Abstract
Background and aims
We aimed to systematically identify, evaluate and summarize the research on adolescent emotion dysregulation and problematic technology use. We critically appraise strengths and limitations and provide recommendations for future research.
Methods
We followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and conducted a systematic review of published original reports on adolescent emotion dysregulation and problematic technology use published until March 1, 2022. A thorough search preceded the selection of studies matching prespecified criteria. Strengths and limitations of selected studies, regarding design and reporting, were identified based on current best practices.
Results
39 studies met inclusion criteria. All of these studies provided on the relationship between adolescent emotion dysregulation and problematic technology use severity based on self-report data.
Discussion
There was a positive correlation between adolescent emotion dysregulation and the severity of problematic technology use. Beyond this, other variables (such as anxiety, depression, self-esteem, etc.) were also closely related to emotion dysregulation and problematic technology use. Such studies are of importance to better understand cause-effect relations regarding both variables.
Introduction
Emotion regulation refers to the psychological processes whereby individuals influence which emotions they have, when they have them, and how they experience and express these emotions (Carl, Soskin, Kerns, & Barlow, 2013; Gross, 1998). It is very important to regulate emotions well in daily life, especially for adolescents. Adolescents are often in a state of emotional “over-arousal” (Michel, Heuzey, Purper-Ouakil, & Mouren-Simeoni, 2001) and can be considered more emotional compared to adults (Montag & Panksepp, 2017). This may be because the hippocampus and amygdala of the human brain are still developing (to be discussed to be of high relevance to the regulation of emotions) (Xu, Zhou, Luo, Luo, & Qin, 2021). Despite humans undergoing neurodevelopment throughout their lives, individual differences in emotional regulation abilities already exist at a young age, and some children and adolescents show tendencies towards emotion dysregulation (Sanchis-Sanchis, 2020). This may also be due to their comparably (to adults) lower level of good emotional regulation. The limited effect of adolescents' internal regulation strategies and the many pressures and challenges they face, the reduced dependence on family support may lead to the emergence of this phenomenon (Young, Sandman, & Craske, 2019).
In emotion dysregulation (ED) research, ED has been conceptualized as difficulties in monitoring, evaluating, and adjusting emotional responses (Gross, 2008; Gross & Jazaieri, 2014). And in the study by Velotti, Rogier, Beomonte Zobel, and Billieux (2021), emotion dysregulation is used to refer to emotion dysregulation failures related to these deficits or regulation strategies. In a recent study by Beauchaine (2015a), emotion dysregulation was defined as a pattern of emotional experience and/or expression that interferes with appropriate goal-directed behavior. For the present research, the definition of Beauchaine (2015a) is reasonable, because this definition emphasizes the core content of emotion dysregulation. The purpose of emotion regulation among others is to express emotions more appropriately, and emotion dysregulation could be defined as the inability to properly regulate emotions and hold a tight grip upon showing strong emotional responses in inappropriate situations. Adolescent emotion dysregulation has been confirmed to be related to many kinds of problematic behaviors (Bjureberg et al., 2018; Lemaigre & Taylor, 2019), especially addictive behaviors with technology use (Casale, Caplan, & Fioravanti, 2016; Evren, Evren, Dalbudak, Topcu, & Kutlu, 2018; Montag & Elhai, 2020; Pettorruso et al., 2020; Sertbaş, Çutuk, Soyer, Çutuk, & Aydoğan, 2020).
Problematic technology use (PTU, i.e., Internet, videogames, and smartphones) refers to excessive use of technology as a critical part of life, going along with several consequences such as functional impairment (e.g., academic and social deficits), and is accompanied by emotional and behavioral problems (Amendola, Spensieri, Biuso, & Cerutti, 2020). Problematic technology use can be divided into two categories: tool-based (Internet, Smartphone) versus content-based (videogame, social media). We should emphasize that there is still controversy about how to properly name and categorize these phenomena (Elhai, Yang, & Levine, 2021; Montag, Wegmann, Sariyska, Demetrovics, & Brand, 2021). Of note, researchers have consistently confirmed the relationship between adolescent problematic technology use and a variety of behavioral problems (Huang & Leung, 2009; Kafali et al., 2020; Karma et al., 2019) and emotional disorders (Hussain, Wegmann, Yang, & Montag, 2020; Peterka-Bonetta, Sindermann, Sha, Zhou, & Montag, 2019; Zhang, Ding, & Wang, 2020).
Emotional disorders are psychopathologies characterized by “frequent experiences of strong negative emotions, aversion to negative emotions, and efforts to avoid these emotional experiences” (Bentley, Cassiello-Robbins, Vittorio, Sauer-Zavala, & Barlow, 2015). Both the I-PACE (Interaction of Person-Affect-Cognition-Execution) theoretical model (Brand et al., 2016, 2019) and CIUT (Compensatory Internet Use Theory, Kardefelt-Winther, 2014) propose that emotional disorders are closely related to problematic technology use. Specifically this should be the case for individuals' use of Internet-related technologies, because by using such technology individuals can alleviate negative emotions, which may cause them to overuse the Internet and thus lead to problematic technology use. The more negative emotions individuals experienced, the higher their problematic technology use severity can be (Bonnaire & Baptista, 2019; Richardson, Hussain, & Griffiths, 2018; Yuan, Elhai, & Hall, 2020). It has been shown that emotion dysregulation can predict the occurrence of emotional disorders (Hofmann, Sawyer, Fang, & Asnaani, 2012; McLaughlin, Hatzenbuehler, Mennin, & Nolen-Hoeksema, 2011), and both emotion dysregulation and emotional disorders are strongly related to problematic technology use. These pieces of evidence suggest that it is necessary to clarify the relationship between emotion dysregulation and problematic technology use, especially for adolescents. The main purpose of this review is to systematically collect evidence about the relationship between adolescent emotion dysregulation and their problematic technology use. Finally, based on these existing research results, future research directions are proposed.
Method
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for our review (Moher, Liberati, Tetzlaff, & Altman, 2010). Our PRISMA checklist is also depicted in Fig. 1.
PRISMA flow diagram of study selection
Citation: Journal of Behavioral Addictions 11, 2; 10.1556/2006.2022.00038
Search strategy
We used the Tianjin Normal University electronic library to simultaneously search electronic databases in CNKI, Web of Science (including Science Citation Index Expanded, Social Sciences Citation Index, Current Chemical Reactions, Index Chemicus, KCI-Korean Journal Database, MEDLINE, Russian Science Citation Index, and SciELO Citation Index) and Proquest (including PsycINFO and other psychological databases). Our comprehensive literature search of studies published until March 1, 2022, was used. The final search strategy was (child* OR adolescent* OR teen* OR juvenile* OR young* OR youth*) AND (problematic technology use OR addiction OR Internet OR Internet Gaming Disorder OR smartphone overuse OR online OR cybersex OR social network OR compulsive use OR excessive use OR pathological use OR game OR Computer OR abuse OR Gaming depend* OR virtual addiction) AND (emotion regulation OR emotional disorder OR emotion dysregulation). Additional manual searches were also conducted.
Study selection
According to the literature on adolescents, we define their age-range as 10–24 years old (Pozuelo, Desborough, Stein, & Cipriani, 2021; Sawyer, Azzopardi, Wickremarathne, & Patton, 2018). Studies were eligible for inclusion if they tested a relationship between adolescent emotion dysregulation and some type of problematic technology use measured, and all studies adhered to the foregoing conceptualizations. To identify as many studies as possible in our initial search, no restrictions were placed on academic discipline, publication date or status, language, country, participant demographics, or research design. All abstracts were reviewed and discussed when disagreement occurred as to whether to obtain the document's full text. The authors then reviewed full-text documents to determine if each document was relevant and if so, to extract findings of interest.
Study inclusion criteria
The studies included in this review met the following criteria: (1) published in a peer-reviewed journal; (2) participants are adolescents; (3) investigated at least adolescent emotion dysregulation and problematic technology use; (4) the research method is empirical.
Results
A total of 39 articles met our eligibility criteria and were included in this review. Detailed information is available in Fig. 1, the PRISMA Flow Chart, and Table 1, with summaries and classifications of all articles. All articles represent empirical studies and are consistent with our broad search. All of the included studies were related to adolescent emotion dysregulation and their problematic technology use. In addition, we observed in the literature that also other variables play a role regarding the relationship between adolescent emotion dysregulation and their problematic technology use (such as emotional disorders, behavioral problems). The exact measures are described in Table 1 of the literature.
Characteristics of included studies
| Author (year), Country | Sample | Total N (% male participants) | Mean age (SD), Age range | Emotion Dysregulation measure | Problematic Technology Use measure | Associations between emotion dysregulation and PTU - r (*P < 0.05, **P < 0.01, ***P < 0.001) |
| Austermann et al., (2021), Germany | Ordinary People | 961 (53.5%) | 13.36 (SD = 2.36), 10–17 | Difficulties in Emotion Regulation Scale | Social Media Disorder Scale for Parents (SMDS-P) | 0.35*** |
| Amendola et al., (2019), Italy | Students | 280 (51.1%) | 13.31 (SD = 2.33), 11–18 | Difficulties in Emotion Regulation Scale | Internet Addiction Test (IAT) Video Game Dependency Scale (CSAS) Brief Multicultural Version of the Test of Mobile Phone Dependence (TMDbrief) |
CSAS 0.372***; IAT 0.504***; TMDbrief 0.424*** |
| Anita et al., (2014), USA | Students | 272 (47.06%) | 16.81 (SD = 0.39), 16–17 | Difficulties in Emotion Regulation Scale | Hungarian Problematic Internet Use Questionnaire | |
| Casale et al., (2016), Italy | Students | 293 (48.4%) | 21.73 (SD = 2.17), none | Difficulties in Emotion Regulation Scale | Generalized Problematic Internet Use Scale 2 | 0.342** |
| Chang et al., (2020), China | Adolescent outpatients | IA [no 49 (77.6%)] [yes 52 (59.6%)] | None, 7–18 | Chen Internet Addiction Scale | ||
| Chun (2016), South Korea | Students | 351 (60.6%) | 13.5 (SD = 0.84), none | Difficulties in Emotion Regulation Scale | Korean Internet Addiction Proneness Scale | |
| Coco et al., (2020), Italy | Ordinary People | 242 (45%) | 14.16 (SD = 0.99), 12–16 | Difficulties in Emotion Regulation Scale-Short Form | Smartphone Addiction Scale-short version | 0.392** |
| Domoff et al., (2020), USA | Ordinary People | 111 (44.1%) | 14.57 (SD = 1.08), none | Difficulties in Emotion Regulation Scale | Addictive Patterns of Use (APU) Scale | 0.29 ** |
| Donald et al., (2020), Australia | Students | 2809 (49.7%) | 13.7 (SD = 0.45), none | Difficulties in emotion regulation scale | Compulsive Internet Use scale | |
| Estévez et al., (2017), Spain | Students | 472 (48.4%) | 15.6 (SD = 1.33), 13–21 | Difficulties in Emotion Regulation Scale | Video Game-related Experience Questionnaire | 0.43** |
| Estévez et al., (2020), Spain | Adolescent outpatients and Ordinary People | [outpatients 31 (90.3%)] [ordinary 250 (50.4%)] | [outpatients 20.8 (SD = 2.4)] [ordinary 18.2 (SD = 4.9)], none | Difficulties in Emotion Regulation Scale | MULTICAGE-ICT | |
| Evren et al., (2018), Turkey | Ordinary People | Probable ADHD [Absent 820 (40.49%)] [Present 190 (37.89%)] | Probable ADHD [Absent 21.89 (SD = 3.54)] [Present 21.67 (SD = 2.64)], none | Difficulties in Emotion Regulation Scale | Young's Internet Addiction Test - Short Form | |
| Evren et al., (2019), Turkey | Ordinary People | IA risk [Low 806 (33%)] [High 114 (28.95%)] | IA risk [Low 22.19 (SD = 4.26)] [High 21.69 (SD = 2.21)], none | Difficulties in Emotion Regulation Scale | Internet Addiction Test | |
| Faghani et al., (2019), Iran | Students | 300 (40%) | [20.13 (SD = 1.555) men] [20.27 (SD = 1.467) women], none | Difficulties in Emotion Regulation Scale | Single-factor Internet abusive use questionnaire (IAUQ) | 0.475** |
| Giordano et al. (2020), Italy | Ordinary People | 252 (42.5%) | 13.54 (SD = 0.7), 12–17 | Difficulties in Emotion Regulation Scale-Short Form | the 24-item Italian version of the Smartphone Addiction Inventory | 0.438** |
| Gül et al. (2019), Turkey | Adolescent outpatients | 150 (41.3%) | 15.4 (SD = 1.4), 12–18 | Difficulties in Emotion Regulation Scale | Problematic Mobile Phone Usage Scale | DERS-C(0.34**), DERS-NA(0.22*), DERS-S(0.56**), DERS-I(0.60**), DERS-G(0.50**) |
| Günaydın et al., (2021), Turkey | Students | 5916 (50.9%) | None | Difficulties in Emotion Regulation Scale | Problematic Internet Use Scale-Adolescent Form | 0.33*** |
| Gutiérrez et al., (2014), Spain | Ordinary People | 1312 (57.4%) | 17.28 (SD = 2.7), 12–30 | Difficulties in Emotion Regulation Scale | MULTICAGE CAD-4 | |
| Hormes et al., (2014), USA | Students | 253 (37.2%) | 19.68 (2.85), none | Difficulties in Emotion Regulation Scale | Young Internet Addiction Test | |
| Kafali et al. (2020), Turkey | Patients in hospital | 123 (44.72%) | [OB 15 (SD = 1.9)] [HC 15.5 (SD = 1.8)], none | Difficulties in Emotion Regulation Scale | Internet Addiction Test | 0.451** |
| Karaer and Akdemir (2019), Turkey | Adolescent outpatients | 160 (34.6%) | [IA 15.4 (SD = 1.3)] [15.4 (SD = 1.1)], none | Difficulties in Emotion Regulation Scale | Young's Internet Addiction Test Young's Internet addiction diagnostic criteria |
|
| Kim and Chun (2016), the Republic of Korea | Students | 355 (60.6%) | None, 12–16 | Difficulties in Emotion Regulation Scale | K-scale | 0.34** |
| Liese et al., (2020), USA | Students | 689 (34.8%) | 18.99 (SD = 1.29), 18–31 | Difficulties in Emotion Regulation Scale | Potentially addictive behaviors | |
| Love et al., (2022), USA | Students | 257 (7.9%) | 20.18 (SD = 1.04), 18–29 | Difficulties in Emotion Regulation Scale | Internet Addiction Test | 0.49** |
| Paschke, Austermann, and Thomasius (2021), Germany | Ordinary People | 800 (58.6%) | 12.99 (SD = 2.37), 10–17 | short form of the Difficulties in Emotion Regulation Scale | DSM-5 the Internet Gaming Disorder Scale parental judgment version (PIGDS) | |
| Pettorruso et al., (2020), Italy | Ordinary People | 428 (64.5%) | 22.3 (SD = 3.6), 18–29 | Difficulties in Emotion Regulation Scale | Internet Addiction Diagnostic Questionnaire | |
| Mancinelli et al., (2021), Italy | Adolescent outpatients | 78 (26.9%) | 14.24 (SD = 1.56), 14–19 | Difficulties in Emotion Regulation Scale | Smartphone Addiction inventory | 0.319** |
| Mo et al. (2018), China | Students | 862 (54.4%) | 12.53 (SD = 0.84), 12–15 | Emotion Regulation Scale | 26-item Chen Internet Addiction Scale | 0.39** |
| Müller and Bonnaire (2020), France | Ordinary People and Students | 201 (63.18%) | 19.02 (SD = 4.20), 12–25 | Difficulties in Emotion Regulation Scale | short version of the GAS | |
| Marchica et al., (2020), Canada | Students | 1536 (45.25%) | 20.45, 18–27 | Difficulties in Emotion Regulation Scale | Internet Gaming Disorder Scale—Short-Form | |
| Qi (2019), China | Students | 870 (57.13%) | 13.61 (SD = 0.89), 12–16 | Emotional Reactivity subscale of the Differentiation of Self Inventory | Problematic Internet Use Scale | 0.36*** |
| Tsai, Lu, Hsiao, Hu, and Yen (2020), China | Students | 500 (47.6%) | 22.1 (SD = 1.8), 20–30 | Difficulties in Emotion Regulation Scale | Chen Internet Addiction Scale | |
| Starosta et al., (2021), Poland | Students | 645 (15%) | 20 (SD = 3.04), 18–30 | Difficulties in Emotion Regulation Scale | Questionnaire of Excessive Binge-watching | |
| Sertbaş et al., (2020), Turkey | Students | 297 (49%) | 20.88 (SD = 1.82), 18–36 | Difficulties in Emotional Regulation Scale | Chinese Internet Addiction Scale | 0.57** |
| Uçur & Donmez (2021), Turkey | Ordinary People | 1067 (54.3%) | 14.7 (SD = 1.8), 12–18 | Difficulties in emotion regulation scale | Game addiction scale (short form) | 0.234* |
| Wang and Qi (2017), China | Students | 828 (57.61%) | 13.58, 11–16 | Emotional Reactivity subscale of the Differentiation of Self inventory | Problematic Internet Use Scale | 0.37*** |
| Yorulmaz et al. (2020), Turkey | Students | 400 (45.5%) | 21.24 (SD = 1.73), 18–25 | Difficulties in Emotion Regulation Scale | Internet Addiction Test | 0.47* |
| Yu et al. (2013), Australia | Students | 525 (70.1%) | 15.33 (SD = 0.47), none | Difficulties in Emotion Regulation Scale | The 20-item IAT | |
| Yıldız (2017), Turkey | Students | 262 (49.6%) | 16.57 (SD = 1.13), 14–19 | Emotion Regulation Scale for Adolescents | Young Internet Addiction Test-Brief Form and Smartphone Addiction Scale – Brief Form | 0.53**(EDER and Internet Addiction) 0.37**(EDER and Smartphone addiction) 0.47**(IDER and Internet Addiction) 0.32**(IDER and Smartphone addiction) |
A total of 39 articles included in the present systematic review originated mainly in Turkey (10), Italy (6), China (5), USA (5), Spain (3), Australia (2), Germany (2), South Korea (1), Iran (1), the Republic of Korea (1), France (1), Canada (1) and Poland (1). All studies discussed the relationship between emotion dysregulation and their problematic technology use using a self-report method, using correlation analysis, or variance analysis.
The relationship between adolescent ED and PTU
Table 1 describes the main content of all 39 studies. Twenty-six of the studies indicated that there was a significant positive correlation between the degree of adolescent emotion dysregulation and the severity of problematic technology use. Eight of these articles indicated that the severity of emotion dysregulation in problematic technology users was significantly higher than in non-problematic technology users. In addition to the aforementioned, there are some further notable findings in the literature: Chun's study (2016) indicated that the direct effect of emotion dysregulation and problematic technology use severity was not significant, but the indirect from emotion regulation to problematic technology use mediated by a third variable was significant. Liese, Kim, and Hodgins (2020) observed that emotion dysregulation mediated the relationship between anxious but not avoidant attachment and Internet Gaming Disorder. Karaer and Akdemir's study (2019) showed that Difficulties in Emotion Regulation Scale (DERS) scores in the adolescent “Internet Addiction” group were significantly higher than those in the control group. Estévez et al. (2020) indicated the highest emotion dysregulation scores and the highest scores for difficulties in coping strategies (one of the subscales of DERS) were associated with the comorbid presence of gambling disorder and other problematic technology use. And the study by Chang, Chang, Cheng, and Tzang (2020) noted that emotion dysregulation is frequently seen in severely gaming-addicted ADHD (Attention Deficit Hyperactivity Disorder) youth. The longitudinal results of Donald et al. (2020) point out that teaching adolescents general emotion regulation skills may not be as effective in reducing compulsive Internet use as more direct approaches of limiting the use of the internet. Starosta, Izydorczyk, Sitnik-Warchulska, and Lizinczyk (2021) identified a lack of premeditation, impulse control difficulties, and escapist motivation as significant predictors of problematic binge-watching behaviors.
Of note, the reviewed studies relied on different instruments to measure adolescent differences in propensities towards emotion dysregulation and problematic technology use. Although measurement tools differ across studies, we can classify PTUs into generalized PTUs (as captured via terms such as Internet, Smartphone, etc.) and content-based PTUs (Video game, Social Network, etc.). This is consistent with generalized problematic Internet use versus specific problematic Internet use in the theoretical model proposed by Davis (2001). It has also been validated in recent empirical studies (Montag et al., 2015).
The relationship between adolescent ED and generalized PTUs
Among the included articles, there was a significant positive correlation between adolescents' DERS total scores and their severity of problematic smartphone use (Amendola, Spensieri, Guidetti, & Cerutti, 2019; Coco et al., 2020; Domoff, Sutherland, Yokum, & Gearhardt, 2020; Giordano, Coco, Salemo, & Biasi, 2020; Mancinelli, Sharka, Lai, Sgaravatti, & Salcuni, 2021) and problematic Internet use (Amendola et al., 2019; Anita, András, & Bernadette, 2014; Casale et al., 2016; Estévez, Jáuregui, Sánchez-Marcos, López-González, & Griffiths, 2017; Faghani, Akbari, Hasani, & Marino, 2019; Gutiérrez, Fernández, Gonzalvo, & Bilbao, 2014; Günaydın, Arıcı, Kutlu, & Demir, 2021; Kafali et al., 2020; Kim & Chun, 2016; Love, May, Shafer, Fincham, & Cui, 2022; Mo, Chan, Chan, & Lau, 2018; Qi, 2019; Sertbaş et al., 2020; Uçur & Dönmez, 2021; Wang & Qi, 2017; Yorulmaz, Civgin, & Yorulmaz, 2020). The DERS was developed by Gratz and Roemer (2004) to measure emotion dysregulation. When individual differences in ED are assessed via this inventory it includes six subscales: nonacceptance of emotional responses, difficulties engaging in goal-directed behavior, impulse control difficulties, lack of emotional awareness, limited access to emotion regulation strategies, and lack of emotional clarity (Gratz & Roemer, 2004). Gül et al. (2019) showed that there is a significant positive correlation between adolescent problematic smartphone use severity and DERS subscales including clarity, non-acceptance, strategies, impulse, and goals. Evren et al. (2018) argued that adolescent lack of emotional awareness and problematic Internet use are closely related. Yıldız (2017) used the Emotion Regulation Scale for Adolescents (ERSA) (Phillips & Power, 2007) to measure individual differences in tendencies towards adolescent emotion dysregulation. In this work, it could be observed that adolescent EDER (External-Dysfunctional Emotion Regulation) and IDER (Internal-Dysfunctional Emotion Regulation) were related to higher scores on problematic Internet use and problematic smartphone use. Chun (2016) points out that although ED did not directly affect problematic Internet use alone, it could influence problematic Internet use via the self-esteem variable. The results of the Pettorruso et al. study (2020) pointed out that the DERS total score and each subscale score among problematic Internet users and high-risk participants were higher than those of non-risk and low-risk individuals.
The relationship between adolescent ED and content-based PTUs
Among the included articles, there was a significant positive correlation between adolescents' DERS total scores and their severity of Internet Gaming Disorder (Amendola et al., 2019; Estévez et al., 2017; Gutiérrez et al., 2014; Paschke et al., 2020) and problematic social media use (Austermann, Thomasius, & Paschke, 2021). Hormes, Kearns, and Timko (2014) found that problematic social media users have a higher degree of emotion dysregulation (lack of awareness and non-acceptance). A study by Marchica, Mills, Keough, and Derevensky (2020) indicated that Internet gaming addicts have higher emotion dysregulation levels (Goals, Impulse, Clarity). A study by Müller and Bonnaire (2020) indicated that Internet gaming addicts have higher emotion dysregulation levels (lack of emotional awareness and clarity). Karaer and Akdemir (2019) found that the total DERS score in the group of “Internet Addicted” individuals was significantly higher than controls. Evren et al. (2020) found that the DERS total scores and subscales of the high risk group of Internet addiction were higher than those of the low risk group of Internet addiction (except for awareness). Both studies are again mentioned in the next section.
The role of further variables regarding the association between adolescent ED and PTU
In total, we selected 39 studies for the present systematic review. In these articles, several investigators discussed the role of other variables between emotion dysregulation and problematic technology use. These variables may help to understand the relationship between emotion dysregulation and problematic technology use in adolescents. We therefore briefly describe these studies in this section. We use in this summary always the original wording (regarding the terminology used) from the authors in the original studies.
Casale et al. (2016) indicated that two specific metacognitions about Internet use (escapism and controllability) mediate the association between emotion dysregulation and problematic Internet use. Kim and Chun's research (2016) showed that both closed communication (a kind of problematic communication) between parents and children and adolescent depression-anxiety are significantly positively correlated with their emotion dysregulation and problematic Internet use tendencies, and the relationship between closed communication and adolescent problematic Internet use severity was partially mediated by both depression-anxiety and emotion dysregulation. Chun's work (2016) indicated that emotion dysregulation was related to problematic Internet use severity through low self-esteem as a mediating variable. Wang and Qi (2017) found that child forgiveness of others moderated the indirect relation of harsh parenting to adolescent problematic Internet use via child emotion dysregulation. And there has been a moderating role of psychological flexibility in explaining the correlation between difficulties in emotion regulation and problematic internet use (Yorulmaz et al., 2020).
Discussion
The current systematic review of 39 studies including a total of N = 27,169 participants supported a clear association between emotion dysregulation and problematic technology use severity in adolescents. This finding suggests that emotion dysregulation and problematic technology use are closely related in adolescents, and against the background of the culturally different groups investigated in the studies, this effect may have some cross-cultural consistency. Moreover, the results of this study are also consistent with those by Gioia, Rega, and Boursier (2021), who carried out a literature review on the relationship between problematic Internet use and emotion dysregulation in all ages. It is important to note that the age range of the participants in the selected literature for the present study was 10–24 (adolescents), and although a few participants in some studies were not in this range, the vast majority of participants were. Please note the age of the participants in the present study (the maximum age was 61 years in the study by Gioia et al. (2021)) and the type of problematic behavior investigated in our study was different than in the study by Gioia et al. (2021). Although our literature review and the one by Gioia et al. (2021) differ to some extent, both works come to the conclusion that the association between emotional dysregulation and problematic technology use is of importance. Compared with the study of Gioia et al. (2021), the current study found that in adolescents, emotion dysregulation is closely related not only to problematic Internet use, but also to specific problematic technology use such as Internet Gaming Disorder, problematic social media use, and problematic smartphone use.
In addition, we also observed that adolescents with emotion dysregulation and problematic technology use often report further behavioral problems or higher levels of negative mood symptoms. Of these, the most closely related variables were higher propensity towards depression and anxiety severity. In the process of literature retrieval, we discovered many studies reporting close relationships between adolescent problematic technology use severity and emotional disorder symptoms (Bozkurt, Coskun, Ayaydin, Adak, & Zoroglu, 2013; Fabris, Marengo, Longobardi, & Settanni, 2020; Lee, Shin, Cho, & Shin, 2014; Wartberg et al., 2016), as well as many scientific works presenting evidence for meaningful links between adolescent emotion dysregulation and emotional disorders (Berking & Wupperman, 2012; Dvir, Ford, Hill, & Frazier, 2014). Emotion dysregulation is often associated with emotional disorders and other mental health symptoms (Hofmann et al., 2012). A previous study by Sloan et al. (2017) concluded that difficulties in emotion regulation are central to the development and maintenance of psychopathology and that emotion dysregulation is the common feature across depressive, anxiety, substance use, and eating disorders, and also borderline personality disorder. This is consistent with observations from cross-cultural personality, providing evidence for links between higher self-directedness (linked to higher conscientiousness/self-regulation abilities) and lower tendencies towards problematic Internet use (Sariyska et al., 2014). In conclusion, the here reviewed studies suggest that the “adolescent emotion dysregulation – problematic technology use” may also be related to other important variables such as personality dispositions or behavioral problems.
The relationship between adolescent ED and PTU: a theoretical perspective
In line with the here observed association patterns, psychological theories suggest that (adolescent) emotion dysregulation plays an important role in problematic technology use (Brand et al., 2016; Kardefelt-Winther, 2014). According to CIUT (Kardefelt-Winther, 2014), people are motivated to use the Internet when they experience adversity and stress. Drawing inspiration from this theory, problematic technology use can be sometimes regarded as an acceptable coping style or a form of self-healing. We are of the opinion, that being in a state of problematic technology use for a longer period can itself have a negative impact on a person's life (Kardefelt-Winther, 2014). In our context, problematic technology use itself can cause harm to those affected. Of interest for the present work: Negative life situations (such as stress) are closely related to emotion dysregulation and emotional disorders (Cavalli & Cservenka, 2021; Schneider, Long, Arch, & Hankin, 2021). This may explain why adolescent emotion dysregulation is closely related to their problematic technology use, and emotion dysregulation may even be a predictor of adolescent problematic technology use, but this hypothesis needs to be supported by longitudinal research.
The I-PACE model proposes that an Interaction of Person-Affect-Cognition-Execution variables is of relevance to understanding problematic technology use (Brand et al., 2016, 2019). In the P- variable, some characteristics of the individual (such as emotional disorders and emotion dysregulation) affect the individual problematic technology use. Specifically, the individual's emotional maladaptation coping styles and cognitive processing, which led to addictive behaviors. Regarding the A- and C- variables the model indicates that individual Internet-related cognitive biases and coping styles in many instances can be conceptualized as moderating variables, which may affect the relationship between predisposing factors (person variables) and tendencies towards problematic technology use. The model also states that in other cases, individual differences in coping style and cognitive biases can represent a mediating variable. Thus, almost all studies in this review could be therefore seen as supportive of the I-PACE model's hypotheses.
The relationship between adolescent ED and PTU: distress intolerance and impulsivity
To our knowledge, no study directly explored the relationship between adolescent distress intolerance, emotion dysregulation, and problematic technology use in one single design (in particular not in the 39 reviewed studies), but many studies have revealed at least pairwise relationships in adolescents (Akbari, 2017; Juarascio et al., 2020). But it is worth noting that, emotion dysregulation is usually related to individuals' distress intolerance and impulsivity (Naragon-Gainey, McMahon, & Chacko, 2017), which are closely related to individual differences in predisposition to addictive behaviors (Akbari, 2017; Vinayak & Malhotra, 2017). Distress tolerance is defined as the ability to tolerate emotional distress (Leyro, Zvolensky, & Bernstein, 2010), and it consists of several appraisals of experiencing negative emotions: tolerability, perception of acceptability, attentional interference, and regulation of the emotion. Distress tolerance can influence the specific type of emotion regulation (or dysregulation) strategy used (Simons & Gaher, 2005). Future studies could investigate the role of distress (in)tolerance regarding the relationship between adolescent emotion dysregulation and problematic technology use, which may further elucidate the aforementioned relationship between emotion dysregulation and problematic technology use.
As stated at the beginning of this article, during adolescence, people may exhibit more emotional and impulsive behaviors (Cyders & Smith, 2008). Compared to children or adults, adolescents tend to experience greater emotional volatility (Larson & Richards, 1994), including increases in the rates of rash action, especially when experiencing intense emotions (Arnett, 1992; Luna & Sweeney, 2004; Steinberg, 2004). Of note, similar to distress intolerance, the here reviewed studies (see Table 1) did not discuss the role of impulsivity regarding the association between emotion dysregulation and problematic technology use in adolescents. This said emotion dysregulation includes the concept of impulse control difficulties (Yu, Kim, & Hay, 2013). Impulsivity, which can be also considered as a personality trait of relevance in adolescents, may also have an impact on their emotion dysregulation and problematic technology use tendencies (see P- variable in the I-PACE model).
Strengths and limitations of existing research
The existing research mostly could verify the close association between emotion dysregulation and problematic technology use by adolescents. Beyond the clear evidence, it should be noted that the methodology of the available research is self-reported, which represents a limitation. In the future, the relationship between these two variables (especially causality) should be better explored, by also using longitudinal approaches or by psychological experiments.
The research subjects included in this review were from countries such as Turkey, Italy, China, and USA, etc., in so far results of these studies illustrate the cross-cultural consistency between emotion dysregulation and problematic technology use of adolescents. Despite this, many areas of the world have not been covered so far and this represents a limitation.
Finally, some of the reviewed literature showed that adolescent emotion dysregulation seems to be closely related to impulsivity and distress intolerance, and problematic technology use is also strongly related to the latter two variables. However, the variables of impulsivity and distress tolerance are still understudied in the realm of the present overarching research topic (ED and PTU), which shows that the internal mechanisms between emotion dysregulation and problematic technology use still need to be further explored. In this context we also mention that the construct of ED has many facets and constructs such as alexithymia and interoceptive awareness would be interesting research avenues.
Future research directions
In conducting the literature search for the present systematic review, we also found some studies investigating the relationship between emotion dysregulation and problematic technology use severity in adults and older adults, hence not adolescents (Blasi et al., 2019; Marino et al., 2019). The findings of these studies are consistent with those investigating adolescents only: Emotion dysregulation is positively correlated with problematic technology use severity. Therefore, the studies taken together suggest that the associations between emotion dysregulation and problematic technology use are stable from adolescence onwards, but again this needs to be supported by longitudinal studies. Beyond this, we believe it is also of high importance to investigate the underlying neurobiology regarding emotion dysregulation and problematic technology use (a topic that did not turn up in the papers of the present systematic review).
However, many studies have shown that emotion dysregulation and problematic technology use are related to PFC (prefrontal cortex) function in adolescents (Ball, Ramsawh, Campbell-Sills, Paulus, & Stein, 2012; Beauchaine, 2015b; Chia-Jui, Lin, Tseng, & Gau, 2020; Li et al., 2015). PFC is closely related to individual inhibitory control function. Adolescence is characterized by reduced PFC activity, which may lead to difficulties in inhibiting impulses, weighing the consequences of decisions, prioritizing, and strategizing among adolescents (Luna & Sweeney, 2004). The implication of the incomplete PFC development and incomplete brain integration is that adolescents' ability to engage in affect-guided planning, inhibit impulses, and consider consequences before acting, is less consistent than that of adults. It appears to be particularly true that adolescents appear less able to consider consequences, to plan, and to inhibit actions in “hot” situations, that is, in states of heightened emotionality (Luna & Sweeney, 2004; Steinberg, 2004). Indeed, it has been reported that 80% of 11.5- to 15-year-olds exhibited one or more reckless behavior(s) during the preceding month (Arnett, 1992; Moffitt, 1993). These studies indicate that the close relationship between adolescent emotion dysregulation and problematic technology use may be due to the still-developing PFC (and its interaction with other brain regions). Interacting brain areas in the still developing brain being also of relevance for the construct of ED logically could be subcortical brain areas, where emotional urges arise when being confronted with rewarding technology use. For instance, Sherman, Payton, Hernandez, Greenfield, and Dapretto (2016) observed that their study participants being confronted with more compared to fewer Likes as a reaction to their photos responded with higher activity of the reward circuitry of the brain, perhaps better labeled as the SEEKING system (see also Pankseppian Affective Neuroscience Theory, Davis & Montag, 2019). Hence emotional dysregulation patterns are likely not only a result by a dysregulated PFC, but can be characterized by the interplay of strong subcortical emotional signal, being insufficiently downregulated by the PFC (see also Becker & Montag, 2019; Montag, Duke, & Reuter, 2017).
It is also worth noting that in our review, problematic technology use can be divided into generalized technology use and content-based technology use, although emotion dysregulation in adolescents is significantly and positively associated with problematic behavior in both categories. However, due to the different mechanisms of different categories of problematic technology use, potential influences of adolescent emotion dysregulation on their problematic technology use may differ (see also that for instance different social media platforms might elicit different addictive potential, Rozgonjuk, Sindermann, Elhai, and Montag (2021), due to different platform design, Montag, Lachmann, Herrlich, and Zweig (2019)). In sum, it might be worthy to systematically re-investigate associations between ED and PTU in different areas of technology use.
Conclusion
This systematic review provides evidence for a positive association between adolescent emotion dysregulation and the severity of problematic technology use (including generalized and content-based technology use). The review also showed that the relationship between these two variables in adolescents seems to be robust, regardless of whether subclinical or clinical groups were investigated. In the review of the literature it became apparent, that the simple-sounding correlation is influenced by many variables, including diverse metacognitions or psychological flexibility. However, despite the close correlation between ED and PTU, Donald, Ciarrochi, and Sahdra (2020) considered that teaching adolescents general emotion regulation skills may not be as effective in reducing problematic Internet use as more direct approaches of limiting the use of the internet. Therefore, improving ED alone may not be sufficient to reduce the severity of their problematic technology use. Perhaps the largest problem of the field is that studies investigating causal mechanisms are scarce until now.
Funding sources
This study received a grant from the Tianjin Key Project of philosophy and Social Sciences (TJJX21-001).
Authors’ contribution
Study concept and design HY. Analysis and interpretation of data: HY & ZW. Drafting the manuscript: HY & ZW. Revised the manuscript: HY, JDE & CM. Final edition: HY, ZW, JDE & CM have read and edited the final version of the study. Approval of the version of the manuscript to be published: HY, ZW, JDE & CM.
Conflict of interest
All authors declare that they have no conflicts of interest with this study. However, outside the scope of the present paper, the authors report the following: HY notes that he is a paid full-time faculty member at Tianjin Normal University. ZW notes that he is a doctoral student at Tianjin Normal University. JDE notes that he is a paid, full-time faculty member at University of Toledo and has received grant research funding from the U.S. National Institutes of Health. CM notes that he is a paid, full-time faculty member at Ulm University.
References
Akbari, M. (2017). Metacognitions or distress intolerance: The mediating role in the relationship between emotional dysregulation and problematic internet use. Addictive Behaviors Reports, 6, 128–133. https://doi.org/10.1016/j.abrep.2017.10.004.
Amendola, S. , Spensieri, V. , Biuso, G. S. , & Cerutti, R. (2020). The relationship between maladaptive personality functioning and problematic technology use in adolescence: A cluster analysis approach. Scandinavian Journal of Psychology, 61(6), 809–818. https://doi.org/10.1111/sjop.12664.
Amendola, S. , Spensieri, V. , Guidetti, V. , & Cerutti, R. (2019). The relationship between difficulties in emotion regulation and dysfunctional technology use among adolescents. Journal of Psychopathology, 25, 10–17. https://www.jpsychopathol.it/wp-content/uploads/2018/12/xx_Cerutti_epub.pdf.
Anita, V. , András, L. , & Bernadette, P. (2014). [Investigation of the compulsive and impulsive behavioral addictions among adolescents. Psychiatria Hungarica, 29(2). https://www.researchgate.net/publication/264091688.
Arnett, J. (1992). The soundtrack of recklessness: Musical preferences and reckless behavior among adolescents. Journal of Adolescent Research, 7(3), 313–331. https://doi.org/10.1177/074355489273003.
Austermann, M. I. , Thomasius, R. , & Paschke, K. (2021). Assessing problematic social media use in adolescents by parental ratings: Development and validation of the social media disorder Scale for parents (SMDS-P). Journal of Clinical Medicine, 10, 617. https://doi.org/10.3390/jcm10040617.
Ball, T. M. , Ramsawh, H. J. , Campbell-Sills, L. , Paulus, M. P. , & Stein, M. B. (2012). Prefrontal dysfunction during emotion regulation in generalized anxiety and panic disorders. Psychological Medicine, 43(7), 1475–1486. https://doi.org/10.1017/S0033291712002383.
Beauchaine, T. P. (2015a). Future directions in emotion dysregulation and youth psychopathology. Journal of Clinical Child and Adolescent Psychology, 44, 875–896. https://doi.org/10.1080/15374416.2015.1038827.
Beauchaine, T. P. (2015b). Respiratory sinus arrhythmia: A transdiagnostic biomarker of emotion dysregulation and psychopathology. Current Opinion in Psychology, 3, 43–47. https://doi.org/10.1016/j.copsyc.2015.01.017.
Becker, B. , & Montag, C. (2019). Psychological and neuroscientific advances to understand Internet use disorder. Neuroforum, 25(2), 99–107. https://doi.org/10.1515/nf-2018-0026.
Bentley, K. H. , Cassiello-Robbins, C. F. , Vittorio, L. , Sauer-Zavala, S. , & Barlow, D. H. (2015). The association between nonsuicidal self-injury and the emotional disorders: A meta-analytic review. Clinical Psychology Review, 37, 72–88. https://doi.org/10.1016/j.cpr.2015.02.006.
Berking, M. , & Wupperman, P. (2012). Emotion regulation and mental health: Recent findings, current challenges, and future directions. Current Opinion in Psychiatry, 25(2), 128–134. https://doi.org/10.1097/YCO.0b013e3283503669.
Bjureberg, J. , Sahlin, H. , Hedman-Lagerlöf, E. , Gratz, K. L. , Tull, M. T. , Jokinen, J. , et al. (2018). Extending research on emotion regulation individual therapy for adolescents (ERITA) with nonsuicidal self-injury disorder: Open pilot trial and mediation analysis of a novel online version. BMC Psychiatry, 18(1), 326. https://doi.org/10.1186/s12888-018-1885-6.
Blasi, M. D. , Giardina, A. , Giordano, C. , Coco, G. L. , Tosto, C. , Billieux, J. , et al. (2019). Problematic video game use as an emotional coping strategy: Evidence from a sample of MMORPG gamers. Journal of Behavioral Addictions, 8(1), 25–34. https://doi.org/10.1556/2006.8.2019.02.
Bonnaire, C. , & Baptista, D. (2019). Internet gaming disorder in male and female young adults: The role of alexithymia, depression, anxiety and gaming type. Psychiatry Research, 272, 521–530. https://doi.org/10.1016/j.psychres.2018.12.158.
Bozkurt, H. , Coskun, M. , Ayaydin, H. , Adak, I. , & Zoroglu, S. S. (2013). Prevalence and patterns of psychiatric disorders in referred adolescents with Internet addiction. Psychiatry and Clinical Neurosciences, 67(5), 352–359. https://doi.org/10.1111/pcn.12065.
Brand, M. , Wegmann, E. , Stark, R. , Müller, A. , Wölfling, K. , Robbins, T. W. , et al. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience and Biobehavioral Reviews, 104, 1–10. https://doi.org/10.1016/j.neubiorev.2019.06.032.
Brand, M. , Young, K. S. , Laier, C. , Wölfling, K. , & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience and Biobehavioral Reviews, 71, 252–266. https://doi.org/10.1016/j.neubiorev.2016.08.033.
Carl, J. R. , Soskin, D. P. , Kerns, C. , & Barlow, D. H. (2013). Positive emotion regulation in emotional disorders: A theoretical review. Clinical Psychology Review, 33, 343–360. https://doi.org/10.1016/j.cpr.2013.01.003.
Casale, S. , Caplan, S. , & Fioravanti, G. (2016). Positive metacognitions about Internet use: The mediating role in the relationship between emotional dysregulation and problematic use. Addictive Behaviors, 59, 84–88. https://doi.org/10.1016/j.addbeh.2016.03.014.
Cavalli, J. M. , & Cservenka, A. (2021). Emotion dysregulation moderates the association between stress and problematic cannabis use. Frontiers in Psychiatry, 11. https://doi.org/10.3389/fpsyt.2020.597789.
Chang, C. H. , Chang, Y. C. , Cheng, H. , & Tzang, R. F. (2020). Treatment efficacy of internet gaming disorder with attention deficit hyperactivity disorder and emotional dysregulation. The International Journal of Neuropsychopharmacology, 23(6), 349–355. https://doi.org/10.1093/ijnp/pyaa010.
Chia-Jui, T. , Lin, H. Y. , Tseng, I. W. , & Gau, S. S. (2020). Brain voxel-based morphometry correlates of emotion dysregulation in attention-deficit hyperactivity disorder. Brain Imaging and Behavior, 15, 1388–1402. https://doi.org/10.1007/s11682-020-00338-y.
Chun, J. (2016). Effects of psychological problems, emotional dysregulation, and self-esteem on problematic Internet use among Korean adolescents. Children and Youth Services Review, 68, 187–192. https://doi.org/10.1016/j.childyouth.2016.07.005.
Coco, G. L. , Salerno, L. , Franchina, V. , Tona, A. L. , Blasi, M. D. , & Giordano, C. (2020). Examining bi-directionality between Fear of Missing Out and problematic smartphone use. A two-wave panel study among adolescents. Addictive Behaviors, 106, 106360. https://doi.org/10.1016/j.addbeh.2020.106360.
Cyders, M. A. , & Smith, G. T. (2008). Emotion-based dispositions to rash action: Positive and negative urgency. Psychological Bulletin, 134(6), 807–828. https://doi.org/10.1037/a0013341.
Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17, 187–195. https://doi.org/10.1016/S0747-5632(00)00041-8.
Davis, K. L. , & Montag, C. (2019). Selected principles of Pankseppian affective neuroscience. Frontiers in Neuroscience, 12, 1025. https://doi.org/10.3389/fnins.2018.01025.
Domoff, S. E. , Sutherland, E. Q. , Yokum, S. , & Gearhardt, A. N. (2020). Adolescents’ addictive phone use: Associations with eating behaviors and adiposity. International Journal of Environmental Research and Public Health, 17, 2861. https://doi.org/10.3390/ijerph17082861.
Donald, J. N. , Ciarrochi, J. , & Sahdra, B. K. (2020). The consequences of compulsion: A 4-year longitudinal study of compulsive internet use and emotion regulation difficulties. Emotion. https://doi.org/10.1037/emo0000769.
Donald, J. N. , Ciarrochi, J. , & Sahdra, B. K. (2020). The consequences of compulsion: A 4-year longitudinal study of compulsive internet use and emotion regulation difficulties. Emotion. https://doi.org/10.1037/emo0000769.
Dvir, Y. , Ford, J. D. , Hill, M. , & Frazier, J. A. (2014). Childhood maltreatment, emotional dysregulation, and psychiatric comorbidities. Harvard Review of Psychiatry, 22(3), 149–161. https://doi.org/10.1097/HRP.0000000000000014.
Elhai, J. D. , Yang, H. , & Levine, J. C. (2021). Applying fairness in labeling various types of internet use disorders.•: Commentary on How to overcome taxonomical problems in the study of internet use disorders and what to do with “smartphone addiction”? Journal of Behavioral Addictions, 9(4), 924–927. https://doi.org/10.1556/2006.2020.00071.
Estévez, A. , Jáuregui, P. , Lopez-Gonzalez, H. , Macia, L. , Granero, R. , Mestre-Bach, G. , et al. (2020). Comorbid behavioral and substance-related addictions in young population with and without gambling disorder. International Gambling Studies. https://doi.org/10.1080/14459795.2020.1836250.
Estévez, A. , Jáuregui, P. , Sánchez-Marcos, I. , López-González, H. , & Griffiths, M. D. (2017). Attachment and emotion regulation in substance addictions and behavioral addictions. Journal of Behavioral Addictions, 6(4), 534–544. https://doi.org/10.1556/2006.6.2017.086.
Evren, B. , Evren, C. , Dalbudak, E. , Topcu, M. , & Kutlu, N. (2018). Relationship of Internet addiction severity with probable ADHD and difficulties in emotion regulation among young adults. Psychiatry Research, 269. https://doi.org/10.1016/j.psychres.2018.08.112.
Evren, C. , Evren, B. , Dalbudak, E. , Topcu, M. , Kutlu, N. , & Elhai, J. D. (2019). Severity of dissociative experiences and emotion dysregulation mediate the relationship between childhood trauma and Internet addiction symptom severity among young adults. Neurological Sciences, 32, 334. https://doi.org/10.14744/DAJPNS.2019.00048.
Fabris, M. A. , Marengo, D. , Longobardi, C. , & Settanni, M. (2020). Investigating the links between fear of missing out, social media addiction, and emotional symptoms in adolescence: The role of stress associated with neglect and negative reactions on social media. Addictive Behaviors, 106, 106304. https://doi.org/10.1016/j.addbeh.2020.106364.
Faghani, N. , Akbari, M. , Hasani, J. , & Marino, C. (2019). An emotional and cognitive model of Problematic Internet Use among college students: The Full mediating role of cognitive factors. Addictive Behaviors. https://doi.org/10.1016/j.addbeh.2019.106252.
Gioia, F. , Rega, V. , & Boursier, V. (2021). Problematic internet use and emotional dysregulation among young people: A literature review. Clinical Neuropsychiatry, 18(1), 41–54. https://doi.org/10.36131/CNFIORITIEDITORE20210104.
Giordano, C. , Coco, G. L. , Salemo, L. , & Biasi, M. D. (2020). The role of emotion dysregulation in adolescents’ problematic smartphone use: A study on adolescent/parents triads. Computers in Human Behavior, 115, 106632. https://doi.org/10.1016/j.chb.2020.106632.
Gratz, K. L. , & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation Scale. Journal of Psychopathology and Behavioral Assessment, 26, 41–54. https://doi.org/10.1023/B:JOBA.0000007455.08539.94.
Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271.
Gross, J. J. (2008). Handbook of emotion regulation. London: Guilford.
Gross, J. J. , & Jazaieri, H. (2014). Emotion, emotion regulation, and psychopathology: An affective science perspective. Clinical Psychological Science, 2, 387–401. https://doi.org/10.1177/2167702614536164.
Gül, H. , Fırat, S. , Sertçelik, M. , Gül, A. , Gürel, Y. , & Kılıç, B. G. (2019). Cyberbullying among a clinical adolescent sample in Turkey: Effects of problematic smartphone use, psychiatric symptoms, and emotion regulation difficulties. Psychiatry and Clinical Psychopharmacology, 29(4), 547–557. https://doi.org/10.1080/24750573.2018.1472923.
Günaydın, N. , Arıcı, Y. K. , Kutlu, F. Y. , & Demir, E. Y. (2021). The relationship between problematic Internet use in adolescents and emotion regulation difficulty and family Internet attitude. Journal of Community Psychology, 50(2), 1135–1154. https://doi.org/10.1002/jcop.22708.
Gutiérrez, A. E. , Fernández, D. H. , Gonzalvo, I. S. , & Bilbao, J. (2014). Mediating role of emotional regulation between impulsive behavior in gambling, Internet and videogame abuse, and dysfunctional symptomatology in young adults and adolescents. Adicciones, 26(4). https://pubmed.ncbi.nlm.nih.gov/25577999/.
Hofmann, S. G. , Sawyer, A. T. , Fang, A. , & Asnaani, A. (2012). Emotion dysregulation model of mood and anxiety disorders. Depression and Anxiety, 29(5), 409–416. https://doi.org/10.1002/da.21888.
Hormes, J. M. , Kearns, B. , & Timko, C. A. (2014). Craving facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits. Addiction, 109(12), 79–88. https://doi.org/10.1111/add.12713.
Huang, H. Y. , & Leung, L. (2009). Instant messaging addiction among teenagers in China: Shyness, alienation, and academic performance decrement. Cyberpsychology & Behavior, 12(6). https://doi.org/10.1089/cpb.2009.0060.
Hussain, Z. , Wegmann, E. , Yang, H. , & Montag, C. (2020). Social networks use disorder and associations with depression and anxiety symptoms: A systematic review of recent research in China. Frontiers in Psychology, 11, 211. https://doi.org/10.3389/fpsyg.2020.00211.
Juarascio, A. , Manasse, S. , Clark, K. E. , Schaumberg, K. , Kerrigan, S. , Goldstein, S. P. , et al. (2020). Understanding the overlap and differences in terms describing patterns of maladaptive avoidance and intolerance of negative emotional states. Personality and Individual Differences, 158. https://doi.org/10.1016/j.paid.2020.109859.
Kafali, H. Y. , Uçaktürk, S. A. , Mengen, E. , Akpinar, S. , Demirtas, M. E. , & Uneri, O. S. (2020). Emotion dysregulation and pediatric obesity: Investigating the role of internet addiction and eating behaviors on this relationship in an adolescent sample. Eat Weight Ddisord, 26, 1767–1779. https://doi.org/10.1007/s40519-020-00999-0.
Karaer, Y. , & Akdemir, D. (2019). Parenting styles, perceived social support and emotion regulation in adolescents with internet addiction. Comprehensive Psychiatry, 92, 22–27. https://doi.org/10.1016/j.comppsych.2019.03.003.
Kardefelt-Winther, D. (2014). A conceptual and methodological critique of Internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–355. http://doi.org/10.1016/j.chb.2013.10.059.
Karma, T. , Thinley, D. , Tshering, C. , Phuntsho, W. , Minn, O. M. , Prasad, T. J. , et al. (2019). Internet addiction among secondary school adolescents: A mixed methods study. JNMA; Journal of the Nepal Medical Association(219), 344–351. https://doi.org/10.31729/jnma.4292.
Kim, S. , & Chun, J. (2016). Structural model of parent-adolescent communication, depression-anxiety, emotion dysregulation, and internet addiction among adolescents. Journal of Youth Welfare, 18(1), 159–183. http://doi.org/10.19034/KAYW.2016.18.1.07.
Larson, R. W. , & Richards, M. H. (1994). Family emotions: Do young adolescents and their parents experience the same states? Journal of Research on Adolescence, 4, 567–583. http://doi.org/10.1207/s15327795jra0404_8.
Lee, J. Y. , Shin, K. M. , Cho, S. , & Shin, Y. M. (2014). Psychosocial risk factors associated with internet addiction in Korea. Psychiatry Investigation, 11(4), 380–386. http://doi.org/10.4306/pi.2014.11.4.380.
Lemaigre, C. , & Taylor, E. P. (2019). Mediators of childhood trauma and suicidality in a cohort of socio-economically deprived Scottish men. Child Abuse & Neglect, 88, 159–170. https://doi.org/10.1016/j.chiabu.2018.11.013.
Leyro, T. M. , Zvolensky, M. J. , & Bernstein, A. (2010). Distress tolerance and psychopathological symptoms and disorders: A review of the empirical literature among adults. Psychological Bulletin, 136(4), 576–600. https://doi.org/10.1037/a0019712.
Liese, B. S. , Kim, H. S. , & Hodgins, D. C. (2020). Insecure attachment and addiction: Testing the mediating role of emotion dysregulation in four potentially addictive behaviors. Addictive Behaviors, 107, 106432. https://doi.org/10.1016/j.addbeh.2020.106432.
Li, W. W. , Li, Y. D. , Yang, W. J. , Wei, D. T. , Li, W. F. , Hitchman, G. , et al. (2015). Brain structures and functional connectivity associated with individual differences in Internet tendency in healthy young adults. Neuropsychologia, 70, 134–144. https://doi.org/10.1016/j.neuropsychologia.2015.02.019.
Love, H. , May, R. W. , Shafer, J. , Fincham, F. D. , & Cui, M. (2022). Overparenting, emotion dysregulation, and problematic internet use among female emerging adults. Journal of Applied Developmental Psychology, 79, 101376. https://doi.org/10.1016/j.appdev.2021.101376.
Luna, B. , & Sweeney, J. A. (2004). The emergence of collaborative brain function: fMRI studies of the development of response inhibition. Annals of the New York Academy of Sciences, 1021, 296–309. https://doi.org/10.1196/annals.1308.035.
Mancinelli, E. , Sharka, O. , Lai, T. , Sgaravatti, E. , & Salcuni, S. (2021). Self-injury and Smartphone Addiction: Age and gender differences in a community sample of adolescents presenting self-injurious behavior. Health Psychology Open, 8(2). https://doi.org/10.1177/20551029211038811.
Marchica, L. A. , Mills, D. J. , Keough, M. T. , & Derevensky, J. L. (2020). Exploring differences among video gamers with and without depression: Contrasting emotion regulation and mindfulness. Cyberpsychology, Behavior, and Social Networking. https://doi.org/10.1089/cyber.2019.0451.
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. The Psychiatric Quarterly, 90(2), 405–411. https://doi.org/10.1007/s11126-019-09628-1.
McLaughlin, K. A. , Hatzenbuehler, M. L. , Mennin, D. S. , & Nolen-Hoeksema, S. (2011). Emotion dysregulation and adolescent psychopathology: A prospective study. Behaviour Research and Therapy, 49, 544–554. https://doi.org/10.1016/j.brat.2011.06.003.
Michel, G. , Heuzey, M. F. L. , Purper-Ouakil, D. , & Mouren-Simeoni, M. C. (2001). Recherche de sensations et conduites a risque chez l'adolescent [Sensations seeking and risk behavior among adolescents]. Annales Medico Psychologiques, 159, 708–716. https://doi.org/10.1016/S0003-4487(01)00123-8.
Mo, P. K. H. , Chan, V. W. Y. , Chan, S. W. , & Lau, J. T. F. (2018). The role of social support on emotion dysregulation and internet addiction among Chinese adolescents: A structural equation model. Addictive Behaviors, 82, 86–93. https://doi.org/10.1016/j.addbeh.2018.01.027.
Moffitt, T. (1993). Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy. Psychological Review, 100, 674–701. https://doi.org/10.1037/0033-295X.100.4.674.
Moher, D. , Liberati, A. , Tetzlaff, J. , & Altman, D. G. (2010). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery, 5, 336–341. https://doi.org/10.1016/j.ijsu.2010.02.007.
Montag, C. , Bey, K. , Sha, P. , Li, M. , Chen, Y. F. , Liu, W. Y. , et al. (2015). Is it meaningful to distinguish between generalized and specific internet addiction? Evidence from a cross-cultural study. Asia-Pacific Psychiatry, 7, 20–26. https://doi.org/10.1111/appy.12122.
Montag, C. , Duke, É. , & Reuter, M. (2017). A short summary of neuroscientific findings on Internet addiction. Internet addiction (pp. 209–218). Cham: Springer.
Montag, C. , & Elhai, J. D. (2020). Discussing digital technology overuse in children and adolescents during the COVID-19 pandemic and beyond: On the importance of considering Affective Neuroscience Theory. Addictive Behaviors Reports, 12, 100313. https://doi.org/10.1016/j.abrep.2020.100313.
Montag, C. , Lachmann, B. , Herrlich, M. , & Zweig, K. (2019). Addictive features of social media/messenger platforms and freemium games against the background of psychological and economic theories. International Journal of Environmental Research and Public Health, 16(14), 2612. https://doi.org/10.3390/ijerph16142612.
Montag, C. , & Panksepp, J. (2017). Primary emotional systems and personality: An evolutionary perspective. Frontiers in Psychology, 8, 464. https://doi.org/10.3389/fpsyg.2017.00464.
Montag, C. , Wegmann, E. , Sariyska, R. , Demetrovics, Z. , & Brand, M. (2021). How to overcome taxonomical problems in the study of Internet use disorders and what to do with “smartphone addiction”? Journal of Behavioral Addictions, 9(4), 908–914. https://doi.org/10.1556/2006.8.2019.59.
Müller, T. , & Bonnaire, C. (2020). Intrapersonal and interpersonal emotion regulation and identity: A preliminary study of avatar identification and gaming in adolescents and young adults. Psychiatry Research. https://doi.org/10.1016/j.psychres.2020.113627.
Naragon-Gainey, K. , McMahon, T. P. , & Chacko, T. P. (2017). The structure of common emotion regulation strategies: A meta-analytic examination. Psychological Bulletin, 143(4), 384–427. https://doi.org/10.1037/bul0000093.
Paschke, K. , Austermann, M. I. , & Thomasius, R. (2021). Assessing ICD-11 gaming disorder in adolescent gamers by parental ratings: Development and validation of the Gaming Disorder Scale for Parents (GADIS-P). Journal of Behavioral Addictions, 10(1), 150–168. https://doi.org/10.1556/2006.2020.00105.
Peterka-Bonetta, J. , Sindermann, C. , Sha, P. , Zhou, M. , & Montag, C. (2019). The relationship between Internet Use Disorder, depression and burnout among Chinese and German college students. Addictive Behaviors, 89, 188–199. https://doi.org/10.1016/j.addbeh.2018.08.011.
Pettorruso, M. , Valle, S. , Cavic, E. , Martinotti, G. , Giannantonio, M. d. , & Grant, J. E. (2020). Problematic internet use (PIU), personality profiles and emotion dysregulation in a cohort of young adults: Trajectories from risky behaviors to addiction. Psychiatry Research, 289. https://doi.org/10.1016/j.psychres.2020.113036.
Phillips, K. F. V. , & Power, M. J. (2007). A new self-report measure of emotion regulation in adolescents: The Regulation of Emotions Questionnaire. Clinical Psychology & Psychotherapy, 14, 145–156. https://doi.org/10.1002/cpp.523.
Pozuelo, J. R. , Desborough, L. , Stein, A. , & Cipriani, A. (2021). Systematic review and meta-analysis: Depressive symptoms and risky behaviors among adolescents in low- and middle-income countries. Journal of the American Academy of Child and Adolescent Psychiatry. https://doi.org/10.1016/j.jaac.2021.05.005.
Qi, W. X. (2019). Parental conflict and problematic internet use in Chinese adolescents: Testing a moderated mediation model of adolescents' effortful control and emotional dysregulation. Journal of Interpersonal Violence, 1–17. https://doi.org/10.1177/0886260518822342.
Richardson, M. , Hussain, Z. , & Griffiths, M. D. (2018). Problematic smartphone use, nature connectedness, and anxiety. Journal of Behavioral Addictions, 7(1), 109–116. https://doi.org/10.1556/2006.7.2018.10.
Rozgonjuk, D. , Sindermann, C. , Elhai, J. D. , & Montag, C. (2021). Comparing smartphone, WhatsApp, facebook, instagram, and snapchat: Which platform elicits the greatest use disorder symptoms? Cyberpsychology, Behavior, and Social Networking, 24(2), 129–134. https://doi.org/10.1089/cyber.2020.0156.
Sanchis-Sanchis, A. , Grau, M. D. , Moliner, A. , & Morales-Murillo, C. P. (2020). Effects of age and gender in emotion regulation of children and adolescents. Frontiers in Psychology, 11, 946. https://doi.org/10.3389/fpsyg.2020.00946.
Sariyska, R. , Reuter, M. , Bey, K. , Sha, P. , Li, M. , Chen, Y. F. , …, et al. (2014). Self-esteem, personality and internet addiction: A cross-cultural comparison study. Personality and Individual Differences, 61, 28–33. https://doi.org/10.1016/j.paid.2014.01.001.
Sawyer, S. M. , Azzopardi, P. S. , Wickremarathne, D. , & Patton, G. C. (2018). The age of adolescence. The Lancet Child Adolescence Health. https://doi.org/10.1016/.
Schneider, R. L. , Long, E. E. , Arch, J. J. , & Hankin, B. L. (2021). The relationship between stressful events, emotion dysregulation, and anxiety symptoms among youth: Longitudinal support for stress causation but not stress generation. Anxiety, Stress & Coping, 34(2), 157–172. https://doi.org/10.1080/10615806.2020.1839730.
Sertbaş, K. , Çutuk, S. , Soyer, F. , Çutuk, Z. A. , & Aydoğan, R. (2020). Mediating role of emotion regulation difficulties in the relationship between social anxiety and problematic internet use. Psihologija, 53(3), 291–305. https://doi.org/10.2298/PSI190730013S.
Sherman, L. E. , Payton, A. A. , Hernandez, L. M. , Greenfield, P. M. , & Dapretto, M. (2016). The power of the like in adolescence: Effects of peer influence on neural and behavioral responses to social media. Psychological Science, 27(7), 1027–1035. https://doi.org/10.1177/0956797616645673.
Simons, J. S. , & Gaher, R. M. (2005). The distress tolerance Scale: Development and validation of a self-report measure. Motivation and Emotion, 29(2), 83–102. https://doi.org/10.1007/s11031-005-7955-3.
Sloan, E. , Hall, K. , Moulding, R. , Bryce, S. , Mildred, H. , & Staiger, P. K. (2017). Emotion regulation as a transdiagnostic treatment construct across anxiety, depression, substance, eating and borderline personality disorders: A systematic review. Clinical Psychology Review, 57, 141–163. https://doi.org/10.1016/j.cpr.2017.09.002.
Starosta, j. , Izydorczyk, B. , Sitnik-Warchulska, K. , & Lizinczyk, S. (2021). Impulsivity and difficulties in emotional regulation as predictors of binge-watching behaviours. Frontiers in Psychiatry, 12, 743870. https://doi.org/10.3389/fpsyt.2021.743870.
Steinberg, L. (2004). Risk taking in adolescence: What changes, and why? Annals of the New York Academy of Sciences, 1021, 51–58. https://doi.org/10.1196/annals.1308.005.
Tsai, J. K. , Lu, W. H. , Hsiao, R. C. , Hu, H. F. , & Yen, C. F. (2020). Relationship between difficulty in emotion regulation and internet addiction in college students: A one-year prospective study. International Journal of Environmental Research and Public Health, 17, 4766. https://doi.org/10.3390/ijerph1713476.
Uçur, Ö. , & Dönmez, Y. E. (2021). Problematic internet gaming in adolescents, and its relationship with emotional regulation and perceived social support. Psychiatry Research, 296. https://doi.org/10.1016/j.psychres.2020.113678.
Velotti, P. , Rogier, G. , Beomonte Zobel, S. , & Billieux, J. (2021). Association between gambling disorder and emotion (dys)regulation: A systematic review and meta-analysis. Clinical Psychology Review, 87, 102037. https://doi.org/10.1016/j.cpr.2021.102037.
Vinayak, S. , & Malhotra, M. (2017). Impact of impulsiveness on mobile phone addiction. Indian Journal of Health and Wellbeing, 8(10), 1102–1106.
Wang, M. Z. , & Qi, W. X. (2017). Harsh parenting and problematic Internet use in Chinese adolescents: Child emotional dysregulation as mediator and child forgiveness as moderator. Computers in Human Behavior, 77, 211–219. https://doi.org/10.1016/j.chb.2017.09.005.
Wartberg, L. , Kriston, L. , Kramer, M. , Schwedler, A. , Lincoln, T. M. , & Kammerl, R. (2016). Internet gaming disorder in early adolescence: Associations with parental and adolescent mental health. European Psychiatry, 43, 14–18. https://doi.org/10.1016/j.eurpsy.2016.12.013.
Xu, J. H. , Zhou, Y. , Luo, W. B. , Luo, Y. J. , & Qin, S. Z. (2021). Human developmental cognitive and affective neuroscience: Future-oriented mental health and education. Scientia Sinica(Vitae), 51, 663–678. https://doi.org/10.1360/SSV-2020-0285.
Yıldız, M. A. (2017). Emotion regulation strategies as predictors of internet addiction and smartphone addiction in adolescents. Journal of Educational Sciences & Psychology, 1, 66–78. https://www.researchgate.net/publication/316879025.
Yorulmaz, E. , Civgin, U. , & Yorulmaz, O. (2020). What is the role of emotional regulation and psychological rigidity in the relationship between stress and pathological Internet use? Journal of Psychiatry and Neurological Sciences, 33(1), 71–78. https://doi.org/10.14744/dajpns.2019.00062.
Young, K. S. , Sandman, C. F. , & Craske, M. G. (2019). Positive and negative emotion regulation in adolescence: Links to anxiety and depression. Brain Sciences, 9, 76. https://doi.org/10.3390/brainsci9040076.
Yuan, G. Z. , Elhai, J. D. , & Hall, B. J. (2020). The influence of depressive symptoms and fear of missing out on severity of problematic smartphone use and internet gaming disorder among Chinese young adults: A three-wave mediation model. Addictive Behaviors, 112, 106648. https://doi.org/10.1016/j.addbeh.2020.106648.
Yu, J. J. , Kim, H. , & Hay, I. (2013). Understanding adolescents’ problematic Internet use from a social/cognitive and addiction research framework. Computers in Human Behavior, 29, 2682–2689. https://doi.org/10.1016/j.chb.2013.06.045.
Zhang, Y. X. , Ding, Q. , & Wang, Z. Q. (2020). Why parental phubbing is at risk for adolescent mobile phone addiction: A serial mediating model. Children and Youth Services Review, 121, 105873. https://doi.org/10.1016/j.childyouth.2020.105873.