Extending the use of routine outcome monitoring: Predicting long-term outcomes in cognitive behavioral therapy for severe health anxiety

Objective: Routine outcome monitoring (ROM) is a well-evidenced means of improving psychotherapy’s effectiveness. However, it is unclear how meaningful ROM is for problems that span physical and mental health, such as severe health anxiety. Physical and mental health comorbidities are common amongst severe health anxiety sufferers and cognitive behavioral therapy (CBT) is a recommended treatment. Method: Seventy-nine participants received CBT for severe health anxiety in a clinical trial. The Outcome Rating Scale (ORS: a ROM assessment of wellbeing) was completed at each session. Multilevel modeling assessed whether last-session ORS predicted health anxiety and other outcomes over 12-month follow-up. Similar models were developed using health anxiety as a comparative outcome-predictor. Outcome-improvements of treatment-responders with sudden gains were compared to those of non-sudden-gainers. Results: Last-session ORS scores predicted all outcomes up to 12 months later, with a comparable predictive effect to health anxiety. Sudden-gainers on the ORS reported significantly greater improvement in depression, functioning, and wellbeing, but no difference in health anxiety or other measures. Conclusion: The ORS may be a feasible, overall estimate of health, functioning, and quality of life in psychotherapy for severe health anxiety. Sudden gains on the ORS may be clinically meaningful with respect to some long-term outcomes

An explanatory sequential investigation of the working alliance as a change process in videoconferencing psychotherapy

Objectives and Design Debate exists as to patient experience, and the importance, of the working alliance (WA) in videoconferencing psychotherapy (VCP). This study used a two-phase explanatory sequential design to investigate the WA as a change process in VCP. Methods Phase I: sessional VCP outcome and WA data were analysed using multilevel modelling (n = 46). Phase II: participants (n = 12) from Phase I were recruited to semi-structured interviews, analysed using thematic framework analysis. Results and Conclusions Results demonstrate: (1) a significant correlation between WA and outcome (F(1, 15.19) = 25.01, p < 0.001), (2) previous session WA significantly predicted outcome in the next session (F(1, 355.61) = 4.47, p < 0.05), and (3) previous session outcome significantly predicted next session WA (F(1, 55.3) = 15.19, p < 0.001), with three core themes explaining patient experience (engaging with the medium, connection with the therapist, and working via the medium). Results are discussed and future research recommended

The Acceptability and Usability of Digital Health Interventions for Adults With Depression, Anxiety, and Somatoform Disorders: Qualitative Systematic Review and Meta-Synthesis

The prevalence of mental health disorders continues to rise, with almost 4% of the world population having an anxiety disorder and almost 3.5% having depression in 2017. Despite the high prevalence, only one-third of people with depression or anxiety receive treatment. Over the last decade, the use of digital health interventions (DHIs) has risen rapidly as a means of accessing mental health care and continues to increase. Although there is evidence supporting the effectiveness of DHIs for the treatment of mental health conditions, little is known about what aspects are valued by users and how they might be improved. This systematic review aimed to identify, appraise, and synthesize the qualitative literature available on service users' views and experiences regarding the acceptability and usability of DHIs for depression, anxiety, and somatoform disorders. A systematic search strategy was developed, and searches were run in 7 electronic databases. Qualitative and mixed methods studies published in English were included. A meta-synthesis was used to interpret and synthesize the findings from the included studies. A total of 24 studies were included in the meta-synthesis, and 3 key themes emerged with descriptive subthemes. The 3 key themes were initial motivations and approaches to DHIs, personalization of treatment, and the value of receiving personal support in DHIs. The meta-synthesis suggests that participants' initial beliefs about DHIs can have an important effect on their engagement with these types of interventions. Personal support was valued very highly as a major component of the success of DHIs. The main reason for this was the way it enabled individual personalization of care. Findings from the systematic review have implications for the design of future DHIs to improve uptake, retention, and outcomes in DHIs for depression, anxiety, and somatoform disorders. DHIs need to be personalized to the specific needs of the individual. Future research should explore whether the findings could be generalized to other health conditions. [Abstract copyright: ©Shireen Patel, Athfah Akhtar, Sam Malins, Nicola Wright, Emma Rowley, Emma Young, Stephanie Sampson, Richard Morriss. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.07.2020.

Preventing Relapse with Personalised Smart-Messaging After Cognitive Behavioral Therapy: A Proof of Concept Evaluation

Objective. Current Cognitive Behavioral Therapy (CBT) relapse prevention methods are often resource intensive. The paper investigates a personalized means of reducing relapse using smart-messaging in two settings; research and routine care. Methods. Fifteen of 56 CBT completers who participated in a trial for the treatment of health anxiety wrote advice they would want if in future they were doing well, experiencing early warning signs of relapse, or experiencing full relapse. Following CBT, participants received weekly text-message requests to rate their wellbeing. Dependent upon their response, participants received tailored advice they had written, appropriate to the wellbeing level reported after recovery from health anxiety. Smart-messaging was also trialed in a routine practice sample of 14 CBT completers with anxiety and depression. Results. Across a 12-month follow-up, participants receiving smart-messaging showed greater health improvements than those who did not. Wellbeing scores showed stability between CBT completion and six-month follow-up among routine care patients. Conclusion. These findings suggest that a low-intensity, personalized relapse prevention method can have a clinical benefit following CBT for common mental health problems

QOL-26. Exploring the experience of young people receiving remotely delivered Acceptance and Commitment Therapy following treatment for a brain tumour

Despite high survival rates of children and young people diagnosed with a brain tumour, survival is often associated with poor psychological, physical, and social outcomes. Acceptance and Commitment Therapy (ACT) is an evidence-based psychological intervention shown to improve psychological and physical outcomes in adults and children with chronic disease, including cancer. The ACT Now study investigates the feasibility of ACT delivered remotely with young people who have experienced a brain tumour. This study aims to describe participant experience whilst better understanding the impact of therapy and capturing the barriers and facilitators to engagement. Participants of the ACT Now study were invited to take part in a semi-structured interview with questions covering experience of study initiation, receipt of ACT, remote delivery and overall impact of ACT. Ten participants who had previously undergone treatment for a brain tumour have been interviewed to date. Interviews were transcribed verbatim and coded into broad themes. We found that pre-therapy mood and altruism served as motivation for interviewees’ involvement in the study. Interviewees reported hoping to learn coping techniques to navigate fluctuating moods and the pressures of young adult life. Despite the technology used for remote delivery occasionally malfunctioning, interviewees reported increased ability to access therapy via this method. However, an overall preference for face-to-face therapy delivery was reported with interviewees describing that they felt communication might have been easier in person. The therapeutic relationship and the therapists’ flexible schedules were seen as facilitators to session attendance. Barriers to attendance were scarcely reported but included scheduling conflicts due to work or school. ACT was highly regarded amongst interviewees and provided an opportunity for them to learn about themselves and how they can live in accordance with their personal values. Interviewees benefitted from ACT psychologically, physically, and socially and reported an overall positive experience of study involvement

Developing an Automated Assessment of In-session Patient Activation for Psychological Therapy: Codevelopment Approach

Background: Patient activation is defined as a patient’s confidence and perceived ability to manage their own health. Patient activation has been a consistent predictor of long-term health and care costs, particularly for people with multiple long-term health conditions. However, there is currently no means of measuring patient activation from what is said in health care consultations. This may be particularly important for psychological therapy because most current methods for evaluating therapy content cannot be used routinely due to time and cost restraints. Natural language processing (NLP) has been used increasingly to classify and evaluate the contents of psychological therapy. This aims to make the routine, systematic evaluation of psychological therapy contents more accessible in terms of time and cost restraints. However, comparatively little attention has been paid to algorithmic trust and interpretability, with few studies in the field involving end users or stakeholders in algorithm development. Objective: This study applied a responsible design to use NLP in the development of an artificial intelligence model to automate the ratings assigned by a psychological therapy process measure: the consultation interactions coding scheme (CICS). The CICS assesses the level of patient activation observable from turn-by-turn psychological therapy interactions. Methods: With consent, 128 sessions of remotely delivered cognitive behavioral therapy from 53 participants experiencing multiple physical and mental health problems were anonymously transcribed and rated by trained human CICS coders. Using participatory methodology, a multidisciplinary team proposed candidate language features that they thought would discriminate between high and low patient activation. The team included service-user researchers, psychological therapists, applied linguists, digital research experts, artificial intelligence ethics researchers, and NLP researchers. Identified language features were extracted from the transcripts alongside demographic features, and machine learning was applied using k-nearest neighbors and bagged trees algorithms to assess whether in-session patient activation and interaction types could be accurately classified. Results: The k-nearest neighbors classifier obtained 73% accuracy (82% precision and 80% recall) in a test data set. The bagged trees classifier obtained 81% accuracy for test data (87% precision and 75% recall) in differentiating between interactions rated high in patient activation and those rated low or neutral. Conclusions: Coproduced language features identified through a multidisciplinary collaboration can be used to discriminate among psychological therapy session contents based on patient activation among patients experiencing multiple long-term physical and mental health conditions

Involving psychological therapy stakeholders in responsible research to develop an automated feedback tool: Learnings from the ExTRAPPOLATE project

Understanding stakeholders’ views on novel autonomous systems in healthcare is essential to ensure these are not abandoned after substantial investment has been made. The ExTRAPPOLATE project applied the principles of Responsible Research and Innovation (RRI) in the development of an automated feedback system for psychological therapists, ‘AutoCICS’. A Patient and Practitioner Reference Group (PPRG) was convened over three online workshops to inform the system's development. Iterative workshops allowed proposed changes to the system (based on stakeholder comments) to be scrutinized. The PPRG reference group provided valuable insights, differentiated by role, including concerns and suggestions related to the applicability and acceptability of the system to different patients, as well as ethical considerations. The RRI approach enabled the anticipation of barriers to use, reflection on stakeholders’ views, effective engagement with stakeholders, and action to revise the design and proposed use of the system prior to testing in future planned feasibility and effectiveness studies. Many best practices and learnings can be taken from the application of RRI in the development of the AutoCICS system

Clinical Perspectives on Using Remote Measurement Technology in Assessing Epilepsy, Multiple Sclerosis, and Depression: Delphi Study

Background: Multiple sclerosis (MS), epilepsy, and depression are chronic central nervous system conditions in which remote measurement technology (RMT) may offer benefits compared with usual assessment. We previously worked with clinicians, patients, and researchers to develop 13 use cases for RMT: 5 in epilepsy (seizure alert, seizure counting, risk scoring, triage support, and trend analysis), 3 in MS (detecting silent progression, detecting depression in MS, and donating data to a biobank), and 5 in depression (detecting trends, reviewing treatment, self-management, comorbid monitoring, and carer alert). Objective: In this study, we aimed to evaluate the use cases and related implementation issues with an expert panel of clinicians external to our project consortium. Methods: We used a Delphi exercise to validate the use cases and suggest a prioritization among them and to ascertain the importance of a variety of implementation issues related to RMT. The expert panel included clinicians from across Europe who were external to the project consortium. The study had 2 survey rounds (n=23 and n=17) and a follow-up interview round (n=9). Data were analyzed for consensus between participants and for stability between survey rounds. The interviews explored the reasons for answers given in the survey. Results: The findings showed high stability between rounds on questions related to specific use cases but lower stability on questions relating to wider issues around the implementation of RMT. Overall, questions on wider issues also had less consensus. All 5 use cases for epilepsy (seizure alert, seizure counting, risk scoring, triage support, and trend analysis) were considered beneficial, with consensus among participants above the a priori threshold for most questions, although use case 3 (risk scoring) was considered less likely to facilitate or catalyze care. There was very little consensus on the benefits of the use cases in MS, although this may have resulted from a higher dropout rate of MS clinicians (50%). Participants agreed that there would be benefits for all 5 of the depression use cases, although fewer questions on use case 4 (triage support) reached consensus agreement than for depression use cases 1 (detecting trends), 2 (reviewing treatment), 3 (self-management), and 5 (carer alert). The qualitative analysis revealed further insights into each use case and generated 8 themes on practical issues related to implementation. Conclusions: Overall, these findings inform the prioritization of use cases for RMT that could be developed in future work, which may include clinical trials, cost-effectiveness studies, and the commercial development of RMT products and services. Priorities for further development include the use of RMT to provide more accurate records of symptoms and treatment response than is currently possible and to provide data that could help inform patient triage and generate timely alerts for patients and carers

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Non peer reviewe