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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.

Type
Service Models, Forms of Delivery and Cultural Adaptations of CBT
Creative Commons
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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

Introduction

Background

Amongst older adults, mental health difficulties are common, with depression affecting 22–28% (Age UK, 2016) and anxiety affecting 5% (Bryant et al., Reference Bryant, Jackson and Ames2007). Despite this, older adults are significantly less likely to be referred for psychological therapies than their working age counterparts (Frost et al., Reference Frost, Bhanu, Walters, Beattie and Ben-Shlomo2019; Nair et al., Reference Nair, Bhanu, Frost, Buszewicz and Walters2020; Walters et al., Reference Walters, Falcaro, Freemantle, King and Ben-Shlomo2018). In fact, Cooper et al. (Reference Cooper, Bebbington, McManus, Meltzer, Stewart, Farrell, King, Jenkins and Livingston2010) found that younger adults were 80% more likely than older adults with comparable mental health difficulties to receive therapy. This inequality increases with age, with those aged ≥85 years five times less likely to be referred for psychological therapies than those aged 55–59 years (Walters et al., Reference Walters, Falcaro, Freemantle, King and Ben-Shlomo2018).

Such patterns have been observed in Talking Therapies (previously called Improving Access to Psychological Therapies, IAPT), the UK’s initial treatment pathway for anxiety and depression. Older adults represent just 5.1% of their referrals (NHS Digital, 2021), significantly below the government target of 12%. However, when older adults access Talking Therapies, they are more likely to complete treatment and experience better outcomes (NHS Digital, 2021; Pettit et al., Reference Pettit, Qureshi, Lee, Stirzaker, Gibson, Henley and Byng2017).

Numerous studies have explored why older adults are under-referred for and are under-accessing mental health support. Common barriers have included the belief that poor mental health is an understandable part of ageing (amongst both older adults and healthcare professionals), stigma, fear of burdensomeness, and discomfort talking about mental health (Frost et al., Reference Frost, Bhanu, Walters, Beattie and Ben-Shlomo2019; Nair et al., Reference Nair, Bhanu, Frost, Buszewicz and Walters2020; Wuthrich and Frei, Reference Wuthrich and Frei2015). In addition, practical barriers such as mobility and frailty, transport to sessions, and confidence accessing online therapy may prevent older adults from accessing treatment (Age UK, 2024). These barriers may interfere with access not only at referral, but also in decisions to opt-in to therapy once referred.

Service context and background

In 2021, a Talking Therapies service in the South of England identified that under 2% of clients accessing therapy were over 65 years, in line with the national under-representation of older adults accessing psychological therapies, but lower than the national average. The service also found that from July to August 2021, 35% of older adults referred were not assessed. For many this was because the service decided that Talking Therapies was not a suitable referral for the client; however, in over half of these cases the older adults did not opt-in for assessment, declined assessment, or did not attend their assessment (hereafter referred to as did not opt-in [DNOI]; personal communication, November 2021).

Increasing access to psychological therapies for older adults is a national priority across all mental health services, and increasing access to Talking Therapies for older adults is one of the key NHS objectives for 2023–2024 (NHS England, 2022). Staff at Talking Therapies were committed to increasing the number of older adults seen; however, efforts to date had focused on increasing referrals. It was evident that alongside increasing referrals, understanding why so many older adults who were referred DNOI was essential, thus this project was commissioned.

Theory of behaviour change

Barriers to opting-in will be considered within the COM-B model (Michie et al., Reference Michie, Van Stralen and West2011), a model of behaviour change. The COM-B model proposes that for behaviours like opting-in to occur, people must have Capability (internal factors like physical and psychological skills and knowledge), Opportunity (external factors like physical and social circumstances), and Motivation (automatic processes like emotion, and reflective processes like beliefs and plans). This framework can be used to help identify corresponding evidence-based intervention approaches (see Fig. 1) and is increasingly used in healthcare research. It has informed recommendations to change the behaviours of healthcare professionals and service-users in areas like digital risk assessment (Lau-Zhu et al., Reference Lau-Zhu, Anderson and Lister2022), medication adherence (Mishra et al., Reference Mishra, Vamadevan, Roy, Bhatia, Naik, Singh, Amevinya, Ampah, Fernandez, Free, Laar, Prabhakaran, Perel and Legido-Quigley2021) and social prescribing (Aughterson et al., Reference Aughterson, Baxter and Fancourt2020).

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. (Reference McDonagh, Harwood, Saunders, Cassell and Rait2020) under Creative Commons Attribution 4.0 Unported (CC BY 4.0) license.

Aims

A service evaluation was consequently approved with the following aims:

  1. (1) To understand the characteristics of older adults who DNOI to Talking Therapies.

  2. (2) To explore how older adults who DNOI experience the process of opting-in at Talking Therapies, and their reasons for not opting-in.

  3. (3) To make recommendations for overcoming barriers to opting-in to increase the accessibility of Talking Therapies for older adults.

Phase 1 Method

Design

Phase 1 involved cross-sectional quantitative analysis of data routinely collected by Talking Therapies at referral, to understand differences between older adults who do and DNOI.

Sample and procedure

Anonymised data were extracted for people aged 65 years and over who were referred to Talking Therapies between 1 February 2019 and 1 February 2022; 4388 referrals were made in this time-period; 3335 where the client opted-in, 691 where the client DNOI, and 362 where this was unclear or the option to opt-in was not offered so these were excluded. The process of identifying referrals to be included and excluded is illustrated in Fig. 2. A retrospective dataset of 4026 referrals was formed. Some clients had multiple referrals in the time-period studied, thus the 4026 referrals in the dataset were for 3796 clients.

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

Analysis

Analyses were conducted using IBM SPSS statistics version 28 (IBM Corporation, 2021). The opted-in and DNOI groups were compared on demographic and referral characteristics using chi-square test of homogeneity, t-tests or Mann–Whitney U-test. Tests of normality determined which variables met criteria for parametric analysis. Due to small sample sizes within variable categories, many were simplified to ensure that expected frequencies met the assumptions of the analyses used.

Next, binomial logistic regression with simultaneous entry was used to establish the individual contributions of variables that differed between the groups to predicting not opting-in. Whether English was a first language was not included, as 80% of cases were excluded due to missing data; 3296 cases were included in the regression, 2919 who opted-in and 377 who DNOI.

Phase 1 Results

Sample characteristics

Clients were 72.9 years on average (SD=6.5, range=65–99), predominantly female (67.9%, n=2732) and of White British ethnicity (79.5%, n=3202). The Index of Multiple Deprivation Decile, a measure of relative deprivation (1=most deprived, 10=least deprived; McLennan et al., Reference McLennan, Noble, Noble, Plunkett, Wright and Gutacker2019), had a median of 8 (range=1–10); 25.3% of clients had a disability (n=1018), and 52.7% had one or more long-term conditions (n=2123).

A majority of the sample were self-referred (61.8%, n=2490), relatively evenly split between the East and West of the county; 43.7% of referrals (n=1760) had at least one previous referral (M=1.0, SD=1.6); 71.3% of referrals (n=2871) were able to receive text messages. Full sample characteristics are reported in Appendix A of the Supplementary material.

Table 1 shows the numbers of older adults referred and opting-in over the audit period. Notably, the proportion of older adults who DNOI increases.

Table 1. Opt-in status by time period

Group differences

The opted-in and DNOI groups differed significantly on 10 variables, presented in Table 2.

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

IMDD, Index of Multiple Deprivation Decile. Characteristics marked with * are those where the categories have been simplified to broader categories due to small sample sizes within subgroups. Male includes trans men, and female includes trans women.

Demographics

The DNOI group were significantly older on average than the opted-in group. A significantly higher proportion of clients who were from ethnic minority backgrounds, had a disability, had a long-term condition, or did not speak English as their first language DNOI. However, these associations were weak and explained at most 1.1% of the variance in opt-in. There were no significant differences across gender, Index of Multiple Deprivation Decile (IMDD), relationship status or sexuality.

Referral characteristics

A significantly higher proportion of clients who had no previous referral, were referred by others, were from the east of the county, and could not receive text messages DNOI. The proportion of clients who DNOI significantly increased with each referral period. However, these associations were weak and explained at most 6.3% of the variance in opt-in. There was no significant difference in number of previous referrals.

Binomial logistic regression

A binomial logistic regression was performed to ascertain the relative odds of not opting-in whilst controlling for inter-relationships between the variables (Table 3). The model was statistically significant, χ2(10)=113.228, p < .001, and explained 6.6% (Nagelkerke R 2) of the variance in opting-in. It correctly classified 88.6% of cases, but showed no discrimination ability. Only age, ethnicity, whether previously referred, whether text messages were allowed, and referral source remained significant as predictors of not opting-in. Increasing age was associated with increased likelihood of not-opting in. Not opting-in was 2.16 times more likely for people from ethnic minority groups, 1.74 times more likely if not able to receive text messages, and 1.92 times more likely if referred by others. People with a previous referral were more likely to not-opt in.

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

Phase 2 Method

Design

Phase 2 involved qualitative analysis of older adult clients’ reasons for not opting-in, elicited through surveys and interviews to contextualise Phase 1 findings. Their ideas for improvements to support older adults to opt-in were also sought.

Participants

Clients aged 65 years and over who DNOI to Talking Therapies between September and November 2022 were invited to provide survey or interview feedback about their experience and reasons for not opting-in. Recruitment was repeated in December, January and February due to lower-than-expected response; 39 of the 60 clients referred were successfully contacted. Clients read and discussed an information sheet and gave written or oral informed consent if they agreed to participate; 18 agreed to be sent the survey, and eight completed (44.4% response rate); five online, two by telephone, and one by post. Eight clients were interviewed.

Procedure

A survey was co-developed with the Older Adult Workstream within Talking Therapies and reviewed by service users. Questions explored referral experiences, reasons for not opting in, and suggestions for improvement. These questions were subsequently developed into a semi-structured interview schedule. The survey could be completed online, by telephone, or by post. Interviews took place by telephone between February and March 2023, were audio recorded, and lasted 15–60 minutes.

Analysis

Interviews were transcribed verbatim and anonymised. Transcripts and survey free-text were analysed using thematic analysis, following guidance from Braun and Clarke (Reference Braun and Clarke2022), using NVivo 12 (QSR International, 1999). Each transcript was read several times to aid familiarisation, and a reflexive log was kept. Keywords and phrases were used to generate initial codes, which were then reviewed and grouped into candidate themes. An inductive stance was taken whilst coding. The COM-B model was then used to organise the themes and identify intervention functions. All authors, as well as clinicians in the Older Adult Workstream, reviewed candidate and final themes to ensure credibility and coherence.

Phase 2 Results

Respondent characteristics

Characteristics of survey and interview respondents are shown in Table 4.

Table 4. Participant characteristics for surveys and interviews

Male includes trans men, and female includes trans women. Characteristics marked with * are those where the categories have been simplified to broader categories due to small sample sizes within subgroups.

Thematic analysis

Four themes and 10 subthemes were identified, corresponding to capability, opportunity and motivational domains of the COM-B model (Fig. 3). Additional illustrative quotes are in Appendix B of the Supplementary material. Names are pseudonyms.

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

The process of referral and opt-in

Some respondents experienced communications with Talking Therapies as happening ‘smoothly’ (Angela); however, for others these were ‘another process that wasn’t working well’ (Pam) and were confusing and time-consuming, especially due to ‘pushbutton’ telephone services. For some, communication had been so poor that they were unaware of their referral until they were discharged. Others described communication issues like calls from withheld numbers and lack of voicemails, resulting in them feeling they had no opportunity to opt-in despite wanting to.

Furthermore, tickboxes and questionnaires in the process of opt-in were off-putting for many respondents as they made interactions feel scripted and made some feel like they were ‘wasting someone’s time’ as options ‘didn’t really fit’ (Survey Response).

Overall, the process was missing the personal touch that respondents felt was crucial in building the trust they required to opt-in. They emphasised the value of telephone calls where they could speak with a human and ask questions, and recommended that older adults might appreciate being followed-up by telephone call after not opting-in.

Talking Therapies is a mystery

Some respondents knew what Talking Therapies were, often through previous referrals, but the majority had limited knowledge and awareness of Talking Therapies and found them ‘a mystery’ (Survey Response). Limited knowledge of the service meant respondents did not know what to expect after referral, with one commenting: ‘If people don’t understand what it is they might just think, I don’t know if that’s what I want’ (Pam). Many stressed that ‘more information about what to expect’ (Survey Response) and information about ‘why it’s worth doing and how it’s helped other people’ their age (Frank) would be helpful.

Regarding making information accessible , online information was described as accessible for some older adults, but that others ‘wouldn’t even think of googling or looking online’ (Survey Response) and may not have the capability or technology to access online resources. Respondents stressed that having information in multiple formats online and offline, with preference for interaction, was important.

Beliefs and attitudes about therapy

Many respondents expressed uncertainty about the effectiveness of therapy , conflicted between awareness that it could be helpful but also believing that ‘rambling on’ could not solve problems: ‘I don’t think you can talk yourself out of problems … Life’s life’ (Paul). For some, these beliefs and their decision to not opt-in were influenced by previous therapy which they found unhelpful. Others felt that therapy effectiveness was therapist dependent, and worried about the youthfulness of Talking Therapies clinicians, wondering ‘how could somebody inexperienced in life start to understand or help people, particularly if they’re stuck in their ways like I am?’ (Douglas).

Respondents commented on a generational difference, whereby the older generation don’t ‘go on about mental health’ , preferring to get on with life and ‘sort yourself out’ (Frank) rather than accept support. Mental health difficulties were still stigmatised for many older adults: ‘a kind of shame that you’re not coping’ (Angela). This meant that many ‘wouldn’t go to the doctors unless [they were] really struggling’ (Frank). Following up older adults who DNOI was therefore stressed as important, as well as normalising mood difficulties.

Many felt that therapy isn’t for me , for different reasons. Some ‘didn’t feel as if [they] needed it’ (Susan). However, alongside this were narratives that their difficulties were not bad enough to warrant support, and worries that they would be in the way of ‘someone else who desperately needed help’ (Paul). Many acknowledged the current pressure on NHS services, not wanting to ‘contribute to the backlog’ (Pam) or ‘bother anybody’ (Susan). Conversely, others felt that Talking Therapies were too ‘superficial’ (Angela) to help with longstanding difficulties. Others believed that they were at the ‘wrong end of life’ (Paul) for therapy, believing they were too old to be helped.

Getting older is a barrier

Physical and cognitive changes were discussed, with not ‘feeling well enough’ (Maria) resulting in some respondents not opting-in. Although acute illness was an understandable barrier, others described longer-term health changes as barriers to opt-in: ‘because of my health difficulties and … disability, it takes quite a lot of energy to get appointments’ (Angela). Online and telephone appointments could be helpful; however, their impersonal nature was also off-putting for some. Cognitive changes also made remembering information they had been given and opting-in difficult for some: ‘I get confused utterly between care providers’ (Douglas). Reminders and repetition of information were considered crucial for overcoming this.

More broadly, older adults described how life changes are overwhelming and could leave them feeling too busy to opt-in, describing that life ‘becomes full of barriers’ (Frank) including losses related to retirement, bereavement, and health. In particular, respondents who were carers highlighted that this role ‘takes over everything and [they] have little or no time or energy for anything else’ (Survey Response) as they did not have sufficient support. It was suggested that asking older adults about barriers and helping them problem-solve may help, but that showing an understanding of the challenges of older age was essential.

Discussion

This service evaluation explored the characteristics of older adults who DNOI to Talking Therapies and the barriers they identified to opting-in.

Results showed that 23.9% of older adults referred to Talking Therapies in the time period audited were not seen, with 15.7% not opting-in, indicating an important point of attrition that could be targeted to increase the number of older adults accessing therapy. Opt-in rates worsened over the three years audited, and although referrals increased post-COVID, a greater proportion of older adults now DNOI, indicating that the pandemic may have exacerbated barriers to older adults opting-in, potentially linked to concerns about burdening the NHS highlighted in interviews. This is worrying as the mental health of older adults worsened throughout the pandemic (Zaninotto et al., Reference Zaninotto, Iob, Demakakos and Steptoe2022) and Office for National Statistics (2022) data indicate that rates of depression remain at double pre-pandemic levels for over-70s, thus the level of unmet need may be growing.

Not opting-in was more likely with increasing age, in line with previous research which found that the proportion of clients referred to IAPT who took up assessments declined after age 64 (Pettit et al., Reference Pettit, Qureshi, Lee, Stirzaker, Gibson, Henley and Byng2017). Notably, over-80s were not represented in our interview sample. Different barriers and cohort beliefs about therapy are likely to be relevant to this group compared with ‘younger’ older adults, and with longevity increasing it is crucial that the barriers to opting-in for different cohorts of older people are understood through further evaluation. Older adults from UK ethnic minority backgrounds were also less likely to opt-in. Racial and ethnic minority populations are less likely to access mental health services generally (Cooper et al., Reference Cooper, Spiers, Livingston, Jenkins, Meltzer, Brugha, McManus, Weich and Bebbington2013; McManus et al., Reference McManus, Bebbington, Jenkins and Brugha2016), and were not represented in our interview sample. Exploring and addressing the barriers to opting-in experienced by older adults from minority populations should be considered in future service evaluations. Similarly, a greater proportion of the DNOI group were disabled and had long-term conditions; however, when inter-relations with other variables were controlled for these were not significant.

People who were referred by others were much more likely to not opt-in compared with those who self-referred, an effect observed across all ages in IAPT (Sweetman et al., Reference Sweetman, Knapp, McMillan, Fairhurst, Delgadillo and Hewitt2022). Talking Therapies may therefore wish to work with local referrers when implementing recommendations, and particularly consider older adults who are not able to self-refer by the current processes. Finally, older adults unable to receive text messages had higher odds of not opting-in, possibly indicating barriers related to access to and confidence using technology, but also highlighting a need for opt-in reminders to be offered in alternative formats.

Thematic analysis of survey and interview data showed that many older adults found the process of opting-in to Talking Therapies confusing, and sometimes had no way of knowing they had been contacted, thus no opportunity to opt-in. Respondents also expressed a strong preference for speaking with clinicians rather than navigating automated systems and questionnaires. This preference extended to ways of accessing information about the service, with most respondents having limited knowledge of Talking Therapies and emphasising that information was inaccessible for many due to it mainly being online, affecting their capability to opt-in. Participants highlighted the importance of making more information about therapy and its benefits for older adults available, and it has been shown that knowledge about treatment promotes participation (Kyle and Shaw, Reference Kyle and Shaw2014). They valued opportunities to ask questions, indicating that allowing more time to speak with older adults may be helpful to facilitate personal connection and increase knowledge of the service.

Some beliefs about therapy were barriers to opt-in, including uncertainty about the helpfulness of therapy, but also whether problems were bad enough and not wanting to be a burden on services or prevent someone who needed it more accessing support. Some also believed they were too old to change, or that therapists were too youthful to understand and help them. These attitudinal barriers have been acknowledged by numerous studies exploring barriers to referral and uptake of therapy by older adults (Age UK, 2024; Berry et al., Reference Berry, Sheardown, Pabbineedi, Haddock, Cross and Brown2020; Frost et al., Reference Frost, Bhanu, Walters, Beattie and Ben-Shlomo2019). Some of these attitudes may reflect internalised ageism, excessively negative stereotypes and beliefs about growing old endorsed by older people and resulting in self-fulfilling limitations (Law et al., Reference Law, Laidlaw and Peck2010; Levy, Reference Levy2003). Allen and Ranger (Reference Allen and Ranger2013) emphasise the importance of exploring and challenging ageist beliefs early in therapy as part of treatment socialisation, as beliefs that they are too old to change or that they are wasting the therapist’s time may increase the likelihood of disengagement. Exploring these beliefs with older adults in early conversations with Talking Therapies and through outreach may therefore promote opt-in. Stigma was also identified as an important motivational barrier to opt-in. Mental health stigma is a significant barrier to help-seeking for people of all ages (Clement et al., Reference Clement, Schauman, Graham, Maggioni, Evans-Lacko, Bezborodovs, Morgan, Rüsch, Brown and Thornicroft2015); however, its impact has been found to be stronger amongst older adults, possibly due to exposure to negative images of mental illness that used to be prevalent (Laidlaw and Knight, Reference Laidlaw and Knight2008), suggesting targeted interventions to improve this are indicated.

Cognitive and physical changes also affected respondents’ capability and opportunity to opt in, making it harder to access technology, travel to appointments, and remember to opt-in, in line with previous research (Berry et al., Reference Berry, Sheardown, Pabbineedi, Haddock, Cross and Brown2020; Nair et al., Reference Nair, Bhanu, Frost, Buszewicz and Walters2020). Some older adults wanted to access therapy but felt too overwhelmed by life changes, particularly evident for respondents with caring responsibilities, who are more likely to experience poor mental health (Carers UK, 2019). Increasing awareness and availability of home-based interventions may be helpful in supporting carers and people living with mobility difficulties to opt-in.

Many barriers to opting-in identified here have also been highlighted as barriers to referral, suggesting that these are not service or opt-in specific. Indeed, the IAPT Positive Practice Guide (Age UK, 2024) makes many recommendations which are echoed in this report. This suggests that service initiatives which have focused predominantly on increasing referrals may not have adequately addressed the range of barriers experienced by older adults, which then persist and affect opt-in, limiting effectiveness of efforts to increase the number of older adults accessing therapy.

Strengths and limitations

A strength of this service evaluation was the use of mixed-methodology, combining audit with surveys and interviews to offer a comprehensive understanding of the differences between older adults who do and DNOI, as well as elaboration on their experiences. The use of a psychological model was a further strength, harnessing a theory-driven approach to optimise recommendations to change opt-in behaviour. Consultation of both Talking Therapies clinicians and older adult service users ensured that questions and their delivery were accessible and relevant, and additionally helped to check the feasibility of recommendations, hopefully increasing the likelihood of their implementation. Co-production of future studies with older adults may improve this further, as well as consultation of other services and charities who work with older adults. Finally, the audit time-period allowed the impact of the COVID-19 pandemic on opt-in to be studied and controlled for, indicating that differences observed were enduring.

Key limitations must also be noted. In the audit there was substantial missing data across demographic variables, largely from the DNOI group. Data may have been more complete for clients with previous episodes of care, potentially biasing the regression. This also prevented more detailed analysis of effects of sexuality, employment, relationship status, and presenting difficulties on opt-in. Collecting more data at referral would enable future evaluations to consider these. Furthermore, the sample of interview and survey respondents was small and was not representative of characteristics least likely to opt-in (e.g. from ethnic minority background, older age). Different barriers may be important for those who did not (or were not able) to participate. Feedback is currently collected from clients who have completed therapy. More routine follow-up of clients who DNOI could increase opportunities to capture and understand the views of under-represented groups.

Recommendations

Respondents suggested many potential interventions to improve opt-in behaviour of older adults, which were elaborated on after consideration of the intervention functions recommended by the COM-B model. These were provided to the service in detail and are summarised in Fig. 4 should they assist those developing or delivering services in similar settings. In addition to process changes and education, organisational culture which includes leadership encouraging attention to barriers faced by older adults across service development decisions will be needed to enable improvements. Adoption of one-size-fits-all procedures without considering the specific needs of older adults, and other underrepresented groups, risks indirect discrimination.

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

Conclusion

A proportion (15.7%) of older adults referred to Talking Therapies DNOI. This project has outlined which older adults may be less likely to opt-in following referral, and highlighted key barriers within domains of capability, opportunity and motivation which may negatively impact opting in. Several recommendations have been suggested to improve opt-in amongst older adults. It is hoped these recommendations will support the service to make changes to consider the needs of older adults and increase opt-in rates.

Key practice points

  1. (1) Mental health difficulties are common amongst older adults, yet they are consistently under-represented in mental health services. Considerable effort has focused on increasing referral; however, when they are referred a substantial proportion do not opt-in for support, indicating an important point of attrition that many services could target.

  2. (2) Impersonal and confusing processes, limited knowledge of who Talking Therapies are, stigma and beliefs about therapy, concerns that their problems were not severe enough and of burdening the NHS, and physical, cognitive and life changes with age were barriers to opting-in.

  3. (3) Strategies to increase accessibility of information, change procedures to improve personal connection, and explore and overcome practical and motivational barriers for older adults are suggested, which may be helpful for other services.

  4. (4) Many barriers to opting-in identified here echo research exploring barriers to referral and engaging with therapy, suggesting that they are not service or opt-in specific. Clinicians and those involved in developing services are encouraged to review the many existing materials and guidelines related to working with older people in therapy.

  5. (5) Services must consider barriers to accessing mental health services faced by older adults when considering any service developments, as otherwise these may be exacerbated and the unmet mental health needs of older adults will grow.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S1754470X24000151

Data availability statement

The anonymised quantitative data from this study is available from the corresponding author, A.C., upon reasonable request. We have not made the qualitative data used in this service evaluation publicly available as it would not be possible to be certain that the full transcripts were sufficiently anonymised, and this would not be in the best interest of the patients who participated.

Acknowledgements

The authors wish to thank the Talking Therapies service users who participated in this project. Additional thanks to Claire Hall, Natalie Holmes, Mark Hodgson, and the service users and staff members in the Berkshire Talking Therapies Older Adults Workstream who provided advice and support in the development of this project and its recommendations.

Author contributions

Rachel Prosser: Conceptualization (lead), Data curation (lead), Formal analysis (lead), Investigation (lead), Methodology (lead), Project administration (lead), Writing – original draft (lead), Writing – review & editing (lead); Louisa Dosanjh: Conceptualization (supporting), Data curation (equal), Project administration (supporting), Writing – review & editing (equal); Grace Jell: Conceptualization (equal), Data curation (supporting), Methodology (supporting), Writing – review & editing (equal); Alasdair Churchard: Conceptualization (equal), Formal analysis (supporting), Methodology (supporting), Supervision (lead), Writing – review & editing (supporting).

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing interests

Louisa Dosanjh and Grace Jell are employed by NHS Berkshire Talking Therapies. Rachel Prosser and Alasdair Churchard have no competing interests.

Ethical standards

The authors abided by the ethical Principles of Psychologists and Code of Conduct as set out by the BABCP and BPS. Both phases of this project were deemed service evaluation so did not require ethical approval. The project was discussed with the service research lead, then a detailed project proposal including methodology, materials and analysis was reviewed and approved by the relevant NHS Foundation Trust clinical audit and service improvement team (Audit ID: 9353).

References

Further reading

Age UK (2024). NHS Talking Therapies Positive Practice Guide: Older People. //babcp.com/Therapists/Older-Adults-Positive-Practice-Guide Google Scholar
Charlesworth, G. (2022). Embedding the silver thread in all-age psychological services: training and supervising younger therapists to deliver CBT for anxiety or depression to older people with multi-morbidity. the Cognitive Behavioural Therapist, 15, e49. https://doi.org/10.1017/S1754470X22000447 CrossRefGoogle Scholar
Frost, R., Bhanu, C., Walters, K., Beattie, A., & Ben-Shlomo, Y. (2019). Management of depression and referral of older people to psychological therapies: a systematic review of qualitative studies. British Journal of General Practice, 69, 171181. https://doi.org/10.3399/bjgp19X701297 CrossRefGoogle ScholarPubMed

References

Age UK (2024). NHS Talking Therapies Positive Practice Guide: Older People. https://babcp.com/Therapists/Older-Adults-Positive-Practice-Guide Google Scholar
Allen, C., & Ranger, G. (2013). Ageist beliefs among older people and adapting CBT to challenge this in the therapeutic setting. Clinical Psychology Forum, 250, 1117. https://doi.org/10.53841/bpscpf.2013.1.250.11 CrossRefGoogle Scholar
Aughterson, H., Baxter, L., & Fancourt, D. (2020). Social prescribing for individuals with mental health problems: a qualitative study of barriers and enablers experienced by general practitioners. BMC Family Practice, 21, 194. https://doi.org/10.1186/s12875-020-01264-0 CrossRefGoogle ScholarPubMed
Berry, K., Sheardown, J., Pabbineedi, U., Haddock, G., Cross, C., & Brown, L. J. E. (2020). Barriers and facilitators to accessing psychological therapies for severe mental health difficulties in later life. Behavioural and Cognitive Psychotherapy, 48, 216228. https://doi.org/10.1017/S1352465819000596 CrossRefGoogle ScholarPubMed
Braun, V., & Clarke, V. (2022). Thematic Analysis: A Practice Guide. Sage Publications.CrossRefGoogle Scholar
Bryant, C., Jackson, H., & Ames, D. (2007). The prevalence of anxiety in older adults: methodological issues and a review of the literature. Journal of Affective Disorders, 109, 233250. https://doi.org/10.1016/j.jad.2007.11.008 CrossRefGoogle Scholar
Carers UK (2019). State of caring. A snapshot of unpaid care in the UK, 2019. London: Carers UK.Google Scholar
Clement, S., Schauman, O., Graham, T., Maggioni, F., Evans-Lacko, S., Bezborodovs, N., Morgan, C., Rüsch, N., Brown, J. S. L., & Thornicroft, G. (2015). What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychological Medicine, 45, 1127. https://doi.org/10.1017/S0033291714000129 CrossRefGoogle ScholarPubMed
Cooper, C., Bebbington, P., McManus, S., Meltzer, H., Stewart, R., Farrell, M., King, M., Jenkins, R., & Livingston, G. (2010). The treatment of common mental disorders across age groups: results from the 2007 Adult Psychiatric Morbidity Survey. Journal of Affective Disorders, 127, 96101.CrossRefGoogle ScholarPubMed
Cooper, C., Spiers, N., Livingston, G., Jenkins, R., Meltzer, H., Brugha, T., McManus, S., Weich, S., & Bebbington, P. (2013). Ethnic inequalities in the use of health services for common mental disorders in England. Social Psychiatry and Psychiatric Epidemiology, 48, 685692. https://doi.org/10.1007/s00127-012-0565-y CrossRefGoogle ScholarPubMed
Frost, R., Bhanu, C., Walters, K., Beattie, A., & Ben-Shlomo, Y. (2019). Management of depression and referral of older people to psychological therapies: a systematic review of qualitative studies. British Journal of General Practice, 69, 171181. https://doi.org/10.3399/bjgp19X701297 CrossRefGoogle ScholarPubMed
IBM Corporation (2021). IBM SPSS Statistics for Macintosh, Version 28.0.Google Scholar
Kyle, S., & Shaw, D. (2014). Doctor–patient communication, patient knowledge and health literacy: how difficult can it all be? Bulletin of the Royal College of Surgeons of England, 96, e9e13. https://doi.org/10.1308/rcsbull.2014.96.6.e9 CrossRefGoogle Scholar
Laidlaw, K., & Knight, B. (2008). Handbook of Emotional Disorders in Later Life: Assessment and Treatment. Oxford University Press. https://doi.org/10.1093/med:psych/9780198569459.001.0001 CrossRefGoogle Scholar
Lau-Zhu, A., Anderson, C., & Lister, M. (2022). Assessment of digital risks in child and adolescent mental health services: a mixed-method, theory-driven study of clinicians’ experiences and perspectives. Clinical Child Psychology and Psychiatry, 28, 255269. https://doi.org/10.1177/13591045221098896 CrossRefGoogle ScholarPubMed
Law, J., Laidlaw, K., & Peck, D. (2010). Is depression viewed as an inevitable consequence of age? The “understandability phenomenon” in older people. Clinical Gerontologist, 33, 194209. https://doi.org/10.1080/07317111003773627 CrossRefGoogle Scholar
Levy, B. R. (2003). Mind matters: cognitive and physical effects of aging self-stereotypes. Journal of Gerontology Series B: Psychological Sciences and Social Sciences, 58, P203P211.CrossRefGoogle ScholarPubMed
McDonagh, L. K., Harwood, H., Saunders, J. M., Cassell, J. A., & Rait, G. (2020). How to increase chlamydia testing in primary care: a qualitative exploration with young people and application of a meta-theoretical model. Sexually Transmitted Infections, 96, 571581. https://doi.org/10.1136/sextrans-2019-054309 CrossRefGoogle ScholarPubMed
McLennan, D., Noble, S., Noble, M., Plunkett, E., Wright, G., & Gutacker, N. (2019). The English Indices of Deprivation 2019: Technical Report.Google Scholar
McManus, S., Bebbington, P. E., Jenkins, R., & Brugha, T. (2016). Mental Health and Wellbeing in England: The Adult Psychiatric Morbidity Survey 2014. NHS Digital.Google Scholar
Michie, S., Van Stralen, M. M., & West, R. (2011). The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implementation Science, 6, 112.CrossRefGoogle ScholarPubMed
Mishra, P., Vamadevan, A. S., Roy, A., Bhatia, R., Naik, N., Singh, S., Amevinya, G. S., Ampah, E. A., Fernandez, Y., Free, C., Laar, A., Prabhakaran, D., Perel, P., & Legido-Quigley, H. (2021). Exploring barriers to medication adherence using COM-B Model of behaviour among patients with cardiovascular diseases in low- and middle-income countries: a qualitative study. Patient Prefer Adherence, 15, 13591371. https://doi.org/10.2147/ppa.S285442 CrossRefGoogle ScholarPubMed
Nair, P., Bhanu, C., Frost, R., Buszewicz, M., & Walters, K. R. (2020). A systematic review of older adults’ attitudes towards depression and its treatment. The Gerontologist, 60, 93104. https://doi.org/10.1093/geront/gnz048 Google ScholarPubMed
Office for National Statistics (2022). Coronavirus (COVID-19) Latest Insights: Well-Being. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/articles/coronaviruscovid19latestinsights/wellbeing (accessed 27 June 2023)Google Scholar
Pettit, S., Qureshi, A., Lee, W., Stirzaker, A., Gibson, A., Henley, W., & Byng, R. (2017). Variation in referral and access to new psychological therapy services by age: an empirical quantitative study. British Journal of General Practice, 67, 453459. https://doi.org/10.3399/bjgp17X691361 CrossRefGoogle ScholarPubMed
QSR International (1999). NVivo Qualitative Data Analysis Software.Google Scholar
Sweetman, J., Knapp, P., McMillan, D., Fairhurst, C., Delgadillo, J., & Hewitt, C. (2022). Risk factors for initial appointment non-attendance at Improving Access to Psychological Therapy (IAPT) services: a retrospective analysis. Psychotherapy Research, 33, 535550. https://doi.org/10.1080/10503307.2022.2140616 CrossRefGoogle ScholarPubMed
Walters, K., Falcaro, M., Freemantle, N., King, M., & Ben-Shlomo, Y. (2018). Sociodemographic inequalities in the management of depression in adults aged 55 and over: an analysis of English primary care data. Psychological Medicine, 48, 15041513. https://doi.org/10.1017/S0033291717003014 CrossRefGoogle ScholarPubMed
Wuthrich, V. M., & Frei, J. (2015). Barriers to treatment for older adults seeking psychological therapy. International Psychogeriatrics, 27, 12271236. https://doi.org/10.1017/S1041610215000241 CrossRefGoogle ScholarPubMed
Zaninotto, P., Iob, E., Demakakos, P., & Steptoe, A. (2022). Immediate and longer-term changes in the mental health and well-being of older adults in England during the COVID-19 pandemic. JAMA Psychiatry, 79, 151159. https://doi.org/10.1001/jamapsychiatry.2021.3749 CrossRefGoogle ScholarPubMed
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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