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The Spanish Journal of Psychology (2017), 20, e24, 1–10.
© Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid
doi:10.1017/sjp.2017.20
There is no longer any doubt that Information and
Communications Technology (ICT) is part of everyday
life for young adults; they use it to communicate, and
as a tool to learn and explore. Subrahmanyam and
Šmahel (2011) proposed a theoretical model to analyze
young people’s online behavior from a psychodevel-
opmental perspective. According to those authors, ICT
(understood as using mobile devices and social net-
working) has become a real space for young people’s
development and learning, a context in which they can
express themselves and grapple with the main chal-
lenges of their age, which revolve around assuming
responsibility in different spheres of social and per-
sonal life, including romantic life (Brown & Bobkowski,
2011; Shulman & Connolly, 2013). From that point of
view, one would expect online and offline behavior to
be related, not only reflecting young people’s interests
and concerns, but providing two-way feedback.
Studies of online behavior in young adults seem to
confirm Subrahmanyan and Šmahel’s postulates (2011)
that young adults use the Internet in fundamental
ways to communicate with their romantic partner and
develop the relationship (Fox & Warber, 2013), and
publicly share emotional states, photos, and other con-
tent from their romantic relationships (Carpenter &
Spottwood, 2013). By the same token, it has been sug-
gested that online couple behavior influences percep-
tions of the romantic relationship overall. For example,
Caughlin and Sharabi (2013) analyzed online and offline
behavior in the form of private and public messages via
Internet, text messages, chat, video chat, and phone calls
between American young adults and their romantic
partners. They concluded that people who adopted both
modes of communication, in a balanced way, had more
favorable results in terms of intimacy and relationship
satisfaction than those who used only one (online or
offline), and those who had trouble switching online to
offline or vice versa. Similarly, Morey and her collabora-
tors (Morey, Gentzler, Creasy, Oberhauser, & Westerman,
2013) found that communicating via phone and text
message was associated with greater relationship satis-
faction and intimacy in American young adults.
Romantic Relationship Quality in the Digital Age:
A Study with Young Adults
Virginia Sánchez1, Noelia Muñoz-Fernández1 and Rosario Ortega-Ruiz2
1 Universidad de Sevilla (Spain)
2 Universidad de Córdoba (Spain)
Abstract. Recent studies suggest that the online and offline behaviors young people display in romantic relationships are
closely related. However, the differential effects of the dimensions of couple quality in the online context have not yet
been explored in depth. The aim of this study was to explore online couple quality in young-adult relationships, and its
association with romantic relationship satisfaction, also looking at effects of gender, age, and length of the relationship.
431 university students currently in a romantic relationship (68.2% females; mean age = 21.57) participated in this study.
They completed different self-report measures to tap the online quality of their romantic relationships (online intimacy,
control, jealousy, intrusiveness, cyberdating practices, and communication strategies) and level of satisfaction with those
relationships. Results showed that participants more often reported online intimacy (Mmen = 2.49; Mwomen = 2.38) than the
negative scales of online quality (mean ranged from .43 to 1.50), and all the online quality scales decreased with age
(correlations ranged from –.12 to –.30) and relationship length (correlations ranged from –.02 to –.20). Linear regression
analyses indicated that online intimacy (b = .32, p = .001) and intrusiveness (b = .11, p = .035) were positively related to rela-
tionship satisfaction, while cyberdating practices (b = –.20, p = .001) and communication strategies (b = –.34, p = .001) were
negatively correlated with relationship satisfaction. Moreover, gender and relationship length moderated some of these
associations. Results indicate that while online quality and relationship satisfaction are related, the impact of different
online quality dimensions on relationship satisfaction differs depending on a participant’s sex, age, and relationship length.
Received 5 May 2016; Revised 24 March 2017; Accepted 27 March 2017
Keywords: communication, online couple quality, romantic relationships, satisfaction, young people.
Correspondence concerning this article should be addressed to
Virginia Sánchez Jiménez. Departmento de Psicología Evolutiva y de
la Educación. Universidad de Sevilla. C/ Camilo José Cela, s/n. 41018.
Seville (Spain). Phone: +34–954557650. Fax: +34–954557650.
E-mail: virsan@us.es
This research was funded by the Spanish Ministerio de Economía y
Competitividad into the national I+D program: (PSI2013-45118-R).
Parejas y redes de iguales en la adolescencia. Noelia Muñoz-Fernández has
a grant from the Spanish Ministerio de Educación, Cultura y Deporte
(FPU2013/00830).
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2 V. Sánchez et al.
More numerous studies have analyzed the relation
between negative online relationship dynamics and
different indicators of romantic relationship quality in
young adults. For instance, online jealousy – understood
as an emotional reaction prompted by visualizing
online relationship content – and concerns and suspi-
cions about a partner’s interest in someone else (Utz &
Beukeboom, 2011) have been associated with low levels
of relationship satisfaction (Elphinston & Noller, 2011),
and predict involvement in psychological (Strawhun,
Adams, & Huss, 2013) and physical abuse (Sánchez,
Muñoz, Nocentini, Ortega-Ruiz, & Menesini, 2014). On
the other hand, research on online intrusive behavior,
which is understood as repeated, obsessive attempts
to initiate contact and communicate with a partner
after a break-up or fight, has revealed that people who
exhibit these behaviors in online mode do so offline
too (Spitzberg & Hoobler, 2002; Strawhun et al., 2013),
and has linked it to low relationship quality (Lavy,
Mikulincer, Shaver, & Gillath, 2009) as well as intimate
partner abuse (Sánchez et al., 2014; Strawhun et al.,
2013). Regarding online monitoring or control, that is,
surveillance and tracking of the partner’s online activity
(Tokunaga, 2011), results have been inconclusive. Some
studies have found negative associations between con-
trol and relationship satisfaction (Elphinston & Noller,
2011), while other studies have not (Stewart, Dainton, &
Goodboy, 2014). Finally, the research on online infidelity,
understood as using ICT to flirt or contact others, have
produced similarly disparate results: some studies
related it to lower relationship satisfaction (Cravens,
Leckie, & Whiting, 2013), while others found it was
more closely tied to sensation-seeking behaviors than
low relationship satisfaction (Hertlein & Stevenson,
2010). What these studies do clearly suggest is that
while positive online practices – like using ICT to com-
municate with one’s partner, and spending time together
online – are related to positive relationship outcomes,
associations with negative online relationship dynamics
have been inconclusive.
In addition to those findings, differences in online
practices and relationship satisfaction have been
observed as a function of sex, age, and relationship
length. The research suggests that women are involved
in longer, more serious relationships with higher satis-
faction (Dhariwal, Connolly, Paciello, & Caprara, 2009;
Rauer, Pettit, Lansford, Bates, & Dodge, 2013), but tend
to exhibit more online jealousy (Muise, Christofides, &
Desmarais, 2014). Men, meanwhile, tend to engage in
more cyberbullying and cyberdating (Duran-Segura &
Martínez-Pecino, 2015; Sánchez, Muñoz-Fernández, &
Ortega-Ruiz, 2015). To date, we do not know of previous
studies that relate age to higher relationship satisfac-
tion, but it does seem to be negatively associated with
Internet usage (Correa, Hinsley, & De Zuniga, 2010) and
certain online practices, such as partner monitoring
(Tokunaga, 2011). Studies exploring the effect of rela-
tionship length appear to be more conclusive, indicating
that more enduring couples feel more satisfied with
their relationships (Ahmetoglu, Swami, & Chamorro-
Premuzic, 2010; Hurley & Reese-Weber, 2012) and uti-
lize the Internet less (Lenhart & Duggan, 2014). Recently,
Rahaman (2015) concluded that long-term couples pre-
sented less online conflicts, and therefore greater com-
mitment to the relationship.
In light of the above, the literature suggests that the
kind of relationship dynamics a couple establishes
online impacts their satisfaction with the relationship;
However, it could be hypothesized that this associa-
tion can differ as a function of sex, age, and relation-
ship length. The research to date on this association
has focused on specific online behaviors – like jealousy,
control, communication, and intrusiveness – only
sometimes including the effects of variables like sex
(Muise et al., 2014), age (Tokunaga, 2011), and relation-
ship length (Rahaman, 2015). Thus, we do not know
with certainty what dimensions of online couple
quality are most important to explaining relationship
satisfaction, nor what effect those three variables might
have on the association.
In Spain, research on this subject remains nascent.
Many studies have analyzed cyberbullying in young
couples (Durán-Segura & Martínez-Pecino, 2015) in
relation to offline violence (Sánchez et al., 2014), but
we know of no study that analyzed how online couple
quality contributes to relationship satisfaction in a col-
lege population. In this study, we understand relation-
ship satisfaction as an indicator of relationship quality,
and as characterized by intimacy, communication, and
a desire to stay in the relationship (Madsen & Collins,
2011). With that in mind, this study’s first objective is to
analyze online relationship quality in young adult,
Spanish couples, taking into account the effects of sex,
age, and relationship duration. The second objective is
to explore the connection between online relationship
quality and relationship satisfaction, specifically ana-
lyzing which dimensions of online couple quality (inti-
macy, jealousy, control, intrusiveness, communication,
or cyberdating practices) are most closely related to
relationship satisfaction, and to include the possible
effects of age, sex, and relationship length in the results.
According to earlier studies’ findings, we expect
that women will exhibit more online jealousy (Muise
et al., 2014) and men more cyberdating (Sánchez et al.,
2015), and that in general, positive and negative online
practices will decrease with age (Tokunaga, 2011) and
length of the relationship (Lenhart & Duggan, 2014).
Regarding the relationship between online couple
quality and relationship satisfaction, we expect that posi-
tive dynamics like online intimacy will be positively
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Relationship Quality in the Digital Age 3
associated with relationship satisfaction (Caughlin &
Sharabi, 2013; Morey et al., 2013). Since findings in
Spain about negative online couple quality have been
scant and inconclusive, we have formulated no clear
hypothesis about it. It is for that reason that the second
objective aims to further our understanding of this
association by generating new data.
Method
Participants
Initially, 793 college students at the University of Córdoba
(Spain) participated in this study. From those, 431 were
selected because they reported a current dating rela-
tionship (68.2% women; age range 18 to 26 years,
average age 21.57, SD = 1.92). Participants were selected
through convenience sampling from the departments
of Literature (10.8%), Education (26%), Law (3.9%),
Business Administration and Management (4.2%),
Occupational Science (11.4%), Veterinary and Medicine
(19.3%), Biology (3.2%), and Engineering (19.3%), heed-
ing Ferrer and collaborators’ (2006) remarks about the
impact of curriculum on romantic relationship knowl-
edge (Ferrer, Bosh, Ramis, & Navarro, 2006). The stu-
dents’ distribution by department was representative
of the university sample at large.
The sample’s characteristics and descriptive results
appear in Table 1.
Instruments
Ad hoc measures
Participants were asked about descriptive variables
including sex, age, family level of education, and hours
of Internet use.
Relationship status
Two items from the Dating Questionnaire (Connolly,
Craig, Goldberg, & Pepler, 2004) were posed. The first
gauges relationship status and was multiple-choice
(response categories as follows: a) Yes, I have a girl(boy)
friend right now; b) No, I don’t have a girl(boy)friend
right now, but I had one in the last two months; c) I don’t
have a girl(boy)friend right now, but I did more than
two months ago; d) No, I’ve never had a girl(boy)
friend). The second item measures relationship length
in weeks. The relationship status variable was applied
as a filter, such that only participants who reported a
romantic relationship at the time they completed the
questionnaire were selected for this study.
Relationship satisfaction
This was assessed using six items from the Network of
Relationships Inventory (Furman & Buhrmester, 1992),
measured on a 5-point Likert scale with anchors 0 (never)
and 4 (all the time) (e.g., “I am sure this relationship will
continue in the future ” “I tell my boy/girlfriend things
I would not want others to know”). A given partici-
pant’s relationship satisfaction score was computed
from his or her average scores.
Online couple quality
This was measured by the Cyberdating Q_A (Sánchez
et al., 2015). The questionnaire is comprised of 28 items
on a 5-point Likert scale (from never-0 to always-4)
that analyze six dimensions of online couple quality:
(1) four items about online jealousy, which is a person’s
emotional reaction and concerns about content shared
by their partner, and the possibility that he or she is
interested in someone else (e.g., “I get jealous when my
partner posts provocative photos on their social net-
work profile;” “I worry about my partner starting a
relationship with someone else via social networks”);
(2) four items about online intrusive behavior, that is,
trying to resume communication after an argument by
means of mass, insistent messages and calls (e.g., “When
we’ve had an argument and my partner blocks me,
I use a friend’s profile to leave him/her messages,
communicate by chat or on their page;” “When we’ve
had an argument and my partner blocks me, I use a
friend’s profile to leave him/her messages, communi-
cate by chat or on their page”); (3) six items about
online control, which is the process of supervising and
monitoring the partner’s profile and online activity in
his or her social network (e.g., “I have added my part-
ner’s friends as a way of controlling him/her;” “I have
opened a fake account so that my partner adds me and
I can control him/her”); (4) three items about online
intimacy, which refers to shared time on the Internet
Table 1. Sample Descriptive Statistics
Sex Men 137 (31.8%)
Women 294 (68.2%)
Father’s level of
education
None 14 (3.4%)
Elementary school 188 (45.3%)
Secondary school 110 (26.6%)
Higher education 101 (24.2%)
Other 2 (0.5%)
Mother’s level
of education
None 17 (4%)
Elementary school 192 (45.3%)
Secondary school 125 (29.3%)
Higher education 88 (20.9%)
Other 2 (0.5%)
Relationship length
(M; SD)
135.01 (104.09)
Age (M; SD) 21.57 (1.92)
Note: Father’s level of education (n = 415); Mother’s level
of education (n = 424).
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4 V. Sánchez et al.
and a feeling of closeness to one’s partner while online
(e.g., “I have a really good time with my partner when
we’re online together;” “I spend a lot of free time talk-
ing to my partner on chat”); (5) four items about cyber-
dating practices, that is, contacting and flirting with
other parties while in a relationship (e.g., “I have
‘flirted’ with other people via social networks whilst in
a relationship;” “When I meet someone I like, I quickly
give them my mobile number”); and (6) seven items
referring to emotional communication strategies, which are
tactics to manipulate or control one’s partner, or dis-
play anger or show that there is a problem (e.g., “I use
capital letters when I am annoyed with my partner;”
“I use ellipses to insinuate something to my partner”).
Scores on these online quality scales are calculated
using participants’ average scores. According to earlier
results reported by the scale’s authors, online intimacy
is considered a positive dimension of online couple
quality, and the remaining dimensions are negative.
Procedure
These self-report instruments were administered in
paper form during school time in a single 40-minute
session. Participants completed an informed consent
form, and participation was entirely voluntary. Trained
researchers executed data collection and we ensured
the confidentiality of all information collected.
Data analysis
The first step was to do two Confirmatory Factor
Analyses (CFAs) of online couple quality and relation-
ship satisfaction in order to validate the instruments
in this study’s sample. Next, means comparisons were
done as a function of gender, using Student’s t test
on each scale of online couple quality and romantic
relationship satisfaction. Subsequently, we analyzed
Pearson’s correlations between age, relationship dura-
tion, online couple quality, and relationship satisfac-
tion. These analyses were done separately for men and
women in order to differentially analyze the associa-
tion between these variables by gender. To satisfy this
study’s second objective, a multiple linear regression
was done using a step-wise method; in it, relationship
satisfaction was the dependent variable, and sex, age,
relationship length, and online couple quality were
independent variables. Moderating variables (sex, age,
and relationship length) were entered into a first block;
a second block included the dimensions of online
couple quality; and the third block added the interaction
terms of the moderating variables in online couple
quality: the interaction between sex and each dimension
of online couple quality, the interaction between age and
each dimension of online couple quality, and the interac-
tion between relationship duration and each dimension
of online couple quality. To diminish collinearity issues,
all the independent variables were first standardized;
all interactions were computed using standardized
variables. The gender variable was coded such that a
value of 0 was assigned to men, and 1 to women.
Analyses were conducted using the statistics pack-
ages Lisrel 8.72 and SPSS 23. Goodness of fit of the
models resulting from CFA was appraised based on
Satorra-Bentler’s chi-square, RMSEA, and CFI. We
determined that goodness of fit was adequate when
the value of RMSEA was under .08, and CFI over .90.
Results
Preliminary analyses
Two CFAs were tested, one for online couple quality
and another for romantic relationship satisfaction.
The model of online quality revealed a high correlation
between online jealousy and online control (r = .91),
so we test a model with five correlated factors where
those two scales merged into one factor. The remaining
scales were the same as in the original instrument:
online intrusiveness, online intimacy, cyberdating prac-
tices, and emotional communication strategies. The
results of relationship satisfaction CFA, meanwhile,
suggested freeing the correlations between error terms
in three items (see Table 2). Both models showed good-
ness of fit.
Descriptive analyses
This study’s first objective was to analyze online cou-
ple quality in romantic relationships between young
adults as a function of sex, age, and relationship length.
Table 3 presents means and standard deviations of online
quality and relationship satisfaction as a function of
sex. Evidently online intimacy, emotional communica-
tion strategies, and relationship satisfaction had the
highest means, exceeding 3 points in young men and
Table 2. Goodness of Fit Indices for Online Couple Quality and
Relationship Satisfaction
χ2 S-B df p RMSEA CFI
Online quality 759.99 314 <.001 .06 .94
Relationship satisfaction* 19.27 6 <.001 .08 .99
Note: Robust maximum likelihood estimation was
employed because the assumption of multivariate normal
distribution was not met. *Correlations between the error
terms in three items were added; they measure relationship
satisfaction. (Reliability: Online intimacy α = .68; cyberdating
practices α = .60; online intrusiveness α = .65; emotional
communication strategies α = .76; online jealousy-control
α = .81; romantic relationship satisfaction α = .87.)
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Relationship Quality in the Digital Age 5
women alike. Online intrusiveness, conversely, had the
lowest means. Significant differences were only found
on the cyberdating practices dimension (t(422) = 3.552;
p < .01, d = .35), on which men scored higher than
women on average, though the effect size was small.
Table 4 lists the correlations of age and relationship
duration with online couple quality and relationship
satisfaction, as a function of sex.
According to the results, age was negatively related to
online intimacy, cyberdating practices, online jealousy-
control, and emotional communication strategies in
men as well as women. Furthermore, it was not related
to relationship satisfaction, but was related to relation-
ship length in women. In terms of relationship dura-
tion, this was negatively associated with cyberdating
practices in both sexes. In women only, we found
that relationship length was negatively associated with
online intimacy and emotional communication strat-
egies. In men, no relationship was found between rela-
tionship duration and the other dimensions of online
couple quality. All significant correlations registered a
small or medium effect size.
Regression model of the association between online couple
quality and relationship satisfaction
Table 5 presents results from the multiple linear regres-
sion model. As in the results in the last step, Model 7,
we observed that relationship satisfaction was explained
by relationship length, online intimacy, cyberdating
practices, emotional communication strategies, online
intrusiveness, the interaction between sex and com-
munication strategies, and the interaction between
relationship duration and cyberdating practices,
with a total explained variance of 21.7% (F(7, 400) =
15.810; p = .011.
To be specific, relationship length, online intimacy, and
online intrusiveness were observed to positively corre-
late with relationship satisfaction, whereas relationship
satisfaction negatively correlated with cyberdating
Table 3. Comparison of Online Couple Quality and Relationship
Satisfaction by Gender
Men Women
Mean (SD) Mean (SD)
Online intimacy 2.49 (.90) 2.38 (1.04)
Cyberdating practices .96 (.72)** .71 (.65)
Online jealousy/control .80 (.58) .84 (.70)
Online intrusiveness .44 (.58) .43 (.59)
Emotional communication strategies 1.43 (.77) 1.50 (.86)
Relationship satisfaction 3.29 (.70) 3.34 (.71)
Note: **p < .01; *p < .05.
Table 4. Correlations between Age, Relationship Length, Dimensions of Online Couple Quality, and Relationship Satisfaction in Young Men and Women
Relationship
length
Online
intimacy
Cyberdating
practices
Online
jealousy/control
Online
intrusiveness
Online emotional
communication strategies
Relationship
satisfaction
Age .30** (.32**) –.21** (–.19**) –.16* (–.21**) –.21** (–.12*) –.17** (–.12*) –.17** (–.31**) –.06 (.02)
Relationship length - –.03 (–.18**) –.20* (–.20**) .01 (–.11) –.03 (–.02) –.05 (–.20**) .17 (.23**)
Online intimacy - .07 (.20**) .09 (.19**) –.04 (.19**) .37** (.49**) .18** (.21**)
Cyberdating practices - .51** (.49**) .19** (.36**) .43** (.46**) –.46** (–.30**)
Online jealousy/control - .54 (.57**) .60** (.53**) –.20** (–.17**)
Online intrusiveness - .41** (.47**) –.06 (.07)
Emotional communication strategies - –.15* (–.11*)
Note: **p < .01; *p < .05. Correlations in men appear sans parentheses.
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6 V. Sánchez et al.
Table 5. Relationship Satisfaction Model Resulting from Hierarchical Multiple Linear Regression
Models B (SE) b CI t p
Model 1 (R2 = .048) Relationship length .15 (.03) .22 (.09, .22) 4.544 .001
Model 2 (R 2= .114) Relationship length .18 (.03) .25 (.11, .24) 5.384 .001
Online intimacy .18 (.03) .26 (.12, .25) 5.472 .001
Model 3 (R2 = .170) Relationship length .15 (.03) .21 (.08, .21) 4.539 .001
Online intimacy .20 (.03) .29 (.14, .27) 6.279 .001
Cyberdating practices –.17 (.03) –.25 (–.24, –.11) –5.250 .001
Model 4 (R2 = .180) Relationship length .14 (.03) .21 (.08, .21) 4.443 .001
Online intimacy .23 (.04) .33 (.16, .30) 6.648 .001
Cyberdating practices –.15 (.04) –.21 (–.21, –.08) –4.198 .001
Emotional communication strategies –.08 (.04) –.12 (–.16, –.01) –2.155 .032
Model 5 (R2= .189) Relationship length .14 (.03) .20 (.08, .20) 4.323 .001
Online intimacy .24 (.04) .34 (.17, .31) 6.876 .001
Cyberdating practices –.15 (.04) –.22 (–.22, –.08) –4.373 .001
Emotional communication strategies –.12 (.04) –.17 (–.20, –.04) –2.888 .004
Online intrusiveness .08 (.04) .11 (–.01, .15) 2.165 .031
Model 6 (R2 = .205) Relationship length .14 (.03) .21 (.08, .21) 4.525 .001
Online intimacy .23 (.04) .33 (.16, .30) 6.602 .001
Cyberdating practices –.16 (.03) –.23 (–.23, –.09) –4.593 .001
Emotional communication strategies –.25 (.06) –.35 (–.36, –.13) –4.065 .001
Online intrusiveness .08 (.04) .11 (.01, .15) 2.166 .031
Sex*Emotional communication strategies .20 (.07) .23 (.06, .33) 2.843 .005
Model 7 (R2 = .216) Relationship length .15 (.03) .22 (.09, .22) 4.815 .001
Online intimacy .23 (.04) .32 (.16, .29) 6.552 .001
Cyberdating practices –.14 (.04) –.20 (–.21, –.07) –4.104 .001
Emotional communication strategies –.24 (.06) –.34 (–.35, –.12) –3.936 .001
Online intrusiveness .07 (.04) .11 (.01, .14) 2.115 .035
Sex*Emotional communication strategies .18 (.07) .21 (.05, .32) 2.656 .008
Relationship length*Cyberdating P. .08 (.03) .11 (.01, .14) 2.403 .017
practices and emotional communication strategies.
Finally, to make the interaction terms easier to inter-
pret, we carried out a simple analysis of slopes, finding
that for the interaction between sex and communica-
tion strategies (Figure 1), the slope was significant in
men only (t = –3.795, p = .001; for the women it was
t = –.435, p = .664) such that the more communication
strategies male participants reported, the lower their
satisfaction with the relationship.
On another note, regarding the interaction between
cyberdating practices and relationship duration
(Figure 2), the slope was only significant in shorter-
term relationships (t = –2.214, p = .027; for longer
relationships it was t = –.717, p = .474). Accordingly,
greater use of cyberdating practices was associated
with lower relationship satisfaction in shorter rela-
tionships; that effect was not produced in longer
relationships.
Figure 1. Interaction effect between sex and emotional online
communication on relationship satisfaction.
Figure 2. Interaction effect between relationship length and
cyberdating practices on relationship satisfaction.
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Relationship Quality in the Digital Age 7
Discussion
In recent years, we have seen a rising number of
studies interested in how young people incorporate
new technologies into their romantic relationships
(Fox & Warber, 2013; Morey et al., 2013; Stewart et
al., 2014). However the influence of those behaviors
on couples’ lives is still up for debate, especially in
Spain, where studies on this have been few. Therefore,
this study aimed to explore relationship quality online
in young adults, and its association with overall rela-
tionship satisfaction. In line with earlier studies that
found differences on some measures of online couple
quality as a function of sex (Muise et al., 2014), age
(Tokunaga, 2011), or relationship length (Hurley &
Reese-Weber, 2012), this study also analyzed those
three variables as potential moderators in the rela-
tionship between online quality and relationship
satisfaction.
Descriptive analyses showed that these young
people had moderate levels of online intimacy and
communication strategies, and low online jealousy,
intrusiveness, and control. These results confirm, first,
that a couple’s life also develops in the space of virtual
media (Fox & Warber, 2013), and second, that positive
relationship dynamics are more common than nega-
tive, which is consistent with research examining rela-
tionship quality in couples off-line (Sánchez et al., 2014).
Analysis of a potential gender effect on results revealed
differences only in cyberdating practices, with young
men more than women reporting that they flirt with
various people while in a relationship, and empha-
sizing physique as the most important feature of peo-
ple they meet on the Internet. These results are similar
to findings in adolescent populations (Sánchez et al.,
2015), which some authors have interpreted as a
greater tendency for adolescent boys and young men
to engage in sensation-seeking behaviors and risk-
taking (Hertlein & Stevenson, 2010); that would logi-
cally increase in an environment where anonymity and
privacy are attained more easily than off-line (Utz &
Beukeboom, 2011). Nonetheless, it might also reflect
differing male and female interpretations of what they
can and cannot do while in a relationship. Along those
lines, studies about beliefs and attitudes about love
have suggested that females still have more romantic,
conservative ideas about love, while males more openly
accept flirting and infidelity (Espinoza, Correa, & García,
2014). The lack of differences on other scales, namely
the negative ones, contradicts earlier findings that
females exhibit higher levels of jealousy (Elphinston &
Noller, 2011), which would lead them to deploy more
partner-monitoring and -control behaviors (Muise
et al., 2014). These differences could be explained by
methodological aspects such as different designs and
measurement instruments. For example, Muise et al.
(2014) used an experimental design to test whether
jealousy levels predicted monitoring and surveillance
behavior after seeing the partner’s Facebook posts.
In contrast, the present study was survey-based. In
relation to measurements, in our study, jealousy and
control dimensions were considered part of a single
dimension; earlier studies examined them sepa-
rately even though their authors concluded that the
two scales are strongly correlated (Elphinston &
Noller, 2011; Muise et al., 2014). Future research
could confirm whether the lack of differences
between males and females on this dimension is due
to methodology, or the presence of cultural differ-
ences, in love styles for instance (Rohman, Führer, &
Bierhoff, 2016).
Correlation analyses showed that age and relation-
ship length were negatively associated with online
couple quality scales, but that effect size was small.
These results are in line with past studies where less
partner monitoring was observed in older participants
(Tokunaga, 2011); and more stable couples presented
less flirting behavior and infidelity (Blow & Harnett,
2005), as well as less use of new ICTs (Pew Research
Centre, 2014). These results reinforce the hypothesis
that the online world becomes less important in more
stable couples during the transition to adulthood, a
tendency that was not found, however, in adolescent
populations (Sánchez et al., 2015). It is worth noting
that the correlations were small, suggesting that while
there was in fact a trend, these variables’ association
was not very strong. Future studies might extend par-
ticipants’ age range and test whether the online world’s
influence on the couple’s life continues to decrease
significantly in older participants.
Finally, multiple linear regression analysis showed
that online quality was related to overall relationship
satisfaction. In particular, satisfaction was explained
positively by online intimacy and intrusiveness, and
negatively by cyberdating and emotional communica-
tion strategies. These results confirm that the relation-
ship dynamics unfolding in online media impact a
young person’s satisfaction with his or her partner,
and highlight the connection between life on- and
off-line (Subrahmanyan & Šmahel, 2011). Accordingly,
positive relationship dynamics that take place in online
media, like spending time together on the Internet and
having greater online intimacy, are associated with
higher relationship satisfaction (Morey et al., 2013),
while higher levels of cyberdating and emotional com-
munication strategies were associated with lower rela-
tionship satisfaction. It is interesting to consider that
online jealousy did not enter into our regression
equation, in contrast to earlier studies on this subject
(Elphinston & Noller, 2011), and despite the association
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8 V. Sánchez et al.
between the two variables found in correlation analyses,
in females only. These results seem to indicate that
even though the two variables are related, their influ-
ence on relationship satisfaction is not as important as
other measures of online relationship quality. From
that point of view, we believe that jointly analyzing the
influence of different online quality scales on overall
relationship satisfaction, as we did in this study, repre-
sents an advance over prior studies because it allowed
for deeper analysis of how important each of the vari-
ables analyzed was.
Online intrusiveness was associated with higher
relationship satisfaction, contradicting the findings
of past studies relating it to negative relationship out-
comes such as dating aggression (Sánchez et al., 2014).
Some studies have tried to further explore the associa-
tion between intrusiveness and relationship satisfac-
tion by analyzing possible mediating variables, such as
attachment styles. Lavy, Mikulincer, and Shaver (2013)
found that intrusiveness was associated with higher
relationship satisfaction in people with more insecure
attachment styles, with intrusive behaviors lowering
uncertainty (Stewart et al., 2014), which in turn increased
perceived relationship satisfaction. Future research
could confirm this meditational role of attachment
style in the association, and the role of the other dyad
member’s reactions to such behaviors. We could
hypothesize that one partner’s type of response to
an insecure and intrusive boy/girlfriend would rein-
force his/her online behavior and thus increase his/
her relationship satisfaction.
The negative impact of cyberdating and emotional
communication strategies on relationship satisfac-
tion confirms others studies’ findings about flirting
and infidelity in virtual contexts (Cravens et al., 2013)
and about the role of online conflict in relationship
decline for both sexes (Clayton, 2014; Rahaman, 2015).
These results were also moderated by gender and
relationship length. Thus, while relationship length
was associated with higher relationship satisfaction,
it also moderated the association between cyberdat-
ing and satisfaction, such that cyberdating behaviors
were associated with low relationship satisfaction in
shorter relationships, but not in the context of longer
relationships. These results are consistent with what
Clayton, Nagurney, and Smith reported (2013); those
authors suggested that flirting behavior and com-
munication with ex-partners had a more negative
impact on relationships less than three years than in
more enduring couples. That would indicate that in
less established couples – with less maturity, trust,
and commitment – certain online behaviors (like the
ones this study analyzed) negatively affect the rela-
tionship. In more stable, solid couples, meanwhile,
those online behaviors are not important enough to
significantly influence the overall value young people
place on their dating relationships.
Gender ultimately moderated the negative relation
between emotional communication strategies and rela-
tionship satisfaction such that men who make greater
use of those strategies are less satisfied with their rela-
tionships. Given the nature of this scale, which taps
communication strategies geared toward manipu-
lating or controlling one’s partner, or displaying anger
when problems arise, these results suggest that when
young men deploy these strategies, they are ineffec-
tive, which would explain their low levels of relation-
ship satisfaction. Future studies could confirm this
hypothesis and, using information from both members
of the romantic dyad, determine how one partner
using these communication strategies affects the cou-
ple’s relationship dynamic, and therefore relationship
satisfaction.
By way of summary, this study’s results provide
evidence that the online context matters to young adults
in dating relationships, a connection which is moder-
ated by sex and relationship length. We analyzed posi-
tive as well as negative relationship dynamics so we
could take a closer look at the online dynamics that
impact relationship satisfaction the most, in one of the
first studies conducted in this area, especially in Spain.
This study was not, however, without various limi-
tations that warrant consideration. The first is a matter
of methodological design. This study’s cross-sectional
design makes it less possible to establish causal rela-
tions between variables; so future studies should
utilize longitudinal designs to ascertain with greater
accuracy the direction of the relationship among the
study’s variables. Next, the present study’s accidental
sampling method and sample size both limit the gen-
eralizability of results. Therefore we should broaden
the study to include other Spanish universities using
stratified random sampling. On another note, the very
construct of online couple quality remains a challenge
for the scientific community. Measures validated in
different countries need to be developed in order to
determine whether the differences observed might be
due to cultural differences. Most studies have devel-
oped ad hoc measures of concrete negative behaviors
like jealousy or controlling partner behavior, setting
aside measures of positive online couple quality. Future
studies should take a closer look at the range of posi-
tive behaviors couples can implement online, and how
those impact relationship satisfaction. In closing, it is
important for future studies to include perspective
from both members of the couple, and different mod-
erating variables – like attachment style and beliefs
and attitudes about love – to better understand these
variables’ role in the association between life online
and off.
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Relationship Quality in the Digital Age 9
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