Skip to main content
PMC home page
Springer Nature - PMC COVID-19 Collection logoLink to Springer Nature - PMC COVID-19 Collection
. 2023 Mar 10:1–9. Online ahead of print. doi: 10.1007/s12144-023-04432-4

People with higher relationship satisfaction use more humor, valuing, and receptive listening to regulate their partners’ emotions

Sarah A Walker 1,✉, Rebecca T Pinkus 1, Sally Olderbak 2, Carolyn MacCann 1
PMCID: PMC9999077  PMID: 37359582

Abstract

The emotional experiences you have with a romantic partner shape how satisfied you are in your relationship. Engaging in attempts to make a romantic partner feel better is linked with better relationship outcomes. However, it is not yet clear which specific processes people use to regulate their partners’ emotions, nor which processes are most strongly linked with relationship satisfaction. In the current study of 277 individuals (55% female), we tested the extent to which eight extrinsic emotion regulation processes (expressive suppression, downward social comparison, humor, distraction, direct action, reappraisal, receptive listening, and valuing) predict relationship satisfaction. Six of the eight processes showed significant positive correlations with relationship satisfaction, with the strongest associations for valuing (r = .43), humor (r = .33), and receptive listening (r = .27). Relative weights were significant only for valuing, humor, and receptive listening, suggesting that these are the most important predictors of relationship satisfaction. Results are discussed in terms of the distinction between intrinsic and extrinsic regulation processes and the potential importance of motives for regulation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-023-04432-4.

Keywords: Emotion regulation, Relationship satisfaction, Humor, Valuing

Emotion regulation refers to the processes people use to influence the intensity, duration, and expression of emotions (Gross, 2002). While emotion regulation is typically studied as an intrinsic process (how someone regulates their own emotions; Gross, 1998), there is substantial evidence that people also regulate the emotions of others (Niven, Macdonald et al., 2012; Nozaki & Mikolajczak, 2020; Williams et al., 2018). For example, you may try to make your romantic partner feel better if you noticed they have had a stressful day. This attempt to modulate the emotional experience of another person is understood as ‘extrinsic emotion regulation’ (Nozaki & Mikolajczak). Recent research shows that attempting to make your partner feel better (regulating their emotions) is linked to higher relationship satisfaction (e.g., Kinkead et al., 2021). However, it is not yet clear whether some extrinsic emotion regulation strategies may be more beneficial than others. For example, using positive reappraisal (encouraging your partner to re-interpret events more positively) may be a more effective approach than using expressive suppression (encouraging your partner to hide their emotions). As yet, there is no research comparing multiple extrinsic regulation processes in romantic relationships. We address this gap by examining the extent to which eight discrete extrinsic emotion regulation processes predict romantic relationship satisfaction.

Extrinsic emotion regulation

Emotion regulation is a core feature of our emotional lives and is important for personal wellbeing (Gross & John, 2003), workplace wellbeing (Fan & Wang, 2022; Greenier et al., 2021) and relationship quality (Niven et al., 2015; Williams et al., 2018). Research distinguishes between intrinsic (regulating one’s own emotions), extrinsic (regulating the emotions of another person), and interpersonal emotion regulation (regulating one’s own emotions through interpersonal social interactions) (Nozaki & Mikolajczak, 2020; Zaki & Williams, 2013). Both intrinsic and extrinsic emotion regulation can be represented by the Extended Process Model of Emotion Regulation (Gross, 2015) which is a theoretical framework used to understand how people regulate their own emotions, and the emotions of others. The model consists of three stages: (a) Identification. An individual must first recognize the need for regulation by inferring the emotional state of the target person, assigning a value to the emotional state, and then forming a regulation goal, (b) Selection. An individual perceives, evaluates, and chooses the most effective regulation processes, and (c) Implementation. An individual operationalizes the selected processes and evaluates the feasibility and outcomes of the specific tactic/s chosen.

There is a large extant literature exploring the range of processes people use to influence their own emotional experiences (Webb et al., 2012) with some strategies found to be more effective than others. For example, cognitive reappraisal (reframing a situation in a more positive light) has been found to be generally more effective than expressive suppression (not physically showing one’s emotions). However, less is understood about the processes people use to influence the emotional trajectory of others – known as extrinsic emotion regulation. Extrinsic emotion regulation is typically measured in terms of two broad goals: affect improving (i.e., enhancing someone else’s emotions) and affect worsening (i.e., diminishing someone else’s emotions; Niven et al., 2011). The primary conceptual model of extrinsic regulation describes multiple different processes that could be used to improve or worsen affect (Niven et al., 2009). For example, I could use humor to make a friend laugh, or use valuing to make an employee feel proud by telling them how important and valued their work is. Importantly, according to Nozaki and Mikolajczac (Nozaki & Mikolajczak, 2020), extrinsic emotion regulation has three core features: (1) the regulator must have the goal of influencing the emotional trajectory of another person, (2) the extrinsic regulation goal can either increase or decrease negative or positive emotions, and (3) extrinsic regulation is distinguished from other related constructs such as empathy and emotional contagion.

The expression of negative emotions can influence an emotional and behavioural responses in others (Keltner & Haidt, 1999; Keltner & Kring, 1998) which may motivate a sympathetic reaction toward the person expressing the negative emotion (Lench et al., 2016). Attempting to regulate the emotions of another person can result in the development of stronger relationships, and deeper trust in those relationships (Keltner & Haidt, 2001; Keltner & Kring, 1998; Niven et al., 2012). Evidence suggests that by regulating the emotions of others, an individual may experience an increase in their own positive affect, thereby benefiting from the act of helping others regulate their emotional experience (Austin et al., 2018; Austin & Vahle, 2016; Niven et al., 2012).

Although there is burgeoning interest in examining the broad categories of affect improving, and affect worsening, little is yet understood about the relative benefits of different, discrete regulation processes that people use to modulate the emotional experiences of others (MacCann et al., 2019) and the impact on regulation on the regulators perception of relationship satisfaction. To address this gap, the current study examines the eight regulation strategies of the Regulation of Others’ Emotions Scales (ROES; MacCann et al., 2019). Each process can be classified in terms of the degree of engagement with the target person (low, moderate, or high) and the focus of process (disengagement-focused, diversion-focused, change-focused, and relationship-focused; Table 1). Intrinsic emotion regulation research clearly shows that some processes are more effective than others (Mazzuca et al., 2019). We will explore if extrinsic regulation processes similarly have different effects on a key outcome among romantic partners - relationship satisfaction.

Table 1.

Description of extrinsic emotion regulation processes included in the Regulation of Others’ Emotions Scales (ROES; MacCann et al., 2019)

Process Description Focus Emotional Engagement

Expressive

suppression

 The regulator encourages the target to avoid verbally or physically expressing their emotions. Disengagement Low

Downward

comparison

 The regulator compares the target’s situation to someone in a worse situation. Disengagement Low
Humor The regulator tries to increase positive affect by making the target laugh (e.g., telling a joke or sharing a funny story). Diversion Moderate
Distraction The regulator attempts to reduce negative affect by refocusing the target’s attention away from the emotional event. Diversion Moderate
Direct action The regulator directly changes the target’s situation to reduce negative affect Change Moderate
Positive reappraisal This occurs when the regulator encourages the target to shift the way they think about a situation in order to increase positive affect. Change High
Receptive listening The regulator encourages the target to express their emotions to help reduce negative affect. Relationship High
Valuing The regulator expresses how much the target is valued and special to increase positive affect. Relationship High
Open in a new tab

Note: ER = extrinsic emotion regulation

Relationship satisfaction

Romantic relationships represent a core feature of people’s lives. Characteristics such as commitment, love, trust, communication, security, and emotional support help people evaluate how satisfied they feel in their relationship (Fletcher et al., 2015; Hendrick et al., 1998). Romantic relationships inevitably involve the ebb and flow of negative and positive events that influence both partners’ wellbeing (Antonucci et al., 2001). For example, when a person’s needs and expectations are not met in the relationship, this can lead to increased negative affect and adverse mental and physical health outcomes for both partners (Bravo et al., 2017; McNulty et al., 2021; Whisman, 2007). Furthermore, the longer adverse outcomes persist, the more likely relationship satisfaction will decline, potentially leading to a breakdown of the relationship (Bravo, 2017; McNulty et al.,2021). In contrast, when a person’s needs and expectations are met in the relationship, and arising conflict is met with effective communication and emotional support, this can lead to increased positive affect, wellbeing, self-esteem, life satisfaction, and relationship satisfaction (Antonucci et al., 2001; Pateraki & Roussi, 2013; Voss et al., 1999). Therefore, it is essential to examine and understand the factors that improve and maintain relationship satisfaction as well as identify factors that undermine relationship satisfaction.

Extrinsic emotion regulation and relationship satisfaction

Most research on emotion regulation in romantic relationships examines how people regulate their own emotions (rather than their partner’s emotions). However, one partner’s efforts to regulate their own emotions (intrinsic regulation) can also positively or negatively impact their partner’s emotions (extrinsic regulation; Proulx et al., 2007). We know that intrinsic emotion regulation affects romantic relationship functioning and satisfaction (Ben-Naim et al., 2013; Gross & John, 2003; Vater & Schroder-Abe, 2015). We also know that some processes are better than others. For example, intrinsic expressive suppression (suppressing one’s own emotions) leads to lower relationship satisfaction over time (Gross & John, 2003; Impett et al., 2012) whereas intrinsic cognitive reappraisal processes relate to higher relationship quality (Ruso et al., 2019). Similarly, downward comparison in romantic relationships tends to result in lower positive feelings (Pinkus et al., 2008). It is feasible that extrinsic expressive suppression, reappraisal, and downward social comparison might have similar effects on relationship satisfaction.

The two relationship-focused processes (valuing and receptive listening) centre on the relationship between the regulator and the target and involve high levels of engagement with the other person. Intuitively, relationship-focused processes should relate to people’s satisfaction in their relationships. There is evidence that empathic listening improves the other person’s emotional response to negative events in terms of both subjective feelings and physiological response (Seehausen et al., 2012). Moreover, using receptive listening relates to increased closeness and reduced loneliness (Nils & Rimé, 2012; Pauw et al. 2018).

There is also evidence that humor may relate to relationship satisfaction. Humor tends to improve positive emotions (Fredrickson & Levenson, 1998) and distract from negative emotions (Strick et al., 2009). In fact, although humor involves less engagement with the target, using humor is positively associated with relationship quality (Cann et al., 2009; Carstensen et al., 1995; Kurtz & Algoe, 2015). Although both direct and indirect support have been shown to positively relate to relationship satisfaction, direct action tends to be less effective than indirect action and may also increase negative affect (Girme et al., 2018).

Given the findings above, we hypothesize that humor, direct action, distraction, reappraisal, receptive listening, and valuing will relate to higher relationship satisfaction, whereas downward comparison, and expressive suppression will relate to lower satisfaction. Because the eight extrinsic regulation strategies are highly inter-correlated, we will examine relative weights analysis (Tonidandel et al., 2009) as well as multiple regression in evaluating the relative importance of each of the eight processes.

Method

Participants

Participants (N = 277, 55% female, mean age = 36.8 years, SD = 12.21 years) were recruited through Prolific in May 2020, as part of a larger project examining wellbeing during the coronavirus pandemic. Most participants (n = 267, 96%) were in a romantic relationship with an opposite-sex partner. An additional 57 participants completed the protocol but were excluded based on pre-registered exclusion criteria (i.e., taking less than a third of the median response time, failing a data check item, stopping halfway through, showing invariant responding across 2 or more screens, or answering that they spoke English “not well” or “not at all; see https://aspredicted.org/blind.php?x=HSL_CMW).

Materials

Regulation of others’ emotions scale1 (ROES; MacCann et al., 2019)

Partner frame-of-reference instructions were used, with reference to the coronavirus pandemic, which put stress on relationships (i.e., “Since the coronavirus outbreak, I do the following things to MAKE MY ROMANTIC PARTNER FEEL BETTER”). Eight subscales were assessed with four items each (expressive suppression, downward social comparison, distraction, humor, direct action, reappraisal, receptive listening, and valuing). Sample items include “I ask them to put a brave face on” (expressive suppression) or “I do what I can to find an answer for them” (direct action). Participants rated each item on a 6-point scale, from 1 (Strongly Disagree) to 6 (Strongly Agree).

Relationship satisfaction (Hendrick, 1988)

Instructions requested participants rate each of the five items on a 7-point Likert scale, from 1 (Strongly Disagree) to 7 (Strongly Agree). Items included “How well does you partner meet your needs?” and “How often do you wish you hadn’t gotten into this relationship?” (reverse scored).

Procedure

Participants were recruited from Prolific by seeing a study ad and provided written consent after viewing a participant information statement. All participants completed demographic questions and then several rating scales including the ROES and the relationship satisfaction scale (see preregistration for full list of measures not included in the current study). This study was approved by the Human Ethics Committee at the first author’s institution.

Analysis

Three measures of the association of the eight regulation processes with relationship satisfaction were conducted: (1) Pearson’s correlations (r); (2) multiple regressions where the 8 processes predicted relationship satisfaction, and (3) relative weights analysis (RWA) to test the relative importance of each of the eight predictors. An RWA partitions the R2 into pseudo-orthogonal parts with each part representative of the relative contribution of each predictor variable (Tonidandel et al., 2009). While regression analyses can help identify the relationship between variables, relatively weights analysis provides a more detailed understanding of the relative importance of each variable in the model – particularly with multiple predictor variables, as it helps to identify which variables are most important in predicting the outcome. We interpret effect size of correlations and regression coefficients with respect to Cohen’s r, with.10, 0.30, and 0.50 considered as “small”, “medium” and “large” respectively (Cohen, 1988). Statistics were calculated using R 4.1.0 (R Core Team, 2021), effsize (v0.8.1; Torchiano, 2020), and RWA (v0.0.3; Chan, 2021). The full reproducible code is available in supplementary materials.

Results

Internal consistency and descriptive statistics

Table 2 presents the internal consistency indices, and descriptive statistics for the ROES subscales and relationship satisfaction. Mean scores were lowest for the disengagement-focused processes and highest for the relationship-focused processes. Internal consistency reliability for the ROES subscale scores were good. Confirmatory factor analyses were conducted to test model fit for the Regulation of Others’ Scale, and relationship satisfaction. There was good model fit for the eight-factor structure of the Regulation of Others’ Scale (χ2 = 714.50, df = 436, CFI = 0.994, SRMR = 0.060, RMSEA = 0.048, 90% CI = 0.042 − 0.054), and good fit for Relationship Satisfaction (χ2 = 27.08, df = 14, CFI = 0.999, SRMR = 0.03, RMSEA = 0.058, 90% CI = 0.23 − 0.91).

Table 2.

Descriptive statistics, inter-correlations of regulation processes, and prediction of relationship satisfaction (correlations, multiple regression, and relative weights analysis)

Descriptive
Statistics		 Inter-Correlations of
Extrinsic Regulation Processes		 Prediction of
Relationship Satisfaction
M SD α 1 2 3 4 5 6 7 8 r β RW %R2
1. Expressive Suppression 2.21 0.92 0.80 − 0.05 − 0.09 0.01 2.23
2. Downward Comparison 3.39 1.31 0.91 .61*** .06 0.03 0.00 0.81
3. Humor 4.83 0.88 0.89 .02 .15* .33*** 0.18** 0.05* 21.20
4. Distraction 4.45 0.86 0.83 .27*** .37*** .57*** .23*** − 0.05 0.01 5.56
5. Direct Action 4.11 0.94 0.77 .33*** .35*** .30*** .39*** .22*** 0.10 0.02 8.76
6. Reappraisal 4.31 0.85 0.86 .32*** .52*** .28*** 0.51*** .56*** .18** 0.03 0.01 3.19
7. Receptive Listening 5.07 0.77 0.83 − .18** .06 .37*** .40*** .23*** .43*** .27*** − 0.10 0.02* 9.73
8. Valuing 5.03 0.81 0.89 − .09 .07 .44*** .44*** .27*** .29*** .67*** .43*** 0.40*** 0.11* 48.50
9. Relationship Satisfaction 3.54 0.38 0.92 − .05 .06 .33*** .23*** .22*** .18** .27*** .43***
Open in a new tab

*p < .05, **p < .01, ***p < .001

Correlations

Relationship satisfaction was not significantly correlated with the two disengagement-focused strategies but showed significant positive correlations for the other six regulation strategies. The effect size was moderate-to-large for valuing, moderate for receptive listening and humor, and small-to-moderate for the remaining processes (distraction, direct action and reappraisal).

Hypothesis testing

Regression coefficients were significant for valuing and humor only, with a moderate-to-large effect for valuing and a small-to-moderate effect for humor. The regression explained 23% of the variance in relationship satisfaction. Relative weights analysis (RWA) was used to test hypotheses. Relative weights were significant for valuing (which explained 48.5% of the R2), humor (21.2% of R2) and receptive listening (9.73% of R2), as hypothesized. However, the hypothesized relationships for downward comparison, expressive suppression, direct action, and reappraisal were not supported.

Discussion

Our results supported hypotheses based on extrinsic regulation research and theory (i.e., valuing, humor, and receptive listening significantly predicted greater relationship satisfaction) but not for the hypotheses based on prior research on intrinsic emotion regulation (i.e., downward comparison, expressive suppression, direct action, and reappraisal did not significantly predict relationship satisfaction). These results highlight the distinction between intrinsic and extrinsic emotion regulation - just because a process works for you does not mean it works for your partner.

Valuing

Consistent with prior research, valuing was the strongest predictor of greater regulator relationship satisfaction. Complimenting and valuing one’s partner benefits both the giver and receiver of the compliments (Doohan & Manusov, 2004). What is less clear from our results is the direction of causation. Relationship satisfaction may facilitate the act of valuing one’s partner (where those who are more satisfied are more likely to use valuing to regulate their partner’s emotions). Alternatively valuing one’s partner may create positive feelings about the partner and relationship thus strengthening relationship satisfaction (Murray & Homes, 2009; Murray et al., 2010).

Humor

Results for humor are consistent with prior meta-analytic findings where humor predicted greater relationship satisfaction (Hall, 2017). In fact, shared laughter within a relationship predicts not only relationship satisfaction, but also evaluations of closeness, relationship quality, and social support (Kurtz & Algoe, 2015). This is in line with research on humour and attraction which demonstrates that men are more likely to be attracted to women who value their wit, and in turn, women are attracted to someone who makes them laugh (Bressler et al., 2006; Hone et al., 2015).

Receptive listening

Consistent with prior research, our results indicate that receptive listening positively predicts relationship satisfaction (Pasupathi et al., 1999; Seehausen et al., 2012). Disclosing negative emotions to one’s romantic partner may indicate trust and a desire to connect with the listener (Graham et al., 2008). This may increase feelings of closeness and trust between the listener and their partner (Graham et al., 2008; Kashdan et al., 2007; Von Culin et al., 2018), which ultimately enhances the listener’s perception of their relationship satisfaction.

In contrast, expressive suppression, downward comparison, distraction, direct action, and reappraisal did not significantly predict relationship satisfaction. The null results for expressive suppression deviate from prior research where expressive suppression was associated with lower relationship satisfaction (English et al., 2012; Sasaki et al., 2021; Vater & Schröder-Abé, 2015). However, this past research has examined intrinsic regulation. Suppressing one’s own emotions is qualitatively different to the verbally-mediated act of telling someone else to change their expression of emotion. Similarly, the prior research showing that cognitive reappraisal processes related to greater relationship satisfaction focused on intrinsic regulation. These results may not generalize to extrinsic processes. In fact, Niven et al. (2015) suggest that extrinsic reappraisal may be viewed negatively by targets—as ‘splaining’ their own thoughts and feelings to them.

The motivation underlying the use of disengagement-focused processes, such as expressive suppression, may influence the extent to which they predict relationship satisfaction (Niven et al., 2019). That is, when the regulator’s prosocial underlying motivation is to positively influence their partner’s emotions, then the usually negative impact of using a less emotionally-engaging process may be diminished (Niven et al., 2019). Conversely, when the motivation of the regulator in using disengagement-focused processes is egoistic, we may see disengagement-focused processes leading to lower relationship satisfaction in both the target and regulator.

Limitations and future research

The results of this study may represent the perspective of partner-as-regulators who are already happy in their relationship. Because the regulators are satisfied with their relationship, they are willing to engage emotionally with their partner. On the other hand, the regulator’s belief in their ability to make their partner laugh, and/or value their partner, may increase the regulator’s confidence that they can regulate their partner’s emotions thus leading to greater feelings of relationship satisfaction (Kirby & Baucom, 2017). Similarly, concerning the use of disengagement-focused processes, the already strong relationship satisfaction of the partner-as-regulator may act as a buffer such that the use of disengagement-focused processes do not significantly relate to relationship satisfaction. As the results from this study are potentially bi-directional, it is not possible to derive causal explanations from this cross-sectional study. Future longitudinal research is needed to determine whether the use of emotionally engaging extrinsic regulation processes increase relationship satisfaction, whether existing relationship satisfaction encourages greater emotional engagement when regulating one’s romantic partner, or whether there is a feedback loop, consistent with Gross’ extended process model (Gross, 2015).

Additionally, future research may consider taking a dyadic approach to examine how much the discrete extrinsic emotion regulation processes used by the regulator predict relationship satisfaction of both regulator and target. Moreover, exploring the extent to which the regulator’s underlying motivation for regulation impacts not only the use of discrete extrinsic regulation processes, but also the extent to which the discrete processes and motivation interact to predict relationship satisfaction in both target and regulator is needed.

Conclusion

This research is among the first to evaluate the extent to which eight discrete emotion regulation processes relate to the relationship satisfaction of the regulator. The results of this study demonstrates that using receptive listening, humor and valuing to make one’s partner feel better is associated with the regulator feeling more satisfied in their relationship.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (125.3KB, csv)
Supplementary Material 2 (2.2KB, r)

Funding

Open Access funding enabled and organized by CAUL and its Member Institutions

Footnotes

1

While the preregistration specified 10 extrinsic regulation processes, the latest version of the ROES instrument includes only 8 processes. We therefore report these 8 processes (rather than the 10 that were pre-registered).

Author Note:This research was supported by Australian Research Council Discovery Grants to the last author (DP150101158 and DP210103484). Analysis and publication of these results are supported by a grant from the Margarete von Wrangell-Habilitationsprogramm für Frauen and ProTrainU from Ulm University awarded to the third author.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Antonucci TC, Lansford JE, Akiyama H. Impact of positive and negative aspects of marital relationships and friendship on well-being of older adults. Applied Developmental Science. 2001;5:68–75. doi: 10.1207/S1532480XADS0502_2. [DOI] [Google Scholar]
  2. Austin, E. J., Saklofske, D. H., & Smith, M. M. (2018). Development and validation of two short forms of the Managing the Emotions of Others (MEOS) Scale. Frontiers in Psychology, 9, 974. 10.3389/fpsyg.2018.00974 [DOI] [PMC free article] [PubMed]
  3. Austin, E. J., & Vahle, N. (2016). Associations of the Managing the Emotions of Others Scale (MEOS) with HEXACO personality and with trait emotional intelligence at the factor and facet level. Personality and Individual Differences, 94, 348–353. 10.1016/j.paid.2016.01.047
  4. Ben-Naim S, Hirschberger G, Ein-Dor T, Mikulincer M. An experimental study of emotion regulation during relationship conflict interactions: the moderating role of attachment orientations. Emotion. 2013;13(3):1–14. doi: 10.1037/a0031473. [DOI] [PubMed] [Google Scholar]
  5. Bravo V, Connolly J, McIsaac C. Why did it end? Breakup reasons of youth of different gender, dating stages, and ages. Emerging Adulthood. 2017;5(4):230–240. doi: 10.1177/2167696817700261. [DOI] [Google Scholar]
  6. Bressler ER, Martin RA, Balshine S. Production and appreciation of humor as sexually selected traits. Evolution and Human Behavior. 2006;27(2):121–130. doi: 10.1016/j.evolhumbehav.2005.09.001. [DOI] [Google Scholar]
  7. Cann A, Zapata CL, Davis HB. Positive and negative styles of humor in communication: evidence for the importance of considering both styles. Communication Quarterly. 2009;57:452–468. doi: 10.1080/01463370903313398. [DOI] [Google Scholar]
  8. Carstensen LL, Gottman JM, Levenson RW. Emotional behavior in long-term marriage. Psychology and Aging. 1995;10(1):140. doi: 10.1037/0882-7974.10.1.140. [DOI] [PubMed] [Google Scholar]
  9. Chan, M. (2021). Martinctc/rwa: Perform a Relative Weights Analysis. (URL: https://github.com/martinctc/rwa), R package version 0.0.3, https://cran.r-project.org/web/packages/rwa/readme/README.html
  10. Doohan EAM, Manusov V. The communication of compliments in romantic relationships: an investigation of relational satisfaction and sex differences and similarities in compliment behavior. Western Journal of Communication (includes Communication Reports) 2004;68(2):170–194. doi: 10.1080/10570310409374795. [DOI] [Google Scholar]
  11. English T, John OP, Srivastava S, Gross JJ. Emotion regulation and peer-rated social functioning: a 4-year longitudinal study. Journal of Research in Personality. 2012;46:780–784. doi: 10.1016/j.jrp.2012.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fan, J., & Wang, Y. (2022). English as a foreign language teachers’ professional success in the chinese context: the effects of well-being and emotion regulation. Frontiers in Psychology, 13, 10.3389/fpsyg.2022.952503 [DOI] [PMC free article] [PubMed]
  13. Fletcher GJ, Simpson JA, Campbell L, Overall NC. Pair-bonding, romantic love, and evolution the curious case of homo sapiens. Perspectives on Psychological Science. 2015;10:20–36. doi: 10.1177/1745691614561683. [DOI] [PubMed] [Google Scholar]
  14. Fredrickson BL, Levenson RW. Positive emotions speed recovery from the cardiovascular sequelae of negative emotions. Cognition & Emotion. 1998;12:191–220. doi: 10.1080/026999398379718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Girme YU, Maniaci MR, Reis HT, McNulty JK, Carmichael CL, Gable SL, Baker LR, Overall NC. Does support need to be seen? Daily invisible support promotes next day relationship well-being. Journal of Family Psychology. 2018;32(7):882–893. doi: 10.1037/fam0000453. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Graham SM, Huang JY, Clark MS, Helgeson VS. The positives of negative emotions: willingness to express negative emotions promotes relationships. Personality and Social Psychology Bulletin. 2008;34(3):394–406. doi: 10.1177/0146167207311281. [DOI] [PubMed] [Google Scholar]
  17. Greenier V, Derakhshan A, Fathi J. Emotion regulation and psychological well-being in teacher work engagement: a case of british and iranian english language teachers. System. 2021;97:102446. doi: 10.1016/j.system.2020.102446. [DOI] [Google Scholar]
  18. Gross JJ. The emerging field of emotion regulation: an integrative review. Review of General Psychology. 1998;2(3):271–299. doi: 10.1037/1089-2680.2.3.271. [DOI] [Google Scholar]
  19. Gross JJ. Emotion regulation: affective, cognitive, and social consequences. Psychophysiology. 2002;39(3):281–291. doi: 10.1017/S0048577201393198. [DOI] [PubMed] [Google Scholar]
  20. Gross JJ. The extended process model of emotion regulation: elaborations, applications, and future directions. Psychological Inquiry. 2015;26(1):130–137. doi: 10.1080/1047840X.2015.989751. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Gross JJ, John OP. Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. Journal of Personality and Social Psychology. 2003;85(2):348–362. doi: 10.1037/0022-3514.85.2.348. [DOI] [PubMed] [Google Scholar]
  22. Hall JA. Humor in romantic relationships: a meta-analysis. Personal Relationships. 2017;24(2):306–322. doi: 10.1111/pere.12183. [DOI] [Google Scholar]
  23. Hendrick, S. S. (1988). A generic measure of relationship satisfaction. Journal of Marriage and the Family, 93–98. 10.2307/352430
  24. Hendrick SS, Dicke A, Hendrick C. The relationship assessment scale. Journal of Social and Personal Relationships. 1998;15:137–142. doi: 10.1177/0265407598151009. [DOI] [Google Scholar]
  25. Hone LS, Hurwitz W, Lieberman D. Sex differences in preferences for humor: a replication, modification, and extension. Evolutionary Psychology. 2015;13(1):147470491501300110. doi: 10.1177/147470491501300110. [DOI] [PubMed] [Google Scholar]
  26. Impett, E. A., Kogan, A., English, T., John, O., Oveis, C., Gordon, A. M., & Keltner, D. (2012). Suppression sours sacrifice: Emotional and relational costs of suppressing emotions in romantic relationships. Personality and Social Psychology Bulletin, 38(6), 707–720. 10.1177/0146167212437249 [DOI] [PubMed]
  27. Kashdan TB, Volkmann JR, Breen WE, Han S. Social anxiety and romantic relationships: the costs and benefits of negative emotion expression are context-dependent. Journal of Anxiety Disorders. 2007;21(4):475–492. doi: 10.1016/j.janxdis.2006.08.007. [DOI] [PubMed] [Google Scholar]
  28. Keltner, D., & Haidt, J. (1999). Social functions of emotions at four levels of analysis. Cognition and Emotion, 13(5), 505–521.
  29. Keltner, D., & Haidt, J. (2001). Social functions of emotions. In T. J. Mayne & G. A. Bonanno (Eds.), Emotions: Currrent issues and future directions (pp. 192–213). Guilford Press.
  30. Keltner, D., & Kring, A. M. (1998). Emotion, social function, and psychopathology. Review of General Psychology, 2(3), 320–342. 10.1037/1089-2680.2.3.320
  31. Kinkead A, Sanduvete-Chaves S, Chacón-Moscoso S, Salas CE. Couples extrinsic emotion regulation questionnaire: psychometric validation in a chilean population. Plos One. 2021;16(6):e0252329. doi: 10.1371/journal.pone.0252329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kurtz, L. E., & Algoe, S. B. (2015). Putting laughter in context: Shared laughter as behavioral indicator of relationship well‐being. Personal Relationships, 22(4), 573–590. 10.1111/pere.12095 [DOI] [PMC free article] [PubMed]
  33. Lench, H. C., Tibbett, T. P., & Bench, S. W. (2016). Exploring the toolkit of emotion: What do sadness and anger do for us? Social and Personality Psychology Compass, 10(1), 11–25. 10.1111/spc3.12229
  34. MacCann, C., Olderback, S., Austin, E., Pinkus, R. T., Double, K. S., Walker, S. A., Kunst, H., & Niven, K. (2019). What do we do to help others feel better? Eight extrinsic emotion regulation processes linked to affective and interpersonal outcomes. [Conference session]. Australasian Congress for Personality & Individual Differences, Bond University, QLD, Australia.
  35. Mazzuca S, Kafetsios K, Livi S, Presaghi F. Emotion regulation and satisfaction in long-term marital relationships: the role of emotional contagion. Journal of Social and Personal Relationships. 2019;36(9):2880–2895. doi: 10.1177/0265407518804452. [DOI] [Google Scholar]
  36. McNulty, J. K., Meltzer, A. L., Neff, L. A., & Karney, B. R. (2021). How both partners’ individual differences, stress, and behavior predict change in relationship satisfaction: Extending the VSA model. Proceedings of the National Academy of Sciences, 118(27). 10.1073/pnas.2101402118 [DOI] [PMC free article] [PubMed]
  37. Murray SL, Holmes JG. The architecture of interdependent minds: a motivation-management theory of mutual responsiveness. Psychological Review. 2009;116(4):908. doi: 10.1037/0022-3514.88.2.327. [DOI] [PubMed] [Google Scholar]
  38. Murray SL, Holmes JG, Pinkus RT. A smart unconscious? Procedural origins of automatic partner attitudes in marriage. Journal of Experimental Social Psychology. 2010;46(4):650–656. doi: 10.1016/j.jesp.2010.03.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Nils F, Rimé B. Beyond the myth of venting: social sharing modes determine the benefits of emotional disclosure. European Journal of Social Psychology. 2012;42:672–681. doi: 10.1002/ejsp.1880. [DOI] [Google Scholar]
  40. Niven K, Garcia D, Löwe IVD, Holman D, Mansell W. Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks. Frontiers in Psychology. 2015;6:1452. doi: 10.3389/fpsyg.2015.01452. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Niven K, Macdonald I, Holman D. You spin me right round: cross-relationship variability in interpersonal emotion regulation. Frontiers in Psychology. 2012;3:394. doi: 10.3389/fpsyg.2012.00394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Niven K, Totterdell P, Holman D, Headley T. Does regulating others’ feelings influence people’s own affective well-being? The Journal of Social Psychology. 2012;152(2):246–260. doi: 10.1080/00224545.2011.599823. [DOI] [PubMed] [Google Scholar]
  43. Niven K, Totterdell P, Stride CB, Holman D. Emotion regulation of others and self (EROS): the development and validation of a new individual difference measure. Current Psychology. 2011;30(1):53–73. doi: 10.1007/s12144-011-9099-9. [DOI] [Google Scholar]
  44. Niven K, Troth AC, Holman D. Do the effects of interpersonal emotion regulation depend on people’s underlying motives? Journal of Occupational and Organizational Psychology. 2019;92(4):1020–1026. doi: 10.1111/joop.12257. [DOI] [Google Scholar]
  45. Nozaki Y, Mikolajczak M. Extrinsic emotion regulation. Emotion. 2020;20(1):10–15. doi: 10.1037/emo0000636. [DOI] [PubMed] [Google Scholar]
  46. Pateraki E, Roussi P. Marital quality and well-being: the role of gender, marital duration, social support and cultural context. A positive psychology perspective on quality of life. Social Indicators Research Series. 2013;51:125–145. doi: 10.1007/978-94-007-4963-4_8. [DOI] [Google Scholar]
  47. Pauw, L. S., Sauter, D. A., Van Kleef, G. A., & Fischer, A. H. (2018). Sense or sensibility? Social sharers’ evaluations of socio-affective vs. cognitive support in response to negative emotions. Cognition and Emotion, 32, 1247–1264. 10.1080/02699931.2017.1400949 [DOI] [PubMed]
  48. Pinkus RT, Lockwood P, Schimmack U, Fournier MA. For better and for worse: everyday social comparisons between romantic partners. Journal of Personality and Social Psychology. 2008;95(5):1180–1201. doi: 10.1037/0022-3514.95.5.1180. [DOI] [PubMed] [Google Scholar]
  49. Proulx, C. M., Helms, H. M., & Buehler, C. (2007). Marital quality and personal well-being: A meta‐analysis. Journal of Marriage and Family, 69(3), 576–593. 10.1111/j.1741-3737.2007.00393.x
  50. R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
  51. Ruso PP, Bodenmann G, Kayser K. Cognitive emotion regulation and positive dyadic outcomes in married couples. Journal of Social and Personal Relationships. 2019;36(1):359–376. doi: 10.1177/0265407517751664. [DOI] [Google Scholar]
  52. Sasaki E, Overall NC, Chang VT, Low RS. A dyadic perspective of expressive suppression: own or partner suppression weakens relationships. Emotion. 2021 doi: 10.1037/emo0000978. [DOI] [PubMed] [Google Scholar]
  53. Seehausen M, Kazzer P, Bajbouj M, Prehn K. Effects of empathic paraphrasing–extrinsic emotion regulation in social conflict. Frontiers in Psychology. 2012;3:482. doi: 10.3389/fpsyg.2012.00482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Strick M, Holland RW, van Baaren RB, Van Knippenberg AD. Finding comfort in a joke: consolatory effects of humor through cognitive distraction. Emotion. 2009;9:574–578. doi: 10.1037/a0015951. [DOI] [PubMed] [Google Scholar]
  55. Tonidandel S, LeBreton JM, Johnson JW. Determining the statistical significance of relative weights. Psychological Methods. 2009;14(4):387. doi: 10.1037/a0017735. [DOI] [PubMed] [Google Scholar]
  56. Torchiano, M. (2020). _effsize: efficient effect size Computation_. R package version, 0, 10.5281/zenodo.1480624. https://CRAN.R-project.org/package=effsize> .8.1, <
  57. Vater A, Schröder-Abé M. Explaining the link between personality and relationship satisfaction: emotion regulation and interpersonal behaviour in conflict discussions. European Journal of Personality. 2015;29(2):201–215. doi: 10.1002/per.1993. [DOI] [Google Scholar]
  58. Von Culin KR, Hirsch JL, Clark MS. Willingness to express emotion depends upon perceiving partner care. Cognition and Emotion. 2018;32(3):641–650. doi: 10.1080/02699931.2017.1331906. [DOI] [PubMed] [Google Scholar]
  59. Voss K, Markiewicz D, Doyle AB. Friendship, marriage and self-esteem. Journal of Social and Personal Relationships. 1999;16(1):103–122. doi: 10.1177/0265407599161006. [DOI] [Google Scholar]
  60. Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: a meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138(4), 775–808. 10.1037/a0027600 [DOI] [PubMed]
  61. Whisman MA. Marital distress and DSM-IV psychiatric disorders in a population-based national survey. Journal of Abnormal Psychology. 2007;116(3):638. doi: 10.1037/0021-843X.116.3.638. [DOI] [PubMed] [Google Scholar]
  62. Williams, W. C., Morelli, S. A., Ong, D. C., & Zaki, J. (2018). Interpersonal emotion regulation: Implications for affiliation, perceived support, relationships, and well-being. Journal of Personality and Social Psychology, 115(2), 224. 10.1037/pspi0000132 [DOI] [PubMed]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (125.3KB, csv)
Supplementary Material 2 (2.2KB, r)

Articles from Current Psychology (New Brunswick, N.j.) are provided here courtesy of Nature Publishing Group

RESOURCES