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Background Despite the effectiveness of cognitive remediation, it is not widely implemented because we do not know whether teams will accept it, how much therapist time is needed, whether there are factors which predict lower benefits, whether it is cost-effective and what is required for large-scale roll-out. Objective To understand the factors that will enhance implementation and benefits of cognitive remediation in Early Intervention Services. Design Four work packages: (1) focus groups and interviews exploring the development of satisfaction and preference measures for staff and service users; participant team interviews to collect data, before and after introducing cognitive remediation, to understand team dynamics; (2) an observational study of a newly developed therapist e-training programme; (3) a multiarm multistage four-arm randomised controlled trial comparing different amounts of therapist input with Treatment as Usual; and (4) an analysis of trial data to understand potential mediating and moderating factors that affect treatment benefits. Setting Early Intervention Services in the United Kingdom National Health Service. Participants Staff and service users in touch with Early Intervention Services. Interventions For the e-training, we piloted and then provided an e-learning system for training cognitive remediation therapists. For the randomised trial, we provided a cognitive remediation software programme (CIRCuiTS™,King’s College London, London) that was delivered in three conditions, all offering up to 42 sessions of cognitive remediation. The conditions were: Intensive (one to one with a therapist), Group treatment with a therapist, Independent with drop-in sessions. Main outcome measures Work package 1: We developed two satisfaction measures and tested a team dynamic model. Work package 2: Feasibility and acceptability questionnaire, time to complete e-training modules. Work package 3: The personal recovery measure – Goal Attainment Scale. Results Work package 1: The service user satisfaction with cognitive remediation was reliable and valid. Although it did not show statistically significant differences between the arms of the trial, the most preferred methods (Group and Intensive) had higher associated satisfaction. Team leadership and especially a flattened hierarchy, resources and time were identified as vital for implementation. Our team dynamic model supported the importance of leadership in influencing organisational climate, which then affected staff attitudes. However, this was only significant before staff had any experience of their patients receiving cognitive remediation. Although the sample was much smaller after therapy, this may indicate that experience of the beneficial therapy changes team dynamics. Work package 2: The e-training modules were completed by 43% of the recruited participants. They judged the training to be feasible and acceptable, but it did take longer to complete than expected. COVID-19 with the increased workload may have had some effects, but our data exploration shows that it was individuals who had most recently qualified who had the best outcomes. This may be because of a lighter workload or that they were more used to online training. Adaptations suggested are now being implemented. Work package 3: Following the interim analysis we closed two arms – Independent therapy and Treatment as Usual. Four hundred and forty-eight patients consented and 377 were eligible and completed baseline assessment. They were randomised: Group 134, Independent 65, Intensive 112 and Treatment as Usual 66. At post therapy, there were no differences between Group and Intensive or between Independent and Treatment as Usual, but the combined Group and Intensive versus Treatment as Usual was significant (mean difference: 5.734; standard error = 1.958; p = 0.003; lower confidence interval = 1.898 to upper confidence interval = 9.571). Our economic analysis showed that Group and Intensive cognitive remediation were not different with respect to quality-adjusted life-years (difference £150, 95% confidence interval –£1132 to £1905). Both conferred significant benefit compared with standard care (Group and Treatment as Usual: difference £257, 95% confidence interval –£1694 to £2615; Intensive vs. Treatment as Usual: difference £260, 95% CI –£1654 to £2239). Their cost–benefit for quality-adjusted life-year improvement was well below the National Institute for Health and Care Excellence threshold for adopting the intervention to National Health Service services. Work package 4: Cognition had a small mediation effect, and negative symptoms moderated the transfer of cognitive benefits to goal attainment. Limitations The trial suffered from recruitment difficulties which were overcome when we switched from block to individual randomisation. The final target was large enough to test our main outcomes and moderating and mediating variables. Conclusions Cognitive remediation should be provided in the National Health Service, involving a trained therapist on a Group or Intensive format with team and training support. Future work We have a large database and will continue to investigate factors that affect cognitive remediation benefits. Study registration This study is registered as ISRCTN14678860 https://doi.org/10.1186/ISRCTN14678860. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research Programme (NIHR award ref: RP-PG-0612-20002) and is published in full in Programme Grants for Applied Research; Vol. 12, No. 4. See the NIHR funding and Awards website for further award information. Plain language summary Cognitive problems in people with schizophrenia predict functional recovery even with the best-possible rehabilitation opportunities. One psychological treatment, cognitive remediation can improve both cognitive and functional recovery, such as in social relationships and occupational achievements. We investigated the optimal way of delivering computerised cognitive remediation in Early Intervention Services by incorporating service user and staff views. Our work involved exploring what treatment factors are important to service users, developing two bespoke cognitive remediation satisfaction measures for service users and service providers. Our investigation of team dynamics suggested that a more flexible leadership style together with increasing resources might be most suited to successful delivery. One challenge for large-scale roll-out of cognitive remediation is therapist training opportunities, so we developed an online programme and then tested it in the United Kingdom and, with a few adaptations, it can be provided to the National Health Service. Although cognitive remediation is effective, we do not know how much therapist time produces therapy benefits, so we conducted a trial comparing three options for cognitive remediation treatment that differed in the amount of the therapist time (Independent, Group and Intensive). We compared these options with a no-treatment group. We investigated benefits of each option in 377 participants from Early Intervention Services. The main benefit assessed was whether participants could achieve their personal goals that were set before therapy began. Although we found no change in a social or occupational functioning scale rated by an observer, the Group and Intensive cognitive remediation produced significant achievements in the participants’ own personal goals compared with those who did not receive therapy or who carried out therapy on their own. We also found that any cognitive remediation therapy option improved thinking skills. Group and Intensive therapy were also cost-effective. Overall, cognitive remediation was acceptable and well liked by service users, so all our data suggest that it should be more easily accessible in the National Health Service. Scientific summary Cognitive remediation (CR) therapy is a psychological intervention targeting cognitive dysfunction associated with psychosis with the goal of improving functional outcomes. Cognitive remediation can improve cognitive and functional recovery, as well as increasing confidence and motivation. Evidence from the largest meta-analysis demonstrated that these effects are durable. National Health Service Early Intervention for psychosis services provide care soon after a diagnosis of psychosis to optimise recovery. Embedding CR in those services may confer long-lasting benefits such as improved social relationships and the opportunity to work or take part in further education. The overarching aim of the Enhancing Cognition and quality of Life in early PSychosiEs (ECLIPSE) research programme was to determine the optimal method of introducing computerised CR therapy (CIRCuiTS™) into NHS Early Intervention Services (EIS) considering improvement in cognitive and social function and cost-effectiveness. The programme was centred on work package 3 (WP3), a randomised, blinded multiarm multisite controlled trial comparing three CR implementation methods with each other and with routine clinical care [Treatment as Usual (TAU)]. To aid the interpretation of WP3 and bolster our recommendations to the NHS, WP1 included a series of studies investigating: patient and staff satisfaction with CR; preference for the methods of CR delivery; and the influence of team organisational climate. Although the CR was computerised and can be completed independently, its effects are boosted via learning, practice and feedback supervised by a therapist. WP2 was a series of studies to design and test an online CR therapist training package to use in their individual teams. Finally, WP4 examined mediators and moderators of the trial results to inform teams about how the clinical features of their individual patients may influence the effect of CR. In WP3, the CR modalities were: Intensive 1 : 1 therapist supervision; Group supervision with one therapist; and Independent (self-determined with infrequent access to therapist supervision). Participants were recruited from EIS in 12 mental health trusts, linked to 6 universities and serving diverse urban/rural populations. They were clinically stable and presented with a non-affective psychotic episode not

BackgroundPrevious mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. ObjectiveThis study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. MethodsData were sourced from a large longitudinal mHealth study, wherein participants’ depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants’ behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. ResultsAnalyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β=–93.61, P

Abstract Background A substantial proportion of people with bipolar disorder (BD) experience persistent cognitive difficulties associated with impairments in psychosocial functioning and a poorer disorder course. Emerging evidence suggests that cognitive remediation (CR), a psychological intervention with established efficacy in people with schizophrenia, can also benefit people with BD. Following a proof-of-concept trial showing that CR is feasible and potentially beneficial for people with BD, we are conducting an adequately powered trial in euthymic people with BD to 1) determine whether an individual, therapist-supported, computerised CR can reduce cognitive difficulties and improve functional outcomes; and 2) explore how CR exerts its effects. Methods CRiB2 is a two-arm, assessor-blind, multi-site, randomised controlled trial (RCT) comparing CR to treatment-as-usual (TAU). Participants are people with a diagnosis of BD, aged between 18 and 65, with no neurological or current substance use disorder, and currently euthymic. 250 participants will be recruited through primary, secondary, tertiary care, and the community. Participants will be block-randomised (1:1 ratio, stratified by site) to continue with their usual care (TAU) or receive a 12-week course of therapy and usual care (CR + TAU). The intervention comprises one-on-one CR sessions with a therapist supplemented with independent cognitive training for 30–40 h in total. Outcomes will be assessed at 13- and 25-weeks post-randomisation. Efficacy will be examined by intention-to-treat analyses estimating between-group differences in primary (i.e., psychosocial functioning at week 25 measured with the Functional Assessment Short Test) and secondary outcomes (i.e., measures of cognition, mood, patient-defined goals, and quality of life). Global cognition, metacognitive skills, affect fluctuation, and salivary cortisol levels will be evaluated as putative mechanisms of CR through mediation models. Discussion This study will provide a robust evaluation of efficacy of CR in people with BD and examine the putative mechanisms by which this therapy works. The findings will contribute to determining the clinical utility of CR and potential mechanisms of action. Trial registration Cognitive Remediation in Bipolar 2 (CRiB2): ISRCTN registry: https://www.isrctn.com/ISRCTN10362331 . Registered 04 May 2022. Overall trial status: Ongoing; Recruitment status: Recruiting.

Abstract Cognitive Remediation (CR) improves cognition and functioning but is implemented in a variety of ways (independent, group and one-to-one). There is no information on whether service users find these implementation methods acceptable or if their satisfaction influences CR outcomes. We used mixed participatory methods, including focus groups, to co-develop a CR satisfaction scale. This was refined using three psychometric criteria (Cronbach’s alpha, item discrimination, test-retest agreement) to select items. Factor analysis explored potential substructures. The refined measure was used in structural equation joint modelling to evaluate whether satisfaction with CR is affected by implementation method and treatment engagement or influences recovery outcome, using data from a randomised controlled trial. Four themes (therapy hours, therapist, treatment effects, computer use) generated a 31-item Cognitive Remediation Satisfaction scale (CRS) that reduced to 18 Likert items, 2 binary and 2 open-ended questions following psychometric assessment. CRS had good internal consistency (Alpha = 0.814), test-retest reliability (r= 0.763), and concurrent validity using the Working Alliance Inventory (r = 0.56). A 2-factor solution divided items into therapy engagement and therapy effects. Satisfaction was not related to implementation method but was significantly associated with CR engagement. Therapy hours were significantly associated with recovery, but there was no direct effect of satisfaction on outcome. Although satisfaction is important to therapy engagement, it has no direct effect on outcome. CR therapy hours directly affect outcome irrespective of which implementation model is used, so measuring satisfaction early might help to identify those who are likely to disengage. The study has mixed methods design.

Abstract Recent growth in digital technologies has enabled the recruitment and monitoring of large and diverse populations in remote health studies. However, the generalizability of inference drawn from remotely collected health data could be severely impacted by uneven participant engagement and attrition over the course of the study. We report findings on long-term participant retention and engagement patterns in a large multinational observational digital study for depression containing active (surveys) and passive sensor data collected via Android smartphones, and Fitbit devices from 614 participants for up to 2 years. Majority of participants (67.6%) continued to remain engaged in the study after 43 weeks. Unsupervised clustering of participants’ study apps and Fitbit usage data showed 3 distinct engagement subgroups for each data stream. We found: (i) the least engaged group had the highest depression severity (4 PHQ8 points higher) across all data streams; (ii) the least engaged group (completed 4 bi-weekly surveys) took significantly longer to respond to survey notifications (3.8 h more) and were 5 years younger compared to the most engaged group (completed 20 bi-weekly surveys); and (iii) a considerable proportion (44.6%) of the participants who stopped completing surveys after 8 weeks continued to share passive Fitbit data for significantly longer (average 42 weeks). Additionally, multivariate survival models showed participants’ age, ownership and brand of smartphones, and recruitment sites to be associated with retention in the study. Together these findings could inform the design of future digital health studies to enable equitable and balanced data collection from diverse populations.

BackgroundMajor depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. ObjectiveWe aimed to address these 3 challenges to inform future work in stratified analyses. MethodsUsing smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. ResultsWe demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. ConclusionsThis work contributes to our understanding of how these mobile health–derived features are associated with depression symptom severity to inform future work in stratified analyses.

Abstract The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming popular, given their potential for providing rich data on symptom change and indicators of future state in recurrent conditions such as major depressive disorder (MDD). Understanding recruitment into RMT research is fundamental for improving historically small sample sizes, reducing loss of statistical power, and ultimately producing results worthy of clinical implementation. There is a need for the standardisation of best practices for successful recruitment into RMT research. The current paper reviews lessons learned from recruitment into the Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study, a large-scale, multi-site prospective cohort study using RMT to explore the clinical course of people with depression across the UK, the Netherlands, and Spain. More specifically, the paper reflects on key experiences from the UK site and consolidates these into four key recruitment strategies, alongside a review of barriers to recruitment. Finally, the strategies and barriers outlined are combined into a model of lessons learned. This work provides a foundation for future RMT study design, recruitment and evaluation.

BackgroundRemote measurement technology (RMT) has the potential to address current research and clinical challenges of attention-deficit/hyperactivity disorder (ADHD) symptoms and its co-occurring mental health problems. Despite research using RMT already being successfully applied to other populations, adherence and attrition are potential obstacles when applying RMT to a disorder such as ADHD. Hypothetical views and attitudes toward using RMT in a population with ADHD have previously been explored; however, to our knowledge, there is no previous research that has used qualitative methods to understand the barriers to and facilitators of using RMT in individuals with ADHD following participation in a remote monitoring period. ObjectiveWe aimed to evaluate the barriers to and facilitators of using RMT in individuals with ADHD compared with a group of people who did not have a diagnosis of ADHD. We also aimed to explore participants’ views on using RMT for 1 or 2 years in future studies. MethodsIn total, 20 individuals with ADHD and 20 individuals without ADHD were followed up for 10 weeks using RMT that involved active (questionnaires and cognitive tasks) and passive (smartphone sensors and wearable devices) monitoring; 10 adolescents and adults with ADHD and 12 individuals in a comparison group completed semistructured qualitative interviews at the end of the study period. The interviews focused on potential barriers to and facilitators of using RMT in adults with ADHD. A framework methodology was used to explore the data qualitatively. ResultsBarriers to and facilitators of using RMT were categorized as health-related, user-related, and technology-related factors across both participant groups. When comparing themes that emerged across the participant groups, both individuals with and without ADHD experienced similar barriers and facilitators in using RMT. The participants agreed that RMT can provide useful objective data. However, slight differences between the participant groups were identified as barriers to RMT across all major themes. Individuals with ADHD described the impact that their ADHD symptoms had on participating (health-related theme), commented on the perceived cost of completing the cognitive tasks (user-related theme), and described more technical challenges (technology-related theme) than individuals without ADHD. Hypothetical views on future studies using RMT in individuals with ADHD for 1 or 2 years were positive. ConclusionsIndividuals with ADHD agreed that RMT, which uses repeated measurements with ongoing active and passive monitoring, can provide useful objective data. Although themes overlapped with previous research on barriers to and facilitators of engagement with RMT (eg, depression and epilepsy) and with a comparison group, there are unique considerations for people with ADHD, for example, understanding the impact that ADHD symptoms may have on engaging with RMT. Researchers need to continue working with people with ADHD to develop future RMT studies for longer periods.

Abstract Background Cognitive remediation (CR) therapy for psychosis significantly improves recovery but is yet to be widely implemented in NHS services. It is likely to be of value at the earliest stages of psychosis development – at the first episode. Organisational climate is one factor likely to affect implementation into Early Intervention Services (EIS), which serve those experiencing first episode psychosis. We aimed to understand the organisational climate within UK NHS Early Intervention for Psychosis (EIP) services and the barriers and facilitators for the introduction of CR. Methods We conducted semi structured interviews with 42 EIS members of four teams in four NHS Trusts. Thematic analysis was used to analyse the data. Results There were differences between teams, including leadership style, involvement in decision making and willingness to adopt CR. Resource shortages were considered the main barrier for implementation across all teams. The evidence base behind CR and the recognition of there being a clinical need was seen as the main facilitator. Teams with more democratic leadership, and knowledge of both the evidence base and need for CR, may feel better able to successfully incorporate it into their service. Conclusion Despite enthusiasm for novel treatments, EIS teams are limited by their resources. An understanding of the local organisational variables can help teams establish a culture that values innovation. Clear communication of the evidence base for CR is key to help enable staff to implement novel treatments successfully despite these limited resources and time pressures.

Goal Management Training (GMT) improved self-reported executive functioning in a recent randomized, controlled trial in early intervention for psychosis participants. Little is known about the mechanism for this benefit, so this study investigates objectively measured executive function, the difference between subjective and objective executive function, independent living and employment status as potential moderators of efficacy of GMT.Baseline scores from 81 participants (GMT n = 39 vs Treatment-as-usual; TAU n = 42) were analyzed in a linear mixed model analysis for repeated measures as predictors of improvement on the self-reported Behavior Rating Inventory of Executive Function–Adult version (BRIEF-A) immediately and 30 weeks after GMT. Potential moderators were scores from objective measures of executive functioning, discrepancy between subjective and objective measures, independent living and employment status. Discrepancy was assessed by comparing four clusters of participants with differing patterns of scores.The effect of GMT remained significant regardless of initial objective executive functioning at baseline. Those with higher subjective complaints at baseline in two clusters with (i) both objective and subjective executive dysfunction, and (ii) mostly subjective executive dysfunction experienced greater change after treatment. Living arrangements or participation in education or work did not significantly moderate the effects of GMT.Poor performance on neuropsychological tasks is not an obstacle to making use of GMT, but further knowledge is needed about the benefits of strategy training for individuals with a combination of poor performance with few subjective complaints.

BackgroundRemote measurement technologies (RMTs) have the potential to revolutionize major depressive disorder (MDD) disease management by offering the ability to assess, monitor, and predict symptom changes. However, the promise of RMT data depends heavily on sustained user engagement over extended periods. In this paper, we report a longitudinal qualitative study of the subjective experience of people with MDD engaging with RMTs to provide insight into system usability and user experience and to provide the basis for future promotion of RMT use in research and clinical practice. ObjectiveWe aimed to understand the subjective experience of long-term engagement with RMTs using qualitative data collected in a longitudinal study of RMTs for monitoring MDD. The objectives were to explore the key themes associated with long-term RMT use and to identify recommendations for future system engagement. MethodsIn this multisite, longitudinal qualitative research study, 124 semistructured interviews were conducted with 99 participants across the United Kingdom, Spain, and the Netherlands at 3-month, 12-month, and 24-month time points during a study exploring RMT use (the Remote Assessment of Disease and Relapse-Major Depressive Disorder study). Data were analyzed using thematic analysis, and interviews were audio recorded, transcribed, and coded in the native language, with the resulting quotes translated into English. ResultsThere were 5 main themes regarding the subjective experience of long-term RMT use: research-related factors, the utility of RMTs for self-management, technology-related factors, clinical factors, and system amendments and additions. ConclusionsThe subjective experience of long-term RMT use can be considered from 2 main perspectives: experiential factors (how participants construct their experience of engaging with RMTs) and system-related factors (direct engagement with the technologies). A set of recommendations based on these strands are proposed for both future research and the real-world implementation of RMTs into clinical practice. Future exploration of experiential engagement with RMTs will be key to the successful use of RMTs in clinical care.

Background Patient and public involvement (PPI) groups can provide valuable input to create more accessible study documents with less jargon. However, we don't know whether this procedure improves accessibility for potential participants. Aims We assessed whether participant information sheets were rated as more accessible after PPI review and which aspects of information sheets and study design were important to mental health patients compared with a control group with no mental health service use. Method This was a double-blind quasi-experimental study using a mixed-methods explanatory design. Patients and control participants quantitatively rated pre- and post-review documents. Semi-structured interviews were thematically analysed to gain qualitative feedback on opinions of information sheets and studies. Two-way multivariate analysis of variance was used to detect differences in ratings between pre- and post-review documents. Results We found no significant (P < 0.05) improvements in patient (n = 15) or control group (n = 21) ratings after PPI review. Patients and controls both rated PPI as of low importance in studies and considered the study rationale as most important. However, PPI was often misunderstood, with participants believing that it meant lay patients would take over the design and administration of the study. Qualitative findings highlight the importance of clear, friendly and visually appealing information sheets. Conclusions Researchers should be aware of what participants want to know about so they can create information sheets addressing these priorities, for example, explaining why the research is necessary. PPI is poorly understood by the wider population and efforts must be made to increase diversity in participation.

Abstract Stigma has negative effects on people with mental health problems by making them less likely to seek help. We develop a proof of principle service user supervised machine learning pipeline to identify stigmatising tweets reliably and understand the prevalence of public schizophrenia stigma on Twitter. A service user group advised on the machine learning model evaluation metric (fewest false negatives) and features for machine learning. We collected 13,313 public tweets on schizophrenia between January and May 2018. Two service user researchers manually identified stigma in 746 English tweets; 80% were used to train eight models, and 20% for testing. The two models with fewest false negatives were compared in two service user validation exercises, and the best model used to classify all extracted public English tweets. Tweets classed as stigmatising by service users were more negative in sentiment (t (744) = 12.02, p

Abstract Background Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. Methods Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. Results Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. Conclusions RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

BackgroundDementia misconceptions on Twitter can have detrimental or harmful effects. Machine learning (ML) models codeveloped with carers provide a method to identify these and help in evaluating awareness campaigns. ObjectiveThis study aimed to develop an ML model to distinguish between misconceptions and neutral tweets and to develop, deploy, and evaluate an awareness campaign to tackle dementia misconceptions. MethodsTaking 1414 tweets rated by carers from our previous work, we built 4 ML models. Using a 5-fold cross-validation, we evaluated them and performed a further blind validation with carers for the best 2 ML models; from this blind validation, we selected the best model overall. We codeveloped an awareness campaign and collected pre-post campaign tweets (N=4880), classifying them with our model as misconceptions or not. We analyzed dementia tweets from the United Kingdom across the campaign period (N=7124) to investigate how current events influenced misconception prevalence during this time. ResultsA random forest model best identified misconceptions with an accuracy of 82% from blind validation and found that 37% of the UK tweets (N=7124) about dementia across the campaign period were misconceptions. From this, we could track how the prevalence of misconceptions changed in response to top news stories in the United Kingdom. Misconceptions significantly rose around political topics and were highest (22/28, 79% of the dementia tweets) when there was controversy over the UK government allowing to continue hunting during the COVID-19 pandemic. After our campaign, there was no significant change in the prevalence of misconceptions. ConclusionsThrough codevelopment with carers, we developed an accurate ML model to predict misconceptions in dementia tweets. Our awareness campaign was ineffective, but similar campaigns could be enhanced through ML to respond to current events that affect misconceptions in real time.

BackgroundTracking and visualizing health data using mobile apps can be an effective self-management strategy for mental health conditions. However, little evidence is available to guide the design of mental health–tracking mechanisms. ObjectiveThe aim of this study was to analyze the content of user reviews of depression self-management apps to guide the design of data tracking and visualization mechanisms for future apps. MethodsWe systematically reviewed depression self-management apps on Google Play and iOS App stores. English-language reviews of eligible apps published between January 1, 2018, and December 31, 2021, were extracted from the app stores. Reviews that referenced health tracking and data visualization were included in sentiment and qualitative framework analyses. ResultsThe search identified 130 unique apps, 26 (20%) of which were eligible for inclusion. We included 783 reviews in the framework analysis, revealing 3 themes. Impact of app-based mental health tracking described how apps increased reviewers’ self-awareness and ultimately enabled condition self-management. The theme designing impactful mental health–tracking apps described reviewers’ feedback and requests for app features during data reporting, review, and visualization. It also described the desire for customization and contexts that moderated reviewer preference. Finally, implementing impactful mental health–tracking apps described considerations for integrating apps into a larger health ecosystem, as well as the influence of paywalls and technical issues on mental health tracking. ConclusionsApp-based mental health tracking supports depression self-management when features align with users’ individual needs and goals. Heterogeneous needs and preferences raise the need for flexibility in app design, posing challenges for app developers. Further research should prioritize the features based on their importance and impact on users.

BackgroundGait is an essential manifestation of depression. However, the gait characteristics of daily walking and their relationships with depression have yet to be fully explored. ObjectiveThe aim of this study was to explore associations between depression symptom severity and daily-life gait characteristics derived from acceleration signals in real-world settings. MethodsWe used two ambulatory data sets (N=71 and N=215) with acceleration signals collected by wearable devices and mobile phones, respectively. We extracted 12 daily-life gait features to describe the distribution and variance of gait cadence and force over a long-term period. Spearman coefficients and linear mixed-effects models were used to explore the associations between daily-life gait features and depression symptom severity measured by the 15-item Geriatric Depression Scale (GDS-15) and 8-item Patient Health Questionnaire (PHQ-8) self-reported questionnaires. The likelihood-ratio (LR) test was used to test whether daily-life gait features could provide additional information relative to the laboratory gait features. ResultsHigher depression symptom severity was significantly associated with lower gait cadence of high-performance walking (segments with faster walking speed) over a long-term period in both data sets. The linear regression model with long-term daily-life gait features (R2=0.30) fitted depression scores significantly better (LR test P=.001) than the model with only laboratory gait features (R2=0.06). ConclusionsThis study indicated that the significant links between daily-life walking characteristics and depression symptom severity could be captured by both wearable devices and mobile phones. The daily-life gait patterns could provide additional information for predicting depression symptom severity relative to laboratory walking. These findings may contribute to developing clinical tools to remotely monitor mental health in real-world settings.

BackgroundCommunication via technology is regarded as an effective way of maintaining social connection and helping individuals to cope with the psychological impact of social distancing measures during a pandemic. However, there is little information about which factors have influenced increased use of technology to communicate with others during lockdowns and whether this has changed over time. ObjectiveThe aim of this study is to explore which psychosocial factors (eg, mental health and employment) and pandemic-related factors (eg, shielding and time) influenced an increase in communication via technology during the first lockdown in the United Kingdom. MethodsA cross-sectional, web-based survey was conducted between April and July 2020, examining thoughts, feelings, and behaviors associated with the pandemic, including communicating more using technology (eg, via messaging, phone, or video). We collected sociodemographic information, employment status, mental health service user status, and depression symptoms. We used hierarchical logistic regression to test which factors were associated with communicating more using technology during the lockdown. ResultsParticipants (N=1464) were on average 41.07 (SD 14.61) years old, and mostly women (n=1141; 77.9%), White (n=1265; 86.4%), and employed (n=1030; 70.4%). Participants reported a mild level of depression (mean 9.43, SD 7.02), and were communicating more using technology (n=1164; 79.5%). The hierarchical regression indicated that people who were employed and experiencing lower levels of depression were more likely to report increased communication using technology during a lockdown period of the COVID-19 pandemic, and over time, men communicated more using technology. Increased use of technology to communicate was related to greater communication and the inability to see others due to the social distancing measures enacted during the lockdown. It was not related to a general increase in technology use during the lockdown. ConclusionsAlthough most participants reported increased use of technology to communicate during a lockdown period of the COVID-19 pandemic, this was more apparent in the employed and those experiencing low levels of depression. Moving forward, we should continue to monitor groups who may have been excluded from the benefits of support and communication using technology.

Abstract Background The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes a clinical illness Covid-19, has had a major impact on mental health globally. Those diagnosed with major depressive disorder (MDD) may be negatively impacted by the global pandemic due to social isolation, feelings of loneliness or lack of access to care. This study seeks to assess the impact of the 1st lockdown – pre-, during and post – in adults with a recent history of MDD across multiple centres. Methods This study is a secondary analysis of an on-going cohort study, RADAR-MDD project, a multi-centre study examining the use of remote measurement technology (RMT) in monitoring MDD. Self-reported questionnaire and passive data streams were analysed from participants who had joined the project prior to 1st December 2019 and had completed Patient Health and Self-esteem Questionnaires during the pandemic (n = 252). We used mixed models for repeated measures to estimate trajectories of depressive symptoms, self-esteem, and sleep duration. Results In our sample of 252 participants, 48% (n = 121) had clinically relevant depressive symptoms shortly before the pandemic. For the sample as a whole, we found no evidence that depressive symptoms or self-esteem changed between pre-, during- and post-lockdown. However, we found evidence that mean sleep duration (in minutes) decreased significantly between during- and post- lockdown (− 12.16; 95% CI − 18.39 to − 5.92; p

BackgroundAs the number of mental health apps has grown, increasing efforts have been focused on establishing quality tailored reviews. These reviews prioritize clinician and academic views rather than the views of those who use them, particularly those with lived experiences of mental health problems. Given that the COVID-19 pandemic has increased reliance on web-based and mobile mental health support, understanding the views of those with mental health conditions is of increasing importance. ObjectiveThis study aimed to understand the opinions of people with mental health problems on mental health apps and how they differ from established ratings by professionals. MethodsA mixed methods study was conducted using a web-based survey administered between December 2020 and April 2021, assessing 11 mental health apps. We recruited individuals who had experienced mental health problems to download and use 3 apps for 3 days and complete a survey. The survey consisted of the One Mind PsyberGuide Consumer Review Questionnaire and 2 items from the Mobile App Rating Scale (star and recommendation ratings from 1 to 5). The consumer review questionnaire contained a series of open-ended questions, which were thematically analyzed and using a predefined protocol, converted into binary (positive or negative) ratings, and compared with app ratings by professionals and star ratings from app stores. ResultsWe found low agreement between the participants’ and professionals’ ratings. More than half of the app ratings showed disagreement between participants and professionals (198/372, 53.2%). Compared with participants, professionals gave the apps higher star ratings (3.58 vs 4.56) and were more likely to recommend the apps to others (3.44 vs 4.39). Participants’ star ratings were weakly positively correlated with app store ratings (r=0.32, P=.01). Thematic analysis found 11 themes, including issues of user experience, ease of use and interactivity, privacy concerns, customization, and integration with daily life. Participants particularly valued certain aspects of mental health apps, which appear to be overlooked by professional reviewers. These included functions such as the ability to track and measure mental health and providing general mental health education. The cost of apps was among the most important factors for participants. Although this is already considered by professionals, this information is not always easily accessible. ConclusionsAs reviews on app stores and by professionals differ from those by people with lived experiences of mental health problems, these alone are not sufficient to provide people with mental health problems with the information they desire when choosing a mental health app. App rating measures must include the perspectives of mental health service users to ensure ratings represent their priorities. Additional work should be done to incorporate the features most important to mental health service users into mental health apps.

BackgroundThere is increasing interest in the potential uses of mobile health (mHealth) technologies, such as wearable biosensors, as supplements for the care of people with neurological conditions. However, adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests that engagement is moderated by several barriers and facilitators, but their relative importance is unknown. ObjectiveTo determine preferences and the relative importance of user-generated factors influencing engagement with mHealth technologies for 2 common neurological conditions with a relapsing-remitting course: multiple sclerosis (MS) and epilepsy. MethodsIn a discrete choice experiment, people with a diagnosis of MS (n=141) or epilepsy (n=175) were asked to select their preferred technology from a series of 8 vignettes with 4 characteristics: privacy, clinical support, established benefit, and device accuracy; each of these characteristics was greater or lower in each vignette. These characteristics had previously been emphasized by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Subgroup analyses explored the effects of demographic factors (such as age, gender, and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy), and symptoms that could influence motivation (such as depression). ResultsAnalysis of the responses to the discrete choice experiment validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit, and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support. ConclusionsFor people with neurological conditions such as epilepsy and MS, accuracy (ie, the ability to detect symptoms) is of the greatest interest. However, there are individual differences, and people who are less accepting of technology may need far greater reassurance about data privacy. People with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mHealth technologies.

Background The high prevalence of mental distress among university students is gaining academic, policy and public attention. As the volume of research into student mental health increases, it is important to involve students to ensure that the evidence produced can translate into meaningful improvements. Aims For the first time, we consult UK students about their research priorities on student mental health. Method This priority setting exercise involved current UK university students who were asked to submit three research questions relating to student mental health. Responses were aggregated into themes through content analysis and considered in the context of existing research. Students were involved throughout the project, including inception, design, recruitment, analysis and dissemination. Results UK university students (N = 385) submitted 991 questions, categorised into seven themes: epidemiology, causes and risk factors, academic factors and work–life balance, sense of belonging, intervention and services, mental health literacy and consequences. Across themes, respondents highlighted the importance of understanding the experience of minority groups. Conclusions Students are interested in understanding the causes and consequences of poor mental health at university, across academic and social domains. They would like to improve staff and students’ knowledge about mental health, and have access to evidence-based support. Future research should take a broad lens to evaluate interventions; considering how services are designed and delivered, and investigating institutional and behavioural barriers to accessibility, including how this varies across different groups within the student population.

BackgroundRemote measurement technologies (RMT) such as mobile health devices and apps are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, although little is known about visualization design preferences from the perspectives of those living with chronic conditions. ObjectiveThe aim of this review was to explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health. MethodsIn this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, Association for Computing Machinery Computer-Human Interface proceedings, and the Cochrane Library) for original papers published between January 2007 and September 2021 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised, and extracted data underwent thematic synthesis. ResultsWe identified 35 eligible publications from 31 studies representing 12 conditions. Coded data coalesced into 3 themes: desire for data visualization, impact of visualizations on condition management, and visualization design considerations. Data visualizations were viewed as an integral part of users’ experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting both between and within conditions. ConclusionsWhen used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not “one-size-fits-all,” and it is important to engage with potential users during visualization design to understand when, how, and with whom the visualizations will be used to manage health.

BackgroundThe mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. ObjectiveWe aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. MethodsData used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. ResultsThis study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=−0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, P

BackgroundDementia misconceptions on social media are common, with negative effects on people with the condition, their carers, and those who know them. This study codeveloped a thematic framework with carers to understand the forms these misconceptions take on Twitter. ObjectiveThe aim of this study is to identify and analyze types of dementia conversations on Twitter using participatory methods. MethodsA total of 3 focus groups with dementia carers were held to develop a framework of dementia misconceptions based on their experiences. Dementia-related tweets were collected from Twitter’s official application programming interface using neutral and negative search terms defined by the literature and by carers (N=48,211). A sample of these tweets was selected with equal numbers of neutral and negative words (n=1497), which was validated in individual ratings by carers. We then used the framework to analyze, in detail, a sample of carer-rated negative tweets (n=863). ResultsA total of 25.94% (12,507/48,211) of our tweet corpus contained negative search terms about dementia. The carers’ framework had 3 negative and 3 neutral categories. Our thematic analysis of carer-rated negative tweets found 9 themes, including the use of weaponizing language to insult politicians (469/863, 54.3%), using dehumanizing or outdated words or statements about members of the public (n=143, 16.6%), unfounded claims about the cures or causes of dementia (n=11, 1.3%), or providing armchair diagnoses of dementia (n=21, 2.4%). ConclusionsThis is the first study to use participatory methods to develop a framework that identifies dementia misconceptions on Twitter. We show that misconceptions and stigmatizing language are not rare. They manifest through minimizing and underestimating language. Web-based campaigns aiming to reduce discrimination and stigma about dementia could target those who use negative vocabulary and reduce the misconceptions that are being propagated, thus improving general awareness.

Abstract Background Although cognitive impairment is a core symptom of schizophrenia related to poorer outcomes in different functional domains, it still remains a major therapeutic challenge. To date, no comprehensive treatment guidelines for cognitive impairment in schizophrenia are implemented. Methods The aim of the present guidance paper is to provide a comprehensive meta-review of the current available evidence-based treatments for cognitive impairment in schizophrenia. The guidance is structured into three sections: pharmacological treatment, psychosocial interventions, and somatic treatments. Results Based on the reviewed evidence, this European Psychiatric Association guidance recommends an appropriate pharmacological management as a fundamental starting point in the treatment of cognitive impairment in schizophrenia. In particular, second-generation antipsychotics are recommended for their favorable cognitive profile compared to first-generation antipsychotics, although no clear superiority of a single second-generation antipsychotic has currently been found. Anticholinergic and benzodiazepine burdens should be kept to a minimum, considering the negative impact on cognitive functioning. Among psychosocial interventions, cognitive remediation and physical exercise are recommended for the treatment of cognitive impairment in schizophrenia. Noninvasive brain stimulation techniques could be taken into account as add-on therapy. Conclusions Overall, there is definitive progress in the field, but further research is needed to develop specific treatments for cognitive impairment in schizophrenia. The dissemination of this guidance paper may promote the development of shared guidelines concerning the treatment of cognitive functions in schizophrenia, with the purpose to improve the quality of care and to achieve recovery in this population.

The pathways from trauma—via dissociation—to psychosis have been thoroughly tested and evidenced, but what has received less attention has been the social pathways—via dissociation—to psychosis. Often social factors are more commonly linked to other influences, e.g., to appraisals and the creation of negative schema in cognitive models, or to unsupportive caregiving experiences where there is high “expressed emotion.” However, evidence is now emerging that negative social rank experiences, such as being excluded or shamed, may themselves have dissociative properties, which poses intriguing questions as to how trauma pathways and social pathways might interact. This article reviews the state of knowledge in trauma and social pathways to psychosis and then considers the potential mechanisms and the relationships between them, specifically (i) dissociation, (ii) attachment, and (iii) social rank. Recommendations are suggested for future modeling and testing of three-way interactions (dissociation × attachment × social rank) in the pathway from trauma to psychosis.

Abstract Background Staff and service users have expressed concerns that service improvements in British mental health wards have been slow or transient. It is possible that certain changes are positive for some (e.g. service users), but negative for others (e.g. staff), which may affect implementation success. In this study, we explore whether a programme of change to improve the therapeutic milieu on mental health wards influenced staff perceptions of barriers to change, 12 months after implementation. Method A cluster randomised controlled trial called DOORWAYS was conducted on eight British, inner-city acute mental health wards. Randomisation was achieved using a list randomly generated by a computer. A psychologist trained ward staff (mainly nurses) to deliver evidence-based groups and supported their initial implementation. The impact of these changes was measured over 12 months (when 4 wards were randomised), according to nurses’ perceptions of barriers to change (VOCALISE), using unstructured multivariate linear regression models. This innovative analysis method allows maximum use of data in randomised controlled trials with reduced sample sizes due to substantial drop out rates. The contextual influences of occupational status (staff) and of workplace setting (ward) were also considered. Results Staff who participated in the intervention had significantly worse perceptions of barriers to change at follow up. The perceptions of staff in the control group did not change over time. In both groups (N = 120), direct care staff had more negative perceptions of barriers to change, and perceptions varied according to ward. Across time, direct care staff in the intervention group became more negative than those in the control group. Conclusion Participation in this program of change, worsened staff perceptions of barriers to change. In addition, occupational status (being from the direct care group) had a negative effect on perceptions of barriers to change, an effect that continued across time and was worse in the intervention group. Those providing direct care should be offered extra support when changes are introduced and through the implementation process. More effort should be placed around reducing the perceived burden of innovation for staff in mental health wards. Trial registration ISRCTN, ISRCTN 06545047. Registered 29/04/2010, https://www.isrctn.com/search?q=06545047

Background Patient and public involvement can improve study outcomes, but little data have been collected on why this might be. We investigated the impact of the Feasibility and Support to Timely Recruitment for Research (FAST-R) service, made up of trained patients and carers who review research documents at the beginning of the research pipeline. Aims To investigate the impact of the FAST-R service, and to provide researchers with guidelines to improve study documents. Method A mixed-methods design assessing changes and suggestions in documents submitted to the FAST-R service from 2011 to 2020. Quantitative measures were readability, word count, jargon words before and after review, the effects over time and if changes were implemented. We also asked eight reviewers to blindly select a pre- or post-review participant information sheet as their preferred version. Reviewers’ comments were analysed qualitatively via thematic analysis. Results After review, documents were longer and contained less jargon, but did not improve readability. Jargon and the number of suggested changes increased over time. Participant information sheets had the most suggested changes. Reviewers wanted clarity, better presentation and felt that documents lacked key information such as remuneration, risks involved and data management. Six out of eight reviewers preferred the post-review participant information sheet. FAST-R reviewers provided jargon words and phrases with alternatives for researchers to use. Conclusions Longer documents are acceptable if they are clear, with jargon explained or substituted. The highlighted barriers to true informed consent are not decreasing, although this study has suggestions for improving research document accessibility.

Objective Given the increasing number of publicly available mental health apps, we need independent advice to guide adoption. This paper discusses the challenges and opportunities of current mental health app rating systems and describes the refinement process of one prominent system, the One Mind PsyberGuide Credibility Rating Scale (PGCRS). Methods PGCRS Version 1 was developed in 2013 and deployed for 7 years, during which time a number of limitations were identified. Version 2 was created through multiple stages, including a review of evaluation guidelines and consumer research, input from scientific experts, testing, and evaluation of face validity. We then re-reviewed 161 mental health apps using the updated rating scale, investigated the reliability and discrepancy of initial scores, and updated ratings on the One Mind PsyberGuide public app guide. Results Reliabilities across the scale's 9 items ranged from −0.10 to 1.00, demonstrating that some characteristics of apps are more difficult to rate consistently. The average overall score of the 161 reviewed mental health apps was 2.51/5.00 (range 0.33–5.00). Ratings were not strongly correlated with app store star ratings, suggesting that credibility scores provide different information to what is contained in star ratings. Conclusion PGCRS summarizes and weights available information in 4 domains: intervention specificity, consumer ratings, research, and development. Final scores are created through an iterative process of initial rating and consensus review. The process of updating this rating scale and integrating it into a procedure for evaluating apps demonstrates one method for determining app quality.

Background: Changes in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDDs) and Multiple Sclerosis (MS). Methods: Data were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse—Central Nervous System) program. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night; social activity; sedentary state, steps and physical activity of varying intensity. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender. Results: Participants with MDDs (N = 255) and MS (N = 214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. A lower mean HR and HR variation were observed between pre and during lockdown during the day for MDDs and during the night for MS. HR variation during rest periods also decreased between pre- and post-lockdown in both clinical conditions. We observed a reduction in physical activity for MDDs and MS upon the introduction of lockdowns. The group with MDDs exhibited a net increase in social interaction via social network apps over the three periods. Conclusions: Behavioral responses to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDDs and MS. Remote technology monitoring might promptly activate an early warning of physical and social alterations in these stressful situations. Future studies must explore how stress does or does not impact depression severity.

BackgroundSharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth. ObjectiveThis study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems. MethodsA total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes. ResultsSix main themes, with several subthemes were identified, such as the purpose of data sharing—for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent—increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security. ConclusionsThis study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service.

BackgroundResearch in mental health has found associations between depression and individuals’ behaviors and statuses, such as social connections and interactions, working status, mobility, and social isolation and loneliness. These behaviors and statuses can be approximated by the nearby Bluetooth device count (NBDC) detected by Bluetooth sensors in mobile phones. ObjectiveThis study aimed to explore the value of the NBDC data in predicting depressive symptom severity as measured via the 8-item Patient Health Questionnaire (PHQ-8). MethodsThe data used in this paper included 2886 biweekly PHQ-8 records collected from 316 participants recruited from three study sites in the Netherlands, Spain, and the United Kingdom as part of the EU Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) study. From the NBDC data 2 weeks prior to each PHQ-8 score, we extracted 49 Bluetooth features, including statistical features and nonlinear features for measuring the periodicity and regularity of individuals’ life rhythms. Linear mixed-effect models were used to explore associations between Bluetooth features and the PHQ-8 score. We then applied hierarchical Bayesian linear regression models to predict the PHQ-8 score from the extracted Bluetooth features. ResultsA number of significant associations were found between Bluetooth features and depressive symptom severity. Generally speaking, along with depressive symptom worsening, one or more of the following changes were found in the preceding 2 weeks of the NBDC data: (1) the amount decreased, (2) the variance decreased, (3) the periodicity (especially the circadian rhythm) decreased, and (4) the NBDC sequence became more irregular. Compared with commonly used machine learning models, the proposed hierarchical Bayesian linear regression model achieved the best prediction metrics (R2=0.526) and a root mean squared error (RMSE) of 3.891. Bluetooth features can explain an extra 18.8% of the variance in the PHQ-8 score relative to the baseline model without Bluetooth features (R2=0.338, RMSE=4.547). ConclusionsOur statistical results indicate that the NBDC data have the potential to reflect changes in individuals’ behaviors and statuses concurrent with the changes in the depressive state. The prediction results demonstrate that the NBDC data have a significant value in predicting depressive symptom severity. These findings may have utility for the mental health monitoring practice in real-world settings.

Background Ketamine is a new and promising treatment for depression but comes with challenges to implement because of its potential for abuse. Aims We sought the views of patients to inform policy and practical decisions about the clinical use of ketamine before large-scale roll-out is considered. Method This qualitative study used three focus groups and three validation sessions from 14 patients with prior diagnoses of depression but no experience of ketamine treatment. Focus groups explored their views about clinical use of ketamine and the best way for ketamine to be administered and monitored. The qualitative data were analysed by three service-user researchers using thematic analysis. Results Five themes were generated: changing public perceptions, risks, monitoring, privacy and data protection, and practical aspects. Participants were conscious of the stigma attached to ketamine as a street drug and wanted better public education, and evidence on the safety of ketamine after long-term use. They felt that monitoring was required to provide evidence for ketamine's safe use and administration, but there were concerns about the misuse of this information. Practical aspects included discussions about treatment duration, administration and accessibility (for example who would receive it, under what criteria and how). Conclusions Patients are enthusiastic about ketamine treatment but need more information before national roll-out. The wider societal impact of ketamine treatment also needs to be considered and patients need to be part of any future roll-out to ensure its success.

Background People with bipolar disorder have moderate cognitive difficulties that tend to be more pronounced during mood episodes but persist after clinical remission and affect recovery. Recent evidence suggests heterogeneity in these difficulties, but the factors underlying cognitive heterogeneity are unclear. Aims To examine whether distinct cognitive profiles can be identified in a sample of euthymic individuals with bipolar disorder and examine potential differences between subgroups. Method Cognitive performance was assessed across four domains (i.e. processing speed, verbal learning/memory, working memory, executive functioning) in 80 participants. We conducted a hierarchical cluster analysis and a discriminant function analysis to identify cognitive profiles and considered differences in cognitive reserve, estimated cognitive decline from premorbid cognitive functioning, and clinical characteristics among subgroups. Results Four discrete cognitive profiles were identified: cognitively intact (n = 25; 31.3%); selective deficits in verbal learning and memory (n = 15; 18.8%); intermediate deficits across all cognitive domains (n = 30; 37.5%); and severe deficits across all domains (n = 10; 12.5%). Cognitive decline after illness onset was greater for the intermediate and severe subgroups. Cognitive reserve scores were increasingly lower for subgroups with greater impairments. A smaller proportion of cognitively intact participants were using antipsychotic medications compared with all other subgroups. Conclusions Our findings suggest that individuals with cognitively impaired profiles demonstrate more cognitive decline after illness onset. Cognitive reserve may be one of the factors underlying cognitive variability across people with bipolar disorder. Patients in the intermediate and severe subgroups may be in greater need of interventions targeting cognitive difficulties.

Background: There is evidence that cognitive remediation (CR) is moderately effective in improving cognitive and functional difficulties in people with schizophrenia. However, there is still a limited understanding of what influence different treatment responses. Aim: To identify moderators influencing CR response in people with schizophrenia. Methods: This systematic review follows PRISMA guidelines. Searches were conducted up to January 2019 on PubMed and PsychInfo to identify randomized controlled trials of CR reporting analyses of moderators of treatment response. All papers were assessed for methodological quality and information on sample size, intervention and control condition, moderators, outcomes, effect of moderator on outcomes and demographic characteristics from each study was extracted and critically summarised. Results: Thirty-six studies were included, considering 2737 participants. Study participants consisted on average of people in their late-thirties, mostly men, with over 10 years of illness. The review identified moderators that could be grouped into five categories: demographics, biological, cognitive and functional, psychological, and illness-related characteristics. The assessment of methodological quality showed that many studies had a high risk of bias. Conclusions: There was no high-quality replicated evidence which identifies reliable moderators of CR response. Many moderators were not replicated or presented in single, underpowered studies. Studies also investigated moderators independently despite their potential to overlap (e.g. age and education). Future research should concentrate on evaluating, with sound studies, the role moderators may play in affecting CR treatment response. This information can inform who will benefit most from the therapy and help to improve the benefits of CR. Keywords: Cognitive remediation, Cognition, Moderator, Schizophrenia, Psychosis

BackgroundTo estimate the potential gain in life expectancy from addressing modifiable risk factors for all-cause mortality (excluding suicide and deaths from accidents or violence) across specific serious mental illness (SMI) subgroups, namely schizophrenia, schizoaffective disorders, and bipolar disorders in a Western population.MethodsWe have used relative risks from recent meta-analyses to estimate the population attribution fraction (PAF) due to specific modifiable risk factors known to be associated with all-cause mortality within SMI. The potential gain in life expectancy at birth, age 50 and age 65 years were assessed by estimating the combined effect of modifiable risk factors from different contextual levels (behavioural, healthcare, social) and accounting for the effectiveness of existing interventions tackling these factors. Projections for annual gain in life expectancy at birth during a two-decade was estimated using the Annual Percentage Change (APC) formula. The predicted estimates were based on mortality rates for year 2014-2015.ResultsBased on the effectiveness of existing interventions targeting these modifiable risk factors, we estimated potential gain in life expectancy at birth of four (bipolar disorders), six (schizoaffective disorders), or seven years (schizophrenia). The gain in life expectancy at age 50 years was three (bipolar disorders) or five (schizophrenia and schizoaffective disorders) years. The projected gain in life expectancy at age 65 years was three (bipolar disorders) or four (schizophrenia and schizoaffective disorders) years.ConclusionsThe implementation of existing interventions targeting modifiable risk factors could narrow the current mortality gap between the general and the SMI populations by 24% (men) to 28% (women). These projections represent ideal circumstances and without the limitation of overestimation which often comes with PAFs.

Abstract Background Cognitive problems in people with schizophrenia predict poor functional recovery even with the best possible rehabilitation opportunities and optimal medication. A psychological treatment known as cognitive remediation therapy (CRT) aims to improve cognition in neuropsychiatric disorders, with the ultimate goal of improving functional recovery. Studies suggest that intervening early in the course of the disorder will have the most benefit, so this study will be based in early intervention services, which treat individuals in the first few years following the onset of the disorder. The overall aim is to investigate different methods of CRT. Methods This is a multicentre, randomised, single-blinded, controlled trial based in early intervention services in National Health Service Mental Health Trusts in six English research sites. Three different methods of providing CRT (intensive, group, and independent) will be compared with treatment as usual. We will recruit 720 service users aged between 16 and 45 over 3 years who have a research diagnosis of non-affective psychosis and will be at least 3 months from the onset of the first episode of psychosis. The primary outcome measure will be the degree to which participants have achieved their stated goals using the Goal Attainment Scale. Secondary outcome measures will include improvements in cognitive function, social function, self-esteem, and clinical symptoms. Discussion It has already been established that cognitive remediation improves cognitive function in people with schizophrenia. Successful implementation in mental health services has the potential to change the recovery trajectory of individuals with schizophrenia-spectrum disorders. However, the best mode of implementation, in terms of efficacy, service user and team preference, and cost-effectiveness is still unclear. The CIRCuiTS trial will provide guidance for a large-scale roll-out of CRT to mental health services where cognitive difficulties impact recovery and resilience. Trial registration ISRCTN, ISRCTN14678860, Registered on 6 June 2016.

Table of contents S1 Using computerized adaptive testing Tim Croudace S2 Well-being: what is it, how does it compare to health and what are the implications of using it to inform health policy John Brazier O1 “Am I going to get better?”—Using PROMs to inform patients about the likely benefit of surgery Nils Gutacker, Andrew Street O2 Identifying Patient Reported Outcome Measures for an electronic Personal Health Record Dan Robotham, Samantha Waterman, Diana Rose, Safarina Satkunanathan, Til Wykes O3 Examining the change process over time qualitatively: transformative learning and response shift Nasrin Nasr, Pamela Enderby O4 Developing a PROM to evaluate self-management in diabetes (HASMID): giving patients a voice Jill Carlton, Donna Rowen, Jackie Elliott, John Brazier, Katherine Stevens, Hasan Basarir, Alex Labeit O5 Development of the Primary Care Outcomes Questionnaire (PCOQ) Mairead Murphy, Sandra Hollinghurst, Chris Salisbury O6 Developing the PKEX score- a multimodal assessment tool for patients with shoulder problems Dominic Marley, James Wilson, Amy Barrat, Bibhas Roy O7 Applying multiple imputation to multi-item patient reported outcome measures: advantages and disadvantages of imputing at the item, sub-scale or score level Ines Rombach, Órlaith Burke, Crispin Jenkinson, Alastair Gray, Oliver Rivero-Arias O8 Integrating Patient Reported Outcome Measures (PROMs) into routine primary care for patients with multimorbidity: a feasibility study Ian Porter, Jaheeda Gangannagaripalli, Charlotte Bramwell, Jose M. Valderas O9 eRAPID: electronic self-report and management of adverse-events for pelvic radiotherapy (RT) patients Patricia Holch, Susan Davidson, Jacki Routledge, Ann Henry, Kevin Franks, Alex Gilbert, Kate Absolom & Galina Velikova O10 Patient reported outcomes (PROMs) based recommendation in clinical guidance for the management of chronic conditions in the United Kingdom Ian Porter, Jose M.Valderas O11 Cross-sectional and longitudinal parameter shifts in epidemiological data: measurement invariance and response shifts in cohort and survey data describing the UK’s Quality of Life Jan R. Boehnke O12 Patient-reported outcomes within health technology decision making: current status and implications for future policy Andrew Trigg, Ruth Howells O13 Can social care needs and well-being be explained by the EQ-5D? Analysis of Health Survey for England dataset Jeshika Singh, Subhash Pokhrel, Louise Longworth O14 Where patients and policy meet: exploring individual-level use of the Long-Term Conditions Questionnaire (LTCQ) Caroline Potter, Cheryl Hunter, Laura Kelly, Elizabeth Gibbons, Julian Forder, Angela Coulter, Ray Fitzpatrick, Michele Peters

BackgroundOnly one-third of patients with major depressive disorder achieve remission. One new and promising treatment, ketamine, may prove challenging to implement because of its abuse potential. Although clinicians' views have been sought, we need patients' views before large scale roll-out is considered.AimsTo explore patients’ and carers' views to inform policy and practical decisions about the clinical use of ketamine.MethodWe carried out a mixed-methods study using data from 44 participants in 21 focus groups in three sessions and an online survey with patients, carers and advocates during a consultation day. Focus groups explored participant's views about ketamine as a form of treatment and the best way for ketamine to be prescribed and monitored. The qualitative data were analysed by two patient–researchers using an exploratory framework analysis and was supplemented by a survey.ResultsThe ten themes generated were monitoring, information, effect on daily life, side-effects, recreational use, effectiveness, appropriate support, cost, stigma and therapy. Participants wanted better evidence on the safety of ketamine after long-term use and felt that monitoring was required. Collecting this information would provide evidence for ketamine's safe use and administration. There were, however, concerns about the misuse of this information. Practical issues of access were important: repeated travelling to clinics and a lack of sufficiently informed medical staff were key barriers.ConclusionsClinicians have some similar and some different views to those of patients, carers and advocates, which need to be considered in any future roll-out of ketamine.Declaration of interestR.M. has had UK National Institute for Health Research grant funding to study ketamine, is participating in trials of esketamine, runs a clinic that provides ketamine treatment, and has consulted for Johnson & Johnson and Eleusis.

Background: Interventions targeting cognition in people with schizophrenia have shown moderate effects on improving functioning. Recent cognitive remediation (CR) approaches have begun to target metacognition to improve functioning outcomes. This study aims to develop a novel measure of metacognition and assess whether metacognitive-based CR (mCR) can improve metacognition. Method: We use data from a single-blinded randomized controlled trial comparing mCR plus treatment as usual (TAU) to TAU alone in people with schizophrenia. Participants were assessed with measures of cognition, functioning, and a new measure of metacognition at three time points: Week 0 (baseline), Week 12, and Week 24. Results: The evaluation of the novel metacognition assessment suggests that it is a reliable and valid measure. The measure positively correlates with cognitive measures, in particular with executive function and IQ but also with a measure of functioning. We found that a course of mCR was able to increase metacognition compared to TAU by Week 24. Conclusions: Metacognition may be an important mechanism to explain how CR affects functioning outcomes in people with psychosis. The systematic assessment of metacognition as part of CR studies may help to evaluate more clearly its role and relevance to functioning.

BackgroundAlthough patients value evidence-based therapeutic activities, little is known about nurses' perceptions.AimsTo investigate whether implementing an activities training programme would positively alter staff perceptions of the ward or be detrimental through the increased workload (trial registration: ISRCTN 06545047).MethodWe conducted a stepped wedge cluster randomised trial involving 16 wards with psychology-led nurse training as the intervention. The main outcome was a staff self-report measure of perceptions of the ward (VOTE) and secondary outcomes measuring potential deterioration were the Index of Work Satisfaction (IWS) and the Maslach Burnout Inventory (MBI). Data were analysed using mixed-effects regression models, with repeated assessments from staff over time.ResultsThere were 1075 valid outcome measurements from 539 nursing staff. VOTE scores did not change over time (standardised effect size 0.04, 95% CI –0.09 to 0.18, P = 0.54), neither did IWS or MBI scores (IWS, standardised effect size 0.02, 95% CI –0.11 to 0.16, P = 0.74; MBI standardised effect size –0.09, 95% CI –0.24 to 0.06, P = 0.24). There was a mean increase of 1.5 activities per ward (95% CI –0.4 to 3.4, P = 0.12) and on average 6.3 more patients attended groups (95% CI –4.1 to 16.6, P = 0.23) following training. Staff feedback on training was positive.ConclusionsOur training programme did not change nurses' perceptions of the ward, job satisfaction or burnout. During the study period many service changes occurred, most having a negative impact through increased pressure on staffing, patient mix and management so it is perhaps unsurprising that we found no benefits or reduction in staff skill.Declaration of interestNone.

Background: Despite the movement towards care in the community, 40% of the NHS budget on mental health care is still attributed to inpatient services. However, long before the Francis Report highlighted grave shortcomings in inpatient care, there were reports by service user groups on the poor quality of these services in mental health. The programme provides a particular focus on the inclusion of the patient’s perspective in the development and evaluation of evidence. Objectives: To understand how changes to inpatient care affect the perceptions of the ward by service users and staff by using stakeholder participatory methods. Design: The programme consisted of four work packages (WPs). (1) Lasting Improvements for Acute Inpatient SEttings (LIAISE): using participatory methods we developed two new scales [Views On Therapeutic Environment (VOTE) for staff and Views On Inpatient CarE (VOICE) for service users]. (2) Client Services Receipt Inventory – Inpatient (CITRINE): working with nurses and service users we developed a health economic measure of the amount of contact service users have with staff. The self-report measure records interactions with staff as well as the number of therapeutic activities attended. (3) Delivering Opportunities for Recovery (DOORWAYS): a stepped-wedge randomised controlled trial to test if training ward nurses to deliver therapeutic group activities would improve the perception of the ward by service users and staff. A total of 16 wards were progressively randomised and we compared the VOICE, VOTE and CITRINE measures before and after the intervention. A total of 1108 service users and 539 staff participated in this trial. (4) Bringing Emergency TreatmenT to Early Resolution (BETTER PATHWAYS) was an observational study comparing two service systems. The first was a ‘triage’ system in which service users were admitted to the triage ward and then either transferred to their locality wards or discharged back into the community within 7 days. The second system was routine care. We collected data from 454 service users and 284 nurses on their perceptions of the wards. Main outcome measures: The main outcomes for the DOORWAYS and BETTER project were service user and staff perceptions of the ward (VOICE and VOTE, respectively) and the health economic measure was CITRINE. All were developed in WPs 1 and 2. Results: We developed reliable and valid measures of (1) the perceptions of inpatient care from the perspectives of service users and nurses (VOICE and VOTE) and (2) costs of interactions that were valued by service users (CITRINE). In the DOORWAYS project, after adjusting for legal status, we found weak evidence for benefit (standardised effect of –0.18, 95% CI 0.38 improvement to 0.01 deterioration; p = 0.062). There was only a significant benefit for involuntary patients following the staff training (N582, standardised effect of –0.35, 95% CI –0.57 to –0.12; p = 0.002; interaction p-value 0.006). VOTE scores did not change over time (standardised effect size of 0.04, 95% CI –0.09 to 0.18; p = 0.54). We found no evidence of an improvement in cost-effectiveness (estimated effect of £33, 95% CI –£91 to £146; p = 0.602), but resource allocation did change towards patient-perceived meaningful contacts by an average of £12 (95% CI –£76 to £98; p = 0·774). There were no significant differences between the triage and routine models of admission in terms of better perceptions by service users (estimated effect 0.77-point improvement in VOICE score on the triage ward; p = 0.68) or nurses (estimated effect of 1.68-point deterioration in VOTE on the triage ward; p = 0.38) or in terms of the cost of the length of care provided (£391 higher on triage; p = 0.77). Strengths and limitations: We have developed measures using methods involving both service users and staff from mental health services. The measures were developed specifically for acute inpatient services and, therefore, cannot be assumed to be useful for other services. For instance, extensions of the measures are under construction for use in mother and baby units. The strength of the BETTER PATHWAYS and DOORWAYS projects is the large-scale data collection. However, we were testing specific services based in inner city areas and stretching to inner urban areas. It may be that different effects would be found in more rural communities or in different types of inpatient care. Future work: Our database will be used to develop an understanding of the mediating and moderating factors for improving care quality. Trial registration: Current Controlled Trials ISRCTN06545047. Funding: This project was funded by the NIHR Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 6, No. 7. See the NIHR Journals Library website for further project information.

Schizophrenia is associated with deficits in theory of mind (ToM) (i.e., the ability to infer the mental states of others) and cognition. Associations have often been reported between cognition and ToM, and ToM mediates the relationship between impaired cognition and impaired functioning in schizophrenia. Given that cognitive deficits could act as a limiting factor for ToM, this study investigated whether a cognitive remediation therapy (CRT) that targets nonsocial cognition and metacognition could improve ToM in schizophrenia. Four men with schizophrenia received CRT. Assessments of ToM, cognition, and metacognition were conducted at baseline and posttreatment as well as three months and 1 year later. Two patients reached a significant improvement in ToM immediately after treatment whereas at three months after treatment all four cases reached a significant improvement, which was maintained through 1 year after treatment for all three cases that remained in the study. Improvements in ToM were accompanied by significant improvements in the most severely impaired cognitive functions at baseline or by improvements in metacognition. This study establishes that a CRT program that does not explicitly target social abilities can improve ToM.

Background: The negative symptoms of schizophrenia significantly impact on quality of life and social functioning, and current treatment options are limited. In this study the clinical effectiveness and cost-effectiveness of group body psychotherapy as a treatment for negative symptoms were compared with an active control. Design: A parallel-arm, multisite randomised controlled trial. Randomisation was conducted independently of the research team, using a 1 : 1 computer-generated sequence. Assessors and statisticians were blinded to treatment allocation. Analysis was conducted following the intention-to-treat principle. In the cost-effectiveness analysis, a health and social care perspective was adopted. Participants: Eligibility criteria: age 18–65 years; diagnosis of schizophrenia with symptoms present at > 6 months; score of ≥ 18 on Positive and Negative Syndrome Scale (PANSS) negative symptoms subscale; no change in medication type in past 6 weeks; willingness to participate; ability to give informed consent; and community outpatient. Exclusion criteria: inability to participate in the groups and insufficient command of English. Settings: Participants were recruited from NHS mental health community services in five different Trusts. All groups took place in local community spaces. Interventions: Control intervention: a 10-week, 90-minute, 20-session group beginners’ Pilates class, run by a qualified Pilates instructor. Treatment intervention: a 10-week, 90-minute, 20-session manualised group body psychotherapy group, run by a qualified dance movement psychotherapist. Outcomes: The primary outcome was the PANSS negative symptoms subscale score at end of treatment. Secondary outcomes included measures of psychopathology, functional, social, service use and treatment satisfaction outcomes, both at treatment end and at 6-month follow-up. Results: A total of 275 participants were randomised (140 body psychotherapy group, 135 Pilates group). At the end of treatment, 264 participants were assessed (137 body psychotherapy group, 127 Pilates group). The adjusted difference in means of the PANSS negative subscale at the end of treatment was 0.03 [95% confidence interval (CI) –1.11 to 1.17], showing no advantage of the intervention. In the secondary outcomes, the mean difference in the Clinical Assessment Interview for negative symptoms expression subscale at the end of treatment was 0.62 (95% CI –1.23 to 0.00), and in extrapyramidal movement disorder symptoms –0.65 (95% CI –1.13 to –0.16) at the end of treatment and –0.58 (95% CI –1.07 to –0.09) at 6 months’ follow-up, showing a small significant advantage of body psychotherapy. No serious adverse events related to the interventions were reported. The total costs of the intervention were comparable with the control, with no clear evidence of cost-effectiveness for either condition. Limitations: Owing to the absence of a treatment-as-usual arm, it is difficult to determine whether or not both arms are an improvement over routine care. Conclusions: In comparison with an active control, group body psychotherapy does not have a clinically relevant beneficial effect in the treatment of patients with negative symptoms of schizophrenia. These findings conflict with the review that led to the current National Institute for Health and Care Excellence guidelines suggesting that arts therapies may be an effective treatment for negative symptoms. Future work: Determining whether or not this lack of effectiveness extends to all types of art therapies would be informative. Trial registration: Current Controlled Trials ISRCTN842165587. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 11. See the NIHR Journals Library website for further project information.

The objective of this case study was to assess the specific effect of cognitive remediation for schizophrenia on the pattern of cognitive impairments. Case A is a 33-year-old man with a schizophrenia diagnosis and impairments in visual memory, inhibition, problem solving, and verbal fluency. He was provided with a therapist delivered cognitive remediation program involving practice and strategy which was designed to train attention, memory, executive functioning, visual-perceptual processing, and metacognitive skills. Neuropsychological and clinical assessments were administered at baseline and after three months of treatment. At posttest assessment, Case A had improved significantly on targeted (visual memory and problem solving) and nontargeted (verbal fluency) cognitive processes. The results of the current case study suggest that (1) it is possible to improve specific cognitive processes with targeted exercises, as seen by the improvement in visual memory due to training exercises targeting this cognitive domain; (2) cognitive remediation can produce improvements in cognitive processes not targeted during remediation since verbal fluency was improved while there was no training exercise on this specific cognitive process; and (3) including learning strategies in cognitive remediation increases the value of the approach and enhances participant improvement, possibly because strategies using verbalization can lead to improvement in verbal fluency even if it was not practiced.