Personal and psychosocial predictors of doping use in physical activity settings: a meta-analysis.

BACKGROUND There is a growing body of empirical evidence on demographic and psychosocial predictors of doping intentions and behaviors utilizing a variety of variables and conceptual models. However, to date there has been no attempt to quantitatively synthesize the available evidence and identify the strongest predictors of doping. OBJECTIVES Using meta-analysis, we aimed to (i) determine effect sizes of psychological (e.g. attitudes) and social-contextual factors (e.g. social norms), and demographic (e.g. sex and age) variables on doping intentions and use; (ii) examine variables that moderate such effect sizes; and (iii) test a path analysis model, using the meta-analyzed effect sizes, based on variables from the theory of planned behavior (TPB). DATA SOURCES Articles were identified from online databases, by contacting experts in the field, and searching the World Anti-Doping Agency website. STUDY ELIGIBILITY CRITERIA AND PARTICIPANTS Studies that measured doping behaviors and/or doping intentions, and at least one other demographic, psychological, or social-contextual variable were included. We identified 63 independent datasets. STUDY APPRAISAL AND SYNTHESIS METHOD Study information was extracted by using predefined data fields and taking into account study quality indicators. A random effects meta-analysis was carried out, correcting for sampling and measurement error, and identifying moderator variables. Path analysis was conducted on a subset of studies that utilized the TPB. RESULTS Use of legal supplements, perceived social norms, and positive attitudes towards doping were the strongest positive correlates of doping intentions and behaviors. In contrast, morality and self-efficacy to refrain from doping had the strongest negative association with doping intentions and behaviors. Furthermore, path analysis suggested that attitudes, perceived norms, and self-efficacy to refrain from doping predicted intentions to dope and, indirectly, doping behaviors. LIMITATIONS Various meta-analyzed effect sizes were based on a small number of studies, which were correlational in nature. This is a limitation of the extant literature. CONCLUSIONS This review identifies a number of important correlates of doping intention and behavior, many of which were measured via self-reports and were drawn from an extended TPB framework. Future research might benefit from embracing other conceptual models of doping behavior and adopting experimental methodologies that will test some of the identified correlates in an effort to develop targeted anti-doping policies and programs.