BackgroundTimely access to intervention for psychosis is crucial yet problematic. As such, health care providers are forming digital strategies for addressing mental health challenges. A theory-driven digital intervention that monitors distressing experiences and provides real-time active management strategies could improve the speed and quality of recovery in psychosis, over and above conventional treatments. This study assesses the feasibility and acceptability of Actissist, a digital health intervention grounded in the cognitive model of psychosis that targets key early psychosis domains.MethodsA proof-of-concept, single, blind, randomized controlled trial of Actissist, compared to a symptom-monitoring control. Thirty-six early psychosis patients were randomized on a 2:1 ratio to each arm of the trial. Actissist was delivered via a smartphone app over 12-weeks; clinical and functional assessment time-points were baseline, post-treatment and 22-weeks. Assessors’ blind to treatment condition conducted the assessments. Acceptability was examined using qualitative methods.ResultsActissist was feasible (75% participants used Actissist at least once/day; uptake was high, 97% participants remained in the trial; high follow-up rates), acceptable (90% participants recommend Actissist), and safe (0 serious adverse events), with high levels of user satisfaction. Treatment effects were large on negative symptoms, general psychotic symptoms and mood. The addition of Actissist conferred benefit at post-treatment assessment over routine symptom-monitoring and treatment as usual.ConclusionsThis is the first controlled proof-of-concept trial of a theory-driven digital health intervention for early psychosis. Actissist is feasible and acceptable to early psychosis patients, with a strong signal for treatment efficacy.Trial Registration: ISRCTN: 34966555.

BackgroundOver the past decade policy makers have emphasised the importance of healthcare technology in the management of long-term conditions. Mobile-phone based assessment may be one method of facilitating clinically- and cost-effective intervention, and increasing the autonomy and independence of service users. Recently, text-message and smartphone interfaces have been developed for the real-time assessment of symptoms in individuals with schizophrenia. Little is currently understood about patients’ perceptions of these systems, and how they might be implemented into their everyday routine and clinical care.Method24 community based individuals with non-affective psychosis completed a randomised repeated-measure cross-over design study, where they filled in self-report questions about their symptoms via text-messages on their own phone, or via a purpose designed software application for Android smartphones, for six days. Qualitative interviews were conducted in order to explore participants’ perceptions and experiences of the devices, and thematic analysis was used to analyse the data.ResultsThree themes emerged from the data: i) the appeal of usability and familiarity, ii) acceptability, validity and integration into domestic routines, and iii) perceived impact on clinical care. Although participants generally found the technology non-stigmatising and well integrated into their everyday activities, the repetitiveness of the questions was identified as a likely barrier to long-term adoption. Potential benefits to the quality of care received were seen in terms of assisting clinicians, faster and more efficient data exchange, and aiding patient-clinician communication. However, patients often failed to see the relevance of the systems to their personal situations, and emphasised the threat to the person centred element of their care.ConclusionsThe feedback presented in this paper suggests that patients are conscious of the benefits that mobile-phone based assessment could bring to clinical care, and that the technology can be successfully integrated into everyday routine. However, it also suggests that it is important to demonstrate to patients the personal, as well as theoretical, benefits of the technology. In the future it will be important to establish whether clinical practitioners are able to use this technology as part of a personalised mental health regime.

BackgroundSemi-structured interview scales for psychosis are the gold standard approach to assessing psychotic and other symptoms. However, such assessments have limitations such as recall bias, averaging, insensitivity to change and variable interrater reliability. Ambulant, real-time self-report assessment devices may hold advantages over interview measures, but it needs to be shown that the data thus collected are valid, and the collection method is acceptable, feasible and safe. We report on a monitoring system for the assessment of psychosis using smartphone technology. The primary aims were to: i) assess validity through correlations of item responses with those on widely accepted interview assessments of psychosis, and ii) examine compliance to the procedure in individuals with psychosis of varying severity.MethodsA total of 44 participants (acute or remitted DSM-4 schizophrenia and related disorders, and prodromal) completed 14 branching self-report items concerning key psychotic symptoms on a touch-screen mobile phone when prompted by an alarm at six pseudo-random times, each day, for one week. Face to face PANSS and CDS interviews were conducted before and after the assessment period blind to the ambulant data.ResultsCompliance as defined by completion of at least 33% of all possible data-points over seven days was 82%. In the 36 compliant participants, 5 items (delusions, hallucinations, suspiciousness, anxiety, hopelessness) showed moderate to strong (rho 0.6-0.8) associations with corresponding items from interview rating scales. Four items showed no significant correlation with rating scales: each was an item based on observable behaviour. Ambulant ratings showed excellent test-retest reliability and sensitivity to change.ConclusionsAmbulatory monitoring of symptoms several times daily using smartphone software applications represents a feasible and valid way of assessing psychotic phenomena for research and clinical management purposes. Further evaluation required over longer assessment periods, in clinical trials and service settings.

Scientific data stands to represent a significant portion of the linked open data cloud and science itself stands to benefit from the data fusion capability that this will afford. However, simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Publishing has requirements of provenance, quality, credit, attribution, methods in order to provide the reproducibility that allows validation of results. In this paper we make the case for a scientific data publication model on top of linked data and introduce the notion of Research Objects as first class citizens for sharing and publishing.

BackgroundMobile phone–based assessment may represent a cost-effective and clinically effective method of monitoring psychotic symptoms in real-time. There are several software options, including the use of native smartphone applications and text messages (short message service, SMS). Little is known about the strengths and limitations of these two approaches in monitoring symptoms in individuals with serious mental illness.ObjectiveThe objective of this study was to compare two different delivery modalities of the same diagnostic assessment for individuals with non-affective psychosis—a native smartphone application employing a graphical, touch user interface against an SMS text-only implementation. The overall hypothesis of the study was that patient participants with sewrious mental illness would find both delivery modalities feasible and acceptable to use, measured by the quantitative post-assessment feedback questionnaire scores, the number of data points completed, and the time taken to complete the assessment. It was also predicted that a native smartphone application would (1) yield a greater number of data points, (2) take less time, and (3) be more positively appraised by patient participant users than the text-based system.MethodsA randomized repeated measures crossover design was employed. Participants with currently treated Diagnostic and Statistical Manual (Fourth Edition) schizophrenia or related disorders (n=24) were randomly allocated to completing 6 days of assessment (four sets of questions per day) with a native smartphone application or the SMS text-only implementation. There was then a 1-week break before completing a further 6 days with the alternative delivery modality. Quantitative feedback questionnaires were administered at the end of each period of sampling.ResultsA greater proportion of data points were completed with the native smartphone application in comparison to the SMS text-only implementation (β = -.25, SE=.11, P=.02), which also took significantly less time to complete (β =.78, SE= .09, P<.001). Although there were no significant differences in participants’ quantitative feedback for the two delivery modalities, most participants reported preferring the native smartphone application (67%; n=16) and found it easier to use (71%; n=16). 33% of participants reported that they would be willing to complete mobile phone assessment for 5 weeks or longer.ConclusionsNative smartphone applications and SMS text are both valuable methods of delivering real-time assessment in individuals with schizophrenia. However, a more streamlined graphical user interface may lead to better compliance and shorter entry times. Further research is needed to test the efficacy of this technology within clinical services, to assess validity over longer periods of time and when delivered on patients’ own phones.