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. Author manuscript; available in PMC: 2023 Sep 19.
Published in final edited form as: J Soc Pers Relat. 2022 Jan 7;39(6):1794–1813. doi: 10.1177/02654075211067254

Daily social media use, social ties, and emotional well-being in later life

Yijung K Kim 1, Karen L Fingerman 2
PMCID: PMC10508904  NIHMSID: NIHMS1881654  PMID: 37727534

Abstract

Older American adults are increasingly utilizing communication technologies, but research has seldom explored older adults’ daily social media use and its interface with other “offline” social ties. To explore a complementary and/or compensatory function of social media in later life, this study employed data from the Daily Experiences and Well-Being Study (2016–2017) to examine associations between daily social media use, daily social encounters, social network structure, and daily mood. Community-dwelling older adults (N = 310; Mage = 73.96) reported on their overall social network structure (diversity in types of social ties and size of network), their daily social encounters in-person and by phone, social media use, and emotional well-being for 5 to 6 days. Multilevel models revealed that daily social media use was associated with daily mood in the context of daily social encounters and the size of the social network. Individuals reported less negative mood on days with more social media use and more in-person encounters. More daily social media use was associated with more positive mood for individuals with a relatively small social network but not for their counterparts with larger social networks. Findings suggest that social media is a distinct form of social resource in later life that may complement the emotional benefits of daily social encounters and compensate for the age-related reduction in social network size. Future research should consider how socially isolated older adults might use computer-mediated communication such as social media to foster a sense of social connection.

Keywords: technology, social media, daily diary, emotional well-being, social network

Social media are internet-based channels that enable users to consume, create, and share user-generated contents with other individuals in either real-time or asynchronously (Carr & Hayes, 2015). Although older adults comprise the smallest age group among social media users, the proportion of older American adults on different social networking platforms (e.g., Twitter and Facebook) has steadily increased in recent years (Pew Research Center, 2021). Social media use in later life holds the potential to foster social connections beyond geographical distance and to compensate for health limitations (Antonucci et al., 2017; Fingerman et al., 2020a). Even so, communication based on digital technologies are structurally and functionally distinct from offline communication, and there is little research on how online social experiences interact with the social environment and contribute to the well-being of older adults (Hülür & Macdonald, 2020; Lieberman & Schroeder, 2020). Most social media users, including older adults, use these social networking services at least several times a week, if not on a daily basis (Aarts et al., 2015; Gaia et al., 2020; Pew Research Center, 2021). Despite this trend, many studies have focused on individual differences that distinguish older social media users from non-users in later life (Newman et al. 2019), and questions remain regarding the daily experiences of those older adults who use social media.

The present study investigated the associations between daily social media use, daily emotional well-being, daily social encounters, and social network structure in later life. We used data from the Daily Experiences and Well-Being Study, which included ecological momentary assessment (EMA) of older adults’ social and affective experiences every 3 hours of their day. By gathering data in real time, EMA limits recall biases, minimizes variability of estimates, and offers a more comprehensive picture of respondents’ daily lives than traditional survey methods (Cain et al., 2009). As such, we were able to examine social media use and emotional well-being as they occur in daily life and how those associations may vary depending on the context of older adult’s larger social network.

Social media and daily emotional well-being in later life

Adolescents and young adults are the heaviest users of various social networking sites, and extensive literature documents both the costs and benefits of daily social media use in these age groups (Keles et al., 2020; Naslund et al., 2020). Social media could provide an opportunity for self-expression, provide access to a peer support network, and facilitate social interactions among individuals experiencing difficulties interacting in face-to-face settings (Naslund et al., 2020). Notwithstanding the numerous benefits, there is also widespread concern about the potential harm daily social media has on adolescents and young adults, as a risk factor for addiction, anxiety, depression, and psychological distress perhaps due to social comparisons and diminished offline social contact (Keles et al., 2020; Lin et al., 2016). Social comparison is a key mechanism by which frequent social media use could lead to damaging consequences; The user-created contents on social media often display highly enhanced and idyllic representations of others, eliciting negative feelings about individuals’ own lives in comparison (Alfasi, 2019; Verduyn et al., 2020). Frequent social media use has been associated with psychopathology among adolescents and young adults, who have a tendency to compare themselves to their peers online (Alfasi, 2019; Keles et al., 2020; Lin et al., 2016).

It is possible that the implications of daily social media use for emotional well-being are more positive for older adults than they are for young adults, but daily social media use among older adults remains an understudied area of research. Past studies that have examined the link between social media use frequency and older adults’ psychological well-being report mixed findings, with frequent social media use (i.e., every day/almost every day) predicting higher life satisfaction (Gaia et al., 2020), but not leading to any changes in loneliness and depressive symptoms (Aarts et al., 2015). Nonetheless, the general implications of communication technology use appear more positive for older adults than they are for young adults. According to the strength and vulnerability integration framework, older adults report lower negative and higher positive emotional well-being despite their vulnerability to daily stressors because they adopt strategies to reduce exposure to negative experiences and reappraise their situation on a daily basis (Birditt et al., 2020; Charles, 2010). Older adults tend to select and limit online activities to enhance positive experiences and increase social engagement (Nimrod, 2020; Szabo et al., 2019), and their social media use is primarily motivated by intentions to pursue socially and emotionally meaningful goals (Hülür & Macdonald, 2020; Hutto et al., 2015). These age-related changes in emotional regulation strategies and intentions suggest that daily social media use may confer benefits to older adult’s daily emotional well-being. We thus hypothesize older adults to report more positive and less negative daily mood on days with more social media use, compared to other days with less social media use (H1a).

Offline social networks and social media use

Offline social encounters refer to social interactions existing outside computer-mediated communication (e.g., in person or by telephone; Lieberman & Schroeder, 2020). Older adults’ offline social ties involve social encounters that occur on a day-to-day basis (Fingerman et al., 2020b; Hülür & Macdonald, 2020). In-person social interaction affects older adults’ psychological well-being above and beyond other modes of contact, leading to reduced levels of loneliness (Luhmann & Hawkley, 2016), mood (Huxhold et al., 2014), and depression (Teo et al., 2015). Telephone communication is the most commonly used communication technology for older adults when it comes to daily social interactions with family and friends, allowing them to overcome geographical limitations (Yuan et al., 2016). It is also important to consider the overall structure of the offline social network, such as the number and the diversity of social ties. Although the size of the social network generally decreases with age due to the loss of weak/peripheral ties, the number of emotionally close social ties remains a significant predictor of their emotional well-being (Antonucci et al., 2017; Bruine de Bruin et al., 2020). Social interaction with a wide range of social ties (e.g., acquaintances and neighbors) is also an important indicator of social integration, and a more diverse social network has been associated with better mental health, mood, and physical activity in later life (Fingerman et al., 2019; Fiori et al., 2007). Based on prior research, we thus expect older adults to report more positive and less negative daily mood on days with more daily social encounters, compared to other days with fewer daily social encounters (H1b). We also expect individuals with a more diverse and bigger social network to report more positive and less negative daily mood on average across the observation period, compared to other individuals with a less diverse and smaller social network (H1c).

Online communication intersects with offline social encounters, and these offline social encounters may provide an important context for the associations between online social activities and psychological well-being for older adults. How online social network complements (i.e., social enhancement) or compensates (i.e., social compensation) for individual characteristics and offline social ties has been at the heart of social media research since social media’s initial rise in popularity (Zywica & Danowski, 2008). Early research showed that individuals with strong offline social relationships are more likely to use and benefit from online social interactions, thereby supporting the social enhancement hypothesis (Zhang & Leung, 2015). However, a preponderance of earlier studies investigated university students and their Facebook use, and older adults remain relatively understudied segment of social media users (Hutto et al., 2015). Further, daily associations between various communication technologies, individual characteristics, and social factors suggest a more complex picture (Ruppel et al., 2018a).

Whether older adults’ use of technologies for social connections complements or compensates their offline social network structure and social encounters remains to be elucidated (Antonucci et al., 2017; Fingerman et al., 2020a; Lieberman & Schroeder, 2020), but there is a stronger conceptual support for the complementary hypothesis. Many older adults initially adopt new technologies for social connections at the request of and with assistance from younger family members (Newman et al., 2019). A form of digital solidarity with younger family members is the main motivation for adopting social media for many older adults (Peng et al., 2018), meaning that older adults depend on their offline social ties (e.g., child and grandchild) to set up software, access and actively use social media. These observations suggest that the potential benefit of social media may complement the existing offline social ties. In line with this view, a study on Facebook profiles show that more frequent Facebook use was associated with a reduced risk of mortality for those older adults who engage in more face-to-face social activities (Hobbs et al., 2016).

Much less is known about the compensatory effect of social media. Related studies on the general use of digital technologies (e.g., internet) show that computer-mediated communication reduces loneliness and depressive symptoms among older adults who have infrequent telephone contact with others (Lee et al., 2020) or live alone (Cotten et al., 2014; Silva et al., 2020). In line with the digital solidarity perspective, we expect daily social media use to serve a complementary function. We hypothesize any positive association between daily social media use and the same-day negative and/or positive mood to be stronger on days with more social encounters (H2a). We also expect any positive association between daily social media use and better same-day mood to be stronger for individuals with a more diverse and bigger social network structure (H2b).

The present study

Using data from the Daily Experiences and Well-Being Study, this study investigated whether more social media use throughout the day was associated with the same-day negative or positive mood in later life, and how these associations varied with older adults’ daily social encounters and social network structure.

First, we examined whether daily social media use, daily social encounters (i.e., in-person encounters and telephone communication), and social network structure (i.e., network diversity and network size) are associated with the same-day positive and negative mood.

  • H1a. More daily social media use is associated with more positive and less negative daily mood, compared to other days with less social media use.

  • H1b. More daily social encounters are associated with more positive and less negative daily mood, compared to other days with fewer daily social encounters.

  • H1c. Individuals with a more diverse and bigger social network report more positive and less negative daily mood on average across the observation period, compared to other individuals with a less diverse and smaller social network.

Second, we assessed interactions between daily social media use and daily social encounters (i.e., in-person encounters and telephone communication), as well as interactions between daily social media use and social network structure (i.e., network diversity and network size) on the same-day negative and positive mood. We expected daily social media use to serve a complementary function.

  • H2a. Any positive association between daily social media use and the same-day negative and/or positive mood is stronger on days with more social encounters.

  • H2b. Any positive association between daily social media use and better same-day mood is stronger for individuals with a more diverse and bigger social network structure.

Method

The Daily Experiences and Well-Being Study (2016–2017) involved community dwelling adults aged 65 and older in the greater Austin Texas Metropolitan Statistical Area. The sample was recruited via a landline list with matched addresses and individuals working less than 20 h a week were eligible to participate. Individuals from high-density underrepresented neighborhoods and lower SES neighborhoods were oversampled to represent racial and ethnic diversity as well as the full range of SES. More than 30% of the participants self-identified as ethnic or racial minorities (e.g., African Americans, Hispanic). The majority of participants (~55%) had a bachelor’s degree, which was higher than that of the general older adult population in the greater Austin area (U.S. Census Bureau, 2017). The University of Texas at Austin Institutional Review Board approved all procedures.

We recruited a total of 333 participants who initially completed a 2-h in-person interview (i.e., global interview) assessing their demographic backgrounds, health, and psychosocial characteristics. Participants were further invited to complete 5–6 days of Ecological Momentary Assessments (EMA) surveys every 3 h of their waking hours (approximately six times) to report on their social encounters and behaviors. EMA surveys were scheduled on a study-provided Android device based on each participant’s usual bedtime and wake time during weekdays and weekends.

This study was limited to 313 individuals who participated in the EMA surveys. Of 313 respondents, we used a list-wise deletion method and excluded three individuals who did not report on their social media use, positive and negative mood throughout the study period. The final sample was 310 individuals (1617 day-level observations) who completed on average 5.2 days of EMA surveys. Overall, the excluded participants (n = 23) were more likely to be male and identify themselves as people of color than our analytic sample.

Ecological Momentary Assessments

Positive and negative mood.

At each EMA survey, participants rated their mood using eight items (i.e., loved, content, calm, lonely, bored, nervous, irritated, and sad) from the modified positive and negative affect measures (Watson et al., 1988). Each item was rated with a 5-point scale ranging from 1 (not at all) to 5 (a great deal). To calculate participants’ state of emotional well-being on a given day, we averaged three positive items over each day to create average daily positive mood (i.e., loved, content, and calm; α2l = .74; Lai, 2021) and four negative items to create average daily negative mood (i.e., lonely, nervous, irritated, and sad; α2l = .72).

Social media use.

At each EMA survey, participants indicated whether they used social media (e.g., Facebook and Twitter) in the past 3 hours (1 = yes, 0 = no). We then divided the number of assessments with social media use by the total number of assessments for the day. Higher scores indicate more proportion of daily assessments spent using social media on a given day.

Daily social encounters.

At each EMA survey, participants indicated whether they had contact with someone in the past 3 hours, and if yes, they reported with whom and the means by which contact had occurred. We coded whether each assessment had any in-person encounters (1 = had an in-person encounter, 0 = no in-person encounter). The number of assessments with in-person encounters was then divided by the total number of assessments for the day to indicate the proportion of daily assessments with in-person encounters. Talking to someone over the phone was similarly coded (1 = had a telephone communication, 0 = no telephone communication). The number of assessments with phone encounters was also divided by the total number of assessments for the day to indicate the proportion of daily assessments with telephone communication.

The global interview

Social network structure.

Network diversity was measured during the baseline interview using the Cohen Social Network Index (SNI; Cohen et al., 1997). Participants were asked about having regular contact (i.e., at least every 2 weeks) with at least one person in 13 different social roles. The roles were: spouse, parent/parent-in-law, sibling, child, grandchild, extended relative, close friend, church/temple member, student/teacher, coworker/employee/employer, neighbor, volunteer, and group member. The total number of social roles was used to indicate network diversity.

Network size was also measured at baseline using three concentric convoy circles. The three circles represent different levels of closeness, and participants were asked to list names of individuals who were close and important to them in a hierarchical fashion (Antonucci et al., 2013). The total number of people listed was used to indicate the number of convoy members.

Covariates

This study considered a set of factors that could potentially confound the relationship between social media use and well-being. Despite the increase in older adults’ social media use, sociodemographic factors (i.e., education, income, age, gender, disability status, immigration status, and urban/rural residence) remain key determinants of general information and communication technology (ICT) access and emotional well-being in later life (Fang et al., 2019; Mitchell et al., 2019). Health-related difficulties in internet use are also important determinants of older adults’ social support networks and quality of life in later life (Ang et al., 2020). As such, the profiles of older social media users show that they are healthier, more likely to be female, and more socially connected than the non-users (Newman et al., 2019).

We thus included time-invariant characteristics such as participants’ age (in years), gender (1 = women, 0 = men), marital status (1 = married or cohabiting, 0 = divorced, separated, or never married), education, ethnicity/race, and self-rated health. Education ranged from 1 (no formal education) to 8 (having an advanced degree), and we categorized education to indicate finishing high school or less, having some college education, and having a college degree or more. Based on self-identified ethnicity and race, we generated an indicator variable for underrepresented groups (1 = people of color, 0 = non-Hispanic White). Self-rated health was measured on a 5-point scale that ranged from 1 (poor) to 5 (excellent). We also considered whether the given day was a weekend or a weekday (1 = weekend, 0 = weekday).

Analytic strategy

To address our research aims, we utilized two-level multilevel analysis to account for the nested structure of the data (i.e., days nested within individuals). Our key predictors included time-varying (i.e., daily social media use, in-person encounters, and telephone communication; level 1) as well as time-invariant (i.e., network diversity and network size; level 2) characteristics. To account for these different relationships between the predictor and the outcome at different levels, we utilized a series of within-between random effects models that distinguish within-person changes from between-person differences (Bell et al., 2019; Hamaker & Muthén, 2020). All time-varying predictors (i.e., daily social media use, in-person encounters, and telephone communication; time-varying) were recoded to their person-mean across the study days (level 2) and the deviation from their person-mean at each day (level 1) in the process. This modeling approach thus concurrently compares individuals who used more social media to those who used less (i.e., between-person differences; level 2), and an individual with more social media use on a given day to him or herself on different days (i.e., within-person changes; level 1). In other words, this separation allows for unbiased estimation of the daily social media use (level 1) even though some participants did not report using social media during the study period. All time-invariant variables were centered to their grand means. Analyses were performed using the MIXED command in Stata 16 and we used the vce(cluster) option to estimate robust standard errors.

To examine the associations between daily social media use, daily social encounters, social network structure, and the same-day positive and negative mood, we regressed average daily mood on daily social media use, daily in-person encounters, daily telephone communication, network diversity, network size, and all covariates. Negative mood and positive mood were estimated as separate outcomes.

We then investigated interactions between daily social media use and daily social encounters, as well as interactions between daily social media use and social network structure. In line with our research aims, we included level 1 interaction terms between daily social media use and each indicator of daily social encounters (i.e., daily in-person encounters and daily telephone communication). Regarding social network structure (i.e., network diversity and network size), we estimated cross-level interaction terms between daily social media use and each indicator of time-invariant social network structure.

Results

Table 1 presents the characteristics of the study sample. Participants were on average about 74 years old and the majority had a college degree or more. Regarding the overall social network structure, participants reported engaging in six different social roles and having 15 convoy members on average. Daily reports showed that participants had in-person encounters and telephone communication during 77% and 32% of their daily assessments on a given day, respectively. Social media was used about 16% during daytime assessments. See Supplementary Table 1 for correlations between study variables.

Table 1.

Descriptive statistics of sample.

Variables M/% (SD) Range
Participant characteristics (N = 310; level 2)
Age 73.95 (6.39) 65–90
Female, % 56
Marrieda, % 59
Education
 High school degree or less, % 15
 Some college, % 28
 College degree or more, % 57
Race/ethnicity
 Non-Hispanic White, % 69
 African American, % 15
 Hispanic or Latinx, % 15
 Otherb, % 1
Self-rated healthc 3.57 (1.01) 1–5
Network diversityd 6.09 (1.84) 1–11
Network sizee 15.18 (6.95) 0–30
Day-level characteristics (N = 1617; level 1)
 Daily social media usef, % 16
 Daily in-person encountersg, % 77
 Daily telephone communicationh, % 32
 Average negative moodi 1.24 (0.37) 1–5
 Average positive moodj 3.80 (0.77) 1–5
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Notes. Respondent, N = 310; respondent-day observation, N = 1617.

a

Coded as 1 (married) and 0 (non-married).

b

Self-identified as Asian, or American Indian, or Alaska Native.

c

Coded as 1 (poor) to 5 (excellent).

d

Number of social roles in which the respondent has regular contact.

e

Total number of social partners reported in the three convoy circles.

f

Percentage of daily assessments reported using social media.

g

Percentage of daily assessments reported having in-person encounters.

h

Percentage of daily assessments reported having telephone communication.

i

Mean of four negative items that range from 1 (not at all) to 5 (a great deal).

j

Mean of three positive items that range from 1 (not at all) to 5 (a great deal).

Table 2 presents key findings from multilevel analyses (see Supplementary Table 2 for the full model). Estimates from the negative mood main model (Model 1A) show that daily social media use was not associated with the same-day negative mood (H1a), but individuals reported more negative mood on days with more telephone communication (b = 0.05, p < .05), compared to the days with less telephone communication (H1b). Furthermore, daily in-person encounters moderated the daily association between more social media use and negative mood (b = −0.23, p <.01; Model 1B). A post hoc simple slopes analysis examined the association between daily social media use and negative mood at three conditional values of daily in-person encounters. The results showed that using more social media was associated with less negative mood on days spent with someone (b = −0.15, p < 01; Figure 1(a)), whereas the association was non-significant on days with fewer in-person encounters (“half day spent alone” b = −0.04, p = .55; “all day spent alone” b = 0.07 p = .45). Thus, the interactions between daily social media use and in-person encounters for negative mood confirmed our complementary hypothesis (H1c).

Table 2.

Multilevel models for social media use and social networks predicting average daily mood.

Variables Negative mood Positive mood
Model 1A: Main Model 1B: Interaction Model 2A: Main Model 2B: Interaction
b (SE) b (SE) B (SE) b (SE)
Fixed effects
 Intercept 1.53*** (0.12) 1.55*** (0.13) 3.13*** (0.26) 3.15*** (0.27)
Daily social media use (level 1)
 Daily social media usea −0.07 (0.05) −0.27 (0.28) 0.06 (0.06) −0.03 (0.28)
Daily social encounters (level 1)
 Daily in-person encountersb −0.03 (0.04) 0.01 (0.05) 0.17*** (0.04) 0.15** (0.05)
 × Daily social media usea — — −0.23* (0.09) — 0.11 (0.11)
 Daily telephone communicationc 0.05* (0.02) 0.06* (0.03) 0.03 (0.03) 0.00 (0.04)
 × Daily social media usea — — −0.05 (0.06) — — 0.14 (0.11)
Social network structure (level 2)
 Network diversityd −0.01 (0.01) −0.00 (0.01) 0.04 (0.02) 0.02 (0.03)
 × Daily social media usea — 0.06 (0.04) — — −0.00 (0.04)
 Network sizee −0.01 (0.00) −0.01* (0.00) 0.02** (0.01) 0.03*** (0.01)
 × Daily social media usea — — 0.00 (0.01) — −0.02* (0.01)
Random effects
 Intercept variance 0.08 (0.01) 0.08 (0.01) 0.41 (0.03) 0.40 (0.03)
 Residual variance 0.04*** (0.01) 0.04*** (0.01) 0.11*** (0.00) 0.11*** (0.00)
 −2 log likelihood 280.0 260.7 1902.0 1889.5
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Notes. Respondent, N = 310; respondent-day observation, N = 1617. Models adjusted for the level 2 effects of daily social media use, daily social encounters, and other covariates but omitted from the tables. A full model could be found in supplementary documents.

*

p < .05.

**

p < .01.

***

p < .001.

a

Proportion of daily assessments reported using social media.

b

Proportion of daily assessments reported having in-person encounters.

c

Proportion of daily assessments reported having telephone communication.

d

Number of social roles in which the respondent has regular contact.

e

Total number of social partners reported in the three convoy circles.

Figure 1.

Figure 1.

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1 (a) Predicted level of average daily negative mood by the proportion of daily social media use and daily in-person encounters. (b) Predicted level of average daily positive mood by the proportion of daily social media use and the size of social networks. Smaller social network indicates 1 SD below the grand-mean (convoy members, n = 9) and bigger social network indicates 1 SD above the grand-mean (convoy members, n = 22).

Estimates from the positive mood main model (Model 2A) show that daily social media use was not associated with the same-day positive mood (H1a). Individuals reported more positive mood on days with more in-person encounters (b = 0.17, p < .001), compared to the days with fewer in-person encounters (H1b). Regarding social network structure, individuals with a bigger social network reported more positive mood (b = 0.02, p < .01), compared to individuals with a smaller social network (H1c). Moreover, social network size moderated the link between daily social media use and positive mood (b = −0.02, p < .05; Model 2B). Simple slopes analyses demonstrate the association between daily social media use and positive mood at one standard deviation above and below the grand-mean social network size. We found that more daily social media use was associated with more positive mood for individuals with a smaller social network than average (b = 0.22, p < .01; Figure 1(b)), and the link was non-significant for the individuals with a bigger social network than average (b = −0.07, p = .37). Thus, the interaction between daily social media use and the social network size for positive mood was contrary to our expectation, demonstrating a compensatory effect (H1c).

Sensitivity analysis

We conducted several sensitivity analyses to examine robustness of our findings and to gain a deeper understanding of different aspects of social network characteristics and encounters. First, we calculated local effect sizes (Cohen’s f2; Selya et al., 2012) and the results indicate that the local effect sizes of four significant findings in Table 2 were small, ranging from .004 to .012. Second, we compared the background characteristics between respondents who used social media at least once during the study period (n = 129) and those who did not use social media (n = 181). Respondents who used social media were younger, had a larger and more diverse social network, and had less negative and more positive daily mood than those who did not use social media (Supplementary Table 3). It should be noted that we cannot distinguish between social media users and non-users in this study. That is, individuals who have social media accounts (e.g., Facebook) may not have used those accounts during the 5- to 6-day intensive data collection period.

We also had information on different types of social encounters participants reported at each EMA survey, as well as the names and relationships of participants’ 10 closest social ties in the baseline interview. From these responses, we recoded our daily social encounter variables to distinguish in-person or phone encounters with “close ties” from those with “peripheral ties” (Fingerman et al., 2019). We then re-estimated the main effect and the interaction effect models using the recoded daily social encounters variables (Supplementary Table 4). The findings showed that individuals reported less negative mood on days with more social media use and encounters with peripheral ties (b = −0.19, p < .01), and more positive mood on days with more social media use and more telephone conversations with peripheral ties (b = .35, p <.01). That is, daily social media use complemented individuals’ contact with their peripheral ties—encounters with those who were not listed as the respondent’s 10 closest social ties—throughout the day.

Discussion

Technological advances have fundamentally changed the ways individuals establish social connections and communicate ideas on a daily basis (Antonucci et al., 2017; Fingerman et al., 2020a). Internet-based social media platforms became invaluable resources for social connections and information dissemination when social distancing measures dramatically decreased in-person social interactions during the recent COVID-19 outbreak (Cuello-Garcia et al., 2020; Xie et al., 2020). Although unequal access to and utilization of digital communication technologies among the older adult population remains a persistent issue, older adults’ social media use is estimated to have been higher than usual during the COVID-19 (Krendl & Perry, 2020). Despite the sharp uptick in older adults’ social media use and other types of computer-mediated communication, our understanding of how such new forms of social interaction influence older adults’ daily experiences is limited. This study adds to the literature by investigating the same-day associations between social media use and emotional well-being among community-dwelling older adults. In addition, we further advanced the literature by investigating how the effect of online social engagement on older adults’ well-being may vary by their offline social network characteristics.

Distinctiveness of online and offline social connections in later life

Our findings on daily in-person encounters, telephone communication, and the size of the overall social network demonstrate that online and offline social experiences are distinct social resources (Lieberman & Schroeder, 2020). Contrary to our expectation, more daily telephone communication was associated with worse same-day negative mood. Telephone communication may be more prone to negative exchanges than in-person encounters because of their inability to provide real-time reactions (Antonucci et al., 2017). It is also possible the potential effects of receiving phone calls may be qualitatively different from making phone calls, on average. More research is needed to address this unexpected finding. Daily in-person encounters and social network size were associated with daily positive mood in the expected directions. Preserving a stable set of emotionally close relationships is one of the most important correlates of health and well-being in later life (Rook & Charles, 2017). Our findings also emphasize the significance of face-to-face activities shared with members of the social convoy in later life, suggesting that ICT may not always be effective in substituting in-person encounters (Fingerman et al., 2020a; Huxhold et al., 2014).

Daily social media use was not associated with same-day mood, even though it was negatively and positively correlated with the negative and positive mood on a bivariate level, respectively. The link between social media use and well-being among older adults remains generally inconclusive (Newman et al., 2019). Despite the steady growth in older adults’ social media use (Pew Research Center, 2021), several key sociodemographic factors (i.e., higher education and income and being non-Hispanic white) are associated with technology use in later life (Fingerman et al., 2020a; Gaia et al., 2020). Relatedly, adopting EMA surveys meant that older adults in our sample had a certain level of familiarity with smartphones, and the study sample was indeed more educated than the average adults over age 65 in study area (i.e., Austin, Texas; Fingerman et al., 2019). Our findings thus have limited generalizability to the general population of older adults or to older adults residing in residential facilities. It should also be noted that our social media measure lacked details that could be used to explicate the mechanism underlying social media use and older adults’ mood. For example, passive (i.e., browsing content produced by others) use of social media has been associated with emotional distress and negative social comparison (Verduyn et al., 2020) among older adults (Hutto et al., 2015). Future research should consider the content of the specific network platforms and individuals’ behaviors on different social networking platforms to fully explore this topic.

Interdependence of online and offline social connections in later life

Older adults reported less negative mood on days with more social media use and in-person encounters. This finding supports the complementary function of daily social media use, that is, conferring emotional benefits on days with substantial in-person encounters—and suggests that the key benefits of social media use may lie in enriching in-person encounters that already exist in older adults’ daily lives. As an illustrative example, using social networking sites to view photos of the day-to-day development of grandchildren could act as a positive conversation starter. A series of sensitivity tests also revealed that daily social media use primarily complemented individuals’ daily social encounters with their peripheral ties. Peripheral relationships are an essential source of social support that enhances the diversity of social network and physical activity levels in later life (Fingerman et al., 2019). Considering that older adults primarily use social media to stay in touch with family members (Hutto et al., 2015; Peng et al., 2018), this finding highlights the emotional benefits of engaging in daily interactions with diverse social ties in later life.

As for the overall structure of the offline social network, we found that individuals with a relatively smaller social network size reported more positive mood on days with more social media use, but this was not the case for individuals with a bigger social network. Using more social media throughout the day was therefore deemed compensatory in this case, that is, only conferring emotional benefits to those individuals with less than the average size social network. Age-related reduction in social network size is often explained by the socioemotional selectivity theory (Carstensen, 2006), which postulates the salience of emotionally meaningful goals and social relationships in later life. Mirroring this phenomenon, older adults tend to have a smaller online friend network that matches their actual offline friends, reflecting their social needs and goals to prioritize close social relationships (Chang et al., 2015). For example, a recent study by Kim and Shen (2020) on Facebook users found that the association between directed communication activities (e.g., tagging photos of friends, as opposed to broadcasting to an untargeted audience) and life satisfaction were higher among older adults than younger adults. In this context, we suspect that older adults with a relatively fewer number of close ties may be more selective in their online contacts, interacting with information in ways that limit exposure to negative feelings (Charles, 2010).

In sum, we find support for the complementary effect of daily social media use on how in-person social encounters are associated with less negative mood. Our post-hoc analysis found that more social media use was associated with less negative mood on days with more social encounters with peripheral ties, highlighting the benefits of engaging with diverse social ties throughout the day. This finding does not contradict how daily social media use may compensate for the overall social network size in later life. A smaller social network size may be indicative of socioemotional selectivity in both online and offline environments. More studies with detailed information on online social network composition and activities are needed to confirm these explanations.

Limitations and future directions

As noted earlier, we cannot generalize our findings to a general older population whose sociodemographic characteristics (e.g., race/ethnicity and education) are strong determinants of their technology use (Mitchell et al., 2019). We also did not ask for information on gender identity or sexual orientation. Moreover, the study participants generally reported low negative mood, and the effect sizes, albeit significant, were small. Therefore, even though our findings suggested the overall positive impact of social media use in later life, the clinical implications of this study are limited. We also aggregated our EMA data to a day level to focus on how daily variations in social media use are associated with same-day mood and to examine the role of offline social ties. Analyzing the aforementioned associations across more fine-grained time intervals would be a fruitful avenue of future research.

Furthermore, our data lacked information on the quality of both online and offline social ties, which is likely to influence older adults’ online social behaviors and their relevance to well-being (Bruine de Bruin et al., 2020; Yu et al., 2018). For instance, we cannot distinguish whether the day spent with more frequent telephone communication indicates the presence of a stressful issue or a cause for celebration. Future research should consider the emotional quality of social interactions in their analysis to address this issue. We explored how social media use is associated with mood, but there is potential for reverse causation. Findings from studies on adolescent and young adult population especially demonstrate that individuals’ engagement with communication technologies changes as a function of psychological well-being and stress (Ruppel et al., 2018b; Yoon et al., 2019), leading to problematic behaviors like “stressed posting” (sharing negative updates with a social network) on social media (Radovic et al., 2017). Less is known about such phenomenon in the older adult population, and the bidirectional associations between daily social media use and well-being remain to be verified in future studies.

Conclusion

A growing number of older adults are adopting social media in their social lives, but there is very little research on the effects of daily social media use in later life. Utilizing EMA data from a sample of community-dwelling older adults, the current study contributed to the literature by providing the initial evidence for the linkages between social media use, different types of social encounters, social network characteristics, and emotional well-being. Our findings revealed that offline social ties may provide an important context for online social experiences in later life. Individuals reported less negative mood on days with more social media use and more in-person encounters. More daily social media use was associated with more positive mood for individuals with a relatively small social network but not for their counterparts with larger social networks. Overall, our study highlights the need to concurrently examine different aspects of the online and offline social environment when assessing the influence of computer-mediated communication in older adults’ daily lives.

Supplementary Material

Table 1A

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grants R01AG046460 and P30AG066614 from the National Institute on Aging (NIA), and grant P2CHD042849 awarded to the Population Research Center (PRC) at The University of Texas at Austin by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD).

Footnotes

Declaration of conflicting interests

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

Open research statement

As part of IARR’s encouragement of open research practices, the authors have provided the following information: This research was not pre-registered. The data used in the research are currently not available to the public. The data can be obtained by emailing: yijung.kim@ausin.utexas.edu. The materials used in the research are not available to the public. The materials can be obtained by emailing: yijung.kim@austin.utexas.edu.

Supplemental Material

Supplemental material for this article is available online.

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Table 1A
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