A Psychometric Analysis of the Brief Self-Control Scale

Abstract

The Brief Self-Control Scale (BSCS) is a widely used measure of self-control, a construct associated with beneficial psychological outcomes. Several studies have investigated the psychometric properties of the BSCS but have failed to reach consensus. This has resulted in an unstable and ambiguous understanding of the scale and its psychometric properties. The current study sought resolution by implementing scale evaluation approaches guided by modern psychometric literature. Additionally, our goal was to provide a more comprehensive item analysis via the item response theory (IRT) framework. Results from the current study support both unidimensional and multidimensional factor structures for the 13-item version of the BSCS. The addition of an IRT analysis provided a new perspective on item- and test-level functioning. The goal of a more defensible psychometric grounding for the BSCS is to promote greater consistency, stability, and trust in future results.

Keywords

factor analysis item response theory brief self-control scale scale evaluation psychometrics

Get full access to this article

View all access options for this article.

References

Ackerman

T. A.

Gierl

M. J.

Walker

C. M.

(2003). Using multidimensional item response theory to evaluate educational and psychological tests. Educational Measurement: Issues and Practice, 22(3), 37-51. doi:10.1111/j.1745-3992.2003.tb00136.x

Babinski

Hartsough

Lambert

(1999). Childhood conduct problems, hyperactivity-impulsivity, and inattention as predictors of adult criminal activity. Journal of Child Psychology and Psychiatry, 40, 347-355.

Bock

R. D.

Mislevy

R. J.

(1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psycho-logical Measurement, 6, 431-444. doi:10.1177/014662168200600405

Brennan

G. M.

Baskin-Sommers

A. R.

(2018). Brain-behavior relationships in externalizing: P3 amplitude reduction reflects deficient inhibitory control. Behavioural Brain Research, 337, 70-79.

Browne

M. W.

Cudeck

(1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21, 230-258. doi:10.1177/0049124192021002005

Browne

M. W.

Cudeck

Tateneni

Mels

(2010). CEFA: Comprehensive exploratory factor analysis, version 3.04 [Computer software and manual]. Retrieved from https://psychology.osu.edu/dr-browne-software

Byrne

B. M.

(2005). Factor analytic models: Viewing the structure of an assessment instrument from three perspectives. Journal of Personality Assessment, 85, 17-32. doi:10.1207/s15327752jpa8501_02

Cai

(2017). flexMIRT version 3.51: Flexible multilevel multidimensional item analysis and test scoring. Chapel Hill, NC: Vector Psychometric Group.

Cai

(2010a). High-dimensional exploratory item factor analysis by a Metropolis-Hastings Robbins-Monro algorithm. Psychometrika, 75, 33-57. doi:10.1007/s11336-009-9136-x

10.

Cai

(2010b). Metropolis-Hastings Robbins-Monro algorithm for confirmatory item factor analysis. Journal of Educational and Behavioral Statistics, 35, 307-335. doi:10.3102/1076998609353115

11.

Chen

Thissen

(1997). Local dependence indexes for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22, 265-289.

12.

Christoffersson

(1975). Factor analysis of dichotomized variables. Psychometrika, 40, 5-32. doi:10.1007/BF02291477

13.

Cronbach

L. J.

(1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334. doi:10.1007/BF02310555

14.

Čubranić-Dobrodolac

Lipovac

Čičević

Antić

(2017). A model for traffic accidents prediction based on driver personality traits assessment. Promet (Zagreb), 29, 631-642.

15.

De Ayala

R. J

. (2008). The theory and practice of item response theory. New York, NY: Guilford Press.

16.

De Ridder

D. T. D.

De Boer

B. J.

Lugtig

Bakker

A. B.

Van Hooft

E. A. J

. (2011). Not doing bad things is not equivalent to doing the right thing: Distinguishing between inhibitory and initiatory self-control. Personality and Individual Differences, 50, 1006-1011. doi:10.1016/j.paid.2011.01.015

17.

DeVellis

R. F.

(2012). Scale development: Theory and applications. Thousand Oaks, CA: Sage.

18.

DeWalt

D. A.

Thissen

Stucky

B. D.

Langer

M. M.

Morgan DeWitt

Irwin

D. E.

. . . Varni

J. W.

(2013). PROMIS Pediatric Peer Relationships Scale: Development of a peer relationships item bank as part of social health measurement. Health Psychology, 32, 1093-1103. doi:10.1037/a0032670

19.

Edwards

M. C.

(2009). An introduction to item response theory using the Need for Cognition Scale. Social and Personality Psychology Compass, 3, 507-529. doi:10.1111/j.1751-9004.2009.00194.x

20.

Edwards

M. C.

Houts

C. R.

Cai

(2018). A diagnostic procedure to detect departures from local independence in item response theory models. Psychological Methods, 23, 138-149. doi:10.1037/met0000121

21.

Eisenberg

I. W.

Bissett

P. G.

Canning

J. R.

Dallery

Enkavi

A. Z.

Whitfield-Gabrieli

. . . Poldrack

R. A.

(2018). Applying novel technologies and methods to inform the ontology of self-regulation. Behaviour Research and Therapy, 101, 46-57. doi:10.1016/j.brat.2017.09.014

22.

Embretson

S. E.

Reise

S. P.

(2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum.

23.

Enkavi

A. Z.

Eisenberg

I. W.

Bissett

P. G.

Mazza

G. L.

MacKinnon

D. P.

Marsch

L. A.

Poldrack

R. A.

(2019). A large-scale analysis of test-retest reliabilities of self-regulation measures. Proceedings of the National Academy of Sciences of the United States of America, 116, 5472-5477. doi:10.1073/pnas.1818430116

24.

Fabrigar

L. R.

Wegener

D. T.

MacCallum

R. C.

Strahan

E. J.

(1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272-299. doi:10.1037/1082-989X.4.3.272

25.

Ferrari

J. R.

Stevens

E. B.

Jason

L. A.

(2009). The role of self-regulation in abstinence maintenance: Effects of communal living on self-regulation. Journal of Groups in Addiction & Recovery, 4, 32-41. doi:10.1080/15560350802712371

26.

Flora

D. B.

Curran

P. J.

(2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9, 466-491. doi:10.1037/1082-989X.9.4.466

27.

Follmer

D. J.

Sperling

R. A.

Suen

H. K.

(2017). The role of MTurk in education research: Advantages, issues, and future directions. Educational Researcher, 46, 329-334. doi:10.3102/0013189X17725519

28.

Horn

J. L.

(1965). A rationale and technique for estimating the number of factors in factor analysis. Psychometrika, 30, 179-185.

29.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. doi:10.1080/10705519909540118

30.

Lindner

Nagy

Retelsdorf

(2015). The dimensionality of the Brief Self-Control Scale: An evaluation of unidimensional and multidimensional applications. Personality and Individual Differences, 86, 465-473. doi:10.1016/j.paid.2015.07.006

31.

MacCallum

R. C.

Widaman

K. F.

Zhang

Hong

(1999). Sample size in factor analysis. Psychological Methods, 4, 84-99. doi:10.1037/1082-989X.4.1.84

32.

Maloney

P. W.

Grawitch

M. J.

Barber

L. K.

(2012). The multi-factor structure of the Brief Self-Control Scale: Discriminant validity of restraint and impulsivity. Journal of Research in Personality, 46, 111-115. doi:10.1016/j.jrp.2011.10.001

33.

McDonald

R. P.

(1970). The theoretical foundations of principal factor analysis, canonical factor analysis, and alpha factor analysis. British Journal of Mathematical and Statistical Psychology, 23, 1-21. doi:10.1111/j.2044-8317.1970.tb00432.x

34.

McNeish

(2018). Thanks coefficient alpha, we’ll take it from here. Psychological Methods, 23(3), 412-433.

35.

Monroe

Cai

(2015). Examining the reliability of student growth percentiles using multidimensional IRT. Educational Measurement: Issues and Practice, 34(4), 21-30. doi:10.1111/emip.12092

36.

Morean

M. E.

Demartini

K. S.

Leeman

R. F.

Pearlson

G. D.

Anticevic

Krishnan-Sarin

. . . O’Malley

S. S.

(2014). Psychometrically improved, abbreviated versions of three classic measures of impulsivity and self-control. Psychological Assessment, 26, 1003-1020. doi:10.1037/pas0000003

37.

Paolacci

Chandler

(2014). Inside the Turk: Understanding Mechanical Turk as a participant pool. Current Directions in Psychological Science, 23, 184-188. doi:10.1177/0963721414531598

38.

Patton

J. H.

Stanford

M. S.

Barratt

E. S.

(1995). Factor structure of the Barratt Impulsiveness Scale. Journal of Clinical Psychology, 51, 768-774. doi:10.1002/1097-4679(199511)51:6<768::AID-JCLP2270510607>3.0.CO;2-1

39.

Preston

K. S. J.

Gottfried

A. W.

Park

J. J.

Manapat

P. D.

Gottfried

A. E.

Oliver

P. H.

(2018). Simultaneous linking of cross-informant and longitudinal data involving positive family relationships. Educational and Psychological Measurement, 78, 409-429. doi:10.1177/0013164417690198

40.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

41.

Reckase

M. D.

(1997). The past and future of multidimensional item response theory. Applied Psychological Measurement, 21, 25-36. doi:10.1177/0146621697211002

42.

Reise

S. P.

Moore

T. M.

Sabb

F. W.

Brown

A. K.

London

E. D.

(2013). The Barratt Impulsiveness Scale-11: Reassessment of its structure in a community sample. Psychological Assess-ment, 25, 631-642. doi:10.1037/a0032161

43.

Rosseel

(2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. Retrieved from http://www.jstatsoft.org/v48/i02/

44.

Samejima

(1969). Estimation of latent ability using a response pattern of graded scores. (Psychometric Monograph No. 17). Richmond, VA: Psychometric Society. Retrieved from https://www.psychometricsociety.org/sites/default/files/pdf/MN17.pdf

45.

Sharma

Markon

K. E.

Clark

L. A.

(2014). Toward a theory of distinct types of “impulsive” behaviors: A meta-analysis of self-report and behavioral measures. Psychological Bulletin, 140, 374-408.

46.

Sijtsma

(2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74, 107-120. doi:10.1007/s11336-008-9101-0

47.

Tangney

J. P.

Baumeister

R. F.

Boone

A. L.

(2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271-324. doi:10.1111/j.0022-3506.2004.00263.x

48.

Thissen

Steinberg

(2009). Item response theory. In Millsap

R. E.

Maydeu-Olivares

(Eds.), The SAGE handbook of quantitative methods in psychology (pp. 148-177). London, England: Sage.

49.

Thissen

Wainer

(2001). Test scoring. Mahwah, NJ: Lawrence Erlbaum.

50.

Thurstone

L. L.

(1947). Multiple factor analysis. Chicago, IL: University of Chicago Press.

51.

Venables

N. C.

Foell

Yancey

J. R.

Kane

M. J.

Engle

R. W.

Patrick

C. J.

(2018). Quantifying inhibitory control as externalizing proneness: A cross-domain model. Clinical Psychological Science, 6, 561-580. doi:10.1177/2167702618757690

52.

Wirth

R. J.

Edwards

M. C.

(2007). Item factor analysis: Current approaches and future directions. Psychological Methods, 12, 58-79. doi:10.1037/1082-989X.12.1.58

53.

Zhang

Yuan

K.-H.

(2015). coefficientalpha: Robust coefficient alpha and omega with missing and non-normal data (R package version 0.5) [Computer software]. Retrieved from https://CRAN.R-project.org/package=coefficientalpha