Edited by: Vera Sacharin, University of Geneva, Switzerland
Reviewed by: Cosimo Urgesi, University of Udine, Italy; Peter McGraw, University of Colorado Boulder, USA
*Correspondence: Karen Niven, Manchester Business School, University of Manchester, Booth Street East, Manchester M15 6PB, UK. e-mail:
This article was submitted to Frontiers in Emotion Science, a specialty of Frontiers in Psychology.
This is an open-access article distributed under the terms of the
Individuals use a range of interpersonal emotion regulation strategies to influence the feelings of others, e.g., friends, family members, romantic partners, work colleagues. But little is known about whether people vary their strategy use across these different relational contexts. We characterize and measure this variability as “spin,” i.e., the extent of dispersion in a person’s interpersonal emotion regulation strategy use across different relationships, and focus on two key questions. First, is spin adaptive or maladaptive with regard to personal well-being and relationship quality? Second, do personality traits that are considered important for interpersonal functioning (i.e., empathy, attachment style) predict spin? The data used in this study is drawn from a large online survey. A key contribution of this study is to reveal that people who varied the type of strategies they used across relationships (i.e., those with high spin) had lower positive mood, higher emotional exhaustion, and less close relationships. A further key contribution is to show that spin was associated with low empathic concern and perspective taking and high anxious attachment style. High variability in interpersonal emotion regulation strategies across relationships therefore appears to be maladaptive both personally and socially.
People often try to shape the feelings of others in interpersonal relationships. This is reflected in the many anecdotal tales of people cheering friends up, making family members feel guilty, calming anxious coworkers, or making romantic partners feel jealous. Attempting to influence the feelings of a relationship partner has been termed “interpersonal emotion regulation” and research has documented that people use a broad range of interpersonal emotion regulation strategies (Niven et al.,
The first aim of this paper is to examine whether it is adaptive or maladaptive to have higher variation in the use of interpersonal emotion regulation strategies across different types of relationship (romantic, friendly or familial, work), focusing on the outcomes of personal well-being (i.e., positive mood, emotional exhaustion) and relationship quality (i.e., relational closeness). Based on analytic innovations within the psychology of interpersonal behavior (Moskowitz and Zuroff,
Emotion regulation refers to “the process of initiating, maintaining, modulating, or changing the occurrence, intensity, or duration of internal feeling states” (Eisenberg et al.,
Increasingly, however, researchers are interested in the social aspects of emotion regulation. Many theoretical models begin with the basic assumption that emotions and emotion regulation are typically experienced and engaged in the presence of others (e.g., Côté,
Within this broader context, the process of interpersonal emotion regulation has emerged as an important research concern. Interpersonal emotion regulation concerns deliberate attempts to influence others’ feelings. Although interpersonal emotion regulation can be used by larger social groups (e.g., a support group working together to alleviate the negative emotions of one of its members; Thoits,
A person engaging in interpersonal emotion regulation has many strategies at his or her disposal. A classification developed by Niven et al. (
Regulatory motive |
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To improve affect | To worsen affect | ||
Engaging with the target’s cognitions about his or her feelings or a situation in order to improve his or her affect, |
Engaging with the target’s cognitions about his or her feelings or a situation in order to worsen his or her affect, |
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Pleasant behaviors intended to improve the target’s affect, |
Unpleasant behaviors intended to worsen the target’s affect, |
Initial studies exploring the relative effects of these strategy types have primarily concentrated on differences between improving and worsening strategies. Improving strategies have been found to have positive consequences for the short-term affect and longer-term well-being of the agent and target of regulation and the quality of the relationship between the two, while worsening strategies are found to have negative consequences for these outcomes (Niven et al.,
While the emerging body of research concerning interpersonal emotion regulation has much to say about the use and effects of different strategies within social relationships, little is known about whether people vary their use of interpersonal emotion regulation across social contexts and if it is adaptive or maladaptive to do so. In the present study, we explore this question by investigating whether high variation in one’s use of interpersonal emotion regulation across relationships (i) facilitates or inhibits personal and social functioning, and (ii) is associated with personality traits that are typically considered functional or dysfunctional for interpersonal relationships. We focus on the use of interpersonal emotion regulation within three distinct types of relationships: romantic, familial or friendly, and work. According to Neyer et al. (
The idea that people might vary their behavior across different situations has been studied for some years now by researchers of interpersonal behavior (see Moskowitz,
Although early studies of variability focused on taking measures in multiple situations and calculating the standard deviation or coefficient of variability of mean scores across the various situations as an index of variation (e.g., Fleeson,
Applied to the present study, Moskowitz and Zuroff’s (
Theoretically, there are reasons to believe that high variability in the use of interpersonal emotion regulation strategies might be adaptive. In different relationships there are likely to be different demands and social norms, and it would seem important to display a certain degree of flexibility in the way one attempts to regulate a relationship partner’s emotions (the functional flexibility argument; Paulhus and Martin,
However, there are also reasons to believe that high variability might be maladaptive. It has been suggested that high variability is the result of heightened reactivity to the influence of situations, such that the person is unable to maintain consistency and to develop effective strategies for interaction (Erickson et al.,
In addition, variability might compromise people’s well-being. More inconsistent interactions are likely to be more demanding to carry out and will thus require more attention and effort, particularly if the person needs to repair interactions that have gone wrong (Schegloff et al.,
Although both perspectives are equally viable theoretically, the cumulative evidence from studies of spin in interpersonal behavior provides strong support for the perspective that high variability is maladaptive. Higher levels of interpersonal spin have been linked to indicators of poor quality relationships, including low relationship closeness, low dyadic adjustment, and high coworker social avoidance (Côté et al.,
Given that interpersonal spin might be maladaptive, it would seem important to understand its antecedents. Previous research has revealed that interpersonal spin is positively associated with personality traits typically considered to be dysfunctional (e.g., neuroticism) and negatively associated with functional traits (e.g., agreeableness, extraversion, self-esteem; Moskowitz and Zuroff,
Empathic concern and perspective taking are two facets of empathy, i.e., “the reactions of one individual to the observed experiences of another” (Davis,
Based on the existing evidence that spin tends to be maladaptive for the development of close relationships (Côté et al.,
A repeated measures study design was used, whereby participants reported their use of interpersonal emotion regulation strategies within up to three specific relationships: a romantic relationship, a work relationship, and a familial relationship or friendship. Those participants who did not have a romantic partner or who did not work did not complete the measures of their interpersonal emotion regulation within those particular relationships. Participants were randomly assigned to complete the interpersonal emotion regulation measures corresponding to each relationship in different orders, and independent-samples analyses of variance (ANOVAs) using the mean interpersonal emotion regulation strategy scores in the three different relationships as dependent variables confirmed no order effects (
An online survey was advertised to members of the public via several means, including advertising on websites that promote social sciences research studies and specialist websites designed to target harder-to-reach populations in order to ensure the sample was representative (e.g., lesbian gay bisexual transgender websites), as well as emails to staff and students at several UK universities. To be eligible to take part, people had to be over the age of 16. Informed consent was obtained from all respondents in a form at the start of the survey. A total of 1509 people completed the survey. Because calculating spin requires measures across multiple situations, respondents who only completed a single measure of interpersonal emotion regulation (
Our final sample therefore comprised 1211 participants (79% females). The ages of participants ranged from 16 to 71 (
Due to the relatively high load placed on participants of responding to the interpersonal emotion regulation measure up to three times relating to different relationships, we split our participants randomly into groups to complete our individual difference measures, so that each participant only had to complete one set of measures. A total of 228 participants (79% females;
The 12-item extrinsic subscale of the Emotion Regulation of Others and Self (EROS; Niven et al.,
Respondents’ self-reports of their use of interpersonal emotion regulation were validated using a follow-up measure of their strategy use as reported by the other person in each of their relationships. At the end of the survey, respondents were invited to leave the email addresses of those individuals who they had reported their use of interpersonal emotion regulation toward. These people were then contacted with a link to a new survey which comprised a single interpersonal emotion regulation scale; this time people were asked to report on use of strategies by their relationship partner (the original participant) toward themselves over the same 4 week period. Although only a small number of matched pairs were collected (
The self-report data was used to calculate spin. The first step to calculate spin was to create a motive score and a resource score for each relationship. The motive score was derived by taking the mean score of all six worsening items within a given relationship from the mean score of all six improving items. The resource score was similarly calculated by taking the mean score of all six behavioral items within a given relationship from the mean score of the six cognitive items. In the second step, the resulting scores on the dimensions of resource and motive for each relationship were treated as Cartesian coordinates (
Participants were asked to rate the closeness of each relationship they reported on, using the Inclusion of Other in the Self measure (Aron et al.,
Two indicators of participants’ well-being were included in the survey. The first was a six-item measure used to assess participants’ moods over the past 4 weeks. Each item was a mood state selected from the UWIST checklist (Matthews et al.,
The empathic traits of empathic concern and perspective taking were both measured using subscales from Davis’s (
Avoidant and anxious attachment styles were assessed using Brennan et al.’s (
We measured several variables to serve as controls in our analyses to help rule out possible alternative explanations. Specifically, we controlled for the age and gender of the participant, which might have been related to the outcomes of interest (e.g., relationship closeness, well-being). In addition, we controlled for variability in the gender of the relationship partner (calculated as the standard deviation of the gender of all relationship partners each participant reported on), because it is possible that people use different types of interpersonal emotion regulation strategies toward males and females, which could conflate our results. For a similar reason, we controlled for the number of relationships that participants had reported about (two or three), as higher variability would be expected when reporting on more relationships. Finally, we controlled for the mean amount of interpersonal emotion regulation used across all relationships (calculated as the average of all 12 strategies across all relationships reported on), to ensure that any observed relationships were uniquely relating to interpersonal emotion regulation variability rather than simply the amount of regulation used.
Mean levels of the use of each type of interpersonal emotion regulation strategy are shown in Table
Romantic relationship | Friend or relative | Work relationship | Mean strategy use across relationships | |
---|---|---|---|---|
Cognitive improving | 3.79 | 3.49 | 2.73 | 3.34 |
Behavioral improving | 3.95 | 3.43 | 2.51 | 3.30 |
Cognitive worsening | 1.76 | 1.32 | 1.20 | 1.43 |
Behavioral worsening | 1.58 | 1.25 | 1.21 | 1.35 |
Mean use of interpersonal emotion regulation | 2.77 | 2.38 | 1.92 | 2.35 |
The focus of the current study, however, was on between-relationship variation at the individual-level, operationalized as a person’s level of “spin.” Means, standard deviations, and correlations between spin and the other variables are displayed in Table
Mean | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1. Gender | – | – | ||||||||||||
2. Age | 30.96 | 12.08 | −0.06* | – | ||||||||||
3. Variability in gender of partner | 0.46 | 0.28 | 0.08** | 0.03 | – | |||||||||
4. Number of relationships reported | – | – | −0.02 | 0.17** | 0.22** | – | ||||||||
5. Mean interpersonal emotion regulation | 2.43 | 0.46 | 0.11* | −0.26** | −0.03 | −0.18** | – | |||||||
6. Relationship closeness | 3.93 | 1.35 | 0.06* | −0.26** | <0.01 | −0.10** | 0.40** | – | ||||||
7. Positive mood | 3.50 | 1.10 | −0.03 | 0.14** | −0.05 | 0.03 | −0.02 | 0.04 | – | |||||
8. Emotional exhaustion | 2.55 | 1.01 | 0.04 | −0.18** | 0.01 | −0.01 | 0.18** | 0.05 | −0.53** | – | ||||
9. Empathic concern | 3.95 | 0.61 | 0.21** | 0.03 | 0.02 | 0.03 | 0.13* | 0.13* | 0.07 | 0.02 | – | |||
10. Perspective taking | 3.51 | 0.65 | 0.10 | 0.25** | 0.06 | 0.04 | 0.07 | <0.01 | 0.10 | 0.04 | 0.42** | – | ||
11. Avoidant attachment | 2.78 | 1.08 | −0.02 | 0.05 | −0.09 | −0.27** | −0.06 | −0.30** | −0.14* | 0.22** | – | – | – | |
12. Anxious attachment | 3.61 | 1.29 | 0.20** | −0.30** | 0.02 | −0.22** | 0.17** | 0.03 | −0.44** | 0.35** | – | – | 0.16** | – |
13. Spin (inverse transformation) | 0.16 | 0.15 | −0.04 | 0.03 | 0.06* | 0.14** | −0.13** | −0.19** | −0.11** | 0.09** | −0.17* | −0.13* | 0.04 | 0.14* |
Spin was also negatively related to mean levels of interpersonal emotion regulation across the relationships (
Regression results further demonstrate that the observed relationships between spin and the main study variables held after controlling for participant age and gender, variation in partner gender, number of relationships reported, and mean levels of interpersonal emotion regulation. With regard to relationship quality and psychological well-being, regression analyses, shown in Table
Relationship closeness |
Positive mood |
Emotional exhaustion |
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β | β | β | ||||
Gender | 0.01 | 0.20 | −0.02 | −0.74 | 0.02 | 0.57 |
Age | −0.17 | −6.32** | 0.13 | 3.83** | −0.14 | −4.24** |
Variability in gender of partner | 0.02 | 0.91 | −0.06 | −1.60 | <0.01 | −0.01 |
Number of relationships reported | 0.01 | 0.30 | 0.05 | 1.34 | −0.02 | −0.44 |
Mean interpersonal emotion regulation | 0.34 | 12.72** | −0.01 | −0.20 | 0.16 | 4.89** |
Spin | −0.14 | −5.41** | −0.11 | −3.21** | 0.11 | 3.31** |
With respect to the individual difference predictors of spin, we ran our regression analyses separately for each predictor so that the effects of each predictor would not be conflated (empathic concern and perspective taking were correlated, as were anxious and avoidant attachment; see Table
Empathic concern |
Perspective taking |
Avoidant attachment |
Anxious attachment |
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---|---|---|---|---|---|---|---|---|
β | β | β | β | |||||
Gender | 0.07 | 0.98 | 0.04 | 0.62 | −0.05 | −0.83 | −0.09 | −1.44 |
Age | 0.04 | 0.61 | 0.08 | 1.04 | −0.04 | −0.72 | 0.02 | 0.27 |
Variability in gender of partner | 0.04 | 0.61 | 0.05 | 0.70 | −0.01 | −0.11 | −0.02 | −0.33 |
Number of relationships reported | 0.03 | 0.45 | 0.03 | 0.36 | 0.19 | 2.84** | 0.19 | 3.02** |
Mean interpersonal emotion regulation | −0.12 | −1.72 | −0.11 | −1.58 | <0.01 | 0.02 | −0.03 | −0.42 |
Empathic concern | −0.17 | −2.58* | ||||||
Perspective taking | −0.15 | −2.22 | ||||||
Avoidant attachment | 0.09 | 1.48 | ||||||
Anxious attachment | 0.21 | 3.25** |
Because spin was differentially related to mean use of different types of strategies, we also conducted exploratory analyses to investigate whether variability in different types of interpersonal emotion regulation related to the main study variables. To assess such variability, we calculated four measures of “flux” to assess the standard deviation in the use across different relationships of improving strategies, worsening strategies, cognitive strategies, and behavioral strategies (Moskowitz and Zuroff,
The results in Table
Flux in improving strategies | Flux in worsening strategies | Flux in cognitive strategies | Flux in behavioral strategies | |
---|---|---|---|---|
Flux in improving strategies | – | |||
Flux in worsening strategies | 0.07** | – | ||
Flux in cognitive strategies | 0.62** | 0.37** | – | |
Flux in behavioral strategies | 0.65** | 0.37** | 0.63** | – |
Relationship closeness | −0.14** | −0.01 | −0.10** | −0.14** |
Positive mood | <0.01 | −0.17** | −0.09** | −0.03 |
Emotional exhaustion | 0.03 | 0.20** | 0.08** | 0.06 |
Empathic concern | 0.03 | 0.03 | 0.03 | 0.03 |
Perspective taking | 0.04 | −0.07 | 0.01 | 0.03 |
Avoidant attachment | 0.13* | 0.05 | −0.05 | −0.03 |
Anxious attachment | 0.06 | 0.28** | 0.22** | 0.09 |
The regulation of others’ feelings is a common feature of most of the important relationships people have, e.g., those with romantic partners, friends or family members, and people at work. Our findings indicate that variability in a person’s interpersonal emotion regulation strategy use across these different relationships, as indicated by a person’s level of interpersonal “spin,” is associated with higher emotional exhaustion and lower positive mood and relationship closeness. Moreover, high anxious attachment style, low empathic concern, and low perspective taking were associated with higher levels of spin. These findings suggest that, in line with previous research on spin, high variability in the use of interpersonal emotion regulation can be considered maladaptive for both personal and social functioning (Moskowitz and Zuroff,
Our findings are consistent with theoretical arguments that high variability in interpersonal emotion regulation is a sign of heightened reactivity to the influence of situations (Erickson et al.,
A potential alternative explanation is that our findings were strongly influenced by the use of strategies to worsen others’ emotions. Strategies to worsen others’ emotions have previously been linked to negative outcomes (e.g., poor well-being; Niven et al.,
Against expectations, we did not observe a relationship between avoidant attachment style and interpersonal spin. We had anticipated this relationship because avoidant attachment style is typically considered dysfunctional (people with an avoidant attachment style tend to have poorer quality relationships, characterized by anger, hostility, and distress; Mikulincer,
The present study makes a key contribution to research on interpersonal emotion regulation. To date, most studies of this process have focused on exploring the divergent effects of different strategies used to regulate others’ emotions (e.g., Niven et al.,
A second key contribution of this research is with regard to studies of intra-individual variability. Previous studies have examined variability of interpersonal behavior and core affect, using the framework of spin (e.g., Moskowitz and Zuroff,
Nonetheless, there are some important limitations of the present study. First, our results are all based on self-reported cross-sectional data, which could be subject to biases, including social desirability. However, the validation of our self-reported interpersonal emotion regulation data against relationship partners’ reports, along with the fact that the key variable of interest, spin, was an indicator of variability across relationships rather than a mean score, gives us confidence that such biases have not unduly affected our findings. The direction of causality also cannot be stated with certainty, and thus future longitudinal research is needed on this subject. Second, due to a desire not to overload participants in the study, we only studied three types of relationships (romantic, friend or family, work), whereas interpersonal emotion regulation may be used in many other relational contexts (e.g., towards support group members, teammates in sports, or even strangers; Cahill and Eggleston,
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The support of the Economic and Social Research Council (ESRC) UK is gratefully acknowledged [RES-060-25-0044: “Emotion regulation of others and self (EROS)”].