Ming Zhang
Chenru Chi
Qingwei Liu4- 1School of Educational Science, Anhui Normal University, Wuhu, Anhui, China
- 2School of Innovation and Entrepreneurship, Wannan Medical College, Wuhu, Anhui, China
- 3Graduate School of Wannan Medical College, Wuhu, Anhui, China
- 4School of Nursing, Shandong First Medical University, Jinan, Shandong, China
- 5School of Medical Imaging of Wannan Medical College, Wuhu, Anhui, China
- 6Department of Nursing, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu, Anhui, China
- 7Department of Hemodialysis, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu, Anhui, China
Background: The incidence of smartphone addiction has been widely studied, but the research on the relationship between smartphone addiction and psychological distress and internet gaming disorder is limited. This study investigated the characteristics and prevalence of smartphone addiction and its relation with psychological distress and internet gaming disorder. Furthermore, it provides the scientific basis for intervention measures in schools, families, and society.
Methods: A random cluster sampling method was applied to investigate 656 medical students from grades 1 to 4 at Wannan Medical College in Anhui province, People’s Republic of China. The questionnaire consisted of general information, a smartphone addiction scale, an Internet gaming disorder scale, and a Kessler 6-item psychological distress test. The obtained results were first summarized using descriptive statistics. The Chi-square test was used to compare the status of smartphone addiction. Binary logistic regression was used to analyze the relationship between smartphone addiction and various variables.
Results: Our results showed that the prevalence of smartphone addiction in medical students was 49.5% (325/656). Psychological distress (p < 0.001), internet gaming disorder (p < 0.001), and childhood trauma (p = 0.001) were highly correlated with smartphone addiction in medical students. Psychological distress, and internet gaming disorder were positively associated with smartphone addiction (p < 0.000).
Conclusion: The prevalence of smartphone addiction is high among medical students in Chinese. Smartphone addiction is highly related to related to internet gaming disorder and psychological distress.
Introduction
The smartphone represents the most significant technological advance of the 21st century (1). The increasingly rich functions of smartphones have brought great convenience to our life, study and work, and at the same time, it has also caused many increasingly serious social problems. According to the Cyberspace Administration of China (2), by December 2022, the number of Internet users in China reached 1.067 billion, an increase of 35.49 million over December 2021, of which 99.8% of Chinese Internet users use mobile phones to access the Internet. However, just like every coin has two sides, smart phones also have some obvious disadvantages, smart phones are a double-edged sword. Studies have shown the associations between smartphone addiction and individual health outcomes, such as mental health (3, 4), sleep disturbances (5, 6) and quality of life (7). Research has shown that smartphone addiction can lead to a variety of problems, such as anxiety, depression, sleep disorders, mood disorders, social disorders, and even suicide (8–10). Today’s college students are growing up with smartphones, which have become a necessity for college student’s life and study (11). Compared with other professions in society, college students have more access to the Internet, prefer to establish online relationships, and are more likely to develop symptoms of smartphone addiction (12). One meta-analysis found that the average prevalence of smartphone addiction among Chinese college students was about 23% (13). During the COVID-19 pandemic, smartphones have played a considerable role in medical care and higher education due to their powerful functions (14), making college students more dependent on the Internet and smartphones in life and study (14). A national survey of 746,217 Chinese college students by Ma et al. (15) found that the prevalence of acute stress, anxiety and depressive symptoms among college students was 34.9, 11, and 21.1%, and the risk of depression and anxiety disorders increased with the increase of electronic device exposure time. One study found that problematic smartphone use was associated with fatigue symptoms and problems with sleep quality in medical students (16).
Psychological distress refers to symptoms such as anxiety, depression, psychological stress, and absence of well-being (17). Higher levels of problematic Internet use among student nurses have been confirmed to be associated with increased psychological distress (18). Psychological distress is highly correlated with burnout, cognitive problems, and behavioral problems (19). A study (20) found a high rate of self-reported psychological distress among school-aged children and adolescents during the COVID-19 pandemic and a significant correlation between Internet-related behaviors and psychological distress among Chinese children during the COVID-19 pandemic.
Internet Gaming Disorder (IGD) is an activity characterized by persistent and repeated Internet use to play video games over 1 year, which can lead to significant considerable impairment or distress to the individual (21). Symptoms in people with IGD include excessive addiction to video games, significant withdrawal symptoms, unsuccessful attempts to stop, and other symptoms similar to substance dependence jeopardizing meaningful relationships or opportunities due to video games (22). IGD has become a substantial and widespread public health threat worldwide. In addition to the symptoms of smartphone addiction, it is also important to carefully assess the risk of smartphone addiction, which is essential for future prevention and intervention measures. Study showed that IGD is an emerging health issue for men (23). Studies also found that men risk developing IGD more than women (24–26). Teng et al. (27) found that IGD is negatively correlated with self-esteem and social support. Given these current limitations, we believe further research is warranted to explore the relationship between psychological distress, IGD, and smartphone addiction.
Many mechanistic studies have explored the relationship between smartphone addiction and mental health. Smartphone addiction can cause symptoms of depression, anxiety, and loneliness, and affect individual’s mental health through a variety of complex mechanisms (28). There are several theories to explain the development of smartphone addiction (29–31). For example, the Person-Affect-Cognition-Execution (I-PACE) model suggests that individuals could use smartphones as a coping strategy to overcome their troubles and satisfy their emotional needs. However, when individuals use their smartphones too often to form habitual and dependent behaviors, they risk developing smartphone addiction symptoms. However, the mechanism of the development of smartphone addiction is still unclear, because the factors affecting behavioral addiction are very complex, and more research evidence is needed to confirm these theories and models. In this sense, it is more urgent and important to explore the relationship between smartphone addiction, psychological distress, and online gaming.
Childhood trauma is defined as experiences of extreme threats experienced or perceived by children early in life, including the death of a parent, exposure to war, harrowing accidents, serious illness, exposure to violence, childhood neglect, and abuse (32, 33). The incidence of childhood trauma is high, with approximately two-thirds of the population experiencing severe childhood trauma before 18 years old (34). Research (35) had found that childhood trauma often leads to many harmful health outcomes. Studies have found that childhood trauma is extremely harmful and can lead to various psychological and behavioral problems in individuals, including depression, increased aggression, substance abuse, interpersonal difficulties, PTSD, and even suicidal thoughts (36, 37). Research has found that compared to college students who have not been abused, college students who were abused in childhood are more likely to induce mobile phone addiction (38). One study confirmed that experiencing trauma had a significant predictive effect on smartphone addiction among college students (39). Studies have found that childhood trauma greatly increases the risk of PSH in adolescents, and childhood trauma is also highly associated with multiple types of mental disorders, affecting them into adulthood (40).
Therefore, smartphone addiction and mental health problems among medical students should attract more attention. Based on the existing theoretical mechanisms and research, smartphone addiction seems to be related to IGD and psychological distress among medical students. We thus proposed the following research hypotheses:
Hypothesis 1 (H1): Smartphone addiction is positively correlated with levels of IGD and psychological distress.
Hypothesis 2 (H2): Childhood trauma significantly and positively predicts smartphone addiction among medical college students.
Materials and methods
Study design and participants
This study conducted a cross-sectional survey at Wannan Medical College in Wuhu City, southern Anhui Province, China, from June to July 2023. The method of cluster sampling was used to investigate Wannan Medical College in Wuhu City. The research team conducted detailed training for the investigators in advance to ensure the quality of the investigation after selecting counselors and class cadres as investigators. Before the survey, students were informed about the purpose and measurement method of the survey, and the paper questionnaire was issued after obtaining their signed consent. It took about 5–10 min to complete all the questions and can be recalled after the investigators have checked it. The investigator from each college was trained in standardised questionnaires collection, sending and receiving paper versions of the questionnaire, and all participants volunteered to participate in the study and signed paper informed consent forms.
A cluster sampling survey was used to recruit participants. Four different grades were randomly selected, and the inclusion criteria for participants were: (1) students in the Wannan Medical College, (2) agreed to participate and signed a paper informed consent form. The exclusion criteria were: (1) dropped out of Wannan Medical College; (2) did not complete the questionnaire; (3) whose response time is more than 20 min.
A total of 700 medical students completed the investigation, of which 44 were excluded, and the remaining 656 respondents met the requirements, with an effective response proportion of 93.7% (details are shown in Figure 1).
Figure 1. Sample selection process for this cross-sectional study.
Measurement
General demographic characteristics
Personal information of participants was collected using a self-reported questionnaire. The contents of the questionnaire include age, gender, grade, place of origin (rural/urban/urban), monthly living expenses, academic pressure, the only child, serving as a student leader (yes/no), playing online games (yes/no), whether you feel lonely, etc.
Smartphone addiction scale short version (SAS-SV)
The Smartphone Addiction Scale Short version (SAS-SV) (41) was used to measure the smartphone addiction status of medical students. SAS-SV consists of 10 items with a scale of Likert 6 scales (1 = strongly disagree, 6 = strongly agree). The total score ranges from 10 to 60. The smartphone addiction thresholds for male and female subjects were ≥ 31 and ≥ 33, respectively. The Cronbach’s alpha coefficient in this study was 0.81. The SAS-SV has been confirmed to have good reliability and validity among Chinese medical students (42). In this study, the Cronbach’s α coefficient of SAS-SV was 0.83.
Kessler 6-item psychological distress scale (K-6)
Psychological distress was measured via the Kessler 6-item psychological distress scale (K-6). The K-6 scale was developed by Kessler et al. (43). It has been proven and widely used to assess an individual’s degree of non-specific psychological distress within the past 1 month. The Chinese version was proved to have good reliability and validity (44). The scale consists of six psychological symptoms. The scale is scored by a 5-point Likert scale (0 = no time, 4 = all the time). The total score is 0 ~ 24, and more than 12 points were classified as severe psychological distress (45). In this study, the Cronbach’s α coefficient of K-6 was 0.79.
IGD
To evaluate the symptoms of IGD among medical students, the diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) (45) were used. The scale comprises nine items, and participants were asked whether these symptoms (e.g., enthusiasm, withdrawal, tolerance, loss of control, loss of interest in other activities, persistence, cheating, avoidance, victimization) occurred in the past 12 months (0 = no, 1 = yes). A total of five positive responses was suggestive of a higher risk of IGD (46). In this study, the Cronbach’s coefficient of the scale was 0.72.
Statistical analysis
Data analyses were performed using IBM Statistical Package for Social Science, Version 21.0 (SPSS Inc., Chicago, IL, United States). Descriptive statistical methods were used to summarize participants’ characteristics. Based on the Smartphone Addiction Scale score, the participants were divided into two groups: non-smartphone addiction and smartphone addiction. Chi-square tests were used to examine differences in demographics, psychological distress, and IGD symptoms between the smartphone and non-smartphone addiction groups. Binary logistic regression analysis was used to analyze the factors associated with smartphone addiction, and the ORs (odds ratios) and 95% CIs (confidence intervals) were calculated.
Result
Participant characteristics
Among 656 medical student included in the data analysis, The age of the respondents ranged from 17 to 24 years old, which the mean age being (19.66 ± 2.14) years old. 388 (59.1%) were male, and 268 (40.9%) were female. 390 (59.5%) were the only child, 291(44.3%) were freshmen, 49(7.5%) were sophomore, 257(39.2%) were junior, and 59(9.0) were senior. Further socio-demographic information about this study is displayed in Table 1.
Table 1. Participants’ demographic information (n = 656).
Factors associated with smartphone addiction in the univariate analysis
In this study, the prevalence of smartphone addiction among the medical students was 49.5% (325/656). There were significant differences between the the only child or not, grade, want to change major, satisfied with the major, childhood trauma, college adaptability, study stress, monthly living expenses, IGD, and psychological distress (K-6) (p < 0.05, Table 2).
Table 2. Characteristics of the participants based on the presence of smartphone addiction (n = 656).
Correlation between smartphone addiction and psychological distress and IGD in medical college students
From Figures 2, 3 psychological distress, and IGD were positively associated with smartphone addiction (r = 0.37, P<0.001; r = 0.42, P<0.001).
Figure 2. Smartphone addiction total score vs. K-6 total score Pearson Correlation.
Figure 3. Smartphone addiction total score vs. internet gaming disorder total score Pearson Correlation.
Binary analysis factors associated with smartphone addiction
We put independent variables (p < 0.05) and dependent variables (0 = non-smartphone addiction, 1 = smartphone addiction) into a binary logistic regression analysis model. Factors affecting smartphone addiction of medical students are shown in Table 3. As shown in Table 3 and Figure 4, smartphone addiction is more severe among medical students with psychological distress, IGD, and childhood trauma(OR = 4.275, 95% CI 2.475–7.383; OR = 13.010, 95% CI 6.923–24.449; OR = 2.000, 95% CI 1.344–2.976).
Table 3. Binary logistic regression analysis of factors associated with smartphone addiction.
Figure 4. Forest plot: factors affecting smartphone addiction using binary logistic regression analysis.
Discussion
Key findings
With the progress of science and technology, smart phones have become an increasingly important and indispensable part of college students’ lives. In recent years, the overuse of smart phones has become a public health problem of widespread concern (47). The purpose of this study was to explore the status of smartphone addiction among medical students and its relationship with IGD and psychological distress. The results showed that the smartphone addiction rate among medical students is relatively high, which is basically consistent with previous research results (11). According to the SAS-SV scale, the smartphone addiction rate among students in different countries ranged from 12 to 78.3% (48). This difference may stem from the differences in different social and cultural environments and the development of information technology. At the same time, the measurement scales used in different studies may differ.
Differences in smartphone addiction
Consistent with previous studies (49–51), this study found that Psychological distress is one of the important risks leading to smartphone addiction among medical students. Studies have found significant associations between smartphone addiction and psychosocial factors such as depression, anxiety, and stress among university medical students (48, 52). Study (53) found that psychological distress indirectly affects smartphone addiction by affecting social capital and social need satisfaction. Psychological distress is a negative emotion that is an indicator of poor levels of mental health, with symptoms including anxiety, depression, behavioral problems, and functional impairment (54). Studies have found strong correlations between psychological distress and smartphone addiction among university students (55–57). The above studies supported our Hypothesis 1 (H1), that smartphone addiction is positively correlated with psychological distress.
This study found that IGD is one of the important influencing factors of smartphone addiction. Research shows that the prevalence of IGD has increased in recent years (58). Research has proven that IGD has been associated with loneliness and introversion, boredom tendencies, social inhibition, and decreased self-control ability (59). Internet gaming is a popular leisure activities among college students, while dysfunctional gaming can lead to addiction-like symptoms. A systematic review of relevant studies in China showed that the prevalence of gaming disorder ranges from 3.5 to 17% (60). Another study found that the prevalence of IGD in men is higher than that in women (61). Studies shown that heavy gamers had lower levels of self-control (62) and, in addition, higher levels of impulsivity (63, 64). Research shown that excessive addiction to online games is a common feature among some college students and is also a decisive factor in their Internet addiction (65). The above studies supported our Hypothesis 1 (H1), that smartphone addiction is positively correlated with levels of IGD.
Exposure to childhood trauma is a risk factor for psychosis (66). Research has found that childhood trauma is linked to poorer physical and mental health outcomes in adulthood (67, 68). Childhood trauma could increase the risk of physical and mental health problems in adults and unhappiness (69, 70). Adolescents who grew up in unsafe family environments and suffered childhood trauma may self-medicate negative emotions through excessive use of the Internet, ultimately leading to Internet addiction (IA) (71). For individuals who have experienced childhood trauma, excessive use of the Internet is a strategy to cope with stress. However, this strategy further strengthens their dependence on the Internet and is prone to Internet addiction (71). The above studies supported our Hypothesis 2 (H2), that childhood trauma is one of the influencing factors of smartphone addiction.
Limitations
This study still has some limitations. First, the study used a cross-sectional design, so causal relationships between the study variables could not be determined. Future prospective studies should be conducted on serial assessments of smartphone addiction causes and psychological stress and online gaming addiction. Second, our study sample only included medical students from one medical school in Anhui Province, so generalization of the results to the whole of China or other countries would be limited. Third, the sample size is limited. Finally, because the questionnaire method is based on the subjective evaluation of the research subjects, the participants’ answers may be exaggerated or weakened.
Conclusion
In summary, smartphone addiction is related to psychological distress and IGD. For medical students with psychological distress, IGD, and childhood trauma, educational institutions and teachers should recognize early and provide relevant psychological assistance and intervention measures to prevent their further development, thereby reducing smartphone addiction. Additionally, teachers should consider childhood trauma and psychological distress when dealing with smartphone-addicted medical students, which could help provide more effective interventions.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
All students were informed of the purpose of the study and signed written consent. Ethical approval was obtained from the Ethics Committee of Wannan Medical College (Decision No. 2023212).
Author contributions
MZ: Funding acquisition, Investigation, Resources, Supervision, Writing – original draft, Writing – review & editing. CC: Formal analysis, Investigation, Writing – original draft. QL: Data curation, Investigation, Software, Writing – original draft. YZ: Investigation, Methodology, Validation, Writing – review & editing. XT: Formal analysis, Investigation, Resources, Writing – review & editing. HL: Data curation, Formal analysis, Investigation, Software, Validation, Writing – original draft, Writing – review & editing. BX: Conceptualization, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by Anhui Provincial University Scientific Research Key Project (2023AH051733), the National Natural Science Fund of China (32371112), Anhui Province Educational Science Research Project (JK23173), Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention (SYS2023B09), the Industry-University Cooperation Collaborative Education Project of the Ministry of Education (220905875062412), the Anhui Provincial College Outstanding Young Talents Support Program (gxyq2022045, gxgwfx2019032), the Teaching Quality and teaching reform project of Wannan Medical College (2020jyxm58, 2022jbgs10, 2022kcszsfkc01), and the Teaching Reform Project of Wannan Medical College (2021zybz06).
Acknowledgments
We thank the study participants and the reviewers for their details.
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.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Moses, JC, Adibi, S, Wickramasinghe, N, Nguyen, L, Angelova, M, and Islam, SMS. Smartphone as a disease screening tool: a systematic review. Sensors. (2022) 22:3787. doi: 10.3390/s22103787
2. China CAO (2023) China CAo: The 51th China statistical report on internet development. Available at: https://cnnic.cn/n4/2023/0302/c199-10755.html
3. Chen, IH, Chen, CY, Liu, CH, Ahorsu, DK, Griffiths, MD, Chen, YP, et al. Internet addiction and psychological distress among Chinese schoolchildren before and during the COVID-19 outbreak: a latent class analysis. J Behav Addict. (2021) 10:731–46. doi: 10.1556/2006.2021.00052
4. Kakul, F, and Javed, S. Internet gaming disorder: an interplay of cognitive psychopathology. Asian J Soc Health Behav. (2023) 6:36–45. doi: 10.4103/shb.shb_209_22
5. Chang, KC, Chang, YH, Yen, CF, Chen, JS, Chen, PJ, Lin, CY, et al. A longitudinal study of the effects of problematic smartphone use on social functioning among people with schizophrenia: mediating roles for sleep quality and self-stigma. J Behav Addict. (2022) 11:567–76. doi: 10.1556/2006.2022.00012
6. Ranjan, LK, Gupta, PR, Srivastava, M, and Gujar, NM. Problematic internet use and its association with anxiety among undergraduate students. Asian J Soc Health Behav. (2021) 4:137–41. doi: 10.4103/shb.shb_30_21
7. Kwok, C, Leung, PY, Poon, KY, and Fung, XC. The effects of internet gaming and social media use on physical activity, sleep, quality of life, and academic performance among university students in Hong Kong: a preliminary study. Asian J Soc Health Behav. (2021) 4:36–44. doi: 10.4103/shb.shb_81_20
8. Cho, HY, Kim, DJ, and Park, JW. Stress and adult smartphone addiction: mediation by self-control, neuroticism, and extraversion. Stress Health. (2017) 33:624–30. doi: 10.1002/smi.2749
9. Yang, H, Liu, B, and Fang, J. Stress and problematic smartphone use severity: smartphone use frequency and fear of missing out as mediators. Front Psych. (2021) 12:659288. doi: 10.3389/fpsyt.2021.659288
10. Kil, N, Kim, J, McDaniel, JT, Kim, J, and Kensinger, K. Examining associations between smartphone use, smartphone addiction, and mental health outcomes: a cross-sectional study of college students. Health Promot Perspect. (2021) 11:36–44. doi: 10.34172/hpp.2021.06
11. Liu, H, Zhou, Z, Huang, L, Zhu, E, Yu, L, and Zhang, M. Prevalence of smartphone addiction and its effects on subhealth and insomnia: a cross-sectional study among medical students. BMC Psychiatry. (2022) 22:305. doi: 10.1186/s12888-022-03956-6
12. Jang, KS, Hwang, SY, and Choi, JY. Internet addiction and psychiatric symptoms among Korean adolescents. J Sch Health. (2008) 78:165–71. doi: 10.1111/j.1746-1561.2007.00279.x
13. Tao, J, Luo, C, and Huang, J. Meta-analysis of the current situation of mobile phone dependence among college students in China (in Chinese). Chin J School Health. (2018) 39:1391–4. doi: 10.16835/j.cnki.1000-9817.2018.09.032
14. Iyengar, K, Upadhyaya, GK, Vaishya, R, and Jain, V. COVID-19 and applications of smartphone technology in the current pandemic. Diabetes Metab Syndr. (2020) 14:733–7. doi: 10.1016/j.dsx.2020.05.033
15. Ma, Z, Zhao, J, Li, Y, Chen, D, Wang, T, Zhang, Z, et al. Mental health problems and correlates among 746 217 college students during the coronavirus disease 2019 outbreak in China. Epidemiol Psychiatr Sci. (2020) 29:e181. doi: 10.1017/S2045796020000931
16. Zhang, C, Zeng, P, Tan, J, Sun, S, Zhao, M, Cui, J, et al. Relationship of problematic smartphone use, sleep quality, and daytime fatigue among quarantined medical students during the COVID-19 pandemic. Front Psych. (2021) 12:755059. doi: 10.3389/fpsyt.2021.755059
17. Burnette, JL, Knouse, LE, Vavra, DT, O'Boyle, E, and Brooks, MA. Growth mindsets and psychological distress: a meta-analysis. Clin Psychol Rev. (2020) 77:101816. doi: 10.1016/j.cpr.2020.101816
18. Labrague, LJ . Problematic internet use and psychological distress among student nurses: the mediating role of coping skills. Arch Psychiatr Nurs. (2023) 46:76–82. doi: 10.1016/j.apnu.2023.08.009
19. Arbabisarjou, A, Mehdi, HS, Sharif, MR, Alizadeh, KH, Yarmohammadzadeh, P, and Feyzollahi, Z. The relationship between sleep quality and social intimacy, and academic burn-out in students of medical sciences. Glob J Health Sci. (2015) 8:231–8. doi: 10.5539/gjhs.v8n5p231
20. Chen, IH, Chen, C-Y, Pakpour, AH, Griffiths, MD, and Lin, CY. Internet-related behaviors and psychological distress among schoolchildren during COVID-19 school suspension. J Am Acad Child Adolesc Psychiatry. (2020) 59:1099–1102.e1. doi: 10.1016/j.jaac.2020.06.007
21. King, DL, and Delfabbro, PH. The cognitive psychology of internet gaming disorder. Clin Psychol Rev. (2014) 34:298–308. doi: 10.1016/j.cpr.2014.03.006
22. Wu, AMS, Chen, JH, Tong, KK, Yu, S, and Lau, JTF. Prevalence and associated factors of internet gaming disorder among community dwelling adults in Macao China. J Behav Addict. (2018) 7:62–9. doi: 10.1556/2006.7.2018.12
23. Chen, KH, Oliffe, JL, and Kelly, MT. Internet gaming disorder: an emergent health issue for men. Am J Mens Health. (2018) 12:1151–9. doi: 10.1177/1557988318766950
24. Yu, Y, Mo, PKH, Zhang, J, Li, J, and Lau, JTF. Why is internet gaming disorder more prevalent among Chinese male than female adolescents? The role of cognitive mediators. Addict Behav. (2021) 112:106637. doi: 10.1016/j.addbeh.2020.106637
25. Wu, XS, Zhang, ZH, Zhao, F, Wang, WJ, Li, YF, Bi, L, et al. Prevalence of internet addiction and its association with social support and other related factors among adolescents in China. J Adolesc. (2016) 52:103–11. doi: 10.1016/j.adolescence.2016.07.012
26. Taechoyotin, P, Tongrod, P, Thaweerungruangkul, T, Towattananon, N, Teekapakvisit, P, Aksornpusitpong, C, et al. Prevalence and associated factors of internet gaming disorder among secondary school students in rural community, Thailand: a cross-sectional study. BMC Res Notes. (2020) 13:11. doi: 10.1186/s13104-019-4862-3
27. Teng, ZJ, Pontes, HM, Nie, Q, and Guo, C. Internet gaming disorder and psychosocial well-being: a longitudinal study of older-aged adolescents and emerging adults. Addict Behav. (2020) 110:106530. doi: 10.1016/j.addbeh.2020.106530
28. Park, N, and Lee, H. Social implications of smartphone use: Korean college students' smartphone use and psychological well-being. Cyberpsychol Behav Soc Netw. (2012) 15:491–7. doi: 10.1089/cyber.2011.0580
29. Brand, M, Wegmann, E, Stark, R, Müller, A, Wölfling, K, Robbins, TW, et al. 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. Neurosci Biobehav Rev. (2019) 104:1–10. doi: 10.1016/j.neubiorev.2019.06.032
30. Campbell, JL, and Miller, JD. Narcissism and the world wide web In: WK Campbell and JD Miller, editors. The handbook of narcissism and narcissistic personality disorder: Theoretical approaches, empirical findings, and treatments. Hoboken, NJ: John Wiley & Sons, Inc (2011). 371–81.
31. McCain, JL, and Campbell, WK. Narcissism and social media use: a meta-analytic review. Psychol Pop Media Cult. (2018) 7:308–27. doi: 10.1037/ppm0000137
32. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association (2001).
33. Bulut, S . Classification of posttraumatic stress disorder and its evolution in diagnostic and statistical manual of mental disorders (DSM) criteria. Int J Psych Counsell. (2020) 12:105–8. doi: 10.5897/IJPC2020.0597
34. Hughes, K, Bellis, MA, Hardcastle, KA, Sethi, D, Butchart, A, Mikton, C, et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public Health. (2017) 2:e356–66. doi: 10.1016/S2468-2667(17)30118-4
35. Gladish, N, Merrill, SM, and Kobor, MS. Childhood trauma and epigenetics: state of the science and future. Curr Environ Health Rep. (2022) 9:661–72. doi: 10.1007/s40572-022-00381-5
36. El-Khodary, B, and Samara, M. The relationship between multiple exposures to violence and war trauma, and mental health and behavioural problems among Palestinian children and adolescents. Eur Child Adolesc Psychiatry. (2020) 29:719–31. doi: 10.1007/s00787-019-01376-8
37. Nelson, CA, Scott, RD, Bhutta, ZA, Harris, NB, Danese, A, and Samara, M. Adversity in childhood is linked to mental and physical health throughout life. BMJ. (2020) 371:m3048. doi: 10.1136/bmj.m3048
38. Schwandt, ML, Heilig, M, Hommer, DW, George, DT, and Ramchandani, VA. Childhood trauma exposure and alcohol dependence severity in adulthood: mediation by emotional abuse severity and neuroticism. Alcohol Clin Exp Res. (2013) 37:984–92. doi: 10.1111/acer.12053
39. Liang, HY, Zhang, B, Jiang, HB, and Zhou, HL. Adult attachment: its mediation role on childhood trauma and mobile phone addiction. J Psychol Africa. (2021) 31:369–74. doi: 10.1080/14330237.2021.1952706
40. Green, JG, McLaughlin, KA, Berglund, PA, Gruber, MJ, Sampson, NA, Zaslavsky, AM, et al. Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders. Arch Gen Psychiatry. (2010) 67:113–23. doi: 10.1001/archgenpsychiatry.2009.186
41. Kwon, M, Kim, DJ, Cho, H, and Yang, S. The smartphone addiction scale: development and validation of a short version for adolescents. PLoS One. (2013) 8:e83558. doi: 10.1371/journal.pone.0083558
42. Liu, H, Zhou, Z, Zhu, E, Huang, L, and Zhang, M. Smartphone addiction and its associated factors among freshmen medical students in China: a cross-sectional study. BMC Psychiatry. (2022) 22:308. doi: 10.1186/s12888-022-03957-5
43. Kessler, RC, Andrews, G, Colpe, LJ, Hiripi, E, Mroczek, DK, Normand, SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. (2002) 32:959–76. doi: 10.1017/S0033291702006074
44. Kang, YK, Guo, WJ, Xu, H, Chen, YH, Li, XJ, Tan, ZP, et al. The 6-item Kessler psychological distress scale to survey serious mental illness among Chinese undergraduates: psychometric properties and prevalence estimate. Compr Psychiatry. (2015) 63:105–12. doi: 10.1016/j.comppsych.2015.08.011
45. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. DSM-5. 5th edn. Washington, DC: American Psychiatric Publishing (2013). P. 371.
46. Petry, NM, Rehbein, F, Gentile, DA, Lemmens, JS, Rumpf, HJ, Mößle, T, et al. An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction. (2014) 109:1399–406. doi: 10.1111/add.12457
47. Shoukat, S . Cell phone addiction and psychological and physiological health in adolescents. Excli J. (2019) 18:47–50.
48. Nikolic, A, Bukurov, B, Kocic, I, Vukovic, M, Ladjevic, N, Vrhovac, M, et al. Smartphone addiction, sleep quality, depression, anxiety, and stress among medical students. Front Public Health. (2023) 11:1252371. doi: 10.3389/fpubh.2023.1252371
49. Lei, LY, Ismail, MA, Mohammad, JA, and Yusoff, MSB. The relationship of smartphone addiction with psychological distress and neuroticism among university medical students. BMC Psychol. (2020) 8:97. doi: 10.1186/s40359-020-00466-6
50. Ou-Yang, Q, Liu, Q, Song, PY, Wang, JW, and Yang, S. The association between academic achievement, psychological distress, and smartphone addiction: a cross-sectional study among medical students. Psychol Health Med. (2023) 28:1201–14. doi: 10.1080/13548506.2022.2148697
51. Alzhrani, AM, Aboalshamat, KT, Badawoud, AM, Abdouh, IM, Badri, HM, Quronfulah, BS, et al. The association between smartphone use and sleep quality, psychological distress, and loneliness among health care students and workers in Saudi Arabia. PLoS One. (2023) 18:e0280681. doi: 10.1371/journal.pone.0280681
52. Zhang, K, Guo, H, Wang, T, Zhang, J, Yuan, G, Ren, J, et al. A bidirectional association between smartphone addiction and depression among college students: a cross-lagged panel model. Front Public Health. (2023) 11:1083856. doi: 10.3389/fpubh.2023.1083856
53. Bian, M, and Leung, L. Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Soc Sci Comput Rev. (2015) 33:61–79. doi: 10.1177/0894439314528779
54. Drapeau, A, Marchand, A, and Beaulieu-Prévost, D. Epidemiology of psychological distress In: L L’Abate , editor. Mental illnesses—Understanding, prediction and control. Croatia: InTech (2012). 105–34.
55. Squires, LR, Hollett, KB, Hesson, J, and Harris, N. Psychological distress, emotion dysregulation, and coping behaviour: a theoretical perspective of problematic smartphone use. Int J Ment Health Addiction. (2021) 19:1284–99. doi: 10.1007/s11469-020-00224-0
56. Chen, IH, Pakpour, AH, Leung, H, Potenza, MN, Su, JA, Lin, CY, et al. Comparing generalized and specific problematic smartphone/internet use: longitudinal relationships between smartphone application-based addiction and social media addiction and psychological distress. J Behav Addict. (2020) 9:410–9. doi: 10.1556/2006.2020.00023
57. Volungis, AM, Kalpidou, M, Popores, C, and Joyce, M. Smartphone addiction and its relationship with indices of social-emotional distress and personality. Int J Ment Health Addiction. (2020) 18:1209–25. doi: 10.1007/s11469-019-00119-9
58. Stevens, C, Zhang, E, Cherkerzian, S, Chen, JA, and Liu, CH. Problematic internet use/computer gaming among US college students: prevalence and correlates with mental health symptoms. Depress Anxiety. (2020) 37:1127–36. doi: 10.1002/da.23094
59. Griffiths, MD, Kuss, DJ, and King, DL. Video game addiction: past, present and future. Curr Psyciatry Rev. (2012) 8:308–18. doi: 10.2174/157340012803520414
60. Jiang, L, Tieqiao, L, Yueheng, L, Hao, W, Maurage, P, and Billieux, J. Prevalence and correlates of problematic online gaming: a systematic review of the evidence published in Chinese. Curr Addict Rep. (2018) 5:359–71. doi: 10.1007/s40429-018-0219-6
61. Stevens, MW, Dorstyn, D, Delfabbro, PH, and King, DL. Global prevalence of gaming disorder: a systematic review and meta-analysis. Aust N Z J Psychiatry. (2021) 55:553–68. doi: 10.1177/0004867420962851
62. Li, Q, Wang, Y, Yang, Z, Dai, W, Zheng, Y, Sun, Y, et al. Dysfunctional cognitive control and reward processing in adolescents with internet gaming disorder. Psychophysiology. (2020) 57:e13469. doi: 10.1111/psyp.13469
63. Shin, Y-B, Kim, H, Kim, S-J, and Kim, J-J. A neural mechanism of the relationship between impulsivity and emotion dysregulation in patients with internet gaming disorder. Addict Biol. (2020) 26:e12916. doi: 10.1111/adb.12916
64. Wang, L, Tian, M, Zheng, Y, Li, Q, and Liu, X. Reduced loss aversion and inhibitory control in adolescents with internet gaming disorder. Psychol Addict Behav. (2020) 34:484–96. doi: 10.1037/adb0000549
65. Yiyu, C, Yue Yu, M, and Zhanyu, Y. Influence of internet game addiction on empathy of college students from the perspective of new game era:the mediating role of alexithymia. Chin J Health Psychol. (2020) 28:1268–72. doi: 10.13342/j.cnki.cjhp.2020.08.033
66. Loewy, RL, Corey, S, Amirfathi, F, Dabit, S, Fulford, D, Pearson, R, et al. Childhood trauma and clinical high risk for psychosis. Schizophr Res. (2019) 205:10–4. doi: 10.1016/j.schres.2018.05.003
67. Kalmakis, KA, and Chandler, GE. Health consequences of adverse childhood experiences: a systematic review. J Am Assoc Nurse Pract. (2015) 27:457–65. doi: 10.1002/2327-6924.12215
68. Taylor, SE, Way, BM, and Seeman, TE. Early adversity and adult health outcomes. Dev Psychopathol. (2011) 23:939–54. doi: 10.1017/S0954579411000411
69. Felitti, VJ, Anda, RF, Nordenberg, D, Williamson, DF MS, PhD, Spitz, AM MS, MPH, Edwards, V BA, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The adverse childhood experiences (ACE) study. Am J Prev Med. (1998) 14:245–58. doi: 10.1016/S0749-3797(98)00017-8
70. Norman, RE, Byambaa, M, de, R, Butchart, A, Scott, J, and Vos, T. The long-term health consequences of child physical abuse, emotional abuse, and neglect: a systematic review and meta-analysis. PLoS Med. (2012) 9:e1001349. doi: 10.1371/journal.pmed.1001349
Keywords: smartphone addiction, psychological distress, internet gaming disorder, medical, students
Citation: Zhang M, Chi C, Liu Q, Zhang Y, Tao X, Liu H and Xuan B (2024) Prevalence of smartphone addiction and its relation with psychological distress and internet gaming disorder among medical college students. Front. Public Health. 12:1362121. doi: 10.3389/fpubh.2024.1362121
Edited by:
Wulf Rössler, Charité University Medicine Berlin, GermanyReviewed by:
Tamara Jovanović, University of Niš, SerbiaKıvanç Kök, Istanbul Medipol University, Türkiye
Laura N. Smith, Texas A&M Health Science Center, United States
Copyright © 2024 Zhang, Chi, Liu, Zhang, Tao, Liu and Xuan. 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: Huan Liu, MjcyMzc2NDc2NkBxcS5jb20=; Bin Xuan, eHVhbmJpbkBhaG51LmVkdS5jbg==