Using EMPOWER in daily life: a qualitative investigation of implementation experiences.

BACKGROUND: Digital self-management tools blended with clinical triage and peer support have the potential to improve access to early warning signs (EWS) based relapse prevention in schizophrenia care. However, the implementation of digital interventions in psychosis can be poor. Traditionally, research focused on understanding how people implement interventions has focused on the perspectives of mental health staff. Digital interventions are becoming more commonly used by patients within the context of daily life, which means there is a need to understand implementation from the perspectives of patients and carers. METHODS: Semi-structured one-on-one interviews with 16 patients who had access to the EMPOWER digital self-management intervention during their participation in a feasibility trial, six mental health staff members who supported the patients and were enrolled in the trial, and one carer participant. Interviews focused on understanding implementation, including barriers and facilitators. Data were coded using thematic analysis. RESULTS: The intervention was well implemented, and EMPOWER was typically perceived positively by patients, mental health staff and the carer we spoke to. However, some patients reported negative views and reported ideas for intervention improvement. Patients reported valuing that the app afforded them access to things like information or increased social contact from peer support workers that went above and beyond that offered in routine care. Patients seemed motivated to continue implementing EMPOWER in daily life when they perceived it was creating positive change to their wellbeing, but seemed less motivated if this did not occur. Mental health staff and carer views suggest they developed increased confidence patients could self-manage and valued using the fact that people they support were using the EMPOWER intervention to open up conversations about self-management and wellbeing. CONCLUSIONS: The findings from this study suggest peer worker supported digital self-management like EMPOWER has the potential to be implemented. Further evaluations of these interventions are warranted, and conducting qualitative research on the feasibility gives insight into implementation barriers and facilitators, improving the likelihood of interventions being usable. In particular, the views of patients who demonstrated low usage levels would be valuable.

Eye Movement Patterns Can Distinguish Schizophrenia From the Major Affective Disorders and Healthy Control Subjects.

Background and hypothesis: No objective tests are currently available to help diagnosis of major psychiatric disorders. This study evaluates the potential of eye movement behavior patterns to predict schizophrenia subjects compared to those with major affective disorders and control groups. Study design: Eye movements were recorded from a training set of UK subjects with schizophrenia (SCZ; n = 120), bipolar affective disorder (BPAD; n = 141), major depressive disorder (MDD; n = 136), and healthy controls (CON; n = 142), and from a hold-out set of 133 individuals with proportional group sizes. A German cohort of SCZ (n = 60) and a Scottish cohort of CON subjects (n = 184) acted as a second semi-independent test set. All patients met DSMIV and ICD10 criteria for SCZ, BPAD, and MDD. Data from 98 eye movement features were extracted. We employed a gradient boosted (GB) decision tree multiclass classifier to develop a predictive model. We calculated the area under the curve (AUC) as the primary performance metric. Study results: Estimates of AUC in one-versus-all comparisons were: SCZ (0.85), BPAD (0.78), MDD (0.76), and CON (0.85). Estimates on part-external validation were SCZ (0.89) and CON (0.65). In all cases, there was good specificity but only moderate sensitivity. The best individual discriminators included free viewing, fixation duration, and smooth pursuit tasks. The findings appear robust to potential confounders such as age, sex, medication, or mental state at the time of testing. Conclusions: Eye movement patterns can discriminate schizophrenia from major mood disorders and control subjects with around 80% predictive accuracy.

Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon?

The development of trait markers of schizophrenia would represent an important advance in understanding the genetic architecture of the disease. To date, no candidate markers have satisfied all of the trait marker criteria, and many are not specific to the schizophrenia spectrum. Abnormalities in visual scanpaths are frequently reported in patients with schizophrenia and are emerging as a novel candidate for a schizophrenia biomarker. Here we review the suitability of scanpath measures as a target for trait marker research in schizophrenia. Papers reporting scanpath patterns in patients with schizophrenia were identified by PubMed and Google Scholar searches and by scanning reference lists in relevant articles. Search terms included "schizophrenia," "psychosis," "scanpath," "scan path," "fixation," "saccade" and "eye movement." Scanpath abnormalities afford impressive sensitivity and specificity and appear largely independent of psychotropic medications. Scanpaths may demonstrate some fluctuation with symptomatology and may be useful in illuminating illness state or subtypes. However, there is evidence that viewing behaviours remain atypical regardless of symptom remission and may be present in unaffected relatives of individuals with schizophrenia. This research is in its early stages, and further investigation regarding patterns of inheritance is required. Our findings support scanpath measures as a favourable topic for further investigation as a trait marker.

Sensory auditory interval perception errors in developmental dyslexia.

Developmental dyslexia (DD) is a heritable condition associated with reading, visual and auditory deficits. Atypical processes involved in low-level sensory coding have been implicated. We tested the contribution made by auditory magnocellular function using a behavioural task which considered the temporal difference between pairs of identical sinewave tones. Adult undergraduates with an existing diagnosis of DD (n = 78) were compared with controls (n = 111) from the same population on error rates and response times at different interval durations. Error rates and response times increased in both groups with increasing task difficulty. However, on average the DD group made uniformly more errors and slower decisions than controls. Unsupervised learning of error patterns exposed a trait continuum associated with individual differences in response efficiency. Difficulty in using temporal information in DD arising from impaired sensory coding in the auditory thalamus is suggested. The results provide strong support for the idea that auditory processing difficulties in dyslexia, along with visual and sensorimotor deficits, have a common neurodevelopmental cause.

Understanding Implementation of a Digital Self-Monitoring Intervention for Relapse Prevention in Psychosis: Protocol for a Mixed Method Process Evaluation.

BACKGROUND: Relapse is common in people who experience psychosis and is associated with many negative consequences, both societal and personal. People who relapse often exhibit changes (early warning signs [EWS]) in the period before relapse. Successful identification of EWS offers an opportunity for relapse prevention. However, several known barriers impede the use of EWS monitoring approaches. Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) is a complex digital intervention that uses a mobile app to enhance the detection and management of self-reported changes in well-being. This is currently being tested in a pilot cluster randomized controlled trial. As digital interventions have not been widely used in relapse prevention, little is known about their implementation. Process evaluation studies run in parallel to clinical trials can provide valuable data on intervention feasibility. OBJECTIVE: This study aims to transparently describe the protocol for the process evaluation element of the EMPOWER trial. We will focus on the development of a process evaluation framework sensitive to the worldview of service users, mental health staff, and carers; the aims of the process evaluation itself; the proposed studies to address these aims; and a plan for integration of results from separate process evaluation studies into one overall report. METHODS: The overall process evaluation will utilize mixed methods across 6 substudies. Among them, 4 will use qualitative methodologies, 1 will use a mixed methods approach, and 1 will use quantitative methodologies. RESULTS: The results of all studies will be triangulated into an overall analysis and interpretation of key implementation lessons. EMPOWER was funded in 2016, recruitment finished in January 2018. Data analysis is currently under way and the first results are expected to be submitted for publication in December 2019. CONCLUSIONS: The findings from this study will help identify implementation facilitators and barriers to EMPOWER. These insights will inform both upscaling decisions and optimization of a definitive trial. TRIAL REGISTRATION: ISRCTN Registry ISRCTN99559262; http://www.isrctn.com/ISRCTN99559262. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15634.

A parallel group randomised open blinded evaluation of Acceptance and Commitment Therapy for depression after psychosis: Pilot trial outcomes (ADAPT).

BACKGROUND: Depression is one of the major contributors to poorer quality of life amongst individuals with psychosis and schizophrenia. The study was designed as a Pilot Trial to determine the parameters of a larger, definitive pragmatic multi-centre randomised controlled trial of Acceptance and Commitment Therapy for depression after psychosis (ACTdp) for individuals with a diagnosis of schizophrenia who also meet diagnostic criteria for major depression. METHODS: Participants were required to meet criteria for schizophrenia and major depression. Blinded follow-ups were undertaken at 5-months (end of treatment) and at 10-months (5-months posttreatment). Primary outcomes were depression as measured by the Calgary Depression Scale for Schizophrenia (CDSS) and the Beck Depression Inventory (BDI). RESULTS: A total of 29 participants were randomised to ACTdp + Standard Care (SC) (n=15) or SC alone (n=14). We did not observe significant differences between groups on the CDSS total score at 5-months (Coeff=-1.43, 95%CI -5.17, 2.32, p=0.45) or at 10-months (Coeff=1.8, 95%CI -2.10, 5.69, p=0.36). In terms of BDI, we noted a statistically significant effect in favour of ACTdp+SC at 5-months (Coeff=-8.38, 95%CI -15.49, -1.27, p=0.02) but not at 10-months (Coeff=-4.85, 95%CI -12.10, 2.39, p=0.18). We also observed significant effects on psychological flexibility at 5-months (Coeff=-8.83, 95%CI -14.94, -2.71, p<0.01) but not 10-months (Coeff=-4.92, 95%CI -11.09, 1.25, p=0.11). IMPLICATIONS: In this first RCT of a psychological therapy with depression as the primary outcome, ACT is a promising intervention for depression in the context of psychosis. A further large-scale definitive randomised controlled trial is required to determine effectiveness. TRIAL REGISTRATION: ISRCTN: 33306437.

Smooth pursuit and visual scanpaths: Independence of two candidate oculomotor risk markers for schizophrenia.

OBJECTIVES: Smooth pursuit and visual scanpath deficits are candidate trait markers for schizophrenia. It is not clear whether eye tracking dysfunction (ETD) and atypical scanpath behaviour are the product of the same underlying neurobiological processes. We have examined co-occurrence of ETD and scanpath disturbance in individuals with schizophrenia and healthy volunteers. METHODS: Eye movements of individuals with schizophrenia (N = 96) and non-clinical age-matched comparison participants (N = 100) were recorded using non-invasive infrared oculography during smooth pursuit in both predictable (horizontal sinusoid) and less predictable (Lissajous sinusoid) conditions and a free viewing scanpath task. RESULTS: Individuals with schizophrenia demonstrated scanning deficits in both tasks. There was no association between performance measures of smooth pursuit and scene scanpaths in patient or control groups. Odds ratios comparing the likelihood of scanpath dysfunction when ETD was present, and the likelihood of finding scanpath dysfunction when ETD was absent were not significant in patients or controls in either pursuit variant, suggesting that ETD and scanpath dysfunction are independent anomalies in schizophrenia. CONCLUSION: ETD and scanpath disturbance appear to reflect independent oculomotor or neurocognitive deficits in schizophrenia. Each task may confer unique information about the pathophysiology of psychosis.

Simple viewing tests can detect eye movement abnormalities that distinguish schizophrenia cases from controls with exceptional accuracy.

BACKGROUND: We have investigated which eye-movement tests alone and combined can best discriminate schizophrenia cases from control subjects and their predictive validity. METHODS: A training set of 88 schizophrenia cases and 88 controls had a range of eye movements recorded; the predictive validity of the tests was then examined on eye-movement data from 34 9-month retest cases and controls, and from 36 novel schizophrenia cases and 52 control subjects. Eye movements were recorded during smooth pursuit, fixation stability, and free-viewing tasks. Group differences on performance measures were examined by univariate and multivariate analyses. Model fitting was used to compare regression, boosted tree, and probabilistic neural network approaches. RESULTS: As a group, schizophrenia cases differed from control subjects on almost all eye-movement tests, including horizontal and Lissajous pursuit, visual scanpath, and fixation stability; fixation dispersal during free viewing was the best single discriminator. Effects were stable over time, and independent of sex, medication, or cigarette smoking. A boosted tree model achieved perfect separation of the 88 training cases from 88 control subjects; its predictive validity on retest assessments and novel cases and control subjects was 87.8%. However, when we examined the whole data set of 298 assessments, a cross-validated probabilistic neural network model was superior and could discriminate all cases from controls with near perfect accuracy at 98.3%. CONCLUSIONS: Simple viewing patterns can detect eye-movement abnormalities that can discriminate schizophrenia cases from control subjects with exceptional accuracy.