Improving mental health provision for adults with learning disabilities and autistic adults – Understanding how to increase inclusiveness of NHS Talking Therapies for Anxiety and Depression (INCLUSIVE-TALK)

Background

About 8 in 10 autistic adults (AA) and 5 in 10 adults with learning disabilities (ALD) have a mental health problem in their lifetime, much higher rates than the general population. This leads to adverse outcomes and avoidable suffering. Talking therapy may help, but the limited evidence-base suggests the key service offering this, NHS Talking Therapies for anxiety and depression (TTad ), does not support ALD&AA well. ALD&AA report access problems, lack of benefit, and lonely, stigmatising experiences.

Aims To improve ALD&AA’s access to, experience in, and outcomes from TTad, so they can live happier, healthier lives. A1: To explore:

a) If ALD&AA status and intersection of this with other aspects affecting care (e.g., minority ethnicity/multiple long-term conditions) is linked to poorer service pathways or outcomes.

b) How to predict TTad treatment response, the link between TTad and future mental health service use, and the accuracy of TTad digital records for ALD.

A2: To build on A1 findings, creating outputs to improve ALD&AA’s TTad access, experience, outcomes, and digital records. Methods In the largest talking therapies study in ALD or AA, we will use mixed methods to address our aims:

Workstream (WS)1 uses England-wide sessional TTad data, linked to healthcare records (n=5 million people referred to TTad; ALD=24,664, AA=23,329; 12-year follow up) to address A1. We have unique access to this data and are the only team who can do this work. We will use:

1. Regression to see if ALD/AA status and its intersection with other aspects affecting care is linked to TTad outcomes (e.g., PHQ-9 scores) and experiences (e.g., wait times). 2. Growth mixture models and regression to examine predictors of TTad treatment response.

3. Poisson regression to look at association of ALD&AA’s TTad pathways/outcomes with future secondary mental health service use. 4. Cohen’s Kappa to compare accuracy of current ALD TTad digital records vs health records diagnoses. WS2 will: 1. Meta-synthesise qualitative literature on ALD&AA’s mental health access & experiences.

2. Interview ALD/AA/clinicians to understand these experiences (15 of each). 3. Thematically analyse 1&2 above, using a co-created framework based on theory (e.g., Candidacy) and WS1 results. 4. Run 6 (n=8) stakeholder consensus nominal groups to co-create outputs below. We have the expertise (>100 relevant papers) to do this work.

PPI

Mental health service improvement is AA’s top research priority and key for ALD. This inspired our project and PPI is central. Our project was co-created with 2 PPI leads. Two charity partners will run ALD&AA PPI groups. PPI from inception-dissemination will facilitate uptake & relevance. To support this ~10% total budget is for PPI.

EDI is central and embedded in the overarching aims to reduce inequities faced by AA&AL and examine intersectionality with other important characteristics. Timelines/Impact/Dissemination Our 3-year project will transform TTad for ALD&AA. Outputs will include (but not be limited to): -Clinical guidelines with implementation plans for pilot sites & beyond.

-Training packages for TTad staff. -Policy briefings. -Co-designed resources for ALD&AA (with easy-read versions) to guide navigation of TTad. We will: -Update ALD&AA (via charity partner membership/social media).

-Work with partners (e.g., AA & ALD, NHS England TTad lead, TTad service leads, charities, Royal College of Psychiatrists) to ensure impact & uptake.