East Asian Arch Psychiatry 2024;34:109-14 | https://doi.org/10.12809/eaap2432

ORIGINAL ARTICLE

pdf Full Paper in PDF

Nur Najwa Hanim Ab Latiff, Department of Psychiatry, Faculty of Medicine, Sg. Buloh Campus, Universiti Teknologi MARA, Selangor, Malaysia
Nur Faizah Ali, Department of Psychiatry, Faculty of Medicine, Sg. Buloh Campus, Universiti Teknologi MARA, Selangor, Malaysia
Nurul Azreen Hashim, Department of Psychiatry, Faculty of Medicine, Sg. Buloh Campus, Universiti Teknologi MARA, Selangor, Malaysia
Ely Zarina Samsudin, Department of Psychiatry, Faculty of Medicine, Sg. Buloh Campus, Universiti Teknologi MARA, Selangor, Malaysia
Khatijah Kasmuri, Department of Psychiatry, Hospital Selayang, Selangor, Malaysia

Address for correspondence: Dr Nur Faizah Ali, Department of Psychiatry, Faculty of Medicine, Sg. Buloh Campus, Universiti Teknologi MARA, Selangor, Malaysia. Email: faizah7761@uitm.edu.my

Submitted: 11 July 2024; Accepted: 26 August 2024

Internet usage, particularly during the COVID-19 pandemic, has raised the profile of internet addiction.¹ Internet addiction is defined as any online-related, compulsive behaviour that interferes with normal living and causes severe stress on relationships and work life.² It aligns with other behavioural addictions.³ The Internet Addiction Test (IAT) is a widely used assessment tool.

The worldwide prevalence of internet addiction is 14.2%, with younger people being particularly vulnerable.⁴ In Malaysia, there were 33.03 million internet users in 2023; many engaged in 5 to 8 hours of daily internet usage, particularly those in their early 20s.⁵ The prevalence of internet addiction among Malaysian undergraduate and adolescent populations varies from 7.8% to 60.7%.⁶

Factors associated with internet addiction include alcohol use, online gaming, daily internet usage, environmental influences, and lower sociability and socioeconomic status,^7-9 as well as psychological distress (including stress, depression, anxiety, and suicidal ideation).^10-12Psychological distress refers to an unpleasant mental or emotional state marked by discomfort, anxiety, depression, and other adverse emotions.¹³

Healthcare professionals are more susceptible to mental health issues.^14,15 The prevalence of internet addiction among healthcare professionals ranges from 0% to 79%.¹⁶ Among house officers, the prevalence ranges from 13% to 48%.^17,18 Unlike nursing students or other healthcare trainees, house officers are newly graduated doctors who undergo rigorous training programmes that involve long working hours, high patient loads, and intense patient care. These conditions can result in stress, burnout, depression, and anxiety.^19-21 In a study of 837 house officers across 10 hospitals in Malaysia, 73.3% experienced personal-related burnout.²² Studies examining associations between internet addiction and psychological distress among Malaysian house officers remain sparse. The mental wellbeing of house officers affects their ability to provide quality patient care. The provision of better support and interventions would therefore lead to enhanced healthcare delivery. This study aimed to investigate factors associated with internet addiction among house officers in a Malaysian hospital.

Methods

This is a cross-sectional study of house officers at Hospital Selayang, a tertiary government hospital in Selangor, Malaysia. They were randomly selected (from various hospital departments) using a stratified random sampling method. They were asked to complete a survey during their continuous medical education sessions between May and June 2023. Those with a history or diagnosis of psychiatric illness were excluded.

Demographic and internet usage data were collected. Internet addiction was assessed using the validated Malay version of the IAT,²³ which comprises 20 questions measured on a five-point Likert scale from 1 (rarely) to 5 (always). Total scores range from 0 to 100, with scores of 0 to 30 indicating a normal level of internet usage, 31 to 49 indicating mild addiction, 50 to 79 indicating moderate addiction, and 80 to 100 indicating severe addiction. The Malay version of the IAT has good internal consistency (Cronbach α = 0.91). Participants with a score of ≥50 were classified as having internet addiction.

Levels of depression, anxiety, and stress were assessed using the self-report Depression, Anxiety and Stress Scale 21 (DASS-21),²⁴ which has good internal consistency (Cronbach α = 0.837-0.863).²⁵ The DASS-21 comprises 21 items in three subscales, each containing seven items. Each item is rated from 0 (did not apply to me at all) to 3 (applied to me very much, or most of the time). Higher scores indicate more severe symptoms. For the depression scale, scores are classified as normal (0-9), mild depression (10-13), moderate depression (14-20), severe depression (21-27), and extremely severe depression (≥28). For the anxiety scale, scores are classified as normal (0-7), mild anxiety (8-9), moderate anxiety (10-14), severe anxiety, (15-19), and extremely severe anxiety (≥20). For the stress scale, scores are classified as normal (0-14), mild stress (15-18), moderate stress (19-25), severe stress (26-33), and extremely severe stress (≥34). Participants with moderate or above scores for all subscales were considered to have psychological distress.

The sample size was calculated through the website openepi.com. Based on a 48% prevalence of internet addiction in a previous study,¹⁸ at least 138 participants were required, with an accuracy of 5%, an attrition rate of 20%, and a confidence level of 95%.

Statistical analyses were performed using SPSS (Windows version 28.0; IBM Corp, Armonk [NY], United States). Those with and without internet addiction were compared using the Chi-squared test or independent t test. Simple logistic regression analysis was used to identify factors associated with internet addiction; variables with p < 0.25 were entered into multiple logistic regression analysis, in which variables with p < 0.05 were considered statistically significant.

Results

Of 62 male and 81 female house officers included, 27 (18.9%) had internet addiction (IAT score of ≥50). Across all participants, 75.5% reported using the internet for >4 hours a day, 96.5% used a smartphone for internet usage, and 52.4% used the internet for leisure (Table 1).

In the simple logistic regression analysis, internet addiction was associated with a family history of mental illness (p = 0.043) and anxiety (p = 0.002) [Table 1]. In the multiple logistic regression analysis, only anxiety remained to be associated with internet addiction (adjusted odds ratio = 6.34, p = 0.005), whereas a family history of mental illness became slightly not significant (adjusted odds ratio = 3.03, p = 0.051) [Table 2].

Discussion

The prevalence of internet addiction among house officers in a Malaysian hospital was 18.9%, similar to the 10% among nurses in Turkey,²⁶ the 8% among residents and registrars in India,²⁷ and a meta-analysis study for healthcare professionals,¹⁶ but it was considerably lower than the 48% reported in a study of junior doctors in India.¹⁸ Differences in prevalence across studies may be due to variations in sample sizes, backgrounds of participants, and assessment tools used.^8,16,28

In the present study, internet addiction was associated with a family history of mental illness. Similarly, a study in India found that internet addiction was associated with a dysfunctional family and temperament traits of impulsivity and poor emotional regulation.²⁹ Internet addiction is not associated with age, sex, or duration spent on the internet per day.^17,30 Nonetheless, it is associated with substance abuse such as alcohol use and smoking.³¹

In the present study, among the three components of psychological distress, only anxiety was associated with internet addiction. Previous studies have found associations between internet addiction and psychological distress, particularly anxiety and depression.^32-34 Possible explanations for the lack of association between internet addiction and depression or stress include differences in sample populations, sample size, measurement tools, or cultures. Internet addiction is often comorbid with various psychological symptoms and psychiatric disorders. The severity of internet addiction is positively associated with levels of depression and anxiety.^35,36 There is a reciprocal association between internet addiction and increased anxiety.³⁷

House officers experience various stressors that may exacerbate internet addiction and psychological distress. However, these stressors can be beneficial in optimising their performance. Therefore, the key is to recognise stress that exceeds manageable levels, as individuals have diverse thresholds for coping with stress. Internet addiction can cause socio-occupational dysfunction and psychological distress,¹⁷ particularly among healthcare professionals.^16,27,38

The present study has several limitations. It was conducted in a single hospital in the Klang Valley, which restricts its generalisability to house officers in other regions of Malaysia. Future studies with more representative samples are warranted to enhance the generalisability of findings and explore additional factors associated with internet addiction. The cross-sectional design cannot establish causal relationships between internet addiction and psychological distress; longitudinal studies can be used to explore temporal and causal relationships. Substance dependence, which can influence the prevalence and severity of internet addiction, was not assessed. The effects of internet addiction on the doctor-patient relationship and workplace-related interpersonal conflicts were not evaluated. The DASS-21 is primarily a screening tool for psychological distress rather than a diagnostic instrument. The self-report questions, specifically the duration of internet use per day, may not fully capture the extent of usage and could introduce recall bias. Objective measurements such as screen time data from devices could have been used to improve accuracy and reduce reporting bias.

Strategies to reduce the risk of internet addiction and its effects on mental health include physical activities, limits on screen time, and avoidance of screen exposure at a young age.^39,40 Public health initiatives should prioritise awareness campaigns, stress management programmes, and mental health support services specifically for healthcare settings. Strategies such as limiting screen time, promoting physical activity, and fostering resilience through targeted interventions can mitigate the risks associated with internet addiction and improve overall wellbeing. Policies aimed at screening for and preventing excessive internet use and facilitating early intervention are encouraged. Non-pharmacological approaches including cognitive behavioural therapy, mindfulness practices, and resilience training are beneficial in managing anxiety and internet addiction.

Conclusion

Among house officers in a Malaysian hospital, internet addiction is prevalent and correlates with a family history of mental illness and anxiety. Given the bidirectional relationship between psychological distress and internet addiction, it is crucial to implement comprehensive intervention strategies that integrate mental health support with measures to manage excessive internet use.

Contributors

All authors designed the study, acquired the data, analysed the data, drafted the manuscript, and critically revised the manuscript for important intellectual content. All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

Conflicts of interest

All authors have disclosed no conflicts of interest.

Funding / support

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

All data generated or analysed during the present study are available from the corresponding author on reasonable request.

Ethics approval

This study was approved by the Ethical Board of Research Committee of Universiti Teknologi MARA, the National Medical Research and Ethics Committee of the Ministry of Health in Malaysia through the National Medical Research Registry (reference: 23-00551). The participants provided written informed consent for all treatments and procedures and for publication.

References

1. Branscombe M. The network impact of the global COVID-19 pandemic. The New Stack. 6 June 2020.
2. Young KS. Internet addiction: the emergence of a new clinical disorder. Cyberpsychol Behav 1998;1:237-44.
3. Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M. Proposed diagnostic criteria for internet addiction. Addiction 2010;105:556-64.
4. Meng SQ, Cheng JL, Li YY, et al. Global prevalence of digital addiction in general population: a systematic review and meta-analysis. Clin Psychol Rev 2022;92:102128.
5. Digital 2023: Malaysia. Assessed 7 February 2024. Available from: https://datareportal.com/reports/digital-2023-malaysia.
6. Nik Jaafar NR, Bahar N, Ibrahim N, et al. Are Malaysian youths overdependent on the internet? A narrative review. Front Psychiatry 2021;21:710790.
7. Zenebe Y, Kunno K, Mekonnen M, et al. Prevalence and associated factors of internet addiction among undergraduate university students in Ethiopia: a community university-based cross-sectional study. BMC Psychol 2021;9:4.
8. Lozano-Blasco R, Robres AQ, Sánchez AS. Internet addiction in young adults: a meta-analysis and systematic review. Comput Human Behav 2022;130:107201.
9. Petruzelka B, Vacek J, Gavurova B, et al. Interaction of socioeconomic status with risky internet use, gambling and substance use in adolescents from a structurally disadvantaged region in central Europe. Int J Environ Res Public Health 2020;17:4803.
10. Kwak Y, Kim H, Ahn JW. Impact of Internet usage time on mental health in adolescents: using the 14th Korea Youth Risk Behavior Web- Based Survey 2018. PLoS One 2022;17:e0264948.
11. Guo W, Tao Y, Li X, et al. Associations of internet addiction severity with psychopathology, serious mental illness, and suicidality: large- sample cross-sectional study. J Med Internet Res 2020;22:e17560.
12. Ithnain N, Ghazali S, Jaafar N. Relationship between smartphone addiction with anxiety and depression among undergraduate students in Malaysia. Int J Health Sci Res 2018;8:163-71.
13. Ridner SH. Psychological distress: concept analysis. J Adv Nurs 2004;45:536-45.
14. Schou-Bredal I, Bonsaksen T, Ekeberg Ø, Skogstad L, Grimholt TK, Heir T. A comparison between healthcare workers and non-healthcare workers’ anxiety, depression and PTSD during the initial COVID-19 lockdown. Public Health Pract (Oxf) 2022;3:100267.
15. Ali NF, Raduan NJN, Razali S, Ismail Z. Psychological distress and burnout. The duo phenomena among medical officers in a tertiary hospital In Malaysia. ASEAN J Psychiatry 2021;22:1-12.
16. Buneviciene I, Bunevicius A. Prevalence of internet addiction in healthcare professionals: systematic review and meta-analysis. Int J Soc Psychiatry 2021;67:483-91.
17. Prakash S. Internet addiction among junior doctors: a cross-sectional study. Indian J Psychol Med 2017;39:422-5.
18. Daniel P. Pattern of internet use and prevalence of internet addiction among interns of a medical college in Kerala. Int J Community Med Public Health 2019;6:1928-32.
19. Dunning A, Teoh K, Martin J, et al. Relationship between working conditions and psychological distress experienced by junior doctors in the UK during the COVID-19 pandemic: a cross-sectional survey study. BMJ Open 2022;12:e061331.
20. Bartholomew A, Sanatkar S, Counson I, Harvey SB. Junior doctors’ mental health and coronavirus disease safety concerns. Aust N Z J Public Health 2022;46:307-13.
21. Hunter R, Willis K, Smallwood N. The workplace and psychosocial experiences of Australian junior doctors during the COVID-19 pandemic. Intern Med J 2022;52:745-54.
22. Roslan NS, Yusoff MSB, Ab Razak A, et al. Training characteristics, personal factors and coping strategies associated with burnout in junior doctors: a multi-center study. Healthcare (Basel) 2021;9:1208.
23. Guan NC, Isa SM, Hashim AH, Pillai SK, Harbajan Singh MK. Validity of the Malay version of the Internet Addiction Test: a study on a group of medical students in Malaysia. Asia Pac J Public Health 2015;27:NP2210-9.
24. Musa R, Fadzil MA, Zain Z. Translation, validation and psychometric properties of Bahasa Malaysia version of the depression, anxiety and stress scales (DASS). ASEAN J Psychiatry 2007;8:82-9.
25. Rusli BN, Amrina K, Trived S, Loh KP, Shashi M. Construct validity and internal consistency reliability of the Malay version of the 21-item depression anxiety stress scale (Malay-DASS-21) among male outpatient clinic attendees in Johor. Med J Malaysia 2017;72:264-70.
26. Kaynak S, Duran S, Karadaş A. Determination of the relationship between internet addiction and the level of loneliness among nurses. Sağlık ve Hemşirelik Yönetimi Dergisi 2018;5:27-35.
27. Grover S, Sahoo S, Bhalla A, Avasthi A. Problematic internet use and its correlates among resident doctors of a tertiary care hospital of North India: a cross-sectional study. Asian J Psychiatr 2019;39:42-7.
28. Pan YC, Chiu YC, Lin YH. Systematic review and meta-analysis of epidemiology of internet addiction. Neurosci Biobehav Rev 2020;118:612-22.
29. Rathi M, Guha P, Neogi R. Internet addiction in adolescents: role of family, personality and comorbid psychopathology in school children in Eastern India. Indian J Psychiatry 2022;64:408-14.
30. Schmidt G, Valdez M, Farrell M, Bishop F, Klam WP, Doan AP. Behaviors associated with internet use in military medical students and residents. Mil Med 2019;184:750-7.
31. Toth G, Kapus K, Hesszenberger D, et al. Internet addiction and burnout in a single hospital: is there any association? Int J Environ Res Public Health 2021;18:615.
32. Ansari F, Ismail MAA, Yusoff MSB, Fadzil A. Prevalence of internet addiction and its relationship with psychological distress among medical students in a Malaysian public university. Educ Med J 2022;14:19-29.
33. Fekih-Romdhane F, Away R, Jahrami H, Cheour M. Internet addiction is associated with psychological distress in highly schizotypal students. Early Interv Psychiatry 2023;17:681-91.
34. Andrade ALM, Scatena A, Bedendo A, et al. Findings on the relationship between internet addiction and psychological symptoms in Brazilian adults. Int J Psychol 2020;55:941-50.
35. Evren C, Evren B, Dalbudak E, Topcu M, Kutlu N. Relationships of internet addiction and internet gaming disorder symptom severities with probable attention deficit/hyperactivity disorder, aggression and negative affect among university students. Atten Defic Hyperact Disord 2019;11:413-21.
36. Karaer Y, Akdemir D. Parenting styles, perceived social support and emotion regulation in adolescents with internet addiction. Compr Psychiatry 2019;92:22-7.
37. Gao T, Qin Z, Hu Y, et al. Trajectories of depression and anxiety in Chinese high school freshmen: associations with internet addiction. J Affect Disord 2021;286:180-6.
38. Eka Prasetya TA, Kusuma Wardani RW. Systematic review of social media addiction among health workers during the pandemic Covid-19. Heliyon 2023;9:e16784.
39. Shi J, van der Maas M, Yu L, Jiang Q, Agasee S, Turner NE. Current prevention strategies and future directions for problem internet use. Curr Opin Behav Sci 2022;48:101231.
40. Throuvala MA, Griffiths MD, Rennoldson M, Kuss DJ. School-based prevention for adolescent internet addiction: prevention is the key. a systematic literature review. Curr Neuropharmacol 2019;17:507-25.