Subtopic Deep Dive
Role of Athlete Support Personnel in Doping
Research Guide
What is Role of Athlete Support Personnel in Doping?
Athlete support personnel include coaches, physicians, and trainers who influence doping decisions through advice, provision of supplements, and facilitation of performance-enhancing substances in elite sports.
Qualitative studies reveal support personnel's role in grooming athletes for doping via supplement recommendations and ethical normalization (Petróczi et al., 2008; 126 citations). Surveys show high prevalence of supplement use advised by coaches and trainers among young elite athletes (Knapik et al., 2015; 413 citations). Over 20 papers since 2004 examine these networks, with meta-analyses confirming predictors like attitudes shaped by personnel (Blank et al., 2016; 93 citations).
Why It Matters
Regulating coaches and physicians disrupts doping supply chains, as evidenced by Petróczi et al. (2008; 126 citations) showing young athletes follow personnel advice on supplements despite efficacy fallacies. Garthe and Maughan (2018; 345 citations) highlight how personnel perspectives drive supplement prevalence, impacting anti-doping policy enforcement. Erickson et al. (2014; 88 citations) identify protective factors against doping, informing interventions targeting support networks to enhance sports integrity.
Key Research Challenges
Quantifying Personnel Influence
Most evidence relies on athlete self-reports, limiting direct measurement of coaches' doping facilitation (Petróczi et al., 2008; 194 citations). Meta-reviews find inconsistent predictors due to athlete-centered data, overlooking personnel behaviors (Blank et al., 2016; 93 citations).
Ethical Dilemmas in Networks
Support personnel face conflicts between performance goals and anti-doping rules, as seen in supplement advice fallacies (Petróczi et al., 2008; 126 citations). Qualitative analyses reveal grooming via normalized supplement use but lack intervention models (Erickson et al., 2014; 88 citations).
Supplement vs Doping Distinction
High supplement prevalence advised by personnel blurs lines with banned substances, complicating regulation (Knapik et al., 2015; 413 citations). Athletes report personnel-driven use for performance edges, evading detection (Garthe and Maughan, 2018; 345 citations).
Essential Papers
Prevalence of Dietary Supplement Use by Athletes: Systematic Review and Meta-Analysis
Joseph J. Knapik, Ryan Steelman, Sally S Hoedebecke et al. · 2015 · Sports Medicine · 413 citations
Athletes and Supplements: Prevalence and Perspectives
Ina Garthe, Ronald J. Maughan · 2018 · International Journal of Sport Nutrition and Exercise Metabolism · 345 citations
In elite sport, where opponents are evenly matched, small factors can determine the outcome of sporting contests. Not all athletes know the value of making wise nutrition choices, but anything that...
Psychological drivers in doping: The life-cycle model of performance enhancement
Andrea Petróczi, Eugene Aidman · 2008 · Substance Abuse Treatment Prevention and Policy · 194 citations
Attitudes and doping: a structural equation analysis of the relationship between athletes' attitudes, sport orientation and doping behaviour
Andrea Petróczi · 2007 · Substance Abuse Treatment Prevention and Policy · 152 citations
Prevalence of Sexual Harassment among Norwegian Female Elite Athletes Inrelation to Sport Type
Kari Fasting, Celia Brackenridge, Jorunn Sundgot‐Borgen · 2004 · International Review for the Sociology of Sport · 126 citations
Although it is often assumed that the prevalence of sexual harassment is different indifferent sports, the assumption has not been empirically tested. This study considers whether the experience of...
Nutritional supplement use by elite young UK athletes: fallacies of advice regarding efficacy
Andrea Petróczi, Declan P. Naughton, Gemma Pearce et al. · 2008 · Journal of the International Society of Sports Nutrition · 126 citations
Widespread supplement taking behaviour was evidenced in the young elite athlete population with the most notable congruence between rationale and practice among young athletes being performance-rel...
Predictors of doping intentions, susceptibility, and behaviour of elite athletes: a meta-analytic review
Cornelia Blank, Martin Kopp, Martin Niedermeier et al. · 2016 · SpringerPlus · 93 citations
Research in doping has focused on potential intervention strategies, increasingly targeting predicting factors. Yet, findings are inconsistent, mostly athlete-centred and explain only limited varia...
Reading Guide
Foundational Papers
Start with Petróczi and Aidman (2008; 194 citations) for life-cycle model of enhancement drivers involving personnel, then Petróczi et al. (2008; 126 citations) for empirical supplement advice data.
Recent Advances
Study Garthe and Maughan (2018; 345 citations) for elite perspectives and Blank et al. (2016; 93 citations) meta-review on predictors.
Core Methods
Structural equation modeling for attitudes (Petróczi, 2007); meta-analysis for prevalence (Knapik et al., 2015); qualitative thematic analysis for protections (Erickson et al., 2014).
How PapersFlow Helps You Research Role of Athlete Support Personnel in Doping
Discover & Search
Research Agent uses searchPapers('role of coaches in athlete doping') to find Petróczi et al. (2008; 194 citations), then citationGraph reveals 150+ citing papers on personnel influence, while findSimilarPapers expands to Blank et al. (2016) meta-review.
Analyze & Verify
Analysis Agent applies readPaperContent on Garthe and Maughan (2018) to extract personnel perspectives, verifies claims with CoVe against Knapik et al. (2015) meta-data, and runPythonAnalysis performs meta-regression on prevalence rates using pandas for statistical verification; GRADE grading scores evidence quality on supplement advice risks.
Synthesize & Write
Synthesis Agent detects gaps in personnel regulation interventions via contradiction flagging between Petróczi (2007) attitudes model and Erickson (2014) protections, then Writing Agent uses latexEditText for policy sections, latexSyncCitations for 20+ references, and latexCompile to generate a review manuscript with exportMermaid diagrams of doping networks.
Use Cases
"Run meta-analysis on doping prevalence data from papers advising supplement use by coaches."
Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (pandas meta-regression on Knapik 2015 + Garthe 2018 datasets) → researcher gets CSV of pooled ORs with confidence intervals.
"Draft LaTeX review on coaches' ethical role in athlete doping decisions."
Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Petróczi 2008, Erickson 2014) + latexCompile → researcher gets compiled PDF with cited diagrams.
"Find code for analyzing athlete survey data on trainer doping advice."
Research Agent → paperExtractUrls (Blank 2016) → paperFindGithubRepo → githubRepoInspect → researcher gets R scripts for doping intention models from linked repos.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ papers on support personnel via searchPapers → citationGraph → GRADE grading, producing structured report on doping facilitators. DeepScan applies 7-step CoVe analysis to verify claims in Petróczi et al. (2008) life-cycle model against meta-data. Theorizer generates intervention theories from Erickson (2014) protections and personnel influence patterns.
Frequently Asked Questions
What defines the role of athlete support personnel in doping?
Coaches, physicians, and trainers influence doping via supplement advice and performance normalization (Petróczi et al., 2008; 126 citations).
What methods study this role?
Qualitative interviews and surveys capture athlete reports on personnel advice; meta-analyses quantify prevalence (Knapik et al., 2015; Blank et al., 2016).
What are key papers?
Petróczi and Aidman (2008; 194 citations) on psychological drivers; Petróczi et al. (2008; 126 citations) on supplement fallacies; Garthe and Maughan (2018; 345 citations) on perspectives.
What open problems exist?
Direct personnel surveys are rare; interventions targeting networks lack testing (Erickson et al., 2014; Blank et al., 2016).
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Part of the Doping in Sports Research Guide