A Feasibility (pilot) Mixed Methods Study of an Innovative Non-Pharmacological Breath-Based Yoga and Social Emotional Intervention Program in an At-Risk Youth Sample in London, Canada
Bibliographic record
Abstract
Abstract Background: Various service provision models for youth at risk of homelessness have been researched and implemented, including access to housing, physical and mental health resources, etc. However, even with these interventions we remain unaware regarding how best to manage symptoms of depression and anxiety and the rate of drug use in these populations primarily because of lack of feasibility data. Methods: This paper presents the results of a mixed-methods study in London, Canada, that examined the feasibility of implementing a biopsychosocial intervention, SKY Schools, in at-risk youth aged between 16-25 (n=49). The study also recorded qualitative responses about the program’s usefulness from the perspective of the service users. The SKY Schools intervention consisted of social-emotional learning combined with Sudarshan Kriya Yoga, a standardized yoga-based breathing exercise routine. The intervention program was divided into two phases; an active learning phase and a reinforcement phase. Results: The results demonstrated that it is feasible to conduct a definitive trial in this population due to a high retention rate (61.2%) and overall positive feedback. Conclusions: Future researchers may consider the feedback received when designing a randomized control trial to further assess efficacy and tolerability. Trial Registration: Trial registration: Clinicaltrials.gov, Identifier NCT02749240. Registered April 22, 2016, https://clinicaltrials.gov/ct2/show/NCT02749240
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".