Chang Liu
Jian-Ling Ma- 1Yangtze Normal University, Chongqing, China
- 2Chongqing University of Posts and Telecommunications, Chongqing, China
While there is substantial evidence that emotion regulation plays a role in the maintenance of substance and behavior addiction, its role in addiction to social networking sites (SNS) remains unclear. Drawing on attachment theory, we explore whether emotion regulation mediates the relationship between insecure attachment and SNS addiction among 463 college students. The participants completed the short version of the Experience in Close Relationships Scale, Difficulties in Emotion Regulation Scale, and Chinese Social Media Addiction Scale. The results indicated that attachment anxiety positively predicted SNS addiction and that emotion regulation mediated this link. These findings suggest that individuals’ affective regulation capability should be a target of future interventions and treatments.
Introduction
The use of social networking sites (SNS) is now pervasive among college students because of the widespread availability of mobile devices. According to the latest official report released by the China Internet Network Information Center (CNNIC, 2019), there are almost 0.829 billion Netizens in China. SNSs are centered on the formation and maintenance of social connections and close relationships. The top three most popular social media sites in China were WeChat (utilization ratio: 85.5%), QQ (utilization ratio: 67.8%), and Sina Weibo (utilization ratio: 37.1%). WeChat is a Chinese multipurpose messaging, social media, and mobile payment app. It was first released in 2011; by 2018, it was one of the world’s largest standalone mobile apps by monthly active users (over 1 billion). Like WeChat, QQ is another well-known social media platform consisting of online social games, music, shopping, microblogging, movies, and group and voice chat software, with a longer history than WeChat. Sina Weibo implements many features from Twitter (i.e., people follow celebrities).
Although SNSs have clear benefits, e.g., for broadening relationships, relaxation, and overcoming physical limitations, the excessive use of SNS—also known as SNS addiction—can have a detrimental effect on health. Excessive use of SNS leads to higher level of envy, anxiety, and depression (Tandoc et al., 2015; Appel et al., 2016; Liu and Ma, 2018a, b; Keles et al., 2019). SNS addiction can be defined as a failure to control compulsive use of SNSs despite the obvious negative consequences (Kuss and Griffiths, 2017). Numerous studies have explored the personality factors associated with SNS addiction, with attachment style being a particularly significant predictor (Flynn et al., 2018; Worsley et al., 2018a, b; Chen, 2019). However, the mechanism underlying this association remains unclear. In the present study, we investigated emotional regulation difficulties as a possible mediator of this association.
Adult attachment style is formed through early interactions between an infant and one or more primary caregivers (Bowlby, 1973, 1980, 1982, 1988). Attachment theory holds that early emotional bonds between infants and caregivers aid in the formation of infants’ internal working model of self and social interactions (Bretherton, 1987). This model is relatively stable and carries into adulthood, and thereby forms the basis of close and romantic relationships (Hazan and Shaver, 1987; Feeney and Noller, 1990; Bartholomew and Horowitz, 1991). When a caregiver is perceived as responsive, accessible, and trustworthy, an infant develops a secure attachment style. However, when the primary caregiver is inconsistent, unavailable and/or unresponsive, it can give rise to a negative internal working model and insecure attachment (Bretherton, 1987). Currently, scholars acknowledge two major dimensions of adult insecure attachment: attachment anxiety and avoidance (Brennan et al., 1998). An anxious attachment style (i.e., having high attachment anxiety) is characterized by hyperactivity of the attachment system, leading to a constant need to seek support and comfort. An avoidant attachment style, on the other hand, is characterized by a deactivated attachment system, which leads to continual inhibition of psychological and social relationship needs, self-reliance, and a marked distance from others. As far as the association between attachment and SNS addiction concerned, prior studies found that attachment anxiety positively predicts, while avoidance negatively predicts, the addiction (Blackwell et al., 2017; Worsley et al., 2018a). This is reasonable, given that the primary function of SNS to foster and maintain social ties, and to obtain comfort and social support (D’Arienzo et al., 2019). Moreover, other investigations reveal that well-being (Worsley et al., 2018b) and needs satisfaction (Chen, 2019) mediated the attachment-SNS addiction association.
Attachment theory has been conceptualized as an emotion regulation theory (Mikulincer et al., 2003; Schore and Schore, 2008). When an infant does not experience reliable or consistent protection and support from its primary caregiver(s), it develops a hyperactivation or deactivation model of the attachment system to obtain attachment-directed goals, which is partially done via the process of emotion regulation (Cassidy, 1994). Emotion regulation refers to the act of altering one’s emotional experiences via the initiation, maintenance, or modification of their frequency, intensity, or duration (Kobak et al., 1993). A hyperactivation attachment model (i.e., attachment anxiety) develops when a caregiver cannot engage in consistent, sensitive, or responsive interactions to their infant. Individuals with higher levels of anxious attachment tendency are inclined to up-regulate their emotions, thereby overreacting and maintaining high levels of negative emotion (Mikulincer et al., 2003). Deactivating strategies are characteristic of people scoring relatively high on the attachment avoidance dimension. Attachment avoidance is associated with low levels of intimacy and emotional involvement in close relationships, suppression of painful thoughts, repression of negative memories, lack of cognitive accessibility to negative self-representations, projection of negative self-traits onto others, failure to acknowledge negative emotions, and denial of basic fears (Kobak et al., 1993).
In fact, numerous studies have found that attachment anxiety and emotional dysregulation are positively correlated, and these two variables also appear to contribute to maladaptive behavior and affective problems, such as problematic internet use (Estevez et al., 2018), eating disorders (Norrish et al., 2019), anxiety (Esbjorn et al., 2012; Nielsen et al., 2017), and depression (Marques et al., 2018; Owens et al., 2018; Read et al., 2018). Difficulties in emotion regulation are in particular considered risk factors for both substance (e.g., alcohol and drug abuse) and behavioral addiction (e.g., gambling disorder, video game addiction, and smartphone addiction). For example, the internet might serve as a way for individuals to escape feelings of distress and cope with stress, anxiety, and depression. The association between emotion regulation and SNS addiction has also been confirmed, that is, greater difficulties in emotion regulation are associated with problematic use of SNS, as assessed using modified measures of substance abuse (Hormes et al., 2015). Dysfunctional emotional regulation has also been found to be correlated with (Pontes et al., 2018) and predict problematic Facebook use (Marino et al., 2019).
Given the empirical and theoretical evidence of the associations between (a) insecure attachment style and SNS addiction, (b) insecure attachment style and emotional dysregulation, and (c) emotional dysregulation and SNS addiction, it is reasonable to assume that insecure attachment promotes maintenance of emotional dysregulation, which in turn gives rise to SNS addiction. To our knowledge, this model has not yet been tested.
Therefore, the aim of the present study was to determine whether there is an indirect relationship between insecure attachment and SNS addiction via emotion regulation. We used cross-sectional data gathered from a sample of Chinese college students. The following hypotheses were proposed: (1) attachment anxiety positively predicts SNS addiction, while attachment avoidance negatively predicts it; and (2) the association between insecure attachment and SNS addiction is mediated by emotional regulation dysfunction. Figure 1 shows the hypothesized model of our study.
Figure 1. The hypothesized conceptual model of present study. When attachment anxiety is a predictor, attachment avoidance and gender were covariates. When attachment avoidance is a predictor, attachment anxiety and gender were covariates.
Materials and Methods
Participants
A total of 463 college students in China (344 female, M ± SD = 19.94 ± 1.11, range = 17–24 years) volunteered and completed a questionnaire survey of paper-pencil version. All the participants have SNS use experiences at least half a year.
Measures
Experiences in Close Relationship Scale Short Version
The Experiences in Close Relationship Scale short version (ECR-SV; Wei et al., 2007) is a twelve-item measure for evaluating adult attachment. The scale is comprised of two six-item subscales: anxiety and avoidance. Each item is rated on a 7-point Likert scale ranging from 1 = strongly disagree to 7 = strongly agree. The ECR-SV has been found to have good psychometric properties (both reliability and validity) in an Asian sample (Lee and Shin, 2019). The Cronbach’s α values in our study were 0.84 for the anxiety scale and 0.747 for the avoidance scale.
16-Item Version of the Difficulties in Emotion Regulation Scale
The 16-item version of the Difficulties in Emotion Regulation Scale (DERS-16) (Bjureberg et al., 2016) covers five dimensions: (1) non-acceptance, or the lack of acceptance of emotional responses; (2) goals, or difficulty engaging in goal-oriented behaviors; (3) impulse, or difficulty in controlling impulses; (4) strategies, or lack of access to emotion regulation strategies; and (5) clarity, or lack of emotional clarity. The items are rated on a scale of 1 = almost never to 5 = almost always. In a previous study, the DERS-16 was found to have high internal consistency (α = 0.92) and a significant and positive correlation with another measure of emotion regulation (Bjureberg et al., 2016), demonstrating its validity. In our sample, the total scale had excellent internal consistency (Cronbach’s α = 0.93), while the five subscales demonstrated acceptable values: non-acceptance, Cronbach’s α = 0.760; goals, α = 0.777; impulse, α = 0.849; strategies, α = 0.846; and clarity, α = 0.725.
Chinese Social Media Addiction Scale
The Chinese Social Media Addiction Scale (Liu and Ma, 2018a, b) consists of 28 items divided into six dimensions: preference for online social interaction, mood alteration, negative consequences of continued use, compulsive use and withdrawal, salience, and relapse. Each item is rated on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree), with higher scores indicating a higher level of SNS addiction. In the present study, the Cronbach’s α value was 0.944.
Procedure
All the data were collected in August 2018. Approval for the study was obtained from the Human Research Ethics Committee of Chongqing University of Posts and Telecommunications. Written informed consent was obtained from all participants above the age of 16 and from the parents of participants below the age of 16. They were informed that their participation was voluntary and that they could terminate participation anytime they wanted. Participants received no rewards for their participation.
Statistical Analysis
Descriptive statistics and correlation analysis were conducted with SPSS Statistics 20.0 (IBM Corp., Armonk, NY, United States). The proposed mediation model was then tested using the PROCESS macro model 4 (Hayes, 2013). We used the bootstrapping method (with 5000 resamples) to produce 95% bias-corrected confidence intervals (CI) of the model effects. CI that did not include zero indicated significant effects (α = 0.05).
Results
The descriptive results are shown in Table 1 and Supplementary Table S1. Both attachment anxiety and avoidance were positively correlated with emotion dysregulation, which in turn was correlated with SNS addiction. Moreover, anxiety and avoidance were correlated with each other significantly. However, the relationship between attachment avoidance and SNS addiction was not significant.
Table 1. Descriptive statistics and results of correlational analysis of variables (N = 463).
Model 4 of the PROCESS macro was used to test the mediating role of emotional dysregulation in the associations of insecure attachment (anxiety and avoidance) and SNS addiction. Since gender is not balanced in this study, it may contribute to the measures. Thus, t-tests were performed on the four measures to test if there is any contribution from gender. The results showed that there are no gender difference concerning attachment anxiety (Mmale = 22.58, Mfemale = 21.60, t = 1.86, p = 0.06) and avoidance (Mmale = 21.84, Mfemale = 21.87, t = −0.06, p = 0.95), but there are significant gender differences for emotional regulation difficulties: (Mmale = 41.99, Mfemale = 38.34, t = 2.87, p < 0.001) and SNS addiction (Mmale = 83.03, Mfemale = 76, t = 3.45, p < 0.01). To obtain the independent effects of attachment anxiety and avoidance on SNS addiction, we included gender as well as avoidance/anxiety as covariate for overall anxiety and avoidance.
Table 2 shows the effect of attachment anxiety on SNS addiction through emotional regulation difficulty. The total effect of attachment anxiety on SNS addition was 1.48 (95% CI = 1.14–1.86). Attachment anxiety significantly predicted emotion dysregulation (b = 0.963, p < 0.001), which in turn significantly predicted SNS addiction (b = 0.6, p < 0.001). The residual direct effect was also significant (b = 0.9, p < 0.001). The indirect effect = 0.58, 95% CI = 0.37–0.82, the effect size = 0.58/1.48 = 0.39, 95%CI = 0.24–0.59. Emotion dysregulation therefore played a partial mediating role in the association between attachment anxiety and SNS addiction. This model accounted for 28.1% of the variance in SNS addiction.
Table 2. The Influence of attachment anxiety on SNS Addiction with gender and avoidance as covariates.
Table 3 shows the effect of attachment avoidance on SNS addiction through emotion regulation difficulty. The total effect of attachment avoidance on SNS addition was 0.0045 (95%CI = −0.344–0.35). Avoidance attachment predicted emotion dysregulation nonsignificantly (b = 0.14, p = 0.2), which in turn predicted SNS addiction significantly (b = 0.6, p < 0.001). The residual direct effect was not significant (b = −0.08, p = 0.63). Emotion dysregulation therefore did not mediate the association between attachment avoidance and SNS addiction (indirect effect = 0.09, 95%CI = −0.05–0.22).
Table 3. The Influence of attachment avoidance on SNS Addiction with gender and anxiety as covariates.
Discussion
The present study examined the mediating role of emotion dysregulation on the association between insecure attachment and SNS addiction. We found that attachment anxiety positively predicts SNS addiction, while attachment avoidance does not. Emotional dysregulation partly mediated the relationship between anxiety attachment and SNS addiction, but it did not mediate the relationship between avoidance attachment and SNS addiction. This study is, to the best of our knowledge, the first to investigate the correlation between attachment style, emotion dysregulation, and SNS addiction among college students.
Our results align with those of prior studies indicating that attachment anxiety is a predictor of SNS addiction (Wardecker et al., 2016; Blackwell et al., 2017; Lucia et al., 2017; Flynn et al., 2018; Chen, 2019). Individuals with high levels of attachment anxiety tend to have a stronger need for social belongingness, feedback, and comfort, all of which can be fulfilled to some extent by SNSs (Hart et al., 2015). Indeed, other studies revealed that SNS use is closely correlated with individual’s attachment characteristics (Kowert and Oldmeadow, 2015; Lin, 2015; Reed et al., 2015). An initial study found that individuals with high attachment anxiety were more likely to spend more time on an SNS site, use it when they were feeling negative emotions, and show concern over how other Facebook users perceived them (Oldmeadow et al., 2013).
Extant studies have shown that people high in emotion dysregulation often use the internet for mood alteration, which can in turn lead to internet addiction (Lei and Wu, 2007). The same may be true of SNSs. We found that attachment anxiety predicts emotional regulation difficulty, which in turn predicts SNS addiction. That is, emotional regulation difficulty mediates the relationship between attachment anxiety and SNS addiction. This accords with an attachment and emotion regulation perspective. Individuals with high attachment anxiety tended to up-regulate their emotions, thereby overreacting and maintaining high levels of negative emotion. Thus, they may resort to SNS to regulate their emotions through interaction on SNS. It is perhaps this feature that is particularly attractive to users high in attachment anxiety.
We did not find a positive relationship between avoidance attachment and SNS addiction. Results from prior studies on the predictive role of attachment avoidance for SNS addiction are mixed. While one study found that attachment avoidance positively predicted SNS addiction (Blackwell et al., 2017), another study found that it negatively predicted SNS addiction (Worsley et al., 2018b). However, our results agree with one study showing that avoidance attachment is associated with lower SNS use (Oldmeadow et al., 2013). Due to the difference in research focus, however, our study cannot be directly compared with those two previous studies. It is reasonable that attachment avoidance does not predict SNS addiction, given that individuals with an avoidant attachment style may find close relationships through SNS to be distressing, and they may find it difficult to engage in self-disclosure and displays of warmth toward others.
This study’s limitations include. First, the imbalance in gender should be avoided in future studies. Second, the cross-sectional nature of the investigation makes it impossible to judge the causality of the relationships. Third, the use of self-report measurements may threaten the validity of the relationship between variables. Last, the conclusions were draw from college student, whether it can be generalized to population groups need further investigation. Despite these limitations, our study adds to previous findings by showing that attachment theory is useful for explaining the nature of excessive SNS use, not just SNS use in general (Hart et al., 2015). Future research aiming to develop treatments or interventions for SNS addiction should consider focusing on emotion regulation and insecure attachment, as these both appear to be risk factors of SNS addiction.
Data Availability Statement
The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.
Ethics Statement
All the data were collected in August 2018. Approval for the study was obtained from the Human Research Ethics Committee of Chongqing University of Posts and Telecommunications. Written informed consent was obtained from all participants above the age of 16 and from the parents of participants below the age of 16. They were informed that their participation was voluntary and that they could terminate participation anytime they wanted. Participants received no rewards for their participation.
Author Contributions
CL designed the study. Both authors collected the data. J-LM wrote the manuscript.
Funding
The present study was supported by Humanities and Social Sciences Program of Chongqing Education Committee (17SKG192) and the Key Social Sciences Program of Chongqing University of Posts and Telecommunications (2017KZD08).
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
The authors thank for the insights from the reviewers.
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02352/full#supplementary-material
TABLE S1 | The data of the study are presented here. It includes gender, age, avoidance, anxiety, and social networking sites addiction score of each participant.
References
Appel, H., Gerlach, A. L., and Crusius, J. (2016). The interplay between facebook use, social comparison, envy, and depression. Curr. Opin. Psychol. 9, 44–49. doi: 10.1016/j.copsyc.2015.10.006
Bartholomew, K., and Horowitz, L. M. (1991). Attachment styles among young adults: a test of a four-category model. J. Pers. Soc. Psychol. 61, 226–244. doi: 10.1037//0022-3514.61.2.226
Bjureberg, J., Ljótsson, B., Tull, M. T., Hedman, E., Sahlin, H., Lundh, L. G., et al. (2016). Development and validation of a brief version of the difficulties in emotion regulation scale: the DERS-16. J. Psychopathol. Behav. Assess. 38, 284–296. doi: 10.1007/s10862-015-9514-x
Blackwell, D., Leaman, C., Tramposch, R., Osborne, C., and Liss, M. (2017). Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Pers. Individ. Differ. 116, 69–72. doi: 10.1016/j.paid.2017.04.039
Bowlby, J. (1973). Attachment and Loss: Vol. 2. Separation: Anxiety and Anger. New York, NY: Basic Books.
Brennan, K. A., Clark, C. L., and Shaver, P. R. (1998). “Self-report measurement of adult attachment: an integrative overview,” in Attachment Theory and Close Relationships, eds J. A. Simpson and W. S. Rholes (New York, NY: Guilford Press), 46–76.
Bretherton, I. (1987). “New perspectives on attachment relations: security, communication, and internal working models,” in Wiley Series on Personality Processes: Handbook of Infant Development, ed. J. D. Osofsky (Oxford: John Wiley & Sons), 1061–1100.
Cassidy, J. (1994). Emotion regulation: influences of attachment relationships. Monogr. Soc. Res. Child Dev. 59, 228–249. doi: 10.2307/1166148
Chen, A. (2019). From attachment to addiction: the mediating role of need satisfaction on social networking sites. Comput. Hum. Behav. 98, 80–92. doi: 10.1016/j.chb.2019.03.034
CNNIC (2019). The 43rd Internet Network Development Statistical Report of China. Available at: http://www.cnnic.net.cn/ (accessed June 20, 2019).
D’Arienzo, M. C., Boursier, V., and Griffiths, M. D. (2019). Addiction to social media and attachment styles: a systematic literature review. Int. J. Ment. Health Addict. 17, 1094–1118. doi: 10.1007/s11469-019-00082-5
Esbjorn, B. H., Bender, P. K., Reinholdt-Dunne, M. L., Munck, L. A., and Ollendick, T. H. (2012). The development of anxiety disorders: considering the contributions of attachment and emotion regulation. Clin. Child Fam. Psychol. Rev. 15, 129–143. doi: 10.1007/s10567-011-0105-4
Estevez, A., Jauregui, P., Sanchez-Marcos, I., Lopez-Gonzalez, H., and Griffiths, M. (2018). Influence of differential emotion regulation difficulties and attachment figures on gambling disorder and Internet and videogame abuse. J. Behav. Addict. 7, 67–67.
Feeney, J. A., and Noller, P. (1990). Attachment style as a predictor of adult romantic relationships. J. Pers. Soc. Psychol. 58, 281–291. doi: 10.1016/j.psychres.2018.01.010
Flynn, S., Noone, C., and Sarma, K. M. (2018). An exploration of the link between adult attachment and problematic facebook use. BMC Psychol. 6:34. doi: 10.1186/s40359-018-0245-0
Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford Press.
Hart, J., Nailling, E., Bizer, G. Y., and Collins, C. K. (2015). Attachment theory as a framework for explaining engagement with facebook. Pers. Individ. Differ. 77, 33–40. doi: 10.1016/j.paid.2014.12.016
Hazan, C., and Shaver, P. (1987). Romantic love conceptualized as an attachment process. J. Pers. Soc. Psychol. 52, 511–524. doi: 10.1037//0022-3514.52.3.511
Hormes, J. M., Kearns, B., and Timko, C. A. (2015). Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits. Addiction 109, 2079–2088. doi: 10.1111/add.12713
Keles, B., McCrae, N., and Grealish, A. (2019). A systematic review: the influence of social media on depression, anxiety and psychological distress in adolescents. Int. J. Adolesc. Youth 1–15. doi: 10.1080/02673843.2019.1590851
Kobak, R. R., Cole, H. E., Ferenz-Gillies, R., Fleming, W. S., and Gamble, W. (1993). Attachment and emotion regulation during mother-teen problem solving: a control theory analysis. Child Dev. 64, 231–245. doi: 10.1111/j.1467-8624.1993.tb02906.x
Kowert, R., and Oldmeadow, J. A. (2015). Playing for social comfort: online video game play as a social accommodator for the insecurely attached. Comput. Hum. Behav. 53, 556–566. doi: 10.1016/j.chb.2014.05.004
Kuss, D., and Griffiths, M. (2017). Social networking sites and addiction: ten lessons learned. Int. J. Environ. Res. Public Health 14:311. doi: 10.3390/ijerph14030311
Lee, J.-Y., and Shin, Y.-J. (2019). Experience in close relationships scale–short version (ECR–S) validation with korean college students. Meas. Eval. Couns. Dev. 52, 119–127. doi: 10.1080/07481756.2018.1497431
Lei, L., and Wu, Y. (2007). Adolescents paternal attachment and internet use. Cyberpsychol. Behav. 10, 633–639. doi: 10.1089/cpb.2007.9976
Lin, J. H. (2015). The role of attachment style in facebook use and social capital: evidence from university students and a national sample. Cyberpsychol. Behav. Soc. Netw. 18, 173–180. doi: 10.1089/cyber.2014.0341
Liu, C., and Ma, J. (2018a). Development and validation of the Chinese social media addiction scale. Pers. Individ. Differ. 134, 55–59. doi: 10.1016/j.paid.2018.05.046
Liu, C., and Ma, J. (2018b). Social media addiction and burnout: the mediating roles of envy and social media use anxiety. Curr. Psychol. doi: 10.1007/s12144-018-9998-0
Lucia, M., Palo, V. D., Mark, D. G., and Sinatra, M. (2017). Social networking addiction, attachment style, and validation of the Italian version of the bergen social media addiction scale. J. Behav. Addict. 6, 178–186. doi: 10.1556/2006.6.2017.023
Marino, C., Caselli, G., Lenzi, M., Monaci, M. G., Vieno, A., Nikčević, A. V., et al. (2019). Emotion regulation and desire thinking as predictors of problematic facebook use. Psychiatr. Q. 90, 405–411. doi: 10.1007/s11126-019-09628-1
Marques, R., Monteiro, F., Canavarro, M. C., and Fonseca, A. (2018). The role of emotion regulation difficulties in the relationship between attachment representations and depressive and anxiety symptoms in the postpartum period. J. Affect. Disord. 238, 39–46. doi: 10.1016/j.jad.2018.05.013
Mikulincer, M., Shaver, P. R., and Pereg, D. J. M. (2003). Attachment theory and affect regulation: the dynamics, development, and cognitive consequences of attachment-related strategies. Motiv. Emot. 27, 77–102.
Nielsen, S. K. K., Lonfeldt, N., Wolitzky-Taylor, K. B., Hageman, I., Vangkilde, S., and Daniel, S. I. F. (2017). Adult attachment style and anxiety - the mediating role of emotion regulation. J. Affect. Disord. 218, 253–259. doi: 10.1016/j.jad.2017.04.047
Norrish, A., Cox, R., Simpson, A., Bergmeier, H., Bruce, L., Savaglio, M., et al. (2019). Understanding problematic eating in out-of-home care: the role of attachment and emotion regulation. Appetite 135, 33–42. doi: 10.1016/j.appet.2018.12.027
Oldmeadow, J. A., Quinn, S., and Kowert, R. (2013). Attachment style, social skills, and facebook use amongst adults. Comput. Hum. Behav. 29, 1142–1149. doi: 10.1016/j.chb.2012.10.006
Owens, G. P., Held, P., Hamrick, L., and Keller, E. (2018). The indirect effects of emotion regulation on the association between attachment style, depression, and meaning made among undergraduates who experienced stressful events. Motiv. Emot. 42, 429–437. doi: 10.1007/s11031-018-9688-0
Pontes, H. M., Taylor, M., and Stavropoulos, V. (2018). Beyond “facebook addiction”: the role of cognitive-related factors and psychiatric distress in social networking site addiction. Cyberpsychol. Behav. 21, 240–247. doi: 10.1089/cyber.2017.0609
Read, D. L., Clark, G. I., Rock, A. J., and Coventry, W. L. (2018). Adult attachment and social anxiety: the mediating role of emotion regulation strategies. PLoS One 13:e0207514. doi: 10.1371/journal.pone.0207514
Reed, L. A., Tolman, R. M., and Safyer, P. (2015). Too close for comfort: attachment insecurity and electronic intrusion in college students’ dating relationships. Comput. Hum. Behav. 50, 431–438. doi: 10.1016/j.chb.2015.03.050
Schore, J. R., and Schore, A. N. (2008). Modern attachment theory: the central role of affect regulation in development and treatment. Clin. Soc. Work J. 36, 9–20. doi: 10.1007/s10615-007-0111-7
Tandoc, E. C. Jr., Ferrucci, P., and Duffy, M. (2015). Facebook use, envy, and depression among college students: is facebooking depressing? Comput. Hum. Behav. 43, 139–146. doi: 10.1016/j.chb.2014.10.053
Wardecker, B. M., Chopik, W. J., Boyer, M. P., and Edelstein, R. S. (2016). Individual differences in attachment are associated with usage and perceived intimacy of different communication media. Comput. Hum. Behav. 59, 18–27. doi: 10.1016/j.chb.2016.01.029
Wei, M., Russell, D. W., Mallinckrodt, B., and Vogel, D. L. (2007). The Experiences in Close Relationship scale (ECR)-short form: reliability, validity, and factor structure. J. Pers. Assess. 88, 187–204. doi: 10.1080/00223890701268041
Worsley, J. D., Mansfield, R., and Corcoran, R. (2018a). Attachment anxiety and problematic social media use: the mediating role of well-Being. Cyberpsychol. Behav. 21, 563–568. doi: 10.1089/cyber.2017.0555
Keywords: adult attachment style, attachment anxiety, attachment avoidance, emotion regulation, SNS addiction
Citation: Liu C and Ma J-L (2019) Adult Attachment Style, Emotion Regulation, and Social Networking Sites Addiction. Front. Psychol. 10:2352. doi: 10.3389/fpsyg.2019.02352
Received: 30 April 2019; Accepted: 02 October 2019;
Published: 24 October 2019.
Edited by:
Nicholas Furl, Royal Holloway, University of London, United KingdomReviewed by:
Barbara Caci, University of Palermo, ItalyAndrej Košir, University of Ljubljana, Slovenia
Copyright © 2019 Liu and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jian-Ling Ma, jianling_ma@163.com