Mode of Social Contact, Verbal Communication of Emotion, and Well-Being in Late Life

doi:10.21203/rs.3.rs-4986997/v1

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Mode of Social Contact, Verbal Communication of Emotion, and Well-Being in Late Life

https://doi.org/10.21203/rs.3.rs-4986997/v1

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Older adults prioritize emotions in their relationships, but communication of emotion may differ by in-person and phone contact. Older adults (N = 266, aged 65–90) completed ecological momentary assessments (EMA; n = 4,627) reporting their modes of social contact and positive and negative mood every 3 hours. Participants wore a device with the Electronically Activated Recorder (EAR) app which recorded 30 seconds every 7 minutes (n = 104,746 sound files). Linguistic Inquiry and Word Count (LIWC) extracted linguistic features reflecting verbal communication of emotions from the sound file transcriptions. Multilevel models revealed that both in-person and phone contact were associated with communicating more positive emotions, yet only in-person contact was associated with communicating more negative emotions. Communicating positive emotions was associated with more positive mood and less negative mood, regardless of mode of contact. Participants who had less in-person contact on average experienced a greater increase in positive mood when they communicated positive emotions. This study emphasizes the emotional benefits of social contact, particularly in enhancing positive mood through communicating positive feelings. Findings highlight the unique role of in-person contact in older adults’ daily lives allowing verbal communication of negative emotions not evident via phone contact.

Social science/Psychology/Human behaviour

Social science/Language and linguistics

Social network

emotion regulation

communication

conversation

Communicating emotions to social partners is an essential feature of relationship functioning that contributes to high-quality social contact, emotion regulation, and emotional well-being^1,2. Communicating emotions and maintaining emotional well-being are especially important for individuals in later adulthood, a life stage where people prioritize emotional needs and high-quality communication with social partners (e.g., spouse, children)³. Notably, due to the various types of verbal and non-verbal cues that are available during social contact, the mode of social contact (in person or by phone) may influence how often older adults express emotions in their speech and the resulting emotional benefits derived from social contact⁴.

Studies examining different modes of contact in a daily context among older adults consistently highlight benefits of in-person contact^5,6. The current study aims to provide a more fine-grained analysis of the emotional influences of different modes of contact, by focusing on individuals’ frequency and benefit of verbal communication of emotions during in-person and phone contact. Indeed, from an interpersonal emotion regulation perspective, individuals may share positive emotions to amplify positive feelings^7,8 and disclose negative feelings as an outlet or relief that also promotes emotional well-being⁹. Different modes of social contact may serve as venues for verbal communication of different emotions and potentially provide different emotional benefits.

We examined the following research questions: (a) Are the associations between in person contact as well as phone contact and communication of emotions the same? (b) Do older adults show benefits in daily mood from expressing both positive and negative emotions? and (c) Are the emotional benefits from verbal communication of emotions the same across different modes of social contact (in-person, phone)? This study does not consider texting, social media, or video communication because fewer than two thirds of older adults have a smart phone and fewer than half use social media¹⁰. The current study presents a unique design by examining older adults’ social experiences and verbal emotional expression in an ecologically valid setting. We draw on the largest known dataset of naturalistically occurring speech among older adults, and do so in combination with self-reports of social contact and mood throughout the day.

Mode of Contact and Communication of Emotion

Different modes of social contact may differ in opportunities to share different information or topics. Specifically, media richness theory suggests that in-person contact carries a larger amount of information, including both verbal and non-verbal cues (e.g., physical contact, eye contact, facial expression) than does phone contact^4,11. These cues may facilitate deep and emotionally engaging conversations. For example, one study found that individuals are more likely to engage in physical contact when they feel the need to express their emotions, stressing the importance of non-verbal and in-person contact for communication of emotions¹². In sum, the availability of cues during in-person contact may enhance interpersonal recognition of positive and negative emotions (e.g., fear, happiness, disgust)^13,14. Verbal communication of emotion may reflect the overall great opportunities for a range of communication available in person.

Additionally, accessing various types of informational cues during in-person contact allows individuals to understand social partners’ emotions better and faster, and thus be able to provide and receive synchronous feedback. These processes may be evident in the verbal content individuals use to express or describe their emotional experiences. In contrast, phone contact may restrict the source of information to verbal cues only and impede emotion recognition and communication in a timely manner. Being able to receive reactions is important for emotional expression in an interpersonal context. As such, in-person contact may provide a rich set of informational cues that are important in emotion recognition and communication. These cues may enhance feedback, communication of emotions, and deeper conversations. In sum, older adults may be more likely to communicate their positive and negative emotions during in-person contact, compared to phone contact (H1).

Benefits of Verbal Communication of Emotion

Individuals often engage in social interactions to regulate emotions, a process known as interpersonal emotion regulation (IER)². Based on the IER framework, engaging in interpersonal communication and social sharing may have intraindividual consequences on individuals’ mood^1,15. For example, when individuals express positive emotions and share positive events, social partners may provide encouraging responses which verify individuals’ initial pleasure and thus boost their original positive emotions¹⁶. On the other hand, sharing negative emotions and events may help individuals relieve emotional burdens, potentially leading to an improved mood. Using a daily diary design with college students, a study found that communicating negative emotions (anger, fear, sadness) was associated with shortening duration of such emotions¹⁷. Another study tracked interactions in romantic couples for a week and found that spouses reported worse emotional well-being on days when they were encouraged to suppress their emotions¹⁸. It is possible that sharing negative feelings with social partners facilitates the receipt of social support and improves individuals’ emotional well-being⁹. We hypothesized that communicating both positive and negative emotions to social partners may be associated with better mood throughout the day (H2).

However, different modes of contact may come with varied levels of emotional information and social engagement, which may further influence how people express their own emotions and how much they benefit from expressing emotions. The Interpersonal Model of Capitalization describes the interpersonal emotion sharing process and intra- and inter-personal outcomes^1,19. Specifically, receiving attentive and empathetic responses may maximize emotional benefits and contribute to sustained positive mood. For instance, in a study where young adults shared positive events with peers, receiving positive social feedback enhanced individuals’ positive mood in the moment²⁰. Importantly, in-person contact provides individuals with visual and context cues along with verbal cues, thus enhancing opportunities for emotional feedback and leading to better communications of emotions⁴. On the other hand, people may be less likely to express emotions and more likely to ignore other people’s emotions on the phone and fail to provide encouraging responses. Not being able to recognize and acknowledge social partners’ emotions may lead to decreased emotional well-being for individuals who express emotions. For example, a daily diary study found that individuals reported worse mood on days when their romantic partners ignored their emotions¹⁸.

In sum, in person contact may provide greater opportunities for verbal and non-verbal cues that facilitate active and high-quality responses. We hypothesize that communicating both positive and negative emotions would be associated with better mood, and such associations would be stronger for communication of emotions during in-person contact, compared to phone contact (H3).

The Current Study and Other Factors Associated with Communication of Emotion

This study also considered other factors associated with emotional expression via different modes of contact and well-being: gender, age, marital status, education, ethnic or racial minority status, health, social network size, and time of the survey (morning, afternoon, evening). Compared to men, women are more likely to express their emotions in conversations yet also reported lower well-being²¹. Older age in late adulthood is associated with lower life satisfaction²². Older adults who are married report better well-being and have better health compared to those who are unmarried²³. Individuals with better education are more likely to have better well-being in late adulthood²⁴. Older adults from racial/ethnic minority groups may face greater risks of social isolation and decreased well-being²⁵. Older adults with worse health conditions tend to have lower levels of emotional well-being²⁶. Circadian rhythm may impact individuals’ social contact and mood. Individuals may be more likely to socialize in the evening and tend to show a better mood in the morning^27,28.

Hypotheses were as follows:

H1: Older adults would be more likely to engage in verbal communication of positive and negative emotions during in-person contact, compared to phone contact

H2: Verbal communication of both positive and negative emotions would be associated with more positive mood and less negative mood in the same 3 hours.

H3: The associations between verbal communication of emotion and mood would be stronger when in-person contact took place.

Samples and Procedures

This study drew on data from The Daily Experiences and Well-being Study (DEWS). The study was pre-registered (https://doi.org/10.17605/OSF.IO/FM3AS). Participants first completed a 2-hour initial interview and then completed Ecological Momentary Assessments (EMA) in which they reported social contact on an Android device every 3 hours during waking hours for 5 to 6 days. An Electronically Activated Recorder (EAR) app was installed on the Android device to unobtrusively record ambient sounds. The EAR was activated for 30 seconds every 7 minutes throughout the day²⁹. Of the 333 older adults who completed the initial interview, 22 participants did not participate in EMA or did not complete more than five EMA assessments, and an additional 27 participants did not have valid EAR data and were excluded from the current study. We also excluded 18 participants with sound files in Spanish that resulted in different linguistic feature analysis. As such, the current analytic sample included 266 participants. Supplementary Fig. 1 summarizes the data collection procedures.

Compared to the participants who did not complete the EMA and/or EAR (n = 67), participants eligible for the current study (n = 266) had a higher score of self-rated health (t(331) = 2.88, p = .004, Cohen’s d = 0.46), were less likely to identify as racial or ethnic minorities (ꭓ² = 44.22, p < .001, Cramer’s V = 0.37), and reported higher educational level (ꭓ² = 9.45, p = .009, Cramer’s V = 0.17). There were no differences between the eligible and excluded samples in age, gender, and marital status. We obtained 104,746 sound snippets which were mapped to 4,627 3-hour EMAs. This resulted in 22.64 sound snippets per 3-hour assessment on average (SD = 3.43), among which participants spoke during 21% of the snippets. The percentage of speaking snippets was consistent with previous EAR studies that tracked participants’ ambient sound in daily lives (e.g., 24%)³⁰.

Baseline Interview Measures

Social Partners

Using the social convoy framework³¹, participants named people who were close and important to them in three concentric circles. This measure is widely used with adults of all ages. Participants listed 15.49 close social partners on average (SD = 6.91, range = 0–30).

Participants Characteristics

Participants reported their age in years and gender as 1 (female) and 0 (male). Marital status was reported as married/remarried, cohabiting, widowed, divorced, never married and was recoded 1 (married or cohabitating) and 0 (not married). We recoded educational attainment as 1 (high school or less), 2 (some college school), and 3 (college or more). Corresponding dummy variables were generated for each education level. Participants reported their race and ethnicity, recoded as 1 (ethnic or racial minority) and 0 (non-Hispanic White). Participants rated their health on a scale from 1 (poor) to 5 (excellent)³².

EMA Measures

Social Contact

We transferred the top ten social partners listed in the baseline survey to the EMA surveys. At each 3 hour EMA assessment, participants indicated whether they had contact with each of their ten closest social partners. They also reported whether they had social contact with up to six additional social partners. If participants indicated an encounter, they reported the mode of social contact (in-person, by phone, or by text/email/social media). We calculated the number of in-person and phone contact in the 3-hour intervals respectively. Additionally, for further analyses, we generated variables indicating if each 3-hour assessment contained (a) in-person contact only, (b) phone contact only, (c) both in person and phone; and (d) neither.

Positive and Negative Mood

Participants rated the extent to which they felt four positive (e.g., calm, content) and five negative (e.g., irritated, sad) emotions from 1 (not at all) to 5 (a great deal) every 3 hours throughout the day^33,34. Average scores were calculated for positive (Cronbach’s α = .69) and negative (Cronbach’s α = .72) mood respectively.

Assessment-Level Covariates

Dummy variables were generated to indicate if the assessment happened in the (a) morning (6am to 11:59am), (b) afternoon (noon to 6:59pm) and (c) evening and bedtime (7pm to 5:59am).

Electronically Activated Recorder (EAR) Measurement

Verbal Communication of Positive and Negative Emotions

The current study used the Electronically Activated Recorder (EAR) to unobtrusively obtain ambient sound, including participants’ conversations for 30 seconds every seven minutes during waking hours throughout the day²⁹. Trained research assistants transcribed participants’ speeches verbatim. Social partners’ speeches were not transcribed due to ethical considerations. Each file was transcribed by two different assistants and meetings were held to reach consistency if different transcriptions emerged.

The transcriptions were then entered into the Linguistic Inquiry and Word Count 2015 (LIWC)³⁵. LIWC is a widely used and validated text analysis tool^36,37 that can provide information on individuals’ language use in expressing emotions³⁸. LIWC uses a word frequency approach and compares text corpus with an embedded dictionary to infer emotional state from verbal behaviors. The positive emotion dictionary contains 620 words (e.g., love, sweet) and the negative emotion dictionary contains 744 words (e.g., hurt, ugly)³⁵. LIWC compared transcribed sound snippets with its embedded dictionary to generate positive and negative emotion scores, indicating levels of verbal communication of positive and negative emotions during social contact. Sound snippets in which participants did not speak corresponded to a score equaled zero for communication of emotions. The scores of expressing emotions were measured 30 seconds out of every 7 minutes and were then aggregated into the 3-hour assessment level (by calculating the average scores) to match EMAs.

Analytic Strategy

First, we examined descriptive statistics and bivariate associations between the key variables. To test the hypotheses, we estimated a series of multilevel models with 3-hour assessments (level 1) nested within participants (level 2). We considered using three-level models with assessments nested within days nested within participants, but three-level models yielded the same pattern as two-level models and were omitted for parsimony. We separated time-varying predictors (i.e., variables on the three-hour assessment level) into person-mean centered variables and person means, in order to isolate the within-person association (i.e., intrapersonal fluctuations within the study period) from the between-person association (i.e., interpersonal differences between participants). All models considered the time of the day (morning, afternoon, evening; assessment level) and participant level age, gender, marital status, racial and ethnic minority status, education, self-rated health, and social network size. All analyses were performed in Stata 17.

We estimated multilevel models to test the associations between mode of contact and verbal communication of emotions (H1). The time-varying predictors were the numbers of in-person and phone contact that participants had during the prior 3 hours. Two separate models were estimated for communication of positive and negative emotions respectively. Random slopes of in-person and phone contact were included in both models.

We then examined the associations between verbal communication of emotions and mood (H2) by estimating multilevel models with communication of positive and negative emotions (LIWC scores) as the time-varying predictors. Communication of positive and negative emotions were entered in the same model to examine their links to mood cohesively. The outcomes were positive and negative mood in two separate models. Random slopes of communication of positive and negative emotions were tested but removed due to insignificant improvement of models. As such, the results we reported were from random intercept only models.

We generated interaction terms between communication of emotions and mode of contact to test how mode of contact may moderate the associations between communication of emotions and mood (H3). The sound snippets themselves did not carry information on the mode of social contact (i.e., social contact information was obtained in the EMA every 3 hours). As such, for this set of analysis specifically, we excluded three-hour assessments in which participants had both in-person and phone contact (22% of total eligible assessments) to ensure the recorded conversation happened during a specific mode of contact (in-person or phone). In-person and phone contact were entered as dummy variables (yes/no) indicating whether participants had each mode or not in prior 3 hours. Because emotional expression and mode of contact are both time-varying variables that were measured on the 3-hour assessment level (level 1), the models considered the within- and between-person components for both variables. The models included the assessment-level interaction terms between emotional expression and social contact, as well as the cross-level interaction between assessment-level emotional expression and participant-level social contact. The outcomes were positive and negative mood in two separate models. Random slopes of mode of social contact (in-person and phone) were included in the model. Equations for models corresponding to all three hypotheses are included in supplementary materials.

On average, participants scored 1.74 (SD = 2.49) and 0.26 (SD = 0.64) on communication of positive and negative emotions respectively. The LIWC-generated scores indicated the levels of communication of emotions, yet they did not represent the exact number of positive or negative words that participants used. Participants’ average scores on positive and negative mood every 3 hours were 3.49 (SD = 0.81) and 1.22 (SD = 0.37) respectively. Out of 4,627 3-hour level assessments, participants reported only in-person or phone contact among 53% and 9% of assessments respectively. They further reported having both modes of contact among 22% and neither among 15% of assessments. Participants had an average of 2.02 (SD = 2.20) in-person and 0.55 (SD = 1.14) phone contact in a 3-hour interval. Table 1 summarizes the descriptive statistics. Supplementary Table 1 shows the bivariate associations between key variables.

Table 1

*Sample Descriptive Information (N = 266)*
	Participants
	M	SD	Range
Age	74.08	6.45	65–90
Self-rated health ^a	3.63	1.00	1–5
	Proportions
Female	.54
Married	.59
Racial/ethnic minority	.24
Education
High school or less	.13
Some college	.28
College or more	.59
Experiences every 3 hours (n = 4,627)
Mood
Positive mood ^b	3.49	0.81	1–5
Negative mood ^c	1.22	0.37	1–4.6
Verbal communication of emotion ^d
Positive emotion	1.74	2.49	0–33.33
Negative emotion	0.26	0.64	0–9.18
Number of social contact ^e
In-person	2.02	2.20	0–16
Phone	0.55	1.14	0–14
Social contact proportions ^f
In-person only	.53
Phone only	.09
Both	.22
Neither	.15
Note. ^a 1(poor), 2 (fair), 3 (good), 4 (very good), and 5 (excellent). ^b Average of content, loved, calm, and proud from 1 (not at all) to 5 (a great deal). ^c Average of nervous/worried, irritated, bored, lonely, and sad from 1 (not at all) to 5 (a great deal). ^d Scores generated by LIWC indicating verbal communication of emotion, merged to three-hour assessments from 104,746 audio files. ^e Number of in-person and phone contact in prior 3 hours. ^f Proportions of 3-hour assessments in which participants reported in-person and phone social contact respectively.

Participants showed considerable intraindividual variability of verbal communication of positive and negative emotions, as well as positive and negative mood, corresponding to intraclass correlation coefficient (ICC) of 0.16, 0.09, 0.75, and 0.54 respectively. Figure 1 demonstrates the intraindividual variability of the communication of positive and negative emotions across the study period.

Mode of Contact and Communication of Emotion

This study focused on intraindividual associations, and all results of the main effects reported in the text are at the within-person level. That is, comparisons of the same person at different points in time. Between-person associations can be found in the tables. Multilevel models showed that more contact in-person (B = 0.23, p < .001, Cohen’s f² = 0.040, 95% CI = [0.18, 0.28]; Fig. 2) and contact by phone (B = 0.17, p < .001, Cohen’s f² = 0.004, 95% CI = [0.10, 0.25]) were associated with more verbal communication of positive emotions. However, in-person contact also was associated with more verbal communication of negative emotions (B = 0.02, p = .001, Cohen’s f² = 0.003, 95% CI = [0.01, 0.03]) whereas phone contact was not (Table 2).

Table 2

*Modes of Social Contact Predicting Verbal Communication of Emotion*
	Positive Emotions ^a				Negative Emotions ^a
	B	p	f²	95% CI	B	p	f²	95% CI
Fixed effects
Intercept	-0.41	.591	–	[-1.89,1.07]	0.38	.019	–	[0.06, 0.70]
Social contact ^b
In person (wp)	0.23	< .001	0.040	[0.18, 0.28]	0.02	.001	0.003	[0.01, 0.03]
Phone (wp)	0.17	< .001	0.004	[0.10, 0.25]	0.01	.173	0.001	[-0.00, 0.04]
In person (bp)	0.30	< .001	0.001	[0.15, 0.44]	0.04	.012	0.000	[0.01, 0.07]
Phone (bp)	0.09	.337	0.000	[-0.09, 0.26]	0.03	.125	0.000	[-0.01, 0.07]
Covariates
Morning (ref.)	–	–	–	–	–	–	–	–
Afternoon (wp)	0.59	< .001	0.009	[0.41, 0.76]	0.10	< .001	0.003	[0.05, 0.14]
Evening (wp)	0.45	< .001	0.004	[0.26, 0.63]	0.06	.022	0.001	[0.01, 0.11]
Age	-0.01	.180	0.000	[-0.04, 0.01]	-0.01	.012	0.001	[-0.01, -0.00]
Female	0.47	.003	0.001	[0.16, 0.78]	-0.01	.682	0.000	[-0.08, 0.05]
Racial/ethnic minority	-0.08	.646	0.000	[-0.43, 0.27]	0.00	.982	0.000	[-0.08, 0.07]
Married	0.04	.803	0.000	[-0.29, 0.38]	-0.06	.081	0.000	[-0.13, 0.01]
High school or less (ref.)	–	–	–	–	–	–	–	–
College	0.27	.252	0.000	[-0.19, 0.72]	0.01	.840	0.000	[-0.09, 0.11]
College graduate and more	0.43	.062	0.000	[-0.02, 0.88]	-0.04	.420	0.000	[-0.14, 0.06]
Health ^c	0.09	.202	0.000	[-0.05, 0.24]	0.01	.475	0.000	[-0.02, 0.04]
Social network size ^d	-0.01	.346	0.000	[-0.03, 0.01]	-0.00	.393	0.000	[-0.01, 0.00]
Random effects
Variances (intercept)	0.06	< .001	–	[0.04, 0.09]	0.00	< .001	–	[0.00, 0.00]
Variances (in-person slope)	0.00	.932	–	[0.00, 0.00]	0.00	< .001	–	[0.00, 0.02]
Variances (phone slope)	0.86	.190	–	[0.68, 1.08]	0.03	< .001	–	[0.02, 0.04]
Variances (residual)	4.68	< .001	–	[4.48, 4.88]	0.37	< .001	–	[0.36, 0.39]
-2 log likelihood	20812.83				8837.78
Number of observations	4631				4631
Note. wp = within-person. bp = between-person. Between-person level effect of time-varying predictors were considered but omitted from the table. All continuous predictors centered on the grand mean. ^a Words usage indicating verbal communication of positive and negative emotions, generated by LIWC. ^b Number of different social contact in the prior 3h. ^c 1 (poor) to 5 (excellent). ^d Number of social partners in the social convoy.

Communication of Emotion, Mode of Contact, and Mood

Higher verbal communication of positive emotions was associated with more positive mood (B = 0.01, p < .001, Cohen’s f² = 0.005, 95% CI = [0.01, 0.02]), but not less negative mood. That is, when individuals expressed more positive words than their own average, they reported more positive mood. Expressing negative emotions was not associated with either positive or negative mood (Table 3).

Table 3

*Verbal Communication of Emotion Predicting Positive and Negative Mood*
	Positive Mood ^a				Negative Mood ^b
	B	p	f²	95% CI	B	p	f²	SE
Fixed effects
Intercept	4.07	< .001	–	[3.14, 5.00]	0.89	< .001	–	[0.53, 1.26]
Communication of emotion ^c
Positive (wp)	0.01	< .001	0.005	[0.01, 0.02]	-0.00	.304	0.000	[-0.01, 0.00]
Negative (wp)	0.01	.142	0.000	[-0.00, 0.03]	-0.00	.855	0.000	[-0.01, 0.01]
Positive (bp)	0.05	.220	0.000	[-0.03, 0.13]	-0.02	.266	0.000	[-0.05, 0.01]
Negative (bp)	-0.35	.062	0.000	[-0.72, 0.02]	0.33	< .001	0.000	[0.18, 0.47]
Covariates
Morning (ref.)	–	–	–	–	–	–	–	–
Afternoon (wp)	0.01	.667	0.000	[-0.02, 0.04]	0.03	.009	0.001	[0.01, 0.05]
Evening (wp)	0.01	.499	0.000	[-0.02, 0.05]	0.01	.177	0.000	[-0.01, 0.04]
Age	-0.00	.456	0.000	[-0.02, 0.01]	-0.00	.666	0.000	[-0.01, 0.00]
Female	-0.01	.911	0.000	[-0.21, 0.19]	-0.01	.800	0.000	[-0.09, 0.07]
Racial/ethnic minority	0.21	.057	0.000	[-0.01, 0.42]	-0.05	.225	0.000	[-0.14, 0.03]
Married	0.11	.285	0.000	[-0.09, 0.30]	0.00	.920	0.000	[-0.07, 0.08]
High school or less (ref.)	–	–	–	–	–	–	–	–
College	0.06	.698	0.000	[-0.23, 0.34]	-0.01	.915	0.000	[-0.12, 0.11]
College graduate and more	-0.16	.271	0.000	[-0.45, 0.13]	0.04	.472	0.000	[-0.07, 0.15]
Health ^d	0.10	.025	0.000	[0.01, 0.19]	-0.07	< .001	0.000	[-0.10, -0.03]
Social network size ^e	0.02	.001	0.000	[0.01, 0.03]	-0.01	.038	0.000	[-0.01, 0.00]
Random effects
Variances (intercept)	0.40	< .001	–	[0.38, 0.54]	1.35	< .001	–	[0.06, 0.08]
Variances (residual)	0.93	< .001	–	[0.15, 0.16]	1.38	< .001	–	[0.06, 0.07]
-2 log likelihood	5443.86				1130.98
Number of observations	4532				4533
Note. wp = within-person. bp = between-person. Between-person level effect of time-varying predictors were considered but omitted from the table. All continuous predictors centered on the grand mean. ^a Average of content, loved, calm, and proud from 1 (not at all) to 5 (a great deal). ^b Average of nervous/worried, irritated, bored, lonely, and sad from 1 (not at all) to 5 (a great deal). ^c Words usage indicating verbal communication of positive and negative emotions, generated by LIWC. ^d 1 (poor) to 5 (excellent). ^e Number of social partners in the social convoy.

The multilevel models involving interaction terms between communication of emotions and mode of contact revealed significant findings. Compared to their personal averages, expressing more positive emotions was associated with more positive mood (B = 0.04, p < .001, Cohen’s f² = 0.003, 95% CI = [0.02, 0.06]). Expressing negative emotions was not associated with either positive or negative mood. The interactions on the 3-hour level were not significant, indicating the associations between verbal communication of emotions and mood did not depend on the mode of social contact. The cross-level interaction between assessment-level (level 1) communication of positive emotions and participant-level (level 2) in-person contact was significant in predicting positive mood (B = -0.04, p = .011, Cohen’s f² = 0.002, 95% CI = [-0.06, -0.01]; Table 4). Simple slopes test showed that participants reported more positive mood when they had more positive communications, and such associations were stronger among participant who had less in-person social contact (B = 0.03, p < .001, 95% CI = [0.02, 0.04]), compared to those who had more social contact on average throughout the study period (B = 0.01, p = .041, 95% CI = [0.00, 0.02]; Fig. 3).

Table 4

*Verbal Communication of Emotion Predicting Positive and Negative Mood, Moderated by Mode of Contact*
	Positive Mood ^a				Negative Mood ^b
	B	p	f²	95% CI	B	p	f²	95% CI
Fixed effects
Intercept	4.12	< .001	–	[3.14, 5.10]	0.95	< .001	–	[0.57, 1.34]
Communication of emotion ^c
Positive (wp)	0.04	< .001	0.003	[0.02, 0.06]	-0.01	.183	0.000	[-0.02, 0.00]
Negative (wp)	0.01	.837	0.000	[-0.06, 0.08]	0.02	.450	0.000	[-0.03, 0.06]
Positive (bp)	0.04	.308	0.000	[-0.04, 0.12]	-0.01	.380	0.000	[-0.04, 0.02]
Negative (bp)	-0.35	.062	0.000	[-0.72, 0.02]	0.33	< .001	0.000	[0.18, 0.47]
Mode of contact ^d
In-Person (wp)	0.04	.006	0.002	[0.01, 0.07]	-0.02	.212	0.001	[-0.04, 0.01]
Phone (wp)	-0.05	.037	0.001	[-0.10, -0.00]	0.03	.130	0.002	[-0.01, 0.07]
In-Person (bp)	0.10	.672	0.000	[-0.35, 0.54]	-0.13	.161	0.000	[-0.30, 0.05]
Phone (bp)	-0.59	.167	0.000	[-1.42, 0.25]	0.06	.739	0.000	[-0.27, 0.38]
Communication of emotion × Mode of contact
Positive (wp) × In-person (wp)	-0.01	.415	0.000	[-0.02, 0.01]	0.00	.618	0.000	[-0.01, 0.01]
Positive (wp) × Phone (wp)	-0.01	.651	0.000	[-0.03, 0.02]	-0.00	.873	0.000	[-0.02, 0.01]
Negative (wp) × In-person (wp)	0.00	.894	0.000	[-0.05, 0.05]	0.01	.610	0.000	[-0.02, 0.04]
Negative (wp) × Phone (wp)	-0.00	.967	0.000	[-0.09, 0.09]	-0.02	.477	0.000	[-0.08, 0.04]
Positive (wp) × In-person (bp)	-0.04	.011	0.002	[-0.06, -0.01]	0.01	.147	0.001	[-0.00, 0.03]
Positive (wp) × Phone (bp)	-0.04	.285	0.000	[-0.11, 0.03]	-0.00	.892	0.000	[-0.05, 0.04]
Negative (wp) × In-person (bp)	0.03	.599	0.000	[-0.07, 0.13]	-0.01	.728	0.000	[-0.08, 0.05]
Negative (wp) × Phone (bp)	-0.12	.353	0.000	[-0.36, 0.13]	-0.14	.082	0.001	[-0.30, 0.02]
Covariates
Morning (ref.)	–	–	–	–	–	–	–	–
Afternoon (wp)	0.01	.620	0.000	[-0.02, 0.04]	0.03	.010	0.001	[0.01, 0.05]
Evening (wp)	0.01	.463	0.000	[-0.02, 0.05]	0.01	.239	0.000	[-0.01, 0.03]
Age	-0.00	.550	0.000	[-0.02, 0.01]	-0.00	.576	0.000	[-0.01, 0.00]
Female	-0.01	.952	0.000	[-0.21, 0.20]	-0.01	.700	0.000	[-0.09, 0.06]
Racial/ethnic minority	0.21	.061	0.000	[-0.01, 0.42]	-0.06	.164	0.000	[-0.15, 0.02]
Married	-0.01	.954	0.000	[-0.25, 0.23]	0.05	.271	0.000	[-0.04, 0.15]
High school or less (ref.)	–	–	–	–	–	–	–	–
College	0.06	.661	0.000	[-0.22, 0.35]	-0.01	.854	0.000	[-0.12, 0.10]
College graduate and more	-0.14	.339	0.000	[-0.44, 0.15]	0.03	.579	0.000	[-0.08, 0.14]
Health ^e	0.10	.033	0.000	[0.01, 0.19]	-0.06	< .001	0.000	[-0.10, -0.03]
Social network size ^f	0.02	< .001	0.000	[0.01, 0.03]	-0.01	.029	0.000	[-0.01, -0.00]
Random effects
Variances (intercept)	0.44	< .001	–	[0.37, 0.53]	0.07	< .001	–	[0.06, 0.08]
Variances (in person)	0.01	< .001	–	[0.00, 0.03]	0.01	< .001	–	[0.01, 0.02]
Variances (phone)	0.00	.973	–	[0.00, 0.00]	0.02	< .001	–	[0.01, 0.03]
Variances (residual)	0.15	< .001	–	[0.15, 0.16]	0.06	< .001	–	[0.06, 0.06]
-2 log likelihood	5410.19				1063.34
Number of observations	4532				4533
Note. wp = within-person. bp = between-person. Between-person level effect of time-varying predictors were considered but omitted from the table. All continuous predictors centered on the grand mean. ^a Average of content, loved, calm, and proud from 1 (not at all) to 5 (a great deal). ^b Average of nervous/worried, irritated, bored, lonely, and sad from 1 (not at all) to 5 (a great deal). ^c Words usage indicating verbal communication of positive and negative emotions, generated by LIWC. ^d Assessments that involved either in-person or phone contact. ^e 1 (poor) to 5 (excellent). ^f Number of social partners in the social convoy.

Sensitivity Analysis

We compared the verbal communication of emotions between in-person and phone contact by limiting analyses to assessments during which participants reported only in-person or phone contact (i.e., excluding assessments with both in-person and phone contact, and neither). A dummy variable for in-person contact was generated and phone contact was entered as the reference group. Compared to phone contact, participants had more verbal communication of positive emotions during in-person contact (B = 0.41, p = .016, Cohen’s f² = 0.002, 95% CI = [0.08, 0.75]), but not negative emotions.

The content of conversations may be influenced by the relationship with the involved social partner. People who are married share more time in-person and may be more likely to share emotions with spouses³⁹. We re-estimated models of the associations between mode of contact and communication of emotions excluding the assessments during which participants encountered their spouse. Results showed the same pattern, such that participants expressed more positive emotions during both in-person and phone contact, yet only in-person contact was associated with expressing more negative emotions, even after excluding contact with romantic partners.

Using an ecologically valid method to capture sound and self-reports of social contact throughout the day, the current study considered verbal communication of positive and negative emotions during in-person and phone contact as well as potential benefits of communicating emotions. Older adults communicated positive emotions during both in-person and phone contact, yet they tended to communicate more negative emotions during in-person contact. Older adults garner emotional benefits from communicating positive emotions, regardless of the mode of contact. Not all older adults have the same opportunity for in-person contact, and the findings also had implications for older adults who typically have less in-person contact. Participants who had less in-person contact on average experienced a greater increase in positive mood when they communicated positive emotions.

Communication of Emotion and Well-being in Late Life

Findings revealed that verbal communication of positive emotions was associated with better mood, yet communication of negative emotions was not associated with better or worse mood. These findings align with the Interpersonal Model of Capitalization which posits that by sharing positive feelings, individuals enhance their positive emotions and derive emotional benefits that extend beyond the original positive events¹⁹. The amplifying effect of sharing positive emotions has been found in previous studies mainly among younger and middle-aged populations⁴⁰. Compared to younger people, older adults tend to prioritize emotional well-being and report better mood⁴¹. This study contributes to the current body of literature by examining older adults’ interpersonal approaches in emotion regulation, highlighting the advantages of sharing positive feelings in their day-to-day experiences.

Interestingly, communicating negative emotions was not associated with either positive or negative mood. Prior studies yield mixed findings and suggest that the emotional outcomes of communicating negative emotions may be complex^43–45; implications of sharing negative emotions depends on the timing of disclosure, characteristics of the negative experience itself, surrounding social context, and social partners’ responses⁴². For example, communicating negative emotions to a social partner was found to be helpful for recent negative events, but not for more distant negative events. Talking about distant negative events may reactivate depressive feelings and lead to ruminations⁴³. Regarding the characteristics of negative events, individuals were more likely to benefit from sharing uncontrollable stressors compared to controllable stressors⁴⁴. Furthermore, some verbalizations of negative emotions may pertain to interpersonal tensions⁴⁵, whereas other such verbalizations may serve the purpose of eliciting social support. In sum, the associations between communicating negative feelings and emotional well-being may be complicated, warranting further studies to examine the link under specific conditions.

Mode of Contact, Communication of Emotion, and Well-being

As hypothesized, older adults communicated more negative mood during in-person contact compared to phone contact; yet contrary to the hypothesis, they communicated similar levels of positive mood during in-person and phone contact. Compared to sharing positive emotions, disclosing negative emotions requires higher levels of mutual understanding and stronger interindividual bonds¹. Older adults may perceive in-person as a better modality for sharing negative feelings that encompasses multiple forms of information and provides opportunities for social support and active response. A study observed aging couples’ discussions and found that caring behaviors, mutual understanding, and active response appeared to protect them from emotional distress⁴⁶. In sum, although older adults share positive emotions through both in-person and phone contact, it may be important for individuals to have in-person outlets and receive social support in-person when negative events happen^1,47. Our findings underscore the potentially irreplaceable role of in-person contact in conveying negative feelings, building deeper social ties, and promoting well-being in older adults’ daily lives.

Regarding the emotional benefits from different modes of social contact, contrary to our prediction that the emotional benefit of communicating positive emotions would be stronger during in-person contact, the association between verbal communication of positive emotions and better mood held robust across modes of contact when examined every 3 hours throughout the day. This finding suggests that the beneficial effect of communicating positive mood may go beyond the modality of social contact and the availability of information cues. In the process of amplifying positive experiences, verbal communication with social partners may already be sufficient to boost positive mood¹⁹. Additionally, we found that the people who had less in-person contact on average benefited more from verbal communication of positive emotions (i.e., experience a larger boost in positive mood), compared to those who had more in-person contact. This was the case, even accounting for marital status. Although people who had less in-person contact reported lower positive mood in general, communicating positive emotions may strengthen social connections and help them achieve better mood overall²⁰. Findings highlight the importance of in-person contact, and also suggest that when in-person contact is not accessible, communicating positive feelings via other modalities may provide older adults emotional benefits⁴⁸.

Disclosing negative emotions was not associated with mood regardless of the mode of social contact. Older adults had more verbal communication of negative emotion during in-person contact compared to when they had no contact, yet this association was not observed during phone contact, suggesting older adults may prefer communicating negative emotion during in-person contact rather than phone contact. In person contact may create venues for better social support and more active reactions, yet in the current study, older adults did not seem to benefit emotionally from talking about negative feelings.

As previously mentioned, additional factors may contribute to the effectiveness and emotional benefits associated with expressing negative mood (e.g., social expectation, social partners’ response strategy, personality)⁴³. For example, one study found that when participants did not perceive that other people expected them to be sad, they reported greater levels of sadness⁴⁹, highlighting the impact of social expectation on emotional communication to social partners. Future studies may consider these intrapersonal, interpersonal, and contextual factors when examining negative emotional expression via different modes of contact in late life.

Limitations and Future Directions

The current study measured participants’ verbal communication of emotions and mood every three hours throughout the day. This study broke new ground in important ways by collecting such a large sample of sound files and providing information about social contact every three-hours, this study did not allow us to detect if a specific conversation happened in-person or by phone. We excluded three-hour intervals in which participants indicated they had both in-person and phone contact to examine independent effects of each mode of contact. Future studies may consider study designs (e.g., event-contingent methods where people provide self-reports when the events actually occur) to examine the emotional communication in each mode of contact as it occurs.

We did not find associations between verbal communication of negative emotions and mood. Yet, the fact that older adults did not report worse mood after discussing negative events may indicate that interpersonal communication helps to alleviate negative mood. Using an event-contingent design that closely tracks individuals’ interpersonal behaviors following specific events may help illuminate such associations.

Furthermore, we studied participants’ verbal communication of emotions by using linguistic features extracted by LIWC. Future studies may utilize other approaches to examine specific aspects of daily conversations. For example, dyadic data may offer insights into conversation dynamics, support exchange, and social partners’ feedback⁵¹. Turn-level datasets (i.e., separating individuals’ speaking to multiple segments) may be appropriate for investigating conversational behaviors⁵², though doing so in a naturalistic context introduces issues of practicality of obtaining consent and ethical considerations of use of data. Additionally, applying natural language processing algorithms for sentiment analysis may yield information on linguistic features and individuals’ emotional states⁵³.

In sum, this study pushes the field forward by examining older adults’ verbal communication with social partners in naturalistic contexts in daily life where they occur. By integrating these data with self-reports of social contact and mood we were able to gain insights into communication of emotions in different modes of contact. Analysis on sound snippets revealed that older adults tended to share positive experiences through both in-person and phone contact, however, they were more likely to communicate negative emotions in-person. Sharing positive emotions during in-person and phone contact was associated with better mood, yet sharing negative emotions was not associated with either positive or negative mood. To conclude, in-person contact may allow older adults to communicate more complex emotions, and phone contact may be suited for simpler communications, discussing positive events, but not negative ones.

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Mode of Social Contact, Verbal Communication of Emotion, and Well-Being in Late Life

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Abstract

Figures

Introduction

Mode of Contact and Communication of Emotion

Benefits of Verbal Communication of Emotion

The Current Study and Other Factors Associated with Communication of Emotion

Methods

Samples and Procedures

Baseline Interview Measures

Social Partners

Participants Characteristics

EMA Measures

Social Contact

Positive and Negative Mood

Assessment-Level Covariates

Electronically Activated Recorder (EAR) Measurement

Verbal Communication of Positive and Negative Emotions

Analytic Strategy

Results

Mode of Contact and Communication of Emotion

Communication of Emotion, Mode of Contact, and Mood

Sensitivity Analysis

Discussion

Communication of Emotion and Well-being in Late Life

Mode of Contact, Communication of Emotion, and Well-being

Limitations and Future Directions

References

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