Qualitative meta-synthesis of user experience of computerised therapy for depression and anxiety.
OBJECTIVE
Computerised therapies play an integral role in efforts to improve access to psychological treatment for patients with depression and anxiety. However, despite recognised problems with uptake, there has been a lack of investigation into the barriers and facilitators of engagement. We aimed to systematically review and synthesise findings from qualitative studies of computerised therapies, in order to identify factors impacting on engagement.


METHODS
Systematic review and meta-synthesis of qualitative studies of user experiences of computer delivered therapy for depression and/or anxiety.


RESULTS
8 studies were included in the review. All except one were of desktop based cognitive behavioural treatments. Black and minority ethnic and older participants were underrepresented, and only one study addressed users with a co-morbid physical health problem. Through synthesis, we identified two key overarching concepts, regarding the need for treatments to be sensitive to the individual, and the dialectal nature of user experience, with different degrees of support and anonymity experienced as both positive and negative. We propose that these factors can be conceptually understood as the 'non-specific' or 'common' factors of computerised therapy, analogous to but distinct from the common factors of traditional face-to-face therapies.


CONCLUSIONS
Experience of computerised therapy could be improved through personalisation and sensitisation of content to individual users, recognising the need for users to experience a sense of 'self' in the treatment which is currently absent. Exploiting the common factors of computerised therapy, through enhancing perceived connection and collaboration, could offer a way of reconciling tensions due to the dialectal nature of user experience. Future research should explore whether the findings are generalisable to other patient groups, to other delivery formats (such as mobile technology) and other treatment modalities beyond cognitive behaviour therapy. The proposed model could aid the development of enhancements to current packages to improve uptake and support engagement.
NIHR School for Primary Care Research, Centre for Primary Care, University of Manchester, Manchester, United Kingdom.
Sarah E
SE
Knowles
NIHR School for Primary Care Research, Centre for Primary Care, University of Manchester, Manchester, United Kingdom.
Gill
G
Toms
NIHR School for Primary Care Research, Centre for Primary Care, University of Manchester, Manchester, United Kingdom.
Caroline
C
Sanders
School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, United Kingdom.
Penny
P
Bee
School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, United Kingdom.
Karina
K
Lovell
Mixed Reality Lab, School of Computer Science, University of Nottingham, Nottingham, United Kingdom.
Stefan
S
Rennick-Egglestone
Department of Computer Science, University of Bristol, Bristol, United Kingdom.
David
D
Coyle
School of Computer Science, University of Birmingham, Birmingham, United Kingdom.
Catriona M
CM
Kennedy
Mental Health & Addictions Research Group, University of York, York, United Kingdom.
Elizabeth
E
Littlewood
School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
David
D
Kessler
Mental Health & Addictions Research Group, University of York, York, United Kingdom.
Simon
S
Gilbody
NIHR School for Primary Care Research, Centre for Primary Care, University of Manchester, Manchester, United Kingdom.
Peter
P
Bower
D001007:Anxiety / Q000628:therapy*; D003863:Depression / Q000628:therapy*; D006801:Humans; D013813:Therapy, Computer-Assisted