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"Facebocrastination"? Predictors of using Facebook for procrastination and its effects on students' well-being

November 2016
Computers in Human Behavior 64:65-76

November 2016
64:65-76

DOI:10.1016/j.chb.2016.06.011

Authors:

Adrian Meier

Friedrich-Alexander-University of Erlangen-Nürnberg

Leonard Reinecke

Johannes Gutenberg-Universität Mainz

Christine E. Meltzer

Hochschule für Musik, Theater und Medien Hannover

Procrastinating with popular online media such as Facebook has been suggested to impair users' well-being, particularly among students. Building on recent procrastination, self-control, and communication literature, we conducted two studies (total N = 699) that examined the predictors of procrastination with Facebook as well as its effects on students' academic and overall well-being. Results from both studies consistently indicate that low trait self-control, habitual Facebook checking, and high enjoyment of Facebook use predict almost 40 percent of the variance of using Facebook for procrastination. Moreover, results from Study 2 underline that using Facebook for the irrational delay of important tasks increases students' academic stress levels and contributes to the negative well-being effects of Facebook use beyond the academic domain. The implications of investigating procrastination as a specific pattern of uncontrolled and dysfunctional media use are discussed with regard to research on the uses and effects of ubiquitous online media.

SEM for trait self-control, Facebook checking habit, and Facebook enjoyment as predictors of procrastination with Facebook (Study 1) Note. Observed structural equation model based on N ¼ 354 participants. Fit indices are c 2 ¼ 316.460, df ¼ 130, p < 0.001, c 2 /df ¼ 2.434, CFI ¼ 0.932, RMSEA ¼ 0.064 (90% C.I.: 0.055, 0.073), SRMR ¼ 0.060. Scores in the figure represent standardized path coefficients. Significance levels are based on 5000 bootstrap samples with replacement and 95% bias-corrected confidence intervals. FB ¼

…

SEM for predictors of procrastination with Facebook and effects on academic stress and FB-induced strains on well-being (Study 2) Note. Observed structural equation model based on N ¼ 345 participants. Fit indices are c 2 ¼ 507.654, df ¼ 343, p < 0.001, c 2 /df ¼ 1.480, CFI ¼ 0.962, RMSEA ¼ 0.037 (90% C.I.: 0.030, 0.044), SRMR ¼ 0.070. Scores in the figure represent standardized path coefficients. Significance levels are based on 5000 bootstrap samples with replacement and 95% bias-corrected confidence intervals. FB ¼ Facebook. * p < 0.05, ** p < 0.01, *** p < 0.001.

…

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Full length article

“Facebocrastination”? Predictors of using Facebook for procrastination

and its effects on students’well-being

Adrian Meier

, Leonard Reinecke, Christine E. Meltzer

Department of Communication, Johannes Gutenberg University Mainz, Germany

article info

Article history:

Received 13 January 2016

Received in revised form

30 April 2016

Accepted 12 June 2016

Keywords:

Procrastination

Social network sites

Facebook

Self-control

Well-being

University students

abstract

Procrastinating with popular online media such as Facebook has been suggested to impair users’well-

being, particularly among students. Building on recent procrastination, self-control, and communica-

tion literature, we conducted two studies (total N¼699) that examined the predictors of procrastination

with Facebook as well as its effects on students’academic and overall well-being. Results from both

studies consistently indicate that low trait self-control, habitual Facebook checking, and high enjoyment

of Facebook use predict almost 40 percent of the variance of using Facebook for procrastination.

Moreover, results from Study 2 underline that using Facebook for the irrational delay of important tasks

increases students’academic stress levels and contributes to the negative well-being effects of Facebook

use beyond the academic domain. The implications of investigating procrastination as a speciﬁc pattern

of uncontrolled and dysfunctional media use are discussed with regard to research on the uses and

effects of ubiquitous online media.

1. Introduction

The pervasive access to social media such as Facebook creates

new self-control challenges for a growing number of Internet users

in different spheres of life (e.g., Hofmann, Vohs, &Baumeister,

2012; Masur, Reinecke, Ziegele, &Quiring, 2014; Panek, 2014; Xu,

Wang, &David, 2016). Student users, in particular, report that the

social network site (SNS) Facebook ‘makes them’lose track of time

and that they delay tasks they actually intended to get done, such as

writing term papers or preparing for ﬁnal exams, ‘because of

Facebook’(e.g, Rosen, Carrier, &Cheever, 2013). Studies ﬁnding a

negative relationship between conscientiousness and Facebook use

among students suggest that low self-control may be a central

driver of this unintended Facebook use (e.g., Lee-Won, Herzog, &

Park, 2015; Wilson, Fornasier, &White, 2010). Moreover, research

on the uses and gratiﬁcations of social media has consistently

identiﬁed the use of Facebook “to put off something I should be

doing”(Quan-Haase &Young, 2010, p. 356) as one of the strongest

motives of Facebook use (Papacharissi &Mendelson, 2011; Smock,

Ellison, Lampe, &Wohn, 2011).

Students, in particular, seem to irrationally delay (i.e., procras-

tinate) important academic tasks in favor of Facebook use, which

has been suggested to be responsible for a large part of the negative

relationship between Facebook use and academic performance

(Junco, 2012; Kirschner &Karpinski, 2010; Panek, 2014; Rosen

et al., 2013; Thompson, 2013). Moreover, initial evidence indicates

that procrastination with Facebook is particularly detrimental to

students’well-being (Hinsch &Sheldon, 2013), which is supported

by research on the negative consequences of general, non-media-

related procrastinatory behavior among students (Kim &Seo,

2015; Sirois &Kitner, 2015; Steel, 2007).

Although Facebook is among the most widely used online ap-

plications around the globe (Alexa, 2015; Facebook, 2015; Pew

Research Center, 2015) and several independent lines of research

suggest that Facebook is a frequently used, but detrimental “tool for

procrastination”(Lavoie &Pychyl, 2001, p. 433) among students,

evidence of this practice of ‘Facebocrastination’is scarce. The pre-

sent research thus aims at furthering our limited understanding of

the uses and effects of procrastination with the popular SNS Face-

book. Speciﬁcally, the predictors of procrastination with Facebook

and its effects on academic and overall well-being will be

investigated.

In the following section, we will ﬁrst review evidence on

media-related procrastination based on the prevailing under-

standing of procrastination as irrational task delay (Sirois &

*Corresponding author. Department of Communication, Johannes Gutenberg

University Mainz, Jakob-Welder-Weg 12, 55099 Mainz, Germany.

E-mail addresses: meier@uni-mainz.de (A. Meier), reineckl@uni-mainz.de

(L. Reinecke), meltzer@uni-mainz.de (C.E. Meltzer).

Contents lists available at ScienceDirect

Computers in Human Behavior

journal homepage: www.elsevier.com/locate/comphumbeh

http://dx.doi.org/10.1016/j.chb.2016.06.011

Computers in Human Behavior 64 (2016) 65e76

Pychyl, 2013; Steel, 2007). By conceptualizing procrastination with

Facebook as a self-control failure (Hofmann, Friese, &Strack, 2009;

Steel, 2007), we will then identify dispositional (trait self-control)

and Facebook-speciﬁc precursors (habitual Facebook checking and

enjoyment of Facebook use) that could predict the frequency of

procrastination with Facebook. Moreover, we will discuss the

potentially detrimental effects of procrastination with Facebook on

students’academic and overall well-being. Based on two studies

using data from two student samples, we will subsequently

address the predictors (Studies 1 and 2) and effects (Study 2) of

procrastination with Facebook. The results will be discussed with

regard to their implications for everyday social media use as well

as future research on the uses and effects of constantly available

online media.

2. Theoretical background

2.1. Media as “tools for procrastination”

Consistent with recent procrastination literature, we deﬁne

procrastination as the “self-regulatory failure of not exerting self-

control necessary for task engagement”(Sirois &Pychyl, 2013,p.

116). Essentially, procrastinators give in to pleasant short-term

temptations such as checking Facebook instead of engaging in

intended, but subjectively aversive tasks such as writing a term

paper. According to this typical procrastination scenario, the pro-

crastinatory activity (i.e., checking Facebook) provides the pro-

crastinator with immediate gratiﬁcations such as the satisfaction

of relatedness needs via Facebook use (Reinecke, Vorderer, &

Knop, 2014; Sheldon, Abad, &Hinsch, 2011). In contrast, the

procrastinated task (i.e., writing a term paper) is often perceived

as stressful, frustrating, or boring and thus increases short-term

negative affect during task engagement (Pychyl, Lee, Thibodeau,

&Blunt, 2000). Moreover, procrastinated tasks typically provide

only distal rewards (e.g., good grades or a higher salary) and are

hedonically less attractive in the here and now than proximal

competing activities (e.g., ‘just quickly’checking Facebook, getting

coffee, or watching a video clip on YouTube). In line with this

conceptualization of procrastination, engaging in an intended, but

aversive task requires the exertion of self-control since self-control

is a crucial ability drawn on by individuals when they prioritize

long-term goals over short-term desires (Hofmann et al., 2009;

Sirois &Pychyl, 2013).

A further deﬁning characteristic that distinguishes procrasti-

nation from more active and strategic forms of delay is its irrational

and dysfunctional nature (Steel, 2007). Although procrastinators

seem to experience some short-term positive affect from indulging

in pleasurable substitute activities such as Facebook use, they

typically realize that their delay of important tasks is futile, irra-

tional, and self-harming in the long term (Sirois &Pychyl, 2013).

Hence, the short-term affective beneﬁts of irrational delay are

outweighed by its long-term costs (e.g., Tice &Baumeister, 1997).

We thus understand procrastination with Facebook not as a func-

tional gratiﬁcation sought by or obtained from Facebook use (cf.,

Quan-Haase &Young, 2010), but as a dysfunctional behavioral

outcome of deﬁcient self-control processes that drive exposure to

Facebook.

Several researchers have recently identiﬁed procrastination as a

pervasive pattern of Internet and computer use (e.g., Breems &

Basden, 2014; Myrick, 2015). Only few studies, however, have

explicitly investigated the predictors of procrastination with media

content and mediated communication so far. Experience sampling

research by Hofmann et al. (2012) demonstrates that people

frequently give in to media desires, even though they try to resist

them. In fact, engaging in media use despite conﬂicts with other

goals and tasks seems to be one of the most common forms of self-

control failure in peoples’everyday lives, suggesting a high preva-

lence of media-related task procrastination. Furthermore, Panek

(2014) recently investigated the role of self-control for college

students’media use. In his correlational study, low trait self-control

was related to increased time spent on leisure media use and

decreased time on self-directed learning. From this, he concluded

that students often give in to proximal media use opportunities

that provide short-term ‘guilty pleasures’compared to important,

but aversive academic tasks. Notably, the use of social media was

particularly strongly related to low trait self-control, implying

frequent uncontrolled and possibly procrastinatory use of SNS such

as Facebook.

Research on media multitasking has further underlined that

media-induced task-switching during (academic) work is driven by

high arousal and hedonic pleasure elicited by the media activity, as

well as low cognitive control over the switching behavior (e.g.,

David, Kim, Brickman, Ran, &Curtis, 2015; Xu et al., 2016; van der

Schuur, Baumgartner, Sumter, &Valkenburg, 2015). The ﬁndings of

this line of research suggest that media in general and social and

mobile media in particular are often selected impulsively and in an

uncontrolled manner during work sessions, although users intend

to work on more important tasks. This ‘media-induced task-

switching’has been found to signiﬁcantly impair students’perfor-

mance and well-being (e.g., Rosen et al., 2013; Xu et al., 2016).

Together, the studies outlined above provide implicit evidence

for high levels of media-related procrastination due to low levels of

self-control and impulsive selection of hedonically pleasant media

stimuli. Two recent studies further corroborate this ﬁnding by

explicitly linking self-control to procrastination with media con-

tent. In a cross-sectional study, Reinecke, Hartmann, and Eden

(2014) found that TV and video game use after work was

perceived as procrastination when participants reported lower

levels of state self-control. Procrastination, in turn, was related to

higher levels of guilt about media use. The ﬁndings thus suggest

that participants perceived their uncontrolled after-work media

use as the result of impulsively ‘giving in’to media temptation

instead of pursuing activities that would have been more aligned

with their long-term goals (e.g., sports). A recent experience sam-

pling study (Reinecke &Hofmann, 2016) further substantiates the

link between media use and self-control failure: Participants re-

ported that media use conﬂicted with other important goals on

more than half of all media use occurrences (61.2%), underlining

that media use poses a particularly difﬁcult self-regulatory chal-

lenge for many people in day-to-day settings. Moreover, higher

trait self-control signiﬁcantly predicted decreased procrastination

with media content, which supports the notion that self-control is a

key factor for media-related procrastination (Reinecke &Hofmann,

2016).

2.2. Procrastination with Facebook as self-control failure

The available evidence suggests a link between procrastination

with both ofﬂine and online media and trait self-control, indicating

that media use for procrastination is a consequence of self-control

failure. Thus, the ﬁrst goal of our research is to investigate whether

low trait self-control also drives the use of Facebook for procrasti-

nation. In line with self-control research, we refer to trait self-

control as individual differences in the capacity to override or

inhibit problematic behavioral tendencies and desires (Hofmann

et al., 2009; Tangney, Baumeister, &Boone, 2004). Trait self-

control has been found to predict numerous positive behavioral

outcomes such as better academic grades, fewer unhealthy eating

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e7666

behaviors, and less substance abuse (e.g., Tangney et al., 2004; de

Ridder, Lensvelt-Mulders, Finkenauer, Stok, &Baumeister, 2011).

Individuals that frequently succeed in restraining their problematic

desires and in attaining their personal goals also report better

psychological adjustment, less psychopathology, more positive

momentary affect, and more life satisfaction (Hofmann, Luhmann,

Fisher, Vohs, &Baumeister, 2014; Tangney et al., 2004). In conclu-

sion, self-control can be characterized as being “among human-

kind’s most valuable assets”(Hofmann et al., 2014, p. 265) and as a

key dispositional factor for a wide range of self-regulatory out-

comes, including frequent procrastination (Sirois &Pychyl, 2013;

Steel, 2007). Since prior research has demonstrated that trait self-

control is a negative predictor of procrastination with both ofﬂine

and online media (Reinecke &Hofmann, 2016), we thus predict

that trait self-control is negatively related to the frequency of

procrastination with Facebook (H1).

Beyond dispositional levels of self-control, prior research sug-

gests that impulsive selection of hedonically tempting media ac-

tivities contributes to uncontrolled and procrastinatory use of

these media. Thus, the second goal of our research is to investigate

whether impulsive media selection is a further predictor of pro-

crastinatory Facebook use, operating as an antagonist to the self-

control efforts of limiting one’s media use when working on

intended tasks. Recent research indicates that self-control failure

is often driven by strong impulsive desires that overwhelm in-

dividuals’self-control ability (Heatherton &Wagner, 2011;

Hofmann &van Dillen, 2012; Hofmann, Kotabe, &Luhmann,

2013). Such impulsive behavior is particularly likely when in-

dividuals are confronted with stimuli that elicit strong automatic

reactions. According to Hofmann et al. (2009), individuals asso-

ciate desirable stimuli (e.g., a delicious candy) with automatic

impulses. Speciﬁcally, individuals develop automatic approach-

avoidance tendencies towards desired stimuli. The stronger these

automatic tendencies are, the more likely the execution of

impulsive behavior (e.g., reaching for the candy jar) becomes, even

if it is inconsistent with long-term goals (e.g., weight loss)

(Hofmann et al., 2009).

We propose that this inﬂuence of automatic approach reactions

on impulsive behavior can be applied to media selection as well.

Speciﬁcally, we argue that automatic approach reactions predict

procrastination with Facebook as a form of self-control failure. The

importance of automatic approach reactions for media use is sub-

stantiated by research on media habits (e.g., LaRose, 2010; Naab &

Schnauber, 2014): In many situations, users do not deliberately

ponder over whether or not they should engage in media use (e.g.,

check their Facebook account). Instead, media exposure is initiated

unconsciously through media habits. Media habits thus represent

automatic behavioral responses that rely on mental scripts (LaRose,

2010; Naab &Schnauber, 2014) and learned stimulus-response

associations (Gardner, 2015). More speciﬁcally, habits are charac-

terized by automatic and impulse-driven initiation of behavior

(Gardner, 2015; Gardner, Abraham, Lally, &Bruijn, 2012; Naab &

Schnauber, 2014). Thus, the more habitually a medium is used,

the more likely the medium is selected automatically and

impulsively.

Several studies underline that Facebook use is a strongly

habitual activity (Giannakos, Chorianopoulos, Giotopoulos, &

Vlamos, 2013; Papacharissi &Mendelson, 2011; Smock et al.,

2011) and that texting applications such as the Facebook

messenger are used in a highly automatic and impulsive fashion

(Bayer, Dal Cin, Campbell, &Panek, 2016). A recent multi-method

study found that Facebook is among the most frequently

‘checked’mobile applications, suggesting that automatic selection

in form of habitual Facebook checking is an integral part of Face-

book use (Oulasvirta, Rattenbury, Ma, &Raita, 2012). Since

habitually checking Facebook represents an automatic approach

reaction that is likely to interfere with important tasks at hand

(Hofmann et al., 2009), we believe that it is a key driver of pro-

crastinatory Facebook use. We thus predict that habitually checking

Facebook is positively related to the frequency of procrastination

with Facebook (H2).

In addition to automatic approach reactions such as habits, we

further propose that associating enjoyment with speciﬁc media

activities is an important predictor of irrational and impulsive se-

lection of these media despite facing important tasks at hand.

Procrastination research (Sirois &Pychyl, 2013) has recently pro-

posed that procrastinators often prioritize the positive affect eli-

cited by hedonically pleasant procrastinatory activities (e.g.,

meeting friends or watching TV) over the attainment of long-term

goals. Thus, associating pleasurable experiences and enjoyment

with a certain activity (e.g., Facebook use) increases the probability

that individuals are tempted by this activity when they simulta-

neously face an aversive task (Sirois &Pychyl, 2013). Notably, an

early study on Internet use and procrastination by Lavoie and

Pychyl (2001) supports this notion of the pivotal role of enjoy-

ment for procrastination. In their cross-sectional survey, the au-

thors found that participants who perceived Internet use as more

entertaining and enjoyable also reported higher levels of online

procrastination. Accordingly, they concluded that “Internet users

appear to be entertaining themselves into task postponement”

(Lavoie &Pychyl, 2001, p. 441). Recent research further indicates

that Facebook use is a highly enjoyable activity that satisﬁes basic

psychological needs through online entertainment and social

interaction (Reinecke, Vorderer et al., 2014; Sheldon et al., 2011).

Combining these results on the enjoyment of Facebook use with the

predictions made by procrastination research (Sirois &Pychyl,

2013), we argue that higher enjoyment of Facebook use should

increase the risk of being tempted by Facebook and, hence,

impulsively selecting Facebook even if it conﬂicts with more

important activities. We thus predict that the enjoyment of Face-

book use is positively related to the frequency of procrastination

with Facebook (H3).

In this section, we have argued that the frequency of procras-

tination with Facebook can be predicted by low trait self-control

and impulsive selection of Facebook due to strong checking

habits and high Facebook enjoyment. Initial evidence further sug-

gests that procrastination with Facebook affects the well-being of

Facebook users (e.g., Hinsch &Sheldon, 2013), particularly in the

academic domain (Kim &Seo, 2015; Sirois &Kitner, 2015; Steel,

2007). However, prior research on the consequences of procrasti-

nation with media content and mediated communication is scarce.

We thus aim at extending prior research by investigating the link

between procrastination with Facebook and students’well-being.

In the following section, we will ﬁrst review the available evi-

dence on the consequences of procrastination and then link these

results to recent research suggesting negative effects of pro-

crastinatory Facebook use on well-being.

2.3. Consequences of procrastination with Facebook

Research has identiﬁed several detrimental consequences of

procrastination for task performance and well-being. A speciﬁc

focus of this research has been on the consequences of dilatory

behavior in the academic domain (Kim &Seo, 2015; Steel, 2007).

Procrastination is particularly prevalent among university students,

who typically face complex tasks in self-directed learning settings

that leave a lot of leeway for ‘slacking’and irrational delay. More-

over, Facebook seems to be a particularly prominent tool for pro-

crastination among students (Hinsch &Sheldon, 2013; Quan-Haase

&Young, 2010). In the present investigation, we thus focus on the

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e76 67

negative effects of procrastination with Facebook in the college

student population.

A large body of research underlines the negative consequences

of procrastination for academic performance (Kim &Seo, 2015;

Steel, 2007). Delaying intended academic tasks can result in

poorer performance on subsequent trials to complete the tasks, for

example, because time pressure rises (Ferrari, 2001). As students

become aware of their decreasing performance due to procrasti-

nation, they start to ruminate (Flett, Stainton, Hewitt, Sherry, &Lay,

2012) and worry (St€

ober &Joormann, 2001) about their delay,

which leads to increased anxiety (Lay &Schouwenburg, 1993) and

feelings of guilt (Pychyl et al., 2000). These negative self-

evaluations greatly impair procrastinators’psychological well-

being. Speciﬁcally, several studies show a strong link between

procrastination and stress: As procrastinators ﬁnally tackle their

postponed work, they typically struggle with the drawbacks of

decreased time for task completion as well as negative self-

evaluative thoughts and emotions, which increases levels of

stress (e.g., Flett et al., 2012; Sirois &Kitner, 2015; Sirois, 2014).

Furthermore, in a longitudinal study conducted among students

(Tice &Baumeister, 1997), procrastination of academic tasks was

not only related to stress as the deadline got closer during the se-

mester, but also to symptoms of stress-related illness.

Taken together, the results from procrastination research

clearly demonstrate the negative consequences of procrastinatory

behavior for students’academic performance and well-being (Kim

&Seo, 2015; Sirois &Kitner, 2015). We propose that procrastina-

tion with Facebook will have similar detrimental effects in the

academic domain and that these effects extend to students’overall

well-being. This rationale is supported by communication research

linking Facebook use to decreased academic performance (e.g.,

Junco, 2012; Kirschner &Karpinski, 2010; Rosen et al., 2013),

which suggests that students frequently and irrationally turn to

Facebook instead of their academic tasks (i.e., procrastinate with

Facebook). Due to the resulting decrease in academic performance,

procrastination with Facebook could thus elicit strong stress re-

actions in the academic domain (e.g., feeling ‘crushed’or ‘over-

whelmed’by the academic work that is piling up due to

procrastination). Accordingly, we predict that the frequency of

procrastination with Facebook is positively related to academic

stress (H4).

Beyond these effects of procrastination with Facebook on

domain-speciﬁc academic stress, procrastination research un-

derlines the detrimental consequences of procrastination for stu-

dents overall well-being (i.e., their well-being beyond the academic

domain) (Steel, 2007). Initial evidence from cross-sectional and

experience sampling research has also linked Facebook use to

impaired overall well-being among students (Kross et al., 2013;

Satici &Uysal, 2015). Experimental research by Sagioglou and

Greitemeyer (2014) further indicates that Facebook use impairs

affective well-being (e.g., current mood) because it is perceived as

“less meaningful, less useful, and more of a waste of time”than

other (online) activities (p. 361). Since procrastination is a highly

dysfunctional activity that is essentially characterized by a mean-

ingless ‘wasting of time’, these results clearly suggest negative ef-

fects of procrastination with Facebook on affective well-being.

Moreover, a recent intervention study found that decreases in so-

cial media use were associated with decreased procrastination and

increased cognitive well-being (i.e., life satisfaction) over time

(Hinsch &Sheldon, 2013). Together, the available evidence suggests

that procrastination with social media may play a signiﬁcant role in

the negative relationship between general Facebook use and

overall well-being. Accordingly, we propose that procrastination

with Facebook contributes to the strains that Facebook use places

on students’overall well-being beyond the academic domain. We

thus hypothesize that the frequency of procrastination with Face-

book is positively related to Facebook-induced strains on students’

overall well-being (H5).

To address the hypothesized predictors (H1eH3) and detri-

mental effects (H4eH5) of procrastination with Facebook, we

conducted two studies. Study 1 was designed to establish, whether

Facebook is a frequently used ‘tool’for procrastination among

students and whether the frequency of procrastination with Face-

book can be predicted by trait self-control (H1), habitually checking

Facebook (H2), and the enjoyment of Facebook use (H3). Study 2

was designed as a follow-up study with two primary goals: (a) to

test whether the hypothesized predictors of procrastination with

Facebook can be replicated in a second student sample and (b) to

examine whether procrastination with Facebook is positively

associated with academic stress (H4) and Facebook-induced strains

(H5). Additionally, Study 2 addressed some of the methodological

limitations of Study 1.

3. Study 1

3.1. Method

3.1.1. Participants

In Study 1, hypotheses H1eH3 were tested with data from a

convenience sample of student Facebook users. Participants were

recruited by 30 undergraduate students through their online social

networks on Facebook. Our student recruiters were enrolled in the

communication program at a large University in Germany. Re-

cruiters were asked to distribute the link to an open online survey

among their friends on Facebook via public status updates, by

posting in Facebook groups, or by writing personal messages.

When following the link, participants were ﬁrst provided with

general information about the aim of the study and then asked for

their consent. Afterwards they completed the measures reported

below as well as additional questions about their general social

media use. Finally, participants provided demographic information

and were asked whether they studied at a German university.

Seven hundred seventy-one individuals started the survey, 480 of

which completed the questionnaire (62%). Of those 480 re-

spondents, 120 were excluded because they were not students and

another ﬁve cases were excluded due to missing data. Thus, our

ﬁnal sample consisted of N¼354 student Facebook users (71.2%

female, M

age

¼22.89, SD ¼2.51).

Frequent use of Facebook was a common activity in the

sample: Seventy-eight percent of participants reported that they

use Facebook on six or seven days of a typical week. On average,

participants estimated their use of Facebook at about 73 min per

day (SD ¼77). Compared to the results of a representative study

on German Internet users (Busemann, 2013), these usage pat-

terns closely resemble those of the German population between

the ages 14 to 29. In this population, 75 percent report daily

social media use and an average of 87 min spent on social media

per day.

Although more prevalent among students, procrastination is also a highly

relevant and detrimental behavior in the general population. Studies using multi-

national samples underline that procrastinatory behavior can become chronic

and problematic for about 20% of the adult population (Ferrari, Diaz-Morales,

O’Callaghan, Diaz, &Argumedo, 2007; Steel &Ferrari, 2013). Accordingly, we

believe that procrastination with widely popular online media such as Facebook is

also relevant in the general population. However, for the purpose of this early

research on the psychological predictors and effects of procrastination with media

use, we focus on students as a population that is particularly likely to procrastinate

with online tools such as Facebook (Hinsch &Sheldon, 2013; Quan-Haase &Young,

2010; Steel, 2007)

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e7668

3.1.2. Measures

All constructs were measured using multi-item Likert scales,

which showed satisfactory internal consistencies (Cronbach’s

alpha) and composite reliabilities (CR) >0.70 (see Table 1 for details

on reliabilities, means, and standard deviations).

We conducted a

series of exploratory factor analyses (EFA) with varimax rotation on

all scales in Study 1 to ﬁrst test the structure of each construct

before conducting further analyses.

Trait self-control was measured with eight items from the Brief

Self-Control Scale (Tangney et al., 2004), which assesses the indi-

vidual capacity to resist temptations and control unwanted urges.

The items (e.g., “I am good at resisting temptation”) were measured

on a scale from 1 (does not apply at all)to5(fully applies). The scale

showed a unidimensional structure (eigenvalue ¼2.93) and

acceptable factor loadings ranging from 0.48 to 0.74, which corre-

sponds with the results of a recent revision of the scales psycho-

metric properties (Lindner, Nagy, &Retelsdorf, 2015).

Participants’Facebook checking habit was assessed with four

items from the Self-Report Habit Index (Verplanken &Orbell,

2003). These four items (“I often check my Facebook account

without having to consciously remember”,“Using Facebook is

something I do without thinking.”,“Sometimes I start using Face-

book before I realize I’m doing it.”,“While logging in on Facebook, I

think about completely different things.”)reﬂect automatic acti-

vation of Facebook checking behavior (Gardner et al., 2012) and

were measured on a scale from 1 (does not apply at all)to7(fully

applies). The scale showed a unidimensional structure

(eigenvalue ¼2.51) with factor loadings exceeding 0.65.

Enjoyment of Facebook use was measured with two items that

were adapted from studies by Quan-Haase and Young (2010) and

Smock et al. (2011). Participants responded to the items “I use

Facebook because it is fun”and “I use Facebook because it is

entertaining”on a scale ranging from 1 (does not apply at all)to5

(fully applies). The scale had a unidimensional structure

(eigenvalue ¼1.20) with factor loadings of 0.77.

Finally, participants reported the frequency of their procrasti-

nation with Facebook by responding to four items from the Pro-

crastination Scale (Tuckman, 1991), which was already used to

measure procrastination with media use in previous research

(Reinecke, Hartmann et al., 2014). The items were adapted to

measure Facebook use as irrational procrastinatory behavior (“I

used Facebook although I had more important things to do”,“I used

Facebook although I had more important things to do.”,“I used

Facebook although I knew that I had an important task to com-

plete.”,“I used Facebook although I had planned to get something

done.”) on a scale ranging from 1 (never)to5(very often). Partici-

pants were asked to estimate the frequency of procrastination with

Facebook by thinking about their Facebook use in the last half year

when working at a computer. The scale showed a unidimensional

structure (eigenvalue ¼2.79) with factor loadings exceeding 0.79.

3.2. Results

In order to establish whether Facebook is used as a tool for

procrastination as suggested by prior research, we ﬁrst conducted a

descriptive analysis of the reported frequency of procrastination

with Facebook. Including all four items used to measure procras-

tination with Facebook in a mean index and using a conservative

estimate (M<2.00 on a scale from 1 to 5), only nine percent of

participants (n¼31) reported that, on average, they had “never”

procrastinated with Facebook in the last half year. In fact, pro-

crastination with Facebook was found to be a frequent behavior in

our student sample (M¼3.43, SD ¼0.98, scale 1e5).

Before testing our hypotheses, we then investigated the

convergent and discriminant validity of all constructs based on the

average variance extracted (AVE), the maximum shared variance

(MSV), and the average shared variance (ASV). Convergent validity

was satisfactory for all scales with AVEs >0.50, except for trait self-

control (AVE ¼0.37). However, all variables, including trait self-

control, showed satisfactory discriminant validity with AVEs

considerably larger than the MSV and ASV values. The suboptimal

level of convergent validity for trait self-control corresponds with

the moderate factor loadings found in our previous exploratory

factor analysis (see 3.1.2 Measures). Although these values

demonstrate room for improvement, they mirror the ﬁndings of a

recent investigation of the psychometric properties of the Brief

Self-Control Scale (cf., Lindner et al., 2015). This low convergent

validity is indicative of the complexity of trait self-control, which is

expressed in the diversity of the items of the Brief Self-Control Scale

(Tangney et al., 2004). However, a unidimensional structure of the

scale seems to outperform alternative two-dimensional structures

(Lindner et al., 2015). Since the Brief Self-Control Scale is a

frequently used and prevalidated measure of trait self-control that

shows convergent validity with other self-control measures

(Duckworth &Kern, 2011) and connects to a large body of existing

research (de Ridder et al., 2011), we decided to retain this variable

in our model in its current form.

We thus continued our analysis by testing the hypothesized

relationships. To test H1eH3, we computed a structural equation

model (SEM) using the AMOS 22 software package. Additionally,

means, standard deviations, and zero-order correlations for all SEM

variables were calculated using SPSS 22 (see Table 1 for details). In

Model 1 (Fig. 1), trait self-control, Facebook checking habit, and

Facebook enjoyment were included as exogenous variables and the

frequency of procrastination with Facebook was included as the

endogenous variable. Two covariances between exogenous vari-

ables (checking habit and trait self-control as well as checking habit

and enjoyment) were included in the model due to moderate zero-

order correlations (see Table 1).

The maximum likelihood (ML) method was chosen for model

estimation. Although the data were not normally distributed (Mar-

dia’s multivariate kurtosis estimate ¼28.109), the ML method was

chosen as it is comparatively robust against variations in kurtosis

(Olsson, Foss, Troye, &Howell, 2000). To cope with non-normality,

however, all hypotheses were tested using the bootstrapping

Table 1

Means, standard deviations, scales, reliabilities, and zero-order correlations for SEM variables (Study 1).

MSDRange

CR 1. 2. 3. 4.

1. Trait self-control 2.94 0.72 1e5 0.82 0.82 e

2. FB checking habit 3.99 1.74 1e7 0.87 0.87 0.17

3. FB enjoyment 3.73 0.92 1e5 0.75 0.75 0.04 0.21

4. Frequency of procrastination with FB 3.43 0.98 1e5 0.90 0.90 0.40

***

0.36

***

0.25

***

Note. Based on N¼354 participants and two-tailed signiﬁcance tests. High values (5 or 7) represent high levels for each construct. FB ¼Facebook. CR ¼composite reliability.

p<0.05,

p<0.01,

***

p<0.001.

All measures used in Studies 1 and 2 can be obtained from the ﬁrst author upon

request.

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e76 69

method. Based on 5000 bootstrap samples with replacement, 95%

bias-corrected conﬁdence intervals were computed for signiﬁcance

testing of all parameters in Model 1 (Fig. 1).

The model showed an acceptable ﬁt(Little, 2013, pp. 109e117)

to the data (

¼316.460, df ¼130, p <0.001,

/df ¼2.434,

CFI ¼0.932, RMSEA ¼0.064 (90% C.I.: 0.055, 0.073), and

SRMR ¼0.060) and conﬁrmed hypotheses H1eH3 (see Fig. 1). As

expected (H1), trait self-control was negatively and signiﬁcantly

related to the frequency of procrastination with Facebook

(

¼0.41, p<0.001). In turn, habitually checking Facebook

(

¼0.29, p<0.01) and enjoyment of Facebook use (

¼0.26,

p<0.001) were positively and signiﬁcantly related to the frequency

of procrastination with Facebook, conﬁrming H2 and H3. Together,

the three predictors explained 40% of the variance in the frequency

of procrastination with Facebook (R

¼0.40, p<0.01).

3.3. Discussion

Study 1 was designed to assess whether the proposed set of

predictors (H1eH3) can explain the frequency of procrastination

with Facebook. The observed structural relationships provided

considerable support for the three hypothesized predictors of

procrastination with Facebook (trait self-control, habitual Facebook

checking, and enjoyment of Facebook use). However, in order to

reduce the possibility that these results were speciﬁc to the sample

under investigation, we aimed at replicating this model in a second

sample. In addition to establishing the validity of our hypothesized

predictors, Study 2 also aimed at addressing the possible conse-

quences of procrastination with Facebook (H4 and H5), thus

signiﬁcantly extending the ﬁndings of Study 1.

4. Study 2

4.1. Method

4.1.1. Participants

We conducted a second online survey with data from another

convenience sample of student Facebook users from Germany.

Analogously to Study 1, participants were recruited via un-

dergraduates’social networks on Facebook. Our 28 student re-

cruiters were enrolled in the communication program at the same

University as in Study 1 and followed the same procedure as in

Study 1. In contrast to Study1, however, non-student participants

were ﬁltered out at the beginning of the survey, rather than

excluded from data analyses subsequently. Five-hundred sixty-one

individuals started the survey, 369 of which reported to be students

and completed the questionnaire (66%). A total of 35 cases were

excluded due to missing data, resulting in a ﬁnal sample of N¼345

student Facebook users (62.3% female, M

age

¼21.17, SD ¼1.98).

Intensity of Facebook use was comparable to Study 1 (M¼73 min

Facebook use on a typical day, SD ¼90).

4.1.2. Measures

Trait self-control and Facebook checking habit were measured

with the scales outlined in Study 1. A series of EFAs with varimax

rotation were conducted on all scales in Study 2 to test the structure

of each construct before conducting further analyses. The scale

measuring trait self-control again showed a unidimensional

structure (eigenvalue ¼2.84) and factor loadings ranging from 0.43

to 0.74 (cf., Lindner et al., 2015). The measure of participants’

Facebook checking habit also showed a unidimensional structure

(eigenvalue ¼2.09) and factor loadings ranging from 0.55 to 0.83.

The frequency of procrastination with Facebook was measured

with the same items used in Study 1. However, we extended the

scope of the procrastination measure to include all forms of pro-

crastinatory Facebook use. Thus, participants in Study 2 were asked

to base their estimates of the frequency of procrastination with

Facebook on their overall Facebook use (as compared to their

Facebook use in the last half year in Study 1), including mobile

access to Facebook via smartphones and tablets. Again, the scale

showed a unidimensional structure (eigenvalue ¼3.13) and factor

loadings exceeding 0.86.

Furthermore, to avoid problems with Heywood cases in the

subsequent structural equation modelling (Chen, Bollen, Paxton,

Trait Self-

Control

FB Enjoyment

FB Checking

Habit

.27***

Procrastination

with FB

-.41***

.29**

.26***

R²=.40**

-.17*

Fig. 1. SEM for trait self-control, Facebook checking habit, and Facebook enjoyment as predictors of procrastination with Facebook (Study 1) Note. Observed structural equation

model based on N¼354 participants. Fit indices are

¼316.460, df ¼130, p<0.001,

/df ¼2.434, CFI ¼0.932, RMSEA ¼0.064 (90% C.I.: 0.055, 0.073), SRMR ¼0.060. Scores in the

ﬁgure represent standardized path coefﬁcients. Signiﬁcance levels are based on 5000 bootstrap samples with replacement and 95% bias-corrected conﬁdence intervals. FB ¼Fa-

cebook.

p<0.05,

p<0.01,

***

p<0.001.

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e7670

Curran, &Kirby, 2001), enjoyment of Facebook use was measured

with three items in Study 2 (as compared to only two items in Study

1). The items (“I enjoy using Facebook”,“Using Facebook is fun.”,“I

feel entertained by the use of Facebook.”) were taken from a recent

study that speciﬁcally focused on the enjoyment of Facebook use

(Reinecke, Vorderer et al., 2014). The scale had a unidimensional

structure (eigenvalue ¼1.56) with factor loadings exceeding 0.60.

To assess negative consequences of procrastination with Face-

book, two additional variables were included in Study 2: First,

participants reported their level of perceived academic stress on

three items adapted from the Perceived Stress Scale (Cohen,

Kamarck, &Mermelstein, 1983). The items (“I feel very stressed

when I try to get work for my studies done”,“It feels as if the dif-

ﬁculties in my studies are piling up so high that I cannot overcome

them.”,“I feel unable to cope with all the upcoming task in my

studies.”) were rated on a scale from 1 (never)to6(very often). The

scale showed a unidimensional structure (eigenvalue ¼2.04) with

factor loadings exceeding 0.80.

As a second measure of well-being, participants reported how

often they perceived strains in different spheres of life as a conse-

quence of their overall Facebook use on a scale from 1 (never)to6

(very often). Six items measuring Facebook-induced strains on well-

being (“My Facebook use …”:“…impairs my general well-being.”,

“…puts strains on my personal relationships.”,“…leads to stress in

my day to day life.”,“…makes it more difﬁcult to relax in my day to

day life.”,“…impairs my temporary moods.”,“…hinders my per-

sonal growth.”) were developed based on prior research (e.g.,

Beutel et al., 2011; Kross et al., 2013; Sagioglou &Greitemeyer,

2014) that assessed negative consequences of Internet use on

different well-being dimensions (e.g., global, affective, or social

well-being, Huta &Waterman, 2014). The scale showed a unidi-

mensional structure (eigenvalue ¼3.34) and factor loadings

exceeding 0.61. All scales in Study 2 showed satisfactory internal

consistencies (Cronbach’s alpha) and composite reliabilities

(CRs) >0.70 (see Table 2 for details).

4.2. Results

We began our analysis by testing the convergent and discrimi-

nant validity of all constructs based on their AVE, MSV, and ASV

values. As in Study 1, convergent validity was satisfactory for all

scales with AVEs >0.50, except for trait self-control (AVE ¼0.36).

All variables, including trait self-control, showed satisfactory

discriminant validity with AVEs considerably larger than the MSV

and ASV values. Consistent with the arguments presented in Study

1 (see 3.2 Results), we decided to continue our analysis albeit

recognizing the limited convergent validity of the trait self-control

measure.

To replicate the results of Study 1 (H1eH3) and to test the hy-

pothesized relationships in H4 and H5, a second SEM was

computed. The model (Model 2, Fig. 2) included the same exoge-

nous variables, endogenous variables, and covariances as in Study 1.

Additionally, academic stress (H4) and Facebook-induced strains

(H5) were included as endogenous variables, reﬂecting the conse-

quences of frequent procrastination with Facebook (see Table 2 for

details on SEM variables). The data in Study 2 was not normally

distributed (Mardia’s multivariate kurtosis estimate ¼80.919).

Thus, again, the model was estimated with the ML method and

signiﬁcance of all parameters was tested with the bootstrapping

method.

The model showed a good ﬁt to the data (

¼507.654, df ¼343,

p<0.001,

/df ¼1.480, CFI ¼0.962, RMSEA ¼0.037 (90% C.I.:

0.030, 0.044), and SRMR ¼0.070) and supported hypotheses

H1eH5 (see Fig. 2). Conﬁrming the results of Study 1, trait self-

control was also negatively and signiﬁcantly related to the

frequency of procrastination with Facebook in Study 2 (

¼0.33,

p<0.001). Moreover, habitually checking Facebook (

¼0.31,

p<0.001) and enjoyment of Facebook use (

¼0.31, p<0.001)

were again positively related to the frequency of procrastination

with Facebook. Thus, all hypothesized relationships (H1eH3) for

the predictors of procrastination with Facebook (R

¼0.37, p <0.01)

were replicated in Study 2. Furthermore, as hypothesized in H4 and

H5, the frequency of procrastination with Facebook was positively

related both with academic stress (

¼0.28, p<0.001) and FB-

induced strains on well-being (

¼0.44, p<0.001). Procrastina-

tion with Facebook explained signiﬁcant portions of variance in

both variables (R

¼0.08 and R

¼0.19, respectively, both

p<0.001).

As we found substantial direct effects for all hypothesized re-

lationships in Study 2, we additionally tested the indirect effects of

trait self-control, checking habit, and Facebook enjoymenton users’

well-being via procrastination with Facebook. To compare possible

indirect effects with respective direct effects, we computed an

alternative version of the model depicted in Fig. 2 that additionally

included six direct paths from our three exogenous variables (i.e.,

trait self-control, checking habit, and Facebook enjoyment) to the

two endogenous variables academic stress and Facebook-induced

strains. Signiﬁcance levels of standardized direct and indirect ef-

fects were based on 5000 bootstrap samples with replacement and

95% bias-corrected conﬁdence intervals (see Table 3 for details).

The model showed a good ﬁt to the data (

¼443.991, df ¼337,

p<0.001,

/df ¼1.317, CFI ¼0.975, RMSEA ¼0.030 (90% C.I.: 0.022,

0.038), and SRMR ¼0.048) and results indicated substantial indi-

rect effects. The frequency of procrastination with Facebook

signiﬁcantly mediated the effects of trait self-control (

¼0.09,

p<0.001), Facebook checking habit (

¼0.09, p<0.001), and

Facebook enjoyment (

¼0.09, p<0.001) on academic stress as

well as the effects of trait self-control (

¼0.12, p<0.001),

Facebook checking habit (

¼0.11, p<0.001), and Facebook

enjoyment (

¼0.12, p<0.001) on Facebook-induced strains on

students’overall well-being.

Results also indicated several signif-

icant direct effects between the exogenous variables and the two

well-being indicators, which are largely consistent with our general

argumentation (see Table 3). Notably, however, Facebook enjoy-

ment showed small, but signiﬁcant negative direct effects on both

academic stress (

¼0.17, p<0.05) and Facebook-induced strains

(

¼0.20, p<0.01), working in opposite direction to the positive

indirect effects and resulting in nonsigniﬁcant total effects (see

zero-order correlations in Table 2).

4.3. Discussion

Study 2 was designed to replicate the relationships investigated

in Study 1 (H1eH3) and to extend the hypothesized model by

including possible effects of procrastination with Facebook on

users’well-being (H4 and H5). The results of Study 2 underline that

trait self-control, habitually checking Facebook, and enjoyment of

Facebook use distinctly contribute to the frequency of procrasti-

nation with Facebook. Notably, the effects found for the hypothe-

sized relationships showed remarkable equivalence in

standardized size, signiﬁcance, and explained variance in both

studies (see Figs. 1 and 2 for details).

In Study 2, we also assessed the frequency of procrastination

with Facebook as a predictor of perceived academic stress and

Please note that the equivalence in size of the beta coefﬁcients for the indirect

effects is due to the almost equivalent effect sizes for the paths from trait self-

control, Facebook checking habit, and Facebook enjoyment to procrastination

with Facebook as well as subsequent rounding errors (see Fig. 2 for details).

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e76 71

Facebook-induced strains on overall well-being. The results support

the notion that procrastination with Facebook is associated with

higher academic stress and more Facebook-induced strains.

Moreover, the frequency of procrastination with Facebook medi-

ated the effects of all three predictors in our model (H1eH3) on

academic stress and Facebook-induced strains on well-being.

Together, the signiﬁcant direct and indirect effects found in our

SEM analysis provide strong support for our proposed theoretical

model. Intriguingly, our supplemental mediation analysis also

revealed an ambiguous role of Facebook enjoyment for students’

well-being: Enjoyment indirectly increased academic stress and

Facebook-induced strains by increasing procrastination with Face-

book. Simultaneously, however, enjoyment of Facebook use directly

decreased participants’self-reported academic stress and

Facebook-induced strains.

5. General discussion

Several lines of research suggest that Facebook is a frequently

used ‘tool for procrastination’, which could be particularly detri-

mental to the well-being of students. The central aim of this study

was to integrate and extend previous ﬁndings on the pro-

crastinatory use of Facebook. Speciﬁcally, our goal was to a)

identify important predictors of procrastination with popular on-

line media such as Facebook and b) investigate whether frequent

procrastination with Facebook affects students’psychological

well-being in the academic domain and beyond. The ﬁndings from

two consecutive studies conﬁrm that students’frequently turn to

Table 2

Means, standard deviations, scales, reliabilities, and zero-order correlations for SEM variables (Study 2).

MSDRange

CR 1. 2. 3. 4. 5. 6.

1. Trait self-control 2.87 0.71 1e5 0.81 0.81 e

2. FB checking habit 3.87 1.60 1e7 0.81 0.81 0.17

3. FB enjoyment 3.27 0.74 1e5 0.75 0.76 0.08 0.16

4. Frequency of procrastination with FB 3.45 1.42 1e6 0.94 0.93 0.36

***

0.36

***

0.33

***

5. Academic stress 3.36 1.20 1e6 0.86 0.86 0.29

***

0.02 0.04 0.25

***

6. FB-induced strains 2.00 0.97 1e6 0.88 0.88 0.19

***

0.38

***

0.01 0.40

***

0.19

***

Note. Based on N¼345 participants and two-tailed signiﬁcance tests. High values (5, 6, or 7) represent high levels for each construct. FB ¼Facebook. CR ¼composite reliability.

p<0.05,

p<0.01,

***

p<0.001.

Trait Self-

Control

FB Enjoyment

FB Checking

Habit

.16*

Procrastination

with FB

-.33***

.31***

R²=.37**

-.17*

FB-induced

Strains

Academic

Stress

R²=.19***

R²=.08***

.28***

.44***

Fig. 2. SEM for predictors of procrastination with Facebook and effects on academic stress and FB-induced strains on well-being (Study 2) Note. Observed structural equation model

based on N¼345 participants. Fit indices are

¼507.654, df ¼343, p <0.001,

/df ¼1.480, CFI ¼0.962, RMSEA ¼0.037 (90% C.I.: 0.030, 0.044), SRMR ¼0.070. Scores in the ﬁgure

represent standardized path coefﬁcients. Signiﬁcance levels are based on 5000 bootstrap samples with replacement and 95% bias-corrected conﬁdence intervals. FB ¼Facebook.

p<0.05,

p<0.01,

***

p<0.001.

Table 3

Standardized direct effects of trait self-control, Facebook checking habit, and Facebook enjoyment on academic stress and Facebook-induced strains and respective indirect

effects via procrastination with Facebook (Study 2).

Academic stress FB-induced strains

Direct effect Indirect effect Direct effect Indirect effect

1. Trait self-control 0.26

[0.40, 0.12] 0.09

***

[0.16, 0.05] 0.01 [0.14, 0.12] 0.12

***

[0.19, 0.07]

2. FB checking habit 0.11 [0.25, 0.02] 0.09

***

[0.04, 0.16] 0.33

***

[0.20, 0.45] 0.11

***

[0.07, 0.18]

3. FB enjoyment 0.17

[0.31, 0.03] 0.09

***

[0.04, 0.13] 0.20

[0.32, 0.08] 0.12

***

[0.07, 0.19]

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e7672

Facebook to procrastinate and consistently support our theoretical

assumptions on the predictors and effects of procrastination with

Facebook.

The ﬁrst part of our hypothesized model addressed the pre-

dictors of procrastination with Facebook and highlighted the

pivotal role of self-regulation processes for using Facebook as a

means of irrational task delay (i.e., procrastination). Our review

suggested that trait self-control as well as precursors of impulsive

media selectiondspeciﬁcally, habitual Facebook checking and high

Facebook enjoymentdpredict the frequency of procrastination

with online media such as Facebook. The results from our two

studies consistently conﬁrm our assumptions (H1eH3) and un-

derline that procrastination with Facebook is a form of “quintes-

sential self-regulatory failure”(Steel, 2007, p. 65) driven by low trait

self-control, strong Facebook checking habits, and high enjoyment

of Facebook use.

The second part of our model addressed the potentially detri-

mental effects of procrastination with Facebook on users’well-

being. We speciﬁcally focused our investigation on students’aca-

demic stress and overall well-being, as prior research suggests that

students are among the most likely individuals to be affected by

procrastination with Facebook. The results from Study 2 support

our notion that procrastination with Facebook contributes to both

the detrimental consequences of Facebook use in the academic

domain (H4) and to students’overall well-being (H5). The more

frequently students procrastinated with Facebook, the more their

academic stress increased and the more they reported strains

resulting from their overall Facebook use on several indicators of

well-being (e.g., temporary mood, personal relationships, and

personal growth).

The present research thus signiﬁcantly extends prior work on

media-related procrastination. Speciﬁcally, our studies have two

main implications for research on the uses and effects of (social)

online media. First, our research integrates the fragmentary evi-

dence on media-related procrastination and provides a coherent

model of procrastination with media content and mediated

communication as an outcome of deﬁcient self-regulatory pro-

cesses. The results underline that not only media users’capacity for

general self-control but also their tendency to impulsively and

unintentionally select speciﬁc media activities due to strong habits

and high media enjoyment drive procrastinatory media use.

Together, our set of predictors signiﬁcantly and consistently

explained almost 40 percent of the variance in the frequency of

procrastination with Facebook in both studies. Our work thus ex-

tends prior communication research by demonstrating that users’

unique patterns (i.e., habitualization) and appraisal (i.e., enjoyment)

of media use crucially inﬂuence the prevalence of procrastination

with these media beyond the mere quantity of media use (cf.,

Hinsch &Sheldon, 2013).

Second, our results underline that these speciﬁc patterns of

Facebook use affect users’well-being: As indicated by the signiﬁ-

cant mediation effects in Study 2, trait self-control, enjoyment, and

habitualization of Facebook use were linked to increased academic

stress and Facebook-induced strains by increasing the frequency of

procrastination with Facebook. Beyond conﬁrming the central role

of self-control for the consequences of procrastination with Face-

book, our results thus advance prior research by revealing the

crucial role of enjoyment and habitualization in the interplay of

procrastinatory Facebook use and well-being: At ﬁrst sight, the

enjoyment of Facebook use may seem to represent a primarily

functional Facebook experience that satisﬁes the user’s need for

affective well-being and mood repair. However, our results indicate

that appraising media use as a highly enjoyable activity can also

drive dysfunctional forms of media use due to increased procrasti-

nation that subsequently impairs users’well-being. Moreover, the

link between habitual Facebook checking, increased procrastina-

tion with Facebook, and decreased well-being supports the notion

that being permanently online and permanently connected

(Vorderer &Kohring, 2013) can have negative consequences on

users’everyday lives. Individuals that frequently and habitually

check Facebook to obtain new (social) information and social

interaction seem to be speciﬁcally prone to use Facebook even in

situations where its usage conﬂicts with more important upcoming

tasks, which reduces their performance and well-being.

Although the results from our two studies provide consistent

support for the hypothesized model, the present research comes

with a number of limitations. The ﬁrst limitation concerns the

cross-sectional nature of our data, which conﬁnes our structural

model to correlational interpretations. Several of the proposed re-

lationships could also show a reversed direction of effects: The

negative affect associated with stress and impaired well-being, for

example, could also predict students’procrastination with Face-

book as it might make students more susceptible to hedonically

pleasant activities such as Facebook use, even though they have

important work to complete (Sirois &Pychyl, 2013). However, the

evidence provided by prior research supports the causal directions

implied by our model. Academic stress, for example, seems to be a

consequence rather than a predictor of procrastination, as

demonstrated by research using longitudinal designs (e.g., Tice &

Baumeister, 1997). Moreover, our hypothesized predictors repre-

sent either relatively stable dispositional variables (trait self-

control) or patterns of overall Facebook use (Facebook checking

habit and Facebook enjoyment) that should inﬂuence the more

narrowly deﬁned use of Facebook for procrastination and not vice

versa. Nonetheless, the reciprocal effects of well-being, self-control,

and procrastination with media content should be investigated by

future research using longitudinal or experimental designs.

A second methodological limitation pertains to the measure we

used to assess participants’level of trait self-control in both studies.

Although the Brief Self-Control Scale (Tangney et al., 2004)isa

well-established and commonly used measure in self-control

research (de Ridder et al., 2011) that has shown to be predictive

of procrastination with media content (Reinecke &Hofmann, 2016),

our analyses indicated limited convergent validity in two student

samples. Future research should thus test whether the connection

between trait self-control and procrastination with Facebook can

be replicated with different measures of self-control capacity, such

as delay of gratiﬁcation tasks or peer ratings (Duckworth &Kern,

2011).

A third limitation concerns our focus on students. Procrastina-

tion is particularly common and detrimental in the academic

context, because students have considerable leeway in switching

between self-directed learning sessions and unstructured leisure

time (Kim &Seo, 2015). Thus, students’performance and well-

being is particularly dependent on their self-regulatory skills,

speciﬁcally, the ability to resist ubiquitously available online and

ofﬂine leisure temptations such as media use (Hofmann et al.,

2012). It is unclear and an important task for future research to

investigate whether our theoretical model of online procrastination

with Facebook can be replicated in the general population. Notably,

research on procrastination with media content has consistently

conﬁrmed frequent use of online media for procrastination among

diverse adult samples (e.g., Lavoie &Pychyl, 2001; Myrick, 2015;

Reinecke &Hofmann, 2016). We are thus conﬁdent that the same

basic psychological self-control processes identiﬁed in the present

study apply to procrastination with online media in the general

population.

Aﬁnal limitation concerns our focus on the negative outcomes of

procrastination with Facebook. As suggested by recent research

(Sirois &Pychyl, 2013), procrastination is driven by procrastinators’

A. Meier et al. / Computers in Human Behavior 64 (2016) 65e76 73

desire for short-term increases in positive affect and their need for

distraction from aversive tasks. However, the results from our

mediation analysis in Study 2 revealed that positive affect associ-

ated with Facebook use (i.e., Facebook enjoyment) did not only

increase participants’procrastination with Facebook, but also

served as a protective factor that seemed to reduce participants’

academic stress levels and the frequency with which they

perceived strains on their well-being as a consequence of their

Facebook use. Thus, it would be particularly interesting to further

investigate whether procrastination with Facebook results in

(short-term) affective well-being beneﬁts, for example, through

need satisfaction (Reinecke, Vorderer et al., 2014), self-afﬁrmation

(Toma &Hancock, 2013), or social sharing on Facebook (Choi &

Toma, 2014). A recent study found that social support via Face-

book can serve as a stress buffer (Nabi, Prestin, &So, 2013), which,

in turn, may counteract the negative well-being effects of irrational

procrastination with Facebook. Consequently, we believe that

future research can beneﬁt from a more ﬁne-grained perspective

on the uses and effects of online media such as Facebook by

addressing the dynamics between short-term beneﬁts and long-

term costs of Facebook use for well-being, particularly in the

context of procrastination.

While our research provides several key insights into the nature

of procrastination with Facebook as well as the role of self-control

processes in media use, several open questions remain. Speciﬁcally,

the generalizability of our proposed predictor model should be

investigated with regard to other ofﬂine and online media. It could

be a promising task for future research to compare how the unique

affordances of popular interpersonal (e.g., Instagram, Snapchat, or

WhatsApp), interactive (e.g., browser games), and non-interactive

(e.g., Netﬂix) forms of social and entertaining online media use

shape the prevalence and consequences of procrastination. Anec-

dotal evidence further suggests that non-hedonic online media

such as news websites or Wikipedia, or less demanding online tasks

such as checking one’s email, are the preferred tools for procrasti-

nation among some individuals. It could be argued that these forms

of procrastination are easier to justify and rationalize as they are

more likely to be perceived as ‘meaningful’activities, leaving pro-

crastinators with less detrimental or even positive effects on their

well-being (cf., Sagioglou &Greitemeyer, 2014). We encourage

other researchers to explore the potentially complex interplay be-

tween the selection of hedonic vs. non-hedonic and ‘meaningful’vs.

‘meaningless’media activities for procrastination and its effects on

different dimensions of well-being (e.g., hedonic vs. eudaimonic

well-being, Huta &Waterman, 2014; Oliver &Bartsch, 2010).

Beyond these more general avenues for future research, we

would like to outline two particular beneﬁts of a) investigating

procrastination as a speciﬁc and reoccurring pattern of media use

and of b) integrating self-control theory into research on the uses

and effects of media. We believe that our results provide valuable

impulses for research on the effects of online media use in learning

environments (e.g., Thompson, 2013) as well as research on media

multitasking (e.g., van der Schuur et al., 2015). Speciﬁcally, the

evidence reviewed and presented in this paper suggests that pro-

crastination is both an important moderator and mediator for the

effects of online media use on students’academic performance and

well-being: Students showing a relatively stable tendency to pro-

crastinate (i.e., high trait procrastination, Steel, 2007) should suffer

from negative consequences of dilatory Facebook use more

frequently, suggesting that procrastinatory tendencies moderate

the negative relationship between overall Facebook use and aca-

demic performance and well-being. Considering the tendency to

procrastinate as a moderator could thus help to clarify some of the

conﬂicting evidence on the outcomes of social media use (e.g.,

Thompson, 2013). Moreover, procrastination with online media

such as Facebook may mediate the negative effects of media

multitasking on performance and well-being. When students

frequently switch from academic ofﬂine tasks to online media ac-

tivities due to impulsive media selection, their media use can easily

extend to the point that it conﬂicts with more important tasks. The

frequency of “media-induced task switching”(Rosen et al., 2013,p.

948) could thus increase the frequency of reported procrastination

with media, which, in turn, should mediate the negative effects of

task-switching on performance and well-being. Moreover, multi-

tasking research could signiﬁcantly beneﬁt from investigating

whether students’(trait and state) capacity for self-control oper-

ates as a moderator of these effects.

Finally, our study did not address how individuals cope with

procrastinatory media use that interferes with their long-term

goals and psychological well-being. Hofmann et al. (2009) pro-

pose that in reaction to detrimental self-control failure, individuals

reﬂect on their behavior and form deliberate self-control standards.

Speciﬁcally, they argue that implementing restraint standards (e.g.,

keeping a diet) should counteract automatic impulsive reactions

such as habitual media selection. Media users struggling with

frequent media-related procrastination could thus attempt to

implement restraint standards that reduce their dilatory media use.

Recent research suggests that behavioral interventions, for

example, temporary reductions in Facebook use, are effective in

decreasing overall procrastination and in increasing life satisfaction

among students (Hinsch &Sheldon, 2013). Moreover, many users

seem to voluntarily commit to such “Facebook vacations”during

periods of increased work demand (Rainie, Smith, &Duggan, 2013).

Further investigating ‘media diets’and ‘media hiatus’as preventive

and interventive self-control strategies (Hofmann &Kotabe, 2012)

aimed at reducing procrastination thus seems to be a fruitful

endeavor for future research.

6. Conclusion

Overall, the present research furthers our understanding of

uncontrolled and potentially detrimental media use by investi-

gating what drives students’use of Facebook for procrastination.

The results from our two studies crucially extend prior research on

media use and procrastination by demonstrating that trait self-

control and users’speciﬁc patterns and appraisal of Facebook use

(i.e., habitualization and enjoyment) are crucial predictors of pro-

crastination with Facebook. Moreover, our results support the

notion that ‘Facebocrastination’signiﬁcantly impairs students’ac-

ademic and overall well-being. We thus hope that our work pro-

vides valuable impulses to future research that aims at addressing

the ubiquitous conﬂicts between online media use and the de-

mands of our day-to-day strivings in work and learning

environments.

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Students’ usage of Over-the-top (OTT) streaming platforms affecting their academic and socio-demographic profile

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Jun 2024

As the world is reeling under the effects of the COVID-19 pandemic, most people have faced the shift to online modes of communication in spheres like education, work from home and even entertainment. Students turned to over-the-top (OTT) platforms in order to relax and relieve stress. The present study attempts to measure the usage of OTT platforms and its effect on students’ academic lives concerning academic performance, concentration and productivity, health issues, time-management, and their socio-demographic profile. The study employed explanatory descriptive research designs and sent out instruments measuring usage of OTT and other variables to 800 students across India. The study obtained 535 successful responses from the students pursuing 11th grade to post-graduation. Data analysis included descriptive statistics, parametric t-test, ANOVA and MANOVA. The study revealed that students used OTT platforms extensively for entertainment. Descriptive data gave a detailed account of their academic lives during the COVID-19 crisis. Usage of OTT affected their academic performance, concentration and productivity, health and time management. The study recommends future researchers to find the positive and negative effects of OTT usage on the youth in the post-pandemic scenario.

Korelasi antara konformitas dengan cyberslacking pada mahasiswa

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May 2024

Background: Cyberslacking is a deviant behavior that is often carried out by students regarding internet use during lectures. Internet access is used for things that have nothing to do with academics. Conformity as a form of social influence is thought to have a relationship with cyberslacking which can make individuals tend to change their attitudes, behavior and beliefs to adapt to existing norms. Purpose: To determine the relationship between conformity and cyberslacking in students. Method: Quantitative research with correlational design. Proportional stratified random sampling technique was used to take a research sample of 346 students. Data collection was carried out using a conformity scale with a reliability value of 0.764 and a cyberslacking questionnaire with a reliability value of 0.901. The correlation analysis used is Spearman's rho. Results: The level of conformity and cyberslacking of respondents was mostly in the medium category with the respective percentages being (70.8%) and (82.7%). The results of the Spearman's rho correlation test obtained a p-value of 0.003, which shows that there is a significant relationship between conformity and cyberslacking. Conclusion: There is a positive and significant relationship between conformity and cyberslacking. Increased conformity will be followed by increased cyberslacking, and vice versa. Suggestion: Future researchers can analyze the factors that strengthen the relationship between conformity and cyberslacking in students. Keywords: Cyberslacking; Student; Suitability. Pendahuluan: Cyberslacking merupakan suatu perilaku menyimpang yang sering dilakukan oleh mahasiswa terkait penggunaan internet selama perkuliahan berlangsung. Akses internet tersebut digunakan untuk hal yang tidak ada kaitannya dengan akademik. Konformitas sebagai bentuk pengaruh sosial diprediksi memiliki hubungan dengan cyberslacking yang dapat membuat individu cenderung mengubah sikap, perilaku maupun keyakinannya untuk menyesuaikan diri dengan norma yang ada. Tujuan: Untuk mengetahui hubungan antara konformitas dengan cyberslacking pada mahasiswa. Metode: Penelitian kuantitatif dengan desain korelasional. Teknik proportionated stratified random sampling digunakan untuk mengambil sampel penelitian yang berjumlah 346 mahasiswa. Data dikumpulkan menggunakan conformity scale dengan nilai reliabilitas sebesar 0.764 dan kuesioner cyberslacking dengan nilai reliabilitas sebesar 0.901. Analisis korelasi yang digunakan adalah Spearman’s rho. Hasil: Tingkat konformitas dan cyberslacking responden sebagian besar berada pada kategori sedang dengan masing-masing persentase, yaitu (70.8%) dan (82.7%). Hasil uji korelasi Spearman’s rho diperoleh p-value sebesar 0.003 yang menunjukkan hubungan signifikan antara konformitas dengan cyberslacking. Simpulan:Terdapat hubungan positif dan signifikan antara konformitas dengan cyberslacking. Peningkatan konformitas akan diikuti dengan peningkatan cyberslacking, begitu pun sebaliknya. Saran: Peneliti selanjutnya dapat menganalisis faktor-faktor yang memperkuat hubungan antara konformitas dengan cyberslacking pada mahasiswa. Kata Kunci: Cyberslacking; Konformitas; Mahasiswa.

Çalışanlarda Gelişmeleri Kaçırma Korkusu (FoMO) ve İş Hayatına Yansımaları

Chapter

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May 2024

Adeviye Erdogan

Günümüzde iş dünyasında hızla değişen teknoloji ve sosyal medya platformlarının yaygın kullanımı, bireylerin sürekli olarak güncel bilgilere erişimini kolaylaştırmaktadır. Ancak, bu bilgi bolluğu ve sürekli bağlantı halinde olma durumu, çalışanlarda "Gelişmeleri Kaçırma Korkusu" veya FoMO (Fear of Missing Out) olarak adlandırılan bir durumu beraberinde getirmektedir.

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Constructing and development of the psycho-computing traits scale: a psychometric analysis of computer users and students in the field of computer science

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Psycho-computing refers to the study of the interaction between humans and computers, with the aim of understanding how people use computer applications in line with their needs and improving their experience. To achieve this goal, it is necessary to have a set of observable and measurable indicators of the behavioral practices of computer application users. Accordingly, a psycho-computing traits scale was developed that extracts six main dimensions of the behavioral practices of computer users and computer science students. To ensure the validity and reliability of the scale, it was applied to a survey sample of 150 students. Subsequently, the final version of the scale was applied to an experimental sample of 722 students to verify its psychometric properties. The results of the study indicate that the psycho-computing traits scale exhibits sound psychometric properties in terms of construct validity, as evidenced by the results of the Rasch model assumptions for the data obtained from its application. Moreover, the confirmatory factor analysis results demonstrate that the goodness of fit indicators align with the main dimensions of the scale. The study’s findings also suggest that the psycho-computing traits scale exhibits high reliability, as indicated by the results of the Rasch model for both person and item reliability. Therefore, the scale can be considered a valid tool for evaluating the psycho-computing traits of computer users and computer science students.

A Study on Determinants of Happiness among University Girl Students Using Social Media

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Full-text available

Dec 2020

Background: There are several substances where human beings get addicted to and social media could be one of them. Although social media is a tool of productivity, it also encourages unproductive activities such as procrastination that affects the mental health of the individual. Objectives: To assess the level of social media addiction, procrastination, happiness and its correlates with the background characteristics of the postgraduate girl students staying in the university hostel; and to identify the major predictors of the subjective happiness of the respondents. Materials and Method: There were 905 postgraduate girl students staying at Bharathidasan University girls' hostel. Of these, 277 were selected as sample using a simple random sampling technique. The data were collected using the Social Media Addiction Scale developed by the researcher, the Procrastination Scale developed by Lay (1986) and the Happiness Scale developed by Lyubomirsky and Lepper (1999). The reliability values for the scales were Alpha 0.868, 0.733 and 0.731 respectively. Result: The findings indicate that nearly two-thirds of the respondents scored a high level of procrastination (65.7%), social media addiction (64.6%) and just over half (51.6%) of the respondents have scored a low level of happiness. The finding also reveals that the happiness score is positively correlated with the current age, age at first use of mobile phone and negatively correlated with procrastination and addiction score. The regression and path analysis shows that the addiction score has had the most impact on the happiness score than the other predictors on the postgraduate university girl students using social media. Conclusion: Findings indicate the need for providing counselling in order to reduce social media addiction and procrastination so that happiness will be enhanced.

Effect of Social Media on Workplace Procrastination Among Employees in Bosnia and Herzegovina

Chapter

May 2024

The paper deals with workplace procrastination, which results from using the Internet and social media during working hours. Practice shows that the appearance of procrastination causes numerous negative consequences, both for employees and organizations. Although procrastination is exceptionally well represented in literature and researched from different angles, this phenomenon has not been given sufficient attention in Bosnia and Herzegovina (B&H), and therefore the number of papers on this topic is negligible. In order to study the effects of workplace procrastination caused by the use of social media, a field survey was conducted on a sample of 701 employees in B&H. Our results align with the findings of other studies worldwide and offer new insights into the topic.

Can mothers avoid guilt about their smartphone usage behavior? Effects of the availability norm and goal conflict on guilt, recovery, and accomplishment experiences

Article

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Balancing everyday tasks with the expectations of others regarding one's availability via smartphone is a challenge, especially for mothers. This research replicated and further developed studies by Halfmann and colleagues in 2021 and 2024 that yielded contradictory results regarding the conditions of feelings of guilt about (not) using the smartphone. More specifically, we investigated how smartphone-related goal conflict, the availability norm, and the parental phone use norm are related to mothers’ feelings of guilt when completing non-stressful everyday tasks. In addition, we researched how smartphone-related goal conflict and guilt are linked with experiences of recovery and task accomplishment. Results from a preregistered experience sampling study among 227 mothers of young children were largely in line with our hypotheses. They revealed, among others, that frequent smartphone use was more strongly linked with guilt when mothers perceived high goal conflict. If the availability norm was salient, little smartphone use was associated with more guilt. The results also indicated that the availability norm partly legitimized frequent smartphone use despite goal conflict. Nevertheless, overall, the findings suggest that mothers tend to experience low levels of guilt about their smartphone usage behavior and that these feelings do not impair the recovery from tasks.

Social Media Breaks: An Opportunity for Recovery and Procrastination

Article

Apr 2024

Social media (SM) breaks from studying can either support students' wellbeing and performance by acting as a recovery behaviour or subvert it by acting as a procrastination behaviour. It is currently unclear which influences lead an SM break to be a positive recovery vs. negative procrastination behaviour. A behavioural and emotion regulation (ER) perspective may help to elucidate these influences. In this paper, we report a semi-structured interview study with 20 undergraduates to explore their experiences of SM breaks when studying. Our analysis describes how motivational and environmental factors can influence a break's propensity for recovery or procrastination during the break initiation and execution phases. We apply an ER perspective to these reports and demonstrate how it helps to explain further in which circumstances SM breaks are likely to support recovery or procrastination. Based on this analysis, we present recommendations for designing interventions to support healthy breaks and reduce unhealthy ones.

The influence of Facebook intensity on life satisfaction and academic performance of college students during COVID-19 pandemic

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Apr 2024

Slacking Off or Winding Down? An Experience Sampling Study on the Drivers and Consequences of Media Use for Recovery Versus Procrastination

Article

Full-text available

Mar 2016
HUM COMMUN RES

Today's constant availability of media content provides users with various recreational resources. It may also challenge self-control, however, once media exposure conflicts with other goals and obligations. How media users deal with these self-regulatory chances and risks in their daily lives is largely unknown. Our study addressed the predictors and consequences of recreational and procrastinatory media use using experience sampling methodology (N = 215; 1,094 media use episodes). Results suggest that trait (self-control, performance goal orientation) as well as state variables (exhaustion) are significant predictors of media use for recovery versus procrastination. Whereas recreational media use showed a positive effect on entertainment, which in turn enhanced subjective well-being, negative self-evaluation elicited by procrastinatory media use negatively affected well-being.

Media multitasking and well-being of university students

Article

Full-text available

Feb 2016
COMPUT HUM BEHAV

This study examines the impact of media multitasking behaviors on university students' social and psychological well-being (indicated by social success, normalcy, and self-control measures). To address inconsistent findings in recent literature, we characterized media multitasking behaviors by motivations, characteristics, and contexts. In particular, we examined the motivation of the primary task and the synchronicity of the task when social interactions were involved. Synchronous social interactions were found to be significantly and positively associated with social success, normalcy, and self-control. However, as predicted, media multitasking during synchronous social interactions was associated with lower social success. Further, although increased media multitasking during cognitive activities was linked with decreased self-control, media multitasking during entertainment activities was correlated with increased social success, normalcy, and self-control.

Psychological Predictors of Young Adults' Use of Social Networking Sites

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Nov 2009

Ergebnisse der ARD/ZDF-Onlinestudie

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Jan 2013

Cognitive neuroscience of self-regulation failure

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Jan 2010

Wer nutzt was im Social Web?

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Jan 2013

K. Busemann

Structural equation modeling

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Jan 2001

D. Lehmann

Hooked on Facebook: The Role of Social Anxiety and Need for Social Assurance in Problematic Use of Facebook

Article

Sep 2015

There is a growing concern that excessive and uncontrolled use of Facebook not only interferes with performance at school or work but also poses threats to physical and psychological well-being. The present research investigated how two individual difference variables-social anxiety and need for social assurance-affect problematic use of Facebook. Drawing on the basic premises of the social skill model of problematic Internet use, we hypothesized that social anxiety and need for social assurance would be positively correlated with problematic use of Facebook. Furthermore, it was predicted that need for social assurance would moderate the relationship between social anxiety and problematic use. A cross-sectional online survey was conducted with a college student sample in the United States (N = 243) to test the proposed hypotheses. Results showed that both social anxiety and need for social assurance had a significant positive association with problematic use of Facebook. More importantly, the data demonstrated that need for social assurance served as a significant moderator of the relationship between social anxiety and problematic Facebook use. The positive association between social anxiety and problematic Facebook use was significant only for Facebook users with medium to high levels of need for social assurance but not for those with a low level of need for social assurance. Theoretical and practical implications of these findings were discussed.

The consequences of media multitasking for youth: A review

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Jul 2015
COMPUT HUM BEHAV

Toward a new(er) sociability: Uses, gratifications and social capital on Facebook

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Jan 2011

"Facebocrastination"? Predictors of using Facebook for procrastination and its effects on students' well-being

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