RSA has been identified as playing a role in children's self-regulation, emotion regulation, and cognitive control, which are essential for children's adaptive functioning (Beauchaine & Thayer, 2015; Eisenberg et al., 2011). EDA responds to almost all discrete emotions (Cacioppo & Berntson, 1997; Kreibig, 2010; Quigley & Barrett, 2014) and has been linked to implicit emotional and attentional processing (e.g., responses to threat, expectations, features, novelty) al., 2013).
Emotional and Physiological Concordance
A large body of work has qualitatively and quantitatively assessed the relationships between autonomic nervous system measures and discrete emotions (e.g., happiness, sadness, fear, anger, etc.) (Cacioppo &. Berntson, 1997; Kreibig, 2010; Lench et al.). , 2011; Quigley & Barrett, 2014). Others ask: if disharmony is the norm, when will concordance emerge (Lougheed et al., 2021).
Emotion Regulation and Coping
Research has shown age differences in emotion regulation and coping strategies (Eschenbeck et al., 2018; Zimmer-Gembeck & Skinner, 2011). This shows that parent–child tasks are effective in eliciting different emotions and emotion regulation.
Summary and Integration
The frequency, intensity, and valence of parental emotional expressions in the family context are related to child functioning, yet most empirical work on parent-child emotion regulation has been assessed in early childhood, not school-age children and adolescents (Bariola et al. al., 2011). Furthermore, dysfunctional parenting is a non-specific risk for internalizing and externalizing problems in youth (Berg-Nielsen et al., 2002).
The Current Study
Further, variability in physiological-emotional associations (with random slopes) will be explored, as physiological-emotional congruence is hypothesized to show significant individual differences and there are moderators of this association (Lougheed et al., 2021). Assess whether emotion regulation moderates the association between emotion ratings and physiological activity in youth and caregivers.
Procedure
This provision began in March 2020 and continued for the remainder of laboratory visits in accordance with Vanderbilt policy. Caregivers and youth then independently viewed the videotape of their conflict discussion in separate rooms and provided moment-to-moment ratings of their own on-task emotion (Girard, 2014).
Measures
The RSQ is a self-report questionnaire that includes 12 items measuring the level of family stress (eg, fighting with your mother) and 57 items measuring three volitional coping scales (ie, primary controlling coping, secondary controlling coping, . removed coping). , and two involuntary responses to stress scales (i.e., involuntary. In this study, these scales demonstrated acceptable internal consistency for parent self-report (primary coping control, a = .76; secondary coping control, a = .83; coping disengagement, a = .74; involuntary inclusion, a = .91; involuntary exclusion, a = .86) and child self-report (primary control coping, a = .78; secondary control coping, a = .75; disengagement coping, a = .83; involuntary inclusion, a = .92; involuntary release, a = .88).
Data Analytic Strategy
Six participants (4 youth, 2 adults) did not complete the CARMA emotion assessment procedure; two participants (1 dyad) missed part (4 epochs) of the emotion ratings due to technical camera failure. Finally, intraclass correlation coefficients (ICC) were estimated in the null model predicting emotion ratings, taking into account clustering to identify the need for multilevel modeling (Pornprasertmanit et al., 2014). The ICC (between-groups variance/total variance) is a ratio that indicates how much of the observed variation in predictions of emotion ratings can be attributed to differences between individuals (i.e., the grouping variable in the current study).
Age, gender, and topic type were first entered into the model as predictors of emotion ratings with fixed effects. To test Aim 1, level 1 physiological–emotional concordance was modeled as the effects of the individual's physiological activity on the individual's emotion ratings (See Appendix for MLM comparisons). Disagreement was reflected in a negative prediction of emotion ratings by physiological activity, such that higher physiological activity scores corresponded to lower emotion ratings.
A one-sample t-test showed that the conflict discussion task also successfully elicited an emotional response (i.e., a change in emotion rating from baseline) from participants, t p = .008, where ratings (M = 5.20, SD = 26.76) was generally significantly different from zero (reflecting a small elevation to an overall positive emotion rating), d = .19, a small effect.
Aim 1: Associations Between Physiology and Emotion Ratings
The between-groups variance was also significant (score = 652.93, SE = 73.47, p < .001), indicating significant between-person (parent and adolescent) differences in emotion ratings. Gender was a significant predictor of emotion ratings (coefficient = −9.70, SE = 4.80, p = .045), demonstrating that emotion ratings were lower (ie, more negative) in females. The within-group variance was significant and sufficiently large (score = 553.23, SE = 21.16, p < .001), indicating significant differences in emotion ratings within participants (parents and adolescents).
To investigate whether the association between SCL and emotion ratings differed for parents and youth (ie, subject type predicted the SCL-emotion slope), an interaction between SCLtp and subject type was added to the previous model. The within-group and between-group variance (p < 0.001) was quite large and significant, indicating variability in emotion ratings within and between subjects. In contrast, in the youth parallel model, all predictors of emotion ratings were significant (Table 5, Model 2).
Age significantly predicted emotion ratings (coefficient = -4.70, SE = 1.74, p = .008), where higher age corresponded to more negative emotion ratings during the conflict task ( Figure 1 ).
Aim 2: Emotion Regulation and Physiological-Emotion Concordance
Primary control coping was a significant predictor of emotion ratings (coefficient = 133.76, SE = 43.35, p = 0.002), with increased reported use of primary control coping in response to family stress corresponding to more positive emotion ratings during the laboratory task (Figure 3, Panel A). Primary control coping remained a significant predictor of emotion ratings (estimate = 127.23, SE = 42.92, p = .003), with increased primary control coping corresponding to more positive emotion ratings. Overall, primary control coping did not alter SCL-emotion or RSA-emotion associations, contrary to Hypothesis 2c, although primary control coping was a significant predictor of emotion ratings during the conflict task.
001, where higher reported use of secondary control coping strategies in response to family stress corresponded to more positive emotion ratings during the family conflict task in the laboratory (Figure 3, panel B). In summary, higher reported use of secondary control coping skills predicted more positive emotion ratings during the conflict task. Disengagement coping was a significant predictor of emotion ratings in the expected direction (estimated SE = 70.99, p = 0.024), with higher reported use of disengagement coping strategies corresponding to more negative emotion ratings during the laboratory conflict task (Figure 3, Panel C) .
Overall, involuntary engagement in response to family stress predicted more negative emotion ratings during the parent–adolescent conflict task.
Aim 1: Physiological-Emotional Associations
In youth, the ability to regulate emotions has been inferred from patterns of physiological-emotional responses, although not empirically assessed as a moderator of the physiological-emotional association (Hastings et al., 2009; Lanteigne et al., 2014; Smith et al. ). , 2011). One study also used the ERQ self-report measure, and cognitive reappraisal was not related to adults' physiological-emotional coherence while watching positive and negative films ( Brown et al., 2020 ). This is consistent with a body of work showing that primary and secondary control coping strategies are mostly adaptive responses to stressors (see Compas et al., 2017 for a meta-analysis and review).
If parents and youth are counseled to use primary and secondary control coping strategies during conflict, the interaction may result in more positive emotional experiences (e.g., Compas et al., 2010). As secondary control coping strategies are generally considered to be adaptive (Compas et al., 2017), this finding implies that increased SNS activity and higher use of acceptance, cognitive reappraisal, positive thinking, and distraction predict more positive . Some suggest that compliance may only occur when strong emotional experiences are unregulated (eg, in clinical populations) (Lougheed et al., 2021).
For example, individuals with snake phobia showed greater coherence between physiology and affective experience than individuals without a snake phobia in response to snake films (Schaefer et al., 2014).
Strengths, Limitations, and Future Directions
Some hypothesize that concordance may only occur in high-intensity, single-emotion states (eg, a pure fear response) that are rarely encountered in contemporary society, which mostly consists of lower-intensity, mixed-emotion states (Friedman et al. ., 2014). Indeed, some research has shown increased coherence for more emotionally intense films compared to those that are less emotionally intense (Brown et al., 2020). Of note, one study quantitatively assessed time lags between physiological measures and emotions and determined that different physiological measures have different best-fit time lags (Butler et al., 2014).
Previous research has often taken the absolute value of bipolar emotional experience rating scales (i.e., ranging from negative to positive) based on the expectation that physiological arousal will occur in response to greater emotionality regardless of valence (Brown et al., 2020; Butler Butler et al., 2014; Sze et al., 2010). Despite this fairly common practice, Lougheed et al. 2021) urged researchers to maintain the importance of emotional experiences in order to deepen understanding of both positive and negative emotional experiences and physiology, as crucial information can be missed by appraisal alone. While this study controlled for general levels of physiological responding (via person-centered physiological outcomes), measures of the ANS have been shown to vary with age (Cohen et al., 2020; Gray et al., 2018; Hinnant et al. ., 2017). ).
Significant within-individual variability in emotional experience was consistent across models in the current study, as in previous research, indicating the possible presence of moderators (Van Doren et al., 2021; Butler et al., 2014).
Conclusion
Evidence was found for SCL-emotional concordance in youth, and RSA was unrelated to emotional experience in the current study. The moderating role of various facets of emotion regulation, coping and involuntary stress responses on emotional-physiological concordance was assessed. Early life adversity and the stress response system: integrating dimensions of biological and psychological responses to stress in adolescence.
Discrepant patterns among emotional experience, arousal, and expression in adolescence: Relationships with emotion regulation and internalizing problems. Coping and responses to stress in Navajo adolescents: Psychometric properties of the responses to stress. ERQ = Emotion Regulation Questionnaire; PE = parameter estimate; SE = standard error; CR = cognitive reappraisal; ES = expressive suppression.
RSQ = Stress Response Questionnaire; PE = parameter estimation; SE = standard error; PCC = primary control coping. RSQ = Stress Response Questionnaire; PE = parameter estimation; SE = standard error; SCC = secondary control coping. 1p: slope term for the relationship between DV and level-1 SCL etp: random error term for the level-1 equation.
