Mental Performance Consultants’ Perspectives on Content and Delivery of Sport Psychology Services to Masters Athletes
Bibliographic record
Abstract
In the absence of sport psychology resources for Masters Athletes, mental performance consultants could benefit from information to assist consultancy with older adult athletes. We conducted semistructured interviews to explore 10 Canadian professional mental performance consultants' (two men and eight women) perspectives of targeted content and the nature of service delivery to Masters Athletes. Following inductive thematic analysis, results for Content of Sport Psychology related to performance readiness (e.g., preparatory routines, mental focus plans); prioritizing sport (e.g., balance/time management, recruiting social support); preserving sport enjoyment (e.g., self-reflection, gratitude/sport as opportunity); and age-related considerations (e.g., managing changing physical realities). Results pertaining to Addressing and Delivering Sport Psychology Services included considerations toward age-related attributes (e.g., values/identity, engaged/invested clients) and accommodating barriers/constraints (e.g., time, stigma). Our results show there are novel considerations when consulting with Masters Athletes, and we discuss what these findings mean for adult-oriented approaches in applied practice.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".