Facebook Addiction Among Turkish College Students: The Role of Psychological Health,Demographic,and Usage Characteristics

Abstract

This study explored Facebook addiction among Turkish college students and its behavioral, demographic, and psychological health predictors. The Facebook Addiction Scale (FAS) was developed and its construct validity was assessed through factor analyses. A total of 447 students reported their personal information and Facebook usage and completed the FAS and General Health Questionnaire (GHQ-28). The results revealed that weekly time commitment, social motives, severe depression, and anxiety and insomnia positively predicted Facebook addiction. Neither demographic variables nor the interactions of gender by usage characteristics were found to be significant predictors.

Introduction

People's interest in social networking sites (SNS) has considerably increased in recent years. Although a number of SNS exist today, Facebook is one of the most popular and widely used ones. More than 500 million people spend about 700 billion minutes on Facebook per month and half of them log into their account in a given day, and average user has about 130 contacts.¹ Despite being a digitalizing country, Turkey has the fourth largest audience with approximately 30 million users more than half of whom are male and aged between 14 and 24.² Such an intensive SNS global usage has recently evoked questions germane to negative consequences on youth's lives.^3,4 Despite a variety of gratifications, including socialization, information, recreation, and academic purposes,^5–8 researchers still know little about how youngsters develop disturbed patterns of usage. May youth loose sleep or neglect daily responsibilities due to excessive SNS usage? May their school performances be disrupted? May they get addicted to SNS? These are some growing concerns among parents and educators that should not be overlooked, but critically examined because they may suggest emerging mental health problems. Therefore, in this study, we investigated the characteristics of Facebook adoption, including the addictive use among college students in Turkey.

The concept of Facebook addiction

Research reviews on Internet addiction suggest that some people may develop disturbed patterns of use to specific online activities (e.g., online gaming, social networking).^9,10 Specific addictive usage may be related to behaviors that people (a) have already been dependent on (e.g., pathological gambling), (b) would only exhibit online (e.g., cybersex) because of the disinhibiting nature of the Internet, or (c) can carry out only on the Internet (e.g., online chat).¹¹ Various underlying possibilities bring about different approaches to explaining how addictive use occurs. It could be a new variant of a pre-existing pathology, a newly developed one due to the use of unique features of the Internet, or a reflection of other problems (e.g., mood disorders). In this study, given the fact that Facebook is the biggest and predominantly used SNS, we conceptualized Facebook addiction (FA) as a specific form of Internet addiction applicable to individuals excessively socially networking the Facebook Website, and thus experiencing detrimental effects on their lives. Hence, we considered that FA is related to online social networking behavior, which is the core function of Facebook.

Limited research exists for FA, in particular, and SNS addiction, in general, since this research stream is gradually evolving. College students have indicated the presence of problematic Facebook use with negative consequences on their school performances.¹² Students with a stronger need for belongingness and those who are strongly extroverted and weakly conscientious were found to be more prone to SNS addiction.^13,14 A case study reported a 24-year-old female who used Facebook excessively and, thus, was dismissed from her job and developed anxiety and insomnia symptoms.¹⁵ Another study on undergraduates in a romantic relationship showed that Facebook intrusion could result in jealousy and relationship dissatisfaction.¹⁶ Communication, passing time, and entertainment motives were identified as strong contributors to FA among female university students.¹⁷ An online survey indicated that the preference of online social interaction and Facebook use for mood regulation explained deficient self-regulation which, in turn, led to FA.¹⁸ Very recently, college students' FA scores were found to be positively related to neuroticism and extraversion, negatively related to conscientiousness, and higher scores were associated with later bedtimes and rising times.¹⁹ On the whole, recent literature reviews have suggested that such research is still in its infancy stage and needs more evidence on the addictive usage and its correlates.⁴ Therefore, we focused on behavioral, demographical, and psychological health indicators as possible predictors of FA.

Psychological health

Research studies show that depression and anxiety are common symptoms of mental disorders among college students.²⁰ College life is a challenging time through which students adapt to adulthood, seek future career, face academic load, and experience emotional stress. Thus, some situations can influence students' psychological health which, in turn, can impact their adaptations, functions, and performances. Research indicates that a negative mental state may impact on productivity, social relationships, substance abuse, and obsessive behaviors.²¹ Individuals with psychological disturbances are known to have higher tendencies toward online interaction to fulfill their social and emotional needs because of its availability, easiness, and high anonymity.^22,23 In fact, earlier studies suggest that individuals with feelings of mood disorders (e.g., loneliness) are susceptible to online addiction.^24–26

Usage characteristics

The uses and gratification theory argues that users' social and psychological needs motivate various exposure to media applications and result in different consequences.²⁷ It implies that when the gratification obtained is greater than expected, users become involved in high satisfaction and adoption. SNS provide an effective platform for self-expression and developing social capital. A study indicated socialization, academic or work-related aid, and daily information as main motives for Facebook usage.²⁸ Another study identified social interaction, communication, passing time, entertainment, and companionship were the motives for Facebook usage that influence FA. A recent review on SNS addiction addressed the need for further research on understanding different motivations and negative correlates of addictive behavior.⁴ Accordingly, we proposed that the inclusion of some Facebook usage characteristics (e.g., time commitment, motives for usage) could be useful in the explanation of FA.

Demographic characteristics

Investigations of sociodemographic differences in SNS usage and addiction are limited and inconclusive. Sheldon²⁹ found that youth's motives for Facebook usage were gendered with females using it mostly for the maintenance of existing relationships and entertainment, whereas males using it mostly for building new relationships. Regarding age, The Pew Research Center³⁰ found that people under 30 in 22 nations were more likely to participate in SNS. While males were more likely than females to use SNS in Turkey and Japan, it was the opposite in the USA. Similarly, gender was found to be a significant predictor favoring females among college students.³¹ Another study showed no gender effect on the use of MySpace or Facebook.⁷ Although sociodemographics have been studied in SNS usage, their potential effects on addictive usage have not been explored so far. Moreover, inconsistent findings germane to gender differences in SNS usage warrant further research to examine whether gender interacts with other variables (e.g., usage characteristics) in affecting addictive usage.

Method

Participants

The convenience sample included 447 students at a technical teacher education college in Turkey, who were accessible and volunteer during our visits to lecture halls for survey administration. Participants were majoring in mechanical (43 percent), computer (27 percent), construction (20 percent), and mechatronic (10 percent) education. Of the sample, 347 (78 percent) were male and 100 (22 percent) were female. The sample's gender ratio was very similar to that of a college population (4:1). Students' ages ranged from 18 to 30 with a mean of 21.64 (SD=1.94). Most (83 percent) perceived that their family income was in the middle socioeconomic class compared to 14 percent in the low and 3 percent in the high class.

Measures

Facebook usage

Students were initially asked several questions about their Facebook usage (e.g., experience, frequency, duration, and place of usage). Next, we employed motives for the Facebook Usage Scale (MFUS)²⁸ to assess why students use Facebook. The MFUS has 11 Likert-type items (1=never, 5=always) divided into three subscales: social (e.g., I use Facebook to make new friends), academic (e.g., I use Facebook to share assignments with my classmates), and daily informational motives (e.g., I use Facebook to follow daily news). The items in each subscale were averaged to construct a single variable. The Cronbach's alpha coefficients for the subscales varied between 0.69 and 0.89.

FA scale

There was no instrument available to measure FA at the beginning of our study and two validated scales were published during the preparation of our manuscript.^16,19 Therefore, adapting from previous research on Internet addiction,^22,32 we developed the Facebook Addiction Scale (FAS) to assess addictive usage. The FAS comprises eight items related to the symptoms of cognitive and behavioral salience, conflict with other activities, euphoria, loss of control, withdrawal, and relapse and reinstatement (Table 1). Students rate each item by using a Likert-type scale ranging from 1 (not true) to 5 (extremely true). Hence, the total score can vary between 8 and 40, with higher scores indicating a greater level of addiction.

Table 1.

Results of Descriptive and Factor Analyses of the Facebook Addiction Scale

Item	Mean	SD	Factor loading (EFA)	Path estimate (CFA)
I have difficulties in focusing on my academic work due to my Facebook use	2.22	1.28	0.64	0.76^*
The first thing on my mind when I get up is log into Facebook	1.45	0.99	0.68	0.56^*
I lose sleep over spending more time on Facebook	1.43	0.91	0.74	0.74^*
My Facebook use interferes with doing social activities	1.59	0.99	0.74	0.70^*
I log into Facebook to make myself feel better when I am down	2.20	1.34	0.62	0.47^*
My family or friends think that I spend too much time on Facebook	1.66	1.11	0.79	0.74^*
I feel anxious if I cannot access to Facebook	1.43	0.87	0.71	0.55^*
I have attempted to spend less time on Facebook but have not succeeded	1.65	1.09	0.69	0.73^*

Student ratings for all items ranged from 1 (min) to 5 (max).

p<0.01.

EFA, exploratory factor analysis; CFA, confirmatory factor analysis.

We randomly split the sample of Facebook users (n=405) and subjected the FAS to exploratory factor analysis (EFA) on half, and then confirmatory factor analyses (CFA) on the other half to cross-validate and refine the factor structure emerged from the former.³³ In the EFA, we employed principal components and varimax as the method of factor extraction and rotation, respectively. The Kaiser–Meyer–Oklin value was 0.90 and the Bartlett's Test of Sphericity was 535.82 (p<0.01), supporting the suitability of the data for factor analysis. The results of EFA revealed a single factor with an eigenvalue of 3.97, explaining 50 percent of the variance, which can be considered moderate and acceptable rate of variance social sciences. The scree plot also revealed a clear break after the first component. The factor loadings varied between 0.62 and 0.79, indicating that all items should be included in the scale (Table 1).

The CFA verified this single-factor solution. The Chi-square/df ratio was 2.63 (χ²=52.61, df=20, p<0.01) and lower than the recommended value of 3 for large samples. Regarding fit indices, GFI was 0.94, NFI was 0.95, CFI was 0.97, and SRMR was 0.04. The path estimates were all meaningful in size ranging from 0.47 to 0.76 (Table 1), indicating that all items significantly contribute to addictive usage. The single-factor model fit to the data well.^34,35 The Cronbach's alpha internal consistency coefficient was 0.84.

General health questionnaire

We employed the General Health Questionnaire (GHQ-28)^36,37 to measure psychological health. The GHQ-28 contains 28 self-report items divided into four subscales: somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression. Each subscale contains seven items asking participants to indicate how often they have recently experienced relevant symptoms on a four-point Likert scale ranging from “0=not at all” to “3=much more than usual.” The total score on each subscale can vary from 0 to 21 with higher scores indicating more severe morbidity. Cronbach's alpha reliability coefficients for the subscales ranged from 0.78 to 0.87.

Results

The description of Facebook usage

Of the students surveyed, 405 (90.6 percent) had used Facebook, while the remaining (9.4 percent) had never used it. Of the Facebook users, more than half (58.5 percent) had less than 3 years of Facebook experience. The most frequently used place for Facebook connection was home or dormitory (70.1 percent), followed by Internet cafes (13.3 percent), a friend's or relative's home (6.2 percent), and schools (5.2 percent). A few users (2.7 percent) connected to Facebook mostly using mobile devices. Almost half (49.6 percent) logged into their Facebook account on a daily basis, while 41 percent logged on a few times a week and 9 percent logged on a few times a month.

Time spent on Facebook varied from 10 minutes to 70 hours and 15 minutes per week with a mean of 7 hours (SD=10). The dominant motives for Facebook usage was daily information followed by social and academic purposes (Table 2). Weekly time commitment was positively, although weakly, associated with social and daily informational motives. Academic, social, and daily informational motives were positively and moderately associated with one another.

Table 2.

Descriptive Statistics and Pearson Correlations Among Study Variables (n=405)

Variable	1	2	3	4	5	6	7	8	9	Mean	SD
Facebook usage
1. Weekly time commitment	—	0.06	0.16^*	0.14^*	0.25^*	−0.01	−0.05	−0.08	0.07	6.99	10.00
2. Academic motives		—	0.36^*	0.59^*	0.18^*	0.01	−0.01	−0.08	0.03	2.16	0.98
3. Daily informational motives			—	0.46^*	0.19^*	−0.01	0.05	0.01	0.04	3.34	1.14
4. Social motives				—	0.22^*	−0.02	0.03	−0.04	0.06	2.98	0.64
5. Facebook addiction					—	0.25^*	0.23^*	0.23^*	0.28^*	13.66	5.92
Psychological health
6. Somatic symptoms						—	0.65^*	0.47^*	0.52^*	5.31	4.27
7. Anxiety and insomnia							—	0.44^*	0.53^*	6.62	5.31
8. Social dysfunction								—	0.53^*	6.91	3.66
9. Severe depression									—	3.84	4.55

p<0.01.

The relationships between Facebook usage and demographics

We conducted a multivariate analysis of variance (MANOVA) with Facebook usage characteristics as dependent variables, while gender was treated as the independent variable. Weekly time commitment was log transformed because it was positively skewed. The omnibus MANOVA indicated significant overall differences [Wilks' λ=0.95, F(4, 400)=5.29, p<0.01, η²=0.05]. Follow-up univariate analyses showed that there were significant gender differences in weekly time commitment [F(1, 403)=4.61, p<0.05, η²=0.01] and academic motives [F(1, 403)=5.59, p<0.05, η²=0.01]. Males (M=0.60, SD=0.50) reported slightly higher hours spent on Facebook than females (M=0.47, SD=0.38). On the other hand, females (M=2.38, SD=0.99) reported more academic use than males (M=2.10, SD=0.97). There were no significant gender differences in social and daily informational motives.

We conducted a similar MANOVA with socioeconomic status being treated as the independent variable. The overall results indicated that Facebook usage characteristics were not dependent on the income level [Wilks' λ=0.98, F(8, 798)=1.26, p>0.05, η²=0.01]. Furthermore, there were no significant correlations between age and Facebook usage characteristics.

FA and its predictors

The mean FAS score was 13.66 (SD=5.92), while the actual scores ranged from 8 to 37, suggesting that FA is not very common among the participants. Mood alternation and negative outcomes on academic works were the most frequent symptoms of addictive usage although they were lowly reported (Table 1). Furthermore, FA positively correlated with all usage characteristics and psychological health symptoms (Table 2).

We employed a stepwise regression analysis to determine influential factors related to FA. The dependent variable was the FAS score, while the independent variables included psychological health symptoms, Facebook usage characteristics, demographics (gender, age, and income), and the interaction terms of gender by Facebook usage characteristics (e.g., gender×weekly time commitment). The FAS score and severe depression were transformed because they were positively skewed. Pearson's correlations among independent variables varied between −0.01 and 0.65 and the variance inflation factor value for the regression analysis was less than 2, indicating no violation of multicollinearity assumption. One case was identified as outlier and excluded from the analysis because it had the absolute residual value above 3.

Table 3 shows regression coefficients for the best model predicting FA. The model suggested that 22 percent of the variance in FA could be explained by four significant predictors, including weekly time commitment, social motives, anxiety and insomnia, and severe depression [F(4, 399)=27.68, p<0.01]. All these predictors were positively associated with addictive usage. Academic and daily informational motives as well as demographics and interaction terms were not significant.

Table 3.

Results of Stepwise Multiple Regression Analysis of Facebook Addiction (n=405)

Dependent variable	Independent variable	B	SE	β	t-value	R²
Facebook addiction^a	Weekly time commitment^a	0.10	0.02	0.29	6.28^*	0.22^*
	Social motives	0.04	0.01	0.16	3.62^*
	Anxiety and insomnia	0.01	0.01	0.16	2.92^*
	Severe depression^b	0.02	0.01	0.17	3.14^*

Scores log transformed.

Scores were square-root transformed.

p<0.01.

B, unstandardized coefficients; SE, standard error; β, standardized coefficients.

Discussion and Conclusion

Corroborating previous similar studies,³⁸ our findings suggest that majority of the students were Facebook members and its usage is current and very popular in college life. The MANOVA analysis indicated statistically significant gender effects on both weekly time commitment and academic use of Facebook. However, they were not substantial enough to make theoretical implications because the effect sizes were quite small. This implies that the gender gap in SNS adoption in Turkey has been rapidly narrowing even if not completely closing. The mean FAS score suggests that the prevalence of FA is low in our sample of students.

As expected, we found both severe depression and anxiety and insomnia as positive predictors of FA. This supports the cognitive behavioral model, which assumes the necessity of a pre-existing psychopathology as a source of online addiction.³⁹ College life has some challenging situations (e.g., fulfilling academic responsibilities, financial needs) that may become overwhelming especially for students with poor coping skills. For example, our subjects were preservice technical teachers whose appointments to schools were very limited. Therefore, some might have become depressed or anxious and, thus, developed some negative feelings about themselves or their school lives which, in turn, prompted them to excessively use Facebook as a social support. The association between disturbed online behavior and depressive mood has been confirmed in other studies of college students as well.^40,41 Nevertheless, the prediction does not necessarily imply causation. It might be that FA causes depression or both are caused by a confounding variable. For example, the effect of Internet use on psychological well-being has been showed to vary according to personality traits.⁴² We need further research to determine the direction of causality.

FA could be related to the social aspect of Facebook because our regression model revealed social motives as a positive predictor. Students who frequently used Facebook for social interaction reported higher levels of addiction. This is consistent with previous studies indicating that Internet addicts are more likely to involve with socially interactive activities.²² Hence, it supports the general proposition that gratifications related to social compensation are associated with addictive tendencies toward online activities. Facebook may provide at-risk students with more social benefits and less threatening platform than other medium. Coupled with the inadequacy of interpersonal skills and support from their friends and teachers, they may become overly involved in Facebook and, thus, developed addictive usage.

Moreover, we found that none of the demographics significantly predicted FA. This contradicts that males are more prone to problematic Internet use than females.^26,43 We proposed that the relationship between gender and FA could be attributable to usage characteristics and, thus, tested this in the regression analysis. Nevertheless, none of the interactions was a significant predictor. These findings suggest that FA can be developed regardless of gender, age, and socioeconomic status. Most colleges provide students with easy, free, and unlimited access to the Internet in dormitories and computer laboratories. The deployment of Wi-Fi hotspots in campus spaces has increased the possibility of perpetual contact with online spaces through the use of mobile devices (e.g., cell phone). College students have also flexible study hours and independent living and thus can allocate more time for the Internet.

Our study has several limitations that should be acknowledged. First of all, our regression model explained low level of variance in FA (22 percent). This implies that there are other factors important for shaping FA, which future research should focus on. Secondly, the research design was based on prediction and thus no definitive conclusions can be made about the causation among the variables. Thirdly, we employed convenience sampling to recruit the participants from a specific faculty and university in Turkey and our sample was skewed with regard to male gender. Therefore, the achieved results cannot be generalized to all university students. Finally, variables were operationalized based on self-report data.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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