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EMPIRICAL ARTICLE
Staying connected during stay-at-home: Communication with
family and friends and its association with well-being
Genavee Brown
1
| Patricia M. Greenfield
2
1
Department of Psychology, Northumbria
University, Newcastle upon Tyne, UK
2
Department of Psychology, University of
California, Los Angeles, California
Correspondence
Genavee Brown, Department of Psychology,
Northumbria University, Newcastle upon
Tyne, UK.
Email: genavee.brown@northumbria.ac.uk
Abstract
COVID-19 and the resulting stay-at-home orders issued to reduce the spread of the
virus created a novel social situation in which people could not spend in-person time
with their family and friends. Thus, emerging technologies like video calling and other
forms of mediated communication like voice calling and text messaging became
important resources for people to stay in touch. The purpose of this study was three-
fold. First, we wanted to test whether people would use more mediated communica-
tion (video calls, voice calls, text messaging) to stay in touch during the stay-at-home
order. Second, we wanted to see if increased mediated communication would be
positively associated with well-being. Finally, we explored whether mediated commu-
nication was related to age. To answer these questions, we surveyed 2092 partici-
pants who answered questions online about how their use of video calls, voice calls,
and text messaging and their well-being had changed since the stay-at-home order.
Our results show that people increased their use of mediated communication, partic-
ularly video calling; and increases in mediated communication with close others, par-
ticularly friends, was related to higher levels of well-being. Finally, we found that age
was related only to the use of video calling; younger people tended to use more
video calling. These findings support the compensatory theory of technology use,
that people use technologically mediated communication to maintain contact with
their close friends and family when in-person contact is not possible, and that this
form of contact, when in-person interaction is unavailable, is associated with positive
outcomes.
KEYWORDS
age, close relationships, COVID-19, emotions, mediated communication, social isolation, text
messages, video calls, voice calls, well-being
1|INTRODUCTION
The COVID-19 pandemic has led to extreme changes in daily life due
to the need to avoid physical contact with other human beings in
order to prevent the spread of the virus. Governments around the
world made the difficult decision to order their populations to isolate
in their homes and avoid going out to see other people. These
extreme restrictions led to a loss of in-person contact with family or
friends who did not live in the same residence. We know that humans
are social beings, are hardwired to crave contact with others, and
indeed feel unfulfilled without it (Baumeister & Leary, 1995; Ryan &
Deci, 2017).
Even more troubling in the context of COVID-19 stay-at-home
orders is the fact that it was a period of extreme stress and one main
coping mechanism for dealing with stress is receiving social support
from others (Cohen & Wills, 1985). Fortunately, technology provided
multiple avenues for staying connected during the stay-at-home
order. Individuals with a mobile phone and an Internet connection or
Received: 14 August 2020 Revised: 9 November 2020 Accepted: 14 November 2020
DOI: 10.1002/hbe2.246
Hum Behav & Emerg Tech. 2021;3:147–156. wileyonlinelibrary.com/journal/hbe2 © 2021 Wiley Periodicals LLC 147
cellular data could use video calls, telephone calls, and text-based
messaging in the form of texts, emails, or Instant Messages via differ-
ent applications (WhatsApp, Facebook Messenger, etc.) to contact
family and friends.
The question in the current study was threefold: First, would indi-
viduals increase their usage of these technologies to maintain contact
with family and friends when they could not see them in-person? Sec-
ond, would using these avenues to stay in touch be beneficial for their
psychological well-being? Third, would age be associated with using
different types of mediated communication? We hope that answers
to these questions will shed light on how humans creatively combat
the social isolation created by COVID-19.
1.1 |Stimulation, displacement, or compensation?
In the early 2000s research on communication technologies centered
on resolving the question of whether online communication stimu-
lated (i.e., increased) or displaced (i.e., decreased) in-person contact
with others (Valkenburg & Peter, 2007). In general, these studies
tended to show that greater amounts of online communication were
associated with greater in-person contact. However, one flaw in this
comparison between stimulation versus displacement in cross-
sectional studies or even short longitudinal studies, is that they do not
take into account the changing societal context that has accompanied
increases in communication technology use. Sociological and psycho-
logical studies show that people are spending less time in the physical
company of others across the lifespan than they did previously. For
example, in adolescence, relatively recent concerns about safety have
meant that American adolescents are allowed less freedom to see fri-
ends in person (boyd, 2014). Concerning adults, authors have also
noted that internal migration in the U.S. is frequent, and people no
longer live their entire lives in the same town, making frequent in-
person communication impossible (Molloy, Smith, & Wozniak, 2011).
Even if or when people settle in a location, there seems to be
decreased investment in democratic life, including decreased in-
person contact with others, such as in bowling leagues
(Putnam, 2000). Finally, the lack of multigenerational living in the
United States has also led to a larger percentage of elderly people
feeling isolated and lonely (Cohen-Mansfield, Hazan, Lerman, &
Shalom, 2016). Taken together, this research shows that people were
already spending less in-person time with others before COVID-19
caused stay-at-home orders to be issued.
Some research suggests that computer-mediated communication
has become a way to compensate for this lack of in-person communi-
cation. For example, in a recent daily diary study, researchers found
that adolescents were spending more time communicating online with
friends on days they did not see them in person (Manago, Brown,
Lawley, & Anderson, 2019). This finding suggests that teens are
substituting computer-mediated communication for in-person com-
munication when it is not possible to hang out with friends in person.
Additionally, young adults attending university have been found to
use computer-mediated communication to stay in touch with friends
from high school when seeing them frequently in-person is not possi-
ble (Brown & Michinov, 2017; Yang & Brown, 2013). Furthermore,
Chinese international students use technology to stay in touch with
both family and friends when they move to the U.S. and visiting home
is not feasible (Cemalcilar, Falbo, & Stapleton, 2005; Kline &
Liu, 2005). Adults also use technology to stay in touch with their close
ties when in-person contact is not possible. For example, immigrants
report maintaining family relationships in their countries of origin
through technology (Chen & Choi, 2011). Finally, older adults who
may be unable to get out to see family and friends, use technology
such as video and voice chat to stay in touch (Xie, 2008; Zamir,
Hennessy, Taylor, & Jones, 2018).
The current context provides us with the opportunity to observe
whether people will increase their mediated communication to main-
tain contact with family and friends when a governmental stay-at-
home order almost completely prevents in-person contact. We
hypothesized that a large portion of the population would engage in
more mediated communication than they did before the stay-at-home
orders were issued as a way to compensate for decreased in-person
contact. Because women engage in more mediated communication
than men (Kimbrough, Guadagno, Muscanell, & Dill, 2013), we have
explored this issue separately for each gender, as well as for the sam-
ple as a whole.
We acknowledge, however, that certain aspects of this study are
exploratory and therefore make no specific predictions about the
types of mediated communication that individuals may prefer to use,
or whether there will be differences in the amounts of mediated com-
munication used with family versus friends. We will however investi-
gate these differences in order to explore people's communication
preferences when in-person contact is not possible.
1.2 |Computer-mediated communication with
close ties: Association with well-being
People need close bonds with family and friends to help maintain their
happiness and self-esteem (Baumeister & Leary, 1995). Close bonds
are maintained through communication (Hartup & Stevens, 1999;
Segrin & Flora, 2005). Typically, elements of communication that are
key to developing emotional closeness, such as self-disclosure, emo-
tion sharing, and offering social support, have been studied in con-
texts where people are in the same physical space. Close ties may be
especially important in the current crisis as individuals may need extra
emotional and instrumental social support during this stressful period
(Taylor et al., 2020; WHO, 2020); but, due to the stay-at-home order,
individuals can only access social support through technological
means. Fortunately, some research suggests that online communica-
tion can provide social support and is associated with positive well-
being.
The positive effects of computer-mediated communication on
well-being have been demonstrated across the lifespan. Starting in
adolescence, teens who use computer-mediated communication to
fulfill their relational needs (Ang, Talib, Tan, Tan, & Yaacob, 2015) and
148 BROWN AND GREENFIELD
improve friendship quality (Valkenburg & Peter, 2007) tend to have
greater satisfaction with life. Young adults at university who engaged
in more self-disclosure through online communication had higher sat-
isfaction with life (Schiffrin, Edelman, Falkenstern, & Stewart, 2010).
In a random community sample of adults aged 18–70, researchers
found that using more communication modalities, such as in-person
conversations, phone calls, video calls, texting, and email, with family
and friends was associated with greater well-being (Chan, 2015).
Finally, in a qualitative study of older adults who used chat rooms and
online voice calls to stay in touch with friends, researchers found that
they felt less lonely and received greater social support (Xie, 2008).
Thus, we hypothesized that individuals who use more mediated com-
munication with friends and family during the stay-at-home orders
would experience greater satisfaction with life, more positive emo-
tions, and fewer negative emotions. We made no specific predictions
about whether communication with friends or family would be more
beneficial to well-being, but planned to test them in the same model
to see if they are equally beneficial for well-being.
1.3 |Current study
In order to answer our research questions, we recruited participants
from two U.S. states: California and Rhode Island. In both states, resi-
dents had lived under a stay-at-home order for 34 days when the sur-
vey began; in both states; residents were still under stay-at-home
orders 7 days later when the survey ended. We used an online survey
to collect data on individuals' use of video calls, phone calls, and text
messages to stay in touch with family and friends. We also measured
shifts in satisfaction with life, positive emotions, and negative emo-
tions during COVID-19 as measures of well-being. Our hypotheses
and questions fell into three areas:
1. We hypothesized that individuals would use more mediated com-
munication with both family and friends during the stay-at-home
order than they did before the order. We explored whether this
predicted increase would take place in all media types: phone
calls, video calls, and text messages or would be concentrated in
the new, emerging media of video and text. We also explored
whether individuals would tend to be consistent across media
types, such that increased use would take place in all types of
communication, or whether individuals would tend to be selective,
increasing their use of one particular communication medium, but
not others.
2. We hypothesized that greater use of mediated communication
with family and friends during the stay-at-home order would be
associated with greater well-being. We also explored whether
communicating with family or friends would have a greater con-
nection to well-being.
3. We explored age effects: Would older adults increase their use of
the phone calls, an older technology? Would younger adults
increase their use of video and text-based communication, newer
technologies?
2|METHOD
2.1 |Participants
We recruited 2092 participants (M
age
= 59.15, SD
age
= 13.56) com-
posed of 476 men, 1,583 women, 29 participants who self-identified
as other genders, and 4 with unreported gender. One reason for this
gender imbalance is that we recruited participants via Facebook and a
higher percentage of American women use Facebook (83%), than
American men (75%) (Greenwood, Perrin, & Duggan, 2016).
Participants were recruited from two states in the U.S., California
(n= 1,137) and Rhode Island (n= 955). They were recruited using
Facebook advertisements with links to the survey.
Our aim was to control for the time after the stay-at-home order
was issued; and since these orders were issued by state, we recruited
from each state individually. Participants had been under stay-at-
home orders a little more than a month (34 days) when the survey
began; it was available for a week in each state. We hoped that this
amount of time would have allowed participants to settle into their
new patterns of living during the stay-at-home order and to have
developed new patterns of communication. In California, data collec-
tion took place from April 22 to April 29, 2020. In Rhode Island data
collection took place from May 1 through May 8, 2020. Ninety-two
percent of participants reported complying with the stay-at-home
order and those who respected the order were at home for an aver-
age of 41.87 days (SD = 13.13) at the time of the survey. Our sample
was mainly composed of European Americans (80.4%) with small per-
centages of LatinX (2.2%), African American (1.1%), Asian American
(1.8%), Native American (1%), and Pacific Islander (0.3%) participants.
11.5% identified as "other;"1.7% did not respond.
2.2 |Procedure
Participants were asked to participate in a study about how their lives
had changed since the coronavirus outbreak and the stay-at-home
order. If participants, clicked on the link, they were directed to Qualtrics,
presented with further information about the study, and asked for
informed consent to participate. The survey instrument included ques-
tions on the types of communication people use to stay in touch with
family and friends during the stay-at-home order and questions about
their emotions and satisfaction with life during the stay-at-home order.
Finally, participants were asked demographic questions. This study was
given ethical approval by the IRB at UCLA. All participants gave
informed consent before taking part in the current research project.
3|MEASURES
3.1 |Communication with family and friends
There were six mediated communication questions, three concerning
communication with family and three concerning communication with
BROWN AND GREENFIELD 149
friends. Participants first read the prompt, “The following questions
are about how the type of communication you now use with your
(family/friends) living outside of your household has changed since
the stay-at-home order.”Participants were then asked if the amount
of time they spend communicating with them via phone calls, video
calls, and textual messages, had changed. For example, “Phone calls
have become…”Possible answer choices were less frequent, no change,
more frequent. We coded the response less frequent as −1, no change
as 0, and more frequent as +1. For each participant, answers on the
phone call, video call, and textual message items were summed to cre-
ate a composite variable for family and friends separately. Scores
could range from −3 (decrease in all three media) to +3 (increase in all
three media). Positive scores indicate an increase since coronavirus
and stay-at-home; negative scores indicate a decrease. Because plus
and minus signs were used in calculating shifts, these scores indicate
net change. For example, a decrease in phone communication (−1),
along with an increase in video calls (+1) and texting (+1) would sum
to +1. Means for the sample show that mediated communication with
family (M = 1.49, SD = 1.32) and mediated communication with fri-
ends (M = 1.24, SD = 1.37) were above zero which indicates a net
increase.
3.2 |Satisfaction with life
Satisfaction with life (SWL) was measured with one item, “Compared
with before coronavirus, my life since the stay-at-home order is...”
Response options were more satisfying, equally satisfying, less satisfy-
ing. More satisfying was coded as +1, equally satisfying as 0, and less
satisfying as −1. Single item measures of SWL are commonly used in
the literature and have been shown to be equally reliable and as valid
as measures with more items (Cheung & Lucas, 2014).
3.3 |Positive and negative emotions
Participants were presented with the following emotion-relevant
questions. For each emotion, they were asked to compare how they
felt before coronavirus with how they were now feeling during the
time of coronavirus and the stay-at-home order:
Compared with before coronavirus, is your life since “stay at home”
(Check all that apply)
i. Calmer.
ii. More anxiety-provoking.
iii. More depressing.
iv. More lonely.
Compared with before coronavirus, I have become (check all that
apply)
i. More peaceful.
ii. More content.
iii. More frazzled and distracted.
In these two emotion lists, there were three positive emotions
(calm, peaceful, content) and four negative emotions (anxious,
depressed, lonely, and frazzled/distracted).
The positive-emotion score consisted of the number of positive
emotions out of three for which a participant reported an increase
since coronavirus; hence, the possible range of individual scores was
zero to three. The mean number of positive emotions for which the
sample reported an increase was 0.75 (SD = 01.05). This mean signifies
that, on average, three-quarters of the total sample reported experienc-
ing a net increase in one positive emotion each during coronavirus.
The negative emotion score consisted of the number of negative
emotions out of four for which a participant reported an increase
since coronavirus; hence, the possible range of individual scores was
zero to four. The mean number of negative emotions for which the
total sample reported an increase was 1.03 (SD = 0.95). This mean sig-
nifies that, on average, sample participants reported experiencing a
net increase in about one negative emotion each during coronavirus.
3.4 |Demographics
We asked participants to report several demographic variables includ-
ing age, gender, and ethnicity. We also asked them to report if they
had been adhering to the stay-at-home order in their state and if so,
for how many days they had been at home.
3.5 |Data analysis
Due to the large sample size in our study, we have chosen to
set alpha at a conservative .001 level. To examine differences in medi-
ated communication before and during the pandemic, we use one-
sample ttests and test the significance of change against zero
(no change). To examine associations between usage of video calls,
phone calls, and textual messages, we use chi-square tests. In order to
examine differences between mediated communication with friends
and family, we conduct a paired-samples ttest. To examine the rela-
tionship between mediated communication and age we use Pearson
correlations. For all of these statistics, we also report effect sizes. To
examine the association between mediated communication and the
well-being variables, we use the composite communication variables
to predict well-being indicators with multiple regression analyses.
4|RESULTS
4.1 |Communication changes during stay-at-home
order
Seventy-nine percent of people reported increasing at least one form of
mediated communication with family; 76% reported increasing at least
150 BROWN AND GREENFIELD
one form of mediated communication with friends. Both men and
women showed the same pattern: 69.6% of men and 83.2% of women
increased at least one form of mediated communication with family;
64% of men and 79.6% women increased at least one form of mediated
communication with friends. Chi-square tests indicated that more
women than men increased communication with family (χ
2
[1] = 42.733,
p< .001) and with friends (χ
2
[1] = 48.338. p<.001); but effect sizes for
these gender differences were small (family: Φ= .14; friends: Φ=.15)
We ran one-sample ttests for each of the six communication
items with 0, no change, as the test value. We found that all types of
communication with both family and friends increased significantly
during the stay home order. Phone use with friends was the type of
communication that increased the least. For both friends and family,
textual communication increased the most compared with the other
types of communication. Effect sizes for all tests were large (Cohen,
1998). ttest values, effect sizes, and pvalues are reported in Table 1.
We carried out the same statistical analyses separately for men and
women. The pattern of results was the same for both genders: with
both family and friends, mediated communication in all modalities had
increased for both men and women, p< .001.
We were also interested in knowing whether people who
increased one form of computer mediated communication would also
increase other forms of mediated communication. To examine this
question, we ran two three-dimensional chi-square tests examining
the relationship between phone calls, video calls, and textual commu-
nication. One test examined this issue with respect to communicating
with family; the other test examined this issue with respect to com-
municating with friends. For both family and friends, the chi-square
values were highly significant (family: χ
2
(4) = 656.109, p< .001; fri-
ends: χ
2
(4) = 757.298, p< .001). Effect sizes were medium (family:
Φ= .56; friends: Φ= .60.)
The significant chi-square values indicated consistency in
response to stay-at-home across communication types. An examina-
tion of the italicized figures in Table 2 shows that people who
increased one type of mediated communication with family members
also tended to increase the other types as well. Similarly, people who
decreased one type of mediated communication also tended to
decrease the other types; and people who did not change their use
of one type of mediated communication tended to not change
their use of other types. We found a similar pattern for mediated
communication with friends. This pattern is demonstrated in the
-italicized figures in Table 3.
4.2 |Mediated communication and well-being
To explore the relationship between well-being and communication
we conducted Pearson's correlations on shifts in the three well-being
variables (SWL, positive emotions, and negative emotions) and shifts
in the composite communication variables for family and friends (com-
bining all three types of communication: phone, text, and video calls).
The bivariate Pearson's correlations reported in Table 4 show that
increased communication with both family and friends is positively
correlated with increased life satisfaction and augmented positive
emotions during coronavirus. There is no correlation between nega-
tive emotional shift and communication with family or friends. In
order to examine whether increased mediated communication with
family or friends was more important for well-being, we ran two
regressions on the indicators of well-being that were significantly cor-
related with communication: increased satisfaction with life (SWL)
and increased positive emotions experienced during the stay-at-home
order. The predictors were the composite variables for communica-
tion with family and with friends.
Concerning satisfaction with life during the stay-at-home order,
we found that model fit with the two predictors was significant, F
(2,1966) = 13.959, p< .001. Including shifts in mediated communica-
tion with friends and with family in the model explained 1.4% of the
variance in changing satisfaction with life. Examining the individual
predictors, we found that an increase in mediated communication
with family did not significantly predict increased satisfaction with life,
but an increase in mediated communication with friends was posi-
tively associated with increased satisfaction with life, β= .104,
t= 3.713, p< .001. For changes in positive emotion experienced dur-
ing the stay-at-home order, we found a similar pattern. Model fit with
the two predictors was significant, F(2,2005) = 21.592, p< .001. The
mediated communication with family and friends explained 2.1% of
the variance in positive emotion change during the pandemic. Only an
increase in mediated communication with friends was a significant
predictor in the equation, β= .122, t= 4.401, p< .001. In summary,
increased levels of mediated communication with friends during the
TABLE 1 One-sample ttests on
mean net change in the different types of
mediated communication for family and
friends
t-value df Mean SD Cohen's D
Family
Video calling 41.533 2058 0.511 0.559 0.914
Phone 30.691 2062 0.429 0.634 0.677
Text 44.337 2061 0.551 0.564 0.977
Friends
Video calling 32.919 2066 0.419 0.579 0.724
Phone 22.136 2068 0.306 0.629 0.486
Text 39.969 2072 0.517 0.589 0.878
Note: For all ttests, p< .001.
BROWN AND GREENFIELD 151
stay-at-home order were associated with increases in life satisfaction
and increases in positive emotions during the pandemic. Negative
emotional shifts were not associated with changes in mediated com-
munication with family or friends.
4.3 |Age and shifts in mediated communication
during stay-at-home
We tested the relationship between age and the use of different com-
munication media with friends and family, using Pearson's correla-
tions. As expected, age was negatively associated with the use of
video calls for communicating with both family (r=−.115, p< .001)
and friends (r=−.118, p< .001). This finding suggests that the youn-
ger participants were, the more frequently they tended to increase
their use of video calls to stay in touch during the stay-at-home
orders; however, effect size is small. Contrary to our prediction that
older participants would augment their use of voice calls during coro-
navirus and stay-at-home more than younger participants, age was
not associated with shifts in using traditional voice calls to stay in
touch with family and friends during stay-at-home. Changes in text
messaging with friends and family were also not significantly corre-
lated with age, indicating that people of all ages changed their use of
texting in similar ways during the stay-at-home order.
5|DISCUSSION
Our study surveyed a large sample of participants from two different
U.S. states a little over a month into the stay-at-home order. We
found that voice calls, video calls, and text-based messages increased
with friends and family during the stay-at-home order. The pattern
held for both genders, although it was slightly stronger for women.
We also found that participants who increased one form of mediated
communication tended to increase their use of the other forms of
mediated communication. Additionally, we found that an increase in
mediated communication with both family and friends was beneficial
for well-being, but that an increase in mediated communication with
friends was the more important factor. Interestingly, we found that
while younger participants increased their use of video calls more
than older ones, there was no association between age and voice calls
or text messages.
5.1 |Increased use of mediated communication for
relationship maintenance
We found that most of our participants (92%) were respecting the
stay-at-home order which meant that they could not have in-person
contact with family and friends outside of household members. Fortu-
nately, many people adapted to this situation by increasing their tech-
nology usage. Indeed, our results showed that people increased their
use of voice and video calls and text-based messages, although for
both family and friends phone calls increased the least. Perhaps this is
because if one has the time and capability to make a phone call on a
mobile phone, they could also use a video call. Video calls may be pre-
ferred because they offer richer cues. Indeed, video calls are the clos-
est form of communication to in-person conversations because many
of the elements of in-person communication such as body language
TABLE 2 Cross-tab chart of mediated communication with family
Video calls
Phone calls Less No change More
Less texting Less 28 10 6
No change 3 9 1
More 1 2 13
No change texting Less 5 13 14
No change 3 371 137
More 1 91 134
More texting Less 17 15 53
No change 2 145 174
More 4 214 570
Note: Numbers in bold are the participants who reported less of all
mediated communication types, no change in all mediated communication
types, or more of all mediated communication types.
TABLE 3 Cross-tab chart of mediated communication with
friends
Video calls
Phone calls Less No change More
Less texting Less 51 97
No change 0 13 6
More 1 2 10
No change texting Less 7 21 9
No change 6 451 145
More 0 75 76
More texting Less 17 20 46
No change 3 209 216
More 10 200 438
Note: Numbers in bold are the participants who reported less of all
mediated communication types, no change in all mediated communication
types, or more of all mediated communication types.
TABLE 4 Pearson correlations between mediated communication
and well-being variables
12 3 4
1 MC with family –
2 MC with friends .601* –
3 SWL .080* .118* –
4 positive emotions .106* .142* .529* –
5 negative emotions .030 −.028 −.435* −.486*
Abbreviations: MC, mediated communication; SWL, satisfaction with life.
*p< .001.
152 BROWN AND GREENFIELD
and facial expressions are present in video calls. Furthermore, video
calls have been found to promote more bonding between friends than
voice calls or text messages (Sherman, Michikyan, & Greenfield, 2013).
Interestingly, although video calls may be a preferred method of
communication when in-person conversations are not possible, peo-
ple still increased their use of voice calls and text-based messages.
Indeed, we found that people who increased one form of mediated
communication were also likely to also increase their use of other
forms of mediated communication. This finding is an example of
media multiplexity theory which suggests that people who are emo-
tionally close tend to use multiple communication channels for staying
in touch with one another (Haythornthwaite, 2005). For example, fri-
ends might text to organize a lunch together, interact in-person during
the lunch, and post pictures of their lunch on social media and com-
ment on them later. Thus, since we asked specifically about close rela-
tionships, it is perhaps unsurprising that people tended to use multiple
forms of mediated communication to stay in touch.
Our findings also provide novel evidence for the compensatory
hypothesis of mediated communication use: that individuals use medi-
ated communication as a substitute when in-person interaction is not
possible. The novelty of our study is that it is a natural experiment
where a large proportion of the population was restricted from seeing
their family and friends in-person. Under this condition, people
increased their use of technology in order to stay in touch with their
close ties and this had important implications for well-being. Further
study needs to be conducted to examine the compensatory hypothe-
sis, but some evidence already exists that when people cannot see
each other in person due to immigration (Chen & Choi, 2011), study
abroad (Cemalcilar et al., 2005; Kline & Liu, 2005), or parental restric-
tions on movement (Manago et al., 2019) they adopt mediated com-
munication as an important tool for staying in touch. One way to test
the hypothesis, would be to look for reductions in mediated communi-
cation once the COVID-19 crisis has subsided and people can move
about freely and interact in person with friends and family.
5.2 |Mediated communication and well-being
Overall, we found that an increase in mediated communication was
positively related to increases in two indicators of well-being: satisfac-
tion with life and positive emotions. This finding mirrors work in the
offline communications literature showing that having numerous
social contacts, more social capital, and more social interactions con-
tribute to well-being and happiness (Cacioppo, Hawkley, &
Thisted, 2010; Diener & Seligman, 2002; Rodríguez-Pose & Von
Berlepsch, 2014). Research on computer-mediated communication
conducted outside of the pandemic also tends to show positive
effects of computer-mediated communication with friends and family
(Manago et al., 2019; Shen et al., 2017; Valkenburg & Peter, 2007).
Our results are also supported by another research project conducted
in the U.S. during COVID-19 showing that feelings of relatedness
were positively associated with well-being and lower levels of stress
(Cantarero, Tilburg, & Smoktunowicz, 2020); however, these
researchers only asked about perceptions of relatedness, not the
methods of communication people were using to stay in touch with
others. Our study is novel in its large sample size from two U.S. states
and measurement of use of mediated communication with friends and
family rather than global measures of relatedness.
Interestingly we found no relationship of changes in mediated
communication with shifts in negative emotions. Shifts in mediated
communication were not associated with increases or decreases in
negative emotions. There are several possible explanations for this.
One is that negative emotions may promote seeking out social sup-
port (Barbee & Cunningham, 1995); but once this social support is
obtained, then negative emotions decrease (Burleson, 1990;
Leatham & Duck, 1990). Thus, the relationship between increased
negative emotions and mediated communication would be positive at
the beginning of this cycle with more negative emotion leading to
more mediated communication with the goal of obtaining social sup-
port. Once the support was obtained the association between medi-
ated communication and negative emotions would be reversed, more
mediated communication would be associated with decreases in nega-
tive emotion. Thus, we may have had participants at different stages
in this process which made the effect average out overall. Another
possible explanation is that negative emotions from the situation sur-
rounding COVID-19 were so strongly tied to external factors (worries
about economic and health insecurity) that social support provided by
family or friends through mediated communication would not be able
to alleviate these negative emotions. Interestingly a previous longitu-
dinal study on disaster victims of the Mount St. Helens volcanic erup-
tion found that social support 1 year after the disaster did not
decrease distress felt by the victims 3 years after the event
(Murphy, 1988). Thus, negative emotions tied to extreme, external,
uncontrollable events, may not be responsive to the provision of
social support, however, more study is required to examine specifi-
cally which types of negative emotion and under what conditions.
Increases in mediated communication with both friends and fam-
ily were positively associated with increased well-being; however,
increases in mediated communication with friends were more strongly
related to increases in well-being than increases in mediated commu-
nication with family. There is some evidence that supports this finding
in the literature. For example, a large, multicounty survey study
showed that frequent in-person interactions with friends were more
strongly positively correlated with well-being than in-person interac-
tion with family (Helliwell & Putnam, 2004). Similarly, in a study on
retirees, researchers found that, although family members provide the
majority of social support for older adults, friendships have a stronger
influence on well-being (Larson, Mannell, & Zuzanek, 1986). There
may be several reasons why friends provide more effective social sup-
port and contribute more to well-being than family. First, as the adage
goes, you can pick your friends but not your family. Thus, negative
relationships with family may be maintained while unfulfilling friend-
ships can be discontinued (Pinquart & Sörensen, 2000). Second,
friendship interactions seem to be qualitatively different from family
interactions, with friends providing an escape from discussions of
daily needs and positive feedback that family members may not
BROWN AND GREENFIELD 153
provide (Larson et al., 1986). Finally, some research suggests that sup-
port from family may be more stable over time and therefore have
less impact in times of stress whereas support from friends may
increase during periods of stress (Dahlem, Zimet, & Walker, 1991;
Zimet, Dahlem, Zimet, & Farley, 1988). Governments as well as mental
health practitioners may want to consider promoting more online
communication between friends as a way for individuals to maintain
their psychological well-being during periods of social or physical
isolation.
5.3 |Age and mediated communication
Younger age was associated with increased video calling during the
stay-at-home order. Phone calls did not have any relationship with
age. Additionally, texting was not associated with age. One reason
that text messaging and age may not be related is because texting is
an accessible form of communication to older adults. While video call-
ing may require learning new skills and also may be difficult for hear-
ing impaired older individuals (Zamir et al., 2018), text messaging,
whether via a computer or phone, is more accessible. For older adults
who are visually impaired, they can enlarge text to make it easier to
read and for those who are hearing impaired, reading text may be eas-
ier than communicating via video calls or phone calls. Furthermore,
many seniors still do not use smartphones which can facilitate video
calls, but more of them do have home Internet access to send text
messages via a computer (Anderson & Perrin, 2017). Thus, different
types of mediated communication may be preferred by different age
groups due to their accessibility.
5.4 |Limitations and future directions
One limitation of our study is that the effect sizes on well-being vari-
ables that we found were small. In other words, increases in mediated
communication with friends and family only explained a small amount
of the observed variability in shifts in satisfaction with life and in posi-
tive emotions. However, any improvement in people's lives and emo-
tions during a period of confinement due to COVID-19 or any other
reason, should be considered important, particularly when the behav-
iors in this case (mediated communication) were so easy to engage
with and relatively cost effective as long as people had an Internet
connection or phone line. Government leaders should consider pro-
moting greater amounts of mediated communication, during periods
when in-person contact is not possible, to help their citizens maintain
their psychological well-being.
A further line of study may interest industry leaders. The current
study focused only on individual well-being, but our results may be
extended to work contexts. Future studies could examine whether
increases in mediated communication with co-workers during home
working can increase satisfaction with work and productivity. These
studies could also address which types of mediated communication
are most effective for different work tasks.
6|CONCLUSION
The current study shows how people have adapted to social isolation
due to stay-at-home orders issued to combat the COVID-19 out-
break. It shows that people compensate for a lack of in-person con-
tact by using emerging technologies like video calls and other forms
of mediated communication. Furthermore, our study shows that
increased mediated communication was associated with increases in
subjective well-being even when people were,physically, socially iso-
lated. This finding demonstrates the importance of technologically
mediated communication during periods of crisis as a way to promote
well-being through social connection.
ACKNOWLEDGMENTS
We would like to acknowledge the help of Sanya Obsivac for rec-
ruiting participants for this study by designing and placing
Facebook ads.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
PEER REVIEW
The peer review history for this article is available at https://publons.
com/publon/10.1002/hbe2.246.
DATA AVAILABILITY STATEMENT
Data are available on https://osf.io/mjnpv/.
ORCID
Genavee Brown https://orcid.org/0000-0002-3169-9067
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AUTHOR BIOGRAPHIES
Dr. Genavee Brown is a Lecturer in Psychol-
ogy at Northumbria University, UK. She
earned her PhD in social psychology at Uni-
versity Rennes 2, France. She then completed
a postdoc examining the potential for pro-
moting creativity and social skills through an
online platform in the project ProFan
financed by the French Ministry of Education. Her research
focuses on how communication technologies like mobile phones
and social media influence social relationships. She her work also
examines how technology use is shaped by social ecologies and
culture. Recent publications have included work on how conspir-
acy beliefs discourage social distancing behaviors during the
BROWN AND GREENFIELD 155
COVID-19 pandemic and research on how teens use mobile
phones to promote intimacy with friends and parents.
Patricia Marks Greenfield received her Ph. D.
from Harvard University. She is Distinguished
Professor of Psychology at UCLA and mem-
ber of the American Academy of Arts and Sci-
ences. She directs Children's Digital Media
Center at Los Angeles, a collaboration
between UCLA and California State Univer-
sity, Los Angeles. She received the 2019 Outstanding Contribu-
tions to Cultural Psychology Award, given by the Advances in
Cultural Psychology Preconference, Society for Personality and
Social Psychology, and the Boesch Prize from the German Society
of Cultural Psychology. Her books include Mind and Media: The
Effects of Television, Video Games, and Computers, which was trans-
lated into nine languages and appeared in 2015 as a 30th anniver-
sary classic edition. With Noah and Gabriel Evers, she has
coauthored a second article in this special issue: COVID-19 shifts
mortality salience, activities, and values in the United States: A big
data analysis ofonline adaptation.
How to cite this article: Brown G, Greenfield PM. Staying
connected during stay-at-home: Communication with family
and friends and its association with well-being. Hum Behav &
Emerg Tech. 2021;3:147–156. https://doi.org/10.1002/
hbe2.246
156 BROWN AND GREENFIELD
