Main Article Content

Abstract

Civil servants (PNS) are vulnerable to excessive digital use when doing their job in the COVID-19 pandemic situation, in fact it can have a negative impact on their well-being. Subjective well-being is very important to support the performance of civil servants to be optimal in the organization. However, studies that identify the relationship between the perceived digital overuse and the subjective well-being in civil servants have never been conducted in Indonesia. The purpose of this study was to obtain an overview about the relationship between the perceived digital overuse in general and its dimensions on the subjective well-being in civil servants. The participants of this study were 143 active civil servants who had worked for more than one year in one of the West Java Government Offices. Convenience sampling technique was applied by taking the entire population based on the researcher's criteria carried out as a representative of civil servants who were prone to showing perceived digital overuse during the implementation of Work From Home. This study used a simple regression method which was measured by the Perceived Digital Overuse Questionnaire (Gui & Büchi, 2021) and subjective well-being was measured by using the Warwick–Edinburgh Mental Well-Being Scale (Stewart-Brown et al., 2011). The results show that there is a negative relationship between perceived digital overuse and subjective well-being in civil servants. The dimension of overconsume is the most influential so that it can be a predictor factor on subjective well-being.

Article Details

Author Biographies

Intan Nurliawati, Program Studi Psikologi, Fakultas Psikologi, Universitas Padjadjaran, Bandung

Fakultas Psikologi Program Studi Magister Profesi Psikologi Industri dan Organisasi

Anissa Lestari Kadiyono, Program Studi Psikologi, Fakultas Psikologi, Universitas Padjadjaran, Bandung

Fakultas Psikologi Program Studi Magister Profesi Psikologi Industri dan Organisasi

References

  1. Agustini, P. (2020). Penggunaan internet naik 40% akibat physical distancing. Aptika.Kominfo.Go.Id. https://aptika.kominfo.go.id/2020/04/penggunaan-internet-naik-40-akibat-physical-distancing/
  2. Amichai-Hamburger, Y. (2007). Internet and well-being. Computers in Human Behavior, 23(2), 893–897. https://doi.org/10.1016/j.chb.2005.08.009
  3. Badan Kepegawaian Daerah Provinsi Jawa Barat (BKD Jabar). (2020). Dampak sosial pandemi COVID 19 pada pekerjaan sektor publik. Bkd.Jabarprov.Go.Id. https://bkd.jabarprov.go.id/artikel/202-dampak-sosial-pandemi-COVID-19-pada-pekerjaan-sektor-publik
  4. Bakker, A. B., & Oerlemans, W. G. M. (2011). Subjective well-being in organizations. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199734610.013.0014
  5. Bellis, M. A., Sharp, C. A., Hughes, K., & Davies, A. R. (2021). Digital overuse and addictive traits and their relationship with mental well-being and socio-demographic factors: A national population survey for Wales. Frontiers in Public Health, 9, 585715. https://doi.org/10.3389/fpubh.2021.585715
  6. Büchi, M., Festic, N., & Latzer, M. (2019). Digital overuse and subjective well-being in a digitized society. Social Media and Society, 5(4). https://doi.org/10.1177/2056305119886031
  7. Cacioppo, J. T., & Hawkley, L. (2009). Perceived social isolation and cognition. National of Health Institute Journal, 13(10), 447–454. https://doi.org/10.1016/j.tics.2009.06.005
  8. Chao, C., Kao, K., & Yu, T. (2020). Reactions to problematic internet use among adolescents : Inappropriate physical and mental health perspectives. Frontiers in Psychology, 11(July), 1–12. https://doi.org/10.3389/fpsyg.2020.01782
  9. Davis, R. A. (2001). A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17, 187–195. https://doi.org/10.1016/S0747-5632(00)00041-8
  10. Degryse, C. (2016). Digitalisation of the economy and its impact on labour markets. In European Trade Union Institute. ETUI Brussels. https://doi.org/10.2139/ssrn.2730550
  11. Deursen, A. J. A. M. Van, Bolle, C. L., Hegner, S. M., & Kommers, P. A. M. (2015). Computers in human behavior modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age , and gender. Computers in Human Behavior, 45, 411–420. https://doi.org/10.1016/j.chb.2014.12.039
  12. Diener, E. (2009). The science of subjective well-being: The collected works of Ed Diener. Springer.
  13. Diener, E., Oishi, S., & Lucas, R. E. (2009). Subjective well-being: The cience of happiness and life satisfaction. In S. J. Lopez & C. R. Snyder (Eds.), The Oxford handbook of positive psychology (pp. 186–194). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195187243.013.0017
  14. Douglas, A. C., Mills, J. E., Niang, M., Stepchenkova, S., Byun, S., Ruffini, C., Ki, S., Loutfi, J., Lee, J., Atallah, M., & Blanton, M. (2008). Computers in human behavior Internet addiction : Meta-synthesis of qualitative research for the decade 1996 – 2006. 24, 3027–3044. https://doi.org/10.1016/j.chb.2008.05.009
  15. Eddington, N., & Shuman, R. (2005). Subjective well-being (happiness). Continuing Psychology Education, 858. 1-16.
  16. Graham, M., Dutton, W. H., & Castells, M. (2014). Society and the internet: How networks of information and communication are changing our lives (D. W. C. M. Graham Mark (ed.); First Edit). Oxford University Press .
  17. Gui, M., & Büchi, M. (2021). From use to overuse: Digital inequality in the age of communication abundance. Social Science Computer Review, 39(1), 3–19. https://doi.org/10.1177/0894439319851163
  18. Gui, M., Fasoli, M., & Carradore, R. (2017). Digital well-being: Developing a new theoretical tool for media literacy research. Italian Journal of Sociology of Education, 9(1), 155–173. https://doi.org/10.14658/pupj-ijse-2017-1-8
  19. Hall, J. A., Johnson, R. M., & Ross, E. M. (2018). Where does the time go? An experimental test of what social media displaces and displaced activities’ associations with affective well-being and quality of day. 1–9. https://doi.org/10.1177/1461444818804775
  20. International Telecommunication Union. (2019). Measuring digital development: Facts and figures 2019. ITU Publications. https://www.itu.int/en/ITU-D/Statistics/Documents/facts/FactsFigures2019.pdf
  21. Kardefelt-Winther, D., Heeren, A., Schimmenti, A., Van Rooij, A., Maurage, P., Carras, M., Edman, J., Blaszczynski, A., Khazaal, Y., & Billieux, J. (2017). How can we conceptualize behavioural addiction without pathologizing common behaviours? Addiction, 112(10), 1709–1715. https://doi.org/10.1111/add.13763
  22. Kwon, M., Kim, D.-J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS ONE, 8(12), e83558. https://doi.org/10.1371/journal.pone.0083558
  23. LaRose, R., Connolly, R., Lee, H., Li, K., & Hales, K. D. (2014). Connection overload? A cross cultural study of the consequences of social media connection. Information Systems Management, 31(1), 59–73. https://doi.org/10.1080/10580530.2014.854097
  24. Lissitsa, S., & Chachashvili-Bolotin, S. (2016). Life satisfaction in the internet age – Changes in the past decade. Computers in Human Behavior, 54, 197–206. https://doi.org/10.1016/j.chb.2015.08.001
  25. Ma’rifah, D. (2020). Implementasi Work From Home: Kajian tentang dampak positif, dampak negatif dan produktivitas pegawai. Civil Service, 14, 1–10.
  26. Noor, M. (2015). Memotret data kuantitatif: Untuk skripsi, tesis dan disertasi. CV. Duta Nusindo.
  27. Noordin, F., Rahim, A. R., Ibrahim, A. B., & Omar, M. S. (2011). An analysis of career stages on organisational commitment of Australian managers. International Journal of Business and Social, 2(17), 117–126.
  28. Ofcom. (2016). Communications market report 2016: Bitesize. Ofcom.Org.Uk. http://www.ofcom.org.uk/research/cm/cmr08/
  29. Pavot, W., & Diener, E. (2004). The subjective evaluation of well-being in adulthood: Findings and implications. Ageing International, 29(2), 113–135. https://doi.org/10.1007/s12126-004-1013-4
  30. Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 29(4), 1841–1848. https://doi.org/10.1016/j.chb.2013.02.014
  31. Rao, C., Umar, M., Bhayo, N. H., & Ijaz, M. S. (2019). Smartphone addiction and subjective well-being: A case of international students at Northeast Normal University, China. American Journal of Creative Education, 2, 70–80. https://doi.org/10.20448/815.22.70.80
  32. Reinecke, L., & Oliver, M. B. (2016). The Routledge handbook of media use and well-being: International perspectives on theory and research on positive media effects. In The Routledge handbook of media use and well-being: International perspectives on theory and research on positive media effects (First Edit). Routledge. https://doi.org/10.4324/9781315714752/ROUTLEDGE-HANDBOOK-MEDIA-USE-WELL-BEING-LEONARD-REINECKE-MARY-BETH-OLIVER
  33. Rumata, V. M., & Nugraha, D. A. (2020). Rendahnya tingkat perilaku digital ASN Kementerian Kominfo: Survei literasi digital pada instansi pemerintah. Jurnal Studi Komunikasi (Indonesian Journal of Communications Studies), 4(2), 467. https://doi.org/10.25139/jsk.v4i2.2230
  34. Salo, M., Pirkkalainen, H., & Koskelainen, T. (2019). Technostress and social networking services: Explaining users’ concentration, sleep, identity, and social relation problems. Information Systems Journal, 29(2), 408–435. https://doi.org/10.1111/isj.12213
  35. Scharkow, M. (2019). The reliability and temporal stability of self-reported media exposure: A meta-analysis. Communication Methods and Measures Journal, 1–14. https://doi.org/10.1080/19312458.2019.1594742
  36. Shapira, N. A., Goldsmith, T. D., Keck, P. E., Khosla, U., & McElroy, S. (2000). Psychiatric features of individuals with problematic internet use. Journal of Affective Disorders 57, 57, 267–272. https://doi.org/10.1016/s0165-0327(99)00107-x
  37. Stephens, K. K., Mandhana, D. M., Kim, J. J., & Li, X. (2017). Reconceptualizing communication overload. Communication Theory, 1–21. https://doi.org/10.1111/comt.12116
  38. Stewart-Brown, S., Platt, S., Tennant, A., Maheswaran, H., Parkinson, J., Weich, S., Tennant, R., Taggart, F., & Clarke, A. (2011). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): A valid and reliable tool for measuring mental well-being in diverse populations and projects. Journal of Epidemiology & Community Health, 65(Suppl 2), A38–A39. https://doi.org/10.1136/jech.2011.143586.86
  39. Tateno, M., Teo, A. R., Ukai, W., Kanazawa, J., Katsuki, R., Kubo, H., & Kato, T. A. (2019). Internet addiction, smartphone addiction, and Hikikomori Trait in Japanese young adult: Social Isolation and Social Network. 10(July), 1–11. https://doi.org/10.3389/fpsyt.2019.00455
  40. Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., Parkinson, J., Secker, J., & Stewart-Brown, S. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Development and UK validation. Health and Quality of Life Outcomes, 5(1), 63. https://doi.org/10.1186/1477-7525-5-63
  41. Yeykelis, L., Cummings, J. J., & Reeves, B. (2014). Multitasking on a single device: Arousal and the frequency, anticipation, and prediction of switching between media content on a computer. Journal of Communication, 64(1), 167–192. https://doi.org/10.1111/jcom.12070
  42. Young, K. S. (2004). Behavioral scientist. American Behavioral Scientist, 48(4), 402–415. https://doi.org/10.1177/0002764204270278