A DESCRIPTIVE STUDY OF PRACTITIONERS’ USE OF YOGA WITH YOUTH WHO HAVE EXPERIENCED TRAUMA
Bibliographic record
Abstract
It is not uncommon for youth (ages 2–19) to experience trauma. There are various types of traumatic events that may lead to adverse effects on youths’ emotional, cognitive, social, physical, and spiritual health. It is important that youth receive support and resources to address the negative impacts trauma may have on their minds and bodies. Yoga is a holistic practice that may address these negative effects in all 5 health domains. However, there are many inconsistencies and gaps in the literature regarding the use of yoga with youth who have experienced trauma. The purpose of this descriptive survey research study was to address these inconsistencies by describing the approaches of 56 practitioners who utilize yoga with youth who have experienced trauma, and their perceptions of how and why they use yoga with these youth. Findings highlighted the importance of implementing trauma-specific adaptations when facilitating yoga with youth who have experienced trauma, such as increasing participant autonomy, providing a safe environment, and developing a therapeutic rapport. Results also indicated that the most common use of yoga among these practitioners was to address emotional and physical needs of youth who have experienced trauma. Implications of study findings and opportunities for future research are discussed.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".