Integrating and Differentiating Aspects of Self-Regulation: Effortful Control, Executive Functioning, and Links to Negative Affectivity

Integrating and Differentiating Aspects of Self-Regulation: Effortful

Control, Executive Functioning, and Links to Negative Affectivity

David J. Bridgett, Kate B. Oddi, Lauren M. Laake, Kyle W. Murdock, and Melissa N. Bachmann

Northern Illinois University

Subdisciplines within psychology frequently examine self-regulation from different frameworks despite

conceptually similar definitions of constructs. In the current study, similarities and differences between

effortful control, based on the psychobiological model of temperament (Rothbart, Derryberry, & Posner,

1994), and executive functioning are examined and empirically tested in three studies (n ⫽ 509).

Structural equation modeling indicated that effortful control and executive functioning are strongly

associated and overlapping constructs (Study 1). Additionally, results indicated that effortful control is

related to the executive function of updating/monitoring information in working memory, but not

inhibition (Studies 2 and 3). Study 3 also demonstrates that better updating/monitoring information in

working memory and better effortful control were uniquely linked to lower dispositional negative affect,

whereas the executive function of low/poor inhibition was uniquely associated with an increased

tendency to express negative affect. Furthermore, dispositional negative affect mediated the links

between effortful control and, separately, the executive function of updating/monitoring information in

working memory and the tendency to express negative affect. The theoretical implications of these

findings are discussed, and a potential framework for guiding future work directed at integrating and

differentiating aspects of self-regulation is suggested.

Keywords: executive function, emotion regulation, temperament, effortful control, negative affect,

working memory

Self-regulation broadly refers to the ability to regulate behavior,

emotion, and cognition (Karoly, 1993). Across many domains,

self-regulation has been identified as a contributor to adaptive and

adverse outcomes in children, adolescents, and adults. For exam-

ple, children’s self-regulation has been implicated in developmen-

tal psychopathology (e.g., Nigg, 2000; Dahl & Conway, 2009),

with compromised self-regulation placing children and adolescents

at risk for externalizing problems (e.g., Bridgett, Valentino, &

Hayden, In Press; Eisenberg, Spinrad, & Eggum, 2010). In adult-

hood, poor self-regulation has been implicated in depressive and

anxiety disorders (e.g., Airaksinen, Larsson, & Forsell, 2005;

Carver, Johnson, & Joorman, 2008). Other studies have noted

connections between self-regulation and obesity (e.g., Gunstad,

Paul, Cohen, Tate, Spitznagel, & Gordon, 2007), sexual risk taking

behaviors, and substance abuse (e.g., Crockett, Raffaelli, & Shen,

2006; Quinn & Kim, 2010). On the other hand, better self-

regulation has been linked with children’s increased social com-

petence (e.g., Eisenberg et al., 1997; Spinrad et al., 2006), and in

young adults, with more intimate interpersonal relationships and

higher self-esteem (e.g., Busch & Hofer, 2012). Additionally,

better caregiver self-regulation has been associated with parenting

practices that promote improved outcomes for children (e.g.,

Bridgett et al., 2011; Deater-Deckard, Sewell, Petrill, & Thomp-

son, 2010). In sum, prior work highlights the importance of self-

regulation for understanding a wide range of human behaviors.

Although self-regulation has been implicated in numerous out-

comes, different subdisciplines within the field of psychology

frequently approach the study of self-regulation from diverse

frameworks. For example, developmental investigators frequently

study self-regulation from a temperament framework using mea-

sures of effortful control (Rothbart, Derryberry, & Posner, 1994;

Rothbart, Ellis, & Posner, 2011; Rueda, Posner, & Rothbart,

2005), whereas clinical, cognitive, and neuroscience investigators

frequently study self-regulation from an executive function (EF)

framework (Blair & Ursache, 2011; Gyurak et al., 2009). Despite

conceptual overlap between effortful control and executive func-

tioning some investigators have argued for a distinction between

them. For example, Blair and Ursache (2011; See also Blair &

Razza, 2007; Liew, 2012) argue that executive attention, the net-

work underlying effortful control, involves quick, automatic pro-

Throughout we use EF to refer to executive function and EFs to refer

to executive functions, depending on the context.

This article was published Online First August 20, 2012.

David J. Bridgett, Kate B. Oddi, Lauren M. Laake, Kyle W. Murdock,

and Melissa N. Bachmann, Department of Psychology, Northern Illinois

University.

We acknowledge the numerous research assistants whose many hours of

data collection and processing were instrumental in the completion of these

studies. The efforts made by Brittney Keilman-Wyatt, Katie Laws, Amy

Kaitschuck, Katherine Siler, Sarah Vadnais, Lauren Rodman, and Minh

Tran are particularly noteworthy. Finally, we gratefully acknowledge Sam-

uel Putnam, M. Christine Lovejoy, and Brad Sagarin for their thoughtful

comments on earlier versions of the final manuscript.

Correspondence concerning this article should be addressed to David J.

Bridgett, Department of Psychology, Emotion Regulation & Temperament

Laboratory, Psychology-Computer Science Building Rm. 400, Northern

Illinois University, DeKalb, IL 60115. E-mail: [email protected]

2013, Vol. 13, No. 1, 47–63 1528-3542/13/$12.00 DOI: 10.1037/a0029536

cesses whereas EF involves slower, more effortful and deliber-

ate processes. Other investigators have argued that there is

substantial overlap between effortful control and EF. For in-

stance, some have noted that specific EFs, such as working

memory, are carried out by the same networks in the brain that

comprise the executive attention network (e.g., Rueda, Posner,

& Rothbart, 2011). Some investigators have even suggested that

effortful control and EF largely overlap and have recently

called for integrated approaches to the study of self-regulation

(Zhou, Chen, & Main, 2012).

Although there are diverse opinions regarding the conceptual

differences or similarities between effortful control and EF, there

are relatively few empirical tests examining the interrelatedness of

these constructs, which are needed as important next steps in

refining self-regulation at the construct, conceptual, and theoretical

levels. Therefore, in the current investigation, we present three

studies, each using structural equation modeling to test associa-

tions between effortful control and EF. In the third study we also

examine links between effortful control, EFs, and the experience

and expression of negative affect.

Conceptual Underpinnings

Effortful control has been defined as the ability to inhibit a

dominant, prepotent response to perform a subdominant, less sa-

lient response and to detect errors (Rothbart & Bates, 2006).

Consistent with its origins in Rothbart and colleagues’ (Rothbart,

Derryberry, & Posner, 1994) psychobiological model of tempera-

ment, effortful control has been widely examined in the develop-

mental literature. From the psychobiological framework, temper-

ament is defined as constitutionally based individual differences in

the domains of reactivity, including emotional reactivity, and

regulation (i.e., processes that modulate reactivity), that are influ-

enced across time by aspects of the environment, heredity, and

maturation (Rothbart & Derryberry, 1981). Effortful control rep-

resents the self-regulatory aspect within the psychobiological

model, and serves to modulate reactivity (i.e., emotion) and be-

havior. Conceptually, effortful control broadly encompasses the

abilities to focus attention and to activate and inhibit behavior

when necessary. Although the precise composition of the

higher-order factor of effortful control varies slightly across

ages, studies examining the factor structure of effortful control

have found that the higher-order construct frequently consists

of attention shifting, activation control, effortful attention,

and/or inhibitory control (Evans & Rothbart, 2007; Putnam,

Gartstein, & Rothbart, 2006). Consistent with conceptual de-

scriptions of effortful control as a singular construct, these

factor analytic findings, as well as similar research using be-

havioral measures of effortful control (e.g., Sulik et al., 2010),

suggest that effortful control is a unitary construct on the basis

that all subcomponents load together on a single factor.

EF reflects higher-level cognitive processes, identified as being

important for the self-regulation of behavior and emotion (Gyurak

et al., 2009; Patrick, Blair, & Maggs, 2008), which help individ-

uals engage in organized, goal-oriented behavior (Friedman et al.,

2008; McCabe, Roediger, McDaniel, Balota, & Hambrick, 2010;

Miyake et al., 2000). Despite the recognized importance of exec-

utive functioning for self-regulation, there has been debate as to

the best characterization of EF, with two views consistently emerg-

ing. Some investigators have conceptualized EF as a unitary con-

struct (e.g., Baddeley, 1998), emphasizing a central executive, or

executive control system that guides behavior and cognition, and

directs attentional resources (Baddeley, 2003; Norman & Shallice,

1986). However, other investigators, on the basis of factor analytic

work, have noted that executive functioning is comprised of dis-

tinct, but interrelated processes (Miyake et al., 2000). Conceptu-

alizations of EFs as a finite set of interrelated processes have

typically noted three core components: shifting, inhibition, and

updating/monitoring information in working memory. Shifting

represents the ability to flexibly reallocate attention between mul-

tiple tasks or mental sets, whereas inhibition is the ability to inhibit

a dominant, overlearned response in favor of a less dominant

response. Finally, updating/monitoring information in working

memory consists of the abilities to monitor and code new infor-

mation and then to actively mentally manipulate such information,

including integrating new information with prior information, as

needed to accomplish a given task (Miyake et al., 2000). Both

models of EF have received support in the literature.

Based on conceptual descriptions of effortful control and EF

there is broad similarity between these constructs. At a finer-

grained level, effortful control closely resembles characterizations

of the EF of inhibition. Furthermore, the executive attention net-

work, which underlies effective effortful control, has been de-

scribed as being responsible for monitoring and resolving conflicts

(e.g., Rueda et al., 2011), which resembles descriptions of the EF

of updating/monitoring information in working memory. Simi-

larly, factor analytic work has also identified effortful control

subcomponents, such as effortful attention (i.e., the ability to

allocate and focus attentional resources), which also resembles

descriptions of the EF of updating/monitoring information in

working memory. However, one conceptual difference does

emerge. Whereas effortful control is considered to be a unitary

construct, some models of EF emphasize distinct, but interrelated

processes.

Neurobiological Substrates

Rothbart, Posner, and colleagues (e.g., Rothbart, Sheese, &

Posner, 2007) have noted that effortful control is under the influ-

ence of the executive attention network. Neuroimaging work in-

dicates that tasks requiring executive attention activate a common

brain network (i.e., the executive attention network) consisting of

the anterior cingulate gyrus and areas in the prefrontal cortex

(Botvinick, Nystrom, Fissell, Carter, & Cohen, 1999; Fan, Flom-

baum, McCandliss, Thomas, & Posner, 2003). Like efforts to

characterize the neurobiological mechanisms of effortful control,

there has been considerable interest in the biological mechanisms

underlying EF. As with effortful control, the anterior cingulate

gyrus and areas in the prefrontal cortex have been implicated in

executive functioning (Koechlin & Summerfield, 2007; Lenarto-

wicz, & McIntosh, 2005; de Pisapia & Braver, 2006).

Two lines of genetic research also support similarities between

EF and effortful control. First, behavioral-genetic investigations

have pointed to substantial genetic contributions to both executive

attention and effortful control (Lemery-Chalfant, Doelger, &

Goldsmith, 2008; Yamagata, Takahashi, Kijima, Maekawa, Ono,

& Ando, 2005), as well as EFs (e.g., Friedman et al., 2008),

supporting the genetic origins of these constructs. Second, molec-

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

ular genetic investigations have also identified similar genetic

links, such as the dopamine D4 receptor gene, that contribute to

effortful control (e.g., Fan, Fossella, Sommer, & Posner, 2003) as

well as to performance during EF tasks requiring inhibition

(e.g., Barnes, Dean, Nandam, O’Connell, & Bellgrove, 2011).

Likewise, other studies have noted that the catechol-o-methyl

transferase gene contributes to the functioning of the executive

attention network that underlies effortful control (e.g., Blasi et

al., 2005) and to performance during tasks requiring working

memory (e.g., Krug et al., 2009). Collectively, neurobiological

and genetic evidence suggests notable similarities between ef-

fortful control and EFs.

Developmental Course

The executive attention network and effortful control come

online at the end of the first year of life (Rothbart, Sheese, Rueda,

& Posner, 2011), with earlier attentional processes supporting their

emergence (e.g., Bridgett et al., 2011; Gartstein, Bridgett, Young,

Pankseep, & Power, In Press). By 18 to 24 months of age, effortful

control can be measured using questionnaires (e.g., Gartstein,

Bridgett, & Low, In Press; Putnam et al., 2006) and structured

laboratory tasks (e.g., Kochanska, Murray, & Harlan, 2000). Sub-

sequently, young children’s effortful control improves steadily

between early toddlerhood and preschool age (e.g., Chang &

Burns, 2005), with continued improvement of children’s effort-

ful control into the school-age years and beyond (e.g., Lengua,

2006). Similarly, EFs appear to have a protracted developmen-

tal course beginning in early childhood and extending into

adulthood (Best, Miller, & Jones, 2009; Bridgett & Mayes,

2011; Huizinga, Dolan, & van der Molen, 2006; Prencipe,

Kesek, Cohen, Lamm, Lewis, & Zelazo, 2011; Williams, Pon-

esse, Schachar, Logan, & Tannock, 1999). Thus, EFs and

effortful control appear to share similar developmental trajec-

tories.

Outcomes/Correlates

In addition to other parallels (e.g., conceptual, neurobiological,

and developmental), EFs and effortful control have consistently

been associated with similar outcomes. For example, both self-

regulation constructs have been associated with externalizing and

internalizing problems as well as academic achievement (e.g.,

Brock, Rimm-Kaufman, Nathanson, & Grimm, 2009; Eisenberg et

al., 2009; Hofer, Eisenberg, & Reiser, 2010; Hughes & Ensor,

2011; Murray & Kochanska, 2002; Valiente, Lemery-Chalfant,

Swanson, & Reiser, 2008). Effortful control and EFs are also

important for the effective regulation of emotion. Studies have

consistently noted negative associations between effortful control,

including attentional precursors of effortful control, and disposi-

tional negative affectivity (e.g., Bridgett et al., 2009; Eisenberg,

Fabes, Bernzweig, & Karbon, 1993; Moriya & Tanno, 2008;

Putnam, Rothbart, & Gartstein, 2008; Rothbart, Ahadi, Hershey, &

Fisher, 2001). Similar to findings relating effortful control to

negative affectivity, previous investigations have noted the impor-

tance of EFs, such as working memory processes, for the effective

regulation of emotion and emotional experience (e.g., Hofmann,

Friese, Schmeichel, & Baddeley, 2011; Schmeichel, Volokhov, &

Demaree, 2008), and specifically negative affectivity (Schretlen,

van der Hulst, Pearlson, & Gordon, 2010; Williams, Suchy, &

Kraybill, 2010).

In contrast to working memory, linked more specifically to the

experience of negative affect, some studies have noted that the EF

of inhibition may be specifically important for regulating expres-

sions of negative affect. For example, adults may use inhibition to

refrain from expressing more automatic negative reactions toward

socially marginalized groups of people (Zelazo & Cunningham,

2007). Likewise, Carlson and Wang (2007) noted that young

children with better inhibition had fewer/less intense expressions

of negative affect in response to receiving a disappointing gift.

Finally, during experimental manipulations, there is evidence sug-

gesting that those with better inhibition are better able to suppress

displays of negative emotions (e.g., von Hippel & Gonsalkorale,

2005) but may still experience negative affect (e.g., Gross &

Levenson, 1997; Gross, 1998a). These findings support dissocia-

tion, at least in some circumstances, between the experience and

expression of emotion along with processes that may serve to

regulate them (also see Gross, John, & Richards, 2000). In sum,

the available evidence suggests that different, but potentially re-

lated, self-regulation processes may play unique roles in the reg-

ulation of emotion.

Gross’ (1998b; McRae, Ochsner, & Gross, 2011) process model

of emotion regulation may help explain how interrelated self-

regulatory processes differentially influence negative affect.

Within the process model of emotion regulation, two strategies,

used at different stages of emotion regulation, are potentially

relevant for the current investigation. Antecedent emotion regula-

tion strategies (i.e., strategies used before or soon after an emotion

is experienced), such as redirecting attention and cognitive reap-

praisal, help regulate emotion by altering the emotional signifi-

cance of a given situation (Gross & Thompson, 2007). Findings

that better working memory and effortful control are associated

with lower dispositional negative affect (e.g., Moriya & Tanno,

2008; Putnam et al., 2008; Williams et al., 2010) might reflect

better capacity for reappraisal soon after experiencing an emo-

tional response through the use of effortful control and/or working

memory processes, thereby reducing the general tendency to ex-

perience negative affect (see Hofman et al., 2011 for more discus-

sion). This possibility has been supported by work demonstrating

that individuals with better working memory who were exposed to

emotional stimuli had less intense emotional reactions due to their

ability to appraise such stimuli in an unemotional manner

(Schmeichel et al., 2008).

The second relevant emotion regulation strategy within the

process model is response modulation, which includes pro-

cesses that regulate emotional expression (Gross & Thompson,

2007). Evidence suggests that the EF of inhibition might con-

tribute to the regulation of expressions of negative affect such

that those with better inhibition express less negative affect

(Carlson & Wang, 2007), potentially differentiating it from

other self-regulatory processes (e.g., the EF of working memory

and/or effortful control). While existing work suggests that

effortful control and EFs may have ties with emotion regula-

tion, studies have not yet simultaneously considered the effects

of multiple, interrelated aspects of self-regulation on the dis-

positional tendency to experience negative affect and to express

negative affect, which could provide some additional support

for models of emotion regulation (e.g., Gross, 1998b). Further-

SELF-REGULATION

more, examining the contribution of EFs and effortful control to

aspects of emotion within a single study would provide the

opportunity to examine how these self-regulation constructs are

similar or differentiated based on associations with potentially

common correlates.

The Current Investigation

In light of the distinct similarities between executive functioning

and effortful control, in the current investigation, three studies are

presented that examine the associations between these constructs.

Study 3 also considers links between EFs, effortful control, and the

tendencies to experience and express negative affect. Across stud-

ies, we selected measures that are typically used within different

subdisciplines of psychology. In particular, we selected measures

of EF that were developed for use in both research and clinical

settings. In addition, we used structural equation modeling (SEM)

to test hypotheses. This analytic approach estimates measurement

error more accurately than traditional approaches (e.g., correlation

and regression; Tomarken & Waller, 2005) and takes into account

associations between independent variables.

Study 1

The goal of Study 1 was to demonstrate that effortful control

and general EF, consistent with conceptualizations of EF as a

unitary construct (e.g., Baddeley, 2003; Norman & Shallice,

1986), are strongly associated, substantially overlapping con-

structs.

Method

Participants and procedure. Young adults (n ⫽ 236; 110

male, 126 female) from a large Midwestern university participated

in the study. Participants ranged from 18 to 30 years (M ⫽ 19.47;

SD ⫽ 2.06) of age, and most self-identified as Caucasian (61%;

Black, 21%; Asian, 9%; Hispanic 7%; other, 2%). Participants

completed the measures described below via an online website that

presented questionnaires in a random order across participants.

Participants received course credit for an introductory psychology

course for their participation.

Measures

Effortful control. Participants completed the short form of

the Adult Temperament Questionnaire (ATQ-SF; Evans & Roth-

bart, 2007), which included the subscales that constitute the ef-

fortful control factor. The ATQ-SF is a 77-item self-report ques-

tionnaire (Rothbart, Ahadi, & Evans, 2000) developed to assess

adult temperament within the framework of the psychobiological

model (Rothbart et al., 1994). This measure was selected on the

basis of its theoretical underpinnings, as well as connections with

other measures of effortful control used in younger populations

within the tradition of the psychobiological model (e.g., Children’s

Behavior Questionnaire; Rothbart, Ahadi, Hershey, & Fisher,

2001).

The effortful control factor of the ATQ-SF comprises the fol-

lowing subscales: effortful attention, inhibitory control, and acti-

vation control. Effortful attention consists of items that assess the

ability to focus and flexibly use attention (e.g., “When I am trying

to focus my attention, I am easily distracted,” reverse scored).

Inhibitory control is the ability to suppress unfavorable or inap-

propriate behavior (e.g., “It is easy for me to hold back my laughter

in a situation when laughter wouldn’t be appropriate”), and acti-

vation control is the ability to perform a particular action even

when there is a strong desire to avoid the task (e.g., “I can keep

performing a task even when I would rather not do it”; Evans &

Rothbart, 2007). In the current investigation, a latent factor of

effortful control (␣⫽.70) was formed using the effortful attention,

inhibitory control, and activation control subscales, with higher

scores reflecting better effortful control.

Executive function. Two broad indices, the metacognition

index and the behavioral regulation index, from the Behavior

Rating Inventory of Executive Function (BRIEF; Roth, Isquith, &

Gioia, 2005), adult version, were utilized as indicators of the EF

factor. The BRIEF is a 75-item self-report measure on which

participants are asked to respond to each statement (e.g., “I am

impulsive”) by indicating whether or not each behavior has been a

problem for them during the past month on a scale ranging from 1

(the behavior is never a problem)to3(the behavior is often a

problem). The metacognition index (MI) assesses the ability to

effectively and efficiently solve problems and to actively sustain

task completion goals and activities in working memory. The

behavioral regulation index (BRI) assesses the ability to exercise

self-regulation of emotion and behavior, including inhibition, flex-

ible use of attention, and the self-monitoring of thoughts and

actions. Good psychometric properties (i.e., validity and reliabil-

ity) of the BRIEF have been reported (Roth et al., 2005) and in the

current study, the internal consistency of the EF factor was excel-

lent (␣⫽.87). The BRIEF was selected for Study 1 as age-

appropriate versions have been used in child, adolescent, and adult

populations for research and clinical purposes to examine prob-

lematic executive functioning. For the purposes of the current

study, items were reverse scored such that higher scores indicated

better EF.

Results and Discussion

Analytic approach. EQS 6.1 (Bentler, 2004), a widely used

SEM program, was used to examine the association between EF

and effortful control using a maximum likelihood estimation ap-

proach. Prior to modeling the association between EF and effortful

control, a model wherein the association between EF and effortful

control was constrained to zero was estimated to facilitate com-

parison against the unconstrained model, in which the association

between EF and effortful was estimated.

Consistent with recom-

mendations to evaluate the fit of SEM models, the following fit

indices were used in the current investigation: Chi-Square Good-

ness of Fit Index, Comparative Fit Index (CFI; Bentler, 1990),

Standardized Root Mean-Square Residual (SRMSR; Joreskog &

Sorbom, 1981), and the Root Mean-Square Error of Approxima-

tion (RMSEA; Steiger, 1990). Finally, the constrained versus

unconstrained model was compared using a chi-square difference

test.

We appreciate an anonymous reviewer who made the suggestion to

compare nested models in the manner reported.

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

SEM results

. Consistent with expectations, all zero-order

associations were in the anticipated direction, with effects indicat-

ing moderate to strong associations (See Table 1 for descriptive

statistics and Table 2 for zero-order associations between vari-

ables). The initial SEM model, in which the association between

EF and effortful control was constrained to be zero, was a poor fit

to the data: ␹

(5) ⫽ 143.97, p ⬍ .05, CFI ⫽ 0.72, SRMR ⫽ 0.29,

RMSEA ⫽ 0.34 (90% CI: 0.29 to 0.39). In contrast, for the model

wherein the association between EF and effortful control was not

constrained, adequate model fit was obtained: ␹

(4) ⫽ 11.15, p ⬍

.05, CFI ⫽ 0.99, SRMR ⫽ .022, RMSEA ⫽ .09 (90% CI: 0.03 to

0.15). Consistent with expectations, a strong association was ob-

served between effortful control and EF, z ⫽ 5.31, p ⬍ .001 (See

Figure 1). Further supporting the overlap between EF and effortful

control, the chi-square difference test, statistically examining the

fit of the unconstrained model against the constrained mode, was

significant, ⌬␹

(1) ⫽ 132.82, p ⬍ .01.

Discussion. These findings suggest that there is a substantial

degree of overlap between effortful control and EF. Nonetheless,

there are some limitations of Study 1. First, self-report questionnaires

were employed to assess both effortful control and EF. Next, only

young adults enrolled in introductory psychology courses were in-

cluded, which may limit the generalizability of the findings. Finally,

in Study 1, EF was measured as a unitary construct (Baddeley, 2003;

Norman & Shallice, 1986). However, some have argued that EF is

comprised of distinct, but interrelated components (e.g., Miyake et al.,

2000). Studies 2 and 3 address these limitations.

Study 2

Given the limitation of relying upon only self-report measures in

Study 1, as well as examining EF solely from the perspective that EF

is a unitary construct (e.g., Baddeley, 2003; Norman & Shallice,

1986), in Study 2 we included individually administered measures of

two specific EFs, inhibition and updating/monitoring information in

working memory. Measurement of these two EF processes in Study 2

is consistent with conceptualizations of executive functioning as a set

of separate, but interrelated processes (e.g., Miyake et al., 2000).

Furthermore, a community sample of participants was used in Study

2, addressing another limitation of Study 1.

In Study 2, we expected better effortful control to be asso-

ciated with faster RTs and fewer errors on a Stroop-like task,

which measures the EF of inhibition. Because some compo-

nents of effortful control (e.g., effortful attention) conceptually

resemble updating/monitoring information in working memory,

we also anticipated that higher effortful control would be as-

sociated with better performance on individually administered

EF tests of working memory. Finally, consistent with studies

that have observed more modest associations between measures

of effortful control when different measurement methods have

been used (e.g., Eisenberg et al., 2003; Gusdorf et al., 2011;

Valiente et al., 2003), more modest associations between the EF

tasks and the self-report measure of effortful control used in

Study 2 were anticipated.

Method

Participants & procedure. Participants in Study 2 con-

sisted of 85 postpartum women recruited to participate in a

longitudinal study examining the effects of maternal self-

regulation on infant emotional development. Participants were a

mean of 26.67 years old (SD ⫽ 6.66) and were recruited from

a rural county through a large OBGYN practice (61%), or

through flyers posted in local communities and birth announce-

ments placed in a local newspaper (39%). Participants primarily

self-identified their ethnicity as Caucasian (70.2%), Hispanic

(13.1%), and African American (10.7%); the remaining partic-

ipants (6%) identified as being of other ethnic origins. The

mean educational attainment was 14.53 years (SD ⫽ 2.78), and

the mean family income-to-needs ratio was 2.43 (SD ⫽ 1.93).

Two weeks before the first laboratory visit, women were mailed

a measure of effortful control to complete and were asked to

bring the completed measure with them to the laboratory. At

four months postpartum, all participants attended a laboratory

session and completed individually administered measures of

executive function. All participants received $50.00 for their

participation.

Measures

Effortful control. The ATQ-SF effortful control factor (␣⫽

.76), consisting of subscales of effortful attention, activation con-

trol, and inhibitory control was used to assess effortful control in

Study 2 (See Study 1 for more details on this measure).

Executive functions. To measure updating/monitoring of in-

formation in working memory with “externally” presented stimuli,

the letter–number sequencing subtest from the Wechsler Adult

Intelligence Scale, 4th Edition (WAIS-IV; Wechsler, 2008) was

used. The latent variable was formed using the total score and

longest recalled span. During this task, participants were presented

with increasingly longer series of mixed letters and numbers, at

1-second intervals and then had to repeat the series back to the

administrator such that numbers were presented first in order from

lowest to highest, followed by the letters in alphabetical order.

This measure was selected because it is a commonly used indicator

of working memory in clinical settings, and because the letter-

number sequencing subtest from the Wechsler Adult Intelligence

Scale, 3rd Edition (Wechsler, 1997), the predecessor of the

WAIS-IV, was found to load with traditionally experimental work-

ing memory tasks (e.g., n-back and operation span; Shelton, El-

liott, Calamia, & Gouvier, 2009). Higher scores and longer spans

are consistent with better working memory.

To form a second latent variable of “internally” generated

information requiring updating/monitoring information in

working memory, the verbal fluency test from the Delis-Kaplan

Executive Function System (D-KEFS; Delis, Kaplan, &

Kramer, 2001) was used. Three indicators from this measure,

In all studies reported in the current investigation, before SEM anal-

yses, variables were examined for normality (Tabachnick & Fidell, 2007).

Based on the recommendations made by Tabachnick and Fidell (2007), a

z test (i.e. Skew/Std. Error of Skew) was used to determine whether the

degree of skew for each variable used in the SEM model was significantly

different from zero. All variables that demonstrated significant skew were

transformed using either a square-root or a log transformation if the results

of the z test were greater than or equal to 2 or less than or equal to ⫺2

(Curran, West, & Finch, 1996; Tabachnick & Fidell, 2007). Transformed

and nontransformed variables are reported in tables associated with each

specific study.

SELF-REGULATION

letter fluency, category fluency, and category switching accu-

racy, were used as indicators of the latent variable. These

measures were selected based on evidence that working mem-

ory is the process that underlies performance on verbal fluency

measures similar to the one employed in the current study (see

Unsworth, Spillers, & Brewer, 2011). These D-KEFS verbal

fluency measures were also selected given other work noting

that they loaded onto a working memory factor (e.g., Latzman

& Markon, 2010), and because the D-KEFS measures have been

standardized to aid in clinical decision making regarding EF

capacities in such settings.

Completion of the letter fluency condition required partici-

pants to say as many words as possible that started with a

specific letter within a 60-second time frame. This was done

with the letters “F,” “A,” and “S,” each in separate trials that

were administered one immediately after the other. Per stan-

dardized administration procedures, participants were in-

structed that they could not use the names of people, places, or

numbers, that they could only use each response once, and that

they could not use the same response with different endings.

Completion of the category fluency condition required partici-

pants to first say as many animals as possible in one 60-second

condition, and then in a second 60-second condition, say as

many boy’s names as possible. During the category switching

condition, participants were asked to switch back and forth

between naming a fruit, and then a piece of furniture. Category

switching is a single 60-second trial, with category switching

accuracy reflecting the number of accurate category changes

made within the specified time frame. Although less restrictive

than the letter fluency condition, participants were instructed

not to repeat the same object or name during the category and

category fluency conditions. Given the nature of the task,

updating/monitoring information in working memory is re-

quired to monitor and keep active words that had already been

used, to access new items, and to keep active the other rules

governing each aspect of the task (Rosen & Engle, 1997;

Unsworth et al., 2011). Higher scores on these verbal fluency

tasks are indicative of better updating/monitoring information

in working memory.

Finally, several indices, inhibition time, inhibition-switching

time, and the sum of errors committed during both the inhibi-

tion and inhibition-switching tasks, from a second D-KEFS

(Delis et al., 2001) measure, the color-word interference test,

were used to form a latent factor of the EF of Inhibition. The

inhibition task is a traditional Stroop-like task wherein partic-

ipants have to inhibit reading a color word, and instead, say the

name of the color in which the word is printed. The inhibition-

switching task requires switching between reading the color

word, and naming the color in which the color word is printed.

Longer times to complete these tasks, and more errors (e.g.,

reading the color word instead of naming the color) indicate

more difficulties with inhibition.

Results and Discussion

Results. The general analytical approach described in Study 1

was also used in Study 2. SEM, using EQS 6.1 (Bentler, 2004) was

used to examine associations between the EFs of inhibition, up-

dating/monitoring information in working memory,

and effortful

control (See Table 3 for descriptive statistics and Table 4 for

associations between variables). The initial model, wherein asso-

ciations between EFs and effortful control were constrained to be

zero fit adequately: ␹

(41) ⫽ 59.02, p ⬍ .05, CFI ⫽ 0.94,

SRMR ⫽ 0.11, RMSEA ⫽ 0.07 (95% CI: 0.02 to 0.11). Although

the initial model was an adequate fit, the model without associa-

tions between EFs and effortful control being constrained was a

significant improvement, ⌬␹

(2) ⫽ 6.60, p ⬍ .05, and an overall

good fit: ␹

(39) ⫽ 52.42, p ⬎ .05, CFI ⫽ 0.96, SRMR ⫽ 0.065,

RMSEA ⫽ .06 (95% CI: 0.00 to 0.10). In the unconstrained model,

Before analyzing the full model, the fit of a single working memory

factor, two correlated working memory factors, and a second order work-

ing memory factor, with two lower order latent variables was examined.

The single working memory factor was a poor fit to the data, ␹

(5) ⫽

78.20, p ⬍ .05, CFI ⫽ .76, RMSEA ⫽ .42. In comparison, a correlated two

factor model was a significant improvement in fit, ⌬␹

(1) ⫽ 65.85, p ⬍

.05, but still a relatively unacceptable overall fit to the data, ␹

(4) ⫽ 12.35,

p ⬍ .05, CFI ⫽ .93, RMSEA ⫽ .16. Relative to the correlated two factor

model, a single higher order working memory factor, with two lower order

latent working memory factors, ␹

(3) ⫽ 5.19, p ⬎ .05, CFI ⫽ .96,

RMSEA ⫽ .09, was a significant improvement in fit, ⌬␹

(1) ⫽ 7.16, p ⬍

.05. Given these findings, a single higher order working memory factor was

specified in the full SEM.

Table 1

Study 1 Descriptive Statistics for Variables Used in the Structural Equation Model

Variable Mean (SD) Skew SE of skew z T.

mean (SD) T. skew T. SE of skew z

ATQ inhibitory control 4.09 (0.72) 0.47 0.157 3.00

ⴱⴱ

2.01 (0.18) 0.18 0.157 1.15

ATQ activation control 4.55 (0.91) 0.14 0.157 0.86 NA NA NA NA

ATQ effortful attention 4.22 (1.06) ⫺0.06 0.157 0.39 NA NA NA NA

BRIEF BRI

2.08 (0.32) ⫺0.67 0.157 ⫺4.27

ⴱⴱ

1.25 (0.09) ⫺0.27 0.157 ⫺1.72

BRIEF MI

2.01 (0.35) ⫺0.58 0.157 ⫺3.63

ⴱⴱ

1.23 (0.10) ⫺0.21 0.157 ⫺1.35

T ⫽ Transformed.

Behavioral Regulation Index.

Metacognitive Index.

ⴱ

p ⬍ .05.

ⴱⴱ

p ⬍ .01.

Table 2

Zero-Order Associations Between Observed Variables in Study 1

Variable 1 2 3 4

1. ATQ inhibitory control

2. ATQ activation control .28

ⴱⴱ

3. ATQ effortful attention .39

ⴱⴱ

.52

ⴱⴱ

4. BRIEF behavioral regulation index .36

ⴱⴱ

.41

ⴱⴱ

.48

ⴱⴱ

5. BRIEF metacognitive index .32

ⴱⴱ

.58

ⴱⴱ

.57

ⴱⴱ

.78

ⴱⴱ

p ⬍ .01.

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

the EFs of inhibition and working memory were significantly

associated, z ⫽⫺3.33, p ⬍ .01. Furthermore, better working

memory was associated with higher effortful control, z ⫽ 2.06,

p ⬍ .05. However, while in the anticipated direction, inhibition

and effortful control were not significantly associated, z ⫽⫺1.69,

p ⬎ .05 (See Figure 2 for the final SEM Model).

Discussion. Study 2 used multiple methods (i.e., self-report

effortful control and individually administered neuropsycholog-

ical measures of EF), using a community sample. Study 2 also

examined associations between effortful control and two dif-

ferent aspects of EF. As in Study 1 and consistent with our

expectations, updating/monitoring information in working

memory was significantly associated with effortful control.

However, contrary to our expectation, the EF of inhibition was

not significantly associated with effortful control, perhaps be-

cause of limited statistical power. Furthermore, although find-

ings in Study 2 were largely consistent with the findings of

Study 1, neither of these studies examined potential correlates

of effortful control and EF. Therefore in Study 3, we tested the

association between EFs and effortful control and their poten-

tial links with negative affectivity.

Study 3

In Study 3, a measurement approach similar to that which

was used in Study 2 was implemented with a larger sample. As

in Study 2, we predicted that better updating/monitoring infor-

mation in working memory would be associated with better

effortful control. In addition, in Study 3 we examined associa-

tions between effortful control, EFs, and the tendency to expe-

rience and express negative affect. This is central to questions

regarding the similarities and differences between effortful

control and EFs insomuch as overlapping constructs should be

associated with common outcomes. Based on prior work (e.g.,

Hofmann et al., 2011; Putnam et al., 2008; Rothbart et al., 2001;

Schretlen et al., 2010), and based on associations between

effortful control and the EF of updating/monitoring information

in working memory observed in Study 2, we anticipated that

better updating/monitoring information in working memory and

effortful control would be associated with lower dispositional

negative affect. Given evidence that emotional expression can

be differentiated from the experience of emotion (Gross et al.,

2000), and that the EF of inhibition may be important for

inhibiting emotional expression (e.g., Carlson & Wang, 2007;

von Hippel & Gonsalkorale, 2005), it was expected that lower

inhibition, indicated by longer completion times and more

errors during the Stroop-like task, would be associated with the

greater tendency to express negative affect.

Two hypotheses regarding mediated effects were also exam-

ined. Because the experience of negative affect should predict

the expression of negative affect (Gross et al., 2000), and

because effortful control and updating/monitoring information

in working memory may be related to dispositional negative

affect (Hofman et al., 2011; Putnam et al., 2008; Williams et al.,

2010), but not necessarily to the tendency to express negative

affect, these self-regulatory processes might not be directly

associated with the expression of negative affect when dispo-

sitional negative affect is simultaneously considered. This pos-

sibility is consistent with the process model of emotion regu-

lation (Gross, 1998b) insomuch as effortful control and/or

working memory are potentially important for more antecedent

emotion regulation strategies (Schmeichel et al., 2008) that

Table 3

Study 2 Descriptive Statistics for Variables Used in the Structural Equation Model

Variable Mean (SD) Skew SE of skew z T.

mean (SD) T. skew T. SE of skew z

ATQ inhibitory control 4.51 (0.89) ⫺0.18 0.266 ⫺0.69 NA NA NA NA

ATQ activation control 5.14 (0.91) ⫺0.60 0.266 ⫺2.26

ⴱ

1.81 (0.28) ⫺0.16 0.266 ⫺0.61

ATQ effortful attention 4.87 (1.10) ⫺0.33 0.266 ⫺1.24

ⴱ

NA NA NA NA

DKEFS inhibition time 49.21 (10.69) 1.68 0.263 6.38

ⴱⴱ

1.68 (0.09) 0.42 0.263 1.57

DKEFS inhibition switch time 55.98 (11.77) 0.93 0.263 3.54

ⴱⴱ

1.74 (0.09) 0.26 0.263 0.99

DKEFS total errors

4.49 (3.72) 1.05 0.263 3.99

ⴱⴱ

0.62 (0.34) ⫺0.51 0.263 ⫺1.94

DKEFS letter fluency 37.57 (9.65) 0.12 0.263 0.46 NA NA NA NA

DKEFS category fluency 41.54 (8.97) 0.39 0.263 1.48 NA NA NA NA

DKEFS cat. switching accuracy 13.14 (3.33) 0.18 0.263 0.68 NA NA NA NA

Letter-number seq. score 19.29 (2.74) ⫺0.26 0.263 0.99 NA NA NA NA

Letter-number seq. Longest string 5.43 (1.03) 0.20 0.263 0.76 NA NA NA NA

T ⫽ Transformed.

DKEFS Total Errors consists of errors (e.g., reading the word instead of naming the color) made during the Inhibition and Inhibition

Switch trials.

ⴱ

p ⬍ .05.

ⴱⴱ

p ⬍ .01.

.77*

Effortful

Control

Executive

Function

.48*

.77*

*79.*38.*67.

BRIEF

BRI

AT Q

Effortful

Attention

AT Q

Activation

Control

AT Q

Inhibitory

Control

.88* .65* .64* .56* .25*

Figure 1. Study 1 structural equation model depicting association be-

tween effortful and executive function. Standardized coefficients are dis-

played.

ⴱ

p ⬍ .05.

SELF-REGULATION

occur before strategies used for response modulation (e.g.,

inhibition). As such, it was anticipated that updating/monitoring

information in working memory and effortful control would be

indirectly associated, through dispositional negative affect,

with the expression of negative affect.

Method

Participants & procedure. Participants consisted of 188

young adults (67.7% female, 32.3% male) between the ages of 18

and 29 years (M ⫽ 19.85 years, SD ⫽ 2.05) enrolled in psychology

courses at a large Midwestern university. Of those participants

who specified their ethnicity, a slight majority (54.3%) were

Caucasian, 28.8% self-identified as African American, 11.4% self-

identified as Hispanic/Latino, 1.6% self-identified as Asian, 1.1%

self-identified as Filipino, and 2.7% self-identified as being vari-

ous other ethnicities. Participants completed a single individual

session in the laboratory where they completed questionnaire

measures interspersed with individually administered measures of

EF and negative affectivity. For their participation, all participants

obtained course credit and were entered into a drawing for $75.

Measures

Effortful control and executive functions. Effortful control

was measured using the ATQ-SF (See Study 1 for description),

with effortful attention, inhibitory control, and activation control

used as indicators of the effortful control latent variable (␣⫽.73).

Table 4

Zero Order Associations Between Observed Variables in Study 2

Variable 1 2 3 4 5 6 7 8 9 10

1. ATQ inhibitory control

2. ATQ activation control .40

ⴱⴱ

3. ATQ effortful attention .64

ⴱⴱ

.57

ⴱⴱ

4. D-KEFS inhibition time ⫺.08 ⫺.16 ⫺.10

5. D-KEFS inhibition switching time ⫺.14 ⫺.19

⫹

⫺.22

ⴱ

.52

ⴱⴱ

6. D-KEFS inhibition/ inhibition switching errors ⫺.15 ⫺.25

ⴱ

⫺.15 .41

ⴱⴱ

.45

ⴱⴱ

7. D-KEFS letter fluency total correct .20

⫹

.01 .21

⫹

⫺.33

ⴱ

⫺.41

ⴱⴱ

⫺.38

ⴱⴱ

8. D-KEFS category fluency total correct .19

⫹

.15 .19

⫹

⫺.43

ⴱⴱ

⫺.34

ⴱⴱ

⫺.38

ⴱⴱ

.61

ⴱⴱ

9. D-KEFS category switching accuracy .19

⫹

.04 .15 ⫺.53

ⴱⴱ

⫺.42

ⴱⴱ

⫺.32

ⴱⴱ

.59

ⴱⴱ

.66

ⴱⴱ

10. LNS total score .25

ⴱ

.01 .25

ⴱ

⫺.30

ⴱⴱ

⫺.33

ⴱⴱ

⫺.40

ⴱⴱ

.40

ⴱⴱ

.25

ⴱ

.39

ⴱⴱ

11. LNS longest correct span .23

ⴱ

⫺.08 .21

⫹

⫺.13 ⫺.25

ⴱ

⫺.25

ⴱⴱ

.41

ⴱⴱ

.18 .30

ⴱⴱ

.76

ⴱⴱ

⫹

p ⬍ .10.

ⴱ

p ⬍ .05.

ⴱⴱ

p ⬍ .01.

.36*

Executive

Function

Updating/

Monitoring

Effortful

Control

Executive

Function

Inhibition

-.88*

.57* .83*

.67* .96* .61* .70* .70* .66*

.92* .56*

Inhibition Inhibition

InhibitionATQ ATQ

ATQ LNS Long LetterLNS Cat. FluencyCategory

.98* .78*

.73* .77*

.85*

Time Switch Time ErrorsInhib. Ctrl. E. Attn. Act. Ctrl. Sequence FluencyScore SwitchingFluency

.74* .29* .79*

.71*

.71* .75* .15* .63* .68* .64* .53*

Updating/

Monitoring

External

Updating/

Monitoring

Internal

Figure 2. Study 2 structural equation model depicting association between effortful control and the executive

functions of updating/monitoring information in working memory and inhibition. Standardized coefficients are

displayed.

ⴱ

p ⬍ .05.

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

The EFs of updating/monitoring information in working memory

and inhibition were assessed using only the D-KEFS. The verbal

fluency measures and color-word interference measures, previ-

ously described in Study 2, were used to form the latent variables

of updating/monitoring information in working memory and inhi-

bition, respectively.

Dispositional negative affect and expression of negative

affect. The latent variable of dispositional negative affect con-

sisted of the ATQ-SF (Evans & Rothbart, 2007) negative affect

factor and the NEO-FFI neuroticism scale (␣⫽.76). The ATQ-SF

negative affect factor is comprised of subscales consisting of the

dispositional temperament characteristics of fear, sadness, discom-

fort, and frustration. The NEO-FFI (NEO-FFI; Costa & McCrae,

1992) is a brief 60-item measure that captures the Big Five

dimensions of personality, including neuroticism. Similar to the

ATQ-SF subscales comprising negative affect, items constituting

the neuroticism scale reflect dispositional tendencies to experience

fear, sadness, and anger. The ATQ-SF negative affect factor and

the NEO-FFI neuroticism scale were selected as indicators of the

dispositional tendency to experience negative affect based on

theoretical and empirical work indicating that negative affect/

neuroticism reflect core dispositional tendencies to experience

negative emotion (Digman, 1990; Evans & Rothbart, 2007; Tel-

legen, 1985; Watson & Clark, 1992) and because these scales have

demonstrated a strong association in prior work (e.g., Evans &

Rothbart, 2007).

The expression of negative affect latent variable (␣⫽.77)

consisted of two scales, negative expressivity and impulse

strength, from the Berkeley Expressivity Questionnaire (BEQ;

Gross & John, 1995). The BEQ was developed based on a model

of emotional expression and generation (Gross & Munoz, 1995) to

capture the expression of specific emotions, as well as the strength

of the impulse to express specific emotions when they are expe-

rienced. Items comprising the impulse strength scale (e.g., “There

have been times when I have not been able to stop crying even

though I tried to stop” and “I am sometimes unable to hide my

feelings even though I would like to”) reflect the tendency to have

difficulties stopping an emotional impulse. Items comprising

the negative expressivity scale reflect the tendency to express negative

emotions (e.g., “It is difficult for me to hide my fear” and reverse

scored, “I’ve learned it is better to suppress my anger than to

show it”).

Results and Discussion

Results

. See Table 5 for the descriptive statistics for vari-

ables used in the SEM analysis. EQS 6.1 (Bentler, 2004) was used

to simultaneously test the hypotheses specified in the current study

using SEM (See Table 6 for associations). The SEM model was a

good fit to the data, ␹

(55) ⫽ 84.17, p ⬍ .05, CFI ⫽ 0.95,

SRMR ⫽ .053, RMSEA ⫽ .054 (95% CI: 0.029 to 0.075). Better

inhibition (i.e., less time to complete the color-word and color-

word switching tasks, and fewer errors during completion of these

tasks) was associated with better ability to update/monitor infor-

mation in working memory, z ⫽⫺3.14, p ⬍ .05. Findings with

regard to hypothesized associations between factors of effortful

control and the EFs of inhibition and updating/monitoring infor-

mation in working memory were consistent with findings obtained

in Study 2. Effortful control demonstrated a robust association

with updating/monitoring information in working memory, z ⫽

2.64, p ⬍ .05. However, the association between effortful control

and the EF of inhibition, while in the anticipated direction, was not

significant, z ⫽⫺1.14, p ⬎ .05 (See Figure 3 for the factor

loadings of the indicators in the model and see Figure 4 for the

pathways between latent variables).

Consistent with hypotheses, better effortful control, z ⫽⫺6.14,

p ⬍ .05, and updating/monitoring information in working memory,

z ⫽⫺1.99, p ⬍ .05, were associated with lower dispositional

negative affect. However, neither effortful control, z ⫽ 0.59, p ⬎

.05, nor updating/monitoring information in working memory, z ⫽

⫺0.01, p ⬎ .05, were associated with the tendency to express

negative affectivity. On the other hand, whereas the EF of inhibi-

tion was not associated with the dispositional tendency to experi-

ence negative affect, z ⫽⫺1.18, p ⬎ .05, poorer inhibition was

associated with the tendency to express more negative affect, z ⫽

2.29, p ⬍ .05. Effortful control and updating/monitoring informa-

tion in working memory accounted for 56% of the variance in

dispositional negative affect; 50% of the variance in the expression

of negative affect was accounted for in the model.

Finally, the potential indirect (i.e., mediated) effects of effortful

control and updating/monitoring information in working memory

on the expression of negative affect through dispositional negative

affect were tested using the effect decomposition feature of the

EQS 6.1 SEM software. Results of tests of indirect effects indi-

cated that effortful control, z ⫽⫺3.22, p ⬍ .05, and updating/

monitoring information in working memory, z ⫽⫺1.75, p ⬍ .05,

were indirectly linked to the tendency to express negative affect

through the dispositional tendency to experience negative affect.

Discussion. As was observed in Study 2, in Study 3, updating/

monitoring information in working memory was significantly as-

sociated with effortful control. Associations in both Studies 2 and

3 were of approximately the same magnitude as associations

between parent-report and laboratory measures of effortful control

that have been noted in the developmental literature (Eisenberg et

al., 2003; Gusdorf et al., 2011; Valiente et al., 2003). However, in

both studies, the EF of inhibition was not significantly associated

with effortful control.

Study 3 also extended Study 2. Both effortful control and

updating/monitoring information in working memory were asso-

ciated with the dispositional experience of negative affect whereas

the EF of inhibition was associated with the tendency to express

negative affect. These findings further support the broader pattern

of results that suggest greater similarity between the EF of updat-

ing/monitoring information in working memory and effortful con-

trol, and the distinction of the EF of inhibition from these other

self-regulatory processes. As anticipated, dispositional negative

affect mediated the association between effortful control and up-

As was done in Studies 1 and 2, a model wherein pathways between

EFs and effortful control were constrained to be zero was compared against

the unconstrained model. For these analyses, negative affectivity variables

were not included. The constrained model was a reasonable fit to the data:

␹

(26) ⫽ 36.61, p ⬍ .10, CFI ⫽ 0.96, SRMR ⫽ 0.08, RMSEA ⫽ 0.05.

However, the unconstrained model, ␹

(24) ⫽ 26.73, p ⬎ .05, CFI ⫽ 0.99,

SRMR ⫽ 0.05, RMSEA ⫽ 0.02, was a significant improvement in fit,

⌬␹

(2) ⫽ 9.88, p ⬍ .01, providing further support for the overlap between

EFs and effortful control.

SELF-REGULATION

dating/monitoring information in working memory and expression

of negative affect.

General Discussion

In the current investigation, we examined similarities between

two self-regulation constructs: effortful control and executive

functioning. Prior investigators have noted that effortful control

and EFs have conceptual, neurobiological, and developmental

similarities, as well as similarities in terms of common correlates

(e.g., Zhou et al., 2012). The present investigation provides addi-

tional and direct evidence of the overlap between these constructs.

In Study 1 we found a strong association between effortful control

and EF. In Studies 2 and 3 effortful control was associated with the

EF of updating/monitoring information in working memory, but

not the EF of inhibition. Finally, in Study 3, we demonstrated that

effortful control and the EF of updating/monitoring information in

working memory were associated with the experience of negative

affect, whereas the EF of inhibition was only associated with the

expression of negative affect.

These findings have several notable implications. First, the

findings support the view that effortful control and EF are largely

overlapping constructs, potentially challenging the distinctions

that are sometimes made between them. In particular, our findings

in Studies 2 and 3 are consistent with Rueda et al.’s (2011)

statement that the executive attention network, underlying effortful

control, comprises networks that carry out some EFs, such as

working memory. Although associations between the EF of up-

dating/monitoring information in working memory and effortful

control in Studies 2 and 3 were more modest than the association

between EF and effortful control in Study 1, this was anticipated

based on the use of different methods to assess EFs and effortful

control. Importantly, the magnitude of these associations was

similar to that which has been observed between parent-report and

laboratory measures of effortful control described in the develop-

mental literature (Eisenberg et al., 2003; Gusdorf et al., 2011;

Valiente et al., 2003). Insomuch as the magnitude of associations

between effortful control and updating/monitoring information in

working memory noted in the current investigation parallel the

Table 5

Study 3 Descriptive Statistics for Variables Used in the Structural Equation Model

Variable Mean (SD) Skew SE of skew z T.

mean (SD) T. skew T. SE of skew z

NEOFFI neuroticism 2.70 (0.67) 0.12 0.177 0.67 NA NA NA NA

ATQ negative affect 3.76 (0.69) 0.02 0.177 0.11 NA NA NA NA

BEQ neg. expressivity 3.67 (0.79) ⫺0.22 0.177 ⫺1.24 NA NA NA NA

BEQ impulse strength 4.39 (1.21) ⫺0.07 0.178 ⫺0.39 NA NA NA NA

ATQ inhibitory control 4.17 (0.86) 0.39 0.177 2.20

ⴱ

2.03 (0.21) 0.06 0.177 0.34

ATQ activation control 4.82 (0.88) ⫺0.39 0.177 ⫺2.20

ⴱ

1.68 (0.26) 0.05 0.177 0.28

ATQ effortful attention 4.12 (1.06) 0.40 0.177 2.26

ⴱ

2.01 (0.26) 0.00 0.177 0.02

DKEFS inhibition time 48.35 (11.71) 1.21 0.177 6.84

ⴱⴱ

1.67 (0.10) 0.39 0.177 2.20

ⴱ

DKEFS inhibition switch time 54.73 (11.17) 1.14 0.177 6.44

ⴱⴱ

1.73 (0.08) 0.40 0.177 2.26

ⴱ

DKEFS total errors

4.78 (4.95) 2.46 0.178 13.82

ⴱⴱ

0.63 (0.34) ⫺0.06 0.178 ⫺0.34

DKEFS letter fluency 36.82 (9.74) 0.19 0.177 1.07 NA NA NA NA

DKEFS category fluency 39.40 (8.06) ⫺0.08 0.177 0.45 NA NA NA NA

DKEFS cat. switching accuracy 11.97 (2.54) ⫺0.37 0.177 ⫺2.09

ⴱ

2.44 (0.46) 0.33 0.177 1.86

T ⫽ Transformed.

DKEFS Total Errors consists of errors (e.g., reading the word instead of naming the color) made during the Inhibition and Inhibition

Switch trials.

ⴱ

p ⬍ .05.

ⴱⴱ

p ⬍ .01.

Table 6

Zero Order Associations Between Observed Variables in Study 3

Variable 123456789101112

1. NEOFFI neuroticism

2. ATQ negative affect .62

ⴱⴱ

3. BEQ negative expressivity .33

ⴱⴱ

.39

ⴱⴱ

4. BEQ impulse strength .42

ⴱⴱ

.39

ⴱⴱ

.54

ⴱⴱ

5. ATQ inhibitory control ⫺.38

ⴱⴱ

⫺.39

ⴱⴱ

⫺.33

ⴱⴱ

⫺.32

ⴱⴱ

6. ATQ activation control ⫺.41

ⴱⴱ

⫺.31

ⴱⴱ

⫺.13

⫹

⫺.04 .38

ⴱⴱ

7. ATQ effortful attention ⫺.47

ⴱⴱ

⫺.44

ⴱⴱ

⫺.32

ⴱⴱ

⫺.20

ⴱⴱ

.53

ⴱⴱ

.52

ⴱⴱ

8. D-KEFS inhibition time .09 .13

⫹

.15

ⴱ

.18

ⴱ

⫺.10 ⫺.03 ⫺.08

9. D-KEFS inhibition switching time ⫺.02 .07 .16

ⴱ

.19

ⴱ

⫺.12

⫹

⫺.02 ⫺.06 .63

ⴱⴱ

10. D-KEFS inhibition/ inhibition switching errors ⫺.05 ⫺.09 .07 .06 ⫺.06 ⫺.02 .04 .34

ⴱⴱ

.39

ⴱⴱ

11. D-KEFS letter fluency total correct ⫺.13

⫹

⫺.16

ⴱ

⫺.14

⫹

⫺.22

ⴱⴱ

.12

⫹

.08 .19

ⴱⴱ

⫺.24

ⴱⴱ

⫺.26

ⴱⴱ

⫺.09

12. D-KEFS category fluency total correct ⫺.26

ⴱⴱ

⫺.24

ⴱⴱ

⫺.20

ⴱⴱ

⫺.14

⫹

.10 .08 .21

ⴱⴱ

⫺.20

ⴱⴱ

⫺.13

⫹

.08 .42

ⴱⴱ

13. D-KEFS category switching accuracy ⫺.18

ⴱ

⫺.04 ⫺.08 ⫺.15

ⴱ

⫺.01 .07 .13

⫹

⫺.27

ⴱⴱ

⫺.30

ⴱⴱ

⫺.14

⫹

.28

ⴱⴱ

.27

ⴱⴱ

⫹

p ⬍ .10.

ⴱ

p ⬍ .05.

ⴱⴱ

p ⬍ .01.

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

magnitude of associations between parent report and laboratory

measures of effortful control in children (i.e., same construct,

different measurement approaches), additional support is provided

for the overlap of updating/monitoring information in working

memory and effortful control.

Next, the overlap between executive functioning and effortful

control identified in the current investigation (e.g., Study 1) has

important theoretical implications. Whereas effortful control is an

aspect of temperament (Rothbart et al., 1994), EFs are typically not

referred to as temperament characteristics. However, because EFs

emerge early in life (Kalkut et al., 2009; Pennequin et al., 2010),

are constitutionally based (i.e., are biologically based, heritable

processes; Lenroot et al., 2009), and change over time as a function

of maturation and the environment (e.g., Bridgett & Mayes, 2011;

Rhoades, Greenberg, Lanza, & Blair, 2011), attributes that are

encompassed within the concept of temperament based on the

psychobiological model (Rothbart et al., 1994), EFs also may be

considered aspects of temperament. Thus, in light of our findings

supporting the overlap between executive functioning and effortful

control, other comparisons between these constructs (e.g., Zhou et

al., 2012), and investigations, such as those noted above, that have

carefully examined the nature of executive functioning, theoretical

integration of these self-regulatory constructs within a tempera-

ment framework may be appropriate.

Although several anticipated effects were observed, nonsignif-

icant associations between effortful control and the EF of inhibi-

tion were obtained in Studies 2 and 3. These findings are incon-

sistent with some investigations that have identified associations

between aspects of effortful control and inhibition (e.g., Carlson &

Moses, 2001; Ellis, Rothbart, & Posner, 2004), yet other investi-

gations, similar to our findings, have found small or no associa-

tions (e.g., Muris, van der Pennen, Sigmond, & Mayer, 2008;

Verstraeten, Vasey, Claes, & Bijttebier, 2010). One potential ex-

planation for these inconsistencies is that effortful control and

working memory overlap more so than inhibition in young adults.

This possibility is consistent with research that has identified

common brain networks underlying effortful control and working

memory (Hester & Garavan, 2005; McCabe et al., 2010; Rueda et

al., 2011). Similarly, from a developmental perspective, the inhib-

itory aspects of effortful control may be more prominent in chil-

dren. This may be attributable to the greater salience of inhibitory

processes earlier in development, or attributable to effortful control

measurement approaches, as laboratory-based measures used with

children focus primarily on inhibitory processes (e.g., Kochanska

et al., 2000). Likewise, because parents are often raters of their

children’s effortful control in developmental studies, it may be the

case that failures of inhibition are more noticeable, resulting in

ratings of effortful control that are unlikely to capture less out-

wardly visible self-regulatory processes (e.g., working memory),

rendering stronger associations between effortful control and lab-

oratory measures that capture inhibition. Future studies should

examine these and other potential explanations for the dissociation

between effortful control and the EF of inhibition observed in this

investigation.

In addition to associations between EFs and effortful control,

Study 3 examined the implications of simultaneously considering

multiple aspects of self-regulation for understanding the tenden-

cies to experience and express negative affect. This approach

permitted testing a model demonstrating that different, albeit re-

lated, self-regulation constructs may be uniquely associated with

the experience and expression of emotion. Consistent with what

might be expected based on the process model of emotion regu-

AT Q

Inhibitory

Control

.58*

.73*

.81*

.68*

NEOFFI

Neuroticism

AT Q

Activation

Control

63*

.79*

.78*

.61*

AT Q

D-KEFS

Effortful

Attention

.56*

68*

.67*

.83*

Negative Affect

D-KEFS

Color-Word

Interference

Inhibition

.52*

.74*

.85*

D-KEFS

Color-Word Int.

Total Errors

Int. Switching

Inhibition

.90*

.45*

BEQ

Negative

Expressivity

D-KEFS

Verbal Fluency

Letter

.72*

.79*

.70*

.62*

BEQ

Impulse

DKEFS

D-KEFS

Verbal Fluency

Category

.64*

.77*

.63*

51*

Strength

Verbal Fluency

Cat. Switching

.86*

.71*

Effortful

Control

Executive Function

Updating/Monitoring

Expression

of Negative

Affect

Dispositional

Negative

Affect

Figure 3. Observed variables, factor loadings, and error variances for the structural equation model testing the

association between effortful control and executive function constructs, and between these self-regulation

constructs and the dispositional tendency to experience negative affect and the tendency to express negative

affect. Only standardized coefficients are displayed.

ⴱ

p ⬍ .05.

SELF-REGULATION

lation (Gross, 1998b), and on prior work (e.g., Hofmann et al.,

2011; Levens & Gotlib, 2010; Moriya & Tanno, 2008; Putnam et

al., 2008; Schmeichel et al., 2008; Schretlen et al., 2010; Williams

et al., 2010), findings indicated that effortful control and the EF of

updating/monitoring information in working memory were related

to dispositional negative affect, but not directly associated with the

tendency to express negative affect. These results suggest that

working memory and effortful control may contribute to the reg-

ulation of the experience of negative affect, perhaps through cog-

nitive reappraisal (Hofmann et al., 2011). In contrast, the EF of

inhibition was only associated with the tendency to express neg-

ative affect, suggesting that the EF of inhibition may only contrib-

ute to the regulation of the outward expression of negative affect.

This interpretation is consistent with prior work suggesting that the

EF of inhibition is important for regulating expressions of emotion

(e.g., Carlson & Wang, 2007). Nevertheless, while the current

study statistically modeled associations between self-regulation

(i.e., EFs and effortful control) and negative affect from the per-

spective that self-regulation of emotion occurs in adults in a

top-down manner (see Ray & Zald, 2012 for discussion of top-

down vs. bottom-up control processes), another potential interpre-

tation of these findings is that negative affectivity disrupted EFs

and effortful control. Such a possibility is consistent with a small

but notable body of research demonstrating, primarily in children,

the potential disruption of later self-regulation and related pro-

cesses (e.g., attention) by earlier negative affect (Bridgett et al.,

2009; Leve et al., In Press; Stifter & Spinrad, 2002). This potential

explanation should be considered in future investigations.

Finally, in the broader context of the current investigation,

findings obtained in Study 3 are important for two reasons. First,

our findings make potentially important connections with theory

related to the self-regulation of emotion, providing a basis for

understanding the potentially unique roles that interrelated self-

regulatory systems may play in emotion regulation. Second, these

findings contribute to understanding how effortful control, work-

ing memory processes, and inhibition might be integrated and

differentiated. That is, consistent with a measurement perspective,

we were able to show that working memory and effortful control

operate as similar constructs because they not only demonstrate

associations with one another, but they also demonstrate similar

patterns of association, and dissociation, with potential correlates.

Methodological Implications

Prior studies examining processes potentially important for the

regulation of negative affect and/or the expression of negative

affect have frequently examined only one self- or emotion-

regulation-related process (e.g., working memory or inhibition). In

the current investigation, multiple interrelated aspects of self-

regulation were examined, and a distinction was made between the

dispositional tendency to experience negative affect and the ten-

dency to express negative affect. Based on zero-order correlations,

the EF of updating/monitoring information in working memory

and effortful control were consistently associated with indicators

of dispositional negative affect as well as the tendency to express

negative affect. However, when modeled simultaneously using

SEM, it was evident that both effortful control and the EF of

updating/monitoring information in working memory were only

indirectly associated with the expression of negative affect. This

serves as an example of the importance of simultaneously mea-

-.66*

(-.47*)

-.11

-.23*

(17*)

.71*

.31*

Inhibition

43*

.25*

Expression

of Negative

Affect

Executive

Function

Monitoring/Updating

-.01

Effortful

Control

Dispositional

Negative

Affect

Executive

Function

Figure 4. Structural equation model, depicting standardized coefficients between latent variables, testing

associations between effortful control and the executive functions of updating/monitoring information in

working memory and inhibition, and between self-regulation constructs and the dispositional tendency to

experience negative affect and the tendency to express negative affect. 1. Standardized coefficient for the indirect

effect of effortful control on the expression of negative affect. 2. Standardized coefficient for the indirect effect

of updating/monitoring information in working memory on the expression of negative affect.

ⴱ

p ⬍ .05.

BRIDGETT, ODDI, LAAKE, MURDOCK, AND BACHMANN

suring and modeling multiple aspects of self-regulation as failing

to do so increases the possibility of missing theoretically important

effects. While work that seeks to isolate specific self-regulation

processes and the influence of such processes on the regulation of

behavior and emotion is important (e.g., Carlson & Wang, 2007;

Schmeichel et al., 2008; Levens & Gotlib, 2010), future work

could build on the current investigation by simultaneously consid-

ering different, but interrelated self-regulation processes in models

of emotional and behavioral regulation. Such work will contribute

important information regarding self-regulation that is potentially

distinct from work that seeks to isolate specific processes.

Another strength of the current investigation was the measure-

ment approach wherein all three studies included measures of EF

that can be used in both research and clinical applications. Because

of this approach, findings in the current investigation potentially

make stronger connections between findings regarding effortful

control and clinical findings regarding executive functioning, en-

hancing the translational implications of the findings in this study.

However, it should also be noted that there are a number of

additional methods available for assessing EFs in clinical and

research settings, and future studies may want to consider incor-

porating additional methods of assessing EFs. Similarly, different

measures of effortful control/executive attention, such as the At-

tention Network Test (Fan, McCandliss, Sommer, Raz, & Posner,

2002), could be used along with self-report and neuropsycholog-

ical measures of EFs and/or self-report measures of effortful

control.

Conclusion, Limitations, and Future Directions

The current investigation has a number of important strengths,

such as (1) the use of a multimethod approach for assessing aspects

of self-regulation, (2) the integration of multiple theoretical frame-

works (i.e., Gross, 1998b; Miyake et al., 2000; Rothbart, Derry-

berry, & Posner, 1994), and (3) the use of SEM to simultaneously

test hypotheses while better accounting for measurement error (see

Tomarken & Waller, 2005). Furthermore, the current investigation

reported three separate studies that converged in terms of conclu-

sions regarding connections between effortful control and EFs in

young adults. Our findings provide further support for the idea that

effortful control and certain aspects of executive functioning are

overlapping constructs, and we join the call to develop integrated

approaches to the study of self-regulation (e.g., Zhou et al., 2012).

Here, we also suggest, and in the current study used, a framework

that can be implemented to potentially aid in the development of

integrated approaches to self-regulation. Specifically, when two

(or more) aspects of self-regulation converge along conceptual,

biological, and developmental lines, share common correlates, and

when empirical connections are established, conceptual and theo-

retical integration may be warranted. Certainly, before such inte-

gration is established, it is important to consider measurement

issues. As in the current investigation, similar methods of mea-

surement are likely to yield stronger associations between (e.g.,

Study 1) and within (e.g., Studies 2 and 3) constructs than when

different methods are employed. While mixed methods may at

times yield more modest associations, these associations are par-

ticularly important when other converging evidence is available,

and findings are replicated.

Despite the strengths of the current study, there are also several

limitations that should be addressed in future work. In Studies 2

and 3, two aspects of EF, inhibition and updating/monitoring

information in working memory, as proposed by Miyake et al.

(2000) were examined. However, attention shifting, the third com-

ponent of the EF model proposed by Miyake et al., which is also

considered to be a core aspect of EF (Latzman & Markon, 2010;

Miyake et al.), was not considered. Similarly, in some studies,

attentional shifting has been noted as one aspect of the broader,

unitary effortful control construct (e.g., Putnam et al., 2006). On

the other hand, other studies (e.g., Hofer, Eisenberg, & Reiser,

2010; Rothbart et al., 2001; Rothbart & Bates, 2006) have found

that attention shifting did not load with, or was not related to, other

aspects of effortful control. Thus, it appears that attention shifting

is not consistently considered to be a component of effortful

control. The ATQ-SF (Evans & Rothbart, 2007) effortful control

factor, used in the current study, does not have an attention shifting

component, which, in part, was one reason why the EF of attention

shifting was not considered. Nevertheless, future work should

consider including attention shifting, examining its potentially

unique associations with other aspects of self-regulation to provide

important additional steps toward integrating and differentiating

aspects of self-regulation. Furthermore, given that prior work has

noted associations between attentional shifting and negative affect

(e.g., Compton, 2000; Eisenberg, Shepard, Fabes, Murphy, &

Guthrie, 1998; Johnson, 2009), future work should examine the

potentially unique role of this aspect of self-regulation in the

regulation of emotion.

It is also important to note that while some findings reported in

the current study are potentially consistent with what might be

anticipated based on the process model of emotion regulation

(Gross 1998b; Gross & Thompson, 2007), only participant reports

of greater or lesser tendencies to experience and express negative

affect were examined as opposed to placing participants in

emotion-eliciting situations. The benefit of this approach was that

it captured participants’ tendencies to experience and express

negative affect in day-to-day situations. The use of self-report

measures is also consistent with measurement methods frequently

used to examine questions regarding temperament and/or person-

ality (Gartstein et al., In Press). Nevertheless, addressing the

limitation of solely relying upon self-report for examination of

negative affect represents an important avenue for further investi-

gation. For example, future work might consider incorporating

laboratory tasks that elicit negative affect (e.g., frustration) as a

means to determine if better inhibition translates into fewer ex-

pressions of negative affect (see Carlson & Wang, 2007, for an

example), in the context of a model that also includes the dispo-

sitional tendency to experience negative affect and multiple self-

regulatory constructs.

Finally, the current study gathered information concurrently, not

longitudinally, and examined associations between effortful con-

trol and EF only in young adults. It will be important for future

investigations to use longitudinal methods, and to examine asso-

ciations between similar, and potentially overlapping aspects of

self-regulation across the entire life span (See Zhou et al., 2012 for

a similar suggestion). Despite the limitations noted above, the

current investigation makes an important contribution by linking

different areas within psychology that have focused, in part, on

understanding self-regulation. The approach and findings reported

SELF-REGULATION

here provide a useful framework for future investigations aimed at

refining theoretical approaches to the study of self-regulation, and

provide some evidence that different, but related aspects of self-

regulation may play differential roles in the regulation of emotion.

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Received July 1, 2011

Revision received June 25, 2012

Accepted July 2, 2012 䡲

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