Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
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The Role of Time Preferences in Compliance With COVID-19 Preventive Behaviors in Iran: A Quasi-hyperbolic Discounting Approach

  • Moslem Soofi (Social Development and Health Promotion Research Center, Health Policy and Promotion Institute, Kermanshah University of Medical Sciences) ;
  • Ali Kazemi Karyani (Social Development and Health Promotion Research Center, Health Policy and Promotion Institute, Kermanshah University of Medical Sciences) ;
  • Shahin Soltani (Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences) ;
  • Zahra Alipoor (Social Development and Health Promotion Research Center, Health Policy and Promotion Institute, Kermanshah University of Medical Sciences) ;
  • Behzad Karamimatin (Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences)
  • Received : 2024.08.17
  • Accepted : 2025.02.03
  • Published : 2025.05.31
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Abstract

Objectives: This study aimed to investigate the role of time preferences in compliance with coronavirus disease 2019 (COVID-19) preventive behaviors in an adult population of Iran. Methods: A web-based questionnaire was utilized to conduct a cross-sectional survey of 672 Iranian adults. The parameters of time preferences were estimated using a quasi-hyperbolic discounting model, and the relationship between COVID-19 preventive behaviors and time preferences was examined using a probit regression model. Results: A significant association was observed between the preventive behaviors of COVID-19 and the levels of patience and present-biased preferences among the study participants. Individuals who exhibited low levels of patience were found to be 12.8 percentage points less inclined to follow preventive behaviors compared to those with high levels of patience. The likelihood of having good preventive behaviors of COVID-19 was found to decrease by 14.3 percentage points among individuals with a present bias as opposed to those with a bias toward future. Conclusions: Patience and present-biased preferences are important determinants of adopting preventive behaviors against COVID-19. These behavioral characteristics should be considered in the design of control and prevention programs. Considering people's discounting behavior and time (in)consistency in their preferences in the design of COVID-19 policy interventions can provide valuable insights for developing tailored public health policy interventions.

Keywords

Acknowledgement

We would like to express our sincere gratitude to Dr. Wojciech Białaszek, Associate Professor of psychology at SWPS University, Poland, for his valuable comments and constructive feedback on an earlier draft of the manuscript.

References

  1. World Health Organization. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV); 2020 [cited 2024 Jul 10]. Available from: https://www.who.int/news-room/detail/30-01-2020-statement-on-thesecond-meeting-of-the-international-health-regulations(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)
  2. World Health Organization. Iran (Islamic Republic of): response to COVID-19 in Iran [cited 2024 Jul 10]. Available from: https://www.who.int/about/accountability/results/who-results-report-2020-mtr/country-story/2021/iran
  3. Chen Y, Liu Q, Guo D. Emerging coronaviruses: genome structure, replication, and pathogenesis. J Med Virol 2020;92(4):418-423. https://doi.org/10.1002/jmv.25681
  4. Wilder-Smith A, Freedman DO. Isolation, quarantine, social distancing and community containment: pivotal role for old style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med 2020;27(2):taaa020. https://doi.org/10.1093/jtm/taaa020
  5. Šuriņa S, Martinsone K, Perepjolkina V, Kolesnikova J, Vainik U, Ruža A, et al. Factors related to COVID-19 preventive behaviors: a structural equation model. Front Psychol 2021;12:676521. https://doi.org/10.3389/fpsyg.2021.676521
  6. Rojpaisarnkit K, Kaewpan W, Pengpid S, Peltzer K. COVID-19 preventive behaviors and influencing factors in the Thai population: a web-based survey. Front Public Health 2022;10:816464. https://doi.org/10.3389/fpubh.2022.816464
  7. Uddin S, Imam T, Khushi M, Khan A, Ali M. How did socio-demographic status and personal attributes influence compliance to COVID-19 preventive behaviours during the early outbreak in Japan? Lessons for pandemic management. Pers Individ Dif 2021;175:110692. https://doi.org/10.1016/j.paid.2021.110692
  8. Wang D, Marmo-Roman S, Krase K, Phanord L. Compliance with preventative measures during the COVID-19 pandemic in the USA and Canada: results from an online survey. Soc Work Health Care 2021;60(3):240-255. https://doi.org/10.1080/00981389.2020.1871157
  9. Cohen J, Ericson KM, Laibson D, White JM. Measuring time preferences. J Econ Lit 2020;58(2):299-347. https://doi.org/10.1257/jel.20191074
  10. Frederick S, Loewenstein G, O'Donoghue T. Time discounting and time preference: a critical review. J Econ Lit 2002;40(2): 351-401. https://doi.org/10.1257/002205102320161311
  11. Miura T. Does time preference affect smoking behavior? A dynamic panel analysis. J Behav Exp Econ 2019;78:170-180. https://doi.org/10.1016/j.socec.2018.11.001
  12. Bradford D, Courtemanche C, Heutel G, McAlvanah P, Ruhm C. Time preferences and consumer behavior. J Risk Uncertain 2017;55:119-145. https://doi.org/10.1007/s11166-018-9272-8
  13. Shuval K, Drope J, Stoklosa M, Yaroch AL, Pachucki MC, Harding M. Time preferences and physical activity: insights from behavioral economics. Health Behav Policy Rev 2017;4(1):53-59. https://doi.org/10.14485/HBPR.4.1.6
  14. Calluso C, Grande E, Erario A, Tosoni A, Committeri G. Effects of individual discount rate and uncertainty perception on compliance with containment measures during the COVID-19 pandemic. Brain Sci 2021;11(10):1256. https://doi.org/10.3390/brainsci11101256
  15. Lloyd A, McKay R, Hartman TK, Vincent BT, Murphy J, Gibson Miller J, et al. Delay discounting and under-valuing of recent information predict poorer adherence to social distancing measures during the COVID-19 pandemic. Sci Rep 2021;11(1):19237. https://doi.org/10.1038/s41598-021-98772-5
  16. Samuelson PA. A note on measurement of utility. Rev Econ Stud 1937;4(2):155-161. https://doi.org/10.2307/2967612
  17. O'Donoghue T, Rabin M. The economics of immediate gratification. J Behav Decis Mak 2000;13(2):233-250. https://doi.org/10.1002/(SICI)1099-0771(200004/06)13:2<233::AID-BDM325>3.0.CO;2-U
  18. Delaney L, Lades LK. Present bias and everyday self‐control failures: a day reconstruction study. J Behav Decis Mak 2017;30(5):1157-1167. https://doi.org/10.1002/bdm.2031
  19. Loewenstein G, Brennan T, Volpp KG. Asymmetric paternalism to improve health behaviors. JAMA 2007;298(20):2415-2417. https://doi.org/10.1001/jama.298.20.2415
  20. Bradford WD. The association between individual time preferences and health maintenance habits. Med Decis Making 2010;30(1):99-112. https://doi.org/10.1177/0272989X09342276
  21. Laibson D. Golden eggs and hyperbolic discounting. Q J Econ 1997;112(2):443-478. https://doi.org/10.1162/003355397555253
  22. Jeong HJ, Lee WC. The level of collapse we are allowed: comparison of different response scales in safety attitudes questionnaire. Biom Biostat Int J 2016;4(4):128-134.
  23. Kang MI, Ikeda S. Time discounting, present biases, and health related behaviors: evidence from Japan. Econ Hum Biol 2016;21:122-36. https://doi.org/10.1016/j.ehb.2015.09.005
  24. Hardisty DJ, Thompson KF, Krantz DH, Weber EU. How to measure time preferences: an experimental comparison of three methods. Judgm Decis Mak 2013;8(3):236-249. https://doi.org/10.1017/S1930297500005957
  25. Stoklosa M, Shuval K, Drope J, Tchernis R, Pachucki M, Yaroch A, et al. The intergenerational transmission of obesity: the role of time preferences and self-control. Econ Hum Biol 2018;28:92-106. https://doi.org/10.1016/j.ehb.2017.12.004
  26. Dohmen T, Falk A, Huffman D, Sunde U, Schupp J, Wagner GG, et al. Individual risk attitudes: measurement, determinants, and behavioral consequences, J Eur Econ Assoc 2011;9(3):522-550. https://doi.org/10.1111/j.1542-4774.2011.01015.x
  27. Wooldridge JM. Introductory econometrics: a modern approach. 6th ed. Boston: Cengage Learning; 2015, p. 584.
  28. Byrne KA, Six SG, Anaraky RG, Harris MW, Winterlind EL. Risk taking unmasked: using risky choice and temporal discounting to explain COVID-19 preventative behaviors. PLoS One 2021;16(5):e0251073. https://doi.org/10.1371/journal.pone.0251073
  29. Müller S, Rau HA. Economic preferences and compliance in the social stress test of the COVID-19 crisis. J Public Econ 2021;194:104322. https://doi.org/10.1016/j.jpubeco.2020.104322
  30. Rafaï I, Blayac T, Dubois D, Duchêne S, Nguyen-Van P, Ventelou B, et al. Stated preferences outperform elicited preferences for predicting reported compliance with Covid-19 prophylactic measures. J Behav Exp Econ 2023;107:102089. https://doi.org/10.1016/j.socec.2023.102089
  31. Krawiec JM, Mizak S, Tagliabue M, Białaszek W. Delay discounting of money and health outcomes, and adherence to policy guidelines during the COVID-19 pandemic. Front Public Health 2022;10:953743. https://doi.org/10.3389/fpubh.2022.953743
  32. Wismans A, Letina S, Wennberg K, Thurik R, Baptista R, Burke A, et al. The role of impulsivity and delay discounting in student compliance with COVID-19 protective measures. Pers Individ Dif 2021;179:110925. https://doi.org/10.1016/j.paid.2021.
  33. Soofi M, Najafi F, Karami-Matin B. Using insights from behavioral economics to mitigate the spread of COVID-19. Appl Health Econ Health Policy 2020;18(3):345-350. https://doi.org/10.1007/s40258-020-00595-4
  34. Bergeot J, Jusot F. Risk, time preferences, trustworthiness and COVID-19 preventive behavior: evidence from France. Eur J Health Econ 2024;25(1):91-101. https://doi.org/10.1007/s10198-023-01573-y
  35. Chan HF, Skali A, Savage DA, Stadelmann D, Torgler B. Risk attitudes and human mobility during the COVID-19 pandemic. Sci Rep 2020;10(1):19931. https://doi.org/10.1038/s41598-020-76763-2
  36. Gassmann X, Malézieux A, Spiegelman E, Tisserand JC. Preferences after pan(dem)ics: time and risk in the shadow of COVID 19. Judgm Decis Mak 2022;17(4):745-767. https://doi.org/10.1017/S1930297500008925
  37. Li KK, Hong Y, Huang B, Tam T. Social preferences before and after the onset of the COVID-19 pandemic in China. Judgm Decis Mak 2022;17(6):1313-1333. https://doi.org/10.1017/S1930297500009438
  38. Bogliacino F, Codagnone C, Montealegre F, Folkvord F, Gómez C, Charris R, et al. Negative shocks predict change in cognitive function and preferences: assessing the negative affect and stress hypothesis. Sci Rep 2021;11(1):3546. https://doi.org/10.1038/s41598-021-83089-0
  39. Drichoutis AC, Nayga RM Jr. On the stability of risk and time preferences amid the COVID-19 pandemic. Exp Econ 2022;25(3):759-794. https://doi.org/10.1007/s10683-021-09727-6
  40. Harrison GW, Hofmeyr A, Kincaid H, Monroe B, Ross D, Schneider M, et al. Subjective beliefs and economic preferences during the COVID-19 pandemic. Exp Econ 2022;25(3):795-823. https://doi.org/10.1007/s10683-021-09738-3