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Methodological considerations regarding response bias effect in substance use research: is correlation between the
Andrea Petróczi1, Tamás Nepusz
1Kingston University, Faculty of Science, School of Life Sciences, Penrhyn Road, Kingston upon Thames, Surrey, KT1 2EE, UK. A.Petroczi@kingston.ac.uk
Substance Abuse Treatment, Prevention, and Policy
|January 20, 2011
Summary
Socially desirable responding (SD) significantly distorts doping research, even when correlations appear weak. Standard correlation analysis is insufficient; structural equation modeling reveals SD
Area of Science:
- Sport Psychology
- Anti-Doping Research
- Social Psychology
Background:
- Anti-doping efforts increasingly focus on behavioral determinants and prevention programs.
- Self-report questionnaires are the primary method for psychological and sociological assessments in doping research.
- The impact of socially desirable responding (SD) on doping research is often overlooked or underestimated.
Purpose of the Study:
- To highlight the potential distorting effects of socially desirable responding (SD) in doping research.
- To demonstrate the limitations of using simple correlation analysis to assess SD's influence.
- To evaluate SD's effect at both indicator and construct levels within doping opinion models.
Main Methods:
- Structural equation modeling (SEM) was employed to test doping opinion models.
- Models were analyzed with and without the socially desirable responding (SD) variable.
- A dataset of 278 athletes was used, with participants categorized into high- and low-SD groups.
Main Results:
- While low correlations (<|0.22|) were observed between SD and indicator variables in the overall sample, SD significantly improved model fit.
- Regression weights varied between high- and low-SD groups, indicating differential effects.
- The study demonstrated the inadequacy of pairwise correlation for assessing SD at a model level.
Conclusions:
- Socially desirable responding (SD) demonstrably affects doping research outcomes.
- Standard correlation analyses are insufficient for evaluating the impact of SD in complex models.
- Future anti-doping research relying on self-reported data must appropriately assess and control for SD effects.
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