A lack of empirical evidence on sport officials’ mental health: a scoping review
Bibliographic record
Abstract
Sport officials—who are essential to organized sport—are tasked with applying competition rules, maintaining fair competitions, and ensuring athlete safety. However, sport officials experience stress, burnout, and non-accidental violence, with incidence of these events increasing worldwide. This has led to rising attrition rates and recruitment issues among sport officials, with many sport organizations concerned for their operational capacity. Possibly, the effects of stress, burnout, and non-accidental violence contribute to sport officials’ negative mental health outcomes. To develop a clear understanding of how sport officials’ mental health is affected by their occupation, it is necessary to identify the mental health outcomes they experience, and to what extent. The purpose of this scoping review was to identify and examine the empirical research surrounding sport officials’ mental health. Using Arksey and O’Malley’s (2005) framework, 1206 articles were identified across three databases: PubMed, Web of Science, SportDiscus, PsycINFO. Following screening, 18 studies met the inclusion criteria for exploring sport officials’ mental health. Participants (N = 7941) in the included studies were mainly European male soccer and basketball referees. Most studies utilized quantitative inquiry (n = 15) rather than qualitative methods (n = 2) or framework development (n = 1). The research demonstrates that sport officials frequently experience negative mental health outcomes including anxiety, depression, burnout, lower mental health literacy, and high levels of stigmatization. These outcomes are influenced by gender, age, and experience. Researchers should continue examining how this profession impacts sport officials’ mental health and implement effective management strategies.
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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 | 0.016 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".