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Open Access Hypothesis

Psychological drivers in doping: The life-cycle model of performance enhancement

Andrea Petróczi1* and Eugene Aidman2

Author Affiliations

1 Kingston University, Faculty of Science, School of Life Sciences, Penrhyn Road, Kingston upon Thames, Surrey, KT1 2EE, UK

2 University of Adelaide, School of Psychology, North Terrace Campus, SA 5005, Australia

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Substance Abuse Treatment, Prevention, and Policy 2008, 3:7  doi:10.1186/1747-597X-3-7

Published: 10 March 2008

Abstract

Background

Performance enhancement (PE) is a natural and essential ingredient of competitive sport. Except for nutritional supplement contamination, accidental use of doping is highly unlikely. It requires deliberation, planning and commitment; and is influenced by a host of protective and risk factors.

Hypothesis

In the course of their career, athletes constantly set goals and make choices regarding the way these goals can be achieved. The cycle of choice – goal commitment – execution – feedback on goal attainment – goal evaluation/adjustment has numerous exit points, each providing an opportunity for behaviour change, which may or may not be related to the use of prohibited methods. The interplay between facilitating and inhibiting systemic and personality factors, constantly influenced by situational factors could result in an outcome vector of 'doping attitudes', which combines with subjective norms to influence intentions to choose prohibited PE methods. These influences also vary from one stage of athlete development to the next, making some athletes more vulnerable to engaging in doping practices than others, and more vulnerable at certain time periods – and not others.

Testing the hypothesis

Model-testing requires a series of carefully planned and coordinated studies. Correlational studies can establish relationships where the directionality is not-known or not important. Experimental studies with the manipulation of doping expectancies and risk factors can be used to demonstrate causality and evaluate potential intervention strategies. The final model can be tested via a behavioural simulation, with outcomes compared to those expected from literature precedence or used as a simulated computer game for empirical data collection.

Implications

A hypothesized life-cycle model of PE identifies vulnerability factors across the stages of athlete development with the view of informing the design of anti-doping assessment and intervention. The model suggests that, instead of focusing on the actual engagement in prohibited PE practices, deterrence strategies are likely to be more effective if they target the influencing factors at the appropriate stage and identify groups of athletes and their respective career stages, which pose particular risks of engagement in doping practices. This enables a more effective intervention approach by targeting specific risk factors and expectancies.