Currently accepted at: JMIR Mental Health
Date Submitted: Oct 10, 2025
Open Peer Review Period: Oct 10, 2025 - Dec 5, 2025
Date Accepted: Nov 13, 2025
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/85635
The final accepted version (not copyedited yet) is in this tab.
What is the strength of evidence to support decision-making on the use of digital mental health technologies? A cross-sectional analysis of studies supporting NICE evaluations
ABSTRACT
Background:
Digital mental health technologies (DMHTs) are playing an increasing role in mental health services. The quality of evidence for DMHTs is variable and there are concerns that evidence is not sufficient to support decision-making.
Objective:
This study used a cross-sectional analysis of evidence supporting DMHTs included in NICE evaluations to examine the strength of evidence available for decision-making.
Methods:
We identified all NICE evaluations relating to DMHTs by reviewing details of published NICE evaluations on the NICE website. From each of these evaluations, we identified included DMHTs and reviewed committee documentation to identify studies which provided supporting evidence for each of these technologies. We extracted information on a series of items relating to study quality and summarised the characteristics of evidence both at the level of individual studies and across the package of evidence from multiple studies supporting DMHTs. We also identified key evidence gaps in available evidence.
Results:
We included 78 studies supporting 30 DMHTs in nine NICE evaluations. We identified common evidence gaps relating to effectiveness compared to relevant comparators, use of appropriate outcomes including on health-related quality of life, cost of delivery and impact on resource use, and reporting of adverse events.
Conclusions:
Our study highlights that some DMHTs have been supported by high-quality studies and that evidence to support DMHTs is likely to be developed across a series of studies. However, there are often key evidence gaps that need to be addressed to provide a stronger case for adoption. Developers should ensure that they consider these gaps while planning evidence generation and where possible address them earlier in the product lifecycle. Clinical Trial: Not applicable
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.