The Relations Among Social Media Addiction,Self-Esteem,and Life Satisfaction in University Students

Abstract

The use of social media has grown exponentially to the extent of engaging close to one third of the world’s population as of January 2016. Actually, social media statistics have been reporting an average annual increase of 10% in total number of users. These extremely impressive statistics have been triggering researchers’ interest in investigating this phenomenon and its impact on every aspect of users’ lives. Our study is an attempt to contribute to the knowledge that is building up in relation to this phenomenon by examining the relationships between the addictive use of social media, self-esteem, and satisfaction with life. To achieve this purpose, a generic questionnaire, the Social Media Addiction Questionnaire (SMAQ), was used stemming from the Facebook Intrusion Questionnaire. Respondents completed an online survey questionnaire which collected demographic information and responses to SMAQ, Rosenberg’s Self-Esteem Scale, and the Satisfaction with Life Scale. In addition to assessing SMAQ’s psychometric properties, data analyses included Pearson correlations between the variables, regression analysis, and structural equation modeling. Results showed that a one-factor model of SMAQ had good psychometric properties and had high internal consistency. As for relations, addictive use of social media had a negative association with self-esteem, and the latter had a positive association with satisfaction with life. Furthermore, path analysis showed that self-esteem mediated the effect of social media addiction on satisfaction with life.

Keywords

social media addiction internet addiction self-esteem life satisfaction university students Social Media Addiction Questionnaire (SMAQ)

The use of social media has grown exponentially to the extent of engaging close to one third of the world’s population as of January 2016 (WeAreSocial, 2016). This growth is facilitated by the numerous active social media sites, especially the most popular ones such as Facebook, Instagram, Twitter, and LinkedIn. As of March 2016, and on average, Facebook had more than 1.09 billion daily active users (Facebook, 2016); Instagram had more than 400 million monthly active users and 80 million daily shared photos with 3.5 billion likes daily (Instagram, 2016); Twitter had 310 million monthly active users (Twitter, 2016); and LinkedIn had more than 433 million active users (LinkedIn, 2016). As for gender differences, more women (68%) have been using social media compared to men (62%), and women on the average spend 46 min per day on social media compared to 31 min by men (Perrin, 2015). Researchers from different disciplines are barely keeping up with these overwhelming growths, trying to understand the different aspects of social media sites, including descriptive analysis of users, motivations, identity presentation, social interactions, implications, and privacy. Social media sites have their advantages and disadvantages; however, our major concern is their negative impact on individuals especially addiction whereby users, irrespective of their context, manifest symptoms of behavioral addiction (Andreassen, 2015; Ryan, Chester, Reece, & Xenos, 2014). As we perceive it, social media addiction is the compulsive use of social media sites that manifests itself in behavioral addiction symptoms. The symptoms include salience, tolerance, conflict, withdrawal, relapse, and mood modification (Griffiths, 2005).

While addictive use of the Internet has been extensively examined over the years (Ha et al., 2007; Hawi, 2012; Tsitsika et al., 2014; Young, 1998), researchers just recently started investigating the impact of social media and its subclasses (such as Facebook and Twitter; van den Eijnden, Lemmens, & Valkenburg, 2016). In 2014, a review of social media addiction research concluded that its legitimacy was still open for debate despite some clear symptoms of addiction, such as negative consequences, preoccupation, and withdrawal (Griffiths, Kuss, & Demetrovics, 2014). Since then, more research studies on social media have been published including studies pertaining to the authors of the aforementioned review (Andreassen, Griffiths, et al., 2016; Andreassen, Pallesen, & Griffiths, 2016). Few studies developed and validated measurement instruments and confirmed that social media addiction is real, as users exhibit most of the symptoms of behavioral addiction including tolerance, withdrawal, conflict, salience, relapse, and mood modification (Andreassen, 2015; Griffiths et al., 2014; Ryan et al., 2014). Our study aims at contributing to the existing body of knowledge on social media addiction especially that social media addicts exhibit behavioral addiction symptoms and which is negatively affecting their mental health including self-esteem and well-being (Pantic, 2014).

Instruments that measure addiction to a social media site proprietary to a company do not necessarily measure the construct social media. In addition, more and more users are signing up with more than one social media site to engage in varying activities, groups, and networks that are available on each one of the sites. For instance, in the United States, 52% of social media users reported using multiple platforms compared to 42% the year before with a projected annual increase of 10% (WeAreSocial, 2016). Furthermore, social media sites have commonalities such as social interaction, creating and maintaining relationships, and self-presentation and identity (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). Therefore, an instrument should either measure addiction to social media or to a specific activity on social media. In this study, we adopted the former approach by adapting the Facebook Intrusion Questionnaire (FIQ; Elphinston & Noller, 2011) to be a generic addiction measure of social media named Social Media Addiction Questionnaire (SMAQ). The FIQ was developed to measure Facebook addiction based on behavioral addiction symptoms in particular withdrawal, relapse and reinstatement, and euphoria.

Self-esteem was defined as “an individual’s positive or negative evaluation of himself or herself” (Smith, Mackie, & Claypool, 2014, p. 107). Most studies that have examined the relation between self-esteem and the use of social media sites have showed that people with low self-esteem tend to use more social media sites to enhance their self-image and self-esteem (Błachnio, Przepiorka, & Rudnicka, 2016; Denti et al., 2012; Gonzales & Hancock, 2011; Steinfield, Ellison, & Lampe, 2008). For instance, a longitudinal study on Facebook users showed that self-esteem moderated the relation between Facebook use and social capital, where users with low self-esteem benefit from additional Facebook use to bridge their social capital (Steinfield et al., 2008). Based on the “social compensation” hypothesis or “the poor gets richer” (Kraut et al., 2001), people with low self-esteem, low life satisfaction, and who have few offline contacts compensate by using Facebook to gain more friends and more popularity (Barker, 2009; Mehdizadeh, 2010). Also, some studies showed a positive relationship between Instagram use and narcissism, where users high in narcissism tend to post more selfies and spend more time on Instagram (Andreassen, Pallesen, et al., 2016; Moon, Lee, Lee, Choi, & Sung, 2016; Sheldon & Bryant, 2016). Moreover, gender differences played a role with Instagram use, as it was the best predictor of Instagram use (Sheldon & Bryant, 2016). A large-scale study of 23,592 social media users (Facebook, Instagram, and Twitter) showed that addicted use of social media is linked to being female, high in narcissism and low in self-esteem (Andreassen, Pallesen, et al., 2016). Most of these studies have been conducted mainly in Europe and the United States. The technology use related studies from the Middle East including Lebanon are rare (Hawi & Rupert, 2015; Samaha & Hawi, 2017). A recent study on 24 emerging and developing countries including Lebanon, released by the Pew Research Center, reported that 72% of Internet users in Lebanon use social networking sites (Pew Research Center, 2014) compared to 73% in the United States (Perrin, 2015). This study also reported that 100% of Lebanese users use social media sites to stay in touch with family and friends. By using social media sites, they share photos, videos, offline activities, and lifestyle. This phenomenon triggered our interest in investigating the use of social media sites in relation to how users value themselves (i.e., self-esteem) and how they evaluate their lives (i.e., satisfaction with life). Therefore, the purpose of our study was to check whether the relation between addictive use of social media and self-esteem exists in our sample, and if it does, how it compares in strength and direction to those relations identified elsewhere and especially when it comes to gender differences.

A multitude of studies showed that technological addictions, including addictions on the Internet and social networking sites, had positive associations with stress, anxiety, and depression and negative association with academic performance, all of which negatively affects satisfaction with life (Hawi & Samaha, 2016; Kabasakal, 2015; Kuss, Griffiths, Karila, & Billieux, 2014; Lepp, Barkley, & Karpinski, 2014; Samaha & Hawi, 2016). In a recent study of a sample of 381 Polish Facebook users, Facebook addicts had lower self-esteem and satisfaction with life than their nonaddict counterparts (Błachnio et al., 2016). This finding was supported by a study of 311 Turkish undergraduate students in which satisfaction with life was negatively associated with problematic Facebook use (Satici & Uysal, 2015). In an experience sampling of 82 Americans (M _age = 19.5), the more participants used Facebook, the more their well-being and satisfaction with life declined (Kross et al., 2013). In line with this finding, a German study of 583 Facebook users showed that people who passively follow online users experience social comparison and feelings of envy, which decreases their satisfaction with life (Krasnova, Wenninger, Widjaja, & Buxmann, 2013). Another study found that people who have used Facebook for a long time and people who check Facebook more frequently believe that other people are happier than they are, that others have a better life, and that life is unfair (Chou & Edge, 2012). In a Swedish study of 1,011 participants, the authors showed that people use Facebook to convey the best of their lives, interesting events, and positive happenings, which makes others falsely believe they live a lesser life by social comparison which in turn negatively affects their self-esteem and well-being (Denti et al., 2012). In fact, positive or negative feedback from online friends can enhance or lower, respectively, self-esteem and well-being (Valkenburg, Peter, & Schouten, 2006). In our study, we examine addictive use of social media in relation to self-esteem and satisfaction with life by (1) adapting the FIQ to social media and verifying the psychometric soundness of the resulting instrument and (2) validating the following research hypotheses:

Hypothesis 1: There is a zero-order correlation between social media addiction and satisfaction with life.

Hypothesis 2: Self-esteem mediates the relation between social media addiction and satisfaction with life.

Hypothesis 3: There are no gender differences between social media addiction and self-esteem.

Hypothesis 4: There are no gender differences between social media addiction and satisfaction with life.

Method

Sampling Procedure

This study was carried out at Notre Dame University–Louaize, Lebanon, and was conducted in English because it is the language of instruction at this university, which adopts the American system of education. The study was the first of its type in the Middle East. It was cross sectional based on voluntary participation of university students. To give an equal chance of participation to each student, systematic random sampling was implemented by randomly picking the first student from the student population, ordered by student identification number, and then selecting each fifth student from the list. With systematic random sampling, it is highly likely that the sample is representative of the population. Approval for the study was obtained from the university’s institutional research board. Before completing the survey, a form explained the purpose of the study and assured volunteers that data collection, storage, and reporting techniques would protect confidentiality and anonymity. A total of 396 respondents filled out the online survey through the university’s Student Information System. Thirty-two respondents were excluded from analysis because they answered trap questions incorrectly, which reduced the sample size to 364 (M _age = 21.1, standard deviation [SD] = 2.3). Of the 364 valid cases, 52.2% were males.

Data Collection Instruments

The survey was composed of four separate sections, including one for demographic information and three for separate research instruments. The demographic information section included gender and age. The remaining sections were composed of the SMAQ, the Rosenberg Self-Esteem Scale (RSES), and the Satisfaction with Life Scale (SwLS). The amount of time required to complete the survey was approximately 15–20 min.

The SMAQ is derived from the FIQ by replacing Facebook with social media (see Table 1). This ensured the shift in focus from a particular social media site offering a collection of activities that form a subset of activities of social media to the technology that encompasses all forms of social media. FIQ is an 8-item instrument that assesses Facebook addiction and was developed based on Brown’s 10 behavioral addiction components (Brown, 1997) and the mobile phone involvement questionnaire (Walsh, White, & McD Young, 2010). It is reliable, short, has good psychometric properties, and covers the symptoms of behavioral addiction. The SMAQ’s instruction of use was “The questions below are about your relationship to and use of online social media (Facebook, Twitter, Instagram, LinkedIn, and the like).” Responses were reported on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree), and summed to indicate higher levels of addiction. A sample item is “the thought of not being able to access social media makes me feel distressed.”

Table 1.

Loadings of the Exploratory Factor Analysis.

Item	PCA
Item	Loadings	Status
I often think about social media when I am not using it	.666	Very good
I often use social media for no particular reason	.608	Good
Arguments have arisen with others because of my social media use	.601	Good
I interrupt whatever else I am doing when I feel the need to access social media	.761	Excellent
I feel connected to others when I use social media	.673	Very good
I lose track of how much I am using social media	.786	Excellent
The thought of not being able to access social media makes me feel distressed	.774	Excellent
I have been unable to reduce my social media use	.733	Excellent

Note. PCA = principal component analysis.

An initial principal components analysis with oblique (Direct Oblimin) rotation and Kaiser Normalization was used to test the factor structure of the SMAQ. Missing value analyses indicated that no more than 2.7% of cases were missing; therefore, the pairwise correlation matrix was analyzed. No univariate or multivariate outliers were detected, and the data were normally distributed. The Kaiser–Meyer–Olkin (Kaiser, 1970) measure of sampling adequacy (MSA) was 0.92, which exceeded the recommended value of 0.60, and Bartlett’s test of sphericity (Bartlet, 1954) reached statistical significance (χ² = 1004.50, df = 28, p <.001), supporting the factorability of the correlation matrix. In resonance with another study, one component was identified, accounting in our study for 52.21% of the overall variability (Elphinston & Noller, 2011). An inspection of the scree plot revealed a clear break after the first component. Using the Cattell scree test (Cattell, 1966), it was decided that one component should be retained. Item loadings are presented in Table 1. All items loaded above .60. Therefore, all of the loadings ranged from good to excellent (Comrey & Lee, 2013; Hawi, 2013). Internal consistency was high (Cronbach’s α = .87).

The mean score on the SMAQ was 24.5 (SD = 9.4), and scores ranged from 8 to 50, indicating an overall moderate level of addictive social media use. The mean score for females, 26.2 (SD = 9.4), was higher than that of males, 22.8 (SD = 9.4). On average, females reported having higher levels of addictive social media use.

RSES is a 10-item instrument that assesses a person’s overall evaluation of worthiness as a human being (Rosenberg, 1965). Responses were coded on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). The RSES contains five positively (e.g., “I am able to do things as well as most people”) and five negatively (e.g., “At times I think I am no good at all”) worded items. The negatively worded items were reverse coded, and then responses were summed to reveal each respondent’s score. Higher scores indicate higher self-esteem. Internal consistency was high (Cronbach’s α = .86) similar to other studies (Hollenbaugh & Ferris, 2014; Link, Struening, Neese-Todd, Asmussen, & Phelan, 2014). The mean score on the RSES was 39.0 (SD = 6.2), and scores ranged from 17 to 50, indicating overall high levels of self-esteem. The mean score for males was 38.5 (SD = 6.8) and that of females was slightly higher at 39.5 (SD = 5.6). On average, females reported having slightly more self-esteem.

The SwLS concerns subjective well-being, assessed by measuring cognitive self-judgment about satisfaction with one’s life (Diener & Diener, 2009). It consists of 5 items rated on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree). In the present study, the scores for this scale ranged from 5 to 35, and the scale had a high internal consistency (Cronbach’s α = .85). High scores on the SwLS indicate high satisfaction with one’s life. In this study, the mean score on the SwLS was 23.5 (SD = 6.7), indicating overall satisfactory levels of satisfaction with life. The mean score for males was 22.8 (SD = 6.2) and that of females was slightly higher at 24.2 (SD = 8.6). On average, females reported being slightly more satisfied with their lives.

Data Analysis

Using IBM SPSS 20, principle component analysis on the SMAQ was conducted, and Pearson product–moment correlation coefficients were calculated. The analyses were used to examine the associations between social media addiction, self-esteem, and satisfaction with life. In all of the simple linear regression analyses, preliminary analyses were first conducted to ensure that there was no violation of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. The identification and estimation of the hypothesized path model was performed in a SEM framework using IBM SPSS Amos Graphics 20.

Results

The means, SDs, and intercorrelations for the study are presented in Table 2. The correlation between social media addiction (as measured by SMAQ) and satisfaction with life (as measured by the SwLS) was investigated using a Pearson product–moment correlation coefficient. There was a zero-order correlation between social media addiction and satisfaction with life. This result confirmed Hypothesis 1 (see Table 2). In addition, there was a small, negative correlation, r = −.23, N = 364, p < .001, between social media addiction and self-esteem (as measured by RSES), with high levels of social media addiction associated with low levels of self-esteem. Additionally, the relation between self-esteem and satisfaction with life was investigated using a Pearson product–moment correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong, negative correlation between the two variables r = −.57, N = 364, p < .001, with high levels of self-esteem associated with high levels of satisfaction with life. That is, if perceived self-esteem decreases by 1 SD from its mean, satisfaction with life would be expected to decrease by 0.57 SDs from its own mean, holding all other relevant regional connections constant. These results confirmed the second hypothesis (see Table 2).

Table 2.

Correlations, Means, Standard Deviations, and Ranges Among Variables.

Variable	M	SD	Range	Gender	SMAQ	RSES	SwLS
Gender				1
SMAQ	24.5	9.4	8–50	0.175**	1
RSES	39.0	6.2	17–50	0.060	−0.231**	1
SwLS	23.5	6.7	5–35	0.122*	−0.028	0.568**	1

Note. SMAQ = Social Media Addiction Questionnaire; RSES = Rosenberg’s Self-Esteem Scale; SwLS = Satisfaction with Life Scale.

*p < .05. **p < .01. ***p < .001.

Simple linear regression was carried out to ascertain the extent to which social media addiction can predict levels of self-esteem. Social media addiction explained 5.2% of the variance in self-esteem, F(1, 364) = 23.9, p = .001. Additionally, self-esteem explained 32.3% of the variance in satisfaction with life F(1, 364) = 216.7, p < .001. The effect of self-esteem on satisfaction with life was checked while saving the residuals. Another regression analysis was carried out to check the effect of social media addiction on the residual variance of satisfaction with life. As a result, no significant effect was found and consequently social media addiction had no direct effect on satisfaction with life. These findings confirmed Hypotheses 1 and 2 that self-esteem mediates the relation between social media addiction and satisfaction with life. All β values are included in the hypothesized path model (see Figure 1).

Figure 1.

Conceptual framework using path analysis.

Furthermore, simple linear regression was carried out to predict the self-esteem of males and females based on social media addiction. The latter explained 3.2% of the variance in self-esteem of males, F(1, 190) = 5.781, p < .05, and 7.3% of the variance in self-esteem of females, F(1, 174) = 23.105, p < .005. These findings contradict Hypothesis 3 because social media addiction explained more of the variance in self-esteem of females compared to males. Similarly, simple linear regression was carried out to predict males and females’ satisfaction with life based on social media addiction. Social media addiction did not predict satisfaction with life for males or females. This finding confirmed Hypothesis 4—that there are no gender differences between social media addiction and satisfaction with life.

The χ² to df ratio (2.189) of the hypothesized path model had a p value of .135. This ratio indicates that our hypothesized model fits the sample data well (Blunch, 2008; Carmines & McIver, 1981). Consequently, the hypothesized model (see Figure 1) was adopted as an adequate description of the sample data. The root mean square error of approximation (RMSEA) for this model was .061. Thus, the acyclic model is an adequate fit because the RMSEA was less than .080 (Browne, Cudeck, Bollen, & Long, 1993). Additionally, the normed fit index, the comparative fit index, the Tucker–Lewis coefficient, and the goodness of fit were .984, .991, .973, and .993, respectively. All these measures suggested that the model had excellent fit. Additionally, the computed PCLOSE (0.281) was significantly higher than .050, indicating that there was absolutely no evidence to reject the fact that RMSEA was higher than .500. The standardized root mean square residual value of .026 indicated excellent fit, as it fell far below the upper limit of .080 (Blunch, 2008). Using AMOS, Version 20, for structural equation modeling, we showed that the hypothesized model fits well with the sample data.

Discussion

The main goal of this study was to examine the relations between social media addiction, self-esteem, and satisfaction with life. To achieve this goal, we changed FIQ into SMAQ to measure addiction to social media and investigated its psychometric properties. The SMAQ’s reliability analysis showed that its internal consistency was very good. In addition, the exploratory factor analysis showed that a one-factor model fits the data very well.

Moreover, our results showed that there was no direct relation between social media addiction and satisfaction with life, which supported Hypothesis 1. This result is in accordance with other studies that showed that use of social networking sites had no direct impact on satisfaction with life (Apaolaza, Hartmann, Medina, Barrutia, & Echebarria, 2013; Valkenburg et al., 2006). It is possible that social media addiction did not associate with university students’ satisfaction with life because the latter, as a construct, assesses the overall quality of life, which includes several aspects such as family, friends, teachers, classmates, and employers (Moksnes & Espnes, 2013). However, social media addiction is associated with self-esteem as the latter assesses only one aspect of one’s life. University students who scored high on social media addiction reported lower levels of self-esteem compared with students who scored low on social media addiction, which is in congruence with other studies’ results (Błachnio et al., 2016; Faraon & Kaipainen, 2014; Schwartz, 2010). Our results confirm that, independently from the culture where the study is conducted, it appears that people with lower self-esteem tend to depend on social media more. Furthermore, students who use social media with the intention of enhancing their self-image are at risk of not only lowering their self-esteem but also their satisfaction with life as well. The evidence of this relation is rooted in the sample data, where analysis showed that self-esteem is strongly positively associated with satisfaction with life. Research has shown a strong relation between self-esteem and satisfaction with life. A study that included more than 13,000 students from 31 nations showed that self-esteem and life satisfaction correlated .47 (Diener & Diener, 2009).

In our study, self-esteem mediated the relation between social media addiction and satisfaction with life, which supported Hypothesis 2. A study that included 881 Dutch adolescents showed that social self-esteem mediated the relation between social networking sites and individual well-being (Valkenburg et al., 2006). Additionally, a study that included 344 Spanish adolescents showed that self-esteem mediated the relation between social networking site use and well-being (Apaolaza et al., 2013).

Our research results mark one of the first milestones on the pathway to understanding, measuring, and preventing social media addiction. This exploratory attempt that yielded SMAQ as a viable scale with good psychometric properties serves as a framework from which to investigate social media addiction in other samples drawn from different segments of a population and with other cognitive, behavioral, and social variables.

Furthermore, there are a few possibilities of how our research findings can be implemented in daily life. The key is in raising awareness that can be launched in universities, schools, and families that targets students in general, students with low self-esteem, or students addicted to social media. Despite their complexity, prevention, intervention, and treatment are needed too.

The study has several limitations. First, the cross-sectional design does not reveal cause and effect relations; longitudinal studies are needed to have a better understanding of the directionality of the relations because they might be reciprocal. Another possible limitation is the sample that included students from one university, and this may not be representative of the whole population. Although most of the studies that have addressed online social media addictions have used samples from a single university (Andreassen, 2015; Griffiths et al., 2014), future research should investigate other universities and different age-groups who also rely heavily on social media. On a final note, even though today Facebook remains the most popular social networking site, and most of the scales were developed to measure only Facebook addiction (Andreassen, 2015; Ryan et al., 2014), we removed the word “Facebook” from the FIQ to make the questionnaire more generic because there are other active social media applications (Griffiths et al., 2014). This was applied to the Bergen Facebook Scale also (Andreassen, Griffiths, et al., 2016).

Conclusion

With the continuous growth of smartphone and tablet ownership, advancement of new technologies, and substantial enhancement of applications, addiction to social media will continue to be a major concern. Our results suggest that, independently from culture and gender, there exists a negative relationship between social media addiction and self-esteem and a mediated negative relationship between social media addiction and satisfaction with life. As the psychology behind social media keeps making it more and more seductive, we expect the problem only to aggravate. So future studies are needed to keep investigating associations as a weak association today might become moderate with time, and a moderate association today might become strong with time. Consequently, future research should build on these results not only to monitor the aforementioned associations but also to investigate prevention and therapy strategies.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the National Council for Scientific Research (CNRS)–Lebanon (Grant 3540/S).

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