The Roles of Communal Motivation in Daily Prosocial Behaviors: A Dyadic Experience-Sampling Study

Abstract

Close relationship partners are communally motivated to engage in prosocial behaviors that can promote each other’s well-being. It remains largely unexplored how both members’ communal motivations jointly shape the daily enactment of prosocial behaviors. This dyadic experience-sampling study aimed to partially fill this gap by studying whether both members’ communal motivations predict (a) the base rate of the actor’s prosocial behaviors, (b) the actor’s reciprocity to the partner’s earlier prosocial behaviors, and (c) the consistency of the actor’s enactment of prosocial behaviors, within a day. Actor–partner interdependence analyses showed that the base rate of prosocial behaviors was positively associated with both members’ communal motivations. Consistency was only associated with the actor’s communal motivation, while reciprocity was not related to either member’s communal motivation. We also explored participants’ rationale for the enacted behaviors. Implications regarding the roles of communal motivation in daily relational functions were discussed.

Keywords

communal motivation prosocial behaviors actor–partner interdependence model romantic relationships

Every day, romantic partners engage in prosocial behaviors, such as giving compliments and texting, to express their concerns for the other’s well-being. These acts are essential to the success of romantic relationships. However, questions remain largely unexplored regarding how the partner-oriented concerns—and specifically, the communal motivations—of both members may jointly influence the daily enactment of prosocial behaviors. We attempted to answer this question via a dyadic experience-sampling study.

Communal Motivation

Individuals are motivated to use communal norms to relate to their romantic partner and to promote their partner’s well-being (Clark & Mills, 2012; Fiske, 1992). When such communal motivation is strong, individuals respond to their partner’s needs in a noncontingent manner, such that they neither monitor the personal costs taken nor expect any immediate return (Clark & Mills, 1993; Clark, Mills, & Powell, 1986).

Communal motivation has been studied extensively in close relationships (for a thorough review, see Clark & Aragón, 2013; Le, Impett, Lemay, Muise, & Tskhay, 2018). Once activated, communal motivation orients people to attend to their partners’ emotional needs (Yoo, Clark, Lemay, Salovey, & Monin, 2011), to sacrifice for these partners (Mattingly, Oswald, & Clark, 2011), and to increase commitment to the relationships (Finkel, Campbell, Buffardi, Kumashiro, & Rusbult, 2009).

Despite the well-established association between communal motivation and prosocial behaviors, little has been known regarding how communal motivation influences the daily implementation of prosocial behaviors. Every day, individuals enact prosocial behaviors to reciprocate relationship partner’s earlier good deeds and to take consistent care for the partner’s well-being. These patterns of behaviors can be potentially strengthened by partner-oriented concerns. Therefore, we explored how communal motivation may influence the likelihood of the actor’s enactment of prosocial behaviors (i.e., base rate), as well as the degree to which the likelihood of actor’s enactment of prosocial behaviors is associated with the presence (or absence) of the partner’s and actor’s prosocial behaviors at an earlier moment (i.e., reciprocity and consistency), within a day. Furthermore, we explored how communal motivation is related to the rationale, perceived impact, and cost of the enacted prosocial behaviors.

Research has consistently shown that an actor’s prosocial behaviors can be influenced by his or her own communal motivation, such as via the route of positive emotional rewards (Kogan et al., 2010). It is also plausible that an actor’s prosocial behaviors can be boosted by the partner’s communal motivation, possibly out of the appreciation of the partner’s genuine responsiveness (Visserman, Righetti, Impett, Keltner, & VanLange, 2017). Since the partner’s communal motivation may add predictive power over the actor’s own (Le et al., 2018), we examined the effects of both members’ communal motivations together on the actor’s daily enactment of prosocial behaviors. The research questions are summarized in Figure 1.

Figure 1.

Summary of research questions: Base rate is captured by the likelihood of actor’s prosocial behaviors at signal T. Path R captures the reciprocity dynamic whereas Path C captures the consistency dynamic. Dashed arrows test the influences of the actor’s and partner’s communal motivations on the target effects.

Finally, prosocial behaviors in close relationships can also be inspired by relationship-oriented motivations as well (Visserman et al., 2017). For instance, relationship commitment reflects one’s intention to sustain the relationship in a long term (Rusbult & Buunk, 1993). It can boost prosocial behaviors via heightened concerns for the relationship’s well-being (Hui, Finkel, Fitzsimons, Kumashiro, & Hofmann, 2014). Since relationship commitment and communal motivation are closely associated (e.g., Finkel et al., 2009), we controlled for relationship commitment to disconfound our hypothesized effects of communal motivations.

Daily Prosocial Behaviors and the Base Rate

Relationship partners engage in prosocial behaviors to support each other’s needs and goals (e.g., Feeney & Collins, 2015; Reis & Gable, 2015), as well as to escalate mutual trust and interdependence (e.g., Hui et al., 2014; Murray & Holmes, 2009; Wieselquist, Rusbult, Foster, & Agnew, 1999). Nevertheless, individuals need to maintain a healthy balance between their relational and personal concerns given the natural constraints by situations and competing goals (Kumashiro, Rusbult, & Finkel, 2008; Slotter, Duffy, & Gardner, 2014). Hence, we expected that the daily enactment (i.e., base rate) of actor’s prosocial behaviors might not be very frequent.

However, we predicted that the base rate of daily prosocial behaviors would be positively related to both members’ communal motivations (i.e., Path m_Ba and m_Bp in Figure 1). Actors high in communal motivation would be more likely to engage in daily prosocial behaviors because they are more responsive to their partner’s needs. Also, actors would be more likely to engage in daily prosocial behaviors toward partners high in communal motivation because they are more grateful to these partners’ benevolent intentions (Visserman et al., 2017).

Reciprocity of Daily Prosocial Behaviors

Past research has shown that actors are more likely to enact prosocial behaviors when they receive benefits from another person’s prosocial behaviors (e.g., Kurzban, Burton-Chellew, & West, 2015). In close relationships, individuals also reciprocate their partner’s good deeds to sustain the relationship that is instrumental to their future interests (Fitzsimons, Finkel, & VanDellen, 2015). Such reciprocation could be driven by gratitude (Algoe, 2012) and concerns for equity (Gleason, Iida, Bolger, & Shrout, 2003). Therefore, we hypothesized that an actor’s likelihood of enacting prosocial behaviors would be positively related to the partner’s prosocial behaviors (i.e., reciprocity; Path R in Figure 1) at an earlier moment within a day.

We predicted that the actor’s and partner’s communal motivations might not affect the degree of an actor’s reciprocity of prosocial behaviors within a day (i.e., Path m_Ra and m_Rp in Figure 1). Timely reciprocation of prosocial behaviors can be motivated by the intention to express one’s appreciation of the good deeds received or simply to be fair rather than elevated communal responsiveness to the partner’s specific needs. In such case, neither the actor’s nor the partner’s communal motivation should affect the degree of reciprocity.

Consistency of Daily Prosocial Behaviors

We hypothesized that an actor’s likelihood of engaging in prosocial behaviors can be related to his or her own prosocial behaviors at an earlier moment as well. The correlation might be positive, to the extent that the actor is committed to dedicating time and resources to responding to the partner’s needs (i.e., consistency; Path C in Figure 1). Alternatively, such a correlation might be negative, to the extent that an actor merely wants to make up some progress for the goal to support the partner shortly before attending to other priorities (i.e., balancing; Fishbach, Koo, & Finkelstein, 2014; Mullen & Monin, 2016). We believe that, when individuals attend to their partner’s needs at one moment, they are more likely to realize partner’s additional needs. As a result, they may engage in prosocial behaviors consistently across time, until they have to work on other goals. Hence, we expected a dynamic of consistency rather than balancing.

Additionally, we predicted that the degree of an actor’s consistency of daily prosocial behaviors can be reinforced by the actor’s own communal motivation (i.e., Path m_Ca in Figure 1). Actors high in communal motivation tend to experience stronger positive emotions from their own prosocial behaviors (Kogan et al., 2010). Such emotional benefits can motivate them to work more for this active caring goal, leading to the consistency of daily prosocial behaviors within a short time frame. It was less clear whether an actor’s consistency of prosocial behaviors would be related to the partner’s communal motivation. We also explored this connection (i.e., Path m_Cp in Figure 1).

The Rationale, Perceived Impact, and Cost of Daily Prosocial Behaviors

As prosocial behaviors can involve considerations of the partner’s well-being, the welfare of the relationship, and even self-interests (Le et al., 2018; Maner & Gailliot, 2007; Visserman et al., 2017), we explored the extent to which both members’ communal motivations affect the rationale (i.e., how important the interests were to the partner, relationship, and self in motivating prosocial behaviors) and the perceived impact (i.e., how beneficial individuals perceived their prosocial behaviors were to those three targets) of the enacted prosocial behaviors. Additionally, we explored how communal motivations are associated with the cost of daily prosocial behaviors (i.e., Path m_a and m_p in Figure 1).

Communally motivated individuals are willing to sacrifice self-interests for the partner’s well-being (Mattingly et al., 2011). However, their self-interests may not be compromised by their prosocial behaviors, to the extent that they can experience hedonic benefits from these behaviors (Kogan et al., 2010), or identify prosocial behaviors that meet both members’ needs (e.g., studying together with the partner who needs help).

The Present Study

We conducted a dyadic experience-sampling study with heterosexual dating couples to study the effects of the actor’s and partner’s communal motivations on their daily prosocial behaviors. In a period of 7 days, participants received six signals each day, separated by random intervals of 60–120 min. Upon receipt of each signal, they would report whether they had enacted any prosocial behaviors toward their partner in the past time window. If yes, they were given additional questions regarding these behaviors.

Our primary goals were to examine how both members’ communal motivations are related to how likely an actor engages in prosocial behaviors and how an actor’s prosocial behavior is related to the presence (or absence) of the partner’s and the actor’s prosocial behaviors at an earlier moment, within a day. We also explored how communal motivations affect the rationale, perceived impact, and cost of daily prosocial behaviors.

Method

Participants

A power analysis was conducted via Optimal Design 3.01 (Spybrook et al., 2011), to determine the minimum number of couples required for two-level cross-classified logistic regressions (persons crossed with signals and nested within couples). We assumed that (a) the effect sizes of the hypothesized main effects regarding communal motivations were small (d = .20) and (b) both members provided (at least) five usable responses. Based on these assumptions, to detect the target effects with an α level of .05, a minimum of 58 couples was required to achieve a power of .80. As attrition rate is typically around 20%, we planned to recruit a minimum of 73 couples.

In total, we were able to recruit 98 heterosexual dating couples (M_age = 20.75, SD_age = 1.92) from a college population in Hong Kong via e-mails and flyers. On average, participants had been dating for 2.02 years (SD = 1.80). Each participant received HK$300 (or US$38.5) for completing all parts of the study.

Procedure

In the intake phase, participants came to the lab and completed a battery of questionnaires in individual cubicles. They also received instructions about the experience-sampling phase.

The experience-sampling phase began about 2 weeks later, in which participants received six signals per day for 7 consecutive days. Signals arrived at a random time every 2 hr between 10:00 and 22:00, with the time gap between two adjacent signals controlled to be at least 60 min. Signals were yoked so that both members of the same couple received every signal simultaneously. Participants were instructed to complete the surveys without discussion with their partner. Participants were also instructed to begin within 60 min after the signal arrived (M_delay = 18.07 min) and to finish within 30 min once they started. Upon arrival of each signal, participants reported whether they had enacted any prosocial behavior since the previous signal. If the answer was positive, they were asked to provide more information about the behavior(s). Participants also completed other measures about their relationship experiences, which were not related to this investigation.

The final phase took place approximately 1 month later, where participants responded to additional surveys and were then debriefed and paid.

Relationship-Specific Measures in the Intake

In the intake phase, participants completed a 10-item measure of communal strength (Mills et al., 2004; 0 = not at all to 10 = extremely; e.g., “How high a priority for you is meeting the needs of your partner?”) and a 12-item scale of relationship commitment (Arriaga & Agnew, 2001; 0 = do not agree at all to 8 = agree completely; e.g., “I intend to stay in this relationship”).

Experience-Sampling Records

In the experience-sampling phase, participants first indicated whether their romantic partner was physically present (effect coding: −1 = absence, 1 = presence). Then, they would report whether they had enacted any prosocial behavior (dummy coding: 0 = no, 1 = yes) within that time interval. If participants reported “no,” they were sent directly to the end of the survey. If they reported “yes,” they were asked to describe the behavior(s) briefly.

Participants then indicated the rationale (via three questions: “How important were the interests for your partner/your relationship/yourself when you decided to enact the behavior(s)?”; 1 = of little importance to 6 = of great importance), the perceived impact (via three questions: “How beneficial were your behavior(s) for your partner/your relationship/yourself?”; 1 = very harmful to 7 = very beneficial), and the cost (“How much did the behavior(s) cost you in terms of resources (e.g., time, money, or effort)?”; 1 = nothing at all to 6 = a lot) of the reported prosocial behavior(s).

Data Screening for Analyses

We retained responses from 89 couples (i.e., 178 participants) because (a) four couples were not romantically involved as reported in the final phase, (b) three couples admitted that their records were not particularly accurate, and (c) two couples did not complete the measure of either communal strength or relationship commitment.

Results

All data and syntax are available at Open Science Framework page osf.io/8u9xj/. Descriptive statistics are presented in Table 1. Descriptive statistics and correlations among the measures of the rationale, perceived impact, and cost of the enacted prosocial behaviors are summarized in Supplementary Table 1.

Table 1.

Summary of Descriptive Statistics, Gender Differences, and Within-Couple Correlations.

Variables	α	Male	Female	t	r
Variables	α	M (SD)	M (SD)	t	r
Communal motivation	.83	8.60 (1.16)	8.56 (1.09)	.27	.08
Relationship commitment	.85	4.37 (0.48)	4.41 (0.48)	−.57	.36***

Note. n = 178.

***p < .001.

Table 2 summarizes the categories of the reported prosocial behaviors. To explore whether communal motivations may promote a particular category of behaviors, we calculated, for each actor, the proportion of his or her enacted prosocial behaviors for each category and then correlated the proportion indices with both members’ communal motivations. Actor’s communal motivation was associated with higher proportions of accompanying, physical contact, and goal support. Partner’s communal motivation was not related to the proportions (ps > .189).

Table 2.

Categories of Enacted Prosocial Behaviors and Correlations between the Proportion Indices for Each Category and Actor’s Communal Motivation.

Category	Count	Percentage	Example	r ^a
Texting	566	45.32	“Texted him morning, and he was energized!:)”	.03
Accompanying	140	11.21	“Accompanied her to class”	.20**
Calling	99	7.93	“Chatted with him on phone”	−.02
Initiating a conversation	70	5.60	“Shared funny stories today”	−.11
Compliment	55	4.40	“Told her that she is cute”	−.02
Expressing care	52	4.16	“Told her to take some good rest”	.04
Physical contact	51	4.08	“Wake-up kiss,” “hug”	.15*
General support	49	3.92	“Verbal support”	−.06
Engagement in joint activities/entertainments	39	3.12	“Swam together with him”	.03
Goal support	34	2.72	“Helped him on review”	.18*
Encouragement	33	2.64	“Cheered her up for exam”	−.01
Interaction via social platform	25	2.00	“Tagged him on FB so he can see funny pictures”	.07
Sending gifts or lending money	22	1.76	“Purchased a toy for him”	.14
Other	14	1.12	“Forgiveness,” “said thx”	−.09
(Sum)	(1,249)

Note. n = 178.

^aThe correlations between actor’s proportions of his or her enacted prosocial behaviors in each category and his or her own communal motivation.

*p < .05. **p < .01.

In this study, persons were crossed with signals and nested within couples. We used cross-classified logistic regressions to account for such statistical dependence (Bolger & Laurenceau, 2013; Kenny, Kashy, & Cook, 2006) and adopted the actor–partner interdependence model to test actor and partner effects simultaneously. The intraclass correlation of the random-intercept model equals .41 (Aly, Zhao, Li, & Jiang, 2014), indicating the nonindependence between relationship partners’ enactments of prosocial behaviors.

Preliminary analyses found that gender did not moderate any of the effects of communal motivations (ps > .099). Hence, dyads were treated as indistinguishable for simplicity.

How Does Communal Motivation Influence the Base Rate, Reciprocity, and Consistency of Daily Prosocial Behaviors?

All multilevel logistic regressions, with random intercepts allowed, were performed on the actor’s prosocial behaviors at signal T (0 = no, 1 = yes) with the glmer function in R package lme4 (Bates, Mächler, Bolker, & Walker, 2015). We included three control variables, namely actor’s gender (effect coding: −1 = female, 1 = male), partner’s presence (effect coding: −1 = absence, 1 = presence), and day (centered at Day 4). It was expected that prosocial behaviors were more frequently enacted by females, when the partner was around, and in the earlier versus later days of the experience-sampling phase (as such behavior might be boosted initially by the reminders of this study).

In the tests of base rate, we included responses of those participants who had responded to at least five signals in the experience-sampling phase; and in the tests of reciprocity and consistency, we only included responses of those participants who had at least five responses that could be paired with their partner’s and their own responses at the previous signal within the day; responses not included were treated as missing values. The numbers of participants and responses included in these analyses therefore differed and are reported accordingly in Table 3.

Table 3.

Fixed Effects Estimates for the Predictors of the Likelihood of Actor’s Prosocial Behaviors at Signal T.

Variables	Model for Base Rate		Model 1 for Reciprocity and Consistency		Model 2 for Reciprocity and Consistency
Variables	B (SE)	95% CI	B (SE)	95% CI	B (SE)	95% CI
Block 1
(Intercept)	−1.37 (.10)***	[−1.56, −1.18]	−2.19 (.19)***	[−2.56, −1.81]	−2.19 (.18)***	[−2.55, −1.83]
Day^a	−0.33 (.03)***	[−0.39, −0.26]	−0.10 (.04)*	[−0.19, −0.02]	−0.15 (.04)***	[−0.23, −0.07]
Partner’s presence^b	1.12 (.14)***	[0.84, 1.39]	0.60 (.19)**	[0.22, 0.97]	0.74 (.16)***	[0.58, 1.29]
Actor’s gender^c	−0.44 (.09)***	[−0.61, −0.26]	−0.69 (.14)***	[−0.97, −0.41]	−0.62 (.14)***	[−0.89, −0.35]
Partner’s PB at signal T-1^d	—		0.97 (.17)***	[0.63, 1.31]	0.87 (.17)***	[0.54, 1.19]
Actor’s PB at signal T-1^e	—		2.43 (.22)***	[2.00, 2.87]	0.80 (.16)***	[0.48, 1.11]
Block 2
(Intercept)	−1.39 (.10)***	[−1.59, −1.20]	−2.23 (.20)***	[−2.63, −1.83]	−2.23 (.19)***	[−2.60, −1.85]
Day	−0.33 (.03)***	[−0.39, −0.27]	−0.11 (.04)**	[−0.20, −0.03]	−0.18 (.04)***	[−0.24, −0.08]
Partner’s presence	1.06 (.14)***	[0.79, 1.33]	0.53 (.20)**	[0.15, 0.92]	0.90 (.19)***	[0.54, 1.27]
Actor’s gender	−0.43 (.09)***	[−0.61, −0.25]	−0.65 (.15)***	[−0.94, −0.37]	−0.62 (.14)***	[−0.90, −0.34]
Partner’s PB at signal T-1	—		0.99 (.18)***	[0.63, 1.35]	0.90 (.18)***	[0.56, 1.25]
Actor’s PB at signal T-1	—		2.32 (.22)***	[1.88, 2.76]	0.72 (.17)***	[0.38, 1.05]
Actor’s communal motivation^f	0.17 (.05)**	[0.07, 0.28]	−0.03 (.11)	[−0.25, 0.18]	−0.02 (.11)	[−0.23, 0.19]
Partner’s communal motivation^g	0.30 (.05)***	[0.19, 0.40]	0.22 (.11) *	[0.01, 0.43]	0.22 (.11)*	[0.01, 0.43]
Partner’s PB at Signal T-1 × Actor’s Communal Motivation	—		−0.06 (.18)	[−0.42, 0.30]	−0.13 (.18)	[−0.48, 0.22]
Partner’s PB at Signal T-1 × Partner’s Communal Motivation	—		−0.10 (.18)	[−0.46, 0.25]	−0.13 (.18)	[−0.47, 0.21]
Actor’s PB at Signal T-1 × Actor’s Communal Motivation	—		0.40 (.18)*	[0.04, 0.75]	0.45 (.18)*	[0.10, 0.81]
Actor’s PB at Signal T-1 × Partner’s Communal Motivation	—		0.18 (.18)	[−0.18, 0.53]	−0.14 (.18)	[−0.49, 0.21]
n_individual (n_response)	150 (4,105)		109 (1,889)		109 (1,889)

Note. Comparing to Model 1, the dependent variable in Model 2 was recoded such that “0” (i.e., no) was assigned to (a) the absence of prosocial behaviors at signal T and (b) the presence of prosocial behaviors at signal T that was identical to the one engaged at signal T-1, while “1” (i.e., yes) was assigned to the presence of prosocial behaviors at signal T that (a) followed the absence of prosocial behaviors at signal T-1 or (b) differed from the behaviors engaged at signal T-1, to exclude the alternative explanation that the consistency dynamic found in Model 1 might reflect engaging in the same behavior across two consecutive signals. PB = prosocial behavior. CI = confidence interval.

^aCentered at Day 4 (i.e., the middle day of the experience-sampling phase). ^b−1 = absence, 1 = presence. ^c−1 = female, 1 = male. ^d0 = no, 1 = yes. ^e0 = no, 1 = yes. ^fStandardized score. ^gStandardized score.

*p < .05. **p < .01. ***p < .001.

Base rate

In the logistic regression, we entered the three aforementioned control variables in the first block and additionally both members’ communal motivations (standardized) in the second block. Results are summarized in the left column of Table 3. In the first block, the negative intercept suggested that participants engaged in prosocial behaviors at fewer than 50% of the signals that they responded. It was also found that more prosocial behaviors were performed by female actors, when the partner was physically present, and in the earlier versus later days. Critically, the second block showed that the actor’s likelihood of enacting prosocial behaviors was positively associated with both members’ communal motivations.

Reciprocity and consistency

We tested reciprocity and consistency simultaneously to control for the effects of each other.¹ In the logistic regression, we entered the control variables, and the partner’s and actor’s prosocial behaviors at signal T-1 (0 = no, 1 = yes) in the first block, and additionally both members’ communal motivations and their interactions with the partner’s and actor’s prosocial behaviors at signal T-1 in the second block.

The analyses are summarized in the middle column of Table 3. In the first block, both reciprocity and consistency were evident as the partner’s and actor’s prosocial behaviors at signal T-1 were both positively associated with the actor’s likelihood of enacting prosocial behaviors at signal T. In the second block, neither the actor’s nor the partner’s communal motivation moderated the effect of the partner’s prosocial behaviors at signal T-1, suggesting that the reciprocity of the actor’s daily prosocial behaviors does not depend on either member’s communal motivation. However, the actor’s communal motivation moderated the effect of the actor’s prosocial behaviors at signal T-1. Simple-slope analysis (see Figure 2; Bauer, 2005) indicated that the consistency of the actor’s daily prosocial behaviors was greater if the actor’s communal motivation was high (i.e., +1SD; B_high = 2.70, SE = .29, t = 9.44, p < .001, 95% confidence interval [CI] = [2.14, 3.26]) versus low (i.e., −1SD, B_low = 1.95, SE = .28, t = 6.96, p < .001, 95% CI [1.40, 2.50]).²

Figure 2.

Likelihood of the actor’s prosocial behaviors at signal T (in log odds) as a multiplicative function of the actor’s prosocial behaviors at signal T-1 and the actor’s communal motivation. Error bars represent standard errors. When an actor did not enact any prosocial behaviors at signal T-1, the likelihood of enacting a prosocial behavior at signal T was not associated with the actor’s communal motivation (B = −0.03, SE = .11, t = −0.27, p = .787, 95% CI [−0.24, 0.18]); however, when an actor enacted some prosocial behaviors at signal T-1, such likelihood was positively associated with the actor’s communal motivation (B = 0.35, SE = .16, t = 2.13, p = .033, 95% CI [0.03, 0.67]).

One might argue that the consistency effect may simply reflect engaging in the same behavior across two consecutive signals. Indeed, this could be a concern. Among the subset of prosocial behaviors preceded by the presence of own prosocial behaviors at the previous signal, 31.69% were identical to the preceding behaviors. Among these repeated behaviors, 84.48% belonged to the category of “Texting.” To exclude this alternative explanation, the dependent variable, the actor’s prosocial behaviors at signal T, was recoded such that “0” (i.e., no) was assigned to (a) the absence of prosocial behaviors at signal T and (b) the presence of prosocial behaviors at signal T that was identical to the one engaged at signal T-1, while “1” (i.e., yes) was assigned to the presence of prosocial behaviors at signal T that (a) followed the absence of prosocial behaviors at signal T-1 or (b) differed from the behaviors engaged at signal T-1. The additional analyses yielded similar conclusions (see the right column of Table 3).

How Does Communal Motivation Influence the Rationale, Perceived Impact, and Cost of Daily Prosocial Behaviors?

Finally, using SPSS MIXED macro, two-level cross-classified regressions with random intercepts were applied to test the effects of the actor’s and partner’s communal motivations (standardized) on the rationale, perceived impact, and cost, controlling for the actor’s gender (effect coding: −1 = female, 1 = male). As shown in Table 4, males reported more rationales regarding the partner’s and relationship’s interests, and less cost in enacting prosocial behaviors, than females.

Table 4.

Fixed Effects Estimates for the Predictors of the Rationale, Perceived Impact, and Cost of the Daily Prosocial Behaviors.

Dependent Variables	Actor’s Gender^a		Actor’s Communal Motivation^b		Partner’s Communal Motivation^c
Dependent Variables	B (SE)	95% CI	B (SE)	95% CI	B (SE)	95% CI
Rationale
Partner	.23 (.05)***	[0.13, 0.33]	.28 (.04)***	[0.20, 0.36]	.11 (.04)**	[0.03, 0.29]
Relationship	.24 (.05)***	[0.14, 0.34]	.19 (.04)***	[0.10, 0.28]	.10 (.04)**	[0.02, 0.19]
Self	.10 (.07)	[−0.04, 0.24]	.14 (.06)*	[0.02, 0.26]	.15 (.06)*	[0.03, 0.26]
Perceived impact
Partner	.03 (.05)	[−0.12, 0.07]	.24 (.05)***	[0.15, 0.33]	.10 (.05)*	[0.01, 0.19]
Relationship	.06 (.05)	[−0.03, 0.16]	.19 (.04)***	[0.11, 0.27]	.07 (.04)	[−0.01, 0.16]
Self	.07 (.05)	[−0.04, 0.18]	.21 (.05)***	[0.10, 0.31]	.08 (.05)	[−0.02, 0.18]
Cost	−.38 (.07)***	[−0.53, −0.24]	.08 (.08)	[−0.08, 0.23]	.08 (.08)	[−0.07, 0.23]

Note. n_individual = 148, n_response = 1,249. CI = confidence interval.

^a−1 = female, 1 = male. ^bStandardized score. ^cStandardized score.

*p < .05. **p < .01. ***p < .001.

Critically, actors with high versus low communal motivation reported more rationales regarding the partner’s and relationship’s interests and perceived the enacted behaviors as more beneficial to the partner and the relationship. Actors with high communal motivation also reported more rationale regarding own interests and perceived more benefits on the self.

Actors whose partner had high versus low communal motivation also reported more rationales regarding the partner’s, relationship’s, and own interests and perceived the enacted behaviors as more beneficial to the partner. Neither the actor’s nor the partner’s communal motivation was associated with the cost.

Ancillary Analyses: The Roles of Relationship Commitments

Because communal motivation and relationship commitment were highly correlated, for female, r(87) = .52, p < .001; for male, r(87) = .74, p < .001, we further conducted ancillary analyses to examine whether the effects of communal motivations hold after controlling for relationship commitments.

First, we ran the above logistic regressions replacing communal motivations with relationship commitments and found that neither member’s relationship commitment affected the base rate, reciprocity, or consistency of daily prosocial behaviors. We also tested the effects of relationship commitments and communal motivations simultaneously. Results showed that the effects of communal motivations remained the same after controlling for relationship commitments. However, the actor’s (B = −0.22, SE = .07, t = −3.13, p = .002, 95% CI [−0.36, −0.08]) and partner’s (B = −0.28, SE = .07, t = −4.05, p < .001, 95% CI [−0.41, −0.14]) relationship commitments were both negatively associated with the base rate of actor’s prosocial behaviors. Since these effects of relationship commitments were not hypothesized, caution is needed for interpretation. The results are summarized in Supplementary Table 3.

Second, we reran the analyses of the rationale, perceived impact, and cost of the enacted prosocial behaviors using relationship commitments as predictors (see Supplementary Table 4). Results showed that the actor’s relationship commitment was associated with more rationales regarding the partner’s and relationship’s interests, and more perceived impacts on the partner, the relationship, and the self; while the partner’s relationship commitment was associated with more rationales regarding the relationship’s and own interests. We then tested the effects of communal motivations and relationship commitments together. Results showed that the effects of actor's communal motivation remained unchanged while the effects of relationship commitments were mostly nonsignificant. To conclude, the effects of communal motivations on daily prosocial behaviors cannot be explained by relationship commitments.

Discussion

Communal motivation contributes to relationship well-being (Le et al., 2018). Nevertheless, how both members’ communal motivations contribute to daily enactments of prosocial behaviors remains largely unexplored. This dyadic experience-sampling study examined the joint influences of both members’ communal motivations on the enactment of daily prosocial behaviors as well as on the rationale, perceived impact, and cost in the enactment.

Prosocial Behaviors: Base Rate, Reciprocity, and Consistency

Our analyses showed that participants enacted prosocial behaviors toward their partner at fewer than 50% of the signals that they responded. Aligned with previous studies (Murray & Holmes, 2009; Wieselquist et al., 1999), a dynamic of reciprocity was found such that participants were more likely to engage in prosocial behaviors if their partner had engaged in some at an earlier moment.

Additionally, we observed a behavioral consistency such that participants were more likely to engage in prosocial behaviors after they had enacted some earlier in the day; and, it was independent of reciprocity. Individuals may be more likely to discover their partner’s additional needs while responding to the partner’s current needs. Subsequently, they are more likely to keep engaging in prosocial behaviors to address these needs across time. Previous research has suggested that individuals desire to have a healthy balance between their personal and relational concerns (Kumashiro et al., 2008). Consistently taking care of the partner’s needs may not necessarily be incompatible to this desire, as caregivers may not always need to sacrifice their self-interests for the partner’s interests. Rather, they can engage in prosocial behaviors that can address both parties’ needs. This still requires empirical testing.

The Roles of Communal Motivations in Daily Prosocial Behaviors

Our analyses explored how both members’ communal motivations may jointly influence the base rate, reciprocity, and consistency of daily prosocial behaviors. First, the base rate of prosocial behaviors was positively associated with both members’ communal motivations. The positive effect of the actor’s communal motivation is not surprising, given that actors high in communal motivation are generally more responsive to the partner’s needs (Clark & Mills, 2012). The partner’s communal motivation can also increase the actor’s base rate of prosocial behaviors, possibly because his or her benevolent intentions can elicit more appreciation from the actor (Visserman et al., 2017).

We also found that the likelihood of reciprocating the partner’s earlier prosocial attempts did not depend on either member’s communal motivation. One reason is that such reciprocity may be driven by the motivation to even out rather than the partner’s current needs. Communal motivation, in its essence, promotes mutual responsiveness that is not characterized by the immediate return of benefit. Instead, communally motivated individuals are more responsive whenever the partner needs support from them.

Finally, we found that individuals were more likely to engage in prosocial behaviors consistently across time if their own communal motivation was strong. Actors high in communal motivation feel more responsible for supporting their partner’s needs (Clark, Fitness, & Brissette, 2001), as the engagement in prosocial behaviors can provide opportunities to discover the partner’s other untended needs, they may continue to offer assistance to their partner.

Inasmuch as individuals high in communal motivation tend to support the romantic partner consistently within a given day, would they inevitably compromise their own pursuits? Although this still awaits empirical testing, we believe it may not be the case. Our base rate analyses suggested that communally motivated individuals engage in prosocial behaviors more frequently; however, they may still manage to pursue their personal goals efficiently as these pursuits can benefit from the increased partner support and relationship satisfaction (Hofmann, Finkel, & Fitzsimons, 2015).

It is noteworthy that the abovementioned effects of communal motivations held after controlling for relationship commitments. This suggests that although communally motivated individuals are typically highly committed, their daily enactment of prosocial behaviors may not be solely motivated by their strong intention to maintain the relationship. Such findings further highlight the importance of differentiating partner- and relationship-oriented motivations in close relationships research (Hui et al., 2014; Visserman et al., 2017).

How Does Communal Motivation Influence the Rationale, Perceived Impact, and Cost of Daily Prosocial Behaviors?

Our exploratory analyses suggested that, consistent with the literature (e.g., Mills & Clark, 2001), actors high in communal motivation reported more rationales regarding the partner’s and relationship’s interests and perceived more positive impacts on the partner and the relationship. Additionally, we found that actors high in communal motivation reported more rationale regarding self-interests and perceived more positive impact on the self. One potential reason is that actors high in communal motivation are able to mentally transform their partner’s gains as their own (Agnew, VanLange, Rusbult, & Langston, 1998) and thus enjoy more emotional benefits from the prosocial behaviors toward their partner (Kogan et al., 2010; Le, Impett, Kogan, Webster, & Cheng, 2012). Another possibility is that communally oriented individuals are motivated and able to identify behavioral options that can maximize both members’ interests.

Interestingly, it appears that an actor’s behavioral rationales can also be inspired by the partner’s communal motivation. We observed that, if the romantic partner had high communal motivation, the actor tended to report more rationales regarding the partner’s, relationship’s, and own interests and perceived more positive impact on the partner. Future studies may explore the related mechanism(s).

Finally, we observed that neither the actor’s nor the partner’s communal motivation predicted the cost involved. One reason may be that the daily prosocial behaviors reported were relatively low in cost (see Supplementary Table 1). These results, again, held after controlling for relationship commitments, which highlights that communal motivations not only affect the enactment of prosocial behaviors but also relate to the perception of those enacted behaviors.

Limitations and Future Directions

This study has several limitations. Methodologically, despite efforts to reduce attrition, the response rate of those participants retained (M_{response rate} = 65.12%) was somewhat lower than expected. Also, our study only relied on self-reports of prosocial behaviors, which could be subject to self-serving biases. Future investigators may consider adopting partner’s reports to test whether those effects still hold. Another limitation is that we did not examine participants’ rationale when they chose not to engage in prosocial behaviors, which precluded us from exploring situations where communal motivation does not promote prosocial behaviors (Hui et al., 2014).

Finally, since our study only recruited dating couples from a college sample, we are not certain if the effects are generalizable to married couples, who are supposedly more communally oriented yet face more relational demands and goal conflicts stemming from escalating interdependence (Finkel, Hui, Carswell, & Larson, 2014). Remaining consistently responsive to a partner on a daily basis, in spite of high level of communal motivation, can be challenging.

Conclusion

Our investigation deepened the understanding of the roles of both members’ communal motivations in the daily enactment of prosocial behaviors, distinguished how communal motivations guide different rationales, and perceived impacts to the partner, the relationship, and the self.

Supplemental Material

SPPS829058_suppl_mat - The Roles of Communal Motivation in Daily Prosocial Behaviors: A Dyadic Experience-Sampling Study

SPPS829058_suppl_mat for The Roles of Communal Motivation in Daily Prosocial Behaviors: A Dyadic Experience-Sampling Study by Sisi Li and Chin-Ming Hui in Social Psychological and Personality Science

Footnotes

Acknowledgments

The authors are grateful to Harry Reis and John Martino for their insightful comments on earlier versions of this article, and David A. Kenny and Randi Garcia for their valuable suggestions on the analytical strategies.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Direct Grant of The Chinese University of Hong Kong and Hong Kong Research Grants Council’s Early Career Scheme (ECS: CUHK24600415) to Chin-Ming Hui.

ORCID iD

Sisi Li

Supplemental Material

Supplemental material for this article is available online.

Notes

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