A Qualitative Description Study of the Patient's Experience With Community-Based Virtual Crisis Care in Canada: Illustrating the Potential Positives and Negatives of Remote Support on Recovery
Bibliographic record
Abstract
The study's objective is to describe how individuals accessing a virtual crisis stabilization program following discharge from an emergency mental health visit perceived the service as either facilitating or hindering recovery. Interested service users were identified through feedback surveys and contacted for an interview. Demographic and service utilization variables were obtained from the survey data. Interview data were analyzed thematically using an inductive approach focused on exploring perspectives related to recovery. Twenty-one participants were interviewed; one with a support person. Four recovery thematic categories were identified: (1) connection to others is possible or lacking; (2) access to care providers/therapeutic relationship; (3) ability to remain at home; and (4) virtual service provision. Each category generated subthemes that demonstrated both positive and negative impacts of the virtual service. Lived experience highlights typical aspects of crisis intervention, as well as unique themes related to the home environment and virtual care option. It is important to identify these contextual factors when determining if virtual care is right for an individual. Some areas for service improvement were also highlighted.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".