"I don’t trust it, but I have to trust it": the paradox of trust vs use of online technology across The mental health spectrum

Abstract

Background: interest in eHealth has grown since the Coronavirus (COVID-19) pandemic. Use of internet-based technologies (IBTs) and artificial intelligence (AI) has the potential to transform the delivery of mental healthcare services, however, trust remains a pivotal factor in public acceptance and adoption of these systems.

Aims: we investigated attitudes and behaviours towards eHealth services, with a focus on mental health and wellbeing provision, in the general population and individuals with experience of serious mental illness. Our investigation was underpinned by the extended technology acceptance model (TAM2), which included trust.

Methods: after trialling a cognitive training exercise involving autonomous feedback, we prompted participants’ views on and trust in IBTs, autonomous systems (AS) and AI for health care. We conducted 22 semi-structured interviews in total, including 8 individuals who declared having experience of a serious mental illness.

Results: we principally identified the privacy paradox extends to eHealth, whereby individuals engaged with IBTs despite distrusting them and/or having privacy concerns regarding them, and this was across all participants. Behaviours instead were driven by both convenience, ease of use, and lack of choice or alternatives.

Conclusions:whilst trust is a factor in uptake and engagement with eHealth, there are other factors involved. It is concerning that individuals will utilise eHealth systems despite mistrusting them or their developers. There are clear ethical implications for both healthcare providers prescribing eHealth, and developers of these systems, with considerations relevant across the mental health and wellbeing spectrum. To foster trust in IBTs, particularly those using AI, a balance is needed between human and eHealth provision. This may lead to greater trust and acceptability of systems, yielding better outcomes for patients.

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Identifiers

ORCID for M. Naiseh: orcid.org/0000-0002-4927-5086

ORCID for M.J. Weal: orcid.org/0000-0001-6251-8786

ORCID for A.M. Hughes: orcid.org/0000-0002-3958-8206

ORCID for E. Palmer-Cooper: orcid.org/0000-0002-5416-1518

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