Correlation Database of 60 Cross-Disciplinary Surveys and Cognitive Tasks Assessing Self-Regulation

Gina L. Mazza, Heather L. Smyth, Patrick G. Bissett, Jessica R. Canning, Ian W. Eisenberg, A. Zeynep Enkavi, Oscar Gonzalez, Sunny Jung Kim, Stephen A. Metcalf, Felix Muniz, William E. Pelham, Emily A. Scherer, Matthew J. Valente, Haiyi Xie, Russell A. Poldrack, Lisa A. Marsch, David P. MacKinnon

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Self-regulation is studied across various disciplines, including personality, social, cognitive, health, developmental, and clinical psychology; psychiatry; neuroscience; medicine; pharmacology; and economics. Widespread interest in self-regulation has led to confusion regarding both the constructs within the nomological network of self-regulation and the measures used to assess these constructs. To facilitate the integration of cross-disciplinary measures of self-regulation, we estimated product-moment and distance correlations among 60 cross-disciplinary measures of self-regulation (23 self-report surveys, 37 cognitive tasks) and measures of health and substance use based on 522 participants. The correlations showed substantial variability, though the surveys demonstrated greater convergent validity than did the cognitive tasks. Variables derived from the surveys only weakly correlated with variables derived from the cognitive tasks (M =.049, range =.000 to.271 for the absolute value of the product-moment correlation; M =.085, range =.028 to.241 for the distance correlation), thus challenging the notion that these surveys and cognitive tasks measure the same construct. We conclude by outlining several potential uses for this publicly available database of correlations.

Original languageEnglish (US)
Pages (from-to)238-245
Number of pages8
JournalJournal of Personality Assessment
Issue number2
StatePublished - 2021

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health
  • Health, Toxicology and Mutagenesis


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