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Prosocial behavior in emergencies: Evidence from blood donors recruitment and retention during the COVID-19 pandemic

Author

Listed:
  • Bilancini, Ennio
  • Boncinelli, Leonardo
  • Di Paolo, Roberto
  • Menicagli, Dario
  • Pizziol, Veronica
  • Ricciardi, Emiliano
  • Serti, Francesco

Abstract

The impact of COVID-19 represents a specific challenge for voluntary transfusional systems sustained by the intrinsic motivations of blood donors. In general, health emergencies can stimulate altruistic behaviors. However, in this context, the same prosocial motivations, besides the personal health risks, could foster the adherence to social distancing rules to preserve collective health and, therefore, discourage blood donation activities. In this work, we investigate the consequences of the pandemic shock on the dynamics of new donors exploiting the individual-level longitudinal information contained in administrative data on the Italian region of Tuscany. We compare the change in new donors' recruitment and retention during 2020 with respect to the 2017–2019 period (we observe 9511 individuals), considering donors’ and their municipalities of residence characteristics. Our results show an increment of new donors, with higher proportional growth for older donors. Moreover, we demonstrate that the quality of new donors, as proxied by the frequency of subsequent donations, increased with respect to previous years. Finally, we show that changes in extrinsic motivations, such as the possibility of obtaining a free antibody test or overcoming movement restrictions, cannot explain the documented increase in the number of new donors and in their performance. Therefore, our analyses indicate that the Tuscan voluntary blood donation system was effective in dealing with the challenges posed by the COVID-19 pandemic.

Suggested Citation

  • Bilancini, Ennio & Boncinelli, Leonardo & Di Paolo, Roberto & Menicagli, Dario & Pizziol, Veronica & Ricciardi, Emiliano & Serti, Francesco, 2022. "Prosocial behavior in emergencies: Evidence from blood donors recruitment and retention during the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:socmed:v:314:y:2022:i:c:s0277953622007444
    DOI: 10.1016/j.socscimed.2022.115438
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    References listed on IDEAS

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    1. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
    2. Wildman, John & Hollingsworth, Bruce, 2009. "Blood donation and the nature of altruism," Journal of Health Economics, Elsevier, vol. 28(2), pages 492-503, March.
    3. Isu Cho & Ryan T Daley & Tony J Cunningham & Elizabeth A Kensinger & Angela Gutchess, 2022. "Aging, Empathy, and Prosocial Behaviors During the COVID-19 Pandemic," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 77(4), pages 57-63.
    4. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    5. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    6. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2015. "Comparative Politics and the Synthetic Control Method," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 495-510, February.
    7. Shusaku Sasaki & Yoshifumi Funasaki & Hirofumi Kurokawa & Fumio Ohtake, 2018. "Blood Type and Blood Donation Behavior," ISER Discussion Paper 1029rr, Institute of Social and Economic Research, Osaka University, revised Jun 2020.
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    Cited by:

    1. Roberto Di Paolo & Veronica Pizziol, 2024. "Gamification and Sustainable Water Use: The Case of the BLUTUBE Educational Program," Simulation & Gaming, , vol. 55(3), pages 391-417, June.
    2. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.

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    More about this item

    Keywords

    Charity; Prosocial behavior; Blood donation; AVIS; Tuscany; COVID-19;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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