IDEAS home Printed from https://ideas.repec.org/a/eee/oprepe/v10y2023ics2214716022000343.html

Analysing the impact of COVID-19 pandemic on the psychological health of people using fuzzy MCDM methods

Author

Listed:
  • Ahmad, Shafi
  • Masood, Sarfaraz
  • Khan, Noor Zaman
  • Badruddin, Irfan Anjum
  • Ompal,
  • Ahmadian, Ali
  • Khan, Zahid A.
  • Khan, Amil Hayat

Abstract

Recently, a large portion of the world's population has experienced an unprecedented devastating effect of the COVID-19 pandemic. At the time of its outbreak, not much was known about this disease and therefore, quarantine and social distancing were the only ways suggested to prevent its spread among humans. Although the current situation is much better than before however, strict social distancing norms as well as frequent long-lasting lockdowns with stringent guidelines and actions to control the spread in the early days have affected the physical and psychological health of the people. Consequently, this study was carried out to attain the following major objectives: (i) to identify the potential psychological problems/factors that might have been caused due to COVID-19 led social distancing and lockdowns, and (ii) to determine the ranks of the identified psychological factors to reflect their degree of criticality. The first objective was achieved by gathering information about the potential psychological factors from the experts. Data, in terms of linguistic variables, was collected from the experts and analyzed using two fuzzy-based multi-criteria decision-making (MCDM) methods i.e. Fuzzy Best Worst Method (F-BWM) and Fuzzy TOPSIS (F-TOPSIS) which led to the accomplishment of the second objective. The results of this study revealed that anxiety, stress, panic attacks, frustration, and insomnia were the top five critical psychological factors that might have affected people due to this pandemic. Consistency of the results was ensured by comparing the obtained ranks with the ranks found using the Fuzzy WSM and Fuzzy MABAC methods. In addition, the robustness of the results was ascertained by conducting the sensitivity analysis. Based on the findings of the study, the identified factors were categorized into most, average, and least critical psychological factors. This research might help the relevant authorities to understand the extent of the seriousness of the various psychological factors caused by this pandemic, so that an effective strategy may be developed for better management, control, and safety.

Suggested Citation

  • Ahmad, Shafi & Masood, Sarfaraz & Khan, Noor Zaman & Badruddin, Irfan Anjum & Ompal, & Ahmadian, Ali & Khan, Zahid A. & Khan, Amil Hayat, 2023. "Analysing the impact of COVID-19 pandemic on the psychological health of people using fuzzy MCDM methods," Operations Research Perspectives, Elsevier, vol. 10(C).
  • Handle: RePEc:eee:oprepe:v:10:y:2023:i:c:s2214716022000343
    DOI: 10.1016/j.orp.2022.100263
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214716022000343
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.orp.2022.100263?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Cuiyan Wang & Riyu Pan & Xiaoyang Wan & Yilin Tan & Linkang Xu & Cyrus S. Ho & Roger C. Ho, 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," IJERPH, MDPI, vol. 17(5), pages 1-25, March.
    2. Siamak Kheybari & S. Ali Naji & Fariba Mahdi Rezaie & Reza Salehpour, 2019. "ABC classification according to Pareto’s principle: a hybrid methodology," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 539-562, June.
    3. Athanasios J. Kolios & Anietie Umofia & Mahmood Shafiee, 2017. "Failure mode and effects analysis using a fuzzy-TOPSIS method: a case study of subsea control module," International Journal of Multicriteria Decision Making, Inderscience Enterprises Ltd, vol. 7(1), pages 29-53.
    4. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    5. Zanakis, Stelios H. & Solomon, Anthony & Wishart, Nicole & Dublish, Sandipa, 1998. "Multi-attribute decision making: A simulation comparison of select methods," European Journal of Operational Research, Elsevier, vol. 107(3), pages 507-529, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mališa Žižović & Dragan Pamučar & Goran Ćirović & Miodrag M. Žižović & Boža D. Miljković, 2020. "A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL)," Mathematics, MDPI, vol. 8(5), pages 1-18, May.
    2. Dong, Yucheng & Liu, Yating & Liang, Haiming & Chiclana, Francisco & Herrera-Viedma, Enrique, 2018. "Strategic weight manipulation in multiple attribute decision making," Omega, Elsevier, vol. 75(C), pages 154-164.
    3. Jiaji Pan & Ruilin Fan & Hanlu Zhang & Yi Gao & Zhiquan Shu & Zhongxiang Chen, 2022. "Investigating the Effectiveness of Government Public Health Systems against COVID-19 by Hybrid MCDM Approaches," Mathematics, MDPI, vol. 10(15), pages 1-20, July.
    4. Heidary Dahooie, Jalil & Qorbani, Ali Reza & Daim, Tugrul, 2021. "Providing a framework for selecting the appropriate method of technology acquisition considering uncertainty in hierarchical group decision-making: Case Study: Interactive television technology," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    5. Krishankumar, Raghunathan & Sundararajan, Dhruva & Ishizaka, Alessio & Ravichandran, Kattur Soundarapandian, 2025. "A double hierarchy fuzzy decision approach for solar farm ranking sites in India," Energy Economics, Elsevier, vol. 152(C).
    6. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    7. José Rui Figueira & José Luis García-Lapresta, 2026. "Relationships between the deck of cards method and the proximity measures approach," Operational Research, Springer, vol. 26(2), pages 1-18, June.
    8. Nitin Sahu & Garima Mittal, 2026. "Resilient supplier selection under operational and disruption risks: A multi-stage framework," Annals of Operations Research, Springer, vol. 359(3), pages 2617-2654, April.
    9. Yuchen Lu, 2024. "Uncovering the Barriers to Foreign Residents' Enrollment in Japan's National Health Insurance: An Econometric Analysis Using Pooled Cross-Sectional Data," Keio-IES Discussion Paper Series 2024-026, Institute for Economics Studies, Keio University.
    10. Nitesh Kumar & Ramesh Anbanandam, 2026. "Selection of Waste Disposal Vendor for Effective Municipal Solid Waste Management," Circular Economy and Sustainability, Springer, vol. 6(2), pages 1-28, April.
    11. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    12. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    13. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    14. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    15. Martín-García, Jaime & Gómez-Limón, José A. & Arriaza, Manuel, 2024. "Conversion to organic farming: Does it change the economic and environmental performance of fruit farms?," Ecological Economics, Elsevier, vol. 220(C).
    16. Juuso Pajasmaa & Kaisa Miettinen & Johanna Silvennoinen, 2025. "Group Decision Making in Multiobjective Optimization: A Systematic Literature Review," Group Decision and Negotiation, Springer, vol. 34(2), pages 329-371, April.
    17. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    18. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    19. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    20. Mulliner, Emma & Smallbone, Kieran & Maliene, Vida, 2013. "An assessment of sustainable housing affordability using a multiple criteria decision making method," Omega, Elsevier, vol. 41(2), pages 270-279.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:oprepe:v:10:y:2023:i:c:s2214716022000343. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/operations-research-perspectives .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.