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Piloting Smartphone Digital Phenotyping to Understand Problematic Internet Use in an Adolescent and Young Adult Sample

Child Psychiatry & Human Development volume 54, pages 997–1004 (2023)Cite this article

Abstract

Problematic Internet use (PIU) preferentially affects youth development, particularly youth with psychiatric conditions. Studies attempting to understand PIU and its impact on adolescent mental health have been limited by cross-sectional design and self-report data. Even with a small sample size, digital phenotyping (DP) methodology can address these limitations through repeated sampling and collection of survey and sensor data through personal smartphones. This study pilots a 6-week DP protocol in 28 youth in mental health treatment in order to assess relationships between PIU, mood symptoms, and daily behaviors like smartphone engagement and daily travel in this high-risk population. Our results found shared associations between depression and PIU, where symptom severity of both worsened in the setting of decreased smartphone engagement. These clinically relevant findings indicate that, rather than uniformly worsening mental health, increased digital engagement may actually provide short-term relief from negative affect in youth with psychiatric comorbidities.

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References

  1. Shapira NA, Lessig MC, Goldsmith TD et al (2003) Problematic internet use: proposed classification and diagnostic criteria. Depress Anxiety 17:207–216. https://doi.org/10.1002/da.10094

    Article  PubMed  Google Scholar 

  2. Durkee T, Kaess M, Carli V et al (2012) Prevalence of pathological internet use among adolescents in Europe: demographic and social factors. Addiction 107:2210–2222. https://doi.org/10.1111/j.1360-0443.2012.03946.x

    Article  PubMed  Google Scholar 

  3. Moreno MA, Jelenchick L, Cox E et al (2011) Problematic internet use among US youth: a systematic review. Arch Pediatr Adolesc Med 165:797–805. https://doi.org/10.1001/archpediatrics.2011.58

    Article  PubMed  PubMed Central  Google Scholar 

  4. Vigna-Taglianti F, Brambilla R, Priotto B et al (2017) Problematic internet use among high school students: prevalence, associated factors and gender differences. Psychiatry Res 257:163–171. https://doi.org/10.1016/j.psychres.2017.07.039

    Article  PubMed  Google Scholar 

  5. Rideout V, Robb M (2019) The common sense census: media use by tweens and teens. commonsense media, San Francisco

  6. Hammond CJ, Mayes LC, Potenza MN (2015) Neurobiology of adolescent substance use and addictive behaviors: prevention and treatment implications. State of the Art Rev 25(1):15–21

    Google Scholar 

  7. Fuchs M, Riedl D, Bock A et al (2018) Pathological internet use: an important comorbidity in child and adolescent psychiatry: prevalence and correlation patterns in a naturalistic sample of adolescent inpatients. BioMed Res Int. https://doi.org/10.1155/2018/1629147

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gansner M, Belfort E, Cook B et al (2019) Problematic internet use and associated high-risk behavior in an adolescent clinical sample: results from a survey of psychiatrically hospitalized youth. Cyberpsychol Behav Soc Netw 22:349–354. https://doi.org/10.1089/cyber.2018.0329

    Article  PubMed  Google Scholar 

  9. Kim B-N, Park S, Park M-H (2017) The Relationship of sexual abuse with self-esteem, depression, and problematic internet use in Korean adolescents. Psychiatry Investig 14:372–375. https://doi.org/10.4306/pi.2017.14.3.372

    Article  PubMed  PubMed Central  Google Scholar 

  10. Rideout V, Fox S (2018) Digital Health Practices, Social Media Use, and Mental Well-Being Among Teens and Young Adults in the U.S. Hopelab Well Trust 1–95

  11. Wang C-Y, Wu Y-C, Su C-H et al (2017) Association between Internet gaming disorder and generalized anxiety disorder. J Behav Addict 6:564–571. https://doi.org/10.1556/2006.6.2017.088

    Article  PubMed  PubMed Central  Google Scholar 

  12. Yen J-Y, Ko C-H, Yen C-F et al (2007) The comorbid psychiatric symptoms of internet addiction: attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. J Adolesc Health 41:93–98. https://doi.org/10.1016/j.jadohealth.2007.02.002

    Article  PubMed  Google Scholar 

  13. Özaslan A, Yıldırım M, Güney E et al (2021) Association between problematic internet use, quality of parent-adolescents relationship, conflicts, and mental health problems. Int J Ment Health Addict. https://doi.org/10.1007/s11469-021-00529-8

    Article  PubMed  PubMed Central  Google Scholar 

  14. Gao L, Gan Y, Whittal A, Lippke S (2020) Problematic internet use and perceived quality of life: findings from a cross-sectional study investigating work-time and leisure-time internet use. Int J Environ Res Public Health 17:4056. https://doi.org/10.3390/ijerph17114056

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kaye K, Orben A, Ellis D et al (2020) The conceptual and methodological mayhem of “Screen Time.” Int J Environ Res Public Health 17:3661. https://doi.org/10.3390/ijerph17103661

    Article  Google Scholar 

  16. Jeong H, Yim HW, Lee S-Y et al (2018) Discordance between self-report and clinical diagnosis of Internet gaming disorder in adolescents. Sci Rep 8:10084. https://doi.org/10.1038/s41598-018-28478-8

    Article  PubMed  PubMed Central  Google Scholar 

  17. Stone AA, Shiffman S (1994) Ecological momentary assessment (EMA) in behavorial medicine. Ann Behav Med 16:199–202. https://doi.org/10.1093/abm/16.3.199

    Article  Google Scholar 

  18. Insel TR (2018) Digital phenotyping: a global tool for psychiatry. World Psychiatry 17:276–277. https://doi.org/10.1002/wps.20550

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gansner M, Nisenson M, Carson N, Torous J (2020) A pilot study using ecological momentary assessment via smartphone application to identify adolescent problematic internet use. Psychiatry Res 293:113428. https://doi.org/10.1016/j.psychres.2020.113428

    Article  PubMed  Google Scholar 

  20. Barnett I, Torous J, Reeder HT et al (2020) Determining sample size and length of follow-up for smartphone-based digital phenotyping studies. J Am Med Inform Assoc. https://doi.org/10.1093/jamia/ocaa201

    Article  PubMed  PubMed Central  Google Scholar 

  21. Onnela JP Digital phenotyping power calculation. https://onnela-lab.shinyapps.io/digital_phenotyping_sample_size_calculator/. Accessed 23 Nov 2020

  22. Torous J (2020) LAMP. In: Div. Digit. Psychiatry BIDMC. https://www.digitalpsych.org/lamp.html. Accessed 20 Apr 2020

  23. Torous J, Kiang MV, Lorme J, Onnela J-P (2016) New tools for new research in psychiatry: a scalable and customizable platform to empower data driven smartphone research. JMIR Ment Health 3:e16. https://doi.org/10.2196/mental.5165

    Article  PubMed  PubMed Central  Google Scholar 

  24. Demetrovics Z, Király O, Koronczai B et al (2016) Psychometric properties of the problematic internet use questionnaire short-form (PIUQ-SF-6) in a nationally representative sample of adolescents. PLoS ONE. https://doi.org/10.1371/journal.pone.0159409

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bauer AM, Baldwin SA, Anguera JA et al (2018) Comparing approaches to mobile depression assessment for measurement-based care: prospective study. J Med Internet Res 20:e10001. https://doi.org/10.2196/10001

    Article  PubMed  PubMed Central  Google Scholar 

  26. Barnett I, Onnela J-P (2018) Inferring mobility measures from GPS traces with missing data. Biostat Oxf Engl 21:e98–e112. https://doi.org/10.1093/biostatistics/kxy059

    Article  Google Scholar 

  27. Wilcockson TDW, Ellis DA, Shaw H (2018) Determining typical smartphone usage: what data do we need? Cyberpsychol Behav Soc Netw 21:395–398. https://doi.org/10.1089/cyber.2017.0652

    Article  PubMed  Google Scholar 

  28. Kaess M, Durkee T, Brunner R et al (2014) Pathological Internet use among European adolescents: psychopathology and self-destructive behaviours. Eur Child Adolesc Psychiatry 23:1093–1102. https://doi.org/10.1007/s00787-014-0562-7

    Article  PubMed  PubMed Central  Google Scholar 

  29. Tan Y, Chen Y, Lu Y, Li L (2016) Exploring associations between problematic internet use, depressive symptoms and sleep disturbance among southern chinese adolescents. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph13030313

    Article  PubMed  PubMed Central  Google Scholar 

  30. Park M-H, Park S, Jung K-I et al (2018) Moderating effects of depressive symptoms on the relationship between problematic use of the Internet and sleep problems in Korean adolescents. BMC Psychiatry. https://doi.org/10.1186/s12888-018-1865-x

    Article  PubMed  PubMed Central  Google Scholar 

  31. Park S, Hong K-EM, Park EJ et al (2013) The association between problematic internet use and depression, suicidal ideation and bipolar disorder symptoms in Korean adolescents. Aust N Z J Psychiatry 47:153–159. https://doi.org/10.1177/0004867412463613

    Article  PubMed  Google Scholar 

  32. Kupferberg A, Bicks L, Hasler G (2016) Social functioning in major depressive disorder. Neurosci Biobehav Rev 69:313–332. https://doi.org/10.1016/j.neubiorev.2016.07.002

    Article  PubMed  Google Scholar 

  33. Oberle E, Ji XR, Kerai S et al (2020) Screen time and extracurricular activities as risk and protective factors for mental health in adolescence: a population-level study. Prev Med 141:106291. https://doi.org/10.1016/j.ypmed.2020.106291

    Article  PubMed  Google Scholar 

  34. Aşut Ö, Abuduxike G, Acar-Vaizoğlu S, Cali S (2019) Relationships between screen time, internet addiction and other lifestyle behaviors with obesity among secondary school students in the turkish republic of northern cyprus. Turk J Pediatr 61:568. https://doi.org/10.24953/turkjped.2019.04.014

    Article  PubMed  Google Scholar 

  35. Guo N, Luk TT, Wang MP et al (2021) Self-reported screen time on social networking sites associated with problematic smartphone use in Chinese adults: a population-based study. Front Psychiatry 11:614061. https://doi.org/10.3389/fpsyt.2020.614061

    Article  PubMed  PubMed Central  Google Scholar 

  36. Jiang J (2018) How Teens and Parents Navigate Screen Time and Device Distractions. Pew Research Center

  37. Araujo T, Wonneberger A, Neijens P, de Vreese C (2017) How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use. Commun Methods Meas 11:173–190. https://doi.org/10.1080/19312458.2017.1317337

    Article  Google Scholar 

  38. American Psychiatric Association (2013) Diagn. Stat. Man. Ment. Disord.

  39. Onnela J-P, Rauch SL (2016) Harnessing smartphone-based digital phenotyping to enhance behavioral and mental health. Neuropsychopharmacology 41:1691–1696. https://doi.org/10.1038/npp.2016.7

    Article  PubMed  PubMed Central  Google Scholar 

  40. O’Flaherty K (2021) Apple’s stunning iOS 14 privacy move: a game-changer for all iPhone users. In: Forbes. https://www.forbes.com/sites/kateoflahertyuk/2021/01/31/apples-stunning-ios-14-privacy-move-a-game-changer-for-all-iphone-users/. Accessed 19 March 2021

  41. Onnela JP Beiwe-Frequently Asked Questions. https://www.beiwe.org/about/.

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Funding

This study was supported by the DuPont Warren Fellowship and Livingston Award, awarded to Dr. M.G. by the Department of Psychiatry, Harvard Medical School.

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Authors and Affiliations

  1. Department of Psychiatry, Cambridge Health Alliance, 1493 Cambridge Street, Cambridge, MA, 02139, USA

    Meredith Gansner, Melanie Nisenson, Vanessa Lin & Nicholas Carson

  2. Department of Digital Psychiatry, Beth Israel Deaconess Medical Center, 330 Brookline Drive, Boston, MA, 02215, USA

    John Torous

Authors
  1. Meredith Gansner
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  2. Melanie Nisenson
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  3. Vanessa Lin
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  4. Nicholas Carson
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  5. John Torous
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Corresponding author

Correspondence to Meredith Gansner.

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Conflict of interest

Dr. John Torous receives research support from Otsuka Pharmaceuticals for work unrelated to this manuscript. Drs. Gansner and Carson and Ms. Nisenson and Ms. Lin have no competing financial interests or other conflicts of interest to disclose.

Consent to Participate and Publish

Written informed consent was obtained for all participants over 18 years of age. For participants under 18 years of age, parental consent and adolescent assent was obtained.

Ethical Approval

This study was conducted in compliance with the ethical standards as outlined in the latest version of the Declaration of Helsinki. This study was approved by the Cambridge Health Alliance Institutional Review Board on 12/24/2021 for continuing review.

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Gansner, M., Nisenson, M., Lin, V. et al. Piloting Smartphone Digital Phenotyping to Understand Problematic Internet Use in an Adolescent and Young Adult Sample. Child Psychiatry Hum Dev 54, 997–1004 (2023). https://doi.org/10.1007/s10578-022-01313-y

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