Advertisement

A Tool to Help or Harm? Online Social Media Use and Adult Mental Health in Indonesia

  • Sujarwoto SujarwotoEmail author
  • Gindo Tampubolon
  • Adi Cilik Pierewan
Original Article

Abstract

The effect of online social media use on individual mental health remains contested. This study examines the effect of online social media (Facebook, Twitter and chat) on adult mental health in Indonesia. Instrumental variable analysis was used to address reverse causality issues. Data come from the Indonesia Family Life Survey (IFLS) 2014, which polled 22,423 individuals age 20 years and older in 9987 households and 297 districts in Indonesia. The findings show that social media use harms adult mental health; an increase of one standard deviation in adult use of social media is associated with 9% increase in CES-D score. The effect is robust with respect to an extensive set of individual, household, community and district covariates. The findings suggest that policies offering advice to wise use of online social media are needed to protect adults from the harmful effects of online social media on their mental health.

Keywords

Online social media Mental health Instrumental variable analysis 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

This study used public source data. Thus, this article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. Almedom, A. M. (2005). Social capital and mental health: An interdisciplinary review of primary evidence. Social Science & Medicine, 61(5), 943–964.Google Scholar
  2. Andresen, E. M., Malmgren, J. A., Carter, W. B., & Patrick, D. L. (1994). Screening for depression in well older adults: Evaluation of a short form of the CES-D. American journal of preventive medicine., 10, 77–84.Google Scholar
  3. APJII. (2016). Survey pengguna Internet Indonesia. Jakarta: APJII.Google Scholar
  4. Araya, R., Lewis, G., Rojas, G., & Fritsch, R. (2003). Education and income: Which is more important for mental health? Journal of Epidemiology and Community Health, 57(7), 501–505.Google Scholar
  5. Baum, C. F. (2006). An introduction to modern econometrics using Stata: Stata press.Google Scholar
  6. Bechtel, L., Lordan, G., & Rao, D. P. (2012). Income inequality and mental health: School of Economics, University of Queensland.Google Scholar
  7. Bergin, A. E. (1983). Religiosity and mental health: A critical reevaluation and meta-analysis. Professional Psychology: Research and Practice, 14(2), 170–184.Google Scholar
  8. Bradley, N., & Poppen, W. (2003). Assistive technology, computers and Internet may decrease sense of isolation for homebound elderly and disabled persons. Technology and Disability, 15(1), 19–25.Google Scholar
  9. Bromet, E., Andrade, L. H., Hwang, I., Sampson, N. A., Alonso, J., De Girolamo, G., et al. (2011). Cross-national epidemiology of DSM-IV major depressive episode. BMC Medicine, 9(1), 1.Google Scholar
  10. Burki, T. K. (2016). Smoking and mental health. The Lancet Respiratory medicine.Google Scholar
  11. Califano, J. A., Jr., Bush, C., Chenault, K. I., Dimon, J., Fisher, M., Fraser, D. A., et al. (2001). So help me God: Substance abuse, religion and spirituality. Chairperson and President of the National Center on Addiction and Substance Abuse. New York: Columbia University.Google Scholar
  12. Case, A., Fertig, A., & Paxson, C. (2005). The lasting impact of childhood health and circumstance. Journal of Health Economics, 24(2), 365–389.Google Scholar
  13. Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357.Google Scholar
  14. Cotten, S. (2009). Using ICTs to enhance quality of life among older adults: Preliminary results from a randomized controlled trial. Paper presented at the Annual Meeting of the Gerontological Society of America.Google Scholar
  15. Cotten, S. R., Ford, G., Ford, S., & Hale, T. M. (2012). Internet use and depression among older adults. Computers in Human Behavior, 28(2), 496–499.Google Scholar
  16. Das, J., Do, Q.-T., Friedman, J., McKenzie, D., & Scott, K. (2007). Mental health and poverty in developing countries: Revisiting the relationship. Social Science & Medicine, 65(3), 467–480.Google Scholar
  17. Dein, S., Cook, C. C., & Koenig, H. (2012). Religion, spirituality, and mental health: Current controversies and future directions. The Journal of Nervous and Mental Disease, 200(10), 852–855.Google Scholar
  18. DeYoung, C. G., Peterson, J. B., & Higgins, D. M. (2002). Higher-order factors of the Big Five predict conformity: Are there neuroses of health? Personality and Individual Differences, 33(4), 533–552.Google Scholar
  19. DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010). Testing predictions from personality neuroscience brain structure and the big five. Psychological Science, 21, 820–828.Google Scholar
  20. d'Hombres, B., Rocco, L., Suhrcke, M., & McKee, M. (2010). Does social capital determine health? Evidence from eight transition countries. Health Economics, 19(1), 56–74.Google Scholar
  21. Dickinson, A., & Gregor, P. (2006). Computer use has no demonstrated impact on the well-being of older adults. International Journal of Human-Computer Studies, 64(8), 744–753.Google Scholar
  22. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125(2), 276–302.Google Scholar
  23. Draper, B., Pfaff, J. J., Pirkis, J., Snowdon, J., Lautenschlager, N. T., Wilson, I., & Almeida, O. P. (2008). Long-term effects of childhood abuse on the quality of life and health of older people: Results from the Depression and Early Prevention of Suicide in General Practice Project. Journal of the American Geriatrics Society, 56(2), 262–271.Google Scholar
  24. Dzator, J. (2013). Hard times and common mental health disorders in developing countries: Insights from urban Ghana. The Journal of Behavioral Health Services & Research, 40(1), 71–87.Google Scholar
  25. Eastman, J. K., & Iyer, R. (2004). The elderly's uses and attitudes towards the Internet. Journal of Consumer Marketing, 21(3), 208–220.Google Scholar
  26. Ellison, C. G., Boardman, J. D., Williams, D. R., & Jackson, J. S. (2001). Religious involvement, stress, and mental health: Findings from the 1995 Detroit Area Study. Social Forces, 80(1), 215–249.Google Scholar
  27. Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168.Google Scholar
  28. Frankenberg, E., Friedman, J., Gillespie, T., Ingwersen, N., Pynoos, R., Rifai, I. U., et al. (2008). Mental health in Sumatra after the tsunami. American Journal of Public Health, 98(9), 1671–1677.Google Scholar
  29. Gartner, J., Larson, D. B., & Allen, G. D. (1991). Religious commitment and mental health: A review of the empirical literature. Journal of Psychology and Theology., 19, 6–25.Google Scholar
  30. Gosling, S. D., Rentfrow, P. J., & Swann, W. B. (2003). A very brief measure of the Big-Five personality domains. Journal of Research in personality, 37(6), 504–528.Google Scholar
  31. Grieve, R., Indian, M., Witteveen, K., Tolan, G. A., & Marrington, J. (2013). Face-to-face or Facebook: Can social connectedness be derived online? Computers in Human Behavior, 29(3), 604–609.Google Scholar
  32. Hanandita, W., & Tampubolon, G. (2014). Does poverty reduce mental health? An instrumental variable analysis. Social Science & Medicine, 113, 59–67.Google Scholar
  33. Heckman, J. J. (1995). Randomization as an instrumental variable: National Bureau of Economic Research Cambridge. USA: Mass.Google Scholar
  34. Hidayat, B., & Thabrany, H. (2010). Cigarette smoking in Indonesia: Examination of a myopic model of addictive behaviour. International Journal of Environmental Research and Public Health, 7(6), 2473–2485.Google Scholar
  35. Huang, C. (2010). Internet use and psychological well-being: A meta-analysis. Cyberpsychology, Behavior and Social Networking, 13(3), 241–249.Google Scholar
  36. IFLS. (2014). Household survey book 3B. Santa Monica: RAND Corporation.Google Scholar
  37. Jelenchick, L. A., Eickhoff, J. C., & Moreno, M. A. (2013). “Facebook depression?” Social networking site use and depression in older adolescents. Journal of Adolescent Health, 52(1), 128–130.Google Scholar
  38. Jenkins, R., Njenga, F., Okonji, M., Kigamwa, P., Baraza, M., Ayuyo, J., et al. (2012). Prevalence of common mental disorders in a rural district of Kenya, and socio-demographic risk factors. International Journal of Environmental Research and Public Health, 9(5), 1810–1819.Google Scholar
  39. Jordan, A. H., Monin, B., Dweck, C. S., Lovett, B. J., John, O. P., & Gross, J. J. (2011). Misery has more company than people think: Underestimating the prevalence of others’ negative emotions. Personality and Social Psychology Bulletin, 37(1), 120–135.Google Scholar
  40. Jorm, A. F., Rodgers, B., Jacomb, P. A., Christensen, H., Henderson, S., & Korten, A. E. (1999). Smoking and mental health: Results from a community survey. The Medical Journal of Australia, 170(2), 74–77.Google Scholar
  41. Judge, T. A., Heller, D., & Mount, M. K. (2002). Five-factor model of personality and job satisfaction: A meta-analysis. Journal of Applied Psychology, 87(3), 530–541.Google Scholar
  42. Kalpidou, M., Costin, D., & Morris, J. (2011). The relationship between Facebook and the well-being of undergraduate college students. Cyberpsychology, Behavior and Social Networking, 14(4), 183–189.Google Scholar
  43. Kavetsos, G., & Koutroumpis, P. (2011). Technological affluence and subjective well-being. Journal of Economic Psychology, 32(5), 742–753.Google Scholar
  44. Kawachi, I., Berkman, L., & Kawachi, I. (2000). Income inequality and health. Social Epidemiology, 76–94.Google Scholar
  45. Kawachi, I., Ichida, Y., Tampubolon, G., & Fujiwara, T. (2013). Causal inference in social capital research Global Perspectives on Social Capital and Health (pp. 87–121): Springer.Google Scholar
  46. Kessler, R. C., McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., et al. (2010). Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. The British Journal of Psychiatry, 197(5), 378–385.Google Scholar
  47. Koenig, H. G., & Larson, D. B. (2001). Religion and mental health: Evidence for an association. International Review of Psychiatry, 13(2), 67–78.Google Scholar
  48. Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58(1), 49–74.Google Scholar
  49. Lasser, K., Boyd, J. W., Woolhandler, S., Himmelstein, D. U., McCormick, D., & Bor, D. H. (2000). Smoking and mental illness: A population-based prevalence study. JAMA: Journal of the American Medical Association, 284(20), 2606–2610.Google Scholar
  50. Lee, P. S., Leung, L., Lo, V., Xiong, C., & Wu, T. (2011). Internet communication versus face-to-face interaction in quality of life. Social Indicators Research, 100(3), 375–389.Google Scholar
  51. Lim, C., & Putnam, R. D. (2010). Religion, social networks, and life satisfaction. American Sociological Review, 75(6), 914–933.Google Scholar
  52. Lindenauer, P. K., Pekow, P. S., Lahti, M. C., Lee, Y., Benjamin, E. M., & Rothberg, M. B. (2010). Association of corticosteroid dose and route of administration with risk of treatment failure in acute exacerbation of chronic obstructive pulmonary disease. JAMA: Journal of the American Medical Association, 303(23), 2359–2367.Google Scholar
  53. Lou, L. L., Yan, Z., Nickerson, A., & McMorris, R. (2012). An examination of the reciprocal relationship of loneliness and Facebook use among first-year college students. Journal of Educational Computing Research, 46(1), 105–117.Google Scholar
  54. Lousdal, M. L. (2018). An introduction to instrumental variabel assumptions, validation and estimation. Emerging Theme in Epidemiology, 15(1), 1–7.Google Scholar
  55. Lu-Yao, G. L., Albertsen, P. C., Moore, D. F., Shih, W., Lin, Y., DiPaola, R. S., & Yao, S.-L. (2008). Survival following primary androgen deprivation therapy among men with localized prostate cancer. JAMA: Journal of the American Medical Association, 300(2), 173–181.Google Scholar
  56. Mancini, L. (2008). Horizontal inequality and communal violence: Evidence from Indonesian districts Horizontal Inequalities and Conflict (pp. 106–135): Springer,.Google Scholar
  57. Miller, D. L., Scheffler, R., Lam, S., Rosenberg, R., & Rupp, A. (2006). Social capital and health in Indonesia. World Development, 34(6), 1084–1098.Google Scholar
  58. Morahan-Martin, J., & Schumacher, P. (2003). Loneliness and social uses of the Internet. Computers in Human Behavior, 19(6), 659–671.Google Scholar
  59. Mumford, D. B., Nazir, M., Jilani, F., & Baig, I. Y. (1996). Stress and psychiatric disorder in the Hindu Kush: A community survey of mountain villages in Chitral, Pakistan. The British Journal of Psychiatry, 168(3), 299–307.Google Scholar
  60. Murphy, G. C., & Athanasou, J. A. (1999). The effect of unemployment on mental health. Journal of Occupational and Organizational Psychology, 72(1), 83–99.Google Scholar
  61. Nie, N. H., Hillygus, D. S., & Erbring, L. (2002). Internet use, interpersonal relations, and sociability. The Internet in Everyday Life, 215–243.Google Scholar
  62. O'Hara, K. (2004). “Curb cuts” on the information highway: Older adults and the Internet. Technical Communication Quarterly, 13(4), 426–445.Google Scholar
  63. Owen, K. U., & Watson, N. (1995). Unemployment and mental health. Journal of Psychiatric and Mental Health Nursing, 2(2), 63–71.Google Scholar
  64. Pantic, I., Damjanovic, A., Todorovic, J., Topalovic, D., Bojovic-Jovic, D., Ristic, S., & Pantic, S. (2012). Association between online social networking and depression in high school students: Behavioral physiology viewpoint. Psychiatria Danubina, 24(1), 90–93.Google Scholar
  65. Paul, K. I., & Moser, K. (2009). Unemployment impairs mental health: Meta-analyses. Journal of Vocational Behavior, 74(3), 264–282.Google Scholar
  66. Pierce, T. (2009). Social anxiety and technology: Face-to-face communication versus technological communication among teens. Computers in Human Behavior, 25(6), 1367–1372.Google Scholar
  67. Radloff, L. S. (1977). The CES-D scale a self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401.Google Scholar
  68. Rosen, L. D., Whaling, K., Rab, S., Carrier, L. M., & Cheever, N. A. (2013). Is Facebook creating “iDisorders”? The link between clinical symptoms of psychiatric disorders and technology use, attitudes and anxiety. Computers in Human Behavior, 29(3), 1243–1254.Google Scholar
  69. Satcher, D., Friel, S., & Bell, R. (2007). Natural and manmade disasters and mental health. JAMA: Journal of the American Medical Association, 298(21), 2540–2542.Google Scholar
  70. Saunders, P. L., & Chester, A. (2008). Shyness and the internet: Social problem or panacea? Computers in Human Behavior, 24(6), 2649–2658.Google Scholar
  71. Selfhout, M. H., Branje, S. J., Delsing, M., ter Bogt, T. F., & Meeus, W. H. (2009). Different types of internet use, depression, and social anxiety: The role of perceived friendship quality. Journal of Adolescence, 32(4), 819–833.Google Scholar
  72. Shonkoff, J. P., Garner, A. S., Siegel, B. S., Dobbins, M. I., Earls, M. F., McGuinn, L., et al. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246.Google Scholar
  73. Silva, J. S., & Tenreyro, S. (2006). The log of gravity. The Review of Economics and Statistics, 88(4), 641–658.Google Scholar
  74. Semiocast. (2013). Internet growth in Asia. France: Semioscast.Google Scholar
  75. Soldz, S., & Vaillant, G. E. (1999). The big five personality traits and the life course: A 45-year longitudinal study. Journal of Research in Personality, 33(2), 208–232.Google Scholar
  76. Staiger, D. O., & Stock, J. H. (1994). Instrumental variables regression with weak instruments: National Bureau of Economic Research Cambridge, Mass., USA.Google Scholar
  77. Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434–445.Google Scholar
  78. Strauss, J., Witoelar, F., and Sikoki, B. (2016). User’s guide for the Indonesia Family Life Survey, Wave 5. Retrieved from.Google Scholar
  79. Stukel, T. A., Fisher, E. S., Wennberg, D. E., Alter, D. A., Gottlieb, D. J., & Vermeulen, M. J. (2007). Analysis of observational studies in the presence of treatment selection bias: Effects of invasive cardiac management on AMI survival using propensity score and instrumental variable methods. JAMA: Journal of the American Medical Association, 297(3), 278–285.Google Scholar
  80. Sturman, E. D. (2011). Involuntary subordination and its relation to personality, mood, and submissive behavior. Psychological Assessment, 23(1), 262–276.Google Scholar
  81. Sum, S., Mathews, R. M., Hughes, I., & Campbell, A. (2008). Internet use and loneliness in older adults. Cyberpsychology & Behavior, 11(2), 208–211.Google Scholar
  82. Suziedelyte, A. (2012). How does searching for health information on the Internet affect individuals' demand for health care services? Social Science & Medicine, 75(10), 1828–1835.Google Scholar
  83. Tampubolon, G., & Hanandita, W. (2014). Poverty and mental health in Indonesia. Social Science & Medicine, 106, 20–27.Google Scholar
  84. The Ministry of Health. (2015). The Indonesia Basic Health Services 2013. Jakarta: The Ministry of Health.Google Scholar
  85. Thoits, P. A. (1983). Multiple identities and psychological well-being: A reformulation and test of the social isolation hypothesis. American Sociological Review, 48, 174–187.Google Scholar
  86. Thomas, D., Witoelar, F., Frankenberg, E., Sikoki, B., Strauss, J., Sumantri, C., & Suriastini, W. (2012). Cutting the costs of attrition: Results from the Indonesia Family Life Survey. Journal of Development Economics, 98(1), 108–123.Google Scholar
  87. Trocchia, P. J., & Janda, S. (2000). A phenomenological investigation of Internet usage among older individuals. Journal of Consumer Marketing, 17(7), 605–616.Google Scholar
  88. Wall, W. D. (1956). Education and mental health.Google Scholar
  89. Warr, P. (1987). Work, unemployment, and mental health: Oxford University Press.Google Scholar
  90. Williams, A. W., Ware, J. E., Jr., & Donald, C. A. (1981). A model of mental health, life events, and social supports applicable to general populations. Journal of Health and Social Behavior, 22, 324–336.Google Scholar
  91. Windmeijer, F. A., & Santos Silva, J. M. (1997). Endogeneity in count data models: An application to demand for health care. Journal of Applied Econometrics, 12(3), 281–294.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Sujarwoto Sujarwoto
    • 1
    Email author
  • Gindo Tampubolon
    • 2
  • Adi Cilik Pierewan
    • 3
  1. 1.Portsmouth Brawijaya Centre for Global Health, Population and PolicyUniversity of Brawijaya Malang IndonesiaMalangIndonesia
  2. 2.GDI University of ManchesterManchesterEngland
  3. 3.Universitas Negeri Yogyakarta IndonesiaYogyakartaIndonesia

Personalised recommendations