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. Author manuscript; available in PMC: 2023 Nov 25.
Published in final edited form as: Soc Dev. 2016 Oct 17;26(3):560–574. doi: 10.1111/sode.12217

Parent–child negative emotion reciprocity and children’s school success: An emotion-attention process model

Anat Moed 1, Elizabeth T Gershoff 2, Nancy Eisenberg 3, Claire Hofer 4, Sandra Losoya 5, Tracy L Spinrad 6, Jeffrey Liew 7
PMCID: PMC10676019  NIHMSID: NIHMS1912968  PMID: 38009128

Abstract

Research has demonstrated that emotions expressed in parent–child relationships are associated with children’s school success. Yet the types of emotional expressions, and the mechanisms by which emotional expressions are linked with children’s success in school, are unclear. In the present article, we focused on negative emotion reciprocity in parent–child interactions. Using structural equation modeling of data from 138 parent to child dyads [children’s mean age at Time 1 (T1) was 13.44 years, SD = 1.16], we tested children’s negative emotionality (CNE) at T1 and low attention focusing (LAF) at Time 2 (T2) as sequential mediators in the relation between parent and child negative emotion reciprocity at T1 and children’s grade point average (GPA) and inhibitory control at T2. Our findings supported an emotion-attention process model: parent–child negative emotion reciprocity at T1 predicted CNE at T1, which predicted children’s LAF at T2, which was, in turn, related to low inhibitory control at T2. Findings regarding children’s GPA were less conclusive but did suggest an overall association of negative reciprocity and the two mediators with children’s GPA. Our findings are discussed in terms of emotion regulation processes in children from negatively reciprocating dyads, and the effects of these processes on children’s ability to obtain and use skills needed for success in school.

Keywords: attention/joint attention, emotion, parents/parenting, schools

1 |. INTRODUCTION

The emotional quality of parent–child relationships has long been recognized as a key to children’s school success (Morrison, Rimm-Kauffman, & Pianta, 2003; NICHD Study of Early Child Care, 2005). School success is defined as including children’s demonstration of understanding information and is generally measured by academic performance (DeRosier, Kupersmidt, & Patterson, 1994). Furthermore, there is consensus among researchers that an underlying factor of school success is children’s self-regulation (Blair, 2002). Self-regulation is a multifaceted construct encompassing cognitive and behavioral processes allowing individuals to maintain optimal levels of emotional, motivational, and cognitive arousal for adaptation (Blair & Diamond, 2008; Molfese et al., 2010). Children’s inhibitory control, a form of behavioral self-regulation, has been theoretically and empirically linked to processes necessary for learning to occur (e.g., enacting appropriate behavior in school, response to stimulation in school; Blair, 2002; Blair & Razza, 2007; Bull & Scerif, 2001; Eisenberg, Valiente, & Eggum, 2010; St. Clair-Thompson & Gathercole, 2006), and thus serves as a marker for children’s school success.

Moreover, there is mounting evidence that children’s emotions influence the manner in which they process and use information (Owens, Stevenson, Hadwin, & Norgate, 2012; Viljaranta et al., 2015). This idea has been proposed by researchers as early as Zajonc (1980), arguing that emotion and cognition constitute two independent processing systems and that emotion is often primary (i.e., that emotions regulate cognition, rather than vice-versa). More recently, Friedman and Förster (2010) showed that when individuals experience negative emotion while completing a task, their attention and functioning are not optimal because of deficiency in resources needed for processing and using information.

Parents’ expressions of negative emotions, as well as parents’ nonsupportive reactions to children’s expressions of negative emotions, are associated with children’s negative emotionality and poor emotion regulation (Dishion & Patterson, 2006; Eisenberg et al., 1999, 2001). An important question arising from these observations concerns the role of parents’ expressed negative emotion in processes that might interfere with children’s school success, particularly activities that require children to maintain an optimal level of emotional arousal (Eisenberg, Cumberland, & Spinrad, 1998; Gottman, Katz, & Hooven, 1997).

This article examines the relation of expressed negative emotion within parent–child interactions to children’s school success. Specifically, we proposed an emotion-attention process model to explain the pathways through which parent–child negative emotion reciprocity undermines children’s school success (see Figure 1 for the theoretical model). To that end, we examined a longitudinal sequential mediation model in which parent-child negative emotion reciprocity (i.e., parental expressed negativity in response to children’s negative emotion, and vice versa) predicts children’s negative emotionality (CNE) which, in turn, predicts later low attention focusing (LAF) that may undermine children’s school success as assessed by children’s (a) academic performance as indicated by their grade point average (GPA), and (b) inhibitory control at school (as rated by teachers), which is an indicator of behavioral self-regulation (Derryberry & Rothbart, 1988).

FIGURE 1.

FIGURE 1

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Standardized coefficients from structural equation modeling examining the links between parent and child negative emotion reciprocity and children’s school success as mediated through the CNE and LAF

1.1 |. Parent–child negative emotion reciprocity and children’s negative emotionality

Both research and theory have focused on the socialization of children’s emotion within the parent–child relationship. Research suggests that parenting practices such as modeling of emotion and reactions to children’s displays of emotions influence children’s emotional competencies (Eisenberg et al., 1998; Halberstadt & Eaton, 2002). However, some parental behaviors can elicit too much arousal in children. Although the methods parents use to activate children’s emotions are not entirely clear, there is considerable evidence that children are particularly vulnerable to displays of parental negative emotion. Children appear to have difficulty regulating their negative emotions in the presence of a parent’s negative emotion (Cummings, Iannotti, & Zahn-Waxler, 1985; Katz & Gottman, 1994).

Furthermore, experiencing negative emotion reciprocity may be even more problematic for children (Eisenberg, Fabes, & Murphy, 1996; Moed et al., 2015). Children’s experience of negativity in response to their own negative emotion may be followed with opposition or chains of defensive behaviors against criticism and disagreement, which can escalate into an extensive negative reciprocity between the parent and the child (Patterson, 1982). Because children may perceive their parent’s negative emotional reaction in response to their own negative emotion as unfair and negatively intended (Grusec & Goodnow, 1994), they may, in turn, react with anger and resistance that undermines the dyad’s ability to regulate emotion and develop mutually responsive patterns of interaction. It is important to note that although it is possible that in some cases child characteristics (e.g., temperament) are setting these negative reciprocities in motion, parents play an active role in perpetuating these interaction patterns (Sameroff, 2009; Shaw & Bell, 1993).

Extended negative emotion reciprocity may be one of the main factors that carries the risk for children’s development and well-being. This is derived from prominent researchers of coercive family and dyadic processes such as Patterson and Gottman. According to Patterson (1980), parents and children can develop patterns of reciprocated emotional exchanges, such that as the parent’s negativity increases, the child is more likely to react with increased negativity as well. Similarly, Gottman (1994) identified patterns of negative emotion reciprocity in the interactions of some couples such that when one spouse expressed negative emotion, the other spouse was more likely to respond with negative emotion, and so on. Such reciprocal expressions of negative emotion, Gottman argued, become an “absorbing state” which is resistant to change. That is, as negative reciprocity grows in length, the probability of successfully exiting it decreases. In parent–child interactions, research shows that such processes may activate children’s own negative emotion and resistance and over time may promote increased mutual negativity and adaptations in children that interfere with their development, well-being, and social relationships (Moed et al., 2015; Stoolmiller, Wilson, & Yamamoto, 2003).

A further implication of extended negative emotion reciprocity within parent-child interactions is that children may attend primarily to the negative emotional component of the conflict, whereas children who experience less negative reciprocity may better attend to the solution component of the conflict (Gottman, 1994; Moed et al., 2015). The negativity expressed by parents through extended reciprocations of negative emotions affects their children’s ability to regulate their own negative emotions (Eisenberg et al., 1999). This, in turn, may increase the pervasiveness of negative emotions across other interactions and situations, leading children to experience higher levels of negative emotionality even in the absence of overt negative cues. This argument is supported by research showing that individuals who are punished for the expression of negative emotions appear to learn to suppress their expression of the emotion, but paradoxically experience heightened negative reactivity in emotional contexts (Eisenberg et al., 1992; Gross & Levenson, 1997; Shipman & Zeman, 2001). Similarly, children with a history of abuse have been found to be hypersensitive in regard to the recognition of angry faces, misclassifying objectively neutral faces as angry (Pollak & Kistler, 2002). It has been suggested that this pattern of results is due, at least in part, to increased exposure to negative emotions in abusive households (Kavanagh, Youngblade, Reid, & Fagot, 1988). These findings suggest that the experience of negative emotion in the parent–child relationship can influence CNE, perhaps by increasing the significance children attribute to negative emotions.

1.2 |. Children’s negative emotionality and low attention focusing

Emotions influence attention (Blair & Ursache, 2011; Damasio, 1994). It has been proposed that children’s emotions influence their ability to focus and shift attention (Derryberry & Reed, 1996; Gray, 1982). Specifically, it has been suggested that children who generally experience high levels of negative emotionality have less effective attention management than children who experience more manageable levels of arousal (Calkins & Johnson, 1998; Eisenberg et al., 1997; Rothbart & Bates, 1998). In temperament research, for example, Rothbart and her colleagues demonstrated numerous times that children’s ability to control attention is related to negative emotionality (Derryberry & Rothbart, 1988; Rothbart et al., 2000). Although temperament is considered to be relatively stable and biologically based (Cloninger, Przybeck, Svrakic, & Wetzel, 1994; Thomas & Chess, 1977), it is modifiable as a function of environmental influences such as parents’ behaviors (Bridgett et al., 2009). It is thus possible that, with time, children exposed to high levels of parental negativity allocate attention disproportionately to anger and other negative emotions (Garner, 2010), whereas children who, in general, experience more manageable levels of emotional arousal may not become overly aroused by negative emotions, and can better focus their attention on adaptive ways of coping with various environmental demands (Hoffman, 1983).

Some investigators (Blair, 2002; Pekrun, Elliot, & Maier, 2009) have proposed that attention is a mediator in the relation between children’s negative emotions and their success in school. Blair (2002) suggested that negative emotions in children are likely to affect their ability to focus attention because the demand to do so is defeated by the demand to regulate the negative emotion. This, Blair (2002) suggests, will eventually lead to underused, and eventually underdeveloped, cognitive skills. Thus, when a child’s experience of negative emotion leads to rumination or focusing on that emotion, cognitive resources are directed to the events or circumstances that distract the child from learning and practicing cognitive and academic skills. In this manner, by reducing cognitive resources, negative emotionality may undermine performance on academic tasks and related activities.

1.3 |. The present study

The current study attempted to clarify the nature of the relation between parent and child negative emotion reciprocity and children’s school success, as measured by their academic performance (i.e., GPA) and behavioral self-regulation (i.e., inhibitory control) at school, and if this relation was mediated by CNE and LAF. To assess the relation between these two constructs, parent–child observed negative emotion reciprocity and CNE were assessed at one time point and children’s LAF, together with their inhibitory control and GPA, were assessed at a later time point. We examined whether the relation between observed negative emotion reciprocity around 13 years of age and children’s school success around 15 years of age was mediated through an emotion-attention mechanism. That is, we examined whether observed parent–child negative emotion reciprocity was associated with children’s increased negative emotionality, and whether that was linked with later LAF and with school success (assessed by academic performance and behavioral self-regulation).

2 |. METHOD

2.1 |. Participants

Participants were 139 parent–child dyads (126 mothers and 13 fathers) who were part of a larger longitudinal study of emotional and social development (Eisenberg et al., 1996, 2005, 2008). For the purpose of this article, we used data from only the fourth and fifth waves of the study, with an average of 1.88 years between assessments; these time-points henceforth will be referred to as T1 and T2, respectively, in the present article. One mother–child dyad was excluded from analyses because the videotape of their T1 interaction task was lost. Thirteen dyads on which we had observational data at T1 attrited between T1 and T2 (11 mother–child dyads and 2 father–child dyads). In the final T1 sample of 138 dyads, boys and girls were approximately equally represented (52% girls). Children’s mean age was 13.44 years (SD = 1.16), ranging from 11 to 16. Of the 138 children, 79% were non-Hispanic White, 13% were Hispanic, 3% were Native American, 2% were of Asian extraction, and 3% were reported as being of another race. Socioeconomic status varied widely. In terms of parental education, 3.6% of parents had less than a high school degree, 7.2% had a high school diploma but no further education, 19.6% had some college but no degree; 13.8% had a 2-year degree of some sort; 36.2% had a college degree; 16.7% had a graduate degree, and 2.9% did not report their level of education. Family income also ranged widely, with 6% of families earning less than $20,000 a year, 12% earning $20,000–$40,000 a year, 29% earning $40,000–$60,000 a year, 20% earning $60,000–$80,000 a year, 18% earning $80,000–$100,000 a year; and 12% earning more than $100,000 a year (3% of the families did not report their annual family income).

The families who participated in the discussion task at T1 were compared with the 59 participants from the longitudinal study who had attrited before or at T1 or who had only participated in the T1 assessment by mail. There were no differences by child temperament, income, parent education, or observed parenting variables. The only difference was in regard to race, with significant attrition by minority families (Eisenberg et al., 2008). All analyses were rerun with only those dyads with mothers and all results were the same; thus, we decided to retain the father–child dyads in the analyses while controlling for parent gender.

2.2 |. Design and procedures

The primary care-giving parent and child came to the laboratory for observed assessments. On arrival, the parent was escorted into a separate room to complete questionnaires while the child engaged in a variety of activities (see Eisenberg et al., 2008, for further details). While separated, the parent and the child separately completed a questionnaire (modified version of the Issues Checklist: Prinz, Foster, Kent, & O’Leary, 1979) to rate which issues had been major sources of disagreement in the past month (daily chores, school, manners). A graduate student compared the two sets of responses and chose the two issues rated as most conflictual by both parent and child, with the condition that the parent had to see a given issue as conflictual. Parents and children were then brought to a room and were asked to participate in a discussion task in which they would discuss their most conflictual issue for “5 to 10 minutes” and try to come up with a solution. The actual discussion length was 6 min for all dyads. The experimenter left the room and the discussions were videotaped with one camera focused on the head and torso of the parent and one on the head and torso of the adolescent. At the end of the 6 min, the experimenter reentered the room, regardless of whether the conflictual issue was resolved or not. At the end of the laboratory assessment, mothers and children were compensated $35–$50 for their participation. Fathers were compensated $5–$10.

In addition to the observations above, children’s teachers at T1 and at T2 (different sets of teachers at each assessment point) were contacted and asked to provide ratings of the children’s behaviors. Data from teachers were always collected at the end of the semester in which the families came into the lab. Forms went to teachers around mid-November or a bit later in the fall or in April in the spring. Teachers were compensated $25–$30 for their assistance.

3 |. MEASURES

3.1 |. Parent–child negative emotion reciprocity at T1

Parents’ and children’s ongoing nonverbal emotions were coded for the entire 6-min interaction using primarily the Family and Peer Process Code (Stubbs, Crosby, Forgatch, & Capaldi, 1998) with some specification of affect definitions from the Kahen Affect Coding System (Gottman et al., 1996, 1997). Using split-screen videotapes, positive, angry, and sad/distressed emotions were coded every 10-s interval (for a total of 36 intervals). For the analyses reported below, we focused solely on the two aspects of negative emotion: anger and sad/distressed affect. Anger was indicated by angry facial expressions (e.g., narrowed eyes), angry tone (e.g., yelling), and body language (e.g., threatening gestures). Indicators of sad or distressed affect were distressed facial expressions (e.g., raised inner eyebrows), distressed verbal tone (e.g., sad or resigned tone), and body language (e.g., crying). Extensively trained coders rated each form of negative affect on a scale from 1 (no evidence of negative affect) to 7 (strong or persistent negative affect) for each 10-s interval. All tapes were coded by a coder reliable on Izard’s Affex facial coding system (Izard, Huebner, Risser, McGinnes, & Dougherty, 1980); a second coder rated 23% of the tapes for reliability purposes. Intraclass correlations across raters for anger and sad/distress affect were .74 and .65 for parents and .71 and .71 for children, respectively.

To determine a cut-off point for the presence of negative affect, we looked at the distribution of negative affect codes across both intervals and participants and found that nearly half of observed negative affect was coded at 1 or 2 (25.7% and 23.9%, respectively) and nearly half at 3 or above (30.6% at 3, 16.7% at 4, 2.6% at 5, 0.4% at 6, 0.1% at 7). We thus decided to use the median of 2.5 as the cut-off for the presence of elevated negative affect, such that we considered significant negative affect to be present if it was coded as 3 or above on the 7-point intensity scale. To determine if negative affect was reciprocated, we aligned the parent and child negative affect codes by time and examined them sequentially to identify when both participants’ negative affect (anger or sadness/distress) was rated by the coders at a 1 or 2 (no or very mild negative affect) in one interval but then one participant’s anger or sadness/distress was coded as rising to a 3 or above in the next interval. We then looked at the subsequent time interval to see if the partner’s anger or sadness/distress was also coded as rising to 3 or above. If so, negative emotion reciprocity was identified. In other words, intervals in which either the parent or the child expressed negativity at an intensity of 3 or more, after previously expressing negativity at a low intensity of 1 or 2, and were then responded to with a similarly high intensity negative emotion (coded as 3 or more), marked the beginning of a negative reciprocity episode. As long as the parent and the child continued to sequentially exchange expressions of negative emotion at an intensity of 3 or more, negative emotion reciprocity was present. Similarly, intervals in which either the parent or the child dropped their negativity to 2 or below marked the end of the negative reciprocity episode. That is, negative emotion reciprocity was defined as continuing until one partner was observed to reduce his or her negative affect to a code of 1 or 2.

We constructed our measure of negative emotion reciprocity using each dyad’s longest observed negative reciprocity. In our data, negative emotion reciprocity varied widely across dyads, ranging from 0 (no negative reciprocity) to 35 interval-long chains out of a possible 36 intervals. The median was 6 consecutive intervals of negative reciprocity (mean = 6.4, SD = 6.3); 9 dyads had no negative reciprocities and received a score of 0 for negative emotion reciprocity. Based on the fact that each interaction included 36 intervals and that some reciprocities were extremely lengthy, we chose to use the length of the longest negative reciprocity rather than the average length of negative reciprocity each dyad had. This decision was based on the possibility that a dyad that had one long negative reciprocity (e.g., 30 intervals-long) could have only few additional short negative reciprocities within the 36 intervals (e.g., one additional 3-intervals long negative reciprocity), and thus an average would obscure the reality that the dyad was, in fact, in negative emotion reciprocity for the majority of the observed interaction. Finally, given the distribution of negative emotion reciprocity (skew = 1.5, kurtosis = 1.87), and because having one variable with a much larger distribution than the others can make it difficult to get to a model solution, we reduced this 0–36 scale to an 8-point scale. Dyads were distributed across the final 8-point scale reflecting the length of the longest interval as follows: 0 5 no chains of negative reciprocity (n = 9); 1 = a 2–3 interval-long chain (n = 21); 2 = a 4–5 interval-long chain (n = 27); 3 = a 6–7 interval-long chain (n = 22); 4 = a 8–10 interval-long chain (n = 20); 5 = a 11–13 interval-long chain (n = 14); 6 = a 14–16 intervallong chain (n = 5); 7 = a 17–36 interval-long chain (n = 20). Thus, dyads in the highest category (7) spent at least half of the 6-min interaction in a negative affect exchange. The mean of this reduced scale was 3.34 (SD = 2.12, skew = .37, kurtosis = −.9).

3.1.1 |. Children’s negative emotionality at T1

Teachers rated 12 items from the Block and Block (1980) Q-sort adapted for a questionnaire format concerning children’s tendency to express negative emotions (e.g., “Tends to brood and ruminate or worry,” “Cries easily, has rapid shifts in mood,”). These items were selected by three experts before analyses based on their content (see Eisenberg et al., 1996). Teachers were instructed to rate how descriptive of the child each item was, from 1 5 most undescriptive to 95 most descriptive (α = .85).

3.1.2 |. Low attention focusing at T1 and T2

To assess children’s attention focusing, parents completed the attention-focusing subscale from the child behavior questionnaire (CBQ, Goldsmith & Rothbart, 1991), which included 11 items assessing the ability to concentrate on a task when needed (e.g., “When drawing or reading a book, shows strong concentration”). α = .78 at T1; α = .77 at T2. Minor changes in wording on CBQ items were made when necessary to make the items age appropriate (e.g., “reading” was not in the original item above, which said when “drawing or coloring”).

3.1.3 |. Low inhibitory control at T1 and T2

The inhibitory control scale consisted of 13 items from the CBQ (Goldsmith & Rothbart, 1991) assessing children’s abilities to regulate their behavior (e.g., “Can lower his/her voice when asked to do so,” “Can wait before entering into new activities if s/he is asked to”) Teachers rated each item on a 7-point scale (1 = extremely true; 7 = extremely untrue; α = .82 at T1; α = .83 at T2). Higher scores thus represented lower inhibitory control. Note that children’s LIC at T2 was reported by a different set of teachers than those reporting CNE at T1.

3.1.4 |. Child grade point average at T2

Teachers reported on students’ overall academic achievement across all subjects (10 = D or below, 9 = C−, 8 = C, 7 = C+, 6 = B−, 5 = B, 4 = B+, 3 = A−, 2 = A, 1 = A+). We used the “mock report card” methodology used by Pierce, Hamm, and Vandell (1999). However, we adapted this measure to reflect the plus/minus grading system used in many of the local schools. In a different sample, parents’ and teachers’ reports of GPA using this same measure correlated above .70 with scores on students’ report cards (Swanson, Valiente, & Lemery-Chalfant, 2012). Note that in the present analyses higher scores represent lower GPA.

4 |. RESULTS

Descriptive statistics for and correlations among all key variables are presented in Table 1. Each analysis below included the following covariates: child’s gender, child’s age, ethnicity (non-Hispanic White vs. all others), participating parent’s education, and the gender of the participating parent. In addition, T1 levels of both LAF and LIC were controlled for in all analyses reported below. Covariates in our analyses were included on the basis of their potential (a) to be confounders in the associations among parent-child negative emotion reciprocity, child negative emotionality, attention focusing, inhibitory control, and GPA, (b) to affect the generalizability of the results, and (c) to affect the ability to draw proper conclusions.

TABLE 1.

Means, standard deviations, and bivariate correlations among the key variables

Mean SD 1 2 3 4
1 Negative reciprocity, T1 3.34 2.12
2 Negative emotionality, T1 3.31 1.21 .28**
3 Low attention focusing, T2 2.23 1.11 .27** .40**
4 Low grade point average (GPA), T2 4.12 2.41 .24** .28** .39**
5 Low inhibitory control, T2 1.42 1.03 .28** .18 .46** .22*
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*

p < .05

**

p < .01.

We tested a single two-outcome multiple mediation model (see Figure 1) in order to examine whether CNE leading to LAF is a possible mechanism by which parent–child negative emotion reciprocity undermines children’s school success. The path analysis and bootstrap testing of mediation reported below were performed using Mplus (version 6.12, Muthen & Muthén, 2011). According to Preacher and Hayes (2008), when testing multiple mediation models, bootstrapping analysis provides the most powerful and reasonable method of obtaining confidence limits for specific indirect effects. Yet, Preacher and Hayes do not discard the examination of specific indirect effects in order to tease apart the separate roles played by individual intervening variables. We therefore present below results from both methods: testing of indirect pathways and bootstrapping test of mediation. Mplus uses full information maximum likelihood to handle missing data. Results from path analysis examining the direct and indirect effects from negative emotion reciprocity to children’s low GPA and LIC are presented in Table 2. Figure 1 graphically displays all path coefficients in this model. Results from the bootstrapping analysis examining the effects of negative reciprocity on children’s low GPA and LIC are presented in Table 3. As outlined by Preacher and Hayes (2004), mediation is demonstrated when the confidence interval (CI) for the indirect effect does not contain zero (i.e., indicating that the indirect effect is significantly different than zero). One thousand bootstrap resamples were used to generate 95% CIs that estimated the size and significance of the indirect effects.

TABLE 2.

Direct, indirect, and total effects from path models predicting children’s low grade point average and LIC from parent to child negative emotion reciprocity

Low grade point average (GPA) B (SE) β
Direct effect
 Negative emotion reciprocity → Low GPA .16 (.11) .14
Specific indirect effects
 Negative emotion reciprocity → Negative emotionality → Low GPA .07 (.04) .06
 Negative emotion reciprocity → Low attention focusing → Low GPA .01 (.02) .01
 Negative emotion reciprocity → Negative emotionality → Low attentionfocusing → Low GPA .02 (.01) .01
 Total indirect effect: Negative emotion reciprocity → Low GPA .09 (.05) .08*
Total effect
 Negative emotion reciprocity → Low GPA .25 (.11) .22*
Low inhibitory control
Direct effect
 Negative emotion reciprocity → Low inhibitory control .11 (.04) .24**
Specific indirect effects
 Negative emotion reciprocity → Negative emotionality → Low inhibitory control −.02 (.02) −.05
 Negative emotion reciprocity → Low attention focusing → Low inhibitory control .01 (.02) .01
 Negative emotion reciprocity → Negative emotionality → Low attentionfocusing → Low inhibitory control .02 (.01) .04*
 Total indirect effect: Negative emotion reciprocity → Low inhibitory control .005 (.02) .01
Total effect
 Negative emotion reciprocity → Low inhibitory control .12 (.05) .25*
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Fit indices: X2 = 20.62 (p-value = .42), CFI = .99, TLI = .99, RMSEA = .02 (90% confidence interval between .00 and .09, probability RMSEA < = .05 is .71).

TABLE 3.

Mean bootstrap indirect effects from parent to child negative emotion reciprocity to children’s low GPA and LIC

Bootstrap effect 95% CI LL 95% CI UL
Low grade point average (GPA)
Direct effect
 Negative emotion reciprocity → Low GPA .16 −.05 .37
Specific indirect effects
 Negative emotion reciprocity → Negative emotionality → Low GPA .07 −.01 .20
 Negative emotion reciprocity → Low attention focusing → Low GPA .01 −.02 .07
 Negative emotion reciprocity → Negative emotionality → Low attentionfocusing → Low GPA .02 −.01 .08
 Total indirect effect: Negative emotion reciprocity → Low GPA .09 .02 .21
Total effect
 Negative emotion reciprocity → Low GPA .25 .04 .47
Low inhibitory control
Direct effect
 Negative emotion reciprocity → Low inhibitory control .11 .03 .21
Specific indirect effects
 Negative emotion reciprocity → Negative emotionality → Low inhibitory control −.02 −.07 .01
 Negative emotion reciprocity → Low attention focusing → Low inhibitory control .01 .01 .06
 Negative emotion reciprocity → Negative emotionality → Low attentionfocusing → Low inhibitory control .02 .01 .06
 Total indirect effect: Negative emotion reciprocity → Low inhibitory control .01 −.04 .06
Total effect
 Negative emotion reciprocity → Low inhibitory control .12 .03 .23
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Note. CI = confidence interval; LL = lower limit; UL = lower limit. Confidence intervals that indicate that an effect differs significantly from zero are bolded.

As shown in Table 2, none of the specific indirect paths from negative emotionality to low GPA was significant, indicating that none of the mediators was sufficient on its own to explain the association. An examination of the specific indirect paths from negative emotion reciprocity to low GPA reveals that negative emotion reciprocity did not predict low GPA via neither negative emotionality, β = .06, ns, nor LAF, β = .01, ns. Additionally, the specific indirect path in which both negative emotionality and LAF were tested as sequential mediators to low GPA was also nonsignificant, β = .01, ns. However, the total indirect effect from negative emotion reciprocity to low GPA, which is the sum of the three specific indirect paths (their combined effect on low GPA), was significant, β = .08, p < .05. Furthermore, the total effect from negative reciprocity to children’s low GPA (i.e., the sum of the direct and indirect effects) was also significant, β = .22, p < .05. This implies that the direct effect was significantly smaller than the total effect. This indicates that negative emotion reciprocity, negative emotionality, and LAF worked together to better explain children’s low GPA than simply negative emotion reciprocity by itself. Similar to the results obtained from the path analysis, the bootstrapping analysis indicated that none of the specific indirect effects was significant.

As indicated in Table 3, the mean bootstrap effect for the specific indirect path from negative reciprocity to low GPA via negative emotionality was .07, with a 95% CI between −.01 and .20. Because zero is in the CI, this indicates that this indirect effect was not significantly different from zero. The mean bootstrap effect for the specific indirect path from negative reciprocity to low GPA via LAF was .01, with a 95% CI between −.02 and .07, indicating that this indirect effect is nonsignificant. The mean bootstrap effect for the specific indirect path that takes both negative emotionality and LAF into consideration was also not significant. The mean bootstrap effect was .02, with a 95% CI between −.01 and .08. However, the total indirect effect from negative emotion reciprocity to low GPA was significant, with a mean bootstrap estimate of .09, and a 95% CI between .02 and .21. This implies that negative emotion reciprocity, negative emotionality, and LAF taken together better explained children’s low GPA than any specific indirect path. Yet, because none of the specific indirect paths was significant, it is difficult to determine how exactly they work together to explain children’s low GPA (MacKinnon, 2008).

In regard to children’s LIC, the indirect path from negative emotion reciprocity to LIC that goes through both negative emotionality and LAF was significant, β = .04, p < .05, indicating a mediational relation though these two variables. None of the other indirect paths (i.e., those involving either negative emotionality or LAF as a single mediator) was significant. Similarly, the bootstrapping analysis showed a significant indirect effect from length of parent–child negative emotion reciprocity to LIC via both CNE at T1 and children’s LAF at T2. The mean bootstrap estimate for the indirect effect was .02, with a 95% CI between .004 and .06. The fact that zero was not in the CI indicates a significant indirect effect of parent–child negative emotion reciprocity on LIC through CNE at T1 and their LAF at T2. As shown in Tables 2 and 3, the total indirect effect from negative emotion reciprocity to LIC was not significant. According to MacKinnon (2008), this is a common occurrence and does not affect the interpretation of the specific indirect effects. This pattern of results often occurs because the power of the test of the individual paths is larger than the power of the test of their product, due to the non-normality of the product.

5 |. DISCUSSION

Considerable research has demonstrated a link between emotions in parent–child relationships and children’s school success (NICHD Study of Early Child Care, 2005), yet the reason for this link has been unclear. In this study, we examined the possibility that extended reciprocations of negative emotion between parents and children undermine children’s school success via an emotion-attention based process. Although our results supported our hypothesis when examining children’s low inhibitory control (LIC), but not when examining GPA, our study generally demonstrated that extended parent–child negative emotion reciprocity interferes with children’s school success. Our results support previous findings regarding parents’ expressed negativity and children’s school success. Furthermore, this study extends previous work by considering the mediating effects of CNE and LAF. The results suggest that parent–child negative emotion reciprocity undermines children’s school success because it leads to increased levels of negative emotionality in children that in turn lead to LAF. Consistent with previous research (Blair, 2002; Pekrun et al., 2009), LAF was then associated with poor behavioral self-regulation, manifested by LIC. In addition, as indicated by the significant total effect and total indirect effect, children’s low GPA was also better predicted when negative emotionality and LAF were examined together with negative emotion reciprocity, but, due to the lack of significance of the specific indirect paths, the specific way in which these three variables work together to predict children’s GPA is unclear. These results demonstrate, at least in part, which patterns of negative expressions interfere with children’s school success and identify the possible affective-cognitive process that may contribute to the problematic parental behaviors linked to children’s school success.

5.1 |. Negative parent–child affect reciprocity and children’s school success

Our results support previous research suggesting that the home environment, including parent–child interaction, influences children’s success in school (Thompson & Raikes, 2007; Uddin, 2011) and that some children’s school success is undermined by early-emerging emotional problems such as temperamental vulnerability that may contribute to negative parent–child interactions (Shonkoff & Phillips, 2000; Thompson & Raikes, 2007). Although temperamental negative emotionality of both parent and child may contribute to the likelihood of negative reciprocity, it is likely that the ways family members typically deal with disagreements, conflict, and others’ negative emotions contribute to CNE, attention, and functioning at school.

We had hypothesized that parent–child negative reciprocity would be linked with school success through a two-mediator indirect pathway. Although this pathway was confirmed for GPA, it was not significant for inhibitory control. This finding seems in large part because there is a strong and direct link between parent and child negative reciprocity and children’s inhibitory control at a later point. The individual links along the mediational chain are significant, but this main effect overcomes them, indicating the importance of parent–child negative reciprocity for predicting children’s later behavioral regulation.

Although in the present study we sought to determine the underlying mechanisms by which negative parent–child emotion reciprocity undermines children’s school success, it may also be that parental behaviors associated with extended negative reciprocities are partly responsible for the associations we observed with children’s school success. One route of influence may involve a decreased flow of information between parents and children in affectively negative relationships. For example, parents may present tasks in a less appealing way, give children less or negatively charged feedback about their attempts to solve problems, or simply be unavailable resources for children. Furthermore, emotionally negative parent–child relationships may undermine children’s social competence (Eisenberg et al., 2001), impairing their ability to elicit and accept assistance from other adults on demanding behavioral or academic tasks. Given the social context of learning, such a disadvantage could hinder children’s academic development. It has long been argued that less socially competent children seem less likely to accept adults’ role in helping the transmission of higher mental functions from the interpsychological (social) to the intrapsychological (individual) plane (Vygotsky, 1978).

5.2 |. The mediating role of negative emotionality and low attention focusing

One particularly important association highlighted by this study is that between CNE and LAF. As hypothesized, not only were these two measures longitudinally related, but they appear to operate together as a process by which parent–child negative emotion reciprocity undermines children’s school success. A possible explanation to the longitudinal association between CNE and LAF is children’s need to regulate the negative emotions that endure as a result of extended negative emotion reciprocities in the parent–child relationship. If the interactions observed in the present study reflect the emotional environment within which parents and children function, it is reasonable to assume that this environment is, to some extent, responsible for the level of CNE. It may thus be that the elevated levels of negative emotionality experienced by children of negatively reciprocating parents require children to continuously regulate their emotion.

However, emotion regulation is cognitively costly. It requires self-monitoring and self-corrective actions, thus reducing the cognitive resources available for processing other information. Indeed, attentional models of self-regulation suggest that attention is a finite resource (Carver & Scheier, 1981), and it has been shown that modifying one’s emotions, thoughts, or behaviors may have the effect of decreasing attentional resources available for other tasks (Ellis & Ashbrook, 1989). Furthermore, resource models of self-regulation (Baumeister, Bratslavsky, Muraven, & Tice, 1998) hold that any sort of self-regulation depletes mental resources. Linking these models to emotion regulation, experimental studies by Baumeister and his colleagues (for a review, see de Ridder, Lensvelt-Mulders, Finkenauer, Stok, & Baumeister, 2012) found that emotion-regulating participants (compared to nonregulating participants) were less persistent on subsequent hand grip task and were found to solve fewer problems on a subsequent anagram task. In addition, Gross (2002) has shown that regulation of negative emotions consumes cognitive resources, impairing memory for information presented during the emotion regulation period. Applying these ideas to the present results, when parent–child negative emotion reciprocity is a prominent characteristic of children’s lives, the demand that children regulate these emotions may be sufficiently frequent that it regularly depletes resources children need for different aspects of success in school.

5.3 |. Strengths and limitations

The present study has several important strengths. First, negative emotion reciprocity was observed rather than reported, and was defined by the levels and synchronicity of the negative emotion expressed by both the parent and the child. Furthermore, by employing sequential methods to investigate parent–child interactions at a microanalytic level, we were able to examine dynamic features of parent–child emotional communication that play a part in children’s school success. Second, we used a longitudinal design that allowed us to relate some of the characteristics of parental expression of negativity to children’s school success in later childhood. Third, this study takes into consideration mediational processes between parental expression of negativity and children’s school success, a relation that has long been observed but had yet to be explained. Last, the different measures included in this study were independently assessed. We obtained observational data for assessing parent–child negative emotion reciprocity; we used multiple raters for the two mediators (i.e., teachers reported CNE at T1 and parents reported children’s LAF at T2); inhibitory control, one of the dependent variables at T2, was reported by a different set of teachers than those reporting CNE at T1; and, GPA, which is a relatively objective measure of performance, was reported by teachers at T2.

This work also has some limitations that should be taken into account when interpreting the results. First, although the relations between parent and child negative emotion reciprocity and children’s school success were assessed longitudinally, as was the association between the two mediators, each of the mediators was measured at the same assessment as either the independent variable or the dependent variable. Ideally, in order to fully establish longitudinal impacts, each of these four measures should be assessed at four separate sequential time points. Second, unmeasured spurious correlations may exist if the observed behavior of both parent and child is linked to some other traits they both share, such as intelligence or temperament. Third, it is possible that the processes examined in this study differ in younger children. Our focus on parent–child reciprocity of negative emotion may yield different results when examining different age groups. For example, younger children may be more likely to express negativity through emotions because their language is not yet developed to the point that they can verbally communicate their needs, concerns, and preferences in a negotiable way. This may change the likelihood of parents’ reciprocating their child’s negativity. Future studies may reveal a clearer view on this issue. Last, the fact that there was a moderate attrition of minority families may mean that our findings cannot be generalized to racial or ethnic minority families.

6 |. CONCLUSION

Previous research has provided support for the link between negative emotions in parent–child relationships and children’s school success. The present study extends this literature by being the first to examine the mechanism through which this link may exist. Our findings suggest that emotion-attention processes mediate the relation between parents’ negative expressions of emotion and some aspects of children’s school success. Furthermore, in relation to children’s school success, this study is the first to examine observed parent–child negative emotion reciprocity as one particularly toxic form of parental expressed negativity (Eisenberg et al., 2008; Patterson, 1982).

Our findings, taken together with previous research (e.g., Blair, 2002; Gross, 2002; Valiente, Swanson, & Eisenberg, 2012), provide some support for the potential role of emotion-related regulation in children’s school success. Parents can help children maintain negative emotions at a level that is adaptive for children’s academic functioning. These results highlight the need to incorporate parent–child emotional communication programs in families where children exhibit poor school success.

ACKNOWLEDGMENTS

The authors wish to acknowledge support for this research from the National Institute of Mental Health (1 R01 MH 60838) awarded to the third author and from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (1R01HD068522-02S1) awarded to the third author and Carlos Valiente.

REFERENCES

  1. Baumeister RF, Bratslavsky E, Muraven M, & Tice DM (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology, 74, 1252–1265. doi: 10.1037/0022-3514.74.5.1252 [DOI] [PubMed] [Google Scholar]
  2. Blair C. (2002). School readiness: Integrating cognition and emotion in a neurobiological conceptualization of children’s functioning at school entry. American Psychologist, 57, 111. doi: 10.1037/0003-066X.57.2.111 [DOI] [PubMed] [Google Scholar]
  3. Blair C, & Diamond A. (2008). Biological processes in prevention and intervention: The promotion of self-regulation as a means of preventing school failure. Development and Psychopathology, 20, 899–911. doi: 10.1017/s0954579408000436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Blair C, & Razza RP (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78, 647–663. doi: 10.1111/j.1467-8624.2007.01019.x [DOI] [PubMed] [Google Scholar]
  5. Blair C, & Ursache A. (2011). A bidirectional model of executive functions and self-regulation. In Baumeister RF & Vohs KD (Eds.), Handbook of self-regulation: Research, theory, and applications (2nd edn, pp. 300–320). New York:Guilford Press. [Google Scholar]
  6. Block JH, & Block J. (1980). The role of ego-control and ego-resiliency in the organization of behavior. In Collins WA (Ed.), Development of cognition, affect, and social relations: The Minnesota symposia on child psychology (Vol. 13, pp. 39–101). Hillsdale, NJ: Erlbaum. [Google Scholar]
  7. Bridgett DJ, Gartstein MA, Putnam SP, McKay T, Iddins E, Robertson C, ... Rittmueller A. (2009). Maternal and contextual influences and the effect of temperament development during infancy on parenting in toddlerhood. Infant Behavior and Development, 32, 103–116. doi: 10.1016/j.infbeh.2008.10.007 [DOI] [PubMed] [Google Scholar]
  8. Bull R, & Scerif G. (2001). Executive functioning as a predictor of children’s mathematics ability: Inhibition, switching, and working memory. Developmental Neuropsychology, 19, 273–293. doi: 10.1111/j.1467-8624.2007.01019.x [DOI] [PubMed] [Google Scholar]
  9. Calkins SD, & Johnson MC (1998). Toddler regulation of distress to frustrating events: Temperamental and maternal correlates. Infant Behavior and Development, 21, 379–395. doi: 10.1016/s0163-6383(98)90015-7 [DOI] [Google Scholar]
  10. Carver CS, & Scheier MF (1981). Self-consciousness and reactance. Journal of Research in Personality, 15, 16–29. doi: 10.1016/0092-6566(81)90003-9 [DOI] [Google Scholar]
  11. Cloninger C, Przybeck T, Svrakic D, & Wetzel R. (1994). TCI—The temperament and character inventory: A guide to its development and use. St Louis (MO): Center for Psychobiology of Personality, Washington University. [Google Scholar]
  12. Cummings EM, Iannotti RJ, & Zahn-Waxler C. (1985). Influence of conflict between adults on the emotions and aggression of young children. Developmental Psychology, 21, 495. doi: 10.1037/0012-1649.21.3.495 [DOI] [Google Scholar]
  13. Damasio AR (1994). Descartes’ error: Emotion, reason, and the human brain. New York: Grosset/Putnam. [Google Scholar]
  14. de Ridder DT, Lensvelt-Mulders G, Finkenauer C, Stok FM, & Baumeister RF (2012). Taking stock of self-control: A meta-analysis of how trait self-control relates to a wide range of behaviors. Personality and Social Psychology Review, 16, 76–99. doi: 10.1177/1088868311418749 [DOI] [PubMed] [Google Scholar]
  15. DeRosier ME, Kupersmidt JB, & Patterson CJ (1994). Children’s academic and behavioral adjustment as a function of the chronicity and proximity of peer rejection. Child Development, 65, 1799–1813. doi: 10.1111/j.1467-8624.1994.tb00850.x [DOI] [PubMed] [Google Scholar]
  16. Derryberry D, & Reed MA (1996). Regulatory processes and the development of cognitive representations. Development and Psychopathology, 8, 215–234. doi: 10.1017/s0954579400007057 [DOI] [Google Scholar]
  17. Derryberry D, & Rothbart MK (1988). Arousal, affect, and attention as components of temperament. Journal of Personality and Social Psychology, 55, 958. doi: 10.1037/0022-3514.55.6.958 [DOI] [PubMed] [Google Scholar]
  18. Dishion TJ, & Patterson GR (2006). The development and ecology of antisocial behavior. In Cicchetti D. & Cohen DJ (Eds.), Developmental psychopathology (Vol. 3, Risk, disorder, and adaptation, 2nd ed., pp. 503–541). Hoboken, NJ: Wiley. doi: 10.1002/9780470939406.ch13 [DOI] [Google Scholar]
  19. Eisenberg N, Cumberland A, & Spinrad TL (1998). Parental socialization of emotion. Psychological Inquiry, 9, 241–273. doi: 10.1207/s15327965pli0904_1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Eisenberg N, Fabes RA, Carlo G, Troyer D, Speer AL, Karbon M, & Switzer G. (1992). The relations of maternal practices and characteristics to children’s vicarious emotional responsiveness. Child Development, 63, 583–602. doi: 10.2307/1131348 [DOI] [PubMed] [Google Scholar]
  21. Eisenberg N, Fabes RA, & Murphy BC (1996). Parents’ reactions to children’s negative emotions: Relations to children’s social competence and comforting behavior. Child Development, 67, 2227–2247. doi: 10.1111/j.1467-8624.1996.tb01854.x [DOI] [PubMed] [Google Scholar]
  22. Eisenberg N., Fabes RA., Shepard SA., Guthrie IK., Murphy BC., & Reiser M. (1999). Parental reactions to children’s negative emotions: Longitudinal relations to quality of children’s social functioning. Child Development, 70, 513–534. doi: 10.1111/1467-8624.00037 [DOI] [PubMed] [Google Scholar]
  23. Eisenberg N, Gershoff ET, Fabes RA, Shepard SA, Cumber Land AJ, Losoya SH, ... Murphy BC (2001). Mothers’ emotional expressivity and children’s behavior problems and social competence: Mediation through children’s regulation. Developmental Psychology, 37, 475–490. doi: 10.1037/0012-1649.37.4.475 [DOI] [PubMed] [Google Scholar]
  24. Eisenberg N, Guthrie IK, Fabes RA, Reiser M, Murphy BC, Holgren R, ... Losoya S. (1997). The relations of regulation and emotionality to resiliency and competent social functioning in elementary school children. Child Development, 68, 295–311. doi: 10.2307/1131851 [DOI] [PubMed] [Google Scholar]
  25. Eisenberg N, Hofer C, Spinrad T, Gershoff E, Valiente C, Losoya SL, ... Maxon E. (2008). Understanding parentadolescent conflict discussions: Concurrent and across-time prediction from youths’ dispositions and parenting. Monographs of the Society for Research in Child Development, 73, 1–160. (Serial No. 290, No. 2). doi: 10.1002/9781444307252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Eisenberg N, Valiente C, & Eggum ND (2010). Self-regulation and school readiness. Early Education and Development, 21, 681–698. doi: 10.1080/10409289.2010.497451 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Eisenberg N, Zhou Q, Spinrad TL, Valiente C, Fabes RA, & Liew J. (2005). Relations among positive parenting, children’s effortful control, and externalizing problems: A three-wave longitudinal study. Child Development, 76, 1055–1071. doi: 10.1111/j.1467-8624.2005.00897.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Ellis HC, & Ashbrook PW (1989). The “state” of mood and memory research: A selective review. Journal of Social Behavior & Personality, 4, 1–21. [Google Scholar]
  29. Friedman RS, & Forster J. (2010). Implicit a€ ffective cues and attentional tuning: An integrative review. Psychological Bulletin, 136, 875. doi: 10.1037/a0020495 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Garner PW (2010). Emotional competence and its influences on teaching and learning. Educational Psychology Review, 22, 297–321. doi: 10.1007/s10648-010-9129-4 [DOI] [Google Scholar]
  31. Goldsmith HH, & Rothbart MK (1991). Contemporary instruments for assessing early temperament by questionnaire and in the laboratory. In Angleitner A. & Strelau J. (Eds.), Explorations in temperament (pp. 249–272). New York: Plenum. [Google Scholar]
  32. Gottman JM (1994). What predicts divorce? The relationship between marital processes and marital outcomes. Hillsdale, NJ: Lawrence Erlbaum. [Google Scholar]
  33. Gottman JM, Katz LF, & Hooven C. (1996). Parental meta-emotion philosophy and the emotional life of families: Theoretical models and preliminary data. Journal of Family Psychology, 10, 243–268. doi: 10.1037/0893-3200.10.3.243 [DOI] [Google Scholar]
  34. Gottman JM, Katz LF, & Hooven C. (1997). Meta-emotion: How families communicate. Mahwah, NJ: Lawrence Erlbaum Associates Inc. [Google Scholar]
  35. Gray JA (1982). The neuropsychology of anxiety. New York: Oxford University Press.doi: 10.1017/s0033291700051175 [DOI] [Google Scholar]
  36. Gross JJ (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39, 281–291. doi: 10.1017/s0048577201393198 [DOI] [PubMed] [Google Scholar]
  37. Gross JJ, & Levenson RW (1997). Hiding feelings: The acute effects of inhibiting negative and positive emotion. Journal of Abnormal Psychology, 106, 95–103. doi: 10.1037/0021-843x.106.1.95 [DOI] [PubMed] [Google Scholar]
  38. Grusec JE, & Goodnow JJ (1994). Impact of parental discipline methods on the child’s internalization of values: A reconceptualization of current points of view. Developmental Psychology, 30, 4–19. doi: 10.1037/0012-1649.30.1.4 [DOI] [Google Scholar]
  39. Halberstadt AG, & Eaton KL (2002). A meta-analysis of family expressiveness and children’s emotion expressiveness and understanding. Marriage & Family Review, 34, 35–62. doi: 10.1300/J002v34n01_03 [DOI] [Google Scholar]
  40. Hoffman ML (1983). Affective and cognitive processes in moral internalization. In Higgins ET, Ruble DN, & Hartup WD (Eds.), Social cognition and social development: A socio-cultural perspective (pp. 236–274). Cambridge, UK: Cambridge University Press. [Google Scholar]
  41. Izard CE, Huebner RR, Risser D, McGinnes GC, & Dougherty LM (1980). The young infant’s ability to produce discrete emotion expressions. Developmental Psychology, 16, 132–140. doi: 10.1037//0012-1649.16.2.132 [DOI] [Google Scholar]
  42. Katz LF, & Gottman JM (1994). Patterns of marital interaction and children’s emotional development. In Parke RD & Kellam SG (Eds.), Exploring family relationships with other social contexts (pp. 49–74). Hillsdale, NJ: Erlbaum. doi: 10.4324/9780203772737 [DOI] [Google Scholar]
  43. Kavanagh KA, Youngblade L, Reid JB, & Fagot BI (1988). Interactions between children and abusive versus control parents. Journal of Clinical Child Psychology, 17, 137–142. doi: 10.1207/s15374424jccp1702_5 [DOI] [Google Scholar]
  44. MacKinnon DP (2008). Introduction to statistical mediation analysis. New York: Routledge. doi: 10.4324/9780203809556 [DOI] [Google Scholar]
  45. Moed A., Gershoff ET., Eisenberg N., Hofer C., Losoya S., Spinrad TL., & Liew J. (2015). Parent-adolescent conflict as sequences of reciprocal negative emotion: Links with conflict resolution and adolescents’ behavior problems. Journal of Youth and Adolescence, 44, 1607–1622. doi: 10.1007/s10964-014-0209-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Molfese VJ, Molfese PJ, Molfese DL, Rudasill KM, Armstrong N, & Starkey G. (2010). Executive function skills of 6–8year olds: Brain and behavioral evidence and implications for school achievement. Contemporary Educational Psychology, 35, 116–125. doi: 10.1016/j.cedpsych.2010.03.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Morrison EF, Rimm-Kauffman S, & Pianta RC (2003). A longitudinal study of mother–child interactions at school entry and social and academic outcomes in middle school. Journal of School Psychology, 41, 185–200. doi: 10.1016/s0022-4405(03)00044-x [DOI] [Google Scholar]
  48. Muthen LK, & Muth en B. (2011). Mplus 6.12 for windows. Los Angeles: Author. [Google Scholar]
  49. NICHD Early Child Care Research Network (Ed.). (2005). Child care and child development: Results from the NICHD study of early child care and youth development. New York: Guilford Press. [Google Scholar]
  50. Owens M, Stevenson J, Hadwin JA, & Norgate R. (2012). When does anxiety help or hinder cognitive test performance? The role of working memory capacity. British Journal of Psychology, 105, 92–101. doi: 10.1111/bjop.12009 [DOI] [PubMed] [Google Scholar]
  51. Patterson GR (1980). Mothers: The unacknowledged victims. Monograph of the Society for Research in Child Development, 45. [Google Scholar]
  52. Patterson GR (1982). A social learning approach. In Coercive family process (Vol. 3). Eugene, OR: Castalia Publishing. [Google Scholar]
  53. Pekrun R, Elliot AJ, & Maier MA (2009). Achievement goals and achievement emotions: Testing a model of their joint relations with academic performance. Journal of Educational Psychology, 101, 115. doi: 10.1037/a0013383 [DOI] [Google Scholar]
  54. Pierce KM, Hamm JV, & Vandell DL (1999). Experiences in after-school programs and children’s adjustment in first-grade classrooms. Child Development, 70, 756–767. doi: 10.1111/1467-8624.00054 [DOI] [PubMed] [Google Scholar]
  55. Pollak SD, & Kistler DJ (2002). Early experience is associated with the development of categorical representations for facial expressions of emotion. Proceedings of the National Academy of Sciences of the United States of America, 99, 9072–9076. doi: 10.1073/pnas.142165999 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Preacher KJ, & Hayes AF (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, and Computers, 36, 717–731. doi: 10.3758/bf03206553 [DOI] [PubMed] [Google Scholar]
  57. Preacher KJ, & Hayes AF (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891. doi: 10.3758/brm.40.3.879 [DOI] [PubMed] [Google Scholar]
  58. Prinz RJ, Foster S, Kent RN, & O’Leary KD (1979). Multivariate assessment of conflict in distressed and nondistressed mother-adolescent dyads. Journal of Applied Behavior Analysis, 12, 691–700. doi: 10.1901/jaba.1979.12-691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Rothbart MK, Ahadi SA, & Evans DE (2000). Temperament and personality: Origins and outcomes. Journal of Personality and Social Psychology, 78, 122. doi: 10.1037/0022-13514.78.1.122 [DOI] [PubMed] [Google Scholar]
  60. Rothbart MK, & Bates JE (1998). Temperament. In Eisenberg N. (Ed.), Damon W(Series Ed.), Handbook of child psychology (Vol. 3, Social, emotional and personality development, 5th ed., pp. 105–176). New York: Wiley. [Google Scholar]
  61. Sameroff AJ (2009). Conceptual issues in studying the development of self-regulation. In Olson SL & Sameroff AJ (Eds.), Biopsychosocial regulatory processes in the development of childhood behavioral problems (pp. 1–18). New York: Cambridge University Press. [Google Scholar]
  62. Shaw DS, & Bell RQ (1993). Developmental theories of parental contributors to antisocial behavior. Journal of Abnormal Child Psychology, 21, 493–518. doi: 10.1007/bf00916316 [DOI] [PubMed] [Google Scholar]
  63. Shipman KL, & Zeman J. (2001). Socialization of children’s emotion regulation in mother–child dyads: A developmental psychopathology perspective. Development and Psychopathology, 13, 317–336. doi: 10.1017/s0954579401002073 [DOI] [PubMed] [Google Scholar]
  64. Shonkoff JP, & Phillips DA (Eds.) (2000). From neurons to neighborhoods: The science of early childhood development. Committee on Integrating the Science of Early Childhood Development, National Research Council and Institute of Medicine. Washington, DC: National Academy Press. [PubMed] [Google Scholar]
  65. St Clair-Thompson HL, & Gathercole SE (2006). Executive functions and achievements in school: Shifting, updating, inhibition, and working memory. The Quarterly Journal of Experimental Psychology, 59, 745–759. doi: 10.1080/17470210500162854 [DOI] [PubMed] [Google Scholar]
  66. Stubbs J, Crosby L, Forgatch MS, & Capaldi DM (1998). Family and Peer Process Code: A synthesis of Three Oregon Social Learning Center behavior codes (Training Manual). Eugene, OR: Oregon Social Learning Center. [Google Scholar]
  67. Swanson J, Valiente C, & Lemery-Chalfant K. (2012). Predicting academic achievement from cumulative home risk: The mediating roles of effortful control, academic relationships, and school avoidance. Merrill-Palmer Quarterly, 58, 375–408. [Google Scholar]
  68. Thomas A, & Chess S. (1977). Temperament and development. New York: Brunner/Mazel. [Google Scholar]
  69. Thompson RA, & Raikes HA (2007). The social and emotional foundations of school readiness. In Perry DF, Kaufman RK, & Knitzer J. (Eds.), Social and emotional health in early childhood: Building bridges between services and systems (pp. 13–36). Baltimore, MD: Brookes. [Google Scholar]
  70. Uddin MK (2011). Parental warmth and academic achievement of adolescent children. Journal of Behavioral Sciences, 21, 1–12. [Google Scholar]
  71. Valiente C, Swanson J, & Eisenberg N. (2012). Linking students’ emotions and academic achievement: When and why emotions matter. Child Development Perspectives, 6, 129–135. doi: 10.1111/j.1750-8606.2011.00192.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Viljaranta J., Aunola K., Mullola S., Virkkala J., Hirvonen R., Pakarinen E., & Nurmi JE. (2015). Children’s temperament and academic skill development during first grade: Teachers’ interaction styles as mediators. Child Development, 86, 1191–1209. doi: 10.1111/cdev.12379 [DOI] [PubMed] [Google Scholar]
  73. Vygotsky L. (1978). Interaction between learning and development. Readings on the Development of Children, 23, 34–41. [Google Scholar]
  74. Zajonc RB (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35, 151. doi: 10.1037/0003-066x.35.2.151 [DOI] [Google Scholar]

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