The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Supporting antidepressant discontinuation: the development and optimisation of a digital intervention for patients in UK primary care using a theory-, evidence-, and person-based approach

Supporting antidepressant discontinuation: the development and optimisation of a digital intervention for patients in UK primary care using a theory-, evidence-, and person-based approach
Supporting antidepressant discontinuation: the development and optimisation of a digital intervention for patients in UK primary care using a theory-, evidence-, and person-based approach
Objectives: we aimed to develop a digital intervention to support antidepressant discontinuation in UK primary care that is scalable, accessible, safe and feasible. In this paper we describe the development using a theory- evidence- and person-based approach.

Design: intervention development using a theory-, evidence-, and person-based approach

Setting: Primary Care in the South of England

Participants: fifteen participants with a range of antidepressant experience took part in ‘think aloud’ interviews for intervention optimisation
Intervention: Our digital intervention prototype (called ‘ADvisor’) was developed on the basis of a planning phase consisting of qualitative and quantitative reviews, an in-depth qualitative study, the development of guiding principles and a theory-based behavioural analysis. Our optimisation phase consisted of ‘think aloud’ interviews where the intervention was iteratively refined.

Results: the qualitative systematic review and in-depth qualitative study highlighted the centrality of fear of depression relapse as a key barrier to discontinuation. The quantitative systematic review showed that psychologically informed approaches such as cognitive behaviour therapy (CBT) were associated with greater rates of discontinuation than simple advice to reduce. Following a behavioural diagnosis based on the Behaviour Change Wheel, Social Cognitive Theory provided a theoretical basis for the intervention. The intervention was optimised on the basis of think aloud interviews, where participants suggested they like the flexibility of the system and found it reassuring. Changes were made to the tone of the material and the structure was adjusted based on this qualitative feedback.
Conclusions: ‘ADvisor’ is an evidence-, theory- and person-based digital intervention designed to support antidepressant discontinuation. The intervention was perceived as helpful and reassuring in optimisation interviews. Trials are now needed to determine the feasibility, clinical and cost effectiveness of this approach.
antidepressants, depression & mood disorders, digital intervention, intervention development, primary care
2044-6055
Bowers, Hannah
c81d418d-3cd7-4da5-bd09-0eee862bd49f
Kendrick, Tony
c697a72c-c698-469d-8ac2-f00df40583e5
Glowacka, Marta A
0a98f919-4886-4029-a2bb-f349746b146e
Williams, Samantha
7cec7c3e-7247-473e-8121-f26b625893e1
Leydon, Geraldine
c5cdaff5-0fa1-4d38-b575-b97c2892ec40
May, Carl
86bf173e-540c-4849-b760-94e85f93c2e3
Dowrick, Chris
30d40fd6-a65c-49e5-8841-2c84a3f82ec1
Moncrieff, Joanna
02891f66-8e9a-4af0-b56f-482041b23a72
Laine, Rebecca
963a62a6-ab30-40b4-8f7a-ff56fda86cd8
Nestoriuc, Yvonne
4e36d95a-657d-4152-a444-b550108913da
Andersson, Gerhard
1965d18a-9891-41f3-8149-ce6aebe2f5ff
Geraghty, Adam
2c6549fe-9868-4806-b65a-21881c1930af
Bowers, Hannah
c81d418d-3cd7-4da5-bd09-0eee862bd49f
Kendrick, Tony
c697a72c-c698-469d-8ac2-f00df40583e5
Glowacka, Marta A
0a98f919-4886-4029-a2bb-f349746b146e
Williams, Samantha
7cec7c3e-7247-473e-8121-f26b625893e1
Leydon, Geraldine
c5cdaff5-0fa1-4d38-b575-b97c2892ec40
May, Carl
86bf173e-540c-4849-b760-94e85f93c2e3
Dowrick, Chris
30d40fd6-a65c-49e5-8841-2c84a3f82ec1
Moncrieff, Joanna
02891f66-8e9a-4af0-b56f-482041b23a72
Laine, Rebecca
963a62a6-ab30-40b4-8f7a-ff56fda86cd8
Nestoriuc, Yvonne
4e36d95a-657d-4152-a444-b550108913da
Andersson, Gerhard
1965d18a-9891-41f3-8149-ce6aebe2f5ff
Geraghty, Adam
2c6549fe-9868-4806-b65a-21881c1930af

Bowers, Hannah, Kendrick, Tony, Glowacka, Marta A, Williams, Samantha, Leydon, Geraldine, May, Carl, Dowrick, Chris, Moncrieff, Joanna, Laine, Rebecca, Nestoriuc, Yvonne, Andersson, Gerhard and Geraghty, Adam (2020) Supporting antidepressant discontinuation: the development and optimisation of a digital intervention for patients in UK primary care using a theory-, evidence-, and person-based approach. BMJ Open, 10 (3), [e032312]. (doi:10.1136/bmjopen-2019-032312).

Record type: Article

Abstract

Objectives: we aimed to develop a digital intervention to support antidepressant discontinuation in UK primary care that is scalable, accessible, safe and feasible. In this paper we describe the development using a theory- evidence- and person-based approach.

Design: intervention development using a theory-, evidence-, and person-based approach

Setting: Primary Care in the South of England

Participants: fifteen participants with a range of antidepressant experience took part in ‘think aloud’ interviews for intervention optimisation
Intervention: Our digital intervention prototype (called ‘ADvisor’) was developed on the basis of a planning phase consisting of qualitative and quantitative reviews, an in-depth qualitative study, the development of guiding principles and a theory-based behavioural analysis. Our optimisation phase consisted of ‘think aloud’ interviews where the intervention was iteratively refined.

Results: the qualitative systematic review and in-depth qualitative study highlighted the centrality of fear of depression relapse as a key barrier to discontinuation. The quantitative systematic review showed that psychologically informed approaches such as cognitive behaviour therapy (CBT) were associated with greater rates of discontinuation than simple advice to reduce. Following a behavioural diagnosis based on the Behaviour Change Wheel, Social Cognitive Theory provided a theoretical basis for the intervention. The intervention was optimised on the basis of think aloud interviews, where participants suggested they like the flexibility of the system and found it reassuring. Changes were made to the tone of the material and the structure was adjusted based on this qualitative feedback.
Conclusions: ‘ADvisor’ is an evidence-, theory- and person-based digital intervention designed to support antidepressant discontinuation. The intervention was perceived as helpful and reassuring in optimisation interviews. Trials are now needed to determine the feasibility, clinical and cost effectiveness of this approach.

Text
REDUCE WS3 patient development paper v3.5 clean revisions - 16.12.2019 - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (98kB)

More information

Accepted/In Press date: 13 January 2020
e-pub ahead of print date: 8 March 2020
Keywords: antidepressants, depression & mood disorders, digital intervention, intervention development, primary care

Identifiers

Local EPrints ID: 437414
URI: http://eprints.soton.ac.uk/id/eprint/437414
ISSN: 2044-6055
PURE UUID: f9a74141-73e0-4333-8f36-a6dad144e93f
ORCID for Tony Kendrick: ORCID iD orcid.org/0000-0003-1618-9381
ORCID for Samantha Williams: ORCID iD orcid.org/0000-0001-9505-6485
ORCID for Geraldine Leydon: ORCID iD orcid.org/0000-0001-5986-3300
ORCID for Adam Geraghty: ORCID iD orcid.org/0000-0001-7984-8351

Catalogue record

Date deposited: 29 Jan 2020 17:35
Last modified: 10 Jan 2022 02:56

Export record

Altmetrics

Contributors

Author: Hannah Bowers
Author: Tony Kendrick ORCID iD
Author: Marta A Glowacka
Author: Carl May
Author: Chris Dowrick
Author: Joanna Moncrieff
Author: Rebecca Laine
Author: Yvonne Nestoriuc
Author: Gerhard Andersson
Author: Adam Geraghty ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×