When Human Behavior Challenges the Data: Strategic Interaction and Response Shift as Threats o Validity in Clinical Research
Main Article Content
Abstract
In clinical research, the validity of results can be compromised by classical factors such as bias, confounding, and sampling error. However, there are other elements related to human behavior that are not always considered and can also affect the conclusions. This article explores two such phenomena: strategic interaction and response shift. The former occurs when individuals adjust their behavior based on what they believe others will do. The latter refers to a change in how people evaluate their own health over time. Through everyday examples –such as penalty kicks in football, traffic decisions, or self-reported quality of life– we examine how these dynamics can impact the validity of clinical studies. Recognizing these mechanisms is essential for accurately interpreting results and designing methodological strategies to minimize their influence.
Downloads
Article Details
Section

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
References
Giunta DH. Bioestadística handbook: fundamentos básicos. Buenos Aires: Merck; 2018.
Zurita-Cruz JN, Villasís-Keever MÁ. Principales sesgos en la investigación clínica. Rev Alerg Mex. 2021 Oct-Dec;68(4):291-299. DOI: https://doi.org/10.29262/ram.v68i4.1003
Ortega-Gómez E, Vicente-Galindo P, Martín-Rodero H, et al. Detection of response shift in health-related quality of life studies: a systematic review. Health Qual Life Outcomes. 2022;20(1):20. DOI: https://doi.org/10.1186/s12955-022-01926-w
Camerer CF. Behavioral game theory: experiments in strategic interaction. Princeton, NJ: Princeton University Press; 2003.
Palacios-Huerta I. Professionals play minimax. Rev Econ Stud. 2003;70(2): 395-415. DOI: https://doi.org/10.1111/1467-937X.00249
Goddard K, Roudsari A, Wyatt JC. Automation bias: a systematic review of frequency, effect mediators, and mitigators. J Am Med Inform Assoc. 2012;19(1):121-127. DOI: https://doi.org/10.1136/amiajnl-2011-000089
Wagner B, Winkler T, Human S. Bias in geographic information systems: the case of Google Maps. Trabajo presentado en: 54th Hawaii International Conference on System Sciences (HICSS54); 2021 ene 5-8; Hawaii, USA. DOI: https://doi.org/10.24251/HICSS.2021.103
T13. Encuestas dan 4 puntos de diferencia a favor de Hillary Clinton [Internet]. Santiago, Chile: Señal T13; 2016 nov 7 [citado 2025 may 13]. Disponible en: https://www.t13.cl//noticia/mundo/encuestas-dan-4-puntos-diferencia-favor-hillary-clinton.
Boyle J, Dayton J, ZuWallack R, et al. The shy respondent and propensity to participate in surveys: a proof-of-concept study. Surv Pract. 2023;16(1):1-15. DOI: https://doi.org/10.29115/SP-2014-0026
Brownback A, Novotny A. Social desirability bias and polling errors in the 2016 presidential election.J. Behav Exp Econ. 2018;74:38-56. DOI: https://doi.org/10.1016/j.socec.2018.03.001
Sprangers MA, Schwartz CE. Integrating response shift into health-related quality of life research: a theoretical model. Soc Sci Med. 1999;48(11):1507-1515. DOI: https://doi.org/10.1016/S0277-9536(99)00045-3
Sprangers M, Hoogstraten J. Pretesting effects in retrospective pretest-posttest designs. J Appl Psychol. 1989;74(2):265-272. DOI: https://doi.org/10.1037//0021-9010.74.2.265
Andrykowski MA, Donovan KA, Jacobsen PB. Magnitude and correlates of response shift in fatigue ratings in women undergoing adjuvant therapy for breast cancer. J Pain Symptom Manage. 2009;37(3):341-351. DOI: https://doi.org/10.1016/j.jpainsymman.2008.03.015
Razmjou H, Schwartz CE, Yee A, et al. Traditional assessment of health outcome following total knee arthroplasty was confounded by response shift phenomenon. J Clin Epidemiol. 2009;62(1):91-96. DOI: https://doi.org/10.1016/j.jclinepi.2008.08.004
Wagner JA. Response shift and glycemic control in children with diabetes. Health Qual Life Outcomes. 2005;3:38. DOI: https://doi.org/10.1186/1477-7525-3-38