Factors influencing adherence to pre-dive checklists among recreational scuba divers

Undersea Hyperb Med. 2016 Nov-Dec;43(7):827-832.

Abstract

Pre-dive checklists can prevent mishaps, injuries, and deaths in recreational scuba diving. However, the prevalence of checklist use remains low. Understanding the environmental and individual factors influencing a diver's checklist use may help in promoting checklists. In the summer of 2012, 617 divers were enrolled in the intervention group of a cluster randomized trial. The divers received an intervention pre-dive checklist to use before they made dives. Logistic regression analyses were used to model adherence to pre-dive checklist with generalized estimating equations. About 70% divers (n=430) adhered to the intervention pre-dive checklist. Factors associated with greater adherence were the use of a diver's own written self-checklist - odds ratio (OR) = 2.48 (95% confidence interval: 0.95, 6.44), older age (⟩ 35 years) - OR = 1.67 (1.15, 2.42), and higher average annual dives (6-10 dives vs. 0-5 dives) - OR = 1.87 (1.09, 3.21). Factors associated with lower adherence were diving in North Carolina as compared to the Caribbean - OR = 0.42 (0.20, 0.85), non-white race - OR = 0.54 (0.27, 1.09), and female gender - OR = 0.77 (0.54, 1.12). Checklist adherence is also a function of risk perception, facilitators, and barriers. Future studies should try to understand diver risk perceptions, promote facilitators, and reduce barriers to foster the use of pre-dive checklists.

Keywords: adherence; injury prevention; pre-dive checklists; recreation; scuba diving.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Caribbean Region
  • Checklist / statistics & numerical data*
  • Diving / psychology
  • Diving / statistics & numerical data*
  • Ethnicity
  • Exophthalmos
  • Female
  • Guideline Adherence / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • North Carolina
  • Observational Studies as Topic
  • Odds Ratio
  • Random Allocation
  • Recreation
  • Regression Analysis
  • Sex Factors