Cognitive Behavioural Relating Therapy (CBRT) for Voice Hearers: A Case Study

Background: There has been a recent focus on the interpersonal nature of the voice hearing experience, with studies showing that similar patterns of relating exist between voice hearer and voice as between voice hearer and social others. Two recent therapeutic approaches to voices, Cognitive Therapy for Command Hallucinations and Relating Therapy, have been developed to address patterns of relating and power imbalances between voice hearer and voice. Aims: This paper presents a novel intervention that combines elements of these two therapies, named Cognitive Behavioural Relating Therapy (CBRT). Method: The application of CBRT is illustrated through a clinical case study. Results: The clinical case study showed changes in patterns of relating, improved self-esteem and reductions in voice-related distress. Conclusions: The outcomes provide preliminary support for the utility of CBRT when working with voice hearers.</jats:p

Derivation of a prediction model for a diagnosis of depression in young adults: a matched case-control study using electronic primary care records.

Background: Approximately 80 000 children and young people in the UK suffer from depression, but many are untreated because of poor identification of early warning signs and risk factors. Aims: This study aimed to derive and to investigate discrimination characteristics of a prediction model for a first recorded diagnosis of depression in young people aged 15–24 years. Method: This study used a matched case–control method using electronic primary care records. Stepwise conditional logistic regression modelling investigated 42 potential predictors including symptoms, co‐morbidities, social factors and drug and alcohol misuse. Results: Of the socio‐economic and symptomatic predictors identified, the strongest associations were with depression symptoms and other psychological conditions. School problems and social services involvement were prominent predictors in men aged 15–18 years, work stress in women aged 19–24 years. Conclusion: Our model is a first step in the development of a predictive model identifying early warning signs of depression in young people in primary care

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse : the EMPOWER feasibility cluster RCT

Funding Information: Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879). Funding Information: The research reported in this issue of the journal was funded by the HTA programme as project number 13/154/04. The contractual start date was in April 2016. The draft report began editorial review in September 2019 and was accepted for publication in March 2020. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HTA editors and publisher have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this report. Funding Information: Declared competing interests of authors: Andrew I Gumley reports personal fees from the University of Manchester, the University of Exeter and the British Association for Behavioural & Cognitive Psychotherapies (BABCP) (Accrington, UK), and other interests with NHS Education for Scotland outside the submitted work. John Ainsworth reports other interests with Affigo CIC (Manchester, UK) outside the submitted work. Sandra Bucci is a director of Affigo CIC, a not-for-profit social enterprise company spun out of the University of Manchester in December 2015 to enable access to social enterprise funding and to promote ClinTouch, a symptom-monitoring app, to the NHS and public sector. Andrew Briggs reports personal fees from Bayer (Leverkusen, Germany), Merck Sharp & Dohme (Kenilworth, NJ, USA), Janssen Pharmaceutica (Beerse, Belgium), Novartis (Basel, Switzerland), SWORD Health (Porto, Portugal), Amgen Inc. (Thousand Oaks, CA, USA) and Daiichi Sankyo (Tokyo, Japan) outside the submitted work. John Farhall reports grants from the National Health and Medical Research Council (Australia) during the conduct of the study and other interests with Melbourne Health (NorthWestern Mental Health, Parkville, VIC, Australia) outside the submitted work. Shôn Lewis reports grants from the Medical Research Council, non-financial support from Affigo CIC and personal fees from XenZone plc (Manchester, UK) outside the submitted work. Cathy Mihalopoulos reports grants from National Health and Medical Research Council (Australia) during the conduct of the study. John Norrie reports grants from the University of Aberdeen and the University of Edinburgh during the conduct of the study and declares membership of the following NIHR boards: CPR Decision Making Committee (2016), HTA Commissioning Board (2010–16), HTA Commissioning Sub-Board (EOI) (2012–16), HTA Funding Boards Policy Group (2016), HTA General Board (2016–19), HTA Post-Board funding teleconference (2016–19), NIHR CTU Standing Advisory Committee (2017–present), NIHR HTA and EME Editorial Board (2014–19) and Pre-exposure Prophylaxis Impact Review Panel (2017–present). Paul French is a member of the HTA Mental Health Prioritisation Panel (2017–present). Chris Williams reports grants from NIHR during the conduct of the study (HTA 10/104/34 BEAT-IT: a randomised controlled trial comparing a behavioural activation treatment for depression in adults with learning disabilities with attention control; NIHR multicentre RCT of a group psychological intervention for postnatal depression in British mothers of South Asian Origin: RP-PG-0514-20012: Integrated therapist and online CBT for depression in primary care); other from Five Areas Ltd (Clydebank, UK) outside the submitted work; and that he has twice been president of the British Association for Behavioural & Cognitive Psychotherapies, the lead body for cognitive–bahavioural therapy in the UK. This body aims to advocate use of evidence-based delivery of cognitive–bahavioural therapy. Publisher Copyright: © Queen’s Printer and Controller of HMSO 2022.Peer reviewedPublisher PD

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT.

BACKGROUND: Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse. OBJECTIVE: How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? DESIGN: A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up. SETTINGS: Glasgow, UK, and Melbourne, Australia. PARTICIPANTS: Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user. INTERVENTIONS: The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted. MAIN OUTCOME MEASURES: The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse. RESULTS: We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference -4.29, 95% confidence interval -7.29 to -1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained. LIMITATIONS: This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness. CONCLUSIONS: A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible. FUTURE WORK: A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3-0.4). TRIAL REGISTRATION: This trial is registered as ISRCTN99559262. FUNDING: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879)