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A longitudinal study of the association between Compulsive Internet use
and wellbeing
q
Linda D. Muusses
a,
, Catrin Finkenauer
b,1
, Peter Kerkhof
c,2
, Cherrie Joy Billedo
c
a
Department of Social and Organizational Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
b
Department of Clinical Child and Family Studies, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
c
Department of Communication Science, VU University Amsterdam, Buitenveldertselaan 3, 1082 VA Amsterdam, The Netherlands
article info
Article history:
Available online 11 April 2014
Keywords:
Compulsive Internet use
Psychological wellbeing
Happiness
Depression
Loneliness
abstract
Objective: Compulsive Internet Use (CIU) has been linked to lower wellbeing, especially among adoles-
cents. Yet, questions regarding the directionality of this association remain unanswered: CIU may influ-
ence wellbeing and vice versa. Theoretically, both directions are plausible, yet so far no studies have
examined the directionality of these effects among adults. This article aims to shed light on the direction-
ality of the relation between CIU and both positive and negative wellbeing, using a prospective, longitu-
dinal sample of adults (n= 398).
Methods: Over the course of four years, participants completed five assessments of their CIU and both
positive and negative indicators of wellbeing. Participants were married couples who were recruited in
the municipalities where they were married.
Results: CIU predicted increases in depression, loneliness and stress over time, and a decrease in happi-
ness. No effect of CIU on the change in self-esteem was found. Further, happiness predicted a decrease in
CIU over time.
Conclusions: The results suggest CIU lowers wellbeing. This is important given that lowered wellbeing
may affect health. Happiness is suggested to be a buffer for developing CIU.
Ó2014 Elsevier Ltd. All rights reserved.
1. Introduction
An increasing number of people finds it hard to regulate their
Internet use. As a result, they develop symptoms of compulsive
Internet Use (CIU): Internet use with addictive characteristics,
including withdrawal reactions when Internet use is impossible
(e.g., unpleasant emotions), lack of control over Internet use (e.g.,
use of the Internet despite the intention or desire to stop or to de-
crease the use), and cognitive and behavioral preoccupation with
the Internet (Van den Eijnden, Meerkerk, Vermulst, Spijkerman, &
Engels, 2008). Many studies have shown that CIU is associated with
lower psychological wellbeing (Chou, Condron, & Belland, 2005;
Widyanto & Griffiths, 2006). However, there is no consensus on
the directionality of this association (e.g., Armstrong, Phillips, &
Saling, 2000; Ha et al., 2007; Sum, Mathews, Hughes, & Campbell,
2008). While some researchers suggest that CIU causes lower well-
being (e.g., Moody, 2001), others argue that low wellbeing causes
an increase in CIU (e.g., LaRose, Lin, & Eastin, 2003). Although both
sides make theoretically compelling cases, it remains unclear
which direction has the strongest effects over time.
Almost all studies on CIU and wellbeing use samples of adoles-
cents or college students. We know surprisingly little about the
link between CIU and wellbeing among adults (Byun et al., 2009;
Chou et al., 2005; Kuss & Griffiths, 2011; Tokunaga & Rains,
2010; Widyanto & Griffiths, 2006). This is surprising, given that,
for example, in the Netherlands, a country which has the 8th high-
est Internet penetration rate in the world, (InternetWorldStats.,
2011), adults are the largest group of Internet users (Centraal
Bureau voor de Statistiek [Central Statistical Office]., 2013). Fur-
thermore, the 78.15% of the Dutch population is over 18 years of
age, and only 7.11% of the Dutch population is a student of voca-
tional or academic education (Centraal Bureau voor de Statistiek
[Central Statistical Office]., 2014). The present study aims to ex-
plore the long-term directionality of the association between CIU
and different indicators of wellbeing, using five consecutive sur-
veys that were conducted over a four year period among adults.
Psychological wellbeing, sometimes referred to as psychological
health or subjective wellbeing, is the evaluation of one’s quality of
http://dx.doi.org/10.1016/j.chb.2014.03.035
0747-5632/Ó2014 Elsevier Ltd. All rights reserved.
q
This research was supported by a Grant to the third author from the
Netherlands Organization for Scientific Research (No. 452-05-322) awarded to
Catrin Finkenauer.
Corresponding author. Tel.: +31 (0)205980132.
E-mail addresses: l.d.muusses@vu.nl (L.D. Muusses), c.finkenauer@vu.nl
(C. Finkenauer), p.kerkhof@vu.nl (P. Kerkhof), c.j.billedo@vu.nl (C.J. Billedo).
1
Tel.: +31 (0)205988857.
2
Tel.: +31 (0)205986815.
Computers in Human Behavior 36 (2014) 21–28
Contents lists available at ScienceDirect
Computers in Human Behavior
journal homepage: www.elsevier.com/locate/comphumbeh
life or life satisfaction. It is positively related to physical health
(Mechanic & Hansell, 1987) and better social functioning (Diener,
1984; Diener, Suh, Lucas, & Smith, 1999; Okun, Stock, Haring, &
Witter, 1984). Given the independent contribution of positive
and negative aspects of wellbeing for health and human function-
ing, psychological wellbeing is considered as comprising both
dimensions. Typically, happiness, depression, stress, loneliness,
and self-esteem are indicators of psychological wellbeing (Augner
& Hacker, 2011; Crocker, Luhtanen, Blaine, & Broadnax, 1994;
Kang, 2007). The present study recognizes the multiple dimensions
of wellbeing, and includes these diverse indicators to examine
their relation with CIU.
1.1. Wellbeing and Compulsive Internet use
CIU is often described as being incapable to control one’s Inter-
net use (Chou & Hsiao, 2000; Johansson & Götestam, 2004). Related
terms in the literature are Internet addiction (e.g., Young, 1998),
problematic (e.g., Caplan, 2002; Morahan-Martin & Schumacher,
2000) or pathological Internet use (e.g., Davis, 2001), and Internet
dependence (e.g., Wang, 2001). Several studies have shown that
CIU is negatively associated with different indicators of wellbeing:
Compulsive Internet users are more depressed, stressed and lonely,
less happy and have lower self-esteem (for recent reviews and
meta-analyses see Byun et al., 2009; Chou et al., 2005; Tokunaga
& Rains, 2010; Widyanto & Griffiths, 2006).
Longitudinal studies yield mixed results. In a study of people’s
first two years with a home Internet connection, greater use of
the Internet increased depression and loneliness (Kraut et al.,
1998). However, in the third year, these effects had dissipated
(Kraut et al., 2002). This begs the question what kind of results
can be expected now that people have been using the Internet
for almost twenty years, and how wellbeing relates to compulsive,
rather than frequent, use of the Internet.
In the, to our knowledge only longitudinal study of CIU and
wellbeing, incoming freshmen were recruited for a three-wave pa-
nel study in the summer before their first year of college (Tokuna-
ga, 2012). Results showed that psychosocial problems such as
loneliness and depression predicted later CIU, which in turn pre-
dicted later functional impairment (i.e., vocational impairment,
impairment in friendships and in family relationships). All three
waves were administered within half a year, from the summer be-
fore freshmen started college to the end of the first semester. At
this time these young people probably underwent important life
changes (e.g., moving away from their parents, living in a new
environment), which may have affected the results and which lim-
its the generalizability of these findings. Finally, a 2-wave study
among adolescents aged 12–15 found that Internet use for com-
munication purposes predicted an increase in depression six
months later (van den Eijnden et al., 2008). Surprisingly, it also
yielded an opposite effect: loneliness predicted a decrease of com-
puter-mediated communication over time. Taken together, these
results suggest that both directions of influence are plausible. Over
time, CIU might affect wellbeing, but wellbeing might also affect
CIU. However, there is no consensus in the literature.
1.2. Directionality of effects
The literature provides theoretical reasons for both directions of
influence. Wellbeing might affect CIU because people with low
self-esteem may develop a preference for online over offline social
interactions, which they experience as a safer way of expressing
themselves (Caplan, 2003, 2006). The preference for online interac-
tions, in turn, may increase their dependence on the Internet,
leading to CIU. Further, the consumption of different media can alter
prevailing mood states, and people’s selection of specific kinds of
media content often serves to regulate their mood (Zillmann,
1988). Depressed individuals may therefore create media habits to
alleviate depressed moods, leading to CIU (LaRose et al., 2003). Sim-
ilarly, people may develop CIU because they use the Internet to dis-
sociate and protect themselves from memories of loss, neglect, and
abuse experienced in childhood (Schimmenti, Guglielmucci, Barba-
sio, & Granieri, 2012; Schimmenti, Passanisi, Gervasi, Manzella, &
Famà, 2013). However, the opposite effect has also been described.
CIU might affect wellbeing because time spent online with weak
ties, such as acquaintances, might substitute time spent on strong
ties, such as family members (Nie & Erbring, 2000; Vitalari, Venk-
atesh, & Gronhaug, 1985). CIU may also negatively affect other life
outcomes, including school or work performance. Such outcomes
can isolate individuals from healthy social activities and increase
their feelings of loneliness (Kim, LaRose, & Peng, 2009; Tokunaga,
2012). Finally, certain types of online content and online interac-
tions may affect wellbeing. To illustrate, excessive use of social med-
ia might decrease one’s self-esteem or lead to depression, because it
provides content that can be used for social comparison (Pantic et al.,
2012). Thus, according to the literature, both directional paths seem
plausible. It may even be the case that they mutually reinforce each
other, in that lower wellbeing may lead to more CIU, which in turn
may decrease wellbeing even further. The present study sought to
examine the directionality of the link between CIU and wellbeing.
1.3. The present study
Our study aims to shed light on the long-term directionality of
the link between CIU and psychological wellbeing. Based on the
existing literature, we expected to replicate the negative associa-
tion between CIU and wellbeing, and extend these findings by
exploring the long-term effects of CIU and wellbeing. Given that
positive and negative indicators are partly independent of one an-
other (Huppert & Whittington, 2003), and psychological wellbeing
is considered a multi-dimensional construct, we examine both
negative (i.e., depression, stress, and loneliness) and positive (i.e.,
happiness and self-esteem) indicators of wellbeing.
Because the literature describes effects in both directions, we
pose the research question: What are the long-term effects of
CIU on wellbeing, and of wellbeing on CIU? To examine these asso-
ciations as well as the directionality of effects, we use data from a
5-year prospective study among married adult couples. These cou-
ples were recruited through the municipalities in which they were
married, and are representative of Dutch married couples. Married
people make up 41.48% of all people in the Netherlands (Centraal
Bureau voor de Statistiek, 2013). Therefore it is an important and
representative group to study. Furthermore, CIU has adverse social
and relational effects; not only does it contributes to greater loss of
self-control, but it also undermines trust (Muusses, Finkenauer,
Kerkhof, & Righetti, 2013). These examples show that married peo-
ple are at risk for CIU related issues, which begs the question of
how CIU and wellbeing are related in married people.
The longitudinal design of our study allows us to examine the
long-term directional effects of CIU and wellbeing. Because the
data is dyadic, we use analyses that correct for this non-indepen-
dence of the data. Furthermore, we provide across-partner correla-
tions for the variables of interest. Although our study is
correlational, the results will contribute to our understanding of
the importance of both directions.
2. Method
2.1. Participants
The data used for this study are derived from the VU University
Panel on Marriage and Well-Being, a 5-wave, longitudinal study
22 L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28
among newlywed couples in the Netherlands. In the five waves
199, 195, 190, 157, and 140 newlywed couples participated,
respectively. At the first wave, the mean age of husbands (coded
as 0) was 32.07 years (SD = 4.86) and the mean age of wives (coded
as 1) was 29.20 years (SD = 4.28). Couples had been romantically
involved on average for 5.71 years (SD = 3.03) and had been living
together for an average of 3.81 years (SD = 2.31). The first wave of
this study took place about one month after marriage (for more
information, including ethical board, consent and assent proce-
dures, see Finkenauer, Kerkhof, Righetti, & Branje, 2009; Pollmann
& Finkenauer, 2009). Nearly all the couples (98.5% of the husbands
and 96.4% of the wives) were Dutch.
2.2. Procedure
Participants were recruited via the municipalities in which they
got married. The municipalities were average sized Dutch cities.
Selection criteria were that (1) for all participants this was their
first marriage, (2) at the first data collection, couples had no chil-
dren from this marriage or from previous relationship partners,
(3) both partners were between 25 and 40 years old, and (4) cou-
ples were heterosexual. Nineteen percent of the couples who were
sent a letter of invitation to participate in the study agreed to par-
ticipate. This response rate is similar to other studies recruiting
participants from public records in the United States (e.g., Kurdek,
1993).
The study was introduced to participants as a study on the
influence of personal dispositions, behavior in the relationship,
and partner perception on marital wellbeing in the first years of
marriage. Wave one took place in 2005, 1–2 months after they
got married. The following waves took place at one-year intervals.
At the data collections, both members of the couple separately
filled out an extensive questionnaire at home in the presence of
a trained interviewer, who visited them at home. The interviewer’s
presence ensured that partners independently completed the
questionnaires without consulting each other. The questionnaire
took about 90 min to complete. At each data collection, after they
completed the questionnaire, couples received 15 Euros and a
small gift (e.g., pen-set, gift voucher). To increase commitment,
we sent birthday cards to each participant. Also, participants were
able to get updates about the progress of the study via the study
website.
2.3. Measures
All measures were assessed in all five waves except loneliness,
which was only measured in the last two waves. Therefore, all
analyses concerning loneliness include only waves 4 and 5. All
other analyses include all five waves. For details on the study see
Finkenauer, Wijngaards-de Meij, Reis, and Rusbult (2010), Kerkhof,
Finkenauer, and Muusses (2011), Muusses et al. (2013). Only scales
relevant to the present hypotheses and research question are
described below.
2.3.1. Measures of Internet use
Compulsive Internet Use (CIU) was assessed using a shortened
version of the Compulsive Internet Use Scale (CIUS; Meerkerk,
van den Eijnden, Vermulst, & Garretsen, 2009). For a description
of the shortened scale and data supporting the reliability and valid-
ity of the scale, see Muusses et al. (2013). The items are: ‘‘How
often.... (1) do you find it difficult to stop using the Internet when
you are online? (2) do you continue to use the Internet despite
your intention to stop? (3) do you prefer to use the Internet instead
of spending time with others (e.g., partner, children, parents,
friends)? (4) are you short of sleep because of the Internet? (5)
do you feel restless, frustrated, or irritated when you cannot use
the Internet?’’ (
a
for the five waves respectively .74, .81, .79, .82
and .84) (for descriptive information, see Tables 1 and 2 and Fig. 1).
To assess Frequency of Internet use, participants reported how
many days per week and how many hours per day during these
days they used the Internet for private purposes (as opposed to
using the Internet for work). The product of the two questions re-
sulted in a score for the frequency of Internet use, ranging from 0 to
686 (h). Theoretically, the measure should have a maximum value
of 168 (7 days in a week 24 h in a day). Consequently, the three
participants who scored higher than the theoretical maximum
probably misunderstood the question. Therefore, for the analyses
that included frequency of Internet use, values higher than the the-
oretical maximum were replaced with missing values. Recoding
the outlier values changed only 1 of the possible 28 results. The
remaining 27 results did not change in significance or direction.
2.3.2. Measures of personal wellbeing
Happiness was assessed using Lyubomirsky and Lepper’s (1999)
Subjective Happiness Scale. The questionnaire contained four
items. The items are: (1) ‘‘In general, I consider myself:’’ (1 = not
a very happy person to 7 = a very happy person);(2) ‘‘Compared to
most of my peers, I consider myself:’’ (1 = less happy to 7 = more
Table 1
Means and SD’s of the variables over time.
Wave Internet frequency CIU Happiness Depression Stress Loneliness Self-esteem
Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
1 7.98 (11.51) 1.57 (.54) 5.72 (.86) 1.35 (.30) 2.06 (.49) 4.05 (.44)
2 18.3 (75.68) 1.62 (.61) 5.67 (.91) 1.37 (.32) 2.11 (.49) 4.08 (.46)
3 12.35 (53.25) 1.63 (.54) 5.69 (.86) 1.36 (.31) 2.12 (.48) 4.12 (.47)
4 15.15 (59.57) 1.61 (.57) 5.66 (.85) 1.36 (.29) 2.05 (.49) 1.21 (.30) 4.10 (.43)
5 17.51 (64.33) 1.60 (.57) 5.60 (.91) 1.36 (.30) 2.08 (.48) 1.21 (.31) 4.11 (.50)
Note: CIU = Compulsive Internet Use; Happiness = Subjective Happiness Scale; Depression = Center for Epidemiologic Studies Depression Scale; Stress = Perceived Stress
Scale; Loneliness = Loneliness Scale; Self-Esteem = Self-Esteem Scale.
Table 2
Within and across partner correlations, means and SD’s for the assessed variables.
Variable 1 2 3 4 5 6
CIU .04 .02 .01 .11
**
.03 .03
Happiness .23
**
.08
**
.03 .05 .04 .04
Depression .16
**
.48
**
.03 .03 .01 .01
Stress .17
**
.49
**
.67
**
.10
**
.05 .01
Loneliness .15
**
.39
**
.32
**
.26
**
.18
**
.04
Self-esteem .16
**
.57
**
.49
**
.51
**
.28
**
.04
M 1.60 5.67 1.36 2.08 1.21 4.09
SD .57 .87 .30 .49 .30 .46
Note: CIU = Compulsive Internet Use; Happiness = Subjective Happiness Scale;
Depression = Center for Epidemiologic Studies Depression Scale; Stress = Perceived
Stress Scale; Loneliness = Loneliness Scale; Self-Esteem = Self-Esteem Scale.
Note: The correlations on and above the diagonal are across partner correlations
between model variables. The correlations below the diagonal line are within-
individual correlations.
p< .05.
**
p< .01.
L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28 23
happy);(3) ‘‘Some people are generally very happy. To enjoy life
regardless of what is going on, getting the most out of everything.
To what extent does this characterization describe you?’’ (1 = not at
all to 7 = a great deal);(4) ‘‘Some people are generally not very hap-
py. Although they are not depressed, they never seem as happy as
they might be. To what extent does this characterization describe
you?’’ (1 = not at all to 7 = a great deal).The scale showed good reli-
ability in our study (Cronbach’s
a
for men = .78, .84, .78; .75, and
.82; and for women = . 76, .81, .79, .77, and .84 for all five waves
respectively) and has good validity (Lyubomirsky & Lepper, 1999).
Depression was assessed using Radloff’s (1977) Center for Epide-
miologic Studies Depression Scale (CES-D Scale). The scale con-
tained 20 items, rated on a 4-point Likert scale; for example,
‘‘During the past week, I was bothered by things that usually don’t
bother me.’’ [1 = Rarely or non of the time (less than 1 day);2=Some
or a little of the time (1–2 days);3=Occasionally or a moderate
amount of time (3–4 days);4=Most or all of the time (5–7 days)].
The scale showed good reliability (Cronbach’s
a
for men = .71,
.87, .83, .78, and .85; and for women = .85, .85, .87 .87, and .85
for all five waves respectively).
Stress was assessed using a short form of the Cohen, Kamarck,
and Mermelstein (1983) Perceived Stress Scale (PSS). The question-
naire contained 11 items. An example item is ‘‘In the last month,
how often have you been upset because of something that hap-
pened unexpectedly.’’ (1 = never to 5 = very often). The scale
showed good reliability (Cronbach’s
a
for men = .77, .85, .81; .87,
and .85; and for women = .84, .86, .87, .86, and .88 for all five waves
respectively).
Self-esteem was assessed using the Rosenberg’s (1965) Self-Es-
teem scale. The scale contained 10 items, rated on a 5-point Likert
scale; for example, ‘‘I feel that I’m a person of worth, at least on an
equal plane with others.’’ (1 = does not apply to 7 = does apply). The
scale showed good reliability (Cronbach’s
a
for men = .78, .86, .85,
.85, and .82; and for women = .79, .84, .87 .87, and .86 for all five
waves respectively).
Loneliness was assessed only in wave 4 and 5, using the De Jong
Gierveld and van Tiburg (1999) Loneliness Scale, measuring over-
all, emotional, and social loneliness. The scale contained 11 items.
An example item is ‘‘In the last month, how often have you been
upset because of something that happened unexpectedly.’’
(1 = yes,2=more or less,3=no). The scale showed good reliability
(Cronbach’s
a
for men = .77 and .81; and for women = .87 and .88
for both waves respectively).
Finally, to be able to control for Commitment, we assessed com-
mitment using the Rusbult, Martz, and Agnew (1998) Scale (8
items; Cronbach’s
a
for men = .86, .90, .93, .93, and .94; and for wo-
men = .91, .91, .93 .93, and .93 for all five waves respectively).
2.4. Strategy of analysis
Data provided by a given participant on multiple research occa-
sions are non-independent, as is data that results from two part-
ners in a given relationship. Accordingly, we analyzed our data
using hierarchical linear modeling (Raudenbush & Bryk, 2002). This
technique accounts for the nonindependence of observations by
simultaneously examining variance associated with each level of
nesting, thereby providing unbiased hypothesis tests. Following
recommended procedures for couples data, we represented inter-
cept terms as random effects and represented slope terms as fixed
effects (Kenny, Mannetti, Pierro, Livi, & Kashy, 2002).
To test for longitudinal effects, we performed multilevel residu-
alized lagged regression analyses. In these analyses, we regressed
each criterion variable onto the earlier predictor and the earlier
measure of the criterion. These analyses allowed us to assess the
extent to which the predictor variable accounts for the change in
the criterion over time. We performed lagged analyses, in which
we simultaneously predict Time 2 criteria from Time 1 predictors,
Time 3 criteria from Time 2 predictors, Time 4 criteria from Time 3
predictors and Time 5 criteria from Time 4 predictors.
3
3. Results
3.1. Descriptive analyses
As suggested by the literature (Chou et al., 2005), gender was
significantly associated with CIU indicating that men were more
likely to use the Internet compulsively than women (see Table 3).
We also found some associations between gender and the wellbe-
ing variables. Consistent with the literature (Kessler, McGonagle,
Swartz, Blazer, & Nelson, 1993; Kling, Hyde, Showers, & Buswell,
1999; Lundberg, 2002), women reported more depression and
stress and less self-esteem, but we found no associations with gen-
der for happiness and loneliness (see Table 3).
The means and standard deviations as well as the individual
and cross-partner correlations of the main variables are presented
in Table 2. Apart from the main variables’ significant within per-
sons correlations, it is interesting to note that CIU in one partner
is positively associated with the other partner’s stress. Put differ-
ently, the more one partner uses the Internet compulsively, the
more stressed is the other partner (and vice versa). Furthermore,
1st wave 2nd
wave
3rd
wave
4th
wave
5th
wave
Internet frequency
CIU
Happiness
Depression
Stress
Loneliness
Self-esteem
Fig. 1. Standardized mean values of the main variables over time. Note: CIU = Compulsive Internet Use; Happiness = Subjective Happiness Scale; Depression = Center for
Epidemiologic Studies Depression Scale; Stress = Perceived Stress Scale; Loneliness = Loneliness Scale; Self-Esteem = Self-Esteem Scale.
3
The results for the longitudinal dyadic data using hierarchical linear models and
lagged analyses are displayed in beta’s. These beta’s can be considered measures of
effect. Effect sizes for these results were not provided, because to our knowledge, no
suitable measure of effect size is commonly used with these types of analyses.
24 L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28
happiness, stress and loneliness are correlated within couples. That
is, when one partner is happy, stressed, or lonely, the other partner
is more likely to be happy, stressed, or lonely too.
Apart from suggesting gender effects for CIU and the wellbeing
effect separately, the literature does not suggest that the relations
between CIU and wellbeing differ for men and women, and hus-
band-wife dyads should thus be treated as indistinguishable. To
test if the data supports this assumption, we performed prelimin-
ary analyses to explore possible moderation by participant gender,
by including main effects and interaction effects for gender to the
analyses testing all possible main effects of the variables. Impor-
tantly, none of the 15 possible associations of the main variables
of interest changed in direction or level of significance when add-
ing gender as a main effect or interaction term. Therefore, we omit-
ted participant gender from the analyses and treated dyad
members as indistinguishable.
To ensure that the relation between CIU and the indicators of
wellbeing was not attributable to commitment, we also controlled
for commitment in our main analyses. None of the associations
changed in significance or direction (positive or negative), indicat-
ing that commitment did not change the relation between CIU and
wellbeing.
3.2. Predicting key model variables cross-sectionally
Using hierarchical linear modeling, the critical relations were
tested for all five time points (Time 1, 2, 3, 4 and 5) simultaneously,
except for loneliness, which was only tested in wave 4 and 5. CIU
was significantly negatively associated with happiness and self-
esteem, and significantly positively with depression, stress, and
loneliness (see Table 3). Furthermore, to test the validity of our
model, we tested whether it held above and beyond Internet
frequency, by including main effects and interaction effects for
Internet frequency to the analyses. None of the effects of CIU
changed in significance or direction, and Internet frequency was
not significantly related to any of the wellbeing indicators.
3.3. Longitudinal analyses
As described in our strategy of analysis, to test the effects longi-
tudinally and explore the change over time in the criteria, we per-
formed multilevel residualized lagged analyses. In these analyses
the earlier independent variable was regressed on the dependent
variable one year later, controlling for the dependent variable
one year earlier. All effects were tested while controlling for the
earlier measure of the criterion variable (e.g., earlier CIU predicts
later happiness, while controlling for earlier happiness). Each effect
therefore predicts the change in the dependent variable.
We tested both the effects of CIU on the wellbeing variables, as
well as the opposite direction: the effects of the wellbeing
variables on CIU. Firstly, CIU was found to significantly predict
the changes in happiness, depression, stress and loneliness
(b
happiness
=.05, p = .04; b
depression
= .06, p= .03; b
stress
= .05,
p= .04; b
loneliness
= .13, p= .01) but not for self-esteem (see Table 4).
In the opposite direction, happiness predicted the change in CIU
over time (b=.06, p< .01), but none of the other wellbeing indi-
cators predicted the change in CIU over time (see Table 4).
4. Discussion
This study investigated the long-term directionality of the rela-
tionship between CIU and psychological wellbeing using an adult
sample. Previous research found negative relations between CIU
and wellbeing (for recent reviews and meta-analyses see Byun
et al., 2009; Chou et al., 2005; Tokunaga & Rains, 2010; Widyanto
& Griffiths, 2006). This study replicated these findings on a range of
wellbeing indicators, both positive and negative: Compulsive
Internet use was negatively related to happiness and self-esteem,
and positively related to depression, stress, and loneliness.
Crucially extending these findings, the current study examined
the directionality of the long-term associations. Longitudinally, the
data showed stronger support for the suggestion that CIU affects
wellbeing over time, than that wellbeing affects CIU: CIU predicted
changes in depression, stress, and loneliness positively, and the
change in happiness negatively. No effect of CIU on changes in
self-esteem was found. These results suggest CIU decreases peo-
ple’s wellbeing. Happiness however, did predict the change in
CIU negatively over time, suggesting happiness could protect peo-
ple from developing CIU.
4.1. Implications and future directions
4.1.1. CIU lowers psychological wellbeing
Our findings provide support for the suggestion that CIU con-
tributes to a decline in psychological wellbeing. In particular, we
found that CIU predicted greater depression, stress, and loneliness
over time. Previous research suggests several reasons as to why
this may happen. One is that the more time people spend online,
the less time they spend on real life interactions such as communi-
cation with offline significant others (Kraut et al., 1998). This may
give rise to feelings of isolation and disconnection, which are often
associated with depression and loneliness (Kim et al., 2009;
Moody, 2001; Tokunaga, 2012). Another reason why CIU may be
associated with low wellbeing is that the Internet exposes a person
to different forms of aversive experiences. Prolonged and excessive
use of social media has been shown to lead to negative feelings
Table 3
Hierarchical linear modeling b’s over T= 1, 2, 3, 4 and 5.
CIU Gender Frequency of Internet Use
CIU .20
**
.12
**
Happiness .12
**
.03 .02
Depression .14
**
.14
**
.03
Stress .14
**
.16
**
.02
Loneliness .10
*
.01 .01
Self-esteem .08
**
.16
**
.02
Note: CIU = Compulsive Internet Use; Happiness = Subjective Happiness Scale;
Depression = Center for Epidemiologic Studies Depression Scale; Stress = Perceived
Stress Scale; Loneliness = Loneliness Scale; Self-Esteem = Self-Esteem Scale.
*
p< .05.
**
p< .01.
Table 4
Residualized lagged analyses b’s for the predicted change in CIU by wellbeing factors,
and predicted change in wellbeing factors by CIU.
Criterion ?Dependent
variable
Criterion at earlier
time point
Effect on change in
dependent variable
Happiness ?CIU .70
**
.06
**
Depression ?CIU .71
**
.02
Stress ?CIU .71
**
.03
Loneliness ?CIU .78
**
.04
Self-esteem ?CIU .71
**
.04
CIU ?Happiness .65
**
.05
*
CIU ?Depression .27
**
.06
*
CIU ?Stress .49
**
.05
*
CIU ?Loneliness .66
**
.13
**
CIU ?Self-esteem .71
**
.03
Note: CIU = Compulsive Internet Use; Happiness = Subjective Happiness Scale;
Depression = Center for Epidemiologic Studies Depression Scale; Stress = Perceived
Stress Scale; Loneliness = Loneliness Scale; Self-Esteem = Self-Esteem Scale.
*
p< .05.
**
p< .01.
L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28 25
about the self and even depression, because it evokes social com-
parison (Pantic et al., 2012). In support of this explanation, Krasno-
va, Wenninger, Widjaja, and Buxmann (2013) found that the
relation of life satisfaction and Facebook use was mediated by
envy, particularly among passive users. Furthermore, the intensity
of passive following was likely to reduce a user’s life satisfaction in
the long run because it triggered this type of upward social
comparison.
Our results show that CIU has the strongest effect on loneliness
compared to the other indicators of wellbeing. This provides sup-
port for previous studies that show that extensive use of the Inter-
net, even for communication purposes, leads to loneliness (Kraut
et al., 1998; Moody, 2001). An explanation may be that people high
on CIU displace time spent on strong ties offline with time spent on
weak ties online (Moody, 2001). Note, though, that we measured
loneliness only in the last two waves, so we know less about the
stability and robustness of this effect than for the other wellbeing
indicators.
Our results did not provide support for Tokunaga’s (2012) find-
ings that loneliness and depression predicted CIU over time. Toku-
naga’s sample included incoming college freshmen. Measures were
administered from before they started college until the end of the
first semester of their first year. The present study was conducted
among newlywed adults from about two months after marriage
until the fifth year of marriage. Apart from different time lags,
we can also speculate that the difference in results could be ex-
plained by differences between the samples and their life stages.
Going to college and getting married are two significant events
that may have very different implications for the lives of individu-
als (e.g., going to college means being away from family and
friends vs. getting married means having a constant companion).
Also, emotional stability tends to increase across the adult life span
(Brose, Scheibe, & Schmiedek, 2012), which could account for
greater vulnerability of college students to loneliness and
depression.
The data did not provide support for the long-term directional-
ity of the link between CIU and self-esteem found among adoles-
cents. Research shows that self-esteem stability tends to increase
gradually throughout adulthood (Robins & Trzesniewski, 2005;
Trzesniewski, Donnellan, & Robins, 2003). It is possible that self-
esteem among adults is relatively stable, making it less susceptible
to the long-term effects of CIU.
Furthermore, it is important to highlight that the negative im-
pact of CIU in our study was not limited to the individual. Our find-
ings showed that the more one partner uses the Internet
compulsively, the more stressed is the other partner. Additionally,
within couples, happiness, stress, and loneliness were correlated.
These results indicate that one’s personal low wellbeing is associ-
ated with the low wellbeing of the partner. Intuitively, such a sit-
uation may intensify low wellbeing, contributing to a downward
spiral of negative emotions (Peterson & Seligman, 1984). This sug-
gests that when CIU takes time away from social activities with off-
line significant others, it may lead not only to the decline of one’s
own well-being (Moody, 2001), but may also affect the wellbeing
of other people in the social network.
4.1.2. The bidirectional relationship of CIU and happiness
Given that CIU is associated with increases in depression, stress,
and loneliness over time, intuitively one would expect CIU to have
the opposite effect on happiness. The results support this, and
showed that CIU had a long-term negative effect on happiness.
However, happiness differed from the other indicators of psycho-
logical wellbeing, because it also predicted a decrease in CIU over
time.
We found that an increase in happiness predicted lower CIU
over time. This findings indicate that the happier people are, the
less prone they are to becoming Compulsive Internet users. Why
may this be the case? Fredrickson’s broaden-and-build theory of
positive emotions (2001) might provide a plausible explanation
for this association. According to this theory, positive emotions
broaden people’s momentary thought-action repertoires and build
people’s personal resources. These personal resources function as
reserves, improving people’s ability to cope and survive. The pres-
ent study suggests that happiness may broaden people’s repertoire
of behaviors and build personal resources including self-regulatory
resources, making them less susceptible to CIU.
Taking happiness as the starting point, our results suggest that
low levels of happiness can lead to an increase in CIU. Consistent
with previous findings, unhappy individuals may seek contexts
where they can experience stimulating experiences. The Internet
can provide such contexts (Caplan 2003, 2006). Zillmann (1988)
asserted that media use has the ability to alter one’s mood and
emotional states, and that individuals choose media content to
get the desired mood. By using the Internet, individuals are able
to experience immediate pleasure, thereby regulating their mood
and emotional states. On social network sites, for instance, users
receive encouragement from their online social network, which
may add to positive feelings (Kuss & Griffiths, 2011). The incentive
of consciously gratifying a need through media use motivates
media consumption behavior that may eventually become a condi-
tioned response to certain moods. These automatic media behav-
iors threaten self-regulation (Rosengren, Wenner, & Palmgreen,
1985). Lower self-control (akin to self-regulation) increases CIU
over time (Muusses et al., 2013). Therefore, once self-regulation
is impaired by media habits to alter one’s mood, one is more prone
to CIU.
According to Lyubomirsky (2008) one of the determinants of
sustainable happiness is engagement in intentional and effortful
activities. These activities are resistant to adaptation/habituation
effects and they can create a self-sustaining cycle of positive
change (Lyubomirsky, 2008). Positive activity increases positive
emotion, which in turn, enhances wellbeing (Lyubomirsky &
Layous, 2013). This provides further support to the proposition that
positive emotion builds psychological resilience and trigger up-
ward spirals of positive emotions (Fredrickson, 2001). Because
the present study showed that happiness could be a protective fac-
tor against CIU, it points to the importance of intentional engage-
ment in activities, preferably outside of the Internet, to attain
happiness. While the above described implications are tenable
assumptions, more research is needed to examine our suggestions
on the protective role of happiness on CIU (and on problematic
Internet use in general) and the impact of CIU on the downward
spiral of negative wellbeing.
4.2. Strengths and limitations
Previous research shows strong support for a negative relation
between CIU and wellbeing. The present study sought to circum-
vent shortcomings of existing research by examining the direction-
ality of the link between CIU and wellbeing among a considerable
sample of adults with five measurements over a period of four
years.
To get a better understanding of the relationship of CIU and psy-
chological wellbeing, it was important to tease apart different com-
ponents of psychological wellbeing. Our study included both
positive indicators (i.e., happiness and self-esteem) and negative
indicators (i.e., depression, stress, and loneliness) of psychological
wellbeing. We found that CIU predicted positive and negative indi-
cators in the predicted direction. Importantly, we found that hap-
piness also predicted a decrease in CIU over time. These
processes had thus far not been studied simultaneously. Our find-
ings emphasize the need to look at both sets of indicators because
26 L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28
they coexist but are partly independent from each other (Huppert
& Whittington, 2003).
This study contributes to the literature by focusing on adult
Internet users. While Kraut et al. (1998) also studied adults, there
are notable differences from the sample of this research. Most
importantly, they did not look at CIU but at frequency of Internet
use. Later research showed that almost all substantial negative ef-
fects are related to CIU rather than frequency of Internet use (e.g.
Kerkhof et al., 2011). Another difference is the experiences the
samples have had with the Internet. While Kraut et al’s (1998)
study included adults in their first and second years of Internet
use in a time when Internet technology was relatively new, the
current sample has been exposed to the Internet for a much longer
period of time. A lot of applications, such as social network sites,
were not yet available during the earlier research. Much like Kraut
et al.’s (1998) study that examined people in the same household
(a large part of whom are in a relationship or married), this study
examined married couples. Although married people are one of the
largest demographics, future research might include adult or el-
derly single users. One could imagine the relation between CIU
and wellbeing might be different for this group of people. One
example is that perhaps loneliness is a bigger reason for single peo-
ple to use the Internet compulsively. Although the current research
provides knowledge about adult Internet users and their wellbeing
not yet present in the literature, more research is needed to inves-
tigate the impact of different internet applications, and crucially
whether the link between CIU and wellbeing changes with longer
use of the Internet.
5. Conclusions
This study explored the directionality between CIU and psycho-
logical wellbeing among adults. Psychological wellbeing was
examined using both positive indicators (happiness and self-es-
teem) and negative indicators (depression, stress and loneliness).
The results revealed that CIU lowers wellbeing over time. The high-
er the CIU, the more depressed, stressed, and lonely, and the less
happy participants became. Importantly, happiness prevented
CIU over time. Thus, while CIU seems to make adults more vulner-
able to decreases in wellbeing, positive wellbeing seems to protect
individuals from developing CIU in the long run.
Acknowledgement
The authors would like to acknowledge the input and participa-
tion in the data analyses of Asuman Buyukcan Tetik.
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28 L.D. Muusses et al. / Computers in Human Behavior 36 (2014) 21–28
... It is defined as uncontrollable and continuous Internet use, characterized by preoccupation with the activity despite its negative consequences and experiencing negative psychological withdrawal reactions (Caplan, 2010;van den Eijnden et al., 2008). Compulsive Internet use has been found to decrease happiness and increase stress, anxiety, loneliness, and depression among adults (Muusses et al., 2014); it is also connected to developing a maladaptive relationship with one's work (Quinones et al., 2016). ...
... Our results, which consider the detrimental effects of compulsive social media use, align with previous studies (Muusses et al., 2014;Quinones et al., 2016) on compulsive Internet use in general. Both within-and between-person comparisons confirmed its negative impact on distress, technostress, and work exhaustion levels, thus providing fresh longitudinal evidence to the field. ...
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This study investigated the impact of cyberbullying victimization at work on well-being and strain in the workplace. This is the first study to use a longitudinal approach to research cyberbullying at work. A nationally representative sample of Finnish workers ( n = 768) took part in a five-wave survey study. Both within-person and between-person effects were analyzed using hybrid regression models showing that experiencing cyberbullying at work leads to psychological distress, technostress, work exhaustion, and decreased work engagement. The effects of remote work and social media use were also explored. These results confirm that cyberbullying at work can have damaging consequences for victims and, consequently, for whole organizations. Thus, it constitutes a significant problem that employers must confront.
... The more trusting users are more likely to rely on the system and click on SERP; they are also more likely to classify common benign symptoms as serious diseases. Meanwhile, indulgence in SERP can be regarded as a form of compulsive internet use that lowers wellbeing by predicting increases in depression and stress over time; the resulting decrease in happiness may affect health (Muussesa et al., 2014). ...
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Background Cyberchondria has been brought into sharp focus during the COVID-19 health emergency; it refers to individuals who obsessively and compulsively search for health information online, resulting in excessive health concerns. Recent scholarship focuses on its obsessive and compulsive aspect, following a biopsychosocial approach as opposed to a pathology of health anxiety. It lacks interpretation of the socio-psychological dynamics between the dimensions.Objective This review aims to propose a holistic view toward understanding cyberchondria as an obsessive–compulsive syndrome and considers possible interventions. It specifically seeks to explain cyberchondria from diversified mediator variables and to pinpoint connections between each perspective.MethodologyComprehensive searches of databases such as PubMed and Springer were conducted to identify English articles relating to cyberchondria from 2001 to 2022. Based on a systematic filtering process, 27 articles were finally reviewed.FindingsThe authors compare and confirm three forecasts to predict cyberchondria, associating it with individual metacognition, uncertainty of unverified information, and algorithm-driven, biased information environments.ValueTheoretically, a holistic framework is proposed to explain the obsessive and compulsive features of cyberchondria. Clinically, the research calls for more professional psychoeducation and chain screening of cyberchondria and other psychological disorders. Socially, it promotes support for risk-sensitive, information-deficient groups during pandemics like COVID-19. It also stresses more careful use of algorithm-driven search engine technology for platforms delivering medical information. Future research may explore areas such as the association between cyberchondria and other social-related disorders, as well as correlations among cyberchondria, obsessive and compulsive disorders, medical trust, and algorithm-driven search results.
... Second, this research is destined to expand the positive psychology and well-being literature by highlighting the complexity of internal influencing mechanisms of internet use on QoL. In contrast, extant research into psychological mechanisms is less conclusive despite the ongoing efforts to carry out discussions on internet use and well-being [17]. A serial multiple mediating effect between LIU and QoL was verified with the path: LIU → + risk perception → +internet addiction → −QoL. ...
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The impact of internet use on quality of life (QoL) has become an increasing focus of academic research. This paper aims to explore the internal influencing mechanisms of internet use (i.e., leisure-oriented internet use (LIU); work-oriented internet use (WIU)) on QoL, with a focus on the multiple mediating effects of risk perception and internet addiction. We constructed a theoretical framework from a psychological perspective and tested the hypotheses using hierarchical regression analysis with a sample of 1535 participants. The results showed that: (1) LIU had a positive effect on QoL, while WIU did not have a significant impact on QoL; (2) both risk perception and internet addiction had a negative influence on QoL; (3) risk perception positively impacted internet addiction; (4) risk perception and internet addiction had multiple mediating effects on the relationship between internet use and QoL.
... Longitudinal studies of problematic internet use have revealed that negative outcome scores are higher [60,61]. However, some studies have obtained conflicting outcomes [62]. ...
Book
This book constitutes the refereed proceedings of the 5th International Symposium on Human Mental Workload: Models and Applications, H-WORKLOAD 2021, held virtually in November 2021. The volume presents 9 revised full papers, which were carefully reviewed and selected from 16 submissions. The papers are organized in two topical sections on models and applications.
... Longitudinal studies of problematic internet use have revealed that negative outcome scores are higher [60,61]. However, some studies have obtained conflicting outcomes [62]. ...
Chapter
This study explored how students' main information problems during the information age, namely internet addiction, information overload, and social network addiction, influence holistic well-being and academic attainment. The participants were 226 university students, all UK based and regular internet users. They answered the Internet Addiction Test, Information Overload Scale, Bergen Social Media Addiction Scale, and the Wellbeing Process Questionnaire. Data were analysed with SPSS using correlation and linear regression analysis. The univariate analyses confirmed the negative impact of information overload, internet addiction and social media addiction on positive well-being but not academic attainment. However, multivariate analyses controlling for established predictors of well-being showed that the effects of information overload, internet addiction and social media addiction were largely non-significant, confirming other research using this analysis strategy. Future research should examine the type of internet use as well as the extent of it.
... The present section proposes a research model which is further empirically tested ( Figure 1). Prior studies have suggested that increased Internet usage is associated with lower wellbeing (Caplan, 2002;Muusses et al., 2014). Recent studies have found that individuals who spent more time on digital platforms or used those more frequently displayed lower PW (Sabik et al., 2020;Twenge and Campbell, 2019). ...
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Purpose Employees have gradually adopted social media sites and their applications that have been associated with enhanced communication and collaboration at the workplace. However, social technologies have both positive as well as negative consequences. The current study examines the impact of loneliness on employees' psychological well-being (PW); subsequently, the mediating role of social media use intensity (SMI) at the workplace. It also examines the moderating role of gender and management status of employees. Design/methodology/approach The present study conducted an online and offline survey using a cross-sectional design. Data were collected from 206 working professionals from the IT industry in India. Structural equation modelling was applied to analyse data. Findings Results revealed that employee loneliness is positively associated with SMI. Employee's SMI was positively associated with enhanced PW. Unexpectedly, employee loneliness is positively and significantly related to PW. However, the moderating roles of gender and management status of employees were not supported. Practical implications The current study can help managers, policymakers and organizations better understand the role of employee social media use in the workplace. Using the insights and understanding offered by the study, social media can be effectively utilized in the workplace. The study recommends that organizations may allow the use of social media at the workplace. Social media resources may also be helpful in improving employee communication and digital literacy. Originality/value The current study is a pioneer work and contributes to the literature by examining the relationship between loneliness, SMI and PW. This study has essential theoretical and managerial contributions.
... Several studies have found that problematic internet use is linked to reduced psychological well-being [56][57][58]. Specific components of well-being, such as subjective vitality and happiness, have been proven to be lower in people who use the internet problematically [59] Longitudinal studies of problematic internet use have revealed that negative outcome scores are higher [60,61]. However, some studies have obtained conflicting outcomes [62]. ...
Preprint
Full-text available
This study explored how students' main information problems during the information age, namely internet addiction, information overload, and social network addiction, influence holistic well-being and academic attainment. The participants were 226 university students, all UK based and regular internet users. They answered the Internet Addiction Test, Information Overload Scale, Bergen Social Media Addiction Scale, and the Wellbeing Process Questionnaire. Data were analysed with SPSS using correlation and linear regression analysis. The univariate analyses confirmed the negative impact of information overload, internet addiction and social media addiction on positive well-being but not academic attainment. However, multivariate analyses controlling for established predictors of well-being showed that the effects of information overload, internet addiction and social media addiction were largely non-significant, confirming other research using this analysis strategy. Future research should examine the type of internet use as well as the extent of it.
... Since Internet activities are largely performed in solitude and can potentially displace more interactive social activities, people who spend large amounts of time using the Internet may end up feeling socially isolated, causing a decline in mood (Sagioglou & Greitemeyer, 2014) and low life satisfaction (Stepanikova et al., 2010). Moreover, researchers have reported compulsive Internet use (Muusses et al., 2014), which can reflect Internet addiction (Cheng & Li, 2014), problematic or pathological Internet use (Caplan, 2002;Morahan-Martin & Schumacher, 2000), and Internet dependence (Wang, 2001), to be associated lower psychological well-being (Widyanto & Griffiths, 2006). The Internet might also facilitate addictive behaviors (e.g., gambling, online gaming, pornography), thus becoming detrimental to one's mental health (Banjanin et al., 2015). ...
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Rehabilitation aims to make necessary changes to help individuals achieve maximum life satisfaction. This study focused on Internet competence and use as factors related to life satisfaction for individuals with physical disabilities. Data from the 2016 Information Divide Index of the National Information Society Agency were analyzed. Regression analyses indicated a negative correlation between Internet use related to life services and life satisfaction; however, findings also suggested Internet use has positive effects on life satisfaction for individuals with physical disabilities. Internet use can help improve the life satisfaction of individuals with physical disabilities, and measures to increase competence and use are necessary.
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The study aims to determine the relationship between problematic Internet use in adolescents and emotion regulation difficulty and family Internet attitude. The study used a descriptive and correlational design. The sample of the study consisted of 5916 students. The data were collected using the “Problematic Internet Use Scale,” “Difficulties in Emotion Regulation Scale,” “Internet Parental Style Scale.” The total score on the Problematic Internet Use Scale was 55.41 ± 19.60 while the total score on the Difficulties in Emotion Regulation Scale was 97.51 ± 17.84. Considering the Internet parental styles, it was found that 42.89% of the parents had a negligent attitude. According to the results of the logistic regression analysis performed, grade level was found to affect problematic Internet use. A highly significant correlation was found between problematic Internet use and emotional regulation difficulties and family control of family Internet attitude (p < 0.01). This study determined that adolescents' grade level and excessive Internet use of the father were effective in the problematic Internet use of the adolescents. Adolescents' difficulties in emotion regulation and the type of families' attitudes towards Internet use were associated with problematic Internet use. In accordance with these results, it can be recommended to form programs to decrease problematic Internet use.
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To be a trustworthy partner, people need self-control. People infer others’ level of self-control from behavioral cues, and this perception influences how much they trust others. Exhibiting compulsive Internet use (CIU) might provide such cues. This research examined whether and how CIU affects perceptions of self-control and trust in a partner. In an experimental study, we manipulated CIU in descriptions of strangers and found that participants in the CIU condition judged the other to have lower self-control and trusted them less than in a control condition. In a prospective dyadic study among newlyweds, we extended these results to close relationships. The results confirmed our hypotheses. Additionally, we found that low trait self-control makes people prone to CIU, illustrating that assessing others’ CIU is a good strategy to gauge others’ level of self-control. These results illuminate how and why CIU may be harmful for relationships.
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Concerns about the problematic nature of internet use have been discussed since the inception of the internet. Internet addiction, problematic internet use (PIU), and the deficient self-regulation of internet use are some issues studied in this domain. Some regard these conditions as genuine disorders that cause disruptions in one's life. Others criticize their legitimacy, claiming that functional impairment associated with internet use is indicative of primary psychosocial problems and has little to do with the internet. The purpose of this investigation was to understand whether cognitive preoccupation and uncontrolled use, components of PIU, are part of a unique disorder or are symptomatic of underlying psychosocial problems. This research tested the mediating role of PIU in the relationships between psychosocial problems (i.e., social anxiety, loneliness, and depression) and impairment of interpersonal relationships and vocational performance in two studies. Different conclusions were reached based on the methodological design of the study; however, the findings generally supported the mediation of PIU.
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Studies on the role played by attachment attitudes among late adolescents who show Problematic Internet Use (PIU) are still lacking. Three self-report measures concerning attachment attitudes, childhood experiences of abuse, and Internet addiction were administered to 310 students (49 % males) aged 18-19 attending the last year of high school. Students who screened positive for PIU were more likely to be male and to have suffered childhood experiences of physical and sexual abuse; they also scored higher than the other participants on scales assessing anxious and avoidant attachment attitudes. A logistic regression showed that the classification of participants in the PIU group was predicted by male gender, having suffered from physical and sexual abuse in childhood, and preoccupation with relationships. Keeping constant the effects of gender and childhood experiences of abuse in the equation model, increasing values of preoccupation with relationships were reflected by an exponential growth in the probability curve for PIU classification. Findings of the study support the hypothesis that insecure attachment attitudes (particularly the preoccupation with relationships) are involved in the development of PIU among late adolescents.
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Theory and research suggest that people can increase their happiness through simple intentional positive activities, such as expressing gratitude or practicing kindness. Investigators have recently begun to study the optimal conditions under which positive activities increase happiness and the mechanisms by which these effects work. According to our positive-activity model, features of positive activities (e.g., their dosage and variety), features of persons (e.g., their motivation and effort), and person-activity fit moderate the effect of positive activities on well-being. Furthermore, the model posits four mediating variables: positive emotions, positive thoughts, positive behaviors, and need satisfaction. Empirical evidence supporting the model and future directions are discussed.
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The wealth of social information presented on Facebook is astounding. While these affordances allow users to keep up-to-date, they also produce a basis for social comparison and envy on an unprecedented scale. Even though envy may endanger users' life satisfaction and lead to platform avoidance, no study exists uncovering this dynamics. To close this gap, we build on responses of 584 Facebook users collected as part of two independent studies. In study 1, we explore the scale, scope, and nature of envy incidents triggered by Face-book. In study 2, the role of envy feelings is examined as a mediator between intensity of passive following on Facebook and users' life satisfaction. Confirming full mediation, we demonstrate that passive following exacerbates envy feelings, which decrease life satisfaction. From a provider's perspective, our findings signal that users frequently perceive Facebook as a stressful environment , which may, in the long-run, endanger platform sustainability.
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The literature on subjective well-being (SWB), including happiness, life satisfaction, and positive affect, is reviewed in three areas: measurement, causal factors, and theory. Psychometric data on single-item and multi-item subjective well-being scales are presented, and the measures are compared. Measuring various components of subjective well-being is discussed. In terms of causal influences, research findings on the demographic correlates of SWB are evaluated, as well as the findings on other influences such as health, social contact, activity, and personality. A number of theoretical approaches to happiness are presented and discussed: telic theories, associationistic models, activity theories, judgment approaches, and top-down versus bottom-up conceptions.
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In this article, the author describes a new theoretical perspective on positive emotions and situates this new perspective within the emerging field of positive psychology. The broaden-and-build theory posits that experiences of positive emotions broaden people's momentary thought-action repertoires, which in turn serves to build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources. Preliminary empirical evidence supporting the broaden-and-build theory is reviewed, and open empirical questions that remain to be tested are identified. The theory and findings suggest that the capacity to experience positive emotions may be a fundamental human strength central to the study of human flourishing.
Article
In this article, the author describes a new theoretical perspective on positive emotions and situates this new perspective within the emerging field of positive psychology. The broaden-and-build theory posits that experiences of positive emotions broaden people's momentary thought-action repertoires, which in turn serves to build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources. Preliminary empirical evidence supporting the broaden-and-build theory is reviewed, and open empirical questions that remain to be tested are identified. The theory and findings suggest that the capacity to experience positive emotions may be a fundamental human strength central to the study of human flourishing.
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Anecdotal reports indicated that some on-line users were becoming addicted to the Internet in much the same way that others became addicted to drugs or alcohol, which resulted in academic, social, and occupational impairment. However, research among sociologists, psychologists, or psychiatrists has not formally identified addictive use of the Internet as a problematic behavior. This study investigated the existence of Internet addiction and the extent of problems caused by such potential misuse. Of all the diagnoses referenced in the Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV; American Psychiatric Association, 1995), Pathological Gambling was viewed as most akin to the pathological nature of Internet use. By using Pathological Gambling as a model, addictive Internet use can be defined as an impulse-control disorder that does not involve an intoxicant. Therefore, this study developed a brief eight-item questionnaire referred to as a Diagnostic Questionnaire (DQ), which modified criteria for pathological gambling to provide a screening instrument for classification of participants. On the basis of this criteria, case studies of 396 dependent Internet users (Dependents) and 100 nondependent Internet users (Nondependents) were classified. Qualitative analyses suggest significant behavioral and functional usage differences between the two groups such as the types of applications utilized, the degree of difficulty controlling weekly usage, and the severity of problems noted. Clinical and social implications of pathological Internet use and future directions for research are discussed.