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Which older adults do not opt-in to Talking Therapies and why?

Published online by Cambridge University Press:  24 May 2024

Rachel Prosser
Affiliation:
Oxford Institute of Clinical Psychology Training and Research, University of Oxford, Isis Education Centre, Warneford Hospital, Headington, Oxford, UK
Louisa Dosanjh
Affiliation:
NHS Berkshire Talking Therapies, UK
Grace Jell
Affiliation:
NHS Berkshire Talking Therapies, UK
Alasdair Churchard*
Affiliation:
Oxford Institute of Clinical Psychology Training and Research, University of Oxford, Isis Education Centre, Warneford Hospital, Headington, Oxford, UK
*
Corresponding author: Alasdair Churchard; Email: Alasdair.churchard@hmc.ox.ac.uk
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Abstract

Abstract

Older adults are under-represented in Talking Therapies (previously named IAPT) services in the UK, a national priority for improvement in the NHS. A Talking Therapies service in the south of England identified that many older adults who were referred did not opt-in to assessment. We aimed to explore the characteristics of these older adults and understand their experiences, to inform recommendations to support them to opt-in to the service in future. First, demographic and referral characteristics were compared for older adults who did and did not opt-in, to explore any that increased odds of not opting-in. Next, surveys and semi-structured interviews were used to investigate older adults’ reasons for not opting-in. Responses were thematically analysed, and themes were categorised using the COM-B model to inform theory-based recommendations. Older age, being from an ethnic minority group, having a previous referral, not being able to receive text messages, and not self-referring (e.g. being referred by GP) all significantly increased the chances of older adults not opting-in. Thematic analysis found that impersonal and confusing processes, as well as older adults’ limited knowledge of Talking Therapies, beliefs about therapy, and physical, cognitive and life changes with age were barriers to opting-in. Several recommendations are made, including ideas to increase accessibility of information, change procedures to improve personal connection, and explore and overcome practical barriers. Improving routine data and feedback collection from people who do not opt-in will be important to inform and evaluate improvements.

Key learning aims

  1. (1) To recognise that the ongoing issue of under-representation of older adults within Talking Therapies extends beyond barriers to referral.

  2. (2) To understand demographic and referral characteristics that may increase the likelihood of older adults not opting-in to a Talking Therapies service following referral.

  3. (3) To understand the experiences of older adults who do not opt-in and the barriers they cite, exploring factors that impacted their capability, opportunity and motivation to opt-in.

  4. (4) To consider how services could change their procedures, information sharing, and community outreach to better serve older adults.

Information

Type
Service Models, Forms of Delivery and Cultural Adaptations of CBT
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of British Association for Behavioural and Cognitive Psychotherapies
Figure 0

Figure 1. The Capability-Opportunity-Motivation-Behaviour (COM-B) model at the centre of the Behavioural Change Wheel. The COM-B model is depicted with associated interventions and policy categories, each with a brief description. Reproduced from McDonagh et al. (2020) under Creative Commons Attribution 4.0 Unported (CC BY 4.0) license.

Figure 1

Figure 2. Process of identifying the opted-in and DNOI groups.

Figure 2

Table 1. Opt-in status by time period

Figure 3

Table 2. Comparisons of older adults who did and did not opt-in

Figure 4

Table 3. Binomial logistic regression model to predict not opting-in (n=3296)

Figure 5

Table 4. Participant characteristics for surveys and interviews

Figure 6

Figure 3. Themes with corresponding domains of the COM-B Model.

Figure 7

Figure 4. Recommended interventions grouped by themes and COM-B domains.

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