Beyond certification: Improving lifeguard drowning detection through validated tools and specialized training
This study investigated two key aims: (1) the external validity of an animated performance assessment tool previously utilized in lifeguard training, with a focus on how lifeguard experience and task duration affect performance metrics, and (2) the impact of two distinct training protocols on lifeguard-specific drowning detection abilities. In the first experiment, experienced lifeguards demonstrated superior performance compared to inexperienced lifeguards in both 30-min tasks; however, both groups exhibited a decline in performance over time. The external validity of the animated tool was supported by its ability to produce performance outcomes aligned with real-world lifeguard tasks. The second experiment revealed that training specifically designed for lifeguard drowning detection significantly enhanced detection performance, while working memory training showed no measurable effect. These results highlight the necessity of incorporating realistic drowning detection challenges—such as varied bather numbers, drowning durations, and locations—into lifeguard certification programs, which currently do not emphasize these critical elements. The study also points to the significant proportion of lifeguards who missed drowning scenarios at baseline, underscoring the urgent need for improved training. Future research should explore the potential of animated tools in training and further investigate the cognitive mechanisms that underpin effective drowning detection. • Experienced lifeguards outperformed novices, but both groups showed performance declines over time. • Repeated exposure to drowning scenarios, even without specific instruction, led to a 29 % improvement in drowning detection, highlighting the importance of scenario-based training for lifeguards. • Findings highlight the necessity of incorporating realistic drowning detection challenges into lifeguard certification programs, which currently do not emphasize these critical elements.
Authors
- William R. Trender (ORCID: https://orcid.org/0000-0003-3947-5532)
- Adam Hampshire (ORCID: https://orcid.org/0000-0002-5176-5420)
- Steven Williams (ORCID: https://orcid.org/0000-0003-4299-1941)
- Benjamin T. Sharpe (ORCID: https://orcid.org/0000-0001-8539-9935)
- Jo Talbot
- Maria Bălăeţ (ORCID: https://orcid.org/0000-0002-0562-6139)
- Jenny Smith (ORCID: https://orcid.org/0000-0003-0405-0251)
- Peter John Hellyer (ORCID: https://orcid.org/0000-0002-5139-3401)
- Marcus S. Smith (ORCID: https://orcid.org/0000-0002-8990-6639)
Institutions
- University of Chichester (GB)
- Royal Society (GB)
- King's College London (GB)
- Imperial College London (GB)
Publication Details
- Journal
- International Journal of Industrial Ergonomics
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1016/j.ergon.2025.103741
- Citations
- 5
- Primary Topic
- Traffic and Road Safety
- Type
- article
- Field-Weighted Citation Impact
- 6.52