Authors: William Koon, Andrew Schmidt, Ana Catarina Queiroga, Justin Sempsrott, David Szpilman, Jonathon Webber, Robert W. Brander.
What is the first thing that comes to mind when you think of beach lifeguards? A particular Hollywood theme song? A bronzed Aussie from Bondi Rescue saving someone from a rip current? How about… data collector?
Beach lifeguards, in addition to many other responsibilities, record lots of data related to their daily activities and beach conditions. This information not only guides beach safety operations but is also used by researchers who study beach hazards, drowning, and other injuries. Lifeguard data has been used in drowning research since the 1980s, and a few challenges have previously been identified. However, what and how that information is recorded hasn’t been formally examined until now.
As researchers involved in beach safety and drowning prevention, we have long been interested in high-quality data. Through increased international collaborations (thanks to organizations like IDRA!), we discovered that a common barrier to our projects was the varied data quality and collection practices that exist across lifeguard organizations. So, we set out to characterize how lifeguards around the world are recording information to identify where and how consistency can be improved in the future to drive data-driven, evidence-based practices.
Through an interconnected network of drowning prevention researchers, we surveyed 55 beach lifeguard leaders (i.e. chiefs, supervisors, managers) from 12 countries. We found two major themes:
- There is a wide range of data recording practices, including what data to record in the first place. From gathering information on beach conditions to recording beach attendance and logging important information about lifeguard activities such as rescues, what is collected, how it is defined, and the methods by which the record is made, varies.
- Challenges in lifeguard data collection include difficulties with staff training and diligence of employees to collect data, inconsistency in methodologies and definitions, and the operational time it takes for documentation. These challenges have led lifeguard leaders to express some levels of uncertainty regarding the accuracy of their data.
This led us to outline three broad areas for improvement:
- Development of standardized ‘case’ definitions for lifeguards
Evidence from the survey results underscored the need for consensus-based definitions of relevant lifeguard data terms. Lifeguard leaders reported multiple definitions of “rescue” in this survey. For many, physical assistance from a lifeguard delineates rescue from other activities, however, others count only the most serious events as rescues, using descriptors like “life-threatening” or “imminent peril”. Without standardization, comparisons between organizations become difficult and unreliable. Even our dataset fell victim to limitations from non-standardized definitions! Responses to our questions about rescues were dependent on the respondent’s interpretation. The result was information on incidents of varied severity and response, a mixed basket of apples and oranges. Defining relevant terms and identifying core and supplemental data variables to be collected (the effort to define ‘drowning’ might be one model to follow) could make lifeguards more efficient in their operations and greatly assist research activities.
- Recording of time-stamped lifeguard activity
Another important consideration for the lifeguard community is the recording of individual time-stamped lifeguard events, particularly rescues, in as near-real-time as possible. Individual records, as opposed to summary counts per day or per week, create richer datasets which allow for more robust research. Time-stamped records allow for linkage to other systems, such as hospital/ambulance records or weather/ocean monitoring systems, which is vital for hazard identification and evaluating beach factors with outcomes. Recording data in near-real-time, as opposed to at the end of the day, reduces reporting error due to recall bias which was a limitation to data accuracy identified by respondents from this survey.
- Transition from manual-based to technology-based data recording
New technology, and innovative uses of existing technology, has the potential to reduce documentation workload for lifeguards in the field, provide timely updates on activity for managers and decision-makers, and allow for seamless automatic linkage to other data systems, streamlining the two previous recommendations. While technological solutions are being implemented in Hawaii, California and Australia, standardization across the beach lifeguard industry, especially regarding case definitions, should remain a priority.
A far cry from Baywatch drama, beach lifeguards are highly skilled, mostly young, men and women who put themselves at risk to keep others safe. They work in dynamic environments most people are not equipped to handle (See this lifeguard rescue video and acquaint yourself with Ben Carlson or Ross and Andrew Powell if you have any preconceived notions about the seriousness of beach lifeguard work). On top of it all, they record important data that informs decisions and research related to safety and the environment. This project represents a first step in identifying areas where lifeguard data could be improved, with the ultimate goal of more effectively preventing drowning and other injuries on beaches.