Skip to main content

Advertisement

SpringerLink
Log in

Can Heart Rate Variability be Viewed as a Biomarker of Problematic Internet Use? A Systematic Review and Meta-Analysis

  • Published:
Applied Psychophysiology and Biofeedback Aims and scope Submit manuscript

Abstract

Heart rate variability (HRV) has been used to explore the parasympathetic activity of individuals with problematic Internet use (PIU), but the results are controversial. We conducted a systematic review and meta-analysis of studies comparing HRV in PIU individuals and healthy participants from several databases. HRV was analyzed according to the parasympathetic activity in hierarchical order (primary analysis), and the total variability (secondary analysis). The baseline HRV and HRV reactivity were both considered. Of the 106 studies screened, 12 were included in the quantitative analysis. Significant differences were observed for baseline HRV in PIU individuals compared to the controls. Regarding HRV reactivity, PIU individuals did not have a significantly lower HRV value during pleasant or unpleasant stimuli. In summary, PIU individuals and healthy subjects had significantly different resting state parasympathetic activity. The finding of HRV reactivity in PIU individuals awaits further investigation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Aarseth, E., Bean, A. M., Boonen, H., Colder Carras, M., Coulson, M., Das, D., et al. (2017). Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal. J Behav Addict, 6(3), 267–270. doi: https://doi.org/10.1556/2006.5.2016.088

    Article  Google Scholar 

  • Alvares, G. A., Quintana, D. S., Hickie, I. B., & Guastella, A. J. (2016). Autonomic nervous system dysfunction in psychiatric disorders and the impact of psychotropic medications: a systematic review and meta-analysis. Journal Of Psychiatry And Neuroscience, 41(2), 89–104

    Article  Google Scholar 

  • American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA: American Psychiatric Association

    Book  Google Scholar 

  • Byun, S., Ruffini, C., Mills, J. E., Douglas, A. C., Niang, M., Stepchenkova, S., et al. (2009). Internet addiction: Metasynthesis of 1996–2006 quantitative research. Cyberpsychology & Behavior : The Impact Of The Internet, Multimedia And Virtual Reality On Behavior And Society, 12(2), 203–207. doi: https://doi.org/10.1089/cpb.2008.0102

    Article  Google Scholar 

  • Cash, H., Rae, C. D., Steel, A. H., & Winkler, A. (2012). Internet addiction: A brief summary of research and practice. Curr Psychiatry Rev, 8(4), 292–298. doi: https://doi.org/10.2174/157340012803520513

    Article  Google Scholar 

  • Chang, J. S., Kim, E. Y., Jung, D., Jeong, S. H., Kim, Y., Roh, M. S., et al. (2015). Altered cardiorespiratory coupling in young male adults with excessive online gaming. Biological Psychology, 110, 159–166. doi: https://doi.org/10.1016/j.biopsycho.2015.07.016

    Article  Google Scholar 

  • Cheng, Y. C., Huang, Y. C., & Huang, W. L. (2019). Heart rate variability as a potential biomarker for alcohol use disorders: A systematic review and meta-analysis. Drug And Alcohol Dependence, 204, 107502

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Earlbaum Associates

    Google Scholar 

  • de Greck, M., Enzi, B., Prosch, U., Gantman, A., Tempelmann, C., & Northoff, G. (2010). Decreased neuronal activity in reward circuitry of pathological gamblers during processing of personal relevant stimuli. Human Brain Mapping, 31(11), 1802–1812. doi: https://doi.org/10.1002/hbm.20981

    Article  Google Scholar 

  • Eddie, D., Kim, C., Lehrer, P., Deneke, E., & Bates, M. E. (2014). A pilot study of brief heart rate variability biofeedback to reduce craving in young adult men receiving inpatient treatment for substance use disorders. Applied Psychophysiology And Biofeedback, 39(3/4), 181–192. doi: https://doi.org/10.1007/s10484-014-9251-z

    Article  Google Scholar 

  • Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. Bmj, 315(7109), 629–634. doi: https://doi.org/10.1136/bmj.315.7109.629

    Article  Google Scholar 

  • Haghshomar, M., & Rahmani, F. (2017). Cognitive challenge to choose healthier food is reflected in heart rate variability. Front Neurosci, 11, 353. doi: https://doi.org/10.3389/fnins.2017.00353

    Article  Google Scholar 

  • Higgins, J. P., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics In Medicine, 21(11), 1539–1558. doi: https://doi.org/10.1002/sim.1186

    Article  Google Scholar 

  • Hong, S. J., Lee, D. K., Park, J. S., Namkoong, K., Lee, J. S., Jang, D. P., et al. (2018). Altered heart rate variability during gameplay in Internet gaming disorder: The impact of situations during the game. Frontiers In Psychiatry, 9, 429–429. doi: https://doi.org/10.3389/fpsyt.2018.00429

    Article  Google Scholar 

  • Hsieh, D. L., & Hsiao, T. C. (2016a). Heart rate variability of Internet gaming disorder addicts in emotional states. Paper presented at the 2016 International Conference on Biomedical Engineering (BME-HUST), 5–6 October 2016

  • Hsieh, D. L., & Hsiao, T. C. (2016b). Respiratory sinus arrhythmia reactivity of Internet addiction abusers in negative and positive emotional states using film clips stimulation. Biomed Eng Online 15. doi: ARTN 6910.1186/s12938-016-0201-2

  • Huang, W. L., Liao, S. C., Yang, C. C., Kuo, T. B., Chen, T. T., Chen, I. M., & Gau, S. S. (2017). Measures of heart rate variability in individuals with somatic symptom disorder. Psychosomatic Medicine, 79(1), 34–42. doi: https://doi.org/10.1097/PSY.0000000000000362

    Article  Google Scholar 

  • Kannan, B., Karthik, S., Pal, G. K., & Menon, V. (2019). Gender variation in the prevalence of Internet addiction and impact of Internet addiction on reaction time and heart rate variability in medical college students. J Clin Diagn Res, 13(4), 1–4. doi: https://doi.org/10.7860/JCDR/2019/40839.12753

    Article  Google Scholar 

  • Kemp, A. H., & Quintana, D. S. (2013). The relationship between mental and physical health: insights from the study of heart rate variability. International Journal Of Psychophysiology, 89(3), 288–296. doi: https://doi.org/10.1016/j.ijpsycho.2013.06.018

    Article  Google Scholar 

  • Kennedy, D., Goshko, C. B., Murch, W. S., Limbrick-Oldfield, E. H., Dunn, B. D., & Clark, L. (2019). Interoception and respiratory sinus arrhythmia in gambling disorder. Psychophysiology, 56(6), e13333. doi: https://doi.org/10.1111/psyp.13333

    Article  Google Scholar 

  • Kim, N., Hughes, T. L., Park, C. G., Quinn, L., & Kong, I. D. (2016). Altered autonomic functions and distressed personality traits in male adolescents with Internet gaming addiction. Cyberpsychol Behav Soc Netw, 19(11), 667–673. doi: https://doi.org/10.1089/cyber.2016.0282

    Article  Google Scholar 

  • Kim, H., Ha, J., Chang, W. D., Park, W., Kim, L., & Im, C. H. (2018). Detection of craving for gaming in adolescents with Internet gaming disorder using multimodal biosignals. Sensors (Basel), 18(1), doi: https://doi.org/10.3390/s18010102

  • Ko, C. H., Yen, J. Y., Yen, C. F., Chen, C. C., Yen, C. N., & Chen, S. H. (2005). Screening for Internet addiction: An empirical study on cut-off points for the Chen Internet Addiction Scale. Kaohsiung Journal Of Medical Sciences, 21(12), 545–551. doi: https://doi.org/10.1016/S1607-551X(09)70206-2

    Article  Google Scholar 

  • Ko, C. H., Yen, J. Y., Chen, S. H., Yang, M. J., Lin, H. C., & Yen, C. F. (2009). Proposed diagnostic criteria and the screening and diagnosing tool of Internet addiction in college students. Compr Psychiatry, 50(4), 378–384. doi: https://doi.org/10.1016/j.comppsych.2007.05.019

    Article  Google Scholar 

  • Ko, C. H., Yen, J. Y., Chen, S. H., Wang, P. W., Chen, C. S., & Yen, C. F. (2014). Evaluation of the diagnostic criteria of Internet gaming disorder in the DSM-5 among young adults in Taiwan. Journal Of Psychiatric Research, 53, 103–110. doi: https://doi.org/10.1016/j.jpsychires.2014.02.008

    Article  Google Scholar 

  • Kuss, D. J., & Lopez-Fernandez, O. (2016). Internet addiction and problematic Internet use: A systematic review of clinical research. World J Psychiatry, 6(1), 143–176. doi: https://doi.org/10.5498/wjp.v6.i1.143

    Article  Google Scholar 

  • Laborde, S., Mosley, E., & Thayer, J. F. (2017). Heart rate variability and cardiac vagal tone in psychophysiological research: Recommendations for experiment planning, data analysis, and data reporting. Frontiers In Psychology, 8, 213. doi: https://doi.org/10.3389/fpsyg.2017.00213

    Article  Google Scholar 

  • Larimer, M. E., Palmer, R. S., & Marlatt, G. A. (1999). Relapse prevention; An overview of Marlatt’s cognitive-behavioral model. Alcohol Research & Health, 23(2), 151–160

    Google Scholar 

  • Lee, D., Hong, S. J., Jung, Y. C., Park, J., Kim, I. Y., & Namkoong, K. (2018). Altered heart rate variability during gaming in Internet gaming disorder. Cyberpsychol Behav Soc Netw, 21(4), 259–267. doi: https://doi.org/10.1089/cyber.2017.0486

    Article  Google Scholar 

  • Lin, P. C., Kuo, S. Y., Lee, P. H., Sheen, T. C., & Chen, S. R. (2014). Effects of Internet addiction on heart rate variability in school-aged children. Journal Of Cardiovascular Nursing, 29(6), 493–498. doi: https://doi.org/10.1097/JCN.0b013e3182a477d5

    Article  Google Scholar 

  • Lu, D. W., Wang, J. W., & Huang, A. C. (2010). Differentiation of Internet addiction risk level based on autonomic nervous responses: The Internet-addiction hypothesis of autonomic activity. Cyberpsychol Behav Soc Netw, 13(4), 371–378. doi: https://doi.org/10.1089/cyber.2009.0254

    Article  Google Scholar 

  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ 339, b2535. doi: https://doi.org/10.1136/bmj.b2535

  • Moretta, T., & Buodo, G. (2018). Autonomic stress reactivity and craving in individuals with problematic Internet use. PLoS One, 13(1), e0190951. doi: https://doi.org/10.1371/journal.pone.0190951

    Article  Google Scholar 

  • Moretta, T., Sarlo, M., & Buodo, G. (2019). Problematic Internet use: The relationship between resting heart rate variability and emotional modulation of inhibitory control. Cyberpsychol Behav Soc Netw 22(7), 500–507. doi: 0.1089/cyber.2019.0059

  • Nunan, D., Sandercock, G. R., & Brodie, D. A. (2010). A quantitative systematic review of normal values for short-term heart rate variability in healthy adults. Pacing And Clinical Electrophysiology, 33(11), 1407–1417. doi: https://doi.org/10.1111/j.1540-8159.2010.02841.x

    Article  Google Scholar 

  • Park, S. M., Lee, J. Y., Choi, A. R., Kim, B. M., Chung, S. J., Park, M., et al. (2019). Maladaptive neurovisceral interactions in patients with Internet gaming disorder: A study of heart rate variability and functional neural connectivity using the graph theory approach. Addict Biol e12805. doi: https://doi.org/10.1111/adb.12805

  • Przybylski, A. K., Weinstein, N., & Murayama, K. (2017). Internet gaming disorder: Investigating the clinical relevance of a new phenomenon. American Journal Of Psychiatry, 174(3), 230–236. doi: https://doi.org/10.1176/appi.ajp.2016.16020224

    Article  Google Scholar 

  • Quintana, D. S., Alvares, G. A., & Heathers, J. A. (2016). Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH): Recommendations to advance research communication. Transl Psychiatry, 6, e803. doi: https://doi.org/10.1038/tp.2016.73

    Article  Google Scholar 

  • Sakaki, M., Yoo, H. J., Nga, L., Lee, T. H., Thayer, J. F., & Mather, M. (2016). Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults. Neuroimage, 139, 44–52. doi: https://doi.org/10.1016/j.neuroimage.2016.05.076

    Article  Google Scholar 

  • Shapira, N. A., Goldsmith, T. D., Keck, P. E. Jr., Khosla, U. M., & McElroy, S. L. (2000). Psychiatric features of individuals with problematic Internet use. Journal Of Affective Disorders, 57(1–3), 267–272. doi: https://doi.org/10.1016/s0165-0327(99)00107-x

    Article  Google Scholar 

  • Stang, A. (2010). Critical evaluation of the Newcastle-Ottawa Scale for the assessment of the quality of nonrandomized studies in meta-analyses. European Journal Of Epidemiology, 25(9), 603–605. doi: https://doi.org/10.1007/s10654-010-9491-z

    Article  Google Scholar 

  • Wang, Y., & Gao, W. B. (2008). A study of heart rate variability frequency field characteristics of Internet addicts. Chin J Clin Psychol, 16(3), 316–318

    Google Scholar 

  • Weiss, F., Aslan, A., Zhang, J. Y., Gerchen, M. F., Kiefer, F., & Kirsch, P. (2020). Using mind control to modify cue-reactivity in AUD: The impact of mindfulness-based relapse prevention on real-time fMRI neurofeedback to modify cue-reactivity in alcohol use disorder: A randomized controlled trial. BMC Psychiatry 20(1). doi: ARTN 30910.1186/s12888-020-02717-7

  • Widyanto, L., & McMurran, M. (2004). The psychometric properties of the Internet addiction test. Cyberpsychology & Behavior : The Impact Of The Internet, Multimedia And Virtual Reality On Behavior And Society, 7(4), 443–450. doi: https://doi.org/10.1089/cpb.2004.7.443

    Article  Google Scholar 

  • Young, K. S. (1999). The research and controversy surrounding Internet addiction. Cyberpsychology & Behavior : The Impact Of The Internet, Multimedia And Virtual Reality On Behavior And Society, 2(5), 381–383. doi: https://doi.org/10.1089/cpb.1999.2.381

    Article  Google Scholar 

  • Young, K. S. (2017). The evolution of Internet addiction. Addictive Behaviors, 64, 229–230. doi: https://doi.org/10.1016/j.addbeh.2015.05.016

    Article  Google Scholar 

  • Zhou, N., Cao, H., Li, X., Zhang, J., Yao, Y., Geng, X., et al. (2018). Internet addiction, problematic Internet use, nonproblematic Internet use among Chinese adolescents: Individual, parental, peer, and sociodemographic correlates. Psychology Of Addictive Behaviors, 32(3), 365–372. doi: https://doi.org/10.1037/adb0000358

    Article  Google Scholar 

Download references

Acknowledgements

We thank Professor Tzu-Chien Hsiao for help with data collection.

Funding

None.

Author information

Authors and Affiliations

  1. Department of Psychiatry, China Medical University Hsinchu Hospital, China Medical University, Hsinchu, Taiwan

    Ying-Chih Cheng

  2. Department of Public Health, Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan

    Ying-Chih Cheng

  3. Research Center of Big Data and Meta-Analysis, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan

    Ying-Chih Cheng & Yu-Chen Huang

  4. Department of Dermatology, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan

    Yu-Chen Huang

  5. Department of Dermatology, School of Medicine and College of Medicine, Taipei Medical University, Taipei, Taiwan

    Yu-Chen Huang

  6. Department of Psychiatry, National Taiwan University Hospital Yunlin Branch, No. 579, Sec. 2, Yunlin Rd, Yunlin County 640, Douliu, Yunlin, Taiwan

    Wei-Lieh Huang

  7. Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan

    Wei-Lieh Huang

  8. Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan

    Wei-Lieh Huang

  9. Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan

    Wei-Lieh Huang

  10. Cerebellar Research Center, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan

    Wei-Lieh Huang

Authors
  1. Ying-Chih Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu-Chen Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei-Lieh Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Y.-C. Cheng and W.-L. Huang reviewed the literature and designed the study; Y.-C. Cheng and Y.-C. Huang analyzed and interpreted the data; and Y.-C. Cheng and W.-L. Huang drafted the manuscript.

Corresponding author

Correspondence to Wei-Lieh Huang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheng, YC., Huang, YC. & Huang, WL. Can Heart Rate Variability be Viewed as a Biomarker of Problematic Internet Use? A Systematic Review and Meta-Analysis. Appl Psychophysiol Biofeedback 48, 1–10 (2023). https://doi.org/10.1007/s10484-022-09557-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10484-022-09557-z

Keywords

Search

Navigation