Zusammenfassung

Abstract Background Understanding athletes' attitudes and behavioural intentions towards performance enhancement is critical to informing anti-doping intervention strategies. Capturing the complexity of these attitudes beyond verbal declarations requires indirect methods. This pilot study was aimed at developing and validating a method to assess implicit doping attitudes using an Implicit Associations Test (IAT) approach. Methods The conventional IAT evaluation task (categorising 'good' and 'bad' words) was combined with a novel 'doping' versus 'nutrition supplements' category pair to create a performance-enhancement related IAT protocol (PE-IAT). The difference between average response times to 'good-doping' and 'bad-doping' combinations represents an estimate of implicit attitude towards doping in relation to nutritional supplements. 111 sports and exercise science undergraduates completed the PE-IAT, the Performance Enhancement Attitude Scale (PEAS) and answered questions regarding their beliefs about doping. Results Longer response times were observed in the mixed category discrimination trials where categories 'good' and 'doping' shared the same response key (compared to 'bad-doping' combination on the same key) indicating a less favourable evaluation of doping substances. The PE-IAT measure did not correlate significantly with the declared doping attitudes ( r = .181, p = .142), indicating a predictable partial dissociation. Action-oriented self-report expressed stronger associations with PE-IAT: participants who declared they would consider using doping showed significantly less implicit negativity towards banned substances ( U = 109.00, p = .047). Similarly, those who reported more lenient explicit attitudes towards doping or expressly supported legalizing it, showed less implicit negativity towards doping in the sample, although neither observed differences reached statistical significance ( t = 1.300, p = .198, and U = 231.00, p = .319, respectively). Known-group validation strategy yielded mixed ...