Cognitive remediation in schizophrenia-now it is really getting personal

Cognitive problems are consistently documented in people with schizophrenia. They negatively influence functioning and contribute to the long term consequences of the illness. Cognitive remediation (CR) is a psychological intervention developed to target these cognitive difficulties. There is evidence that CR is beneficial but there is still a limited understanding of how the putative active therapy ingredients contribute to changes in the brain and translate into improved functioning. This paper reviews recent research focused on topics that, in our view, will drive future developments such as the identification of translational mechanisms, the personalisation of CR, the best implementation methods and potential augmenting strategies to improve treatment effectiveness

Improving Adherence to Web-Based and Mobile Technologies for People with Psychosis:Systematic review of New Potential Predictors of Adherence

Background: Despite the boom in new technologically based interventions for people with psychosis, recent studies suggest medium to low rates of adherence to these types of interventions. The benefits will be limited if only a minority of service users adhere and engage; if specific predictors of adherence can be identified then technologies can be adapted to increase the service user benefits. Objective: The study aimed to present a systematic review of rates of adherence, dropout, and approaches to analyzing adherence to newly developed mobile and Web-based interventions for people with psychosis. Specific predictors of adherence were also explored. Methods: Using keywords (Internet or online or Web-based or website or mobile) AND (bipolar disorder or manic depression or manic depressive illness or manic-depressive psychosis or psychosis or schizophr* or psychotic), the following databases were searched: OVID including MedLine, EMBASE and PsychInfo, Pubmed and Web of Science. The objectives and inclusion criteria for suitable studies were defined following PICOS (population: people with psychosis; intervention: mobile or Internet-based technology; comparison group: no comparison group specified; outcomes: measures of adherence; study design: randomized controlled trials (RCT), feasibility studies, and observational studies) criteria. In addition to measurement and analysis of adherence, two theoretically proposed predictors of adherence were examined: (1) level of support from a clinician or researcher throughout the study, and (2) level of service user involvement in the app or intervention development. We provide a narrative synthesis of the findings and followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for reporting systematic reviews. Results: Of the 20 studies that reported a measure of adherence and a rate of dropout, 5 of these conducted statistical analyses to determine predictors of dropout, 6 analyzed the effects of specific adherence predictors (eg, symptom severity or type of technological interface) on the effects of the intervention, 4 administered poststudy feedback questionnaires to assess continued use of the intervention, and 2 studies evaluated the effects of different types of interventions on adherence. Overall, the percentage of participants adhering to interventions ranged from 28-100% with a mean of 83%. Adherence was greater in studies with higher levels of social support and service user involvement in the development of the intervention. Studies of shorter duration also had higher rates of adherence. Conclusions: Adherence to mobile and Web-based interventions was robust across most studies. Although 2 studies found specific predictors of nonadherence (male gender and younger age), most did not specifically analyze predictors. The duration of the study may be an important predictor of adherence. Future studies should consider reporting a universal measure of adherence and aim to conduct complex analyses on predictors of adherence such as level of social presence and service user involvementpublishersversionPeer reviewe

What is the impact of research champions on integrating research in mental health clinical practice?:A quasiexperimental study in South London, UK

OBJECTIVES: Key challenges for mental health healthcare professionals to implement research alongside clinical activity have been highlighted, such as insufficient time to apply research skills and lack of support and resources. We examined the impact of employing dedicated staff to promote research in community mental health clinical settings. DESIGN: Quasiexperiment before and after study. SETTING: South London and Maudsley National Health Service Foundation Trust. PARTICIPANTS: 4455 patients receiving care from 15 community mental health teams between 1 December 2013 and 31 December 2014. OUTCOME MEASURES: The proportion of patients approached for research participation in clinical services where research champions were present (intervention group), and where research champions were not present (comparison group). RESULTS: Patients in the intervention group were nearly six times more likely to be approached for research participation (Adj. OR=5.98; 95% CI 4.96 to 7.22). CONCLUSIONS: Investing in staff that promote and drive research in clinical services increases opportunities for patients to hear about and engage in clinical research studies. However, investment needs to move beyond employing short-term staff

The development of a measure of social care outcome for older people. Funded/commissioned by: Department of Health

An essential element of identifying Best Value and monitoring cost-effective care is to be able to identify the outcomes of care. In the field of health services, use of utility-based health related quality of life measures has become widespread, indeed even required. If, in the new era of partnerships, social care outcomes are to be valued and included we need to develop measures that reflect utility or welfare gain from social care interventions. This paper reports on a study, commissioned as part of the Department of Health’s Outcomes of Social Care for Adults Initiative, that developed an instrument and associated utility indexes that provide a tool for evaluating social care interventions in both a research and service setting. Discrete choice conjoint analysis used to derive utility weights provided us with new insights into the relative importance of the core domains of social care to older people. Whilst discrete choice conjoint analysis is being increasingly used in health economics, this is the first study that has attempted to use it to derive a measure of outcome

Using wearable technology to detect the autonomic signature of illness severity in schizophrenia

IntroductionResearch suggests that people with schizophrenia have autonomic dysfunctions. These have been linked to functioning problems, symptoms and considered a risk factor for illness chronicity. The aim of this study is to introduce a new Mobile Health (mHealth) method using wearable technology to assessing autonomic activity in people's everyday life. We aim to evaluate the new method acceptability and characterise the association between schizophrenia illness features and autonomic abnormalities.MethodThirty participants with schizophrenia and 25 controls were asked to wear a mHealth device measuring autonomic activity and movements during their normal everyday life. Measures of device use acceptability were collected from all participants. Participants with schizophrenia were also assessed for symptoms and functioning levels. Measures of heart rate variability (HRV), electrodermal activity (EDA) and movement were collected by the device and groups were compared. Correlation between physiological measures, functioning, symptoms and medication levels were assessed in people with schizophrenia.ResultsThe mHealth device method proved to be acceptable and produced reliable measures of autonomic activity and behaviour. Compared to controls, people with schizophrenia showed lower levels of HRV, movement and functioning. In people with schizophrenia illness severity, particularly positive symptoms, was associated with parasympathetic deregulation.ConclusionsAutonomic abnormalities can be detected using wearable technology from people's everyday life. These are in line with previous research and support the notion that autonomic deregulation are relevant illness features for mental and physical health in schizophrenia. This method may be developed as a monitoring system for well-being and relapse prevention