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Proportionate methods for evaluating a simple digital mental health tool

Davies, Eleanor Bethan; Craven, Michael P.; Martin, Jennifer L.; Simons, Lucy

Proportionate methods for evaluating a simple digital mental health tool Thumbnail


Jennifer L. Martin

Lucy Simons


Background: Traditional evaluation methods are not keeping pace with rapid developments in mobile health. More flexible methodologies are needed to evaluate mHealth technologies, particularly simple, self-help tools. One approach is to combine a variety of methods and data to build a comprehensive picture of how a technology is used and its impact on users.

Objective: This paper aims to demonstrate how analytical data and user feedback can be triangulated to provide a proportionate and practical approach to the evaluation of a mental wellbeing smartphone app (‘In Hand’).
Methods: A three-part process was used to collect data: 1) app analytics; 2) an online user survey; and 3) interviews with users.

Findings: Analytics showed that >50% of user sessions counted as ‘meaningful engagement’. User survey findings (N=108) revealed that In Hand was perceived to be helpful on several dimensions of mental wellbeing. Interviews (N=8) provided insight into how these self-reported positive effects were understood by users.

Conclusions: This evaluation demonstrates how different methods can be combined to complete a real-world, naturalistic evaluation of a self-help digital tool and provide insights into how and why an app is used and its impact upon users’ wellbeing.

Clinical implications: This triangulation approach to evaluation provides insight into how wellbeing apps are used and their perceived impact on users’ mental wellbeing. This approach is useful for mental healthcare professionals and commissioners who wish to recommend simple digital tools to their patients and evaluate their uptake, use and benefits.


Davies, E. B., Craven, M. P., Martin, J. L., & Simons, L. (2017). Proportionate methods for evaluating a simple digital mental health tool. Evidence-Based Mental Health, 20(4), 112-117.

Journal Article Type Article
Acceptance Date Sep 15, 2017
Online Publication Date Oct 9, 2017
Publication Date Oct 9, 2017
Deposit Date Oct 11, 2017
Publicly Available Date Oct 11, 2017
Journal Evidence Based Mental Health
Print ISSN 1362-0347
Electronic ISSN 1468-960X
Publisher BMJ Publishing Group
Peer Reviewed Peer Reviewed
Volume 20
Issue 4
Pages 112-117
Keywords mHealth; Mixed methods; Evaluation; Co-design; Young people; Mental health; Apps; Mobile phones
Public URL
Publisher URL
Contract Date Oct 11, 2017


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