Загрузил monarx9n5

Internet addiction and Faceb00k addiction in Spanis wom with eating disorders

реклама
Journal Pre-proof
Internet addiction and Facebook addiction in Spanish women with
eating disorders
Isabel Panea-Pizarro, Fidel López-Espuela, Almudena MartosSánchez, Ana Teresa Domínguez-Martín, Luis Beato-Fernández,
José María Moran-García
PII:
S0883-9417(20)30217-X
DOI:
https://doi.org/10.1016/j.apnu.2020.07.023
Reference:
YAPNU 51304
To appear in:
Archives of Psychiatric Nursing
Please cite this article as: I. Panea-Pizarro, F. López-Espuela, A. Martos-Sánchez, et
al., Internet addiction and Facebook addiction in Spanish women with eating disorders,
Archives of Psychiatric Nursing (2020), https://doi.org/10.1016/j.apnu.2020.07.023
This is a PDF file of an article that has undergone enhancements after acceptance, such
as the addition of a cover page and metadata, and formatting for readability, but it is
not yet the definitive version of record. This version will undergo additional copyediting,
typesetting and review before it is published in its final form, but we are providing this
version to give early visibility of the article. Please note that, during the production
process, errors may be discovered which could affect the content, and all legal disclaimers
that apply to the journal pertain.
© 2020 Published by Elsevier.
Journal Pre-proof
Title page
Title: Internet addiction and Facebook addiction in
Spanish women with eating disorders.
Authors:
ro
-p
na
lP
Almudena Martos-Sánchez 1
Nurse Research. RN.
Mail: amartoss@sescam.jccm.es
re
Fidel López-Espuela *2
PhD. Bachelor Psychologist. RN
Mail: fidel.lopez.es@gmail.com
of
Isabel Panea-Pizarro *1
Nurse Research. RN.
Mail: isabelpanea.pizarro@hotmail.com
Jo
ur
Ana Teresa Domínguez-Martín 3,
Nurse Research. RN.
Mail: anat_dm@hotmail.com
Luis Beato-Fernández 1
MD. PhD.
Mail: lbeato@sescam.jccm.es
José María Moran-García 2
PhD.
Mail: jmmorang@unex.es
*
1
Equal contribution
Mental Health Department, Hospital General Universitario, Ciudad Real, Castilla la
Mancha, Spain.
2
Nursing Department, Nursing and Occupational Therapy College, University of
Extremadura, Caceres, Caceres, Spain
Journal Pre-proof
3 Nursing Department, Complejo Hospitalario Universitario de Cáceres, Cáceres,
Cáceres, Spain
Corresponding Author:
López-Espuela, Fidel
Avenida de la Universidad S/N. Cáceres, Cáceres, CP: 10003, Spain
Email address: fidellopez@unex.es
of
Acknowledgements
To all the participating women, without them the research would not have been possible.
-p
ro
To Juan, Pilar, Irene, Jaime and Elena.
re
Author Contributions: Conceptualization: IPP, FLE, LBF, ATDM; Data curation: IPP,
AMS; Methodology: AMS; FLE; Formal Analysis: JMMG; AMS; Writing- Original
na
Jo
ur
manuscript.
lP
Draft Preparation: JMMG, FLE, LBF, IPP, ATDM ; All authors revised and edited the
Journal Pre-proof
Internet Addiction and Facebook Addiction in Spanish Women with Eating Disorders.
Abstract:
Aim: We aim to investigate the association between the presence of eating disorders and both
Internet addiction (IA) and Facebook addiction (FA)in women suffering from eating disorders.
Methods: A total of 124 women completed three instruments: the Internet Addiction Test
(IAT), the Bergen Facebook Addiction Scale (BFAS) and a sociodemographic questionnaire.
Results: The proportion of FA was 37.9%. The distribution of risk of IA was 21.8%. When the
of
risk of Internet or Facebook addiction was compared with respect to eating disorders, no
ro
significant differences were found between groups (P=0.146 and P=0.086, respectively). Age
and Body Mass Index (BMI) were predictors of BFAS scores; The standardized beta
-p
coefficient (β) for age was -0.463 (P=<0.001), while for BMI it was 3.44; (P=0.001 being a
re
positive predictor of BFAS scores. For IAT scores, β age (negatively) =-0.415; (P<0.001) and β
for weight (positively) 3.657; (P<0.001) were identified.
lP
Conclusions: The presence of an eating disorder does not seem to be a factor that
characterizes the risk of Internet or Facebook addiction in our sample. As information
na
regarding the potential association between Internet and Facebook addiction and the presence
Jo
ur
of eating disorders is limited, we encourage further studies on this topic.
Keywords: anorexia nervosa; binge eating disorder; bulimia nervosa; eating disorders;
facebook addiction; internet addiction
Journal Pre-proof
Introduction
The Internet, an essential contemporary way of collecting information and making connections
with peers, friends and family, has become an increasingly important aspect of human life.
“Healthy Internet use” has been defined as a use of the Internet that makes it possible to reach
a precise objective within an adequate time frame and without conceptual or behavioral
complications [1]. Although Internet usage makes life easier, it can become unhealthy in some
cases [2]. The use of the Internet in an unhealthy way was first defined as Internet addiction (IA)
of
and first used in 1995 by psychiatrist Dr. Ivan Goldberg, who coined the term Internet addiction
ro
disorder along with a list of symptoms, later known as Internet dependency [3], pathological
Internet use [1] and problematic Internet use [2,4]. In the fifth edition of the Diagnostic and
-p
Statistical Manual of Mental Disorders (DSM-5), IA is not indexed among the non-substance
re
addictions, but Internet gambling disorder is catalogued in the appendix as a condition that
deserves further study [5]. Common characteristics used in the definition of Internet addiction
lP
disorder are the length of time spent on the Internet (Internet use greater than 5 hours/day has
been proposed as the threshold [2]), anxiety and anger when the Internet cannot be used, and
na
the continuous need to progressively increase the amount of Internet connection [6]. Up to five
different types of IA have been proposed [7], and although the classification has been criticized
Jo
ur
[8], addiction to social media networks such as Facebook could be included in the cyberrelationship additions [7,9,10].
Eating disorders have become an issue of global interest. Disordered eating among
adolescents and young women [11,12] is characterized by social, cultural, and psychological
circumstances related to eating attitudes and behaviors. The Internet also provides access to
information on a broad variety of topics including eating disorders. Not only as a way to get
information about how to lose weight but also, and more worrying, as a way to expose their
thinness, coach each other on using socially acceptable pretexts for refusing food, share
dangerous ways to achieve their goals, compare themselves or to compete to fast together,
advice on how to best induce vomiting and on using laxatives and emetics, post their weight,
body measurement, details of their dietary regimen or pictures of themselves to solicit
acceptance and affirmation [13]. These webpages offer not only information, but support, and
Journal Pre-proof
sense of community to individual with an eating disorder and explains the huge increase in our
society of Pro-Ana and Pro-Mia pages [14].
Thus, it is predictable that women suffering from high levels of body image anxiety (particularly
body image avoidance) might be more susceptible to Internet addiction [15]. While affective
dimensions of body image are important, it has been generally shown that attitudes have a
limited ability to predict behaviors [15]. Descriptive studies have reported that IA may be
associated with negative body image [16] and be comorbid with body dysmorphic disorder [17].
of
In adolescents and young adult females Internet dependency, in an association with eating
ro
disorders has been reported [18-20], with the proposed link between IA and disordered eating
being the mood regulation function (as a substitute for food) [21]. More recently, cyberaddiction
-p
screened by the Internet Addiction Test has been associated to eating disorders in French
re
young population [22]. Also in young population a clear pattern of association has been reported
between Social Media Networks usage and disordered eating behaviors [23], frequency of fast
lP
food eating [24] and a negative body image [25]. Anyway, to date, little is known about the
prevalence and the role of IA beyond scholars or adolescents diagnosed of eating disorders.
na
Research evidence also suggests that problematic Social Media Networks use, and particularly
Facebook affects large numbers of people worldwide impacting negatively in mental health and
Jo
ur
well-being [26, 27].
Research is needed in the context to understand how Internet, and Social Media Networks are
used by women with eating disorders. Because there is an association among body image
concerns, disordered eating, restricted social interactions, and social avoidance [21,28], it could
be hypothesized that Internet addiction might co-occur with disordered eating. We aim to screen
the use of Internet and Facebook in Spanish women diagnosed of eating disorders to settle the
base of further research that will analyze if such use has both a helpful or harmful component or
if Internet and Facebook use has a differential component between different types of eating
disorder.
Methods
Design and Setting
Journal Pre-proof
We performed an observational, descriptive and cross-sectional study of women consecutively
diagnosed and treated for eating disorders at the General University Hospital of Ciudad Real
(Spain) between February and November 2018.
The inclusion criteria to participate in the study were as follows: being female, being over 12
years old, and undergoing treated at our hospital both in outpatient and hospitalization setting.
The exclusion criterion was the presence of cognitive impairment or physical or mental
disability.
of
Ethics Consideration
ro
Procedures were established in concordance with the Declaration of Helsinki and approved by
the Ethics and Clinical Research Committee of Ciudad Real (Spain) (ref. 2017C/123). All
-p
patients signed a written informed consent form to participate in the study. Written informed
re
consent in minor patients has been obtained through their legal representatives.
lP
Variables and Tools
A specific questionnaire was designed in order to obtain for the following variables: age,
na
education level, marital status, and clinical data including eating disorder subtype, years since
diagnosis, history of previous treatments and hospitalization, weight, height, current diagnosis of

Jo
ur
anxiety or depression, smoker status, and comorbid conditions.
Internet Addiction Test
The IAT consists of 20 items that are scored using a five-point Likert scale (Supplemental table
1), and the test measures the frequency with which problematic situations emerge as a result of
Internet use. The test identifies two main groups of users according to the score obtained: 1)
normal users or users without problems (<40 points) and 2) users with a risk of IA (≥40 points)
[29]. The Internet Addiction Test was first translated into Spanish [30] and then further validated
in the Spanish population [31], with the conclusion that the Spanish short version of the IAT
represents a useful tool for the analysis of problems arising from misuse of the Internet in the
Spanish population.
Journal Pre-proof

Bergen Facebook Addiction Scale
The Bergen Facebook Addiction Scale (BFAS) was applied in the present study to evaluate the
risk of FA [9]. The BFAS is a self-report 6-item Likert scale (see Supplemental table 2) with each
item scored from 1 (very rarely) to 5 (very often). A score between 0 and 10 is normal, 11–14
indicates the possibility of Facebook addiction, and 15 and above indicates FA. The Bergen
Facebook Addiction Scale has also been recently validated in a population of Spanish young
adults [32], which shows that the Spanish version of the BFAS provides useful evidence for
research on behavioral addictions; its inclusion in batteries that assess social network addiction
ro
of
is recommended.
Statistical Analysis.
-p
Some of the studied variables were not normally distributed (Shapiro-Wilk test P<0.05), so a
re
two-step approach was used to normalize the data before statistical analyses when appropriate
[33,34], including transforming the variable into a percentile rank, followed by applying an
lP
inverse normal transformation to the results derived from the first step. Descriptive analyses
were conducted for all variables, including the mean (SD). The following analyses examined the
na
transformed versions of those variables. Pearson’s correlations were used to explore the
relationships between the IAT and BFAS scores with a partial correlation analysis with
Jo
ur
adjustment for age and BMI (kg/m2). A multiple linear regression (using the enter method) was
used to examine whether the studied variables, age (years), BMI (kg/m2), years since
diagnosis, marital status, depression, education level, smoker status, ever hospitalized and
eating disorder subtype were predictors of the IAT or BFAS scores. Some subgroup analyses
were performed, and comparisons between groups were performed using the unpaired
Student’s T-test or one-way ANOVA when appropriate. A p value of <0.05 was considered
statistically significant. Effect sizes for differences in continuous variables are given as Cohen’s
d. All statistical analyses were conducted using the IBM SPSS statistical analysis software
package (version 22.0).
Results
Journal Pre-proof
A total of 124 women diagnosed with eating disorders aged 27.3(±10.1) years were
included in this study. The sociodemographic, biological and clinical characteristics of the
participants are shown in Table 1. According to the IAT, the distribution of potential risk of
Internet addiction was 21.8% (n=27) in the global sample. According to the BFAS, the
distribution of Facebook addiction was 37.9% of the whole sample (n=47). There were
statistically significant differences among the potential presence of Facebook addiction (37.9%),
absence of Facebook addiction (41.1%) and risk of Facebook addiction (21%) (P= 0.013). A
comparison based on the eating disorder diagnosis and clinical and socio-demographic
of
variables (Table 1) and in relation to Facebook or Internet addiction is also given in Table 2.
ro
When the potential risk of Internet or Facebook addiction was compared with respect to the
presence of an eating disorder, no significant differences were found between groups (P=0.146
-p
and P=0.086, respectively) (Table 2).
re
Mean BFAS and IAT scores are compared globally and by addiction components in Table
2. No statistically significant differences were observed in the mean scores for the BFAS and
lP
IAT based on the eating disorder diagnosis. Similarly, no statistically significant differences were
observed in the addiction components of the BFAS between eating disorder subtypes (salience,
na
tolerance, mood modification, relapse, withdrawal (P=0.22) and conflict (P=0.159). Furthermore,
no statistically significant differences were observed in the addiction components of the IAT
Jo
ur
(salience, excessive use, neglect of work, anticipation, lack of control and neglect of social life.
After further adjustment for age (Table 2), statistically significant differences between groups
were observed in the IAT score (P=0.04), including a score difference between the group with
anorexia nervosa and the group with eating disorder not otherwise specified (P=0.043) (effect
size Cohen’s d=0.56).
We further explored potential predictors of BFAS and IAT scores in women diagnosed with
eating disorders by multiple linear regression. The results are shown in table 3. Age and BMI
were predictors of BFAS scores. The standardized beta coefficient for age was -0.463
(P=<0.001) (negative predictor for BFAS score), while BMI was a positive predictor of BFAS
scores (standardized beta coefficient of 3.44; (P=0.001)). IAT scores had a negative association
with age and a positive association with weight, standardized beta coefficient for age =-0.415;
(P<0.001); and standardized beta coefficient for weight= 3.657 (P<0.001).
Journal Pre-proof
The differences between groups in the mean scores for the items of the BFAS
(Supplemental table 1) and the IAT (Supplemental table 2) were based on eating disorder
subtype. No statistically significant differences were observed in the analysis of the BFAS items.
However for the Eating Disorders Not Otherwise Specified (EDNOS) statistically significant
differences between the studied groups were observed in the IAT items “Do you snap, yell, or
act annoyed if someone bothers you while you are online?” (P=0.017) and the item “Do you
neglect household chores to spend more time online?” (P=0.009).
We finally performed a correlation study between BFAS and IAT scores. Both scores were
of
highly correlated (r=0.902; P<0.0001). This correlation remained statistically significant even
ro
after further adjustment for age (r=0.871; P<0.0001). We further explored the potential
correlations of BMI with BFAS and IAT scores. BMI was positively correlated with IAT scores
-p
(r=0.194; P=0.032), but this association disappeared after further adjustment for age (P>0.05)
re
while no significant correlations between BMI and BFAS scores were observed in the studied
Jo
ur
na
lP
sample
Journal Pre-proof
Discussion
This research screened Internet use by means of the Internet Addiction Test (IAT) and
Facebook use by means of the Bergen Facebook Addiction Scale (BFAS) in a cohort of women
with eating disorders. Internet and online social networking addiction shares similarities with
other behavioral addictions [9,10] which also have prevalent addictive symptoms [35,36]. The
IAT was originally developed for screening Internet addiction, while the BFAS was developed
for screening Facebook addiction. Our results confirm the previously reported positive
correlation between these factors in the general population [36], although those scores reflect
of
different addiction components [10, 35-38].
It has been suggested that generational and cultural differences may exist in many aspects
ro
of Internet and online social network usage and addiction [10,36]. Recent findings suggest that
-p
using image-oriented online social networks such as Facebook might be associated with greater
body dissatisfaction and disordered eating [39,40]; however, other studies have shown that
re
greater use of social networking sites is associated with body dissatisfaction but not with
lP
disordered eating [41], as we have observed in our study.
In adolescents, it has been reported that the amount of time spent on Facebook is
na
associated with disordered eating behaviors [42], but it seems that the way that online social
networks are used, not the time spent on them, predicts the association with eating disorders
Jo
ur
[39,43,44,45]. Particularly in the case of Facebook, our results support the findings that
intensive use was not associated with the presence of eating disorders [41,43], with the
probable cause of such associations being the engagement in social media comparisons on
Facebook. Thus, when Facebook is not used to compare oneself physically with others, the
greater use of Facebook could even lead to stronger social and emotional support and thus less
loneliness, which has been positively related to the presence of eating disorders [45,46].
The association between the presence of Internet addiction and the risk of eating disorders
has been studied in populations of adolescents and students [47,48]. Different studies have
reported that Internet addiction can lead to changes in lifestyle-related factors that can result in
irregular dietary habits [47,49]. Those studies mostly refer to populations representing
childhood, adolescence and young adulthood but little is known about the possible abusive use
of the Internet in populations of women diagnosed with and undergoing treatment for an eating
Journal Pre-proof
disorder. In 122 females aged 12-30 diagnosed of eating disorders and recruited thought
hospital-based treatment program, similarly to the method used by our research team,
participants reported spending more time that controls in reading forums and blogs related to
eating, weight and body image issues [50] suggesting that the internet use patters could be
eating disorders-specific as we aimed to explore in our study.
Compulsive internet use has also been reported in women diagnosed of eating disorders
[51], contrarily, in our study there were no associations between the presence of an eating
disorder and the measured IAT score, in fact, we observed that the main predictor of Internet
of
addiction and Facebook addiction is the age of the participant, with a negative association being
ro
the type of eating disorder not included in the models. The results reported in a Spanish cohort
of healthy young adults (n=1011) showed that gender (female) but not age (contrarily to our
-p
observations) was a negative predictor of Internet addiction [52]. In that sample, the risk of
re
Internet addiction was observed in 5.2% of the sample (pooled results for men and women),
which is lower than the risk observed in our sample (21.8%). However, the mean IAT score
lP
observed in our sample, 25.82 (25.51), almost matches the mean reported recently in a large
study that involved the application of the IAT in a cohort of 3279 participants from nine countries
na
[53]. Those authors reported in their manuscript a mean IAT score of 27.76 (15.41), with the
Jo
ur
population at risk of Internet addiction ranging from 8.4% to 45.7%. It is remarkable that the
assessment of Internet addiction is so difficult due to the potential presence of concomitant
disorders listed in DSM-5 [53,54]. In a cohort of 1979 Spanish female college students aged
20.3 ± 4.4 years the prevalence of problematic internet use measured by the IAT was of 6%
much lower than the potential risk screened in our sample, but probably not comparable due to
evident differences in the sociodemographic characteristics of both samples [55]. However, also
in Spanish college students a problematic internet uses higher to the observed in our sample
(36.5%) was reported being associated to a risk of developing eating disorders (adjusted odd
ratio=2.33; P=0.003) [56]. Overall, recent data from meta-analysis has showed that problematic
internet use is a predictor of eating disorders in childhood, adolescence and young adulthood
[57].
Journal Pre-proof
The prevalence of Facebook addiction in adolescents and young adults has been
described as 2% to 10% worldwide, with increases related to psychological distress and
decreases related to well-being [58]. The percentage reported in our study is higher than those
previously reported. However, the potential role of the use of social networking sites in the
eating disorder context is still under discussion. Users motivated to maintain their desire to be
thin could find closed groups of similarly minded individuals. On the other hand, users in the
recovery process could find groups providing support for recovery [59,60]. Thus, social
networking sites such as Facebook can have either positive or negative outcomes for patients
diagnosed with eating disorders.
of
No data have been reported to date about the assessment of both scales (IAT and BFAS)
ro
in Spanish women with eating disorders. Here, we provide initial data on Facebook and Internet
reference for further studies in this population.
-p
addiction assessed in Spanish women diagnosed with eating disorders, which may provide a
re
As a limitation of our study, we recognize that information regarding the potential
association between Internet and Facebook addiction and the presence of eating disorders is
lP
limited. In fact, there are no reliable data to compare with our results regarding the level of
Internet addiction and Facebook addiction in populations with eating disorders. Additionally, the
na
descriptive, cross-sectional design does not allow us to establish cause-effect associations
Jo
ur
between the IAT and BFAS scores and the presence of an eating disorder. Additionally, due to
the lack of group control in our study we cannot assure if the scores of IAT of BFAS observed in
the women diagnosed of eating disorders differ from those that could be potentially observed in
control healthy women with similar sociodemographic characteristics as well as life habits. Due
to the small sample size absence of statistically significant results might be an expression of
type II error. Further research should take our results into account to calculate larger sample
sizes that assure that enough statistical power is achieved. Moreover, the participants were
recruited in a convenience sample, which might potentially limit the study generalizability due to
the presence of bias in the participant recruitment.
Conclusions
Since Internet and social networking sites are an integral part of most eating disorder
patients’ lives, especially for younger individuals, it is important for nurses to understand the role
Journal Pre-proof
that both can have in patients’ everyday lives. Although it has been described that their use
could have a particular role in the onset of an eating disorder, we report data on their use by
young adult women already diagnosed and receiving treatment which is novel in Spanish
women. Our study does not allow to conclude if the screened use of Internet and Facebook in
the women studied has a helpful or harmful component or any specific relationship between IA
and FA in women suffering for eating disorders. So further research with appropriate healthy
controls and larger samples is deserved.
Taking into account that Internet is an essential contemporary way of making connections with
peers, friends and family, the psychopathological expression of eating disorders will probably
of
affect the “contents” of these new forms of communication instead of the “time”. In our opinion it
ro
is important for nurses to understand the role that both can have in patients’ everyday lives.
re
behaviors and its influence on them.
-p
Nurses should ask patients about Internet and Facebook usage in order to detect potential risk
lP
Funding: This research received no external funding.
References
Jo
ur
na
Conflicts of Interest: The authors declare no conflict of interest.
1. Davis RA. A cognitive-behavioral model of pathological Internet use. Comput Hum Behav.
2001;17(2):187-95.
2. Odacı H, Kalkan M. Problematic Internet use, loneliness and dating anxiety among young
adult university students. Comput Educ. 2010;55(3):1091-7.
3. Scherer K. College Life On-Line: Healthy and Unhealthy Internet Use. J Coll Stud Dev.
1997;38(6):655-65.
4. Davis RA, Flett GL, Besser A. Validation of a new scale for measuring problematic internet
use: Implications for pre-employment screening. Cyberpsychol Behav. 2002;5(4):331-45.
5. Association AP. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). American
Psychiatric Pub; 2013. 1520 p.
6. Young KS, Rogers RC. The relationship between depression and internet addiction.
Journal Pre-proof
Cyberpsychol Behav. 1998;1(1):25-8.
7. Mamun MAA, Griffiths MD. The association between Facebook addiction and depression: A
pilot survey study among Bangladeshi students. Psychiatry Res. 2019;271:628-33.
8. Griffiths M. Internet Addiction - Time to be Taken Seriously? Addict Res. 2000;8(5):413-8.
9. Andreassen CS, Torsheim T, Brunborg GS, Pallesen S. Development of a Facebook
Addiction Scale. Psychol Rep. 2012;110(2):501-17.
10. Kuss DJ, Griffiths MD. Online Social Networking and Addiction—A Review of the
Psychological Literature. Int J Environ Res Public Health. 2011;8(9):3528-52.
11. Field AE, Austin SB, Taylor CB, Malspeis S, Rosner B, Rockett HR, et al. Relation between
of
dieting and weight change among preadolescents and adolescents. Pediatrics.
ro
2003;112(4):900-6.
12. Patton GC, Selzer R, Coffey C, Carlin JB, Wolfe R. Onset of adolescent eating disorders:
-p
population based cohort study over 3 years. BMJ. 1999;318(7186):765-8.
re
13. Juarascio A, Shoaib A, Timko A. “Pro-Eating Disorder Communities on Social Networking
10.1080/10640266.2010.511918
lP
Sites: A Content Analysis” Eating Disorders, 2010. 18:393–407. DOI:
14. Borzekowski DLG, Schenk S, Wilson JL, Peebles R. “e-Ana and e-Mia: A Content Analysis
na
of Pro–Eating Disorder Web Sites.” Am J Public Health. 2010;100:1526–1534.
Jo
ur
doi:10.2105/AJPH.2009.172700
15. Rodgers RF, Melioli T, Laconi S, Bui E, Chabrol H. Internet addiction symptoms, disordered
eating, and body image avoidance. Cyberpsychology Behav Soc Netw. 2013;16(1):56-60.
16. Griffiths M. Does Internet and Computer «Addiction» Exist? Some Case Study Evidence.
Cyberpsychol Behav. 2000;3(2):211-8.
17. Shapira NA, Goldsmith TD, Keck PE, Khosla UM, McElroy SL. Psychiatric features of
individuals with problematic internet use. J Affect Disord. 2000;57(1-3):267-72.
18. Sevelko K, Bischof G, Bischof A, Besser B, John U, Meyer C, Rumpf HJ. The role of selfesteem in Internet addiction within the context of comorbid mental disorders: Findings from a
general population-based sample. J. Behav. Addict. 2018;7(4):976-984.
19. Rodgers RF, Melioli T, Laconi S, Bui E, Chabrol H. Internet Addiction Symptoms,
Disordered Eating, and Body Image Avoidance. Cyberpsychol. Behav. Soc. Netw.
2013;16(1):56-60.
Journal Pre-proof
20. Ivezaj V, Potenza MN, Grilo CM, White MA. An exploratory examination of AtRisk/Problematic Internet Use and disordered eating in adults. Addict. Behav. 2017;64:301-307.
21. Grabhorn R, Stenner H, Stangier U, Kaufhold J. Social anxiety in anorexia and bulimia
nervosa: the mediating role of shame. Clin Psychol Psychother. 2006;13(1):12-9.
22. Spillebout A, Dechelotte P, Ladner J, Tavolacci MP. Mental health among university
students with eating disorders and irritable bowel syndrome in France. Rev Epidemiol Sante
Publique. 2019;67(5):295-301. doi:10.1016/j.respe.2019.04.056.
23. Wilksch SM, O'Shea A, Ho P, Byrne S, Wade TD. The relationship between social media
use and disordered eating in young adolescents. Int J Eat Disord. 2019; doi:10.1002/eat.23198.
of
24. Bener A, Yildirim E, Torun P, Çatan F, Bolat E, Aliç S, et al. Internet Addiction, Fatigue, and
2019;17:959-969. doi:10.1007/s11469-018-9937-1.
ro
Sleep Problems Among Adolescent Students: a Large-Scale Study. Int J Ment Health Addict.
-p
25. Al Saud DF, Alhaddab SA, Alhajri SM, Alharbi NS, Aljohar SA, Mortada EM. The
re
Association Between Body Image, Body Mass Index and Social Media Addiction Among
Female Students at a Saudi Arabia Public University. Mal J Med Health Sci. 2019;15(1):16-22.
lP
26. Marino C, Gini G, Vieno A, Spada MM. The associations between problematic Facebook
use, psychological distress and well-being among adolescents and young adults: a systematic
na
review and meta-analysis. J Affect Disord. 2018;226:274-81.
Jo
ur
27. Marino C, Caselli G, Lenzi M, Monaci MG, Vieno A, Nikčević AV, Spada MM. Emotion
Regulation and Desire Thinking as Predictors of Problematic Facebook Use. Psychiatr Q.
2019;90(2):405-411. https://doi.org/10.1007/s11126-019-09628-1.
28. Rosen JC, Srebnik D, Saltzberg E, Wendt S. Development of a body image avoidance
questionnaire. Psychol Assess J Consult Clin Psychol. 1991;3(1):32-7.
29. Jelenchick LA, Becker T, Moreno MA. Assessing the psychometric properties of the Internet
Addiction Test (IAT) in US college students. Psychiatry Res. 2012;196(2-3):296-301.
30. Estévez L, Bayón C, De la Cruz J, Fernández-Líria A. Uso y abuso de Internet en
adolescentes. In: Echeburúa, F; Labrador, F.; Becoña, E. (eds.). Adicción a las nuevas
tecnologías En Jóvenes y adolescentes. 2009. Madrid: Pirámide. Pp:101-130.
31. Fernández-Villa T, Molina AJ, García-Martín M, Llorca J, Delgado-Rodríguez M, Martín V.
Validation and psychometric analysis of the Internet Addiction Test in Spanish among college
students. BMC Public Health. 2015;15(1):953.
Journal Pre-proof
32. Vallejo MA, Lonzoy AJEC, Capa-Luque W. ¿Hay alguien en línea?: Validez y fiabilidad de la
versión en español de la Bergen Facebook Addiction Scale (BFAS) en universitarios. Health
Addict Salud Drog. 2018;18(2):175-84.
33. Templeton GF. «A Two-Step Approach for Transforming Continuous Variables to Normal:
Implications and Recommendations for IS Research». Communications of the Association for
Information Systems. 2011; 28 (4). [Internet]. [cited 10 March 2020]. Available from:
https://aisel.aisnet.org/cais/vol28/iss1/4/. DOI: 10.17705/1CAIS.02804.
34. Lavado-García J, Roncero-Martin R, Moran JM, Pedrera-Canal M, Aliaga I, Leal-Hernandez
O, et al. Long-chain omega-3 polyunsaturated fatty acid dietary intake is positively associated
of
with bone mineral density in normal and osteopenic Spanish women. PLOS ONE.
ro
2018;13(1):e0190539.
35. Griffiths M. A ‘components’ model of addiction within a biopsychosocial framework. J Subst
-p
Use. 2005;10(4):191-7.
re
36. Intapong P, Charoenpit S, Achalakul T, Ohkura M. Assessing symptoms of excessive SNS
usage based on user behavior: Identifying effective factors associated with addiction
lP
components. En: Proceedings of the 20th Congress of the International Ergonomics Association
(IEA 2018) - Volume I: Healthcare Ergonomics [Internet]. Springer Verlag; 2019 [cited 14 March
na
2020]. p. 394-406. Available from: https://shibaura.pure.elsevier.com/ja/publications/assessing-
Jo
ur
symptoms-of-excessive-sns-usage-based-on-user-behavior--5
37. Young KS. The research and controversy surrounding internet addiction. Cyberpsychology
Behav Impact Internet Multimed Virtual Real Behav Soc. 1999;2(5):381-3.
38. Echeburúa E, de Corral P. [Addiction to new technologies and to online social networking in
young people: A new challenge]. Adicciones. 2010;22(2):91-5.
39. Holland G, Tiggemann M. A systematic review of the impact of the use of social networking
sites on body image and disordered eating outcomes. Body Image. 2016;17:100-10.
40. Smith AR, Hames JL, Joiner TE. Status update: maladaptive Facebook usage predicts
increases in body dissatisfaction and bulimic symptoms. J Affect Disord. 2013;149(1-3):235-40.
41. Howard LM, Heron KE, MacIntyre RI, Myers TA, Everhart RS. Is use of social networking
sites associated with young women’s body dissatisfaction and disordered eating? A look at
Black–White racial differences. Body Image. 2017;23:109-13.
42. Tiggemann M, Slater A. NetGirls: the Internet, Facebook, and body image concern in
Journal Pre-proof
adolescent girls. Int J Eat Disord. 2013;46(6):630-3.
43. Mabe AG, Forney KJ, Keel PK. Do you «like» my photo? Facebook use maintains eating
disorder risk. Int J Eat Disord. 2014;47(5):516-23.
44. Fardouly J, Pinkus RT, Vartanian LR. The impact of appearance comparisons made through
social media, traditional media, and in person in women’s everyday lives. Body Image.
2017;20:31-9.
45. Walker M, Thornton L, De Choudhury M, Teevan J, Bulik CM, Levinson CA, et al. Facebook
Use and Disordered Eating in College-Aged Women. J Adolesc Health Off Publ Soc Adolesc
Med. 2015;57(2):157-63.
of
46. Levine MP. Loneliness and eating disorders. J Psychol. 2012;146(1-2):243-57.
ro
47. Alpaslan AH, Koçak U, Avci K, Uzel Taş H. The association between internet addiction and
disordered eating attitudes among Turkish high school students. Eat Weight Disord - Stud
-p
Anorex Bulim Obes. 2015;20(4):441-8.
re
48. Tao Z, Wu G, Wang Z. The relationship between high residential density in student
dormitories and anxiety, binge eating and Internet addiction: a study of Chinese college
lP
students. Springer Plus. 2016;5(1):1579.
49. Kim Y, Park JY, Kim SB, Jung I-K, Lim YS, Kim J-H. The effects of Internet addiction on the
na
lifestyle and dietary behavior of Korean adolescents. Nutr Res Pract. 2010;4(1):51-7.
Jo
ur
50. Bachner-Melman R, Zontag-Oren F, Zohar AH, Sher H. Lives on the Line: The Online Lives
of Girls and Women With and Without a Lifetime Eating Disorder Diagnosis. Front Psychol.
2018; 9: 2128. doi: 10.3389/fpsyg.2018.02128
51. Claes L, Bijttebier P, Van Den Eynde F, Mitchell JE, Faber R, de Zwaan M, Mueller A.
Emotional reactivity and self-regulation in relation to compulsive buying. Pers Individ Dif.
2010;49(5):526-530. doi:https://doi.org/10.1016/j.paid.2010.05.020
52. Ruiz-Olivares R, Lucena V, Pino MJ, Herruzo J. [Analysis of behavior related to use of the
Internet, mobile telephones, compulsive shopping and gambling among university students].
Adicciones. 2010;22(4):301-9.
53. Błachnio A, Przepiórka A, Gorbaniuk O, Benvenuti M, Ciobanu AM, Senol-Durak E, et al.
Cultural Correlates of Internet Addiction. Cyberpsychology Behav Soc Netw. 2019;22(4):258-63.
54. Block JJ. Issues for DSM-V: internet addiction. Am J Psychiatry. 2008;165(3):306-7.
Journal Pre-proof
55. Fernández-Villa T, Alguacil Ojeda J, Almaraz Gómez A, Cancela Carral JM, DelgadoRodríguez M, García-Martín M, et al. Problematic Internet Use in University Students:
associated factors and differences of gender. Adicciones. 2015;27(4):265-275.
56. Martínez-González L, Fernández Villa T, Molina de la Torre AJ, Ayán Pérez C, Bueno
Cavanillas A, Capelo Álvarez R, et al. Prevalencia de trastornos de la conducta alimentaria en
universitarios españoles y factores asociados: proyecto uniHcos. Nutr Hosp. 2014;30(4):927934. doi:10.3305/nh.2014.30.4.7689
57. Hinojo-Lucena FJ, Aznar-Díaz I, Cáceres-Reche MP, Trujillo-Torres JM, Romero-Rodríguez
JM. Problematic Internet Use as a Predictor of Eating Disorders in Students: A Systematic
of
Review and Meta-Analysis Study. Nutrients. 2019;11(9):E2151. doi: 10.3390/nu11092151.
ro
58. Badenes-Ribera L, Fabris MA, Gastaldi FGM, Prino LE, Longobardi C. Parent and peer
attachment as predictors of facebook addiction symptoms in different developmental stages
-p
(early adolescents and adolescents). Addict Behav. 2019;95:226-32.
re
59. David S. “Technology, Body Image, and Disordered Eating” (pp 65-82). In: Smahel, D;
Machackova, H. Smahelova, M. Cevelicek, M. Almenara, C.A., Holubcikova, J. IN: Digital
lP
Technology, Eating Behaviors, and Eating Disorders. 2018. Springer International Publishing.
https://doi.org/10.1007/978-3-319-93221-7
na
60. Custers K. The urgent matter of online pro-eating disorder content and children: clinical
Jo
ur
practice. Eur J Pediatr. 2015;174(4):429-33.
Journal Pre-proof
Table 1. Clinical and socio-demographic characteristics in Eating Disorder Subtypes.
Eating disorder not
otherwise specified
Mean (SD)
(n=19)
27.14 (7.17)
Binge eating
disorder
Mean (SD)
(n=11)
34.29 (5.61)
8.32 (5.41)
14.9 (8.01)
36.8%
63.2%
62.66 (22.65)
1.63 (0.06)
23.04 (7.69)
9.1%
90.9%
90.06 (11.62)
1.62 (0.03)
34.21 (4.18)
20.6%
79.4%
5.3%
94.7%
63.6%
36.4%
<0.001
2.9%
65.7%
31.4%
5.3%
57.9%
36.8%
9.1%
36.4%
54.5%
0.546
60.0%
40.5%
52.6%
47.4%
18.2%
81.8%
0.053
28.6%
71.4%
33.3%
66.7%
45.5%
54.5%
0.580
TOTAL sample
Anorexia nervosa
Bulimia nervosa
Mean (SD)
Mean (SD) (n=59)
Mean (SD) (n=35)
Age (years)
27.34 (10.07)
25.57 (11.55)
Years since diagnosis
10.41 (10.41)
9.94 (7.94)
(years)
Ever hospitalized
Yes
51.6%
79.7%
No
48.4%
20.3%
Weight (kg)
58.4 (22.41)
45.12 (17.08)
Height (m)
1.62 (0.06)
1.61 (0.07)
BMI (kg/m2)
22.18 (8.13)
17.38 (6.46)
Marital status
Married
17.9%
11.9%
Single
82.1%
88.1%
Education level
Low (primary school)
4.0%
3.4%
High school
63.7%
69.5%
University
32.3%
27.1%
Smoker status
Yes
45.2%
39.0%
No
54.8%
61.0%
Depression
Yes
29.3%
25.4%
No
70.7%
74.6%
ANOVA and chi square test analysis. Level of significance p< .001.
l
a
o
J
n
r
u
28.45 (8.94)
f
o
10.93 (8.05)
ro
25.7%
74.3%
69.42 (16.18)
1.63 (0.07)
26.37 (5.41)
r
P
p
e
P-value*
0.07
0.14
<0.001
<0.001
0.275
<0.001
Journal Pre-proof
Table 2. Facebook and Internet Addiction in Eating Disorders Subtypes
Facebook addiction as
measured by the Bergen
Facebook Addiction
Scale (BFAS)
No Facebook addiction
Possibility of addiction
Facebook addiction
Internet addiction (IA)
Non-IA
At risk for IA
BFAS score
BFAS score adjusted by
age
BFAS Salience
BFAS Tolerance
BFAS Mood
modification
BFAS Relapse
BFAS Withdrawal
BFAS Conflict
IAT score
TOTAL sample
Anorexia nervosa
Bulimia nervosa
Mean (SD)
Mean (SD) (n=59)
Mean (SD) (n=35)
41.1%
21.0%
37.9%
37.3%
30.5%
32.2%
78.2%
21.8%
42.68 (21.33)
86.4%
13.6%
40.77 (19.29)
38.97 (C.I. 95% 34.1243.83)
2.03 (0.86)
2.36 (1.11)
2.13 (1.01)
2.43 (1.19)
o
J
2.36 (1.19)
2.19 (1.14)
2.36 (1.22)
25.82 (25.51)
IAT score adjusted by age
IAT Salience
IAT Excessive use
IAT Neglect of work
IAT Anticipation
IAT Lack of control
IAT Neglect of social
1.3 (1.31)
1.28 (1.23)
1.33 (1.32)
1.36 (1.24)
1.29 (1.29)
1.51 (1.27)
f
o
o
r
p
P-value*
63.6%
0%
36.4%
74.3%
25.7%
43.01 (20.96)
44.13 (C.I. 95%
37.87-50.39)
2.05 (0.99)
2.44 (1.17)
63.2%
36.8%
50.74 (24.45)
50.53 (C.I. 95% 42.0459.02)
2.66 (1.31)
2.81 (1.35)
72.7%
27.3%
37.9 (26.38)
48.00 (C.I. 95%
36.07- 59.94)
2.01 (1.12)
2.14 (1.44)
2.81 (1.12)
2.84 (1.12)
3.28 (1.35)
2.6 (1.63)
0.409
2.26 (1.09)
2.04 (0.97)
2.21 (1.11)
23.13 (23.62)
20.88 (C.I. 95% 15.2426.53)
1.13 (1.17)
1.19 (1.1)
1.14 (1.16)
1.2 (1.09)
1.15 (1.05)
1.37 (1.16)
2.37 (1.14)
2.21 (1.21)
2.29 (1.23)
26.59 (24.65)
28.05 (C.I. 95%
20.76-35.33)
1.41 (1.34)
1.22 (1.32)
1.37 (1.41)
1.39 (1.23)
1.24 (1.38)
1.45 (1.28)
2.71 (1.38)
2.67 (1.36)
2.93 (1.3)
37.37 (26.58)
36.90 (C.I. 95% 26.7647.05)a
1.74 (1.25)
1.87 (1.21)
1.97 (1.39)
1.9 (1.35)
1.96 (1.39)
2.15 (1.42)
2.28 (1.59)
2.1 (1.22)
2.37 (1.54)
18.88 (33.16)
31.47 (C.I. 95%
17.58-45.35)
1.13 (1.91)
1.03 (1.5)
1.12 (1.55)
1.19 (1.69)
1 (1.7)
1.32 (1.36)
0.569
0.22
0.159
0.158
l
a
48.6%
11.4%
40.0%
Binge eating
disorder
Mean (SD)
(n=11)
26.3%
21.1%
52.6%
n
r
u
2.87 (1.21)
Eating disorder not
otherwise specified
Mean (SD)
(n=19)
e
r
P
0.086
0.146
0.293
0.094
0.104
0.425
0.04
0.323
0.172
0.11
0.205
0.093
0.114
Journal Pre-proof
life
* Between subtypes of eating disorders. Quantitative variables assessed by ANOVA and qualitative variables assessed by a chi square test. a P=0.043
vs anorexia nervosa [p-values after further adjustment by age (years) (ANCOVA test)].
f
o
l
a
o
J
n
r
u
r
P
e
o
r
p
Journal Pre-proof
Table 3. Socio-demographic and clinical characteristics and BFAS and IAT scores
BFAS score
Optimal model
R
0.504
Selected independent variables
Age (years)
BMI (kg/m2)
Years since diagnosis
Marital status
Depression
Education level
Smoker status
Ever hospitalized
Eating disorder subtype
IAT score
Optimal model
Age (years)
Weight (kg)
Years since diagnosis
Marital status
Depression
Education level
Smoker status
Ever hospitalized
Eating disorder subtype
o
J
n
r
u
l
a
R
0.471
R2
0.254
R2
0.222
F
19.888
t
-5.734
3.444
-1.2
1.337
-0.755
-0.357
1.265
0.324
0.543
P-value
<0.001
P-value
<0.001
0.001
0.233
0.184
0.452
0,722
0.208
0.747
0.588
Adjusted R2
0.209
Standardized B
-0.412
0.297
-0.104
0.126
-0.029
-0.01
0.109
0.043
0.121
F
16.688
t
-4.998
3.604
-0.767
1.257
-0.354
-0.121
1.271
0.47
1.205
P-value
<0.001
P-value
<0.001
<0.001
0.445
0.211
0.724
0.904
0.206
0.639
0.231
f
o
o
r
p
e
r
P
Adjusted R2
0.241
Standardized B
-0.463
0.278
-0.159
0.131
-0.062
-0.03
0.106
0.029
0.054
Multiple linear regression analysis for the association between BFAS and IAT scores and age (years), BMI (Kg/m2), years since diagnosis, marital status,
depression, education level, smoker status, ever hospitalized and eating disorder subtype.
Journal Pre-proof
Table S1. IAT items and Subtype of Eating Disorder
Subtype of
eating disorder
Anorex Bulimi
ia
a
IAT items
nervos nervo
a
sa
Mean
Mean
(SD)
(SD)
Do you choose to spend more time online
0.9
1.4
over going out with others?
(1.3)
(1.7)
Do you snap, yell, or act annoyed if
0.8
1.4
someone bothers you while you are online?
(1.2)
(1.6)
Do you fear that life without the Internet
1.1
1.7
would be boring, empty and joyless?
(1.3)
(1.6)
Do you feel preoccupied with the Internet
1.3
0.9 (11)
when offline or fantasize about being online?
(1.6)
Do you block disturbing thoughts about your
1.1
1.2
life with soothing thoughts of the Internet?
(1.2)
(1.5)
Do you neglect household chores to spend
1.1
1 (1.2)
more time online?
(1.2)
0.9
1.4
Do you lose sleep due to late night log-ins?
(1.2)
(1.8)
Do you feel depressed, Moody, or nervous
1.2
1.3
when you are offline, which goes away once
(1.4)
(1.8)
you are back online?
Do you find that you stay online longer than
1.3
1.2 (1)
you intended?
(1.1)
Do you try to hide how long you’ve been
0.8
1.1
online?
(1.2)
(1.6)
Does your work suffer (e.g., postponing
0.9
1.3
things. not meeting deadlines) because of
(1.2)
(1.6)
the amount of time you spend online?
Does your job performance or productivity
1.1
1.3
suffer because of the Internet?
(1.2)
(1.6)
Do you become defensive or secretive when
1.1
1.3
anyone asks you what you do online?
(1.3)
(1.6)
Do you find yourself anticipating when you
1.2
1 (1.1)
will go online again?
(1.5)
Do you check your e-mail before something
1.2
1.5
else that you need to do?
(1.2)
(1.5)
Do you try to cut down the amount of time
0.9
1.2
you spend online and fail?
(1.1)
(1.5)
Do others in your life complain to you about
1.2
1.3
the amount of time you spend online?
(1.2)
(1.7)
Do you find yourself saying “Just a few more
0.9
1.2
minutes” when online?
(1.1)
(1.5)
Do you form new relationships with fellow
1.4
1.6
online users?
(1.2)
(1.4)
Do you prefer the excitement of the Internet
1.2
1.2
to intimacy with your partner?
(1.3)
(1.5)
Table 1. Supplemental
Eating
disorder not
otherwise
specified
Mean (SD)
Mean
(SD)
1.8 (1.8)
1.5 (2.1)
2.1 (1.7)
1.2 (1.8)
1.9 (1.7)
1.5 (2.1)
of
ro
-p
re
lP
na
Jo
ur
Binge
Peating
val
disorder ue
1.8 (1.8)
1.1 (1.9)
1.9 (1.7)
1.3 (2)
2.3 (1.6)
1.3 (1.5)
1.8 (1.7)
1.1 (1.7)
1.9 (1.8)
1.5 (2)
2.1 (1.4)
1.2 (1.2)
1.8 (1.7)
1.5 (2.1)
2.1 (1.8)
1.4 (1.8)
1.9 (1.7)
1.2 (1.9)
1.9 (1.6)
1 (1.7)
1.9 (1.8)
1.3 (2.1)
2.2 (1.8)
1.2 (1.7)
1.8 (1.6)
1.3 (2.2)
2.1 (1.8)
1.3 (1.8)
1.9 (1.8)
1.2 (2)
2.5 (1.8)
1.3 (1.5)
1.9 (1.6)
1.4 (1.4)
0.2
58
0.0
17
0.2
72
0.1
84
0.2
42
0.0
09
0.1
62
0.4
08
0.1
08
0.1
01
0.1
15
0.1
82
0.1
13
0.2
73
0.1
21
0.0
85
0.2
13
0.1
31
0.1
04
0.2
3
Journal Pre-proof
Table S2. BFAS items and Subtype of Eating Disorder
0.2
09
0.1
63
0.4
77
0.2
9
0.5
8
2.4 (1.8)
0.3
75
2.7
(1.2)
2.6
(1.3)
3.3 (1.4)
2.6 (1.7)
0.2
61
2.8
(1.2)
2.9
(1.3)
3.2 (1.5)
2.6 (1.6)
0.6
85
2.8
(1.3)
2.9
(1.3)
3.2 (1.4)
2.5 (1.6)
0.5
12
2.5
(1.3)
2.5
(1.3)
3.1 (1.6)
2.4 (1.6)
0.5
13
2.1
(1.2)
2.5 (1.5)
2.2 (1.7)
2.6 (1.6)
2.2 (1.6)
2.6 (1.6)
2.4 (1.7)
1.8
(1.1)
2.2
(1.4)
2.1
(1.4)
2.2
(1.5)
2.1
(1.4)
2.7 (1.7)
2.1 (1.4)
1.9
(1.2)
2.1
(1.4)
2.8 (1.6)
2 (1.3)
0.1
76
1.9
(1.2)
2 (1.4)
2.8 (1.6)
2.3 (1.7)
0.1
24
2.1
(1.3)
2.3
(1.4)
2.8 (1.5)
2.5 (1.7)
0.2
72
2.3
(1.3)
2.4
(1.5)
3.1 (1.5)
2.5 (1.8)
0.2
72
re
-p
2.9 (1.6)
na
2.2
(1.3)
Jo
ur
2.3
(1.3)
Pval
ue
lP
Spent a lot of time thinking about
Facebook or planned use of Facebook?
Thought about how you could free more
time to spend on Facebook?
Thought a lot about what has happened
on Facebook recently?
Spent more time on Facebook than
initially intended?
Felt an urge to use Facebook more and
more
Felt that you had to use Facebook more
and more in order to get the same
pleasure from it?
Used Facebook in order to forget about
personal problems?
Used Facebook to reduce feelings of
guilt, anxiety, helplessness, and
depression?
Used Facebook in order to reduce
restlessness?
Experienced that others have told you to
reduce your use of Facebook but not
listened to them?
Tried to cut down on the use of
Facebook without success?
Decided to use Facebook less
frequently, but not managed to do so?
Become restless or troubled if you have
been prohibited from using Facebook?
Become irritable if you have been
prohibited from using Facebook?
Felt bad if you, for different reasons,
could not log on to Facebook for some
time?
Used Facebook so much that it has a
negative impact on your job/studies?
Given less priority to hobbies, leisure
activities, and exercise because of
Facebook?
Ignored your partner, family members, or
friends because of Facebook?
of
BFAS items
Subtype of eating disorder
Anorex Bulimi
Eating disorder
Binge
ia
a
not otherwise
eating
nervos nervos
specified
disorder
a
a
Mean
Mean
Mean
Mean (SD)
(SD)
(SD)
(SD)
1.8
1.9
2.4 (1.2)
1.8 (1.1)
(0.9)
(1.1)
1.9
2 (1.2)
2.8 (1.6)
2.1 (1.4)
(1.1)
2.1
2.1
2.7 (1.6)
2.1 (1.4)
(1.1)
(1.2)
2.2
2.4
2.8 (1.5)
2 (1.3)
(1.1)
(1.3)
2.3
2.4
2.8 (1.5)
2.3 (1.7)
(1.2)
(1.4)
ro
Table 2. Supplemental
2 (1.2)
2 (1.2)
0.8
1
0.5
44
0.6
58
0.2
79
Journal Pre-proof
Highlights
Internet and social networking sites are an integral part of most eating disorder
patients’ lives, especially for younger individuals.

Women with eating disorders may have other addictive behaviors such as
Internet and online social networking addiction.

These behaviors share similarities with other behavioral addictions, that must
be detected early and identify various addiction components.
Jo
ur
na
lP
re
-p
ro
of

Скачать