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

doi:10.1080/00223891.2020.1732994

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

Quantitative Health Sciences

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	238-245
Number of pages	8
Journal	Journal of Personality Assessment
Volume	103
Issue number	2
DOIs	https://doi.org/10.1080/00223891.2020.1732994
State	Published - 2021

ASJC Scopus subject areas

Clinical Psychology
Psychiatry and Mental health
Health, Toxicology and Mutagenesis

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Mazza, G. L., Smyth, H. L., Bissett, P. G., Canning, J. R., Eisenberg, I. W., Enkavi, A. Z., Gonzalez, O., Kim, S. J., Metcalf, S. A., Muniz, F., Pelham, W. E., Scherer, E. A., Valente, M. J., Xie, H., Poldrack, R. A., Marsch, L. A., & MacKinnon, D. P. (2021). Correlation Database of 60 Cross-Disciplinary Surveys and Cognitive Tasks Assessing Self-Regulation. Journal of Personality Assessment, 103(2), 238-245. https://doi.org/10.1080/00223891.2020.1732994

Mazza, GL, Smyth, HL, Bissett, PG, Canning, JR, Eisenberg, IW, Enkavi, AZ, Gonzalez, O, Kim, SJ, Metcalf, SA, Muniz, F, Pelham, WE, Scherer, EA, Valente, MJ, Xie, H, Poldrack, RA, Marsch, LA & MacKinnon, DP 2021, 'Correlation Database of 60 Cross-Disciplinary Surveys and Cognitive Tasks Assessing Self-Regulation', Journal of Personality Assessment, vol. 103, no. 2, pp. 238-245. https://doi.org/10.1080/00223891.2020.1732994

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abstract = "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.",

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

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year = "2021",

doi = "10.1080/00223891.2020.1732994",

language = "English (US)",

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AU - Smyth, Heather L.

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AU - Eisenberg, Ian W.

AU - Enkavi, A. Zeynep

AU - Gonzalez, Oscar

AU - Kim, Sunny Jung

AU - Metcalf, Stephen A.

AU - Muniz, Felix

AU - Pelham, William E.

AU - Scherer, Emily A.

AU - Valente, Matthew J.

AU - Xie, Haiyi

AU - Poldrack, Russell A.

AU - Marsch, Lisa A.

AU - MacKinnon, David P.

PY - 2021

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AB - 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.

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

Abstract

ASJC Scopus subject areas

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