Does the Presence of On-Site Medical Services at Outdoor Music Festivals Affect Attendees’ Planned Alcohol and Recreational Drug Use?
Bibliographic record
Abstract
BACKGROUND: Dedicated on-site medical services have long been recommended to improve health outcomes at mass-gathering events (MGEs). In many countries, they are being reviewed as a mandatory requirement. While it is known that perceptions of risk shape substance use plans amongst outdoor music festival (OMF) attendees, it is unclear if attendees perceive the presence of on-site medical services as a part of the safety net. The aim of this paper is to better understand whether attendees' perceptions of on-site medical services influence high-risk behaviors like alcohol and recreational drug use at OMFs. METHOD: A questionnaire was distributed to a random sample of attendees entering and attending two separate 20,000-person OMFs; one in Canada (Festival A) and one in New Zealand (Festival B). Responses focused on demographics, planned alcohol and recreational drug use, perceptions of medical services, and whether the absence of medical services would impact attendees' planned substance use. RESULTS: A total of 851 (587 and 264 attendees for Festival A and Festival B, respectively) attendees consented and participated. Gender distribution was equal and average ages were 23 to 25. At Festival A, 48% and 89% planned to use alcohol and recreational drugs, respectively, whereas at Festival B, it was 92% and 44%. A great majority were aware and supportive of the presence of medical services at both festivals, and a moderate number considered them a factor in attendance and something they would not attend without. There was significant (>10%) agreement (range 11%-46%; or 2,200-9,200 attendees for a 20,000-person festival) at both festivals that the absence of medical services would affect attendees' planned use of alcohol and recreational drugs. CONCLUSIONS: This study found that attendees surveyed at two geographically and musically distinct OMFs had high but differing rates of planned alcohol and recreational drug use, and that the presence of on-site medical services may impact attendees' perceptions of substance use risk. Future research will aim to address the limitations of this study to clarify these findings and their implications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".