The role of stigma in health data sharing decisions : a Swiss study with a focus on trust in AI and healthcare providers
Creators: name: Bienz, Christof
Publisher: name: ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Year: 2024
Subjects: 006: Spezielle Computerverfahren
362: Gesundheits- und Sozialdienste

description: The integration of artificial intelligence into healthcare is becoming increasingly widespread, offering significant potential to reduce costs and enhance the overall efficiency of healthcare systems. However, the use of AI in healthcare has raised concerns about biased algorithms increasing inequity. These concerns arise because AI algorithms are often trained on datasets that predominantly represent individuals of European ancestry, potentially increasing healthcare disparities. Diversifying these training datasets relies on individuals’ willingness to share their health data, which can help ensure more equitable and accurate AI systems. 
This thesis aimed to investigate the factors influencing Swiss citizens' willingness to share their health data, with a particular focus on how stigma impacts this willingness and how trust in AI and healthcare providers might moderate this relationship. This research is also part of a broader comparative study involving Nigeria. 
A mixed-methods approach was employed to explore these dynamics. The primary method involved a quantitative survey focused on cancer, with a sample drawn from the general population of Switzerland, specifically non-patients. The questionnaire measured key variables, including stigma, trust in AI, and trust in healthcare providers. Participants were presented with vignettes involving an individual having cancer symptoms, with the scenarios differing based on the method of diagnosis. The vignettes included consulting a family doctor, consulting a family doctor using AI, or using a mobile app powered by AI. Qualitative interviews supplemented the quantitative survey to triangulate the results and provide deeper insights into the factors influencing data-sharing decisions. 
The findings revealed that stigma did not significantly impact Swiss citizens' willingness to share health data. However, trust in AI and healthcare providers emerged as critical moderators. High levels of trust in both AI and healthcare providers significantly increased the willingness to share health data, particularly when stigma was present. Moreover, there was a distinct difference in the willingness to share health data between the scenarios, with individuals more likely to engage in diagnosis with their family doctor. As soon as AI was introduced, willingness markedly decreased. 
In conclusion, this thesis provided valuable insights into the challenges of collecting health data for AI applications in healthcare. Trust emerged as a crucial factor influencing data-sharing willingness, with participants expressing general skepticism about AI’s role in healthcare. The thesis recommended increasing trust in AI within healthcare through targeted educational initiatives that address benefits and security concerns. These efforts will likely improve data-sharing willingness and enhance the adoption of AI within the Swiss healthcare system.