Competencies Relevant to Physical Activity Specialists in Navigating Mental Health Contexts: A Scoping Review
Bibliographic record
Abstract
To inform future learning opportunities, we performed a scoping review to identify competencies relevant to physical activity (PA) specialists in supporting the PA and mental health of people experiencing mental health concerns. CINAHL, PsycINFO, and SPORTDiscus databases were searched up to June 22, 2022, for research studies and commentaries. Pertinent text was extracted and subject to content analysis using an inductive approach. Sixty-two competencies from 62 publications were organized into four domains: (a) interacting with mental health care services/systems, (b) responding to mental health concerns, (c) employing PA counseling/coaching to promote mental health among people with diverse mental health needs, and (d) building relationships that are responsive to diverse mental health needs. These findings may serve as a road map for stakeholders interested in developing PA specialists’ confidence to meet the challenges of navigating mental health contexts. Despite consistency across sources, points of divergence warrant consideration from learning institutions and professional bodies.
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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 | 0.036 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.029 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".