Evidence map›Paper›PMID 18331645›Full record

ArticleSubstance abuse treatment, prevention, and policy2008

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

Andrea Petróczi, Eugene Aidman

Abstract read
In one paragraph

Article in Substance abuse treatment, prevention, and policy, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Andrea PetrócziKingston University, Faculty of Science, School of Life Sciences, Penrhyn Road, Kingston upon Thames, Surrey, KT1 2EE, UK. a.petroczi@kingston.ac.uk
Eugene Aidman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerformance 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.

Indexed as

Models, TheoreticalAthletic PerformanceDecision MakingDoping in SportsFeedback, PsychologicalGoalsHumans

Identifiers

PMID18331645
PMCPMC2315642

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.