E-ISSN: 1309-5749 | ISSN: 1018-8681 | Join E-mail List | Contact | Twitter
Problematic smartphone use and mental health problems: current state of research and future directions
1University of Toledo, Department of Psychology, Toledo, Ohio - USA; University of Toledo, Department of Psychiatry, Toledo, Ohio - USA
2Global and Community Mental Health Research Group, Faculty of Social Sciences, University of Macau, Department of Psychology, Taipa, Macao (SAR) - China; Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland - USA
Dusunen Adam Journal of Psychiatry and Neurological Sciences 2019; 32(1): 1-3 DOI: 10.14744/DAJPNS.2019.00001
Full Text PDF

Empirical research on relations between problematic smartphone use (PSU) and mental health problems has made substantial advances in recent years. PSU is a construct involving excessive use of a smartphone, with accompanying functional impairment in everyday life (1). Specifically, what distinguishes PSU from healthy levels of smartphone use are PSU’s maladaptive symptoms resembling substance use disorder criteria. For example, PSU can involve psychological withdrawal when one is unable to use one’s phone (e.g., after battery drain), tolerance for engaging in increasingly greater use to feel satisfied, dangerous use (e.g., when driving), and social/relationship interference from overuse (2).

For several years, research on relations between PSU and psychological constructs have involved two fairly distinct areas. First, one strand of the literature found associations between PSU severity and personality constructs, including small to moderate associations with neuroticism and impulsivity (reviewed in 3). Second, another strand of literature found PSU severity correlated with several psychopathology variables – depression, anxiety, stress, and low self-esteem. In this second strand, the most frequently studied and consistently found associations with PSU severity were for depression (moderate effects), and anxiety severity (small to medium effects) (reviewed in 4, 5).

More recently, the literature on PSU’s relations with mental health has advanced by moving beyond studying traditional correlates such as depression and anxiety. Several additional psychopathology-related variables were recently examined and supported, including behavioral activation (6), rumination and worry (7-9), and emotion dysregulation (10-12). Furthermore, PSU was related to low self-control (13), fear of missing out on rewarding experiences (14-19), and proneness to boredom (20). Many of these newly studied psychopathology-related variables can be considered “transdiagnostic” constructs in that they appear in numerous mental disorders. Such transdiagnostic variables are increasingly important in psychopathology research, as they are involved in the etiology, maintenance, and treatment outcomes for mental disorders (21).

In fact, many of these transdiagnostic psychopathology variables have been examined not only in relation to PSU severity, but also as moderators and mediators between traditional psychopathology variables and PSU. The focus on exploring mechanisms underlying PSU represents another significant advance in research. Theoretical frameworks conceptualize PSU and other forms of problematic internet use (PIU) as coping strategies that people use to regulate negative emotion (22). Because not all individuals with negative affectivity engage in PSU, understanding mechanisms that may account for this relationship is an important area of inquiry.

Studies examining transdiagnostic psychopathology variables as mechanisms of PSU began doing so, perhaps as a result of, or perhaps coincidentally after the development of the Interaction of Person-Affect-Cognition-Execution (I-PACE) theoretical model (23, 24). I-PACE proposes that internet feature use and PIU/PSU are influenced by personal predisposition, including genetic, biological, personality, psychopathology, cognition, and internet use motives. I-PACE also proposes intermediate variables that play an important role in accounting for relations between predisposition and PIU – specifically, affective and cognitive responses such as cognitive and attention bias, internet use expectancies, coping strategies, inhibitory control, and craving. Numerous studies have supported I-PACE in explaining PIU and PSU (e.g., 18,25,26). Thus I-PACE and the associated focus on mechanisms underlying PSU go hand in hand, and are important advances in this area.

We should point out that much of the literature on PSU has measured smartphone use with self-report survey measures. However, research demonstrates that the frequency of smartphone and internet use is typically inaccurately estimated by self-report methodology (27,28). Newer studies have measured smartphone use through objective collection of data through participants’ phone logs (27,29,30), which is an important advance in measuring smartphone use and PSU. Such research practice is becoming more feasible now, as large technology companies are building screen time calculations into their software (31,32). Such measurement can also be used to assess objective phone use by participants over time (29,30). The recent advances in research on PSU are important for this area of study and have a significant impact. We believe that researchers should continue on this trajectory by further examining transdiagnostic psychopathology constructs in relation to PSU and focusing on mechanisms between psychopathology and PSU. Research should continue objective measurement of smartphone use using repeated measures designs, with more fine-grained analysis of various features of smartphone use. We also believe that new advances in research on PSU should be attempted at this time. First, few studies have used person-centered or mixture modeling analyses to examine smartphone use or PSU (7,33). Such investigation can elucidate diverse subtypes of smartphone users based on their ways of interacting with the device. Additionally, network analysis is a method increasingly used to examine covariation between symptoms of psychopathology constructs (34) but has not yet been applied to smartphone research. Mobile sensing studies and ecological momentary assessment studies can also advance our understanding of the association between PSU and psychopathology. Finally, advances in machine learning can be applied to a better detection of PSU based on smartphone use data (35).


1.Billieux J, Maurage P, Lopez-Fernandez O, Kuss DJ, Griffiths MD. Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research. Curr Addict Rep 2015; 2:156-162.

2.De-Sola Gutierrez J, Rodriguez de Fonseca F, Rubio G. Cell-phone addiction: a review. Front Psychol 2016; 7:175.

3.Carvalho LF, Sette CP, Ferrari BL. Problematic smartphone use relationship with pathological personality traits: systematic review and meta-analysis. Cyberpsychology (Brno) 2018; 12:5. https://doi.org/10.5817/CP2018-3-5.

4.Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: a conceptual overview and systematic review of relations with anxiety and depression psychopathology. J Affect Disord 2017; 207:251-259.

5.Elhai JD, Levine JC, Hall BJ. The relationship between anxiety symptom severity and problematic smartphone use: a review of the literature and conceptual frameworks. J Anxiety Disord 2019; 62:45-52.

6.Kim Y, Jeong JE, Cho H, Jung DJ, Kwak M, Rho MJ, Yu H, Kim DJ, Choi IY. Personality factors predicting smartphone addiction predisposition: behavioral inhibition and activation systems, impulsivity, and self-control. PLoS One 2016; 11:e0159788.

7.Elhai JD, Rozgonjuk D, Yildirim C, Alghraibeh AM, Alafnan AA. Worry and anger are associated with latent classes of problematic smartphone use severity. J Affect Disord 2019; 246:209-216.

8.Elhai JD, Tiamiyu MF, Weeks JW. Depression and social anxiety in relation to problematic smartphone use: the prominent role of rumination. Internet Research 2018; 28:315-332.

9.Liu QQ, Zhou ZK, Yang XJ, Kong FC, Niu GF, Fan CY. Mobile phone addiction and sleep quality among Chinese adolescents: a moderated mediation model. Comput Human Behav 2017; 72:108-114.

10.Elhai JD, Levine JC, O’Brien KD, Armour C. Distress tolerance and mindfulness mediate relations between depression and anxiety sensitivity with problematic smartphone use. Comput Human Behav 2018; 84:477-484.

11.Gul H, Firat S, Sertcelik M, Gul A, Gurel Y, Kilic BG. Cyberbullying among a clinical adolescent sample in Turkey: effects of problematic smartphone use, psychiatric symptoms, and emotion regulation difficulties. Psychiatry and Clinical Psychopharmacology 2018 (in pres). https://doi.org/10.1080/24750573.2018.1472923

12.Firat S, Gul H, Sertcelik M, Gul A, Gurel Y, Kilic BG. The relationship between problematic smartphone use and psychiatric symptoms among adolescents who applied to psychiatry clinics. Psychiatry Res 2018; 270:97-103.

13.Cho HY, Kim DJ, Park JW. Stress and adult smartphone addiction: mediation by self-control, neuroticism, and extraversion. Stress Health 2017; 33:624-630.

14.Wolniewicz CA, Tiamiyu MF, Weeks JW, Elhai JD. Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiatry Res 2018; 262:618-623.

15.Chotpitayasunondh V, Douglas KM. How “phubbing” becomes the norm: the antecedents and consequences of snubbing via smartphone. Comput Human Behav 2016; 63:9-18.

16.Elhai JD, Levine JC, Alghraibeh AM, Alafnan A, Aldraiweesh A, Hall BJ. Fear of missing out: testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Comput Human Behav 2018; 89:289-298.

17.Elhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Comput Human Behav 2016; 63:509-516.

18.Oberst U, Wegmann E, Stodt B, Brand M, Chamarro A. Negative consequences from heavy social networking in adolescents: the mediating role of fear of missing out. J Adolesc 2017; 55:51-60.

19.Fuster H, Chamarro A, Oberst U. Fear of Missing Out, online social networking and mobile phone addiction: a latent profile approach. Revista de Psicologia, Ciencies de l’Educacio i de l’Esport 2017; 35:23-30.

20.Elhai JD, Vasquez JK, Lustgarten SD, Levine JC, Hall BJ. Proneness to boredom mediates relationships between problematic smartphone use with depression and anxiety severity. Soc Sci Comput Rev 2018; 36:707-720.

21.Mansell W, Harvey AG, Watkins ER, Shafran R. Cognitive behavioral processes across psychological disorders: a review of the utility and validity of the transdiagnostic approach. Int J Cogn Ther 2008; 1:181-191.

22.Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: towards a model of compensatory internet use. Comput Human Behav 2014; 31:351-354.

23.Brand M, Laier C, Young KS. Internet addiction: coping styles, expectancies, and treatment implications. Front Psychol 2014; 5:1256.

24.Brand M, Young KS, Laier C, Wolfling K, Potenza MN. 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. Neurosci Biobehav Rev 2016; 71:252-266.

25.Dempsey A, O’Brien KD, Tiamiyu M, Elhai JD. Fear of missing out (FoMO) and rumination mediate relations between social anxiety and problematic Facebook use. Addict Behav Rep (in press).

26.Lemenager T, Hoffmann S, Dieter J, Reinhard I, Mann K, Kiefer F. The links between healthy, problematic, and addicted Internet use regarding comorbidities and self-concept-related characteristics. J Behav Addict 2018; 7:31-43.

27.Montag C, Blaszkiewicz K, Lachmann B, Sariyska R, Andone I, Trendafilov B, Markowetz A. Recorded behavior as a valuable resource for diagnostics in mobile phone addiction: evidence from psychoinformatics. Behav Sci 2015; 5:434-442.

28.Boase J, Ling R. Measuring mobile phone use: self-report versus log data. J Comput Mediat Commun 2013; 18:508-519.

29.Elhai JD, Tiamiyu MF, Weeks JW, Levine JC, Picard KJ, Hall BJ. Depression and emotion regulation predict objective smartphone use measured over one week. Pers Individ Dif 2018; 133:21-28.

30.Rozgonjuk D, Levine JC, Hall BJ, Elhai JD. The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week. Comput Human Behav 2018; 87:10-17.

31.Gower AD, Moreno MA. A novel approach to evaluating mobile smartphone screen time for iPhones: feasibility and preliminary findings. JMIR Mhealth Uhealth 2018; 6:e11012.

32.Shu C. We finally started taking screen time seriously in 2018. Tech Crunch 2018, December 25. Available from: https://techcrunch.com/2018/12/25/we-finally-started-taking-screen-time-seriously-in-2018/.

33.Elhai JD, Contractor AA. Examining latent classes of smartphone users: Relations with psychopathology and problematic smartphone use. Comput Human Behav 2018; 82:159-166.

34.Fried EI, Cramer AOJ. Moving forward: challenges and directions for psychopathological network theory and methodology. Perspect Psychol Sci 2018; 12:999-1020.

35.Shin C, Dey AK. Automatically detecting problematic use of smartphones. Proceedings of UbiComp 2013, 335-344.

Problematic smartphone use and mental health problems: current state of research and future directions
1Toledo Üniversitesi, Psikoloji Bölümü, Toledo, Ohio - ABD; Toledo Üniversitesi, Psikiyatri Bölümü, Toledo, Ohio - ABD
2Küresel ve Toplum Ruh Sağlığı Araştırma Grubu, Sosyal Bilimler Fakültesi, Makao Üniversitesi, Psikoloji Bölümü, Taipa, Makao (SAR) - Çin; Johns Hopkins Bloomberg Halk Sağlığı Okulu, Baltimore, Maryland - ABD
Dusunen Adam Journal of Psychiatry and Neurological Sciences 2019; 1(32): 1-3 DOI: 10.14744/DAJPNS.2019.00001