Swimming high-risk behavior is a key causative factor leading to adolescent drowning, which refers to risky behaviors with the risk of self-injury or other injuries performed by an individual or a group of individuals in an aquatic environment (World Health Organization, 2014). Data from the National Health Commission (NHC) show that approximately 56,000 adolescents lose their lives to drowning each year in China, and the loss of individual lives and socio-economic burden have become a major challenge in public health (UNICEF, 2009). For this reason, as of 2025, the Ministry of Education has issued special warning notices for 14 consecutive years to prevent possible swimming injuries (The State Council of the People’s Republic of China, 2025).

Extant research has identified several key factors that elevate drowning risk among adolescents. These commonly include a lack of supervision, overestimation of swimming ability, risk-taking tendencies, peer pressure, and swimming in unsafe environments. Understanding these foundational risk factors is crucial, as they directly manifest themselves in specific, observable high-risk behaviors.

Measurement of high-risk behaviors in swimming has gone through three phases: the initial exploratory phase (2006–2010), when Moran (2006) in New Zealand developed the first waterside high-risk behaviors scale in 2006, which assessed the risks associated with unsupervised solo swimming, ignoring safety instructions, and other supervisory deficits through 10 entries. In 2008, McCool et al. (2008) further refined the original scale with three entries specifically assessing adult swimming risk behaviors; later expanded by Morrongiello et al. (2010) in Canada to form a special measurement tool for adolescents’ at-risk swimming behaviors. The theoretical deepening phase (2012–2017) (Xia et al., 2012) achieved a breakthrough in measurement dimensions with the localized scale constructed based on the theory of knowing, believing, and acting. Petrass and Blitvich (2014) proposed the behavioral dichotomy to differentiate between misbehaviors and lapses in high-risk behaviors for the first time to promote the innovation of the theoretical framework, and Zhang et al. (2017) formed 10 subcategories of high-risk behaviors affecting students by rooting the coding of the interviews and further refined the Erroneous and lapsed behaviors further refined, and for the first inclusion of bad peer infractions in environmental factors occurred in; the systematic refinement phase (2019–2024), in which the peer influence model established by Luo et al. (2019) and the infraction subtypes revealed by the subsequent studies (Taiwo et al., 2024; Vannucci et al., 2020) together improved the behavioral taxonomy system.

Currently, the measurement tools for studying adolescents’ swimming high-risk behaviors are facing a double challenge: first, adolescents have always been the focus of the WHO initiative to intervene in high-risk groups, and swimming drowning accidents among adolescents in China are frequent, so a set of measurement tools suitable for adolescents’ swimming high-risk behaviors in China is urgently needed; and second, there is the lack of discriminant validity of the Swimming High-Risk Behavior Scale in the behavioral motivation dimensions (e.g., risk-taking tendency vs. aggressive violations). Therefore, the research group comprehensively considered the psychological and behavioral characteristics of adolescents in China and conducted interviews and surveys on adolescent swimming risky behaviors to develop a set of scientific and effective scales for adolescent swimming risky behaviors, which is of great significance for measuring adolescent swimming risky behaviors, identifying risky groups, and intervening accurately in advance.

The initial project library primarily originated from a qualitative study using grounded theory methodology, which constructed a model of factors influencing students’ high-risk behaviors in aquatic environments (Xia et al., 2012; Zhang et al., 2017). Subsequently, insights from systematic literature reviews and expert interviews supplemented and refined this foundational framework, ultimately yielding preliminary scale items for assessing high-risk swimming behaviors among adolescents (Koon et al., 2021; Petrass and Blitvich, 2014; Xia et al., 2018). The content validity test was carried out through the discussion of the research group and the consultation of experts (a total of five experts were invited to participate in the questionnaire completion process across the fields of water safety education, swimming rescue training, swimming instruction, physical education, and training). Among them, three are professors and doctoral advisors, one is an associate professor and master’s advisor, and one is a lecturer, focusing on the readability, meaning, logic, wording, and relevance of the scale entries, etc. The pre-testing scale of adolescent swimming high-risk behaviors was formed after repeated revisions and refinements, and the pre-survey was carried out after that. After that, a pre-survey was conducted, and the recovered data were analyzed through item analysis, exploratory factor analysis, and deletion of questions to form a formal scale; a formal test was conducted, and the formal scale was compiled after validation factor analysis and reliability and validity tests.

The construction of the four-dimensional structure for measuring adolescent swimming high-risk behavior, comprising wrong behavior, mistake behavior, general violation, and aggressive violation, represents the core theoretical innovation of this study. While grounded in established frameworks such as the theory of knowing, believing, and acting, this model moves beyond them by proposing a nuanced taxonomy that differentiates risk behaviors based on their underlying mechanisms: from unintentional cognitive errors (wrong behavior), which are linked to adolescents’ underestimation of risk related to the incomplete development of the prefrontal lobe (Pinson et al., 2021) and skill-based lapses (Mistake Behavior) that occur at a higher rate under stress, particularly in adolescents compared to adults (Hu et al., 2020; Causer et al., 2021), and are often due to a lack of ability or chance factors such as cramp handling (Moran and Gilmore, 2018; Moran et al., 2018), to intentional but non-malicious breaches (general violation), which are prevalent and significantly influenced by parental absence and the presence of peers (Ismail et al., 2021; Public Opinion Data Center of People’s Daily Online, 2022), and willfully harmful acts (aggressive violation), which are strongly predicted by externalizing problems and sensation-seeking (Olivier et al., 2020; Liao et al., 2021; de Ruijter et al., 2023), a trait that also amplifies the influence of undesirable peers (Luo et al., 2019). This granular classification addresses a critical gap in existing scales, which often lack such differentiation, and provides a more precise theoretical lens through which to understand how risky behaviors originate and escalate, including the neurodevelopmental perspective that prefrontal lobe development lag leads to risky decision-making bias (Hamilton et al., 2024).

The practical value of this four-dimensional framework lies in its direct applicability to targeted intervention. Distinguishing between error-based and violation-based behaviors enables the development of stratified prevention strategies. For instance, wrong and mistake behaviors may be best addressed through safety knowledge education and skill-based training, as they are tied to cognitive bias and operational error. In contrast, general and aggressive violations, which are strongly associated with social context, peer influence, and sensation-seeking, require interventions that modify subjective norms and enhance perceived behavioral control, an approach supported by the Theory of Planned Behavior’s efficacy in explaining behavioral intention (Cao et al., 2014). Moreover, the finding that prolonged uncorrected errors may evolve into habitual violations or even aggressive violations underscores the need for early and type-specific responses.

This study thus validates and extends existing theoretical research by offering a structured behavioral continuum that connects cognitive, behavioral, and social-ecological factors. It shifts the focus from generic drowning prevention to a differentiated intervention model, informed by the social-ecological model’s emphasis on the interaction of microsystem, mesosystem, and macrosystem factors (Van Wormer and Besthorn, 2017), in which families, schools, and policymakers can collaborate to address specific risk pathways with greater precision. In doing so, it establishes a new foundation for both measuring and mitigating swimming-related risks among adolescents in a theory-informed and empirically actionable manner.