained can be valuable in evaluating services and guiding future service design. Trial registration name and number at Clinicaltrials.gov: ACCESS Open Minds/ACCESS Esprits ouverts, ISRCTN23349893.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".