Understanding key predictors of digital health contact-tracing app adoption

Contact tracing is a recognised public health tool to reduce the spread of infectious diseases.Digital contact-tracing(DCT) utilises mobile applications to quickly identify individuals who may have been exposed to an infection and provide appropriate public health advice. The success of the DCT during a pandemic primarily depends on public acceptance. This study examined factors influencing public adoption of DCT, specifically, privacy, perceived benefits, effectiveness,ego and social norms.It also explored how presentation of privacy and benefit information influenced the intention to adopt DCT. Privacy, perceived benefits, effectiveness, ego, descriptive norms and injunctive norms significantly correlated with the intention to adopt DCT. The amount of privacy and benefits information did not make a significant difference, whilst privacy-related images significantly influenced the adoption intention. Additionally, ego and descriptive norms emerged as significant predictors of willingness to adopt DCT. People valued privacy-preserving features of the app and recognised its social and health benefits. However, a lack of confidence in willingness of others to use apps was identified as primary barrier to adoption. The findings highlight the importance of understanding the key predictors and potential barriers to adopting DCT for future pandemic.Behavioural science research could help strengthen the understanding and inform future development of widely-accepted DCT solutions.