Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Sep 4, 2020
Date Accepted: Apr 28, 2021
Patients and clinicians perceived trust in internet-of-things (IoTs) systems to support asthma self-management: a qualitative study
ABSTRACT
Background:
Internet-of-things (IoT) systems with artificial intelligence can provide customised support for a range of self-management functions, but trust is vital to encourage patients to adopt such systems.
Objective:
We aimed to explore patients/clinicians’ trust in IoT systems in the context of asthma self-management (including emergency advice in action plans).
Methods:
We interviewed patients recruited from research registers and social media, purposively sampled to include a range of age/sex, action plan ownership, asthma duration, hospital admissions and experience with apps. Clinicians, (primary, secondary, community-based), were recruited from professional networks. We transcribed interviews and used thematic analysis to categorise IoT features with reference to McKnight’s trust model.
Results:
We interviewed twelve patients and twelve clinicians. Most patients believed an IoT system could help support a broad range of self-management tasks, but wanted the system to provide customised advice. They believed they could rely on the system to log their asthma condition and provide pre-set action plan advice triggered by their logs. However, they were not confident that the system could generate new advice or reach diagnostic conclusions without the interpretation of their trusted clinicians. Clinicians needed clinical evidence before trusting the system.
Conclusions:
IoT systems were regarded as offering potentially helpful functionality in mediating the action plans developed with a trusted clinician, but technologically adept participants were not yet ready to trust artificial intelligence to generate novel advice. Research is needed to ensure that technological capability does not outstrip the trust of the individuals using it.
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