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Daily Technoference in Relationships 1
McDaniel, B. T., & Drouin, M. (2019). Daily technology interruptions
and emotional and relational well-being. Computers in Human
Behavior.
Published at: https://doi.org/10.1016/j.chb.2019.04.027
Daily Technology Interruptions and Emotional and Relational Well-Being
Brandon T. McDaniel
Illinois State University
Michelle Drouin
Purdue University Fort Wayne
Daily Technoference in Relationships 2
Abstract
The current abundance of technology in daily life creates opportunities for interruptions
in couple interactions, termed technoference or phubbing. The current study examined reports
from both partners in 173 romantic relationships who completed daily surveys on technoference
and relational well-being measures across 14 days. By using daily diary data, we were able to
examine within-person associations and more closely approximate everyday life. Utilizing
multilevel modeling, we found that on days when participants rated more technoference than
usual, they felt worse about their relationship, perceived more conflict over technology use, rated
their face-to-face interactions as less positive, and experienced more negative mood. These
relationships existed even after controlling for general feelings of relationship dissatisfaction,
depression, and attachment anxiety, and there were no significant differences between women
and men in these associations. This suggests that regardless of an individual’s or a couple’s
current level of well-being, if individuals perceive technology use as interfering in their
interactions with their partner, these perceptions may affect their daily assessments of their
relationship and mood.
Keywords: Technoference; phubbing; relationship satisfaction; problematic phone use;
depression; couple conflict
Daily Technoference in Relationships 3
Daily Technology Interruptions and Emotional and Relational Well-Being
1. Introduction
The majority of U.S. adults (95%) own and use cell phones, as well as other devices like
computers and tablets (Pew Research Center, 2018). This abundance of technology creates
opportunities for technological interruptions in couple interactions, termed technoference
(McDaniel & Coyne, 2016a) or phubbing, a portmanteau of “phone” and “snubbing” (Roberts &
David, 2016). Recently, a number of researchers have examined technoference among couples
and found that technoference is common within romantic relationships, and higher rates of
technoference are related to conflict, jealousy, and lower levels of relationship satisfaction,
intimacy, and relational closeness/cohesion (Amichai-Hamburger & Etgar, 2016; Halpern &
Katz, 2017; Krasnova et al., 2016; McDaniel & Coyne, 2016a; McDaniel, Galovan, Cravens, &
Drouin, 2018; Roberts & David, 2016; Wang et al., 2017). Hence, technology use within the
context of couple interactions has the potential to disrupt positive interactions and spur negative
feelings and conflict, and conflict and anger have the potential to contribute to relationship
dissolution (Gottman & Levenson, 2002). However, most of these previous studies have been
cross-sectional and focused on individual-level (rather than couple-level) data. The current study
expands this work by examining reports from both partners in romantic relationships who
completed daily surveys on technoference and emotional and relational well-being measures
across 14 days. By using daily diary data, we were able to examine within-person associations
and more closely approximate life as it is lived (Bolger, Davis, & Rafaeli, 2003).
1.1. Previous Research on Technology Interference in Couple Relationships
The empirical research on technology interference in couple relationships spans only a
few years. In the earliest studies on this phenomenon, researchers found that technoference or
Daily Technoference in Relationships 4
partner phubbing among U.S. participants in committed relationships was related to greater
levels of conflict over technology (McDaniel & Coyne, 2016a; Roberts & David, 2016). In turn,
this conflict predicted lower relationship satisfaction, which was negatively related to depression
and positively related to life satisfaction. Similarly, Wang et al. (2017) found that married
Chinese adults who reported greater amounts of partner phubbing had lower levels of
relationship satisfaction and higher levels of depression. Meanwhile, Amichai-Hamburger and
Etgar (2016) found that college students who reported that their partners engaged in higher rates
of smartphone multitasking, especially private multitasking, had lower levels of intimacy with
their partners. Additionally, Krasnova et al. (2016) found that partner’s smartphone use predicted
jealousy, and this predicted lower relational cohesion. Notably, none of these groups of
researchers reported on dyadic couple data, and they all measured technology interference, as
well as the other outcome variables, at a single time point. With regard to their samples, Roberts
and David (2016) recruited adults in relationships from Amazon’s Mechanical Turk sample,
Wang et al. (2017) recruited married Chinese adults through online forums and chat groups,
Amichai-Hamburger and Etgar (2016) and Krasnova et al. (2016) recruited college students in
romantic relationships through Facebook groups in Israel and Germany, respectively, and
McDaniel and Coyne (2016a) recruited married/cohabiting individuals from the local
community, but their sample included only women.
Halpern and Katz (2017) addressed one of the limitations of previous work by conducting
a longitudinal study on texting and relationship quality. In their study of Chilean adults who had
been in a romantic relationship for more than six months, they found, similar to previous
research on the topic (e.g., McDaniel & Coyne, 2016a; Roberts & David, 2016), that perceived
partner phubbing was related to greater conflict over the phone and lower intimacy. In turn, this
Daily Technoference in Relationships 5
conflict and lack of intimacy predicted lower perceived relationship quality. When they
examined the cross-lagged relationships between variables, they found that individuals’ texting
frequency predicted lower perceived relationship quality one year later, but relationship quality
did not predict later texting frequency. More recently, McDaniel et al. (2018) addressed another
limitation of previous research by examining technology interference within couples, including
dyadic data (reports from both partners). In their two-part study of 183 married/cohabiting
couples in the U.S. with at least one child (study 1) and 239 U.S. and Canadian couples with at
least one child (study 2), these authors found that technoference predicted conflict, which in turn
predicted relationship satisfaction and coparenting quality. Combined these studies suggest
technology use and/or interference among couples predicts conflict and relationship satisfaction;
however, there have not yet been any studies that have examined dyadic couple-level data with
measures of technoference and relationship satisfaction spanning multiple micro-level time
points (such as across days). This is an oversight as individuals’ and couples’ daily lived
experiences likely hold meaning for broader changes in relationships and well-being.
1.2.Theoretical Background
According to researchers who have examined technoference in couple relationships, the
presence of technology has the potential to negatively affect relationships via a number of routes.
Social exchange models provide one theoretical lens for interpreting these potential negative
effects. Social exchange models suggest that couples examine the costs and benefits of
relationships and are continually working to have their needs met within a relationship while also
minimizing costs (Thibault & Kelley, 1959). Applied to the concept of technoference, if a
partner has an expectation of undivided attention, which romantic partners sometimes do (Miller-
Ott & Kelly, 2015), they may react negatively when a partner uses technology in their presence.
Daily Technoference in Relationships 6
In support of this proposition, researchers (Krasnova et al., 2016) found that the majority of their
286 German college students (62%) experienced negative feelings (e.g., sadness, boredom,
anger) in response to their partner’s smartphone use, and Chotpitayasunondh and Douglas (2018)
found that phubbing produced negative affect (e.g., distressed and upset feelings) in
experimental dyadic interactions with 153 British undergraduates. In terms of social exchange,
these negative emotions may register as relational costs, increasing conflict or jealousy in
romantic relationships (Halpern & Katz, 2017; McDaniel & Coyne, 2016a; 2016b; McDaniel et
al., 2018; Roberts & David, 2016). Alternatively (or additionally), a partner’s technoference
behaviors might translate as a loss of relationship rewards (e.g., time or attention), shifting the
balance of the social exchange so that the ‘phubbed’ partner feels excluded and experiences less
relationship satisfaction, closeness, or intimacy (Hales et al., 2018; Halpern & Katz, 2017;
Krasnova et al., 2016; McDaniel & Coyne, 2016a; McDaniel & Drouin, 2018; Van Lange &
Rusbult, 2012).
Additionally, some relationship researchers (e.g., Halpern & Katz, 2017; Juhasz &
Bradford, 2016) have proposed that the sociological theory of symbolic interactionism (Denzin,
1992) may help explain the effects of technology use on relationships. Symbolic interactionism
suggests that people communicate using symbols, and through their interpretation of symbols,
they infer the meaning of their relationships and roles with others (Denzen, 1992). Although
there are different schools of thought related to the present-day interpretation of symbolic
interactionism (i.e., the Chicago School, Iowa School, and Indiana school—see Carter & Fuller,
2016 for more detail), the basic principles of symbolic interactionism include the idea that
symbols and interactions are meaningful, the meanings of these symbols are derived from
interactions with others, and this is a continuous process that individuals engage in during social
Daily Technoference in Relationships 7
interactions (Carter & Fuller, 2016). With regard to the use of technology in relationships, when
individuals use technology to keep in touch with their partners at a distance (e.g., through calls or
text messages), it may be perceived as a symbol of social connectedness (Juhasz & Bradford,
2016); however, if a romantic partner is using their phone or checking updates or alerts instead
of attending to a conversation, it may be interpreted as a symbol of disconnection or disinterest.
As a partner experiences these interactions over time, the symbol (in this case, technoference or
partner phubbing) might affect an individual’s sense of self and their perceptions of their role in
the interpersonal relationship (Denzin, 1992).
This shift in perception may be especially pronounced when the technoference or
phubbing behavior violates one’s expectations in the relationship. According to the expectancy
violation communication theory (Burgoon, 1978), individuals have expectations of others’
behaviors during interpersonal interactions, and if an individual perceives that someone is
violating those expectations, this can prompt negative reactions. Indeed, technoference research
has shown that perceived partner phubbing or technoference can lead to negative affect
(Chotpitayasunondh & Douglas, 2018; Halpern & Katz, 2017; McDaniel & Coyne, 2016a) and
feelings of exclusion (Hales et al., 2018; McDaniel & Drouin, 2018). However,
Chotpitayasunondh and Douglas (2018) also found that perceived social norms of phubbing did
not moderate the relationship between phubbing intensity and negative affect. As their study was
conducted with interaction partners who were not friends or relationship partners, it is unknown
whether social norm expectations intensify or attenuate reactions to technoference within the
context of romantic relationships, and the theoretical lens of expectancy violation theory still
provides some basis for interpreting the negative affect and/or conflict that results from
technoference.
Daily Technoference in Relationships 8
Applying these theoretical frameworks to the current inquiry, when one uses technology
instead of attending to a partner, it may send a signal that technology use is more important than
the current face-to-face interaction (symbolic interactionism theory) and/or violate one’s
expectations of how this couple time should be spent (expectancy violation theory). This may
result in individuals feeling like the social exchange in their relationship is unbalanced (i.e.,
greater costs and/or fewer benefits), which may spur negative mood, couple conflict, perceptions
of lower quality day-to-day interactions, and more negative assessments of the quality of the
relationship. This aligns with the cross-sectional data to date which has found: (1) technoference
among couples exists, (2) it begets relational costs, like negative emotions, conflict over
technology use, and jealousy, and (3) this increase in relational costs and decrease in rewards
(social exchange theory), in turn, is related to lower levels of relationship satisfaction, closeness,
and intimacy (Amichai-Hamburger & Etgar, 2016; Krasnova et al., 2016; McDaniel & Coyne,
2016a; 2016b; Roberts & David, 2016; Wang et al., 2017). Although this model has been
explored only cross-sectionally, with contemporaneous, general measures of technoference and
relationship satisfaction, closeness, and intimacy, we believed that these same relationships
would exist in the more proximal experiences of couples’ daily lives together. Building upon the
previous empirical literature on the topic, we expected that on a daily basis:
H1: Greater amounts of perceived daily technoference would predict lower ratings of
daily relationship quality, more frequent daily couple conflict, lower perceived quality of daily
face-to-face interactions, and greater daily negative mood.
1.3. Technoference, Relationship Satisfaction, and Individual Characteristics
In addition to these associations, we also expected that there would be individual
characteristics, like depression and attachment anxiety, that may be related to technoference,
Daily Technoference in Relationships 9
relationship satisfaction, or both. With regard to the role of depression, seminal works on this
topic (McDaniel & Coyne, 2016a; 2016b; Roberts & David, 2016; Wang et al., 2017) showed
that technoference or partner phubbing predicted relationship satisfaction, which was, in turn,
predictive of depression. Other researchers (e.g., Harwood, Dooley, Scott, & Joiner, 2014) have
also shown that a high amount of smartphone involvement is related to depression, suggesting
that mobile phone involvement on behalf of the user (not just perceived partner phubbing) is
associated with mental health. Recent findings from McDaniel et al. (2018) support this
assertion. In their sample of couples, depression was significantly related to technoference
among men, and depression was also significantly related to relationship satisfaction among both
men and women. Meanwhile, Newsham, Drouin, and McDaniel (2018) found that depression
among mothers was predictive of both technoference in parenting and problematic phone use.
Finally, Meyer, Kemper-Damm, Parola, & Salas (2019) showed that, among men, higher levels
of depression predicted lower relationship satisfaction. As each of these studies were cross-
sectional, the directionality of these influences is unknown, but it is likely that depression is
related to both technoference and perceived relationship quality, as there is a bidirectional
relationship between depression and marital discord (Whisman & Uebelacker, 2009), which may
affect both perceived (or actual) relationship quality and technoference in the relationship.
Regarding attachment anxiety, the theoretical literature has suggested that those with high
levels of attachment anxiety have a need for reassurance in a relationship, and they also may be
more likely to interpret their partner’s behaviors in a negative way (Shaver & Mikulincer, 2006).
In line with this, Roberts and David (2016) found that attachment anxiety moderated the
relationship between perceived partner phubbing and relationship conflict. Additionally,
McDaniel et al. (2018) showed that attachment anxiety, but not attachment avoidance, was a
Daily Technoference in Relationships 10
significant predictor of perceived technoference, which predicted couple conflict and, in turn,
relationship satisfaction. Therefore, based on the previous empirical and theoretical work on this
topic, we expected:
H2: Depression and attachment anxiety would be related to technoference and
relationship satisfaction.
In addition to exploring the zero-order relationships between these variables, we also
wanted to examine whether daily technoference was predictive of daily relationship satisfaction
and our other daily variables after controlling for depression and attachment anxiety, since (as
stated above) depression and attachment anxiety may influence perceptions of technoference and
relationship satisfaction.
Finally, to better understand the trends of daily technoference, we also examined:
(RQ1) What is the overall prevalence of technoference in the daily life of U.S. couples?
2. Method
2.1. Participants
Participants were part of the Project Name Masked for Review, a longitudinal study of
family life from 2014 to 2016, recruited through a database of families (in a Northeastern U.S.
state) and through announcements in the local community and on websites. Heterosexual couples
(N = 183 couples) had to be living together in the U.S. and have a child age 5 or younger (child,
M = 2.88 years, SD = 1.34; 53% female). Both partners completed online surveys at various time
points. In the current study, we utilized data on 173 couples who completed the baseline survey
and the daily diary portion of the study, in which we had data from 173 women and 171 men
within these couples; there were 22 participants who dropped out prior to the daily surveys or
who did not complete any daily surveys. These families resided in the following U.S. regions:
Daily Technoference in Relationships 11
53% Northeast, 17% West, 15% South, and 15% Midwest. The majority (92%) of couples were
in a relationship of 5 years or longer (M = 9.83 years, SD = 4.01). Most were Caucasian (93% for
women, 90% for men) and married (95%). On average, women were 31.46 years old (SD = 4.47;
range 20 to 42), men were 33.31 (SD = 5.04; range 22 to 52), and median yearly household
income was approximately $69,000 (M = $73,336, SD = $38,263), but ranged extensively from
no income to $250,000; 72% had a Bachelor’s degree or higher.
2.2. Procedure
Participants completed informed consent and an online baseline survey that included
baseline demographics (e.g., age, income, etc.) and a number of individual and relational well-
being measures. Then, over 14 consecutive days, participants completed a daily survey online.
Participants (n = 344) completed an average of 11.74 days (SD = 2.95 days) of surveys, with
87% completing 10 or more days, for a total of 4039 days of data. The daily surveys contained
the following measures. Where appropriate the reliability of measures at assessing within-person
change was calculated (Rc; Shrout & Lane, 2012), and all daily measures showed moderate to
good reliability. Participants also rated how many hours they were with their partner each day.
2.3. Measures
2.3.1. Daily Technoference. We adapted the Technology Device Interference Scale
(TDIS; McDaniel & Coyne, 2016a) to the daily context to measure daily technoference. Similar
to the TDIS, participants rated how often each of 4 devices (cellphone/smartphone, television,
computer, and tablet) interrupted a conversation or activity they were engaged in with their
partner. We adapted the scaling from a general frequency scale (i.e., Never to All the time) to a 7-
point frequency scale more appropriate for daily reports (0 = none, 6 = more than 20 times). This
was also done to avoid vague scale point meanings (i.e., “sometimes” could mean very different
Daily Technoference in Relationships 12
frequencies to different participants) and in order to obtain a better estimate of individuals’
perceptions of the actual frequency of technoference. Prior work (e.g., McDaniel et al., 2018) has
shown that, according to individuals’ perceptions, various episodes of technoference (such as a
partner getting on their phone during a conversation) occur once a day or more often in about 17
to 22% of participants. However, these are cross-sectional reports and it was not known how
often individuals might perceive technoference on a daily basis. Therefore, the end-point of
“more than 20 times” was chosen in order to not accidentally restrict the range of responses
individuals could provide. We found that interruptions due to television, computers, and tablets
were perceived fairly rarely (only occurring on about 8%, 6%, and 4% of days respectively);
thus, in the current study we focused on technoference due to cellphones which occurred more
frequently (i.e., on about 21.5% of days).
2.3.2. Daily Relationship Quality. Participants completed 6 items measuring feelings
about the couple relationship (e.g., love, conflict, satisfaction). These items have been used
successfully to measure relationship quality in a variety of daily survey studies (e.g., Curran,
McDaniel, Pollitt, & Totenhagen, 2015; McDaniel, Teti, & Feinberg, 2018; Totenhagen, Serido,
Curran, & Butler, 2012), and in the current study scores on this measure correlated highly (as
one would expect) with an established measure of relationship satisfaction (r = .69, p < .001).
Participants responded on a 7-point Likert scale (1 = not very much or just a little, 7 = very much
or a lot). Items were averaged to produce an overall score each day (Rc = .87).
2.3.3. Daily Conflict over Technology Use. Participants indicated whether they
experienced an argument or disagreement that day over 10 uses of technology (e.g., “time spent
on internet” and “time spent texting”). Participants’ responses were coded as 1 or 0 based on
whether they did or did not, respectively, experience an argument over that technology use.
Daily Technoference in Relationships 13
Items came from or were adapted from the Conflict over Technology Use scale, which has been
used in various forms to measure couple conflict over technology use in cross-sectional studies
(McDaniel & Coyne, 2016a; McDaniel et al., 2018). Items were summed to produce an overall
score each day (Rc = .90).
2.3.4. Daily Positive Face-to-Face Interactions. Participants indicated on a single item
the proportion of their face-to-face (in person) communications with their partner that were
positive that day using a 5-point scale (1 = all negative, 5 = all positive). This measure is
significantly related, in the expected directions, with all of the daily measures (e.g., relationship
quality, conflict, etc.), lending some initial evidence of the validity of this measure.
2.3.5. Daily Negative Mood. We adapted the POMS-15 (Cranford et al., 2006) to a daily
context and asked participants to rate how often they felt three emotion items (i.e., “anxious,”
“angry or annoyed,” and “discouraged or sad”) that day. Participants used a 5-point scale (0 =
none of the time, 4 = all of the time). Items were averaged to produce daily scores (Rc = .63).
Scores on this daily measure correlated strongly (r = .65, p < .001) on average with an
established measure of depressed mood (CES-D), lending some validity to the daily measure.
2.3.6. Baseline control variables. Besides demographics (e.g., income, ethnicity,
education, relationship length, etc.), participants also responded on the baseline online survey to
established and well-validated measures of depressive symptoms (20 items, CES-D; Radloff,
1977), relationship satisfaction (6 items, QMI; Norton, 1983), and attachment anxiety towards
the relationship partner (5 items, ECR-S; Wei, Russell, Mallinckrodt, & Vogel, 2007). All
baseline measures had good reliability (Cronbach’s alphas of .89, .95, and .74 respectively).
3. Results
Daily Technoference in Relationships 14
We first (R1) examined the frequency of technoference due to cellphones. Overall, we
found that 56.1% of participants said that technoference from phones happened at least two to
three days (or more often) out of the two-week period. Specifically, 27.6% of participants said
that technoference from phones never happened during the 14 days, 16.3% said it occurred on
one day, 20% on two to three days, 20.4% on four to six days, and 15.7% on seven or more days
(or half or more of the 14 days). Additionally, overall means and between-person (average)
correlations between our main study variables across all days of data are reported in Table 1. On
days when technoference occurred, most participants (53.9%) indicated that technoference
occurred only once; however, 36.4% indicated it occurred two to three times, 7% indicated it
occurred four to five times, 2% stated it occurred six to 10 times, and 0.7% indicated it occurred
more than 11 times per day. For between-person correlations, those who reported more frequent
daily technoference from phones on average also tended to report poorer daily relationship
quality (r = -.18, p < .001), greater daily conflict over technology use (r = .27, p < .001), less
positive daily face-to-face interactions (r = -.20, p < .001), and greater daily negative mood (r =
.29, p < .001) on average. Additionally, in support of our hypothesis (H2), technoference was
significantly related to depression (r = .23, p < .001) and attachment anxiety (r = .22, p < .001),
and relationship satisfaction was also related to depression (r = -.34, p < .001) and attachment
anxiety (r = -.25, p < .001).
Daily Technoference in Relationships 15
Table 1.
Descriptives and between-person correlations between study variables
Daily Variables
Baseline Variables
1
2
3
4
5
6
7
8
9
Daily Variables
1. Technoference (phones)
--
2. Relationship quality
-.18***
--
3. Conflict over tech. use
.27***
-.25***
--
4. Positive FtF interactions
-.20***
.60***
-.31***
--
5. Negative mood
.29***
-.35***
.25***
-.38***
--
6. Hours together
.08
.22***
.01
.09
-.01
--
Baseline Variables
7. Depression
.23***
-.34***
.24***
-.30***
.65***
.01
--
8. Relationship satisfaction
-.07
.69***
-.15**
.44***
-.22***
.18***
-.37***
--
9. Attachment anxiety
.22***
-.25***
.10
-.24***
.33***
-.01
.48***
-.22***
--
Mean
0.34
6.21
0.13
4.43
0.69
5.90
10.78
38.05
3.11
SD
0.75
0.92
0.85
0.68
0.66
4.41
8.59
7.05
1.19
Note. *p < .05, **p < .01, ***p < .001. Tech = technology, FtF = face-to-face.
Daily Technoference in Relationships 16
We then utilized multilevel modeling (MLM) in SAS Proc Mixed to examine our models
of daily technoference predicting our daily outcome variables. We used MLM to account for
partners being nested within couples, to account for each participant completing multiple
assessments across days, and to allow for an autoregressive structure to the residuals (i.e., that
participant reports from one day to the next would be correlated); this type of modeling was
important to not produce biased standard errors and significance tests. We ran four separate
models, one for each daily outcome, including relationship quality, conflict over technology use,
positive face-to-face interactions, and negative mood (see Table 2). Analyses included any
participant who had at least one day of data. Missing data on any of these outcome variables
were handled using restricted maximum likelihood estimation, while days that contained missing
data on any predictor variables were dropped from the analyses. We also limited the models to
examining only those days on which partners had some time together (n = 3892 days, 96% of
days). We controlled for a variety of demographics and individual characteristics (e.g., age, race,
income, attachment anxiety) as well as baseline individual and relational well-being (e.g.,
depression, relationship satisfaction) where appropriate. Daily variables were split into between-
person and within-person portions (as is standard in daily data).25 This procedure produces two
uncorrelated variables that are both entered into a model. With this split, the effect of the
between-person daily variable indicates differences between people (e.g., those who report more
technoference as compared to those who report less technoference on average), and the effect of
the within-person daily variable indicates within-person processes (e.g., on days when
participants report more technoference than their typical amount, do we see corresponding
fluctuations in the daily outcomes?). We also tested for gender differences on the effects of
technoference predictors.
Daily Technoference in Relationships 17
We report the unstandardized estimates for our four models in Table 2. At the between-
person level, we found a significant effect of average daily technoference on average daily
conflict over technology use, positive face-to-face interactions, and negative mood (although in
the proper direction, the between-person effect was not significant for average daily relationship
quality). These results indicate that, even after controlling for many different demographic and
individual characteristics, those who reported more technoference on average also reported more
conflict over technology use (b = 0.26, p < .001), less positive face-to-face interactions (b = -
0.13, p < .01), and greater negative mood (b = 0.14, p = .01) on average. No significant
differences were found between women and men in these associations.
In terms of the within-person effects and in support of our hypothesis (H1), we found a
significant effect of daily technoference on all four daily outcome variables. In other words, on
days when participants rated more technoference than usual, they felt worse about their
relationship (b = -0.04, p = .02), perceived more conflict over technology use (b = 0.10, p <
.001), rated their face-to-face interactions as less positive (b = -0.05, p < .001), and experienced
more negative mood (b = 0.03, p = .02). No significant differences were found between women
and men in these associations.
Table 2. Unstandardized estimates for the multilevel models of daily technoference predicting daily relationship
quality, conflict over technology, perceived face-to-face interactions, and negative mood
Model 1:
Daily
Relationship
Quality
Model 2:
Daily Conflict
over
Technology
Use
Model 3:
Daily Positive
Face-to-Face
Interactions
Model 4:
Daily Negative
Mood
Fixed effects
b
b
b
b
Intercept
6.13***
0.05
4.41***
0.88***
Day
0.02***
-0.001
0.005
-0.01***
Gender
-0.11
0.03
0.01
-0.10*
Control Variables
Family income
-0.001
0.001
-0.001
-0.003***
Race/Ethnicity
0.01
0.08
-0.19*
-0.04
Daily Technoference in Relationships 18
Not college graduate
0.08
0.18**
-0.05
-0.08
Multiple children
-0.13
-0.05
0.05
0.05
Relationship length
-0.02
0.002
-0.01
0.01
Marital status
-0.89**
0.25
0.08
0.36**
Age
0.001
-0.01
0.01
-0.004
Depression
-0.01**
0.003
-0.004
--
Relationship satisfaction
--
-0.001
0.02***
-0.01*
Attachment anxiety
-0.06
0.02
-0.04*
0.11***
Hours together with partner
0.01***
0.01*
-0.01**
-0.01***
Between-person (BP) portion of daily technoference predicting average daily outcome variable
BP daily technoference
-0.10
0.26***
-0.13**
0.14*
BP daily technoference X gender
--
--
--
--
Within-person (WP) portion of daily technoference predicting daily fluctuations in outcome variable
WP daily technoference
-0.04*
0.10***
-0.05***
0.03*
WP daily technoference X gender
--
--
--
--
Note: ***p < .001, **p < .01, *p < .05. Gender is coded 0 = female and 1 = male. Day is centered on day 1. Control variables were
coded as follows: Race/Ethnicity (0 = Caucasian, 1 = other race), Not college graduate (0 = college grad., 1 = less education than college
grad.), Multiple children (1 = multiple children, 0 = only one child in family), and marital status (1 = living together, not married, 0 =
married). Except for the above mentioned controls, all other variables were grand mean centered. Family income was in $1,000 units.
Technoference was split into trait-like (between-person) and state-like (within-person) portions and both portions were included in the
model.
4. Discussion
Heretofore, the literature has treated technoference and well-being variables in a trait-like
manner (between-person effects), measuring them at a single time point (Amichai-Hamburger &
Etgar, 2016; Krasnova et al., 2016; McDaniel & Coyne, 2016a; 2016b; McDaniel et al., 2018;
Roberts & David, 2016; Wang et al., 2017) or more recently, two time points (Halpern & Katz,
2017). However, in our 14-day diary study, participants rated their experiences and feelings each
day, giving us valuable information about their own and their partner’s daily behaviors and
emotional states.
Most couples (56.1%) indicated that they experienced technoference in their romantic
relationship at least a few days during the 14-day study period. Moreover, 72.4% experienced
technoference on at least one day of the 14-day period. This is unsurprising considering the high
penetration rate of mobile phone ownership in the U.S. (Pew Research Center, 2018) and the
growing numbers of individuals worldwide who report that their cell phone use is problematic or
Daily Technoference in Relationships 19
they have addictive tendencies towards their cell phones (Jenaro et al., 2007; Jiang et al., 2016;
Nagpal & Kaur, 2016). However, we had anticipated that some individuals might experience
technoference with even greater frequency than this, as technoference has been conceptualized as
“everyday intrusions and interruptions” (McDaniel & Coyne, 2016a). Thus, our finding that only
15.7% reported a cellphone as interrupting an interaction on seven or more days (or half or more
of the 14 days) was somewhat surprising. This lower than anticipated rate of reported daily
technoference may be due to the wording of our measure. It may be that participants experienced
minor interruptions or distractions due to a cell phone, but they reported only instances when the
device caused a more serious distraction. Therefore, our measure may not have been sensitive
enough to capture more minor distractions. It may also be that individuals have different
definitions of what they classify as an interruption. That said, our finding that so many reported
this “interrupting” technoference even a few times a week suggests that technoference is
beginning to have an impact on American couples’ daily lives.
In support of our main study hypothesis, daily fluctuations in technoference (within-
person effects) predicted conflict over technology use, quality of face-to-face interactions,
negative mood, and daily assessments of relationship quality; and with the exception of
relationship quality, these same significant relationships existed when we examined between-
person effects of technoference. Moreover, these relationships were significant even after
controlling for many individual and relationship characteristics (i.e., age, gender, depression,
attachment anxiety, etc.) that have been shown to be significantly related to technoference and
relationship well-being in prior work (Krasnova et al., 2016; McDaniel & Coyne, 2016a; 2016b;
McDaniel et al., 2018; Roberts & David, 2016; Wang et al., 2017); depression and attachment
anxiety were also found to be correlated with technoference and relationship satisfaction in the
Daily Technoference in Relationships 20
current study, suggesting that these variables should continue to be examined and controlled for,
at the very least, in future work on technoference and phubbing. It is notable that daily
technoference from a phone had a significant effect on mood, quality of interactions, perceptions
of relationship quality, and couple conflict, above and beyond general relationship dissatisfaction
and any feelings of depression or attachment anxiety. This suggests that regardless of an
individual’s or a couple’s current level of well-being, as individuals perceive technology use as
interfering in their interactions with their partner, these perceptions likely hold implications for
their daily perceptions of their relationship and their mood.
Theoretical Implications
Researchers have proposed that technoference and phubbing affect relationships in a
negative way because a partner may interpret attention to one’s phone as a symbol that the
partner is not the main priority, or it may be a violation of expectations within the relationship
(Halpern & Katz, 2017; Krasnova et al., 2016; McDaniel & Coyne, 2016a; 2016b; McDaniel et
al., 2018; Roberts & David, 2016). Our study adds a dimension to the existing empirical
literature by demonstrating that within individuals, on a daily basis, perceived technoference
contributes to greater conflict, less positive face-to-face interactions, negative mood, and lower
relationship quality. Our ability to narrow these assessments to the daily level suggests that each
of these potential routes from technoference to negative relationship outcomes has immediate
(and possibly cumulative) effects. Further, when considered within the larger frame of social
exchange theory (Thibault & Kelley, 1959), our findings suggest that there is a relational cost (or
lack of benefit) from interacting with technology in the presence of a romantic partner. More
research is necessary to more precisely define the spectrum of technology-related behaviors
individuals consider “interruptions,” and the extent to which these interruptions are considered as
Daily Technoference in Relationships 21
such because of the expectancy violating nature of the particular behavior (e.g., responding to
email while engaged in a conversation might be considered an interruption while quickly
glancing at a phone may not) or whether the interpretations are largely person or couple-specific
(e.g., people who use their phones more often within their dyadic couple may be less likely to
consider technological behaviors as interruptions).
Practical Implications
Technology offers a convenient mechanism for individuals to communicate with others,
both near and far. Texting has become so commonplace that it has even been explored as an
avenue through which romantic partners might increase their relationship satisfaction. As an
example, Luo and Tuney (2015) found that when college students sent their romantic partner a
text message once a day over two weeks, they (the senders) reported slightly more relationship
satisfaction at the end of the two weeks than those who did not send a text message. This effect
emerged regardless of the content of the text message (Luo & Tuney, 2015). However, more
recently, Ohani, Brown, Trub, and Rosenthal (2018), found that perceived partner similarity in
texting practices (e.g., how often they initiated text message interchanges and the extent they
used text messages to express certain feelings, like anger or affection) was related to greater
relationship satisfaction. Combined these studies suggest a complex relationship between the use
of technological communication and relationship satisfaction—rather than frequency of use, it
appears to be perceived similarity between couples on their mobile phone behaviors that is most
important for couple satisfaction. Moreover, when applied more broadly to mobile phone
etiquette, it appears that internalized personal standards, rather than societal norms, and
similarity between partners on their perceptions of public and private phone use norms are
important predictors of relationship quality (Hall, Baym, & Miltner, 2014).
Daily Technoference in Relationships 22
Considered alongside our current findings, this suggests that an act that might be
considered a violation of expectations to one individual (or one couple), such as checking one’s
phone while watching TV with a partner, may not be considered a violation to another person (or
another couple). Provided the individuals in the couple share perceptions of what is and is not a
violation of expectations, technoference, even if it occurs once or twice a day, may not impact
relationship satisfaction. However, incongruencies within couples on standards related to mobile
phone etiquette may be problematic. Consequently, it is important for individuals and couples to
contemplate and communicate their mobile phone etiquette standards with consideration for their
own (and their partner’s) daily technology-related behaviors, so that they can avoid conflict
related to expectancy violations. Although our study focused on only romantic partners, research
has shown that phubbing behaviors also affect friends (Karadağ et al., 2015), and that even those
in experimental dyadic interactions can be affected negatively (in terms of their mood or
perceived relationship quality) by phubbing (Chotpitayasunondh & Douglas, 2018) or even the
mere presence of mobile phones (Przybylski & Weinstein, 2013). Therefore, these
recommendations extend to other types of dyadic conversation partners, as well, such as friends,
work colleagues, and family members.
Future research should explore whether similarity within couples on mobile phone
etiquette standards moderates the relationship between frequency of daily technoference and
daily relationship satisfaction. Better understanding this process and the potential for expectancy
violations could assist clinicians and educators in making more effective and evidence-based
recommendations for individuals and couples. Additionally, future researchers should examine
the cumulative (long-term) effects of these daily interruptions over time on overall relationship
Daily Technoference in Relationships 23
health in romantic and other types of dyadic relationships, as even seemingly small effects could
change the overall course of relationships over long periods of time.
4.1. Limitations and Conclusion
In terms of limitations, our sample was only U.S. residents who had at least one child
under the age of five. Although all U.S. regions and a broad range of socio-economic statuses
were represented, the sample was fairly homogeneous in terms of race (mostly Caucasian) and
we do not know how well these results would generalize to other ethnic groups and other
countries (especially where cell phone penetration rates differ) or to couples without children.
However, as technoference appears to be an issue in romantic relationships generally and not just
within coparenting relationships (Halpern & Katz, 2017; Krasnova et al., 2016; McDaniel &
Coyne, 2016a; McDaniel & Drouin, 2018; Roberts & David, 2016; Wang et al., 2017), we
expect similar findings would emerge in the daily diaries of couples without children. We look to
future research to explore this issue specifically in couples without children. However, other
work has found that even when differences emerge in terms of the perceptions of technoference
(for example, women tend to perceive technoference as occurring more often than men perceive
it), when technoference is perceived the effect on relational and personal well-being is similar
(e.g., McDaniel et al., 2018). Additionally, the current sample contained only heterosexual
couples as the data came from a project originally designed to examine coparenting interactions
between mothers and fathers; however, prior work has shown no significant differences, at least
at the cross-sectional level, in these technoference processes by sexual orientation (McDaniel et
al., 2018). Finally, we utilized a single item as our measure of technoference due to phones. In
the future, we hope to expand on the current work to better examine the possibilities and impacts
of more minor types of technological distractions from couple interactions, as opposed to only
Daily Technoference in Relationships 24
those times when a device interrupted a conversation or activity. Future work should also
examine the sources of the interruptions (e.g., which partner is disengaging from the interaction)
and severity/length of the interruptions. Finally, although we were better able to approximate
daily life experiences with our daily survey data, the data can still suffer from common method
bias. Future work would benefit from using multiple methods (i.e., surveys and naturalistic
observations) to confirm that perceptions match behaviors and/or how perceptions and actual
behaviors may play different roles in these processes. This work could also better examine the
validity of self-report measures of technoference.
Many couples experience technoference from day-to-day. Though a common occurrence
for some couples, it is not one without consequence—daily fluctuations in perceived
technoference from one’s phone affects mood, emotions, evaluations of interactions, and even
assessments of relationship quality. Thus, partners should be mindful of their technology use
while with a romantic partner to avoid the potential negative impacts of technoference.
Moreover, clinicians should include discussions of technoference as a potential contributing
factor to relationship dissatisfaction and decreases in interactional quality.
Daily Technoference in Relationships 25
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