Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Dec 1.
Published in final edited form as: Child Dev Perspect. 2022 Sep 2;16(4):208–214. doi: 10.1111/cdep.12464

Ecological validity in measuring parents’ executive function

Catherine M Diercks 1, Kelley E Gunther 1, Douglas M Teti 2, Erika Lunkenheimer 1
PMCID: PMC9799100  NIHMSID: NIHMS1837123  PMID: 36590076

Abstract

Parents’ executive functions (EFs), or cognitive skills facilitating thought and behavior management, are meaningful correlates of parenting behavior. EFs are theorized to support parents in inhibiting reactive responses, managing information during parent–child interactions, and adapting to novel developmental demands. Less effective EFs associate with risk for harsh parenting and physical abuse, underscoring the importance of research on parental EFs in promoting healthy child development. Yet, despite the strong theory, findings are mixed and reveal only modest effect sizes in relations between EFs and parenting. One explanation may be a lack of ecological validity in measuring parental EFs. Traditional measures of adult EFs have been used, but these are decontextualized and do not reflect the cognitively and emotionally demanding nature of parenting. In this article, we argue that new and adapted measures are needed. We discuss the role of EFs in parenting, review measurement, and offer suggestions for improvements in ecological validity.

Keywords: ecological validity, harsh parenting, parent self-regulation, parental executive function, parenting competence

Parenting behavior is multifaceted and multiply determined (Teti & Cole, 2011). A growing area of parenting research is that of parents’ executive functions (EFs), or higher-level cognitive skills facilitating the goal-oriented management of behavior via influence on lower-level, prepotent processes (Crandall et al., 2015; Friedman & Miyake, 2017). The EF skills of shifting flexibly among tasks, manipulating information via working memory, and inhibiting reflexive responding appear to support positive parenting (Deater-Deckard & Sturge-Apple, 2017; Rutherford et al., 2016; Shaffer & Obradovic, 2017). Parents with stronger EFs spend more time visually attending to their infants (Chico et al., 2014), show more parent–child affective flexibility and mutual positive affect (Zaidman-Zait, 2020), and demonstrate greater consideration for their children’s thoughts and feelings (Rutherford et al., 2018). Weaker EFs are associated with more negative parenting (Crandall et al., 2015), perhaps by magnifying the challenges of managing negative thoughts and emotions, leading to greater reactivity and less effective behavior management (Azar et al., 2008). Accordingly, we need detailed knowledge of the role of EFs in parenting to promote parenting competence and children’s well-being (Chang et al., 2003).

A complete understanding of EFs in parenting, and in human functioning more broadly, has been precluded by low ecological validity of measurement (Burgess et al., 2006). Determined by verisimilitude (whether measure conditions reflect those in daily life) and veridicality (whether a measured skill predicts performance in everyday situations), ecological validity is critical in applying basic science to real-world problems (Parsons et al., 2017). To our knowledge, no current measures of parental EFs demonstrate strong verisimilitude. Rather, most parenting research relies on traditional measures adopted from cognitive psychology. Since these measures were not designed to assess how EFs support or undermine parenting, they bear little resemblance to actual parenting environments, tending to assess EFs in paradigms devoid of the challenges and motivations of parenting. This low verisimilitude may also contribute to lower veridicality, as evidenced by modest effect sizes and inconsistencies in relations between EFs and parenting behaviors (Deater-Deckard & Bell, 2017; Deater-Deckard et al., 2012; Sturge-Apple et al., 2014). Bridging the disconnect between measurement and in vivo elicitations of parental EFs will offer new insights as to how, when, and for whom EFs predict parenting behavior. In this article, we discuss EFs in parenting, review empirical relations between existing EF measures and parenting behavior, and offer suggestions to enhance ecological validity.

EFS AND THE EMOTIONAL NATURE OF PARENTING

Executive functions facilitate behavior modification when reflexive responding would be inappropriate or disadvantageous (Diamond, 2013; Friedman & Miyake, 2017). Largely mediated by the prefrontal cortex, EFs include components such as inhibitory control (interruption of dominant responses, e.g., inhibiting parental interference in a child’s constructive efforts), working memory (manipulation and updating of information in the short term, e.g., applying dynamic contextual information to expectations for children), and cognitive flexibility (effective shifting among tasks or rule sets, e.g., shifting between conversation styles with toddlers and school-age children). These components are theorized to support more complex EFs such as planning or goal-based forethought (e.g., organizing a schedule to maximize children’s cooperation). Indeed, the unity and diversity conceptualization of EFs suggests that core EFs are both shared and distinct (Friedman & Miyake, 2017). For example, researchers have illustrated unity in identifying a common EF factor and diversity in factors specific to updating and shifting (Friedman et al., 2008).

Particularly relevant to parenting is an intricate connection between EFs and emotion regulation (Crandall et al., 2015; Rutherford et al., 2016). EFs are thought to exist on a spectrum from cool, or affectively and motivationally neutral, to hot, or affectively and motivationally salient (Zelazo, 2020). Cool paradigms may include more abstract stimuli (e.g., shapes), while hot stimuli tend to be more evocative (e.g., faces, money). Hot EFs are evoked in decision making involving risk, desire, and beliefs common to parenting, and parenting is an emotional experience necessitating continuous modulation of affect (Dix, 1991; Teti & Cole, 2011). Hot and cool aspects also apply to individual EF components in parenting. For example, hot inhibitory control may come online when a parent suppresses a harsh reaction to a misbehaving child; cool working memory may support updating routine care tasks to match children’s changing developmental needs. Stronger hot EFs may offer more adaptable strategies when challenged, such as reframing negative cognitions, inhibiting aggressive impulses, or developing solutions-based attributions for reactive child behavior (Azar et al., 2008). Thus, understanding within-person functioning in both hot and cool EF domains would shed light on antecedents and drivers of challenges with hot EFs that may lead to more negative parenting behaviors. However, traditional measures may insufficiently capture the dynamic and contextualized nature of these processes (Risko et al., 2016).

Emotion regulation appears to be supported by stronger connectivity between the prefrontal cortex and the amygdala, a structure underlying reactive emotion (Banks et al., 2007). Risk for behaviors such as harsh parenting increases in moments of parental negative emotion, and less effective EFs associate with risk for physical abuse via emotion dysregulation (Crouch et al., 2018). Despite the emotional nature of parenting (Dix, 1991) and evidence that stronger EFs attenuate negative affective responses to children (Deater-Deckard et al., 2010), measures of parental EFs rarely represent hot executive processing (Fontaine & Nolin, 2012). Whereas cool EFs tapped by affectively neutral task paradigms may be relevant for families’ routine maintenance or for scaffolding children’s learning, hot EF processes may be relevant to higher-risk motivationally and affectively salient behaviors (e.g., harsh discipline).

Social information processing approaches underscore the need for empirical integration of EFs and emotion. Theorists posit that EFs influence in-the-moment responding to children in a tripartite cycle of schemas, EFs, and attributions (Azar et al., 2008). Schemas are knowledge structures rooted in life history. A social information processing approach suggests that EFs support parents in inhibiting unproductive responses rooted in schemas, incorporating dynamic contextual information, and shifting strategies to suit situational demands. By recruiting EFs, parents inhibit schema-reliant responses and mindfully consider adaptive, alternative, parent-centered attributions for successes and failures. This regulating role of EFs is underscored by work showing that EFs buffer relations between negative parental attributions about children and subsequent negative parenting behaviors (Sturge-Apple et al., 2014). As theory and evidence identify EFs as critical drivers of parenting behavior, it is crucial to assess parental EFs using paradigms representing the actual emotional and cognitive demands of parenting.

EMPIRICAL FINDINGS LINKING EFS AND PARENTING BEHAVIOR

Few measures of EFs align with theory about the emotional and cognitive demands of parenting. Still, when applied to parenting research, traditional EF measures have identified useful information. Across numerous studies, stronger performance on inhibitory control, working memory, and cognitive flexibility tasks related to lower levels of harsh and abusive parenting (Crouch et al., 2018; Deater-Deckard et al., 2010, 2012; Henschel et al., 2013; Sturge-Apple et al., 2017) and higher levels of positive parenting behaviors (Chico et al., 2014; Rutherford et al., 2018; Yatziv et al., 2018; Zaidman-Zait, 2020). Here, we review some of these findings. Brief descriptions of these commonly used EF task paradigms are listed in Table 1; more complete descriptions can be found elsewhere (e.g., Baggetta & Alexander, 2016; Zelazo, 2020).

TABLE 1.

Brief descriptions of executive function task paradigms

Component Task Description
Inhibitory control Stop-Signal Paradigm (Verbruggen & Logan, 2008) Participants make a simple discrimination following “Go” trials, but must refrain from responding following a random ‘Stop’ signal
Self-Control Scale (Tangney et al., 2004) Participants self-report their day-to-day implementation of self-control skills using a 36-item questionnaire
Working memory Digit Span Test (Wechsler, 1997) Participants repeat number sequences of increasing length. Forward and backward recall versions of the test are used
N-Back Test (Kirchner, 1958) Participants view a series of stimulus pictures and must determine whether stimuli presented match those presented “n” trials prior
Cognitive flexibility Wisconsin Card Sorting Test (Heaton, 1981) Participants sort cards varying in shape, color, and number based on learned hidden rules that change across the course of the task
Delis–Kaplan Color Word Interference Test (Delis et al., 2001) Participants name ink colors and color names of printed color words. Interference occurs when ink colors and color names contradict
Open in a new tab

Note: This is not an exhaustive list of EF task paradigms. Tasks mentioned in the article are outlined for clarity.

Inhibitory control measures assess abilities to thwart prepotent responses. Some research suggests that inhibitory control deficits may exacerbate risk for negative parenting, especially in higher-risk families. Researchers (Sturge-Apple et al., 2017) measured inhibitory control using a stop-signal paradigm (Verbruggen & Logan, 2008) with U.S.-based socioeconomically and ethnically diverse mothers, finding that a positive relation between socioeconomic risk and harsh parenting was explained by deficits in maternal inhibitory control. Similar findings have emerged from studies using self-reported aspects of inhibitory control: For example, one study (Henschel et al., 2013) administered the Self-Control Scale (Tangney et al., 2004) to socioeconomically diverse German mothers with and without histories of childhood abuse; abused mothers reported greater problems with self-control, which in turn related to greater potential for child abuse.

Measures of working memory assess abilities to manipulate short-term information. In research using classic measures, parents’ working memory deficits were negatively related to positive parenting behavior. In one study (Deater-Deckard et al., 2010), researchers administered a digit span task (Wechsler, 1997) to U.S.-based, socioeconomically diverse, majority-White mothers of twins; negative affective reactivity to children’s challenging behavior was present only in mothers with lower working memory capacity. In another study (Yatziv et al., 2018), researchers applied the n-back task (Kirchner, 1958) to socioeconomically diverse Israeli mothers of two-parent households; mothers with less optimal working memory struggled more often to consider their infant’s mental state in interpreting and responding to the infant’s behavior in real time.

Measures of cognitive flexibility assess efficiency in shifting among task or rule sets. Studies using the Wisconsin Card Sorting Test (WCST; Heaton, 1981) suggest that cognitive flexibility may promote more optimal parenting by allowing parents to notice and respond appropriately to their children’s cues. Researchers (Chico et al., 2014) administered a version of the WCST to socioeconomically diverse teenage and adult Canadian mothers, finding that mothers with lower cognitive flexibility displayed less sensitivity with infants, defined as less awareness of infants’ cues and less appropriate and contingent responding. In another study, researchers (Crouch et al., 2018) administered the Delis–Kaplan Color Word Interference Test (Delis et al., 2001; similar to the Stroop, 1935 task) to assess inhibition/switching skills in U.S.-based socioeconomically and ethnically diverse mothers. They found that mothers with less effective inhibition/switching skills had a greater self-reported risk for child physical abuse; this relation was mediated by mothers’ emotion regulation difficulties. In summary, administering classic inhibition, working memory, and cognitive flexibility measures to parents has offered critical insights about the protective nature of these individual EFs for parenting.

Task composite and latent variable approaches have also been used to observe overall EF performance in parents. In a task composite approach, performance on a battery of EF component tasks is aggregated to create an overall EF performance score, which may offer greater predictive validity than occurs when examining individual components of EF (Deater-Deckard et al., 2012). In one study (Deater-Deckard et al., 2012), researchers administered a four-task battery (digit span, Stroop, WCST, Tower of Hanoi) to U.S.-based socioeconomically and ethnically diverse mothers. Using a composite approach in which scores were standardized and averaged, the study found that maternal EFs buffered the effects of harsh parenting on challenging child behavior. In another study of U.S.-based socioeconomically and ethnically diverse mothers (Crandall et al., 2018), a stronger EF composite score related to less controlling parenting attitudes, supporting the notion that EFs help parents inhibit reactive responses and use strategies flexibly. In a latent variable approach, components are measured independently, sometimes with multiple tasks per component, and then modeled as indicators of latent factors in analysis. Researchers used this approach to describe a common EF factor as well as updating-and shifting-specific factors (Friedman et al., 2008). Finally, a latent variable approach to describe individual EFs using multiple task paradigms may help address the problem of task impurity, or the influence of nonexecutive processing performance in individual EF tasks.

In summary, research using classic EF task paradigms provides important information about the relevance of EFs for parenting, and using these measures offers links to prior clinical, cognitive, and neuropsychological research. Despite bearing little resemblance to actual parenting demands, these tasks offer some evidence that the strengths and weaknesses of EFs play important roles in driving positive and negative parenting behaviors.

Moving forward with increased ecological validity

Although theory suggests that EFs influence emotionally salient activities, which we know parenting to be (Azar et al., 2008; Dix, 1991), associations between EFs and parenting behavior have been mixed and modest in size (Deater-Deckard & Bell, 2017; Deater-Deckard et al., 2012; Sturge-Apple et al., 2014). This may suggest that performance on traditional EF paradigms does not relate robustly to actual parenting (i.e., low veridicality; Parsons et al., 2017). For example, in addition to a tendency toward low effect sizes, research is conflicted as to the potential protective effects of EF in the context of parents’ stress (Park & Johnston, 2020; Sturge-Apple et al., 2017), the relevance of identifying emotion regulation strategies (Shaffer & Obradovic, 2017), and the roles of different EFs in behavior—for example, based on maternal age (Chico et al., 2014).

We should recognize possible explanations for these mixed and modest effects other than ecological validity. Some researchers (Enkavi et al., 2019) have highlighted the issue of the low test–retest reliability of many EF measures, and others (von Bastian et al., 2020) have suggested that between-study variation in data processing and selection of dependent variables may produce apparent inconsistency in findings. Given strong relations between socioeconomic status and EFs across the lifespan (Last et al., 2018), between-study variation in socioeconomic demographics may also obscure findings. Finally, modest effects may also result from shortcomings of parenting outcome measures, such as methodological entanglement of conceptually distinct parenting phenomena, reliance on homogeneous samples of parents, or low ecological validity in parenting measurement. Thus, disparate findings may be attributed to notable variation in methodological approaches in this area of parenting research.

Along with these possibilities, mixed and modest effects may be explained in part by classic EF measures showing low verisimilitude when applied to parenting (i.e., that these assessments do not reflect actual parenting conditions). Researchers emphasize the value of investigating both context-specific and context-general characteristics and functions of cognition, and of viewing ecological validity in terms of identifying specific contexts in which processes of interest are thought to unfold (Holleman et al., 2020). Indeed, such an approach would allow for theoretical expansion and more rigorous testing regarding the role of EFs in parenting as unique from the roles of EFs in nonparenting contexts. Specifically, improving the ecological validity of measuring parents’ EFs could illuminate whether and how the effects of EF skills vary by parenting situation or emotional salience of the parenting demand. Furthermore, theory could be expanded as to when and for whom parental EFs may serve as a protective factor. Indeed, to support struggling families in clinical settings, we need a strong empirical understanding of the theorized nuanced roles of EFs for parenting. If assessments of parents’ EFs fail to reflect real-world demands, it may be difficult to identify whether and how challenges with EFs affect parenting on an individual basis.

Accordingly, we recommend that existing EF task paradigms be augmented and that new ones be developed to reveal characteristics and functions of EFs in the unique environment of parenting. To understand more completely the role of EFs in parenting and the conditions under which EFs confer parenting risk or protection, measurement must be improved to represent more fully the conditions under which parental EFs are taxed (Deater-Deckard & Bell, 2017). Here, we offer a framework with which to consider specific areas of improvement in measuring parental EFs (Parsons et al., 2017). Whereas the question of verisimilitude may foster innovation in measurement, veridicality (i.e., the extent to which measured skills relate to performance in daily life) offers a rubric for empirically evaluating a measure’s ecological validity.

Improving verisimilitude and veridicality

The classic EF tasks used in parenting research are decontextualized, primarily tap affectively and motivationally neutral executive processes, and rely on stimuli bearing little resemblance to what taxes cognitive regulation in actual parenting. However, in other areas of EF research, conversations about improving ecological validity have begun and may help inform new developments in parenting research. Even small, incremental changes to existing measures may improve verisimilitude, for example, by modifying task content to increase relevance to real-world parenting demands or priming participants for parenting motivations (e.g., calming a public tantrum) when aiming to tap hot cognitive processes.

For example, some researchers have opted to administer existing task paradigms in the home environment (e.g., Yatziv et al., 2018). Assessing EFs in the home may offer increased ecological validity despite inherent limitations in between-subjects standardization. In-home assessments may reflect more accurately the emotional climate of day-to-day parenting and evoke schemas about parenting that do not typically emerge in the lab environment. In-home assessment could also offer additional insight into how features of the home environment such as clutter and chaos exacerbate parents’ EF difficulties (Deater-Deckard et al., 2012). Similarly, evidence suggests that the relation between EFs and parenting may be more pronounced in the context of socioeconomic hardship (Sturge-Apple et al., 2014), which may influence parenting behavior in the home environment where economic stressors are present (e.g., unpaid bills, overdue home repairs). Considering such environmental factors may be one way to achieve greater verisimilitude and offer evidence on parental EFs that could inform parenting supports for individuals from various socioeconomic backgrounds.

Another promising way to measure parental EFs in real-world parenting environments may be administrating existing or novel EF tasks using ecological momentary assessment (EMA). Although such an approach has not been applied to parenting, in one study, researchers demonstrated the feasibility of using smartphone app-based EMA to measure adolescents’ working memory and inhibitory control skills (Warren & Pentz, 2019). EMA offers the opportunity to examine fluctuations in EF performance and antecedents of these fluctuations. For example, researchers could test the hypothesis that reactive child behavior perpetuates parents’ maladaptive cognitions and thus increases EF demands (Crandall et al., 2018) using real-time measures of EMA-reported child behavior and parental cognitions alongside parental EF tasks. Specifically, EMA could be leveraged to identify mindful and regulated in-the-moment responsiveness to child stimuli (e.g., types of parental cognitions that associate with stronger within-subject EF performance). Because it is theorized that applying EFs to parenting varies based on time and context (Azar et al., 2008), time-sensitive EMA could offer a more realistic representation of how these processes unfold in actual parenting interactions (Risko et al., 2016). However, repeating EF measures could result in training effects and individual differences may appear in training effects among parents and parenting contexts.

To standardize conditions across parents while maintaining relevance to situational demands, another solution may be to assess parents’ EF in virtual environments (Parsons et al., 2017). Technological innovations make virtual environments more accessible and affordable than ever, facilitating the systematic manipulation of parenting stimuli and measuring millisecond-level responses. One example of a virtual EF measure is the SeeMe Virtual Interactive Shopping environment, which has been used with adults recovering from neurological problems (Nir-Hadad et al., 2017). Participants shop in virtual grocery environments and are evaluated on the efficiency and accuracy of their shopping. To our knowledge, virtual environments have not been applied to parental EFs, but they could be adapted to reflect emotionally evocative parenting stimuli (e.g., wrangling children, engaging in playtime, preparing meals) and the developmental status of children under study. For example, in a virtual mealtime environment, parents of toddlers may need to consider strategies to redirect their child’s focus to mealtime and encourage them to eat more independently. Researchers could assess parents’ cognitive flexibility, for example, by indexing the quantity or complexity of attempted strategies. In the neuropsychological literature, EF assessments in virtual environments predicted real-world performance and evoked reports of realistic experiences of the participants (Nir-Hadad et al., 2017).

Finally, another approach that may facilitate between-subjects standardization while introducing real-world parenting relevance is using infant simulators. Parents frequently carry out cognitively demanding tasks despite challenging children’s stimuli (e.g., loud and persistent infant cries). A corresponding task paradigm might administer caregiving-relevant EF tasks (e.g., efficiently sorting infant care products by category) while holding a crying simulator. One such example is the Leiden Infant Simulator Sensitivity Assessment (LISSA; Bakermans-Kranenburg et al., 2015): Looking and sounding like a real infant, the LISSA evokes behavior that correlates highly with mothers’ behaviors with their children. Such an approach would add ecological validity by representing the emotionally evocative environments that may strain parents’ EF skills.

As verisimilitude of parental EF measures increase, we should see respective improvements in veridicality, or the ability to predict real-world displays of EFs in parenting (Vazire et al., 2022). Currently, as evidenced by modest effect sizes linking EFs and parenting, as well as mixed findings, it appears that traditional EF task performance does not strongly reflect actual parental EFs. As we have noted, multiple reasons may explain mixed and modest effects in the literature. However, we suggest that these inconsistencies likely also result from a mismatch between the inherently emotional nature of parenting and the cool, decontextualized nature of traditional EF measurement. This is especially important since much research on parental EF addresses associations of parents’ EF challenges with emotionally charged behaviors such as harsh parenting and the potential for child abuse.

CONCLUSION

Executive function assessments that lack parenting relevance or emotional salience, or that fail to consider parenting beliefs and goals, may mask information about the role of EFs in parenting. Given the pivotal role of parenting in child development, we must go beyond traditional, decontextualized assessments designed without regard for the unique role of cognition in parenting. Adaptations of existing measures, especially those conducted in naturalistic in-home environments, EMA, and standardized virtual environments and simulators, may help improve the ecological validity of parental EF measurement. These novel directions could not only advance our scientific understanding of what drives parenting in the moment, but also help identify points of entry for adaptive in-the-moment parenting interventions.

FUNDING INFORMATION

This work was supported by the National Institutes of Health grants awarded to Diercks (T32HD101390), Lunkenheimer (R01HD097189), and Teti (R01HD052809, R01HD087266, R01HD088566), as well as a National Science Foundation Graduate Research Fellowship awarded to Gunther (DGE1255832).

Funding information

National Institute of Child Health and Human Development, Grant/Award Number: R01HD052809, R01HD087266, R01HD088566, R01HD097189 and T32HD101390; National Science Foundation, Grant/Award Number: DGE1255832; National Institute of Child Health and Human Development, Grant/Award Number: R01HD052809, R01HD087266, R01HD088566, R01HD097189 and T32HD101390; National Science Foundation, Grant/Award Number: DGE1255832

Abbreviations:

EF

executive function

EMA

ecological momentary assessment

LISSA

Leiden Infant Simulator Sensitivity Assessment

WCST

Wisconsin Card Sorting Test

Footnotes

CONFLICT OF INTEREST

The authors declare no conflict of interest.

REFERENCES

  1. Azar ST, Reitz EB, & Goslin MC (2008). Mothering: Thinking is part of the job description: Application of cognitive views to understanding maladaptive parenting and doing intervention and prevention work. Journal of Applied Developmental Psychology, 29(4), 295–304. 10.1016/j.appdev.2008.04.009 [DOI] [Google Scholar]
  2. Baggetta P, & Alexander PA (2016). Conceptualization and operationalization of executive function. Mind, Brain, and Education, 10(1), 10–33. 10.1111/mbe.12100 [DOI] [Google Scholar]
  3. Bakermans-Kranenburg MJ, Alink LRA, Brio S, Voorthuis A, & van Ijzendoorn MH (2015). The Leiden Infant Simulator Sensitivity Assessment (LISSA): Parenting an infant simulator as your own baby. Infant and Child Development, 24(3), 220–227. 10.1002/icd.1905 [DOI] [Google Scholar]
  4. Banks SJ, Eddy KT, Angstadt M, Nathan PJ, & Phan KL (2007). Amygdala-frontal connectivity during emotion regulation. Social Cognitive and Affective Neuroscience, 2(4), 303–312. 10.1093/scan/nsm029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Burgess PW, Alderman N, Forbes C, Costello A, Coates LM-A, Dawson DR, Anderson ND, Gilbert SJ, Dumontheil I, & Channon S (2006). The case for the development and use of “ecologically valid” measures of executive function in experimental and clinical neuropsychology. Journal of the International Neuropsychological Society, 12(2), 194–209. 10.1017/S1355617706060310 [DOI] [PubMed] [Google Scholar]
  6. Chang L, Schwartz D, Dodge KA, & McBride-Chang C (2003). Harsh parenting in relation to child emotion regulation and aggression. Journal of Family Psychology, 17(4), 598–606. 10.1037/0893-3200.17.4.598 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chico E, Gonzalez A, Ali N, Steiner M, & Fleming AS (2014). Executive function and mothering: Challenges faced by teenage mothers. Developmental Psychobiology, 56(5), 1027–1035. 10.1002/dev.21185 [DOI] [PubMed] [Google Scholar]
  8. Crandall A, Deater-Deckard K, & Riley AW (2015). Maternal emotion and cognitive control capacities and parenting: A conceptual framework. Developmental Review, 36(June), 105–126. 10.1016/j.dr.2015.01.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Crandall A, Ghazarian SR, Deater-Deckard K, Bell MA, & Riley AW (2018). The interface of maternal cognitions and executive function in parenting and child conduct problems. Family Relations, 67(3), 339–353. 10.1111/fare.12318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Crouch JL, McKay ER, Lelakowska G, Hiraoka R, Rutledge E, Bridgett DJ, & Milner JS (2018). Do emotion regulation difficulties explain the association between executive functions and child physical abuse risk? Child Abuse & Neglect, 80(June), 99–107. 10.1016/j.chiabu.2018.03.003 [DOI] [PubMed] [Google Scholar]
  11. Deater-Deckard K, & Bell MA (2017). Maternal executive function, heart rate, and EEG alpha reactivity interact in the prediction of harsh parenting. Journal of Family Psychology, 31(1), 41–50. 10.1037/fam0000286 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Deater-Deckard K, Sewell MD, Petrill SA, & Thompson LA (2010). Maternal working memory and reactive negativity in parenting. Psychological Science, 21(1), 75–79. 10.1177/0956797609354073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Deater-Deckard K, & Sturge-Apple ML (2017). Introduction to the special section: Mind and matter: New insights on the role of parental cognitive and neurobiological functioning in process models of parenting. Journal of Family Psychology, 31(1), 5–7. 10.1037/fam0000300 [DOI] [PubMed] [Google Scholar]
  14. Deater-Deckard K, Wang Z, Chen N, & Bell MA (2012). Maternal executive function, harsh parenting, and child conduct problems. The Journal of Child Psychology and Psychiatry, 53(10), 1084–1091. 10.1111/j.1469-7610.2012.02582.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Delis DC, Kaplan E, & Kramer JG (2001). Delis–Kaplan executive function system (DKEFS) technical manual. The Psychological Corporation. 10.1037/t1508 2–000 [DOI] [Google Scholar]
  16. Diamond A (2013). Executive functions. Annual Review of Psychology, 64, 135–168. 10.1146/annurev-psych-113011-143750 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Dix T (1991). The affective organization of parenting: Adaptive and maladaptive processes. Psychological Bulletin, 110(1), 3–25. 10.1037/0033-2909.110.1.3 [DOI] [PubMed] [Google Scholar]
  18. Enkavi AZ, Eisenberg IW, Bissett PG, Mazza GL, MacKinnon DP, Marsch LA, & Poldrack RA (2019). 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(12), 5472–5477. 10.1073/pnas.1818430116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fontaine D, & Nolin P (2012). Study of “hot” executive functions in a sample of parents who have been accused of physical abuse or neglect. Journal of Aggression, Maltreatment & Trauma, 21(1), 1–18. 10.1080/10926771.2012.632391 [DOI] [Google Scholar]
  20. Friedman NP, & Miyake A (2017). Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86(January), 168–204. 10.1016/j.cortex.2016.04.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Friedman NP, Miyake A, Young SE, DeFries JC, Corley RP, & Hewitt JK (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137(2), 201225. 10.1037/00963445.137.2.201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Heaton RK (1981). A manual for the Wisconsin Card Sorting Test. Western. [Google Scholar]
  23. Henschel S, de Bruin M, & Mohler E (2013). Self-control and child abuse potential in mothers with an abuse history and their pre-school children. Journal of Child and Family Studies, 23, 824–836. 10.1007/s10826-013-9735-0 [DOI] [Google Scholar]
  24. Holleman GA, Hooge ITC, Kemner C, & Hessels RS (2020). The ‘real-world approach’ and its problems: A critique of the term ecological validity. Frontiers in Psychology, 11(721). 10.3389/fpsyg.2020.00721 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Kirchner WK (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352–358. 10.1037/h0043688 [DOI] [PubMed] [Google Scholar]
  26. Last BS, Lawson GM, Breiner K, Steinberg L, & Farah MJ (2018). Childhood socioeconomic status and executive function in childhood and beyond. PLoS One, 13(8), e0202964. 10.1371/journal.pone.0202964 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Nir-Hadad SY, Weiss PL, Waizman A, Schwartz N, & Kizony R (2017). A virtual shopping task for the assessment of executive functions: Validity for people with stroke. Neuropsychological Rehabilitation, 27(5), 808–833. 10.1080/09602011.2015.1109523 [DOI] [PubMed] [Google Scholar]
  28. Park JL, & Johnston C (2020). The relations among stress, executive functions, and harsh parenting in mothers. Journal of Abnormal Child Psychology, 48(5), 619–632. 10.1007/s10802-020-00622-x [DOI] [PubMed] [Google Scholar]
  29. Parsons TD, Carlew AR, Magtoto J, & Stonecipher K (2017). The potential of function-led virtual environments for ecologically valid measures of executive function in experimental and clinical neuropsychology. Neuropsychological Rehabilitation, 27(5), 777–807. 10.1080/09602011.2015.1109524 [DOI] [PubMed] [Google Scholar]
  30. Risko EF, Richardson DC, & Kingstone A (2016). Breaking the fourth wall of cognitive science: Real-world social attention and the dual function of gaze. Current Directions in Psychological Science, 25(1), 70–74. 10.1177/0963721415617806 [DOI] [Google Scholar]
  31. Rutherford HJV, Booth CR, Crowley MJ, & Mayes LC (2016). Investigating the relationship between working memory and emotion regulation in mothers. Journal of Cognitive Psychology, 28(1), 52–59. 10.1080/20445911.2015.1075542 [DOI] [Google Scholar]
  32. Rutherford HJV, Byrne SP, Crowley MJ, Bornstein J, Bridgett DJ, & Mayes LC (2018). Executive functioning predicts reflective functioning in mothers. Journal of Child and Family Studies, 27, 944–952. 10.1007/s10826-017-0928-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Shaffer A, & Obradovic J (2017). Unique contributions of emotion regulation and executive functions in predicting the quality of parent-child interaction behaviors. Journal of Family Psychology, 31(2), 150–159. 10.1037/fam0000269 [DOI] [PubMed] [Google Scholar]
  34. Stroop JR (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662. 10.1037/h0054651 [DOI] [Google Scholar]
  35. Sturge-Apple ML, Jones HR, & Suor JH (2017). When stress gets into your head: Socioeconomic risk, executive functions, and maternal sensitivity across childrearing contexts. Journal of Family Psychology, 31(2), 160–169. 10.1037/fam0000265 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Sturge-Apple ML, Suor JH, & Skibo MA (2014). Maternal child-centered attributions and harsh discipline: The moderating role of maternal working memory across socioeconomic contexts. Journal of Family Psychology, 28(5), 645–654. 10.1037/fam0000023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Tangney JP, Baumeister RF, & Boone AL (2004). Higher self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324. 10.1111/j.0022-3506.2004.00263.x [DOI] [PubMed] [Google Scholar]
  38. Teti DM, & Cole PM (2011). Parenting at risk: New perspectives, new approaches. Journal of Family Psychology, 25(5), 625–634. 10.1037/a0025287 [DOI] [PubMed] [Google Scholar]
  39. Vazire S, Schiavone SR, & Bottesini JG (2022). Credibility beyond replicability: Improving the four validities in psychological science. Current Directions in Psychological Science, 31(2), 162–168. 10.1177/09637214211067779 [DOI] [Google Scholar]
  40. Verbruggen F, & Logan GD (2008). Response inhibition in the stop-signal paradigm. Trends in Cognitive Sciences, 12(11), 418–424. 10.1016/j.tics.2008.07.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. von Bastian CC, Blais C, Brewer GA, Gyurkovics M, Hedge C, Kałamała P, Meier M, Oberauer K, Rey-Mermet A, Rouder JN, Souza AS, Bartsch LM, Conway ARA, Draheim X, Engle RW, Friedman NP, Frischkorn GT, Gustavson DE, Koch I, … Wiemers EA (2020). Advancing the understanding of individual differences in attentional control: Theoretical, methodological, and analytical considerations. 10.31234/osf.io/x3b9k [DOI] [Google Scholar]
  42. Warren CM, & Pentz MA (2019). The feasibility and acceptability of assessing inhibitory control and working memory among adolescents via an ecological momentary assessment approach. Child Neuropsychology, 25(8), 1022–1034. 10.1080/09297049.2018.1556624 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Wechsler D (1997). Wechsler Adult Intelligence Scale (3rd ed.). Psychological Corp. [Google Scholar]
  44. Yatziv T, Kessler Y, & Atzaba-Poria N (2018). What’s going on in my baby’s mind? Mothers’ executive functions contribute to individual differences in maternal mentalization during mother-infant interactions. PLoS One, 13(11), e0207869. 10.1371/journal.pone.0207869 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zaidman-Zait A (2020). The contribution of maternal executive functions and active coping to dyadic affective dynamics: Children with autism spectrum disorder and their mothers. Autism, 24(3), 645–657. 10.1177/1362361319854653 [DOI] [PubMed] [Google Scholar]
  46. Zelazo PD (2020). Executive function and psychopathology: A neurodevelopmental perspective. Annual Review of Clinical Psychology, 16, 431–454. 10.1146/annurev-clinpsy-072319-024242 [DOI] [PubMed] [Google Scholar]

RESOURCES