Mobile health: how do researchers understand and measure user acceptance?

User acceptance – why is it important?

While technology is increasingly employed in healthcare, the COVID-19 outbreak is accelerating this transition. Being a patient in 2020 means that you may be screened, treated, or monitored with the assistance of a “smart technology”. This transition also impacts the general population, as governments are deploying tracing apps to enforce public health measures. 

The population’s acceptance of these new monitoring systems is a burning issue. In fact, if asked to install an app that keeps a record of the people we meet each day, we will probably hesitate. The initiative is presented to be for the common good; however, it is hard to predict whether the population will comply with this automatic tracing. 

When designing healthcare technologies, priority is given to ensuring that they effectively serve their purpose – diagnose, treat, monitor, etc. However, providing evidence of effectiveness alone does not guarantee that people will agree to use these technologies. Treatment dropout and problems of adherence are major issues in health and mental health interventions. When delivering treatment with the help of technology, it is essential that the technology is sufficiently accepted by patients; otherwise, they may refuse or abandon treatment. 

Technology acceptance, acceptability, adoption – what is it and how to measure it?

Our recent work “Technology acceptance in mHealth: a scoping review of definitions, models and measurement” reveals how researchers tackle this question.

The review uncovered:

  • The different definitions for acceptance, acceptability and adoption
  • Researchers’ various interpretations for user acceptance
  • Current practices to measure user acceptance of health and mental wellbeing technologies
  • Researchers’ effort to adapt existing measurement tools to their context of study

Multiple factors linked to our health, individual characteristics, social environment, and experience influence our acceptance of technology. In addition, the way that we perceive technology is likely to evolve over time. 

We proposed the Technology Acceptance Lifecycle (TAL) to articulate the process of technology acceptance and its different stages across the user journey.

Check the full text of our paper here.

Refer to this publication

Nadal, C., Sas, C., & Doherty, G. (2020). Technology acceptance in mHealth: a scoping review of definitions, models and measurement. Journal of Medical Internet Research, 22(7),