Journal of Information Technology
The technology-behavioral compensation effect: Unintended consequences of health technology adoption
Document Type
Research Article
Abstract
In their pursuit of public health goals, policymakers increasingly turn to innovative apps to complement existing health measures. However, findings from previous research in non-IT health contexts indicate that individuals may compensate for new interventions (e.g., start exercising) by reducing existing preventive health behaviors (e.g., eating fewer healthy foods). However, the findings are inconclusive, and it is unknown when people tend to engage in behavioral compensation. Building on this observation, we draw on rational choice theory to substantiate the subjective rationality of compensation behavior and develop a utility maximization model that suggests circumstances under which adoption of technological innovation may lead to users reducing existing preventive health behaviors. This research provides evidence from a multi-wave study on COVID-19 contact-tracing apps that confirms the existence of what we term the technology-behavioral compensation effect: Individuals who perceive the app to be highly useful or actively use it reduce other preventive health behaviors (e.g., social distancing) after app adoption. Ironically, this technology-behavioral compensation effect indicates a hitherto-overlooked tension between two established IS design goals (i.e., perceived usefulness and active use) and the successful exploitation of technology to support users’ health. We expand research on dark side effects of IS use by revealing a previously neglected type of unintended consequence and elaborate on its implications for research well beyond the health context. Our findings also will help policymakers make decisions on the design of societal technologies.
DOI
10.1177/02683962231183979
Recommended Citation
Wolf, Tobias; Trang, Simon; Weiger, Welf H.; and Trenz, Manuel
(2024)
"The technology-behavioral compensation effect: Unintended consequences of health technology adoption,"
Journal of Information Technology: Vol. 39:
Iss.
3, Article 7.
DOI: 10.1177/02683962231183979
Available at:
https://aisel.aisnet.org/jit/vol39/iss3/7