Evidence map›Paper›PMID 25138312›Full record

SynthesisSports medicine (Auckland, N.Z.)2014

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

Nikos Ntoumanis, Johan Y Y Ng, Vassilis Barkoukis, Susan Backhouse

Abstract readMeta-AnalysisReview
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 6 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

100 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  3. Parental Influence on Child and Adolescent Physical Activity Level: A Meta-Analysis.International journal of environmental research and public health · 2022
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40 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Nikos NtoumanisHealth Psychology and Behavioural Medicine Research Group, School of Psychology and Speech Pathology, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia, Nikos.Ntoumanis@curtin.edu.au.
Johan Y Y Ng
Vassilis Barkoukis
Susan Backhouse

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere 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.

objectivesUsing 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

participantsStudies 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

methodStudy 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.

resultsUse 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.

conclusionsThis 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.

Indexed as

Health Knowledge, Attitudes, PracticeIntentionAge FactorsAthletesDietary SupplementsDoping in SportsFriendsHumansModels, TheoreticalMoralsPerformance-Enhancing SubstancesPsychological TheorySelf EfficacySex FactorsSocial NormsPerformance-Enhancing Substances

Identifiers

What OpenQuestion holds

Textmetadata
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.