Going virtual: youth attitudes toward and experiences of virtual mental health and substance use services during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, youth mental health and substance use services rapidly moved to virtual modalities to meet social distancing requirements. It is important to understand youth attitudes toward and experience of virtual services. OBJECTIVE: This study examined the attitudes toward and experiences of virtual mental health and substance use services among youth drawn from clinical and non-clinical samples. METHOD: Four hundred nine youth completed a survey including questions about their attitudes toward and experience of virtual services. The survey included quantitative and open-ended questions on virtual care, as well as a mental health and substance use screener. RESULTS: The majority of youth with mental health or substance use challenges would be willing to consider individual virtual services, but fewer would consider group virtual services. However, many have not received virtual services. Youth are interested in accessing a wide variety of virtual services and other supportive wellness services. Advantages and disadvantages of virtual services are discussed, including accessibility benefits and technological barriers. DISCUSSION: As youth mental health and substance use services have rapidly gone virtual during the COVID-19 pandemic, it is essential that we hear the perspectives of youth to promote service utilization among those in need. Diverse, accessible, technologically stable virtual services are required to meet the needs of different youth, possibly with in-person options for some youth. Future research, engaging youth in the research process, is needed to evaluate the efficacy of virtual services to plan for the sustainability of some virtual service gains beyond the pandemic period.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".