Sağlık Arayışındaki Tüketici: Panik Satın Alımlar Sonrası Yaşanan Bilişsel Uyumsuzluk

Year 2022, Volume: 24 Issue: 2, 730 - 756, 27.08.2022

F. Görgün Deveci Tuğba Yıldız

https://doi.org/10.26745/ahbvuibfd.1003324

Abstract

Bu çalışmanın amacı “sağlık arayışındaki” tüketicinin, sahip olduğu aşırı bilgi yükü ve elde ettikleri bilgilerin bir sonucu olarak ortaya çıkan siberkondrinin panik satın alımları ve bu satın alımların ise sonrasında bilişsel uyumsuzluğu ortaya çıkarıp çıkarmadığını belirlemektir. Online anket yönteminin tercih edildiği araştırmanın örneklemini sağlıklarına ilişkin kaygıları doğrultusunda panik satın alımlar yaptığını ifade eden 18 yaş ve üzeri tüketiciler oluşturmuştur. 400 katılımcının yer aldığı araştırmada verilerin analizi için yapısal eşitlik modellemesi ve aracılık analizlerinden yararlanılmıştır. Bulgular, sağlık bilgisi arayışının aşırı bilgi yüklemesi üzerinde; hem bilgi hem de iletişim aşırı yüklemesi siberkondri üzerinde; siberkondri, panik satın alma ve bilişsel uyumsuzluk boyutları üzerinde etkili olduğunu göstermiştir. Panik satın alma, bilişsel uyumsuzluk boyutları üzerinde etkili, siberkondri ve bilişsel uyumsuzluk boyutları arasında aracılık etkisine sahiptir. Bireylerin sağlıklarına ilişkin kaygıları süreklilik arz etmektedir. Bu ise bir döngü şeklinde bilgi arayışını ortaya çıkaracaktır. Bu öngörüyle araştırma, tüketicilerin panik satın almalarını araştırmaktadır. Ancak, araştırma modeli panik satın alma ile son bulmamaktadır. Odak nokta, bu satın alımlar sonrasındaki tüketici tepkisidir ve bunun literatüre katkı sağlayacağı düşünülmektedir.

Keywords

Sağlıkla İlgili Bilgi, Aşırı Yük, Siberkondri, Panik Satın Alma, Bilişsel Uyumsuzluk

Health-Seeking Consumer: Cognitive Dissonance Encountered After Panic Buying

Abstract

This study aims to specify whether the “health-seeking” consumers’ information overload and cyberchondria that arise as a result of the information they acquire, cause panic buying and whether these purchases can later cause cognitive dissonance. The study sample, for which an online survey method was preferred, consisted of consumers aged 18 years and older who stated that they made panic purchases due to health concerns. Structural equation modeling and mediation analyses were applied to analyze the data in the study, which included 400 participants. The findings showed that health information seeking has an effective on information overload; both information and communication overload have an effective on cyberchondria; cyberchondria has an effective on panic buying and cognitive dissonance dimensions. Panic buying has an effective on cognitive dissonance dimensions and has a mediating effect between cyberchondria and cognitive dissonance dimensions. People's health concerns are a constant, which will in turn lead to a cycle of seeking information. With this foresight, the research investigates the consumers’ panic buying. However, proposed research model does not end with panic buying. The focus is on the response of the consumer after these purchases, and this is thought to be a contribution to the literature.

Keywords

Health-Related Information, Overload, Cyberchondria, Panic Buying, Cognitive Dissonance

References

• Ahadzadeh, A. S, Sharif, S. P., Ong, F. S., & Khong, K.W. (2015). Integrating health belief model and technology acceptance model: An investigation of health-related internet use. Journal of Medical Internet Research, 17(2), 1-17.
• Alflayyeh, S. (2020). Theoretical perspective of unusual purchasing tendencies during pandemic situation of Covid-19. European Journal of Molecular & Clinical Medicine, 7(1), 3475-3482.
• Arafat, S.Y., Kar, S.K., Menon, V., Kaliamoorthy, C., Mukherjee, S., Alradie-Mohamed, A., Sharmaf, P., Marthoenisg, M., & Kabir, R. (2020a). Panic buying: An insight from the content analysis of media reports during COVID-19 pandemic. Neurology, Psychiatry and Brain Research, 37,100-103.
• Asmundson, G. J., & Taylor, S. (2020). How health anxiety influences responses to viral outbreaks like COVID-19: What all decision-makers, health authorities, and health care professionals need to know. Journal of Anxiety Disorders, 71, 1-2.
• Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
• Bermes, A. (2021). Information overload and fake news sharing: A transactional stress perspective exploring the mitigating role of consumers’ resilience during COVID-19. Journal of Retailing and Consumer Services, 61, 1-10.
• Brown, R. J., Skelly, N., & Chew‐Graham, C. A. (2020). Online health research and health anxiety: a systematic review and conceptual integration. Clinical Psychology: Science and Practice, 27(2), 1-19.
• Brown, T.A., & Moore, M. T. (2012). Confirmatory factor analysis, in R.H. Hoyle (Ed.), Handbook of Structural Equation Modeling. New York, NY: Guildford Press. 361-379.
• Chakraborty, T., Kumar, A., Upadhyay, P., & Dwivedi, Y.K. (2020). Link between social distancing, cognitive dissonance, and social networking site usage intensity: A country-level study during the COVID-19 outbreak. Internet Research, 31(2), 419-456.
• Chae, J., Lee, C. J., & Jensen, J. D. (2016). Correlates of cancer information overload: Focusing on individual ability and motivation. Health Communication, 31(5), 626-634.
• Cline, R. J., & Haynes, K. M. (2001). Consumer health information seeking on the internet: The state of the art. Health Education Research, 16(6), 671-692.
• Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98-104.
• Crook, B., Stephens, K. K., Pastorek, A. E., Mackert, M., & Donovan, E. E. (2016). Sharing health information and influencing behavioral intentions: The role of health literacy, information overload, and the internet in the diffusion of healthy heart information. Health Communication, 31(1), 60-71.
• Eichhorn, B. R. (2014). Common methods variance techniques. (Accessed 21.05.2021), www.mwsug.org/ proceedings/2014/AA/mwsug-2014-AA11.pdf
• Eppler, M. J., & Mengis, J. (2004). The concept of information overload-a review of literature from organization science, accounting, marketing, mis, and related disciplines. The Information Society, 20(5), 325-344.
• Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272-299.
• Festinger, L. (1957). A theory of cognitive dissonance. Stanford, CA: Stanford University Press.
• Farooq, A., Laato, S., Islam, A.N., & Isoaho, J. (2021). Understanding the impact of information sources on COVID-19 related preventive measures in Finland. Technology in Society, 65, 1-9.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
• Gaspar, R., Luís, S., Seibt, B., Lima, M. L., Marcu, A., Rutsaert, P., Fletcher, D., Verbeke, W., & Barnett, J. (2016). Consumers’ avoidance of information on red meat risks: Information exposure effects on attitudes and perceived knowledge. Journal of Risk Research, 19(4), 533-549.
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis: Pearson New International Edition, London: Pearson Education Limited.
• Henseler, J. (2017). Bridging design and behavioral research with variance-based structural equation modeling. Journal of Advertising, 46(1), 178-192.
• Islam, T., Pitafi, A.H., Arya, V., Wang, Y., Akhtar, N., Mubarik, S., & Xiaobei, L. (2021). Panic buying in the COVID-19 pandemic: A multi-country examination. Journal of Retailing and Consumer Services, 59, 1-13.
• Jokić-Begić, N., Mikac, U., Čuržik, D., & Jokić, C. S. (2019). The development and validation of the short cyberchondria scale (SCS). Journal of Psychopathology and Behavioral Assessment, 41(4), 662-676.
• Jungmann, S. M., & Witthöft, M., (2020). Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: Which factors are related to coronavirus anxiety?. Journal of Anxiety Disorders, 73, 1-9.
• Kalantari, A., Valizadeh-Haghi, S., Shahbodaghi, A., & Zayeri, F. (2021). Opportunities and challenges of consumer health information on the internet: Is cyberchondria an emerging challenge?. Library Philosophy and Practice,1-16.
• Karr-Wisniewski, P., & Lu, Y. (2010). When more is too much: Operationalizing technology overload and exploring its impact on knowledge worker productivity. Computers in Human Behavior, 26(5), 1061-1072.
• Kuruppu, G. N., & De Zoysa, A. (2020). COVID- 19 and panic buying: an examination of the impact of behavioural biases. (Accessed 21. 05. 2021), https://ssrn.com/abstract=3596101
• Laato, S., Islam, A.N., Farooq, A., & Dhir, A. (2020a). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The Stimulus-Organism-Response Approach. Journal of Retailing and Consumer Services, 57, 1-12.
• Laato, S., Islam, A. N., Islam, M.N., & Whelan, E. (2020b). What drives unverified information sharing and cyberchondria during the COVID-19 pandemic?. European Journal of Information Systems, 29(3), 288-305.
• Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51-61.
• Lins, S., & Aquino, S. (2020). Development and initial psychometric properties of a panic buying scale during COVID-19 pandemic. Heliyon, 6(9), 1-6.
• Matthes, J., Karsay, K., Schmuck, D., & Stevic, A. (2020). “Too much to handle”: Impact of mobile social networking sites on information overload, depressive symptoms, and well-being. Computers in Human Behavior, 105, 1-11.
• Mills, A., & Todorova, N. (2016). An integrated perspective on factors influencing online health-information seeking behaviours. ACIS 2016 Proceedings. 83.
• Nunnally, J. C. (1978). Psychometric Theory. McGraw-Hill Book Company.
• Pan, D., Xu, Y., & Wu, Y. (2017). The effect of inconsistent product attribute reviews on consumers’ purchase intention. Psychology, 8(13), 2187- 2199.
• Pólya, T., Kengyel, G. J. & Budai, T. (2021). Narrative construction of product reviews reveals the level of post-decisional cognitive dissonance. Information, 12(46), 1-13.
• Reynolds, B., & Seeger, M. W. (2005). Crisis and emergency risk communication as an integrative model. Journal of Health Communication, 10(1), 43-55.
• Schulte, K. L. (2016). Cyberchondria in relation to uncertainty and risk perception (Bachelor's thesis). University of Twente, Holland.
• Sim, K., Chua, H. C., Vieta, E., & Fernandez, G. (2020). The anatomy of panic buying related to the current COVID-19 pandemic. Psychiatry Research, 288, 113015.
• Singh, C. B. P. (2020). Protection motivation, social distancing and behavioural changes during COVID-19 pandemic. Indian Journal of Mental Health, 7(3), 230-237.
• Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In Samuel Leinhardt (Ed.) Sociological Methodology (pp. 290-312). San Francisco: Jossey-Bass,
• 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), 1-14.
• Soutar, G. N., & Sweeney, J. C. (2003). Are there cognitive dissonance segments?. Australian Journal of Management, 28(3), 227-249.
• Starcevic, V., Fallon, S., Uhlenhuth, E. H., & Pathak, D. (1994). Generalized anxiety disorder, worries about illness, and hypochondriacal fears and beliefs. Psychotherapy and Psychosomatics, 61(1-2), 93-99.
• Starcevic, V., & Berle, D. (2015). Cyberchondria: An old phenomenon in a new guise?. In: E. Aboujaoude, & V. Starcevic (Eds.), Mental Health in The Digital Age: Grave Dangers, Great Promise. Oxford University Press, New York, NY, 106-117.
• Starcevic, V., Schimmenti, A., Billieux, J., & Berle, D. (2020). Cyberchondria in the time of the COVID‐19 pandemic. Human Behavior and Emerging Technologies, 3(1), 53-62.
• Sweeney, J. C., Hausknecht, D., & Soutar, G. N. (2000). Cognitive dissonance after purchase: A multidimensional scale, Psychology and Marketing, 17(5), 369-385.
• Taylor, S. (2021). Understanding and managing pandemic-related panic buying. Journal of Anxiety Disorders, 78, 1-6.
• Upadhyay, V., & Pandey, A. (2020). Cyberchondria: Management and preventions. Parishodh Journal, 9(3), 10128-10140.
• Wang, H. H., & Na, H. A. O. (2020). Panic buying? Food hoarding during the pandemic period with city lockdown. Journal of Integrative Agriculture, 19(12), 2916-2925.
• Wang, R., He, Y., Xu, J., & Zhang, H. (2020). Fake news or bad news? Toward an emotion-driven cognitive dissonance model of misinformation diffusion. Asian Journal of Communication, 30(5), 317-342.
• Whelan, E., Islam, N., & Brooks, S. (2017). Cognitive Control and Social Media Overload. The Americas Conference on Information Systems, Boston MA, 1-10.
• Zheng, R., Shou, B., & Yang, J. (2020). Supply disruption management under consumer panic buying and social learning effects. Omega, 101,1-14.