Pathology of Compliance with Covid-19 Preventive Measures in Iran: The Role of Distress by Information and Information Avoidance

Document Type : Research ŮŽ Article

Authors

1 PhD Student of Knowledge and Information Science, Shiraz University, Shiraz, Iran

2 PhD in Knowledge and Information Science, Associate Professor, Shiraz University, Shiraz, Iran,

Abstract

Purpose: The study aimed to identify the impact of distress by information and information avoidance on the compliance with preventive measures and to identify the intervention effect of information avoidance about corona virus on distress by information in compliance with preventive measures.
Method: In terms of purpose this is applied research, and in terms of method is a descriptive-survey. The statistical population includes all students of Shiraz University in different academic levels who were studying in the even semester of the academic year 2021 (N = 16643). According to Morgan's table, 375 students selected as the research sample. Data collection tool was a combined questionnaire developed by Siebenhaar, et al. (2020) which had three subscales of distress by information, information avoidance and compliance with preventive measures. Research data was collected after confirming the validity of the questionnaire by three experts in the field as well as calculating the reliability (Cronbach's alpha) of all three subscales of distress by information, information avoidance and compliance with preventive measures (0.788, 0.856, 0.890).
Findings: The results showed that the regression model is significant for predicting compliance with preventive measures through the variables of distress by information and information avoidance (F (2, 371) = 18.029, p <.001, R2 = .089). The distress by information explains 13.2% of the variance of compliance with preventive measures (negative and significant) and the information avoidance variable explains 25.8% of the variance of compliance with preventive measures (negative and significant). Findings of block regression model also showed a significant effect of information avoidance intervention (F (2, 371) = 19.628, p <.000) on the relationship between distress by information and compliance with preventive measures with R2 = .096. The distress by information in the presence of the intervention effect of information avoidance explains 34.5% of the variance of compliance with preventive measures.
Conclusion: The results showed that the distress by information variable and the information avoidance variable reduce the compliance with preventive measures. Moreover, the predicting influence of information avoidance is more than the predicting influence of distress by information. On the other hand, information avoidance has a reinforcing intervention effect on the relationship between distress by information and compliance with preventive measures and reduces the compliance with preventive measures. In other words, people who scored higher in distress by information and avoided coronary information more, followed corona preventive measures less than others did.

Keywords

Main Subjects

References

  • Alpers, G. W. (2010). “Avoiding treatment failures in specific phobia,” in Avoiding Threatment Failures in the Anxiety Disorders, Eds M. W. Otto and S. G. Hofmann (New York, NY: Springer), 209–230.
  • Bao, Y., Sun, Y., Meng, S., Shi, J., and Lu, L. (2020). 2019-nCoV epidemic: address mental health care to empower society. Lancet 395, e37–e38.
  • Barbour, J. B., Rintamaki, L. S., Ramsey, J. A., and Brashers, D. E. (2012). Avoiding health information. J. Health Commun. 17, 212–229. doi: 10.1080/10810730.2011.585691
  • Barke, A., Bleichhardt, G., Rief, W., and Doering, B. K. (2016). The cyberchondria severity scale (CSS): German validation and development of a short form. Int. J. Behav. Med. 23, 595–605. doi: 10.1007/s12529-016-9549-8
  • Betsch, C., Korn, L., Felgendreff, L., Eitze, S., Schmid, P., Sprengholz, P., et al. (2020a). COVID-19 snapshot monitoring (COSMO) – Welle 10 (05.05.2020). PsychArchives [Preprint]. doi: 10.23668/PSYCHARCHIVES.2900
  • Bults, M., Beaujean, D. J. M. A., de Zwart, O., Kok, G., van Empelen, P., van Steenbergen, J. E., et al. (2011). Perceived risk, anxiety, and behavioural responses of the general public during the early phase of the influenza A (H1N1) pandemic in the Netherlands: results of three consecutive online surveys. BMC Public Health 11:2. doi: 10.1186/1471-2458-11-2
  • Cheng, C. C., Lam, T. H., and Cheng, K. K. (2020). Mass masking in the COVID-19 epidemic: people need guidance. Lancet 395:945. doi: 10.1016/S0140-6736(20) 30547-X
  • Emanuel, A. S., Kiviniemi, M. T., Howell, J. L., Hay, J. L., Waters, E. A., Orom, H., et al. (2015). Avoiding cancer risk information. Soc. Sci. Med. 147, 113–120.10.058
  • Fischhoff, B., Wong-Parodi, G., Garfin, D. R., Holman, E. A., and Silver, R. C. (2018). Public understanding of Ebola risks: mastering an unfamiliar threat. Risk Anal. 38, 71–83.
  • Garfin, D. R., Silver, R. C., & Holman, E. A. (2020). The novel coronavirus (COVID-2019) outbreak: Amplification of public health consequences by media exposure. Health psychology, 39(5), 355.
  • Hightow, L. B., Miller, W. C., Leone, P. A., Wohl, D., Smurzynski, M., and Kaplan, A. H. (2003). Failure to return for HIV posttest counseling in an SDT clinic population. AIDS Educ. Prevent. 15, 282–290.
  • Howell, J. L., and Shepperd, J. A. (2013b). Reducing health-information avoidance through contemplation. Psychol. Sci. 24, 1696–1703. doi: 10.1177/0956797613478616
  • Howell, J. L., & Shepperd, J. A. (2016). Establishing an information avoidance scale. Psychological Assessment, 28(12), 1695.
  • Jones, J. H., and Salathe, M. (2009). Early assessment of anxiety and behavioral response to novel swine-origin influenza A (H1N1).
  • Khosravi, M. (2020). Perceived risk of COVID-19 pandemic: the role of public worry and trust. Electron. J. Gen. Med. 17, 1–2.
  • Kim, L., Fast, S. M., & Markuzon, N. (2019). Incorporating media data into a model of infectious disease transmission. PloS one, 14(2), e0197646.
  • Klemm, C., Das, E., & Hartmann, T. (2016). Swine flu and hype: a systematic review of media dramatization of the H1N1 influenza pandemic. Journal of Risk Research, 19(1), 1-20.
  • McDonnell, W. M., Nelson, D. S., and Schunk, J. E. (2012). Should we fear “the flu” itself? Effects of H1N1 influenza fear on ED use. Am. J. Emerg. Med. 30, 275–282. doi: 10.1016/j.ajem.2010.11.027
  • Miles, A., Voorwinden, S., Chapman, S., and Wardle, J. (2008). Psychologic predictors of cancer information avoidance among older adults: the role of cancer fear and fatalism. Cancer Epidemiol.Biomark. Prevent. 17, 1872–1880. doi: 10.1158/1055-9965.EPI-08-0074
  • Mitchell, A., Oliphant, J. B., and Shearer, E. (2020). About Seven-in-Ten U.S. Adults Say They Need to Take Breaks From COVID-19 News. Washington, DC: Pew Research Center, 1–5.
  • Orom, H., and Shepperd, J. A. (2015). Avoiding cancer risk information. Soc. Sci. Med. 147, 113–120. doi: 10.1016/j.socscimed.2015.10.058.
  • Pfefferbaum, B., Newman, E., Nelson, S. D., Nitiéma, P., Pfefferbaum, R. L., and Rahman, A. (2014). Disaster media coverage and psychological outcomes: descriptive findings in the extant research. Curr. Psychiatry Rep. 16:464. doi: 10.1007/s11920-014-0464-x
  • Pittig, A., Hengen, K., Bublatzky, F., and Alpers, G. W. (2018). Social and monetary incentives counteract fear-driven avoidance: evidence from approach-avoidance decisions. J. Behav. Ther. Exp. Psychiatry 60, 69–77. doi: 10.1016/j.jbtep.2018.04.002
  • Pittig, A., Schulz, A. R., Craske, M. G., and Alpers, G. W. (2014). Acquisition of behavioral avoidance: task-irrelevant conditioned stimuli trigger costly decisions. J. Abnorm. Psychol. 123, 314–329. doi: 10.1037/a0O36136
  • Qiu, J., Shen, B., Zhao, M., Wang, Z., Xie, B., and Xu, Y. (2020). A nationwide survey of psychological distress among Chinese people in the COVID- 19 epidemic: implications and policy recommendations. Gen. Psychiatry 33: e100213. doi: 10.1136/gpsych-2020-100213
  • Rajkumar, R. P. (2020). COVID-19 and mental health: a review of the existing literature. Asian J. Psychiatry 52, 1–5. doi: 10.1016/j.ajp.2020.102066
  • Rubin, G. J., Amlot, R., Page, L., and Wessely, S. (2009). Public perceptions, anxiety, and behavior change in relation to the swine flu outbreak: cross sectional telephone survey. BMJ 339: b2651. doi: 10.1136/bmj.b2651
  • Rubin, G. J., Potts, H. W. W., and Michie, S. (2010). The impact of communications about swine flu (influenza A H1N1v) on public responses to the outbreak: results from 36 national telephone surveys in the UK. Health Technol.
  • Siebenhaar, K. U., Köther, A. K., & Alpers, G. W. (2020). Dealing with the COVID-19 infodemic: Distress by information, information avoidance, and compliance with preventive measures. Frontiers in psychology, 11, 2981.
  • Song, S., Yao, X., & Wen, N. (2021). What motivates Chinese consumers to avoid information about the COVID-19 pandemic? The perspective of the stimulus-organism-response model. Information Processing & Management, 58(1), 102407.
  • Soroya, S. H., Farooq, A., Mahmood, K., Isoaho, J., & Zara, S. E. (2021). From information seeking to information avoidance: Understanding the health information behavior during a global health crisis. Information processing & management, 58(2), 102440.
  • Sweeny, K., Melnyk, D., Miller, W., & Shepperd, J. A. (2010). Information avoidance: Who, what, when, and why. Review of general psychology, 14(4), 340-353.
  • Taber, J. M., Klein, W. M. P., Ferrer, R. A., Lewis, K. L., Harris, P. R., Shepperd, J. A., et al. (2015). Information avoidance tendencies, threat management resources, and interest in genetic sequencing feedback. Ann. Behav. Med. 49, 616–621.
  • Taha, S. A., Matheson, K., and Anisman, H. (2014). H1N1 was not all that scary: uncertainty and stressor appraisals predict anxiety related to a coming viral threat. Stress Health 30, 149–157. doi: 10.1002/smi.2505
  • Thompson, R. R., Garfin, D. R., Holman, E. A., & Silver, R. C. (2017). Distress, worry, and functioning following a global health crisis: A national study of Americans’ responses to Ebola. Clinical psychological science, 5(3), 513-521.
  • Torales, J., Higgins, M. O., Castaldelli-maia, J. M., and Ventriglio, A. (2020). The outbreak of COVID-19 coronavirus and its impact on global mental health. Int. J. Sco. Psychiatry 66, 317–320. doi: 10.1177/0020764020915212
  • Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., et al. (2020). Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health 17:1729. doi: 10.3390/ ijerph17051729
  • Wheaton, M. G., Abramowitz, J. S., Berman, N. C., Fabricant, L. E., and Olatunji, B. O. (2012). Psychological predictors of anxiety in response to the H1N1 (swine flu) pandemic. Cogn. Ther. Res. 36, 210–218. doi: 10.1007/s10608-011- 9353-3
  • Williams-Piehota, P., Pizarro, J., Schneider, T. R., Mowad, L., and Salovey, P. (2005). Matching health messages to monitor-blunter coping styles to motivate screening mammography. Health Psychol. 24, 58–67. doi: 10.1037/0278-6133. 24.1.58            

 

 

Send comment about this article
CAPTCHA Image

Files

History

  • Receive Date: 29 August 2021
  • Revise Date: 12 October 2021
  • Accept Date: 12 October 2021

Share

How to cite

Statistics