Are we happier with others? An investigation of the links between spending time with others and subjective well-being

Abstract

Previous research suggests that having close relationships is a fundamental human need that, when fulfilled, is positively associated with subjective well-being. Recently, however, scholars have argued that actually interacting with one’s closest partners may be psychologically taxing (e.g., due to pressures to provide support, care, and empathy). In the present research, we tested [a] how experiential affect varied as a function of which persons were currently present (e.g., romantic partners, friends, colleagues), as well as [b] how global well-being varied as a function of total daily time invested in these individuals. Replicating previous research, participants reported the highest levels of experiential well-being in the company of their friends, followed by their romantic partners, and then children. Statistically controlling for the activities performed with others, however, suggested that individuals did not necessarily prefer the mere company of their friends per se: people reported similar levels of well-being while in the presence of friends, partners, and children when adjusting estimates for activities. In contrast to the experiential findings, global well-being varied only as a function of total time spent with one’s romantic partner. Our findings further support the claim that experiential and global well-being are often separable constructs that may and show different patterns of association with relationship experiences (e.g., well-being may operate differently on within- versus between-persons levels).

Positive social relationships have been described as a fundamental human need (e.g., Baumeister & Leary, 1995; Bowlby, 1969; Deci & Ryan, 2000; Myers, 2000; Prager & Buhrmester, 1998). To that end, a large body of research suggests that life satisfaction and global feelings of meaning are enhanced by having a stable romantic partnership (e.g., Argyle, 2001; Dolan, Peasgood, & White, 2008; Myers, 2000), by frequent supportive contact with friends and acquaintances (e.g., Okun, Stock, Haring, & Witter, 1984; Pinquart & Sorensen, 2000; Sandstrom & Dunn, 2014), and—perhaps more controversially—by having and spending time with one’s children (e.g., Nelson, Kushlev, English, Dunn, & Lyubomirsky, 2013; but see Bhargava, Kassam, & Loewenstein, 2014). In fact, positive relationships are even associated with greater mental and physical health outcomes—including decreased mortality (e.g., Holt-Lunstad & Smith, 2012; Murberg, 2004; Weihs, Enright, & Simmens, 2008).

Recently, however, psychologists have emphasized that global well-being (e.g., life satisfaction) is distinct from experiential well-being (e.g., the actual moods and emotions that people experience; Kim-Prieto, Diener, Tamir, Scollon, & Diener, 2005). For example, it is possible for an individual to report high life satisfaction despite experiencing moderate to high negative affect throughout his/her days (or vice versa). This raises the possibility—that despite the fact that relationships are associated with greater global well-being—actually interacting with one’s closest associates may not necessarily produce momentary positive emotions (e.g., Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004). Indeed, debates exist regarding the association between interacting with specific loved ones (such as one’s children) and experiential well-being (e.g., Kahneman et al., 2004; Nelson et al., 2013). The purpose of the present study was to help clarify these debates by evaluating the extent to which time spent interacting with various classes of associates (e.g., romantic partner, children, friends, coworkers) predicts both experiential and global well-being.

Specifically, we collected logs of individuals’ daily time use and examined whether people reported different levels of experiential well-being while currently interacting with various relationship partners (e.g., friends, romantic partners, children). We then tested whether this within-person variation in experiential well-being could be explained by the activities people tend to perform in different relationships (e.g., do people prefer the company of their friends per se, or are people happier while with their friends because they also report engaging in more enjoyable activities while with friends than while with family?). Additionally, we examined whether total time invested in different relationships predicted between-persons variation in global well-being (e.g., do people who spend greater amounts of time with their partners report greater global well-being than people who spend less time with their partners?). Finally, we tested whether demographic factors moderated these findings.

Global versus Experiential Well-Being

Subjective well-being is a broad, multifaceted construct that captures people’s global evaluations of the overall positivity of their lives, as well as the balance of their affective states (Diener, 1984). Well-being includes at least two separate components: global (sometimes called “evaluative”) well-being and experiential well-being. Global well-being refers to people’s overall appraisals of how well their lives are going (e.g., life satisfaction), as well as their beliefs and expectations regarding how frequently they generally experience positive and negative affect (e.g., self-reported trait affect). In contrast, experiential well-being refers to people’s actual, in vivo affective states.

Importantly, global and experiential well-being only partially overlap (e.g., Kim-Prieto et al., 2005; Lucas, Diener, & Suh, 1996; Robinson & Clore, 2002b). For example, people’s global reports of how frequently they experience positive and negative emotions correlate only moderately with more objective assessments of their actual, experienced affect (Hudson, Anusic, Lucas, & Donnellan, 2019; Robinson & Clore, 2002a, 2002b). Researchers are divided regarding whether this discrepancy indicates that global reports are less valid than experiential measures (i.e., people are unable to accurately aggregate across their experiences and report their overall patterns of affect; e.g., Robinson & Clore, 2002b)—or whether global and experiential well-being are both valid indicators of different aspects of well-being (Kim-Prieto et al., 2005).

Irrespective of the debate about measurement approaches, the fact that global and experiential measures of well-being are partially distinct raises the possibility that they may have different predictors and correlates (Kim-Prieto et al., 2005). For example, individuals with higher income tend to report somewhat greater life satisfaction than do their less-wealthy peers; yet income is less strongly related—if at all—to experiencing greater positive emotions in the moment (e.g., Hudson, Lucas, Donnellan, & Kushlev, 2016; Kahneman & Deaton, 2010). Thus, fully understanding well-being requires studying each of its subcomponents separately (Kim-Prieto et al., 2005; Tay, Chan, & Diener, 2014).

Well-Being and Social Relationships

Research suggests that having high-quality social relationships is an important correlate of global well-being (e.g., Dolan et al., 2008; Myers, 2000; Reis, Sheldon, Gable, Roscoe, & Ryan, 2000; Russell, Bergeman, & Scott, 2012; though for a critical perspective see Lucas & Dyrenforth, 2006). For example, individuals in stable romantic partnerships tend to experience higher levels of well-being than do their single peers. Similarly, parents report greater positive affect and life satisfaction than do nonparents (Aassve, Goisis, & Sironi, 2012; Angeles, 2010; Luhmann, Hofmann, Eid, & Lucas, 2012; Nelson et al., 2013)—although there is debate regarding whether this association is spurious (e.g., due to the fact that parents are more likely to be older or married than are nonparents; Bhargava et al., 2014; Nelson, Kushlev, Dunn, & Lyubomirsky, 2014; Rothrauff & Cooney, 2008). Finally, having high-quality friendships as well as many acquaintances has been linked to enhanced well-being (e.g., Pinquart & Sorensen, 2000; Reis et al., 2000; Russell et al., 2012; Sandstrom & Dunn, 2014).

Recently, psychologists have argued that—despite the fact that having high-quality relationships enhances global well-being—actually interacting with one’s closest associates may not necessarily spur momentary experiential well-being (Kahneman et al., 2004). Romantic relationships can be a source of intimacy, compassion, support, and affection (e.g., Debrot, Schoebi, Perrez, & Horn, 2013; Reis, Maniaci, & Rogge, 2014); but the experience of conflict and providing support can drain well-being (e.g., Cichy, Stawski, & Almeida, 2014; Mackinnon et al., 2012). Similarly, although many parents report that having children is the single most positive event in their lives (Berntsen, Rubin, & Siegler, 2011), the demands of parenting can be psychologically taxing (e.g., Dolan et al., 2008; Kahneman et al., 2004). Thus, although having a romantic partner and children can enhance the global sense that one’s life is progressing well (e.g., Argyle, 2001; Dolan et al., 2008; Myers, 2000), the experiences associated with these relationships may not necessarily enhance experiential well-being (e.g., Kahneman et al., 2004).

The empirical evidence for the effects of interacting with various kinds of relationship partners (e.g., romantic partners, children, friends, colleagues) on experiential well-being is mixed and somewhat inconclusive. Studies generally tend to agree that people report greater experiential well-being while with their friends and family, as opposed to when they are alone or with colleagues (Helliwell & Wang, 2014, 2015; Kahneman et al., 2004; Lucas, Le, & Dyrenforth, 2008; Srivastava, Angelo, & Vallereux, 2008). However, whether well-being is highest while with friends or family is unclear. For example, one study found that people were happier while interacting with friends than with their romantic partners or children (Kahneman et al., 2004). Moreover, in that same study, caring for one’s children emerged as one of the least enjoyable activities—with only working, performing housework, and commuting being rated as less enjoyable. In contrast, other studies have found that individuals report greater experiential well-being while interacting with their romantic partners and/or children, as opposed to while apart from them (e.g., Flood & Genadek, 2016; Nelson et al., 2013).

Thus, although existing studies seem to converge on the idea that people experience greater experiential well-being when with family and friends than when alone or with colleagues, it remains unclear whether people are happier when interacting with their immediate families (i.e., romantic partners, children) than when interacting with their friends, roommates, or extended families. Therefore, a primary goal of the present study was to clarify the associations between interacting with various other persons (e.g., partners, friends, children) and experiential well-being. For example, we examined whether people report greater positive affect when currently interacting with their romantic partners, as opposed to when separated from them. Our analyses therefore provide additional data as to whether people are happier while interacting with their friends than romantic partners or vice versa (Kahneman et al., 2004; Nelson et al., 2013).

Importantly, there are several reasons why people might experience varying experiential well-being while with friends versus family. For one, people may simply prefer their friends’ company in and of itself to that of their family. For instance, friendships may entail fewer expectations and conflicts than romantic relationships. Alternatively, it is possible that any observed differences in experiential well-being while interacting with immediate family members versus friends are attributable to the different activities that people perform around different relationship partners. For example, individuals may perform greater numbers of potentially draining activities—such as providing care or performing household chores—while with family members. Similarly, people may engage in greater numbers of enjoyable leisure activities while with friends.

Thus, one innovation of the present study is that we statistically controlled for activities that people performed while with their families and friends to examine whether people reported differential affect due to merely being with friends versus family (e.g., do people report more positive emotions while with friends than with family, holding constant activities being performed?)—or whether any affective differences were attributable to different activities performed with various relationship partners (e.g., do people report similar affective experiences while with family versus friends once the effects of activities are controlled?). Addressing this issue might help to clarify why different relationship partners appear to be associated with different emotional states

Total Time with Others and Global Well-Being

A second goal of the present research was to examine the associations between total daily time spent interacting with various other persons (e.g., partners, friends, colleagues) and global well-being. For example, we tested whether people who spend greater amounts of total daily time with their romantic partners report greater global well-being, as compared with their peers who spend less time with their romantic partners. It may be the case that spending greater amounts of time with one’s romantic partner (or other people, such as friends) builds intimacy and commitment, and fosters the sense that one’s relationships are functioning well—potentially with downstream consequences for well-being. Similarly, spending time with one’s family and friends may nurture valued identities (e.g., as a “family man” or “family woman”) and promote the general sense that one’s life is meaningful and/or progressing well.

The alternative is that—despite the fact that merely having a romantic partner, for example, might be associated well-being (e.g., Dolan et al., 2008)—spending greater amounts of time with one’s romantic partner may not correlate with well-being (e.g., Lucas & Dyrenforth, 2006). Indeed, a similar phenomenon has been described with respect to volunteer work: The mere act of volunteering is associated with greater well-being, but the number of hours contributed appears to be inconsequential (e.g., Son & Wilson, 2012). This type of phenomenon may occur because merely possessing a valued social role leads people to construe their lives more favorably (e.g., “I have attained a valued goal of becoming married”)—and greater investment in that social role may not further affect how they construe the quality of their lives.

In contrast to research on how experiential well-being varies as a function of others’ presence, fewer studies have explicitly investigated the extent to which total daily time with others predicts global well-being. Several reviews and meta-analyses suggest that an amalgam of people’s self-reports of their number of friends and frequency of contact has small associations with well-being (Lucas & Dyrenforth, 2006; Okun et al., 1984; Pinquart & Sorensen, 2000). Indeed, Lucas and Dyrenforth (2006) concluded that spending time with others may be less consequential for well-being than earning greater income (and income has only modest associations with well-being; e.g., Lucas & Diener, 2008). Other studies have found larger associations between global well-being and greater numbers of contacts with friends and acquaintances (Lucas et al., 2008; Russell et al., 2012; Sandstrom & Dunn, 2014; Srivastava et al., 2008), meaningful conversations (Reis et al., 2000), and perceived support from family and friends (Montpetit, Nelson, & Tiberio, 2016). Thus, to the extent that interactions with friends and family generate positivity, intimacy, and supportiveness, spending greater amounts of time around these individuals may predict greater global well-being.

Previous studies have largely focused on individuals’ self-reports of how many close associates they have and their frequency of contact with those people. Fewer studies have measured the amount of time people spend with their friends and families and then assessed its association with well-being. Two recent studies that have directly measured total time spent with others suggest that total time with friends and family (but perhaps not time with one’s romantic partner) may predict daily and global composites of positive affect (Lucas et al., 2008; Srivastava et al., 2008).Nevertheless, much more research is needed to understand the links between time spent with others and global well-being. Thus, one major goal of the present research was to measure total time participants spent with family, friends, and colleagues, and evaluate its associations with global well-being.

Individual Differences

It is important to note that there may be individual differences that moderate the associations between time spent with other persons and well-being. For example, studies suggest that gender, parent age, marital status, and income may predict the psychological consequences of interacting with children. Married, older, male, or lower-income parents may be more likely to enjoy their children’s presence, as compared with unmarried, younger, female, or higher-income parents (Campos et al., 2013; Dyrdal & Lucas, 2013; Kushlev, Dunn, & Ashton-James, 2012; Nelson, Kushlev, & Lyubomirsky, 2014; Nomaguchi & Milkie, 2003; Roeters & Gracia, 2016).

Thus, one final goal of our study was to examine the extent to which demographic characteristics moderate the links between spending time with other people and both global and experiential well-being. Although prior research has identified several potentially important moderators, (e.g., age, gender, and marital status may moderate the link between spending time with children and well-being), we tested the extent to which four demographic variables (age, gender, income, marital status) moderated all analyses in our study. Consequently, the majority of these moderation analyses were exploratory.

Overview of the Present Study

The present study addressed four issues. First, we examined the extent to which experiential well-being varies as a function of the presence of specific classes of other people (e.g., romantic partners, children, friends, roommates, colleagues). For example, we tested whether people are happier while currently in the company of their romantic partners, as opposed to when apart from them. Second, we examined the extent to which global well-being varied as a function of the total time individuals spent around specific classes of other people. For example, we tested whether people who spend greater amounts of time with their romantic partners each day report greater life satisfaction, as compared to their peers who spend less time with their romantic partners.

Third, it is possible that spending time with different people is associated with varying levels of well-being because people may tend to perform different activities around family, friends, and coworkers. For example, people may engage in greater amounts of leisure while with their friends and may perform more household chores and caretaking duties while in the company of their families. Thus, we also examined whether associations found between time with specific other people and well-being could be explained by the types of activities participants engaged in while with specific other people. Finally, we examined whether demographics moderated any of our findings.

To investigate these issues, we collected day reconstruction method (DRM; Kahneman et al., 2004) measures from a statewide sample of Michigan residents up to three times over the course of two months. DRM is an alternative to experience sampling methods (ESM; Shiffman, Stone, & Hufford, 2008), in which respondents categorize their prior day in terms of “episodes,” indicate with whom they interacted during each episode, and rate their affective experiences during the episodes. In contrast to ESM, which sometimes requires specialized devices and can be intrusive for participants in terms of repeatedly interrupting their daily schedules to complete surveys, DRM measures can be administered via standard survey format at a single point in time, and some versions can be completed in as few as 10–15 minutes (Anusic, Lucas, & Donnellan, 2017; Hudson, Anusic, et al., 2019). Preliminary evidence suggests DRM measures produce comparable results to ESM, at least for some types of analyses (Bylsma, Taylor-Clift, & Rottenberg, 2011; Kahneman et al., 2004; Lucas, Tweten, Anusic, & Donnellan, 2016).

In addition to completing DRM measures, participants provided self-report ratings of global life satisfaction and global affect. Collectively, these data allowed us to examine to extent to which: (1) experiential affect varied as a function of the specific persons present during the episode; (2) global well-being varied as a function of total time spent with specific persons; (3) whether these associations withstood controlling daily time use, and (4) whether demographics moderated any of these associations. Moreover, because our participants were sampled across the gamut of demographic diversity present in Michigan, our findings may be more generalizable across adult social relationships than those from studies that have exclusively examined college students’ relational experiences.¹

Method

Participants

This research was approved by the Michigan State University Institutional Review Board (“Comparing measures of experiential and evaluative well-being;” x11–703). Our sample was recruited from a list of Michigan residents who had previously participated in at least one wave of the Michigan State University State of the State Survey (SOSS; Michigan State University Institute for Public Policy and Social Research, 2015), and who had indicated that they would be interested in receiving invitations to participate in other studies. Specifically, the SOSS is a quarterly, statewide telephone survey of approximately 1,000 adult Michiganders per wave, recruited via stratified random sampling procedures (Pierce, 2016). SOSS participants can opt-in to receive invitations to participate in additional, external studies. The SOSS administration team sent participants who had expressed interest in participating in future research an email invitation to participate in our study, alongside a link to the study website. Participants were offered $20 USD per wave for completing up to three waves, plus a $15 USD bonus for completing all three waves (thus, maximum compensation for completing all waves was $75 USD); participants could opt to receive either Amazon.com credit or a check. Participants completed survey responses online.

A total of 410 participants responded to the email invitation and provided at least one wave of data (no participants were excluded for any reason). The final sample at Time 1 was 60% female, with ages ranging from 19 to 92 (M = 52.61, SD = 14.73). The racial composition of the sample was 86% White, 6% Black, 2% Asian, 2% Native American, and 2% Hispanic. Seventy-five percent of participants indicated they were currently involved in a romantic relationship, 82% had children, and 53% were employed.

At Time 1, participants provided their contact information and we later contacted them for Time 2 and Time 3 measures—collected an average of 17.60 (SD = 4.84) and 33.82 (SD = 6.51) days after Time 1, respectively. On average, participants provided 2.31 waves of data (SD = 0.91), with 326 participants (80%) completing at least two waves. Attrition analyses revealed that only extraversion was related to total waves of data provided (r = −.10, 95% CI [−.19, −.01]). No other study variables, as measured at Time 1, were significantly related to waves of data provided, all |r|s < .06.²

Measures

Well-being

Experiential well-being.

Participants’ experiential well-being was measured using a variant of the DRM (Kahneman et al., 2004). Participants first reconstructed their entire prior day in terms of “scenes” or “episodes” that had occurred. Specifically, participants read relatively open-ended instructions to divide their prior day’s morning, afternoon, and evening into episodes,³ to “name” each episode, and to record its start and end time. On average, participants defined 11.23 episodes per reconstructed day (SD = 4.96). After reconstructing their entire prior day, participants were presented with each episode they had defined, and were asked to (1) select all applicable activities that they had performed during the episode from a predetermined list [e.g., commuting, shopping, housework], (2) select all applicable individuals with whom they were interacting during the episode from a predetermined list [e.g., no one, romantic partner, friend, coworker], and (3) rate the extent to which they felt various emotions during the episode: happiness, satisfaction, anger, sadness, frustration, worry, and a sense of meaning. Importantly, when indicating who was present during the episode, participants were instructed to select all options that applied; thus, participants could indicate that multiple types of people (e.g., friends, partner) were present during a single episode. All emotions were rated on a scale from 0 (not at all) to 6 (very much). Because research indicates that positive and negative affect are separable (Watson, Clark, & Tellegen, 1988), we calculated composites for episodic positive affect (an average of episodic happiness and satisfaction; Time-1 α = .82) and episodic negative affect (an average of episodic anger, sadness, frustration, and worry; Time-1 α = .90). Notably, scholars have also argued that hedonic well-being (e.g., positive affect) may operate separately from eudemonic well-being (e.g., a sense of purpose and meaning in life). For example, volunteering may increase one’s sense of meaning, but not positive mood (Son & Wilson, 2012). Thus, we examined episodic meaning separately from episodic positive affect (e.g., to examine whether caretaking roles predict meaning, but not positive affect).

Global affect.

To measure global affective well-being, participants were asked to rate the extent to which they had generally felt various emotions over the past two weeks: happy, satisfied, angry, sad, frustrated, worried, and a sense of meaning. Each emotion was rated from 0 (almost never) to 6 (almost always). As with experiential well-being, we formed separate composites for global positive affect (an average of global happiness and satisfaction; Time-1 α = .84) and global negative affect (an average of global anger, sadness, frustration, and worry; Time-1 α = .79). We examined global meaning separately.

Life satisfaction.

Participants rated their life-satisfaction using the five-item satisfaction with life scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). Items (e.g., “I am satisfied with my life”) were rated on a scale from 1 (strongly disagree) to 7 (strongly agree) and averaged to form a composite (Time-1 α = .90).

Results

Table 1 contains the descriptive statistics for participants’ average values of all well-being across all waves. Aggregated episodic DRM affect correlated moderate-to-highly with aggregated global reports of affect (rs ranged from .61 [negative affect] to .69 [positive affect]), supporting the inference that global and experiential affect are related, albeit separable constructs (e.g., Hudson, Lucas, & Donnellan, 2017; Kim-Prieto et al., 2005; Lucas et al., 1996).

Table 1.

Descriptive statistics and correlations for well-being

				Correlations
Variable	M	SD	ICC	1	2	3	4	5	6	7
1. DRM Positive Affect	3.57	1.18	.47	-	.41	−.37	-	-	-	-
2. DRM Meaning	2.85	1.53	.55	.66	-	−.12	-	-	-	-
3. DRM Negative Affect	0.73	0.73	.46	−.39	−.16	-	-	-	-	-
4. Global Positive Affect	4.20	0.94	.78	.69	.45	−.51	-	-	-	-
5. Global Meaning	3.94	1.30	.76	.57	.62	−.29	.66	-	-	-
6. Global Negative Affect	2.42	0.96	.69	−.46	−.26	.61	−.63	−.39	-	-
7. Life Satisfaction	4.87	1.29	.84	.57	.38	−.48	.76	.59	−.58	-

Note: Averages were computed for each variable for each participant across all measurement occasions (i.e., up to 9 measurements for episodic well-being variable; up to 3 measurements for each other variable). This table contains the descriptive statistics and between-persons correlations among these cross-time average variables (in the lower matrix). The upper matrix of this table contains the within-persons correlations among the episodic variables in italic typeface.

ICC = intraclass correlation for persons across time.

Does Episodic Well-Being Vary as a Function of Others’ Presence?

We first tested whether episodic positive affect, meaning, and negative affect varied as a function of others’ presence. These analyses capture whether, for example, people experienced greater momentary/experiential positive affect during episodes in which their romantic partners were present, as opposed to being absent. We constructed separate multilevel models (MLMs) to test the association between well-being and the presence of each category of person (e.g., partner, children, friends). For example, the MLM predicting episodic positive affect in episode, e, at wave, w, for person, p, as a function of one or more friends being present was:⁴

$${\text{(Episodic}\text{Positive}\text{Affect)}}_{ewp}=b_{\text{0}}\text{+}{b}_{\text{1}}{\text{(Friend[s] Present)}}_{ewp}\text{+}{U}_{wp}\text{+}{U}_p\text{+}{\epsilon }_{ewp}$$

In all models, episodic affect was standardized across all observations (see Ackerman, Donnellan, & Kashy, 2011), and the presence of each individual type of other person was separately dummy coded (1 = present; 0 = absent). To be clear, we created separate variables for the presence of each type of person (thus, we created one variable for whether friends were present [friend_present = 1] or not [friend_present = 0], a separate variable for whether the partner was present [partner_present = 1] or not [partner_present = 0], and so on). Thus, the metric of the b₁ parameter estimates is similar to a Cohen’s d: the standardized difference in episodic affect when others (e.g., friend[s]) are present versus absent. To remind readers of this interpretational nuance, we use the notation b_d when reporting d-like parameter estimates. Finally, to model and control for within-person and within-wave dependencies in the data, random intercepts were included for waves nested within persons (U_wp) and persons (U_p).

Table 2 provides parameter estimates from these MLMs. We first tested a model that assessed the effects of being alone versus not being alone. While completing the DRM, participants were able to check a box to indicate that “no one” was present for an episode. The parameter estimates in the “no one” row of Table 2 capture how experiential affect varied as a function of participants indicating that “no one” was present during episodes. As compared to when any other type of persons were present, while no one else was present, people tended to experience dampened levels of all types of affect—positive (b_d = −0.16, 95% CI [−0.19, −0.13], meaning (b_d = −0.19, 95% CI [−0.22, −0.17]), and negative (b_d = −0.07, 95% CI [−0.10, −0.04]).⁵ In contrast, while in the company of their partners, friends, and children, people reported greater episodic positive affect (respective b_ds = 0.15, 0.27, 0.18; 95% CIs [0.12, 0.19], [0.22, 0.32], [0.14, 0.22]), and meaning (respective b_ds = 0.10, 0.21, 0.18; 95% CIs [0.07, 0.12], [0.16, 0.25], [0.15, 0.22]). People also reported reduced negative affect during episodes in which their partners and friends were present (respective b_ds = −0.07, −0.05; 95% CIs [−0.10, −0.04], [−0.10, −0.00]), but not during episodes in which their children were present (b_d = −0.01, 95% CI [−0.06, 0.03]). While spending time with extended family, individuals reported greater episodic meaning (b_d = 0.09, 95% CI [0.04, 0.14]) and negative affect (b_d = 0.14, 95% CI [0.08, 0.20]), but not positive affect (b_d = 0.04, 95% CI [−0.02, 0.10]). Finally, the presence of roommates was not significantly related to any type of affect (all |b_d|s < 0.03), whereas the presence of work-related others (e.g., clients, colleagues, supervisors) predicted less episodic positive affect (b_ds ranged from −0.14 to −0.09) and greater negative affect (b_ds ranged from 0.26 to 0.29)—albeit also a greater sense of meaning (b_ds ranged from 0.09 to 0.14).

Table 2.

Episodic affect as a function of others’ presence

			Outcome
			Episodic Positive Affect			Episodic Meaning			Episodic Negative Affect
Predictor				95% CI			95% CI			95% CI
Persons present	M	SD	bd	LB	UB	bd	LB	UB	bd	LB	UB
No one	0.37	0.35	−0.16	−0.19	−0.13	−0.19	−0.22	−0.17	−0.07	−0.10	−0.04
Partner*	0.30	0.32	0.15	0.12	0.19	0.10	0.07	0.12	−0.07	−0.10	−0.04
Child(ren)*	0.17	0.25	0.18	0.14	0.22	0.18	0.15	0.22	−0.01	−0.06	0.03
Extended family	0.06	0.15	0.04	−0.02	0.10	0.09	0.04	0.14	0.14	0.08	0.20
Friend(s)	0.09	0.18	0.27	0.22	0.32	0.21	0.16	0.25	−0.05	−0.10	−0.00
Roommate(s)	0.01	0.05	0.02	−0.15	0.19	0.03	−0.12	0.18	0.02	−0.15	0.20
Client(s)	0.05	0.14	−0.09	−0.15	−0.02	0.14	0.09	0.20	0.29	0.22	0.35
Coworker(s)	0.10	0.19	−0.12	−0.17	−0.08	0.10	0.06	0.14	0.26	0.21	0.30
Boss(es)	0.04	0.12	−0.14	−0.21	−0.07	0.09	0.02	0.15	0.27	0.20	0.34

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound.

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

Because of how the predictors were coded (1 = present; 0 = not) and the outcomes were standardized, the mean for each predictor represents the percent of episodes in which each person was present on average, and b_d represents the standardized difference in the outcome when the person was present vs. not.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slopes of partners (or children) being present for partnered individuals (or parents).

Importantly, due to the way our variables were coded, the primary analyses described above contrasted the presence of a type of person (e.g., friends) with their absence. However, when a certain class of person (e.g., friends) was absent, other types of people may have been present (e.g., family members). In other words, when friends were absent, for example, the participant may have been alone, or other types of people (family, coworkers) may have been present. Thus, the “friend(s)” parameters in Table 2 capture the extent to which people experience different affect while with their friends than while apart from them—collapsing across whether participants were alone or with other types of people (e.g., family or coworkers). Therefore, we also tested models in which separate variables for all types of persons were included simultaneously. This shifts the interpretation of the parameters to represent the unique effect of friends (for example) being present (i.e., it statistically holds the presence of all other persons constant). Table A1 in the Appendix contains the parameters from these models. Generally, the pattern of results was similar to our primary analyses—albeit the effect sizes were generally somewhat smaller. The major exception was that in these simultaneous models, clients were no longer associated with statistically significantly lower levels of episodic positive affect (b_d = −0.01, 95% CI [−0.07, 0.06]), and bosses and colleagues were no longer associated with statistically significantly higher levels of episodic meaning (b_ds < 0.04). These findings may indicate that people find interacting with clients (but not bosses or colleagues) meaningful—and thus the zero-order associations between bosses’ and colleagues’ presence and episodic meaning may be spurious due to being confounded with clients’ presence (alternatively, these findings may also indicate insufficient statistical power to detect effects amidst relatively high multiple collinearity).

Thus, to summarize, people generally reported greater positive affect and lesser negative affect while in the company of their immediate family (partners, children) and friends. Moreover, our analyses thus far align with previous research suggesting that positive affect appears to be maximized while with friends, rather than while with one’s immediate family (i.e., partner and children)(Kahneman et al., 2004). The presence of extended family (e.g., parents) was associated with a greater sense of meaning, but also more negative affect. The presence of others typically associated with work (e.g., colleagues) predicted less positive affect and greater negative affect, but also a greater sense of meaning. Finally, while alone, people generally experienced attenuated levels of all types of affect.

Does time use explain the link between others’ presence and affect?

One potential explanation for the association between others’ presence and episodic affect is that individuals may engage in different activities while with different types of other people. For example, people may be more likely to engage in enjoyable activities while with friends, or to perform housework and caretaking duties while with their families. Table 3 presents regressions of each episodic well-being variable onto separate dummy codes for all 21 activities simultaneously (e.g., exercising was coded into one variable [0 = not exercising; 1 = exercising], socializing was coded into a separate variable [0 = not socializing; 1 = socializing], and so on). The activities were not mutually exclusive; thus, participants could report participating in multiple activities during a single episode. The results of these regressions show that specific activities were, in fact, associated with different levels of episodic affect. For example, people tended to experience higher levels of positive affect while having sex (b_d = 0.54, 95% CI [0.41, 0.67]), exercising (b_d = 0.32, 95% CI [0.25, 0.39]), interfacing with religion (b_d = 0.30, 95% CI [0.23, 0.37]), or socializing (b_d = 0.23, 95% CI [0.20, 0.27]). In contrast, people tended to experience higher negative affect while studying (b_d = 0.20, 95% CI [0.08, 0.32]), conversing via phone (b_d = 0.17, 95% CI [0.12, 0.24]), or working (b_d = 0.14, 95% CI [0.10, 0.18]).

Table 3.

Episodic affect as a function of activity being performed

	Outcome
	Episodic Positive Affect			Episodic Meaning			Episodic Negative Affect
		95% CI			95% CI			95% CI
Predictor	bd	LB	UB	bd	LB	UB	bd	LB	UB
Sexual activity	0.54	0.41	0.67	0.44	0.32	0.56	−0.12	−0.26	0.01
Exercising	0.32	0.25	0.39	0.20	0.14	0.27	−0.16	−0.23	−0.09
Spiritual activities	0.30	0.23	0.37	0.42	0.36	0.48	−0.07	−0.14	0.00
Socializing	0.23	0.20	0.27	0.21	0.18	0.24	−0.04	−0.08	−0.01
Other entertainment	0.19	0.13	0.25	0.00	−0.06	0.05	−0.10	−0.16	−0.04
Childcare	0.12	0.06	0.17	0.21	0.16	0.26	0.08	0.02	0.13
Relaxing	0.11	0.08	0.15	0.04	0.01	0.07	−0.11	−0.15	−0.08
Eating	0.11	0.08	0.15	−0.01	−0.04	0.02	−0.11	−0.15	−0.08
Reading	0.08	0.03	0.14	0.04	−0.01	0.09	−0.08	−0.14	−0.02
Preparing food	0.01	−0.04	0.05	0.03	−0.01	0.07	−0.02	−0.07	0.03
Shopping	−0.02	−0.09	0.04	−0.10	−0.15	−0.04	−0.04	−0.11	0.03
Working	−0.05	−0.10	−0.01	0.11	0.07	0.14	0.14	0.10	0.18
Phone usage	−0.05	−0.11	0.00	0.03	−0.02	0.08	0.17	0.12	0.24
Personal care	−0.05	−0.09	−0.01	−0.10	−0.14	−0.07	−0.06	−0.11	−0.02
Viewing television	−0.06	−0.10	−0.02	−0.07	−0.10	−0.03	0.01	−0.03	0.05
Housework	−0.08	−0.12	−0.03	−0.02	−0.06	0.01	0.02	−0.02	0.07
Studying	−0.09	−0.20	0.03	0.16	0.06	0.26	0.20	0.08	0.32
Attending class	−0.10	−0.25	0.05	0.07	−0.06	0.21	0.07	−0.09	0.23
Commuting	−0.10	−0.14	−0.06	−0.05	−0.09	−0.02	0.06	0.02	0.10
Computer usage	−0.11	−0.15	−0.07	−0.05	−0.08	−0.01	0.07	0.02	0.11
Resting	−0.16	−0.22	−0.09	−0.25	−0.31	−0.19	0.00	−0.08	0.07

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound; 95% CIs for parameters in boldface do not contain zero. All predictors were tested simultaneously in a single model. Because of how the predictors were coded (1 = present; 0 = not) and the outcomes were standardized, b_d represents the standardized difference in the variable when the activity is being performed vs. not, holding all other activities constant.

Moreover, as can be seen in Tables 4a–4b, participants tended to perform different activities around different persons. The regression parameters in Table 4a capture the predicted absolute increase in probability of an activity occurring during an episode as a function of each person’s presence. For example, people were 6% more likely to exercise when friends were present versus absent (b_d = 0.06, 95% CI [0.06, 0.07]; i.e., the probability of exercising, expressed as a percentage, increased 6 points when friends were present). In contrast, Table 4b contains the observed percent of episodes with each person in which each activity occurred. For example, only considering episodes in which friends were present, 7.56% of these episodes involved exercise.

Table 4a.

Regression coefficients predicting activities as a function of persons present.

	Person Present:
Outcome	No one	Partner	Child	Extended Family	Friend	Roommate	Client	Coworker	Boss
Sexual activity	.00	.03	−.01	.00	.00	.00	.00	.00	.00
Exercising	.03	.02	.00	.01	.06	−.03	.02	−.01	−.01
Spiritual activities	.04	.03	.01	.02	.06	.06	.01	.00	.00
Socializing	−.02	.18	.12	.29	.53	.13	.06	.11	.01
Other entertainment	.04	.05	.02	.02	.10	.04	.00	−.01	.02
Childcare	.00	.00	.34	.00	.00	−.02	−.02	−.04	.12
Relaxing	.18	.24	.07	.06	.13	.14	−.01	−.01	.03
Eating	.11	.21	.13	.12	.15	.19	−.02	.10	−.04
Reading	.08	.05	.00	.01	.00	.00	.00	.01	.01
Preparing food	.06	.10	.11	.06	.00	.11	.00	.01	.01
Shopping	.01	.01	.03	.03	.03	.02	.01	.00	−.01
Working	.08	.01	.00	.02	.00	.04	.43	.59	.12
Phone usage	.01	.02	.04	.10	.05	.00	.19	.07	.10
Personal care	.16	.09	.04	.00	.01	.10	.00	−.01	.00
Viewing television	.11	.19	.07	.02	−.01	.08	.03	−.03	.03
Housework	.11	.08	.10	.03	.00	.07	.00	.00	.00
Studying	.01	.00	.01	.00	.01	.06	.01	.01	.00
Attending class	.00	.00	.00	.00	.02	−.01	.03	.02	.00
Commuting	.14	.05	.11	.09	.09	.04	.03	.01	−.02
Computer usage	.13	.08	.06	.07	.05	.09	.15	.16	.12
Resting	.06	.02	.00	.00	−.01	.06	.00	.00	.00

Note: 95% CIs for parameters in boldface do not contain zero. All predictors were tested simultaneously in a single model. Because of how the presence of other people was coded (1 = present, 0 = absent), the parameter estimates represent the increase in probability that an activity is being performed as a function of each type of person’s presence, holding all other types of people’s presence constant.

Table 4b.

Percent of episodes with person in which activities occur

	Person Present:
Episode involved:	No one	Partner	Child	Extended Family	Friend	Roommate	Client	Coworker	Boss
Sexual activity	0.05	2.89	0.56	0.78	0.57	0.00	0.16	0.17	0.21
Exercising	3.64	2.67	1.88	2.86	7.56	0.00	2.73	1.26	0.88
Spiritual activities	3.77	3.91	2.96	4.29	7.56	8.60	1.93	1.18	1.31
Socializing	0.66	28.81	26.78	44.73	65.31	35.48	21.09	22.23	20.56
Other entertainment	4.86	6.86	5.74	6.11	11.81	7.53	1.44	1.61	3.50
Childcare	0.38	10.34	36.28	11.96	4.73	1.08	0.64	0.59	12.04
Relaxing	19.46	28.16	20.42	18.59	22.40	22.58	5.15	3.89	7.88
Eating	12.63	27.92	25.69	26.00	26.75	29.03	7.40	12.60	8.53
Reading	7.91	5.80	3.15	2.99	1.80	1.08	0.64	1.27	1.97
Preparing food	7.25	14.09	16.66	13.26	5.67	13.98	1.93	2.62	3.72
Shopping	2.33	2.83	4.56	5.07	4.63	4.30	2.25	0.11	0.43
Working	9.80	4.72	3.10	5.08	11.90	5.38	84.06	77.51	69.15
Phone usage	1.72	4.91	6.68	11.96	9.26	2.15	27.21	17.24	23.41
Personal care	16.20	10.88	8.99	6.11	5.10	12.90	1.77	0.85	1.97
Viewing television	12.34	21.19	16.05	11.70	6.05	11.83	6.12	1.10	5.69
Housework	12.11	11.42	14.59	9.10	4.53	9.68	0.64	0.67	1.09
Studying	1.51	0.51	1.12	0.91	1.61	6.45	0.21	1.78	1.53
Attending class	0.04	0.13	0.14	0.13	2.27	0.00	4.51	3.21	2.40
Commuting	15.86	11.33	16.38	16.64	14.56	10.75	8.21	6.71	4.60
Computer usage	14.40	10.75	10.64	12.74	12.76	11.83	28.82	25.87	30.42
Resting	5.12	2.53	1.60	1.17	0.28	6.45	0.16	0.00	0.43

Note: These are the percent of episodes with a person present in which an activity occurs. In other words, these numbers capture the probability of performing a given activity, assuming a person is around. For example, only considering episodes in which participants’ partners were present, 2.67% of the episodes involved exercise and 3.91% involved spiritual activities.

These numbers were computed by dividing the number of episodes in which a person and activity co-occurred (e.g., partner was present and exercise occurred) by the total number of episodes in which the person was present (e.g., total number of episodes in which partners were present).

The activities people most frequently performed while around their romantic partners included socializing (28.81% of episodes in which partners were present), relaxing (28.16%), eating (27.92%), viewing television (21.19%), preparing food (14.09%), and performing housework (11.42%). Although people tended to engage in similar activities with their friends, a much larger portion of episodes with friends involved socializing (65.31%) and fewer episodes involved housework (4.53%). The most common activities with children involved childcare (36.28%), followed by socializing (26.78%), eating (25.69%), relaxing (20.42%), and preparing food (16.66%). Not surprisingly, the most common activities around work-related others (clients, colleagues, and bosses) were working (69.15–84.06%), computer usage (25.87–30.42%), phone usage (17.24–27.21%), and socializing (20.56–21.09%). Given these differences, it may be the case that the activities that individuals perform with specific types of other people (e.g., friends, colleagues) explain any links between others’ presence and episodic affect. For example, one’s partner being present per se may not boost episodic well-being—rather it may be the case that activities performed with one’s partner (e.g., sex, socializing, relaxing) drive any boosts in episodic well-being.

To evaluate this possibility, we examined the associations between others’ presence and episodic affect, controlling for all 21 activity variables. As can be seen in Table 5, the pattern of results was similar to the uncontrolled analyses. For example, although a portion of the zero-order association between partners’ and friends’ presence on positive affect was accounted for by the activities performed around those individuals (respective reduction in the associations when controlling activities: Δb = 0.09, 95% CI [0.06, 0.13]; Δb = 0.16, 95% CI [0.12, 0.20]), the presence of both partners and friends continued to directly predict heightened episodic positive affect (respective associations controlling activities: b_d = 0.06, 95% CI [0.03, 0.10]; b_d = 0.11, 95% CI [0.06, 0.16]).

Table 5.

Episodic affect as a function of others’ presence, controlling activity being performed

	Outcome
	Episodic Positive Affect				Episodic Meaning				Episodic Negative Affect
Predictor, persons present		95% CI				95% CI				95% CI
	bd	LB	UB	IE	bd	LB	UB	IE	bd	LB	UB	IE
No one	−0.08	−0.11	0.03	−0.08	−0.11	−0.14	−0.08	−0.08	−0.08	−0.11	−0.04	−0.01
Partner*	0.06	0.03	0.10	0.09	0.07	0.04	0.10	0.03	0.00	−0.03	0.04	−0.07
Child(ren)*	0.12	0.08	0.17	0.06	0.13	0.09	0.17	0.05	0.00	−0.05	0.05	−0.01
Extended family	−0.05	−0.11	0.01	0.09	0.01	−0.04	0.06	0.08	0.15	0.09	0.21	−0.01
Friend(s)	0.11	0.06	0.16	0.16	0.06	0.01	0.11	0.15	−0.02	−0.07	0.03	−0.03
Roommate(s)	0.00	−0.17	0.16	0.02	0.01	−0.13	0.16	0.02	0.03	−0.14	0.21	−0.01
Client(s)	0.02	−0.05	0.09	−0.11	0.08	0.01	0.14	0.07	0.12	0.05	0.20	0.17
Coworker(s)	−0.08	−0.14	−0.03	−0.04	0.02	−0.03	0.07	0.08	0.15	0.09	0.21	0.11
Boss(es)	−0.09	−0.16	−0.02	−0.05	0.00	−0.06	0.07	0.09	0.13	0.06	0.21	0.14

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound; IE = total indirect effect of persons on episodic affect via activities (i.e., the extent to which the association between a person’s presence and episodic affect was reduced by controlling all activities).

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

Italicized parameters dropped below the threshold for statistical significance with activity controlled (compare with Table 2); Because of how the predictors were coded (1 = present; 0 = not) and the outcomes were standardized, b_d represents the standardized difference in the variable when the person was present vs. not.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slopes of partners (or children) being present for partnered individuals (or parents).

There were three notable exceptions to this pattern. First, controlling activities, the presence of partners and friends no longer predicted decreased negative affect (controlled |b_d|s < 0.02). In other words, the zero-order associations between the presence of partners and friends on negative affect (see Table 2) were attenuated after considering the activities that tended to be performed around those persons (respective reductions in the associations for partners and friends when controlling activities: Δb = −0.07, 95% CI [−0.11, −0.03]; Δb = −0.03, 95% CI [−0.08, 0.01]). Second, when activities performed were controlled, participants experienced similar levels of positive affect while with their partners, children, and friends—suggesting that affective differences associated with spending time with friends over family (see Table 2 and Kahneman et al., 2004) are likely attributable to engaging in more enjoyable activities with friends than while with immediate family. Indeed, with all activities held constant and from a purely descriptive standpoint, people appeared to report the greatest positive affect and meaning while with their children (a finding that is consistent with Nelson et al., 2013). Finally, the presence of coworkers and bosses no longer predicted increased meaning when activities were controlled (controlled |b_d|s < 0.02; respective reduction in the associations when activities were controlled: Δb = 0.08, 95% CI [0.04, 0.13]; Δb = 0.09, 95% CI [0.04, 0.13]). Notably, however, the presence of clients continued to directly predict heightened episodic meaning (controlled b_d = 0.08, 95% CI [0.01, 0.14]), despite a reduction in the size of the effect when controlling for activities performed while with clients (Δb = 0.07, 95% CI [0.02, 0.12]).

Thus, our analyses suggest that merely being with one’s partner, friends, and especially children predicts greater episodic positive affect and meaning, even holding constant the activities that are associated with these individuals. In contrast, the reduction in negative affect that occurs when people are with their partners and friends might be due to the confounding effect of the activities that people tend to engage in with these individuals. Similarly, interacting with one’s coworkers and bosses is associated with lessened positive affect and heightened negative affect, even accounting for the fact that people primarily engage in less enjoyable activities around colleagues. However, people’s experience of heightened meaning while with their coworkers and bosses might be due to the confounding effect of work on experienced meaning. Stated differently, being around one’s coworkers and supervisors does not appear to be especially meaningful—rather it appears to be the activities that one performs around colleagues that are potentially viewed as meaningful.^6,7

That being said, it is important to note that our data are purely correlational. Thus, despite suggesting that activities can explain some of the associations between others’ presence and well-being, our data cannot comment on whether the presence of other people and/or activities performed cause variation in well-being (e.g., it may be the case that affect causes people to seek out certain activities or relationship partners).

Does Amount of Time Spent with Others Predict Global Well-Being?

For our next series of analyses, we examined whether the total amount of time that individuals spent around categories of other people predicted global well-being. For example, whereas our episodic analyses answered the question “Are people happier while with their partners?”, these global analyses addressed the question, “Are people who spend more time with their partners globally happier?”

For these analyses, we computed the average daily time each participant spent with each class of other person. For example, to obtain participants’ average daily time with their romantic partners, we summed the duration of all episodes across all waves in which participants indicated their romantic partners were present and divided by the number of waves provided. Thus, the final number represented the average amount of time each participant spent with his/her romantic partner each day, aggregated across all measurement occasions.⁸

Table 6 contains the zero-order standardized regression coefficients (i.e., correlations) predicting each global well-being variable from each “daily time with others” variable.⁹ Scatterplots of the correlations between total time spent with one’s partner and all global well-being variables are depicted in Figure 1. Table 7 contains the associations between daily time spent engaging in each of the 21 assessed activities and global well-being, and Table 8 contains the associations between daily time with others and global well-being, controlling for daily time allotted to each of the 21 activities. In contrast to the numerous episodic findings, global well-being primarily varied as a function of only total time spent with partners. Controlling daily time use, people who spent greater amounts of time with their romantic partners tended to report greater global positive affect (β = 0.21, 95% CI [0.09, 0.33]) and life satisfaction (β = 0.21, 95% CI [0.09, 0.33]), and less global negative affect (β = −0.19, 95% CI [−0.32, −0.07]). The only other statistically significant parameter estimate was that people who spent greater amounts of time alone reported lower life satisfaction (β = −0.11, 95% CI [−0.21, −0.01]).

Table 6.

Global affect as a function of daily time spent with others

			Outcome
			Global Positive Affect			Global Meaning			Global Negative Affect			Global Life Satisfaction
Predictor, hours with:				95% CI			95% CI			95% CI			95% CI
Person(s)	M	SD	β	LB	UB	β	LB	UB	β	LB	UB	β	LB	UB
No one	4.65	4.41	−0.09	−0.18	−0.00	−0.06	−0.15	0.03	−0.05	−0.15	0.04	−0.14	−0.23	−0.05
Partner*	4.13	4.29	0.18	0.07	0.29	0.11	0.01	0.23	−0.16	−0.27	−0.05	0.19	0.08	0.29
Child(ren)*	2.35	3.58	−0.02	−0.12	0.07	−0.01	−0.10	0.09	0.13	0.03	0.22	0.04	−0.06	0.13
Extended family	0.90	1.89	−0.01	−0.10	0.08	0.03	−0.06	0.12	0.05	−0.04	0.14	0.00	−0.09	0.09
Friend(s)	1.50	2.27	0.09	0.00	0.18	0.10	0.01	0.19	−0.04	−0.14	0.05	0.07	−0.02	0.17
Roommate(s)	0.11	0.76	0.03	−0.06	0.12	0.05	−0.04	0.14	−0.02	−0.11	0.07	0.05	−0.05	0.14
Client(s)	1.33	2.43	0.04	−0.06	0.13	0.15	0.06	0.24	0.05	−0.04	0.14	0.04	−0.05	0.13
Coworker(s)	2.44	3.32	0.04	−0.05	0.13	0.03	−0.06	0.12	0.00	−0.09	0.09	0.03	−0.06	0.12
Boss(es)	1.01	2.14	0.03	−0.06	0.12	0.01	−0.08	0.10	0.04	−0.05	0.13	0.02	−0.07	0.11

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slopes of partners (or children) being present for partnered individuals (or parents).

Figure 1.

Scatterplots of global affect as a function of total time spent with partner.

Table 7.

Global affect as a function of total time engaged in activities

			Outcome
			Global Positive Affect			Global Meaning			Global Negative Affect			Global Life Satisfaction
Predictor, hours spent:				95% CI			95% CI			95% CI			95% CI
Activity	M	SD	β	LB	UB	β	LB	UB	β	LB	UB	β	LB	UB
Working	3.46	4.25	0.06	0.01	0.10	0.02	−0.03	0.07	−0.02	−0.07	0.03	0.00	−0.04	0.04
Exercising	0.51	1.36	0.05	0.01	0.09	0.00	−0.04	0.04	−0.02	−0.06	0.03	0.01	−0.03	0.04
Studying	0.25	1.02	0.03	−0.01	0.08	0.03	−0.01	0.08	0.03	−0.02	0.08	0.00	−0.03	0.04
Reading	0.90	2.00	0.03	−0.01	0.08	0.01	−0.03	0.06	−0.06	−0.11	−0.01	0.00	−0.04	0.03
Entertainment	1.15	2.19	0.03	−0.01	0.08	−0.03	−0.07	0.02	−0.01	−0.07	0.03	−0.02	−0.06	0.02
Commuting	1.71	2.74	0.03	−0.01	0.06	−0.01	−0.05	0.03	0.02	−0.02	0.07	−0.01	−0.04	0.02
Childcare	1.01	2.42	0.02	−0.03	0.07	0.03	−0.03	0.08	0.05	−0.01	0.10	0.00	−0.05	0.04
Spiritual	0.60	1.92	0.02	−0.02	0.06	0.05	0.01	0.10	0.02	−0.03	0.07	0.01	−0.02	0.05
Eating	2.46	2.58	0.02	−0.03	0.06	0.03	−0.02	0.07	−0.02	−0.07	0.03	0.03	−0.01	0.07
Napping	0.87	2.28	0.02	−0.04	0.05	−0.02	−0.06	0.02	−0.05	−0.09	−0.00	0.01	−0.02	0.04
Relaxing	3.56	4.25	0.00	−0.04	0.05	0.03	−0.02	0.08	−0.03	−0.08	0.02	0.01	−0.03	0.04
Sexual activity	0.16	0.76	0.00	−0.04	0.04	0.03	−0.01	0.07	0.00	−0.05	0.04	0.00	−0.04	0.03
Shopping	0.62	1.57	0.00	−0.04	0.04	−0.01	−0.06	0.03	0.01	−0.04	0.06	−0.02	−0.06	0.01
Housekeeping	1.51	2.54	0.00	−0.04	0.04	−0.03	−0.07	0.02	0.00	−0.04	0.05	0.00	−0.03	0.03
Attending class	0.15	0.87	−0.01	−0.05	0.03	−0.02	−0.06	0.03	−0.01	−0.06	0.03	0.01	−0.02	0.04
Preparing food	1.23	1.94	−0.01	−0.05	0.04	−0.02	−0.06	0.02	0.00	−0.04	0.05	0.01	−0.03	0.04
Socializing	3.17	3.70	−0.02	−0.06	0.03	−0.01	−0.06	0.04	−0.02	−0.07	0.04	0.03	−0.01	0.07
Computer	2.82	3.78	−0.02	−0.07	0.03	0.01	−0.04	0.06	0.04	−0.01	0.10	0.00	−0.05	0.04
Getting ready	1.15	1.72	−0.02	−0.06	0.02	0.00	−0.05	0.04	0.00	−0.05	0.05	0.01	−0.03	0.04
Watching TV	2.71	3.21	−0.03	−0.08	0.01	−0.03	−0.08	0.02	0.02	−0.04	0.07	−0.04	−0.08	−0.00
Phone calls	1.21	2.71	−0.03	−0.08	0.01	0.04	−0.01	0.09	0.00	−0.05	0.05	0.01	−0.03	0.04

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

All predictors were tested simultaneously in a single model.

Table 8.

Global affect as a function of time spent with others, controlling time allocated to daily activities.

	Outcome
	Global Positive Affect				Global Meaning				Global Negative Affect				Global Life Satisfaction
Predictor, daily time with:		95% CI				95% CI				95% CI				95% CI
	β	LB	UB	IE	β	LB	UB	IE	β	LB	UB	IE	β	LB	UB	IE
No one	−0.07	−0.18	0.03	−0.02	−0.04	−0.13	0.06	−0.02	−0.03	−0.13	0.07	−0.02	−0.11	−0.21	−0.01	−0.03
Partner*	0.21	0.09	0.33	−0.03	0.11	−0.01	0.22	0.00	−0.19	−0.32	−0.07	0.03	0.21	0.09	0.33	−0.02
Child(ren)*	0.01	−0.11	0.13	−0.03	0.03	−0.09	0.15	−0.04	0.10	−0.02	0.22	0.03	0.04	−0.08	0.16	0.00
Extended family	−0.04	−0.14	0.05	0.03	−0.02	−0.11	0.07	0.05	0.07	−0.02	0.16	−0.02	−0.03	−013	0.05	0.03
Friend(s)	0.00	−0.11	0.11	0.09	−0.03	−0.13	0.08	0.13	0.03	−0.08	0.14	−0.07	−0.04	−0.15	0.07	0.11
Roommate(s)	0.01	−0.08	0.10	0.02	0.02	−0.07	0.11	0.03	−0.01	−0.10	0.08	−0.01	0.03	−0.06	0.12	0.02
Client(s)	−0.02	−0.12	0.09	0.06	0.09	−0.01	0.19	0.06	0.10	−0.00	0.20	0.05	−0.01	−0.11	0.09	0.06
Coworker(s)	0.01	−0.11	0.13	0.03	−0.03	−0.15	0.09	0.06	0.03	−0.09	0.15	−0.03	−0.01	−0.13	0.11	0.07
Boss(es)	0.01	−0.09	0.12	0.02	−0.05	−0.15	0.05	0.06	0.07	−0.04	0.17	−0.03	−0.01	−0.12	0.09	0.08

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound; IE = total indirect effect of persons on episodic affect via activities (i.e., the extent to which the association between a person’s presence and episodic affect was reduced by controlling all activities).

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

Italicized parameters dropped below the threshold for statistical significance with time use controlled (compare with Table 6).

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slope of partners (or children) being present for partnered individuals (or parents).

To summarize our findings thus far, participants reported greater episodic positive affect and meaning while currently with their partners, children, and friends—and less positive affect and greater negative affect while currently with their coworkers and supervisors. In contrast, when examining the amount of time spent around these classes of individuals, only total time spent with romantic partners was associated with global well-being. Thus, for example, although people experienced boosts in episodic well-being while with their friends, spending greater amounts of time with their friends did not predict greater global well-being. Similarly, although people experienced greater negative affect while currently with their colleagues, spending greater amounts of total time in the company of one’s colleagues did not predict worsened global well-being. The differences in these findings may represent differences between global and experiential well-being—and they may also represent differences in how well-being operates on a within-persons versus between-persons level.

Moderation Analyses

For our next series of analyses, we examined whether several demographic variables moderated the associations between others’ presence/time spent with others and well-being. Notably, although prior research has identified potentially important moderators of the links between time with others and well-being (e.g., fathers may enjoy time with their children more than do mothers), most of the moderators we tested have not been studied by prior research. Thus, the vast majority of our moderation analyses were fully exploratory.

Specifically, we examined whether age, gender, income, and marital status moderated any of our findings (see Table 9 for the correlations between these variables and total time spent around different types of people). All moderators were tested simultaneously. Notably, due to how the moderators were coded and centered, the “reference group” was average-aged (i.e., 52.77), average-salaried (i.e., $59,150 USD/year), non-married/partnered women (thus the first-order coefficients are simple slopes for these individuals). Age and income were standardized, and thus the “Age × Partner Present” parameter estimates in Table 10, for example, capture the extent to which the association between partner presence and episodic well-being changes per SD (14.81 year) increase in age. Gender and marital status were dummy-coded. Thus, the “Male × Partner Present” parameter estimates in Table 10, for example, capture the extent to which the association between partner presence and episodic well-being was different for men, relative to women.¹⁰

Table 9.

Correlations between demographic mediators and total time with other people

	Demographic Attributes
Total Time with:	Age	Male	Income	Married or Equivalent
No One	.27	.02	−.15	−.10
Partner	.11	.09	.27	.61
Child(ren)	−.30	−.17	.11	.26
Extended Family	−.11	−.11	.02	.03
Friend(s)	−.08	.02	−.17	−.04
Roommate(s)	−.11	−.02	−.10	−.12
Client(s)	−.24	−.06	.02	.03
Coworker(s)	−.29	.04	.17	.02
Boss(es)	−.27	.02	.05	.06

Note: Ninety-five percent confidence intervals for correlations in boldface do not contain zero.

Table 10.

Demographics as moderators of the link between episodic affect and others’ presence

	Outcome
	Episodic Positive Affect			Episodic Meaning			Episodic Negative Affect
		95% CI			95% CI			95% CI
Predictor	b	LB	UB	b	LB	UB	b	LB	UB
No one presenta	−0.10	−0.15	−0.04	−0.09	−0.14	−0.04	−0.05	−0.11	0.01
Partner presentab	0.04	−0.06	0.15	0.08	−0.01	0.17	−0.02	−0.13	0.09
Child(ren) presentab	0.13	0.04	0.22	0.06	−0.02	0.14	0.03	−0.07	0.13
Extended family presenta	−0.03	−0.14	0.08	0.01	−0.09	0.11	0.12	0.00	0.24
Friend(s) presenta	0.17	0.07	0.26	0.09	0.01	0.17	−0.11	−0.21	−0.01
Roommate(s) presenta	0.09	−0.24	0.42	0.05	−0.24	0.34	0.09	−0.25	0.44
Client(s) presenta	0.15	0.02	0.28	0.13	0.02	0.25	0.17	0.04	0.31
Coworker(s) presenta	−0.06	−0.15	0.03	−0.02	−0.10	0.06	0.11	0.01	0.20
Boss(es) presenta	−0.15	−0.30	−0.00	−0.12	−0.26	−0.00	0.20	0.05	0.36
Agec
Age × No one present	0.02	−0.01	0.05	0.01	−0.01	0.04	0.00	−0.03	0.03
Age × Partner presentb	−0.05	−0.08	−0.01	−0.03	−0.06	0.00	0.05	0.02	0.09
Age × Child(ren) presentb	−0.02	−0.07	0.04	0.04	−0.00	0.09	0.06	0.00	0.12
Age × Extended family present	−0.03	−0.09	0.03	−0.02	−0.07	0.03	0.00	−0.07	0.06
Age × Friend(s) present	−0.02	−0.06	0.03	0.02	−0.02	0.06	0.01	−0.04	0.06
Age × Roommate(s) present	0.04	−0.15	0.22	−0.05	−0.21	0.12	0.03	−0.17	0.22
Age × Client(s) present	0.08	0.01	0.16	0.01	−0.05	0.08	−0.10	−0.17	−0.03
Age × Coworker(s) present	0.03	−0.03	0.08	0.01	−0.04	0.06	−0.07	−0.12	−0.01
Age × Boss(es) present	0.04	−0.05	0.13	0.04	−0.04	0.12	0.02	−0.07	0.12
Maled
Male × No one present	−0.01	−0.07	0.05	−0.05	−0.10	0.00	−0.03	−0.09	0.03
Male × Partner presentb	0.04	−0.02	0.11	−0.01	−0.07	0.05	0.02	−0.05	0.09
Male × Child(ren) presentb	−0.05	−0.14	0.04	−0.04	−0.12	0.04	−0.03	−0.12	0.07
Male × Extended family present	0.13	0.00	0.26	0.08	−0.03	0.19	−0.09	−0.22	0.04
Male × Friend(s) present	−0.05	−0.15	0.05	0.03	−0.06	0.11	0.10	0.00	0.21
Male × Roommate(s) present	0.00	−0.36	0.35	0.15	−0.16	0.46	−0.18	−0.55	0.19
Male × Client(s) present	−0.01	−0.14	0.12	0.06	−0.05	0.18	−0.10	−0.23	0.04
Male × Coworker(s) present	0.02	−0.08	0.11	0.06	−0.02	0.14	−0.01	−0.11	0.08
Male × Boss(es) present	0.01	−0.13	0.15	0.13	0.00	0.25	−0.03	−0.18	0.12
Incomec
Income × No one present	−0.02	−0.05	0.02	−0.05	−0.07	−0.02	−0.03	−0.06	0.00
Income × Partner presentb	0.02	−0.02	0.06	0.03	−0.01	0.06	−0.02	−0.06	0.02
Income × Child(ren) presentb	−0.02	−0.08	0.03	−0.02	−0.07	0.02	0.06	0.00	0.11
Income × Extended family present	0.00	−0.08	0.07	−0.02	−0.09	0.05	0.00	−0.08	0.08
Income × Friend(s) present	0.06	0.06	0.12	0.06	0.01	0.11	0.04	−0.02	0.10
Income × Roommate(s) present	0.06	−0.17	0.28	0.12	−0.08	0.33	−0.07	−0.30	0.17
Income × Client(s) present	0.04	−0.03	0.12	0.03	−0.03	0.10	0.00	−0.07	0.08
Income × Coworker(s) present	0.06	0.00	0.12	0.08	0.03	0.14	0.00	−0.06	0.06
Income × Boss(es) present	0.10	0.02	0.19	0.08	0.01	0.16	0.00	−0.09	0.09
Marriedde
Married × No one present	0.03	−0.03	0.10	0.00	−0.06	0.06	−0.02	−0.09	0.05
Married × Partner presentb	0.00	−0.11	0.10	−0.02	−0.11	0.08	0.02	−0.09	0.13
Married × Child(ren) presentb	0.02	−0.09	0.13	0.14	0.04	0.24	−0.02	−0.14	0.09
Married × Extended family present	−0.10	−0.25	0.04	−0.04	−0.16	0.09	0.09	−0.06	0.24
Married × Friend(s) present	−0.06	−0.18	0.05	−0.06	−0.17	0.04	0.10	−0.03	0.22
Married × Roommate(s) present	−0.02	−0.50	0.45	−0.09	−0.51	0.33	−0.16	−0.67	0.34
Married × Client(s) present	−0.18	−0.33	−0.03	−0.14	−0.27	−0.00	−0.05	−0.21	0.11
Married × Coworker(s) present	−0.05	−0.16	0.05	0.00	−0.09	0.10	0.05	−0.06	0.17
Married × Boss(es) present	0.08	−0.09	0.25	0.12	−0.03	0.27	−0.08	−0.26	0.10

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

These analyses control for all activity variables.

We created separate models for the presence of each person (e.g., whether the partner was present or not), but all moderators for each person were tested in a single model (e.g., a single model examined whether age, gender, income, and marital status moderated the effects of a partner being present).

^aDue to how the model was specified, these are the simple associations for average-aged, average-salaried, single women;

^bTo separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slope/interaction of partners (or children) being present for partnered individuals (or parents);

^cThese moderators were standardized, and thus represent the change in simple association per SD of the moderator;

^dThese moderators were dummy-coded, and thus represent the differences in the simple association between groups;

^eMarried, or equivalent (e.g., domestic partnership).

As can be seen in Tables 10 and 11, demographic characteristics moderated our findings in inconsistent ways that may or may not be meaningful (as opposed to resulting from sampling error). Of 216 interactions tested, 36 (17%) were statistically significant. Some of the seemingly more systematic and theoretically sensible moderation effects were that, as compared with younger persons, older individuals appeared to experience relatively less episodic positive affect and greater episodic negative affect when in the presence their partners and children (see the Age interaction terms in Table 10). As compared with poorer persons, higher-income individuals appeared to be buffered against the reductions in episodic positive affect that accompany being in the presence of one’s bosses and coworkers (see the Income interactions in Table 10). Finally, married individuals appeared to have higher global well-being as a function of total time spent with their extended families, and lower global well-being as a function of total time spent alone (see the Married interactions in Table 11). The remaining statistically significant coefficients seemed to operate in inconsistent ways across various measures of well-being, suggesting that they may be attributable to sampling error, rather than meaningful effects.

Table 11.

Demographics as moderators of the link between global affect and time spent with others.

	Outcome
	Global Positive Affect			Global Meaning			Global Negative Affect			Global Life Satisfaction
		95% CI			95% CI			95% CI			95% CI
Predictor	b	LB	UB	b	LB	UB	b	LB	UB	b	LB	UB
Time w/ no onea	0.03	−0.16	0.21	0.12	−0.05	0.31	−0.02	−0.21	0.17	0.06	−0.12	0.24
Time w/ partnerab	−0.07	−0.34	0.20	−0.03	−0.30	0.24	0.09	−0.18	0.36	0.12	−0.14	0.38
Time w/ child(ren)ac	−0.25	−0.51	0.01	−0.18	−0.44	0.08	0.31	0.04	0.57	−0.15	−0.40	0.11
Time w/ extended familya	−0.14	−0.28	0.01	−0.17	−0.31	−0.02	0.21	0.06	0.35	−0.06	−0.20	0.08
Time w/ friend(s)a	0.13	−0.08	0.34	0.01	−0.21	0.22	−0.18	−0.39	0.03	0.18	−0.03	0.38
Time w/ roommate(s)a	0.03	−0.12	0.19	0.10	−0.05	0.26	−0.06	−0.22	0.10	0.04	−0.11	0.19
Time w/ client(s)a	0.06	−0.12	0.23	0.20	0.02	0.37	0.07	−0.10	0.25	0.10	−0.07	0.27
Time w/ coworker(s)a	0.09	−0.12	0.29	0.16	−0.04	0.36	−0.01	−0.22	0.19	0.12	−0.07	0.31
Time w/ boss(es)a	0.14	−0.07	0.35	0.06	−0.14	0.27	−0.10	−0.30	0.11	0.10	−0.10	0.30
Aged
Age × No one	0.05	−0.05	0.15	0.01	−0.09	0.11	0.01	−0.09	0.10	0.06	−0.04	0.15
Age × Partnerb	−0.03	−0.13	0.08	−0.03	−0.13	0.07	0.04	−0.07	0.14	−0.06	−0.16	0.04
Age × Child(ren)c	−0.08	−0.22	0.07	−0.03	−0.17	0.12	0.08	−0.06	0.23	−0.11	−0.25	0.03
Age × Extended family	0.04	−0.07	0.14	0.06	−0.04	0.17	0.00	−0.11	0.10	0.01	−0.09	0.12
Age × Friend(s)	0.01	−0.08	0.11	−0.01	−0.10	0.09	0.01	−0.09	0.10	0.00	−0.09	0.09
Age × Roommate(s)	−0.25	−0.42	−0.08	−0.12	−0.29	0.05	0.18	0.01	0.35	−0.21	−0.37	−0.04
Age × Client(s)	0.05	−0.06	0.16	0.07	−0.04	0.18	0.01	−0.10	0.12	−0.01	−0.11	0.10
Age × Coworker(s)	0.03	−0.08	0.14	0.05	−0.06	0.16	0.12	0.01	0.23	−0.04	−0.15	0.07
Age × Boss(es)	−0.04	−0.15	0.07	−0.04	−0.14	0.07	0.15	0.04	0.26	−0.13	−0.23	−0.02
Malee
Male × No one	−0.15	−0.35	0.05	−0.06	−0.26	0.14	0.07	−0.13	0.27	−0.12	−0.31	0.07
Male × Partnerb	0.15	−0.05	0.34	0.06	−0.14	0.26	−0.08	−0.28	0.12	0.18	−0.01	0.37
Male × Child(ren)c	−0.08	−0.31	0.15	0.00	−0.23	0.23	−0.04	−0.27	0.20	0.01	−0.21	0.23
Male × Extended family	−0.25	−0.49	−0.01	−0.16	−0.40	0.08	−0.03	−0.27	0.21	−0.11	−0.34	0.12
Male × Friend(s)	0.02	−0.17	0.21	0.10	−0.09	0.29	−0.06	−0.25	0.14	0.03	−0.15	0.22
Male × Roommate(s)	0.17	−0.08	0.42	0.07	−0.19	0.32	−0.04	−0.29	0.22	0.13	−0.11	0.37
Male × Client(s)	0.06	−0.15	0.26	0.05	−0.15	0.26	−0.08	−0.29	0.13	0.04	−0.16	0.24
Male × Coworker(s)	0.02	−0.17	0.21	−0.08	−0.27	0.11	−0.09	−0.28	0.10	−0.06	−0.24	0.13
Male × Boss(es)	−0.03	−0.22	0.16	−0.08	−0.27	0.11	0.09	−0.09	0.28	−0.08	−0.25	0.11
Incomed
Income × No one	0.05	−0.06	0.15	0.14	0.04	0.24	0.03	−0.08	0.13	0.08	−0.02	0.18
Income × Partnerb	−0.02	−0.13	0.09	0.04	−0.07	0.15	−0.01	−0.12	0.10	−0.01	−0.11	0.09
Income × Child(ren)c	−0.10	−0.21	0.01	−0.06	−0.17	0.06	0.03	−0.09	0.14	−0.04	−0.15	0.07
Income × Extended family	−0.02	−0.14	0.11	−0.09	−0.21	0.04	0.00	−0.13	0.12	0.01	−0.12	0.13
Income × Friend(s)	−0.02	−0.15	0.11	0.02	−0.11	0.15	−0.09	−0.22	0.04	0.01	−0.11	0.14
Income × Roommate(s)	0.29	0.05	0.52	0.21	−0.02	0.45	−0.19	−0.43	0.04	0.21	−0.02	0.43
Income × Client(s)	0.00	−0.12	0.11	0.04	−0.07	0.16	0.07	−0.05	0.18	−0.07	−0.18	0.04
Income × Coworker(s)	−0.01	−0.12	0.11	0.05	−0.06	0.17	−0.06	−0.17	0.06	−0.09	−0.20	0.02
Income × Boss(es)	0.06	−0.07	0.19	0.03	−0.10	0.16	−0.15	−0.28	−0.02	−0.02	−0.15	0.11
Marriedef
Married × No one	−0.11	−0.33	0.11	−0.30	−0.52	−0.08	0.03	−0.19	0.25	−0.23	−0.44	−0.02
Married × Partner	0.22	−0.07	0.52	0.15	−0.15	0.44	−0.22	−0.53	0.08	−0.05	−0.33	0.24
Married × Child(ren)c	0.40	0.08	0.71	0.28	−0.03	0.60	−0.31	−0.63	0.01	0.23	−0.08	0.53
Married × Extended family	0.26	0.06	0.46	0.36	0.15	0.56	−0.27	−0.47	−0.06	0.10	−0.10	0.29
Married × Friend(s)	−0.08	−0.34	0.19	−0.04	−0.30	0.23	0.27	0.00	0.54	−0.16	−0.41	0.10
Married × Roommate(s)	−0.18	−0.49	0.14	−0.10	−0.42	0.22	0.29	−0.03	0.61	−0.10	−0.41	0.20
Married × Client(s)	−0.07	−0.27	0.13	−0.13	−0.33	0.07	−0.03	−0.23	0.17	−0.12	−0.31	0.07
Married × Coworker(s)	−0.08	−0.29	0.12	−0.16	−0.36	0.05	0.08	−0.12	0.29	−0.10	−0.30	0.10
Married × Boss(es)	−0.15	−0.39	0.10	−0.08	−0.32	0.16	0.20	−0.04	0.44	−0.13	−0.37	0.10

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero;

These analyses control for all time use variables.

We created separate models for each person (e.g., time spent with partner), but all moderators for each person were tested in a single model (e.g., a single model examined whether age, gender, income, and marital status moderated the effects time spent with partner).

^aDue to how the model was specified, these are the simple associations for average-aged, average-salaried, single women;

^bDue to how the model was specified, these are the simple slopes of time spent with partners for unmarried individuals;

^cTo separate the effects of simply having children from the effects of total time with one’s children, these coefficients are the simple slope/interaction of children being present for parents; notably, the parameter estimates marked with an ^ab superscript are the simple slope of total time with children on well-being for single parents;

^dThese moderators were standardized, and thus represent the change in simple association per SD of the moderator;

^eThese moderators were dummy-coded, and thus represent the differences in the simple association between groups;

^fMarried, or equivalent (e.g., domestic partnership).

Random slopes models.

Finally, reviewers requested that we rerun our episodic well-being (i.e., within-persons) analyses, including a random slope in the models. In these models, statistically significant variance in the random slope would indicate that others’ presence may have predicted episodic well-being to differing degrees for different participants. Such variance in the size of the effect across participants may indicate the presence of unspecified moderators that were not measured in the present study (e.g., spending time with one’s partner might predict greater or lower episodic well-being, depending on various unspecified moderators, such as personality, demographics, relationship quality, and so on). As can be seen in Appendix Table A4, likelihood ratio tests revealed that there was statistically significant variance in all random slopes tested, all χ²(1)s ≥ 7.84, ps ≤ .005. Thus, these results indicate, for example, that the presence of one’s partner may predict episodic positive affect to a different degree for different individuals, perhaps depending on unspecified moderating variables (see Figure 2 for spaghetti plots illustrating this variance).¹¹

Figure 2.

Spaghetti plots illustrating variance in the effect of partners’ presence on episodic positive and negative affect for various individuals. Each line in these graphs represents one individual participant. The slope of the line represents increases in positive affect across episodes when the partner was present, as compared to episodes when the partner was absent. These graphs depict data from a subsample of only 100 participants in order to “thin” the graphs and make the variation in slopes more obviously apparent.

Discussion

Prior research suggests that, although positive social relationships are a fundamental human need (Baumeister & Leary, 1995; Bowlby, 1969; Deci & Ryan, 2000; Myers, 2000), actually interacting with one’s closest associates may not necessarily spur momentary positive emotions (Kahneman et al., 2004)—potentially because such interactions may require one to engage in caretaking or support roles that are not uniformly pleasant (e.g., Cichy et al., 2014; Dolan et al., 2008; Mackinnon et al., 2012). The purpose of the present study was to more thoroughly examine [1] the extent to which the company of specific classes of other persons (e.g., partners, children, friends, colleagues) predicted concurrent, episodic affect, as well as [2] whether investing greater total daily time in these various relationships was associated with variation in global well-being.

Does the Company of Others Predict Experiential Well-Being?

We first examined the extent to which participants’ experiential well-being (e.g., momentary affect) varied as a function of the specific people with whom they were currently interacting. For example, we tested whether people reported greater positive affect while in the company of their romantic partners, as opposed to while apart from them. On a zero-order level, we replicated previous research suggesting that people report the greatest levels of experiential positive affect and meaning, and lowest levels of experiential negative affect while interacting with their friends, children, and romantic partners, as opposed to while alone or while interacting with colleagues, clients, or supervisors (e.g., Flood & Genadek, 2016; Helliwell & Wang, 2014; Kahneman et al., 2004; Lucas et al., 2008; Nelson et al., 2013; Srivastava et al., 2008). Moreover, our zero-order results aligned with prior findings that people experience maximal experiential well-being specifically while with their friends, as opposed to while with their romantic partners and children (Kahneman et al., 2004). Notably, however, the associations between others’ presence and episodic well-being were small to moderate —with the maximum effect size being equivalent to a Cohen’s d of approximately 0.30. Thus, the effect sizes are inconsistent with a model in which other people’s presence has a dramatic impact on momentary felt emotions.

Nevertheless, the fact that people reported greater positive affect and meaning while with their friends, as opposed to while with their children or partners appears to be attributable to the activities that people tend to perform while with friends versus while with their families. Specifically, in analyses that statistically controlled for the activities in which participants were engaged, children being present had the largest associations with higher experiential well-being (e.g., Nelson et al., 2013)—though the effect sizes were similar for children, friends, and romantic partners being present. As an important caveat, however, our study did not necessarily include an exhaustive list of all activities in which participants might have engaged with various relationship partners. Thus, including more activities—or a different set of activities—might have produced different findings. For example, people may enjoy teaching/mentorship activities, which may explain why experiential well-being seems higher with children (rather than people enjoying their children’s presence per se). This issue should be examined in future studies.

Nevertheless, these findings point to a nuanced understanding of how social interactions relate to concurrent emotions and moods. Specifically, the people who are present and the activities that being performed appear to have separable associations with experiential well-being. When isolating the effects of the people who are present (by statistically controlling for the activities being performed), individuals do not appear to respond more favorably to the mere presence per se of their friends, rather than that of their partners or children. To the contrary—it appears that, when activities are statistically controlled, the presence of children predicts the largest differences in momentary positive emotions (e.g., Nelson et al., 2013)(although the effects are similar in magnitude for friends and partners, as well). Nevertheless, it appears that people do engage in more pleasurable activities while with friends (versus family) and thus do incidentally report higher experiential well-being while with friends (versus family) (Kahneman et al., 2004). However, the increased affect seems to be attributable to the activities being performed—and not necessarily to that friends (versus family) are present.

That said, beyond considering activities, we did not explore why people might enjoy the mere presence of their children, partners, and friends. A variety of processes might explain this phenomenon. For example, children, partners, and friends may provide stimulating conversation, meaningful interactions, social support, validation, affection, and a sense of connectedness and companionship (e.g., Debrot et al., 2013; Reis et al., 2014, 2000). Future studies should more thoroughly tease apart the exact mechanisms that explain why children, partners, and friends are associated with differences in episodic well-being.

To summarize, our findings suggest that an individual would not necessarily experience greater experiential affect while engaged in any arbitrary activity if friends were present, as opposed to their romantic partner or children. Thus, our research aligns with an optimistic view of interactions with one’s immediate family (partners, children): Irrespective of whether activities are held constant, romantic partners and children are associated with more joy than misery (see Nelson, Kushlev, & Lyubomirsky, 2014)—but when activities are held constant, romantic partners and children are associated with just as much positive affect as are friends.

Finally, it is worth mentioning that while interacting with clients, colleagues, and supervisors, participants reported less positive affect and greater negative affect, but also a greater sense of meaning. This greater sense of meaning around colleagues and supervisors, however, appeared to have been attributable to the fact that people find meaning in their work, rather than finding the company per se of their colleagues or supervisors meaningful. Nevertheless, the fact that, on a zero-order level, the presence of colleagues/supervisors was associated with lesser positive affect yet greater meaning may suggest that what some scholars have referred to as “hedonic well-being” (positive affect) and “eudemonic well-being” (a sense of meaning) are separate and may operate via different processes, despite correlating highly with one another (e.g., Son & Wilson, 2012).

Does Spending More Time with Relationship Partners Predict Greater Global Well-Being?

In contrast to the previous findings we have summarized, in which we examined the extent to which experiential well-being varied as a function of the company of others, we also examined the extent to which investing greater amounts of daily time in various other relationships (e.g., romantic partners, children, friends) predicted global well-being. In contrast to the more numerous experiential findings, our global results suggested that, when time allocated to all activities was held constant, only total daily time invested in one’s romantic partner predicted greater global positive affect and life satisfaction, and lesser global negative affect. These associations were modest in magnitude (equivalent to approximately r = .21; Richard, Bond, & Stokes-Zoota, 2003), and similar in size to the association between global well-being and other important predictors, such as income (see Lucas & Dyrenforth, 2006).

Why should spending greater amounts of time with one’s romantic partner predict greater boosts in well-being? For one, it is possible that the mere act of investing time into one’s romantic partnership has the potential to increase the psychological sense that one’s life is progressing well (Argyle, 2001; Baumeister & Leary, 1995; Dolan et al., 2008). For example, forming a successful romantic partnership is highly socially valued, as well as an indicator that one is “progressing well” through culturally-dictated life tasks (e.g., Erikson, 1974; Hutteman, Hennecke, Orth, Reitz, & Specht, 2014). Thus, spending greater amounts of time with one’s partner may enhance the subjective impression that one is flourishing in accomplishing valued developmental tasks. Alternatively, one’s romantic partner may provide numerous instrumental benefits, such as providing affection, validation, and serving as a secure base that enhances one’s ability to negative stressful life events (e.g., Debrot et al., 2013; Hazan & Shaver, 1987; Murray, Holmes, & Griffin, 1996). Thus, spending greater amounts of time with their partners may allow individuals to maximize the instrumental benefits received, ultimately leading to gains in well-being. These possibilities are entirely speculative and should be directly tested by future research.

Nevertheless, our experiential and global findings collectively point to a complex series of associations between social interactions and well-being. Although people experience greater momentary positive affect and meaning while with their children, friends, and romantic partners, it appears that only investing greater amounts of daily time in one’s partner returns dividends with respect to global well-being. In other words, our findings suggest that, despite the fact that people are happier while with their friends, for example, spending greater amounts of time with friends each day does not necessary increase the overall sense that one’s life is progressing well.

The fact that daily time with friends did not predict greater global well-being seems to contrast with previous research, which has found that self-reported number of social contacts and interactions therewith predict greater global well-being (e.g., Lucas & Dyrenforth, 2006; Okun et al., 1984; Pinquart & Sorensen, 2000; Russell et al., 2012; Sandstrom & Dunn, 2014). One potential explanation for this apparent discrepancy is that frequent contact with friends (e.g., seeing friends daily) may predict well-being, but the extent of contact (e.g., duration) is inconsequential (Son & Wilson, 2012 describe a similar phenomenon with volunteering). Alternatively, objective frequency and extent of contact with friends may be irrelevant to well-being—it may only be the case that only one’s subjective sense that one has a large and supportive social network has implications for global well-being.

Do Individual Differences Matter?

For our final series of analyses, we examined whether several individual difference variables moderated our findings. Although we tested a large number of exploratory moderators, prior research has suggested that certain variables theoretically should moderate the link between time spent with others and well-being. We review the moderators anticipated by prior theory and research below.

Parent Characteristics.

With respect to parental demographics, prior research suggests that married, older, male, or lower-income parents may be more likely to enjoy their children’s presence, as compared with unmarried, younger, female, or higher-income parents (Campos et al., 2013; Dyrdal & Lucas, 2013; Kushlev et al., 2012; Nelson, Kushlev, & Lyubomirsky, 2014; Nomaguchi & Milkie, 2003; Roeters & Gracia, 2016). We found mixed support for these propositions. Namely, as compared with unmarried parents, married parents reported greater experiential meaning (but not greater positive affect or lesser negative affect) while with their children (versus while apart), and greater global positive affect as a function of investing greater amounts of time in their children. The only other moderation effects were that older (not younger, as prior research would suggest) and higher-income people reported greater negative affect while with their children (vs. apart), as compared with younger and lower-income parents. Parent gender did not moderate our findings.

Other moderators.

Finally, we examined whether age, gender, income, and marital status moderated all of our other findings. Collectively, we tested more than 200 interaction terms, and less than 20% of them were statistically significant. Moreover, the statistically significant parameter estimates were generally inconsistent across the well-being measures (e.g., men reported greater episodic positive affect while with extended family, yet lower global positive affect as a function of spending time with extended family) and did not operate in particularly a priori theoretically sensible ways—which may suggest that many of these moderation effects were attributable to sampling error, rather than meaningful population effects. For these reasons, other than the interactions we have already discussed, we hesitate to interpret the other interactions found in our study until they are replicated in future research.

Implications, Limitations, and Future Directions

One implication of our study is that global and experiential well-being seem to have some unique predictors and correlates (Kim-Prieto et al., 2005; Lucas et al., 1996). Indeed, despite the fact that people reported greater momentary/experiential positive affect and meaning while currently with friends, children, and partners—only spending greater amounts of time with romantic partners was associated with higher global well-being. Thus, spending time with friends, for example, appears to be associated with experiential, but not global well-being. This may suggest that global and experiential well-being are separable, albeit related, constructs. Along these lines, these findings may also indicate that well-being operates differently on the within-persons (i.e., experiential) and between-persons (i.e., global) levels.

That said, it is critical to note that these data are correlational and do not strongly speak to causal processes. For example, it may be the case that interacting with one’s children boosts positive affect. Or it is possible that people choose to interact with their children when they are happier (reverse causality) or that third variables can account for the associations under investigation. Given the nature of the phenomenon under investigation, it might be difficult to disentangle these possibilities experimentally. However, studies with higher-fidelity measures of affect might be able to provide some additional constraints on causal inference. For example, with sufficiently frequent measures of affect, researchers may be able to disentangle the time course: whether experiencing greater momentary affect proceeds seeking out certain relationship partners or vice versa.

A related limitation is that we did not have sufficient waves of data or study length to explore temporal dynamics between global and experiential well-being. Theoretically, chronic changes to experiential well-being should eventually propagate and be reflected in global well-being (and vice versa)(Kim-Prieto et al., 2005). Thus, it may be the case that investing increasingly greater amounts of time in one’s friends may have delayed, rather than immediate, effects on global well-being. Future research should explore this possibility by testing whether within-person variation in time spent with others (e.g., children, partners, friends) predicts corresponding, potentially delayed changes in global well-being over a longer time span.

In a similar vein, our study was limited in that we relied on the DRM to assess experiential affect. Although DRM and ESM measures appear to track one another closely (at least once aggregated; Bylsma et al., 2011; Kahneman et al., 2004; Lucas et al., 2016), DRM measures do ultimately entail some level of retrospective reporting and thus may be susceptible to different sets of biases than ESM measures (e.g., Robinson & Clore, 2002b). Future research is needed on the comparability of DRM and ESM measures (e.g., Lucas et al., 2016)—and, ideally, future studies should replicate our findings using ESM measures.

A second implication of our study is that certain individual differences may be important for determining the psychological consequences of investing time in various relationships. For example, married parents may enjoy spending time with their children to a greater degree than do single parents. Nevertheless, our study was limited in that we did not have access to a wide range of potentially important moderator variables. Indeed, basic demographics were not especially predictive of variation in the associations between time spent with others and well-being. Other theoretically meaningful moderators may operate differently. For example, the effects of spending time with one’s romantic partner depends on the quality of the romantic relationship (Hudson, Lucas, & Donnellan, 2019). Similarly, the effects of spending time with friends likely depends on the quality and nature of the friendship. For example, it may be the case that high-quality friendships, as well as ones that revolve around mutually enjoyable activities spur positive affect and abate negative affect—whereas lower-quality friendships, or ones with individuals who require high levels of support may tax well-being (e.g., Cichy et al., 2014; Mackinnon et al., 2012).

Relatedly, one final limitation of our study is that we tested more than 200 moderation parameters. Although several of these interaction coefficients were statistically significant—approximately 17% of them—the patterns we found were not particularly consistent across measures of well-being, and were not anticipated by prior research and theory. Thus, we would encourage future research to test whether the interactions found within our study are replicable. For example, it may be the case that older individuals truly do experience greater experiential well-being while interacting with colleagues and bosses—perhaps because they have more enjoyable or established careers. Future research should test this and other possibilities.

Conclusion

Positive social relationships are a fundamental human need (e.g., Baumeister & Leary, 1995; Bowlby, 1969; Myers, 2000). To that end, our study suggests that people do, in fact, experience the higher levels of positive affect and meaning when in the company of loved ones—children, friends, and romantic partners than when in the company of other types of relationship partners (e.g., bosses, colleagues, extended family) or when alone. Moreover, investing increasingly large amounts of time in romantic partners is associated with higher reports of global well-being. Our findings underscore the importance of studying the predictors and correlates of global and experiential well-being separately, and demonstrate that there may be substantial individual differences in the factors that predict both momentary, lived well-being as well as the overall sense that one’s life is progressing well.

Appendix

Table A1.

Episodic affect as a function of others’ presence, with all persons’ presence modeled simultaneously

		Outcome
		Episodic Positive Affect			Episodic Meaning			Episodic Negative Affect
Predictor			95% CI			95% CI			95% CI
Persons present	M	bd	LB	UB	bd	LB	UB	bd	LB	UB
Intercept	0.37	−0.10	−0.14	−0.06	−0.11	−0.15	−0.07	−0.05	−0.09	−0.01
Partner	0.30	0.08	0.04	0.12	0.03	−0.00	0.07	−0.07	−0.11	−0.03
Child(ren)	0.17	0.10	0.05	0.14	0.14	0.10	0.17	0.00	−0.04	0.05
Extended family	0.06	−0.04	−0.10	0.03	0.03	−0.03	0.08	0.15	0.08	0.21
Friend(s)	0.09	0.23	0.19	0.29	0.16	0.11	0.20	−0.09	−0.14	−0.04
Roommate(s)	0.01	−0.04	−0.20	0.13	−0.02	−0.17	0.13	0.02	−0.16	0.19
Client(s)	0.05	−0.01	−0.07	0.06	0.10	0.04	0.16	0.15	0.08	0.22
Coworker(s)	0.10	−0.12	−0.18	−0.07	0.04	−0.01	0.08	0.16	0.10	0.21
Boss(es)	0.04	−0.08	−0.16	−0.01	0.02	−0.04	0.09	0.12	0.04	0.20

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

All predictors were tested simultaneously in a single model.

Because the predictors were dummy-coded (1 = present; 0 = not) and the outcomes were standardized, the mean for each predictor represents the percent of episodes in which each person was present on average, and b_d represents the standardized difference in the outcome when the person was present vs. not, holding constant the presence of all other types of people. Furthermore, the intercept captures mean affect when participants were alone (i.e., no one else was present).

Table A2.

Global affect as a function of proportion of daily time spent with others.

	Outcome
	Global Positive Affect			Global Meaning			Global Negative Affect			Global Life Satisfaction
Predictor, daily time with:		95% CI			95% CI			95% CI			95% CI
	β	LB	UB	β	LB	UB	β	LB	UB	β	LB	UB
No one	−0.13	−0.22	−0.04	−0.08	−0.18	0.01	−0.06	−0.15	0.04	−0.13	−0.22	−0.04
Partner*	0.16	0.05	0.28	0.09	−0.02	0.21	−0.12	−0.23	−0.01	0.21	0.11	0.32
Child(ren)*	−0.04	−0.14	0.05	−0.03	−0.12	0.07	0.16	0.07	0.26	0.02	−0.08	0.11
Extended family	−0.03	−0.12	0.06	0.02	−0.07	0.11	0.06	−0.03	0.16	0.00	−0.09	0.09
Friend(s)	0.08	−0.01	0.17	0.08	−0.01	0.17	−0.04	−0.13	0.05	0.08	−0.01	0.17
Roommate(s)	0.03	−0.07	0.12	0.04	−0.05	0.13	−0.01	−0.10	0.08	0.05	−0.04	0.14
Client(s)	0.03	−0.06	0.13	0.13	0.04	0.22	0.07	−0.02	0.16	0.04	−0.05	0.13
Coworker(s)	0.04	−0.05	0.13	0.05	−0.05	0.14	0.02	−0.07	0.12	0.04	−0.05	0.13
Boss(es)	0.04	−0.06	0.13	0.01	−0.08	0.10	0.05	−0.04	0.14	0.04	−0.06	0.13

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slope of partners (or children) being present for partnered individuals (or parents).

Table A3.

Mean episodic affect as a function of total daily time with others

	Outcome
	Mean Episodic Positive Affect			Mean Episodic Meaning			Mean Episodic Negative Affect
Predictor, daily time with:		95% CI			95% CI			95% CI
	β	LB	UB	β	LB	UB	β	LB	UB
No one	−0.11	−0.21	−0.02	−0.07	−0.16	0.03	−0.05	−0.15	0.05
Partner*	0.17	0.05	0.29	0.10	−0.03	0.22	−0.15	−0.27	−0.03
Child(ren)*	−0.10	−0.19	0.00	0.01	−0.09	0.11	0.04	−0.06	0.14
Extended family	0.02	−0.07	0.11	0.01	−0.08	0.10	0.04	−0.05	0.13
Friend(s)	0.11	0.02	0.20	0.14	0.05	0.23	−0.05	−0.15	0.04
Roommate(s)	0.00	−0.09	0.09	−0.01	−0.10	0.08	−0.04	−0.13	0.05
Client(s)	−0.07	−0.16	0.02	0.07	−0.03	0.16	0.05	−0.04	0.14
Coworker(s)	−0.12	−0.21	−0.03	−0.05	−0.15	0.05	0.01	−0.08	0.11
Boss(es)	−0.09	−0.19	−0.00	−0.02	−0.12	0.07	−0.01	−0.10	0.09

Note: CI = confidence interval; LB = lower-bound; UB = upper-bound;

95% CIs for parameters in boldface do not contain zero.

Each predictor was tested in a separate model.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slope of partners (or children) being present for partnered individuals (or parents).

Table A4.

Likelihood ratio tests examining whether there is significant variance in the effect of others’ presence in predicting episodic well-being.

	Outcome
Random slope for person present:	Episodic Positive Affect			Episodic Meaning			Episodic Negative Affect
	s2	Δ−2LL	p	s2	Δ−2LL	P	s2	Δ−2LL	p
No one	0.07	102.97	<.001	0.06	111.15	<.001	0.03	27.30	<.01
Partner*	0.06	62.06	<.001	0.05	80.51	<.001	0.07	51.56	<.01
Child(ren)*	0.08	54.39	<.001	0.09	88.33	<.001	0.07	44.71	<.01
Extended family	0.08	19.41	<.001	0.04	9.78	.002	0.20	50.51	<.01
Friend(s)	0.10	37.20	<.001	0.07	33.57	<.01	0.04	7.84	.005
Roommate(s)†		-	-	-	-	-	-	-	-
Client(s)	0.09	37.64	<.001	0.16	98.06	<.01	0.23	61.48	<.01
Coworker(s)	0.09	41.71	<.001	0.10	79.00	<.01	0.16	85.29	<.01
Boss(es)	0.10	18.76	<.001	0.09	28.53	<.01	0.17	28.26	<.01

Note: s² = variance in random effect; Δ−2LL = likelihood ratio test comparing models including and not including a random effect; p values are based on -Δ2LL being distributed roughly χ²(1).

Each predictor was tested in a separate model.

^*To separate the effects of simply having a partner (or children) from the effects of being with one’s partner (or children), these coefficients are the simple slope of partners (or children) being present for partnered individuals (or parents).

^†These models would not properly converge when a random slope was included.

Table A5.

Within-persons correlations among episodic affect items

	Within-Persons Correlations
Variable	1	2	3	4	5	6	7
1. Happiness	-
2. Satisfaction	.52	-
3. Meaning	.33	.38	-
4. Anger	−.25	−.21	−.10	-
5. Frustration	−.34	−.31	−.12	.54	-
6. Sadness	−.23	−.22	−.09	.39	.37	-
7. Worry	−.22	−.19	−.06	.37	.38	.40	-

Note: This table presents the episode-to-episode within-persons correlations between all seven emotion items.

Figure A1.

Within-person scatterplots of episodic positive affect as a function of whether or not participants’ partners were present. This Figure depicts data from two individuals. The left-hand panel depicts positive affect scores for one individual when his/her partner was present versus absent. The right-hand panel depicts positive affect scores for a different individual when his/her partner was present versus absent. There is within-person variance in positive affect even within “conditions” (i.e., whether someone’s partner is present or absent). Each of the regression lines in the panels represent one of the many regression lines in the spaghetti plot depicted in Figure 2.