119 research outputs found

    Blending Active and Passive Digital Technology Methods to Improve Symptom Monitoring in Early Psychosis

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    Aims: Psychotic symptoms fluctuate over time and effective and regular monitoring may contribute to relapse prevention and improve long-term outcomes. In this proof-of-concept study we test the feasibility, acceptability and potential usefulness of a novel digital method assessing the association between physiological signals and psychotic symptom distress.Methods: Fifteen participants with first episode psychosis were asked to use a self-assessment mobile phone application for psychotic symptom monitoring for 10 days while using a wrist worn device continuously recording heart rate variability (HRV) and electrodermal activity (EDA). We compared physiological activity when participants reported experiencing distressing and non-distressing psychotic symptoms.Results: Participants completed on average 76% of the mobile phone symptom assessments. When reporting distressing hallucinations and delusions participants had significantly higher EDA levels and non-significant lower HRV values compared to when these symptoms were non-distressing.Conclusions: This study provides further evidence linking psychotic symptom's distress, as experienced in everyday life, and autonomic deregulation. This proof-of-concept study may lead to further longer-term efforts to identify relapse biosignatures using automated methods based on passive monitoring. This method may allow for earlier interventions, contribute to improverelapse prevention and reduce symptoms interfering with recovery

    Technological innovations in mental healthcare: harnessing the digital revolution

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    Digital technology has the potential to transform mental healthcare by connecting patients, services and health data in new ways. Digital online and mobile applications can offer patients greater access to information and services and enhance clinical management and early intervention through access to real-time patient data. However, substantial gaps exist in the evidence base underlying these technologies. Greater patient and clinician involvement is needed to evaluate digital technologies and ensure they target unmet needs, maintain public trust and improve clinical outcomes

    “They Are Not Hard-to-Reach Clients. We Have Just Got Hard-to-Reach Services.” Staff Views of Digital Health Tools in Specialist Mental Health Services.

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    Background: Digital health products designed to help people with severe mental health problems appear to be feasible, acceptable, and efficacious. The challenge facing the digital mental health field is implementing digital tools in routine service delivery. To date, there has been a paucity of qualitative research exploring staff views of digital health solutions in the context of mental healthcare. Engaging and involving frontline staff in the design and rollout of new technology to improve utilization is imperative for successful uptake and adoption of digital tools. The aim of the current study is to explore frontline staff views regarding the utility and appropriateness of using digital tools in the healthcare pathway for people accessing specialist secondary care mental health services.Method: Qualitative study using framework analysis was used with 48 mental health staff working in early intervention for psychosis services. Six groups comprising 5–10 early intervention service staff members in each group were conducted across the Northwest of England. Robust measures were used to develop a stable framework, including member checking, triangulation, and consensus meetings.Results: Three themes were identified a priori: i) perceived barriers to adopting smartphone apps for early psychosis; ii) acceptability of digital health tools for early psychosis patients; and iii) data security, safety, and risk. Alongside exploring the a priori topics, one theme was generated a posteriori: iv) relationships.Conclusions: Staff working in specialist early intervention for psychosis services found digital tools on the whole acceptable in mental health service provision, but raised a number of concerns that will likely affect implementation of such systems into routine service delivery and practice. Thirteen recommendations are made in this paper as a result of the themes generated in these data. Implementing of digital systems needs to be simple and uncomplicated and improve clinical workflows for staff rather than hinder and increase clinical workflows. Furthermore, organizational support with a clear plan for implementing technological innovations is required for successful adoption of digital systems. Consideration of staff views around digital systems is important if successful adoption and implementation of such systems are to occur.Clinical Trial Registration: http://www.isrctn.com, identifier ISRCTN34966555

    Cognitive and neural processes in non-clinical auditory hallucinations

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    BACKGROUND: The nosological status of auditory hallucinations in non-clinical samples is unclear. AIMS: To investigate the functional neural basis of non-clinical hallucinations. METHOD: After selection from 1206 people, 68 participants of high, medium and low hallucination proneness completed a task designed to elicit verbal hallucinatory phenomena under conditions of stimulus degradation. Eight subjects who reported hearing a voice when none was present repeated the task during functional imaging. RESULTS: During the signal detection task, the high hallucination-prone participants reported a voice to be present when it was not (false alarms) significantly more often than the average or low participants (P<0.03, d.f.=2). On functional magnetic resonance imaging, patterns of activation during these false alarms showed activation in the superior and middle temporal cortex (P<0.001). CONCLUSIONS: Auditory hallucinatory experiences reported in non-clinical samples appear to be mediated by similar patterns of cerebral activation as found during hallucinations in schizophrenia

    The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia:Data from the STRATA collaboration

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    Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- Îą and IFN-Îł). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-Îł) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment

    Essential elements of an early intervention service for psychosis: the opinions of expert clinicians

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    BACKGROUND: Early intervention teams attempt to improve outcome in schizophrenia through earlier detection and the provision of phase-specific treatments. Whilst the number of early intervention teams is growing, there is a lack of clarity over their essential structural and functional elements. METHODS: A 'Delphi' exercise was carried out to identify how far there was consensus on the essential elements of early intervention teams in a group of 21 UK expert clinicians. Using published guidelines, an initial list was constructed containing 151 elements from ten categories of team structure and function. RESULTS: Overall there was expert consensus on the importance of 136 (90%) of these elements. Of the items on which there was consensus, 106 (70.2%) were rated essential, meaning that in their absence the functioning of the team would be severely impaired. CONCLUSION: This degree of consensus over essential elements suggests that it is reasonable to define a model for UK early intervention teams, from which a measure of fidelity could be derived

    Mobile early detection and connected intervention to coproduce better care in severe mental illness

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    Current approaches to the management of severe mentalillness have four major limitations: 1) symptom reporting isintermittent and subject to problems with reliability; 2) serviceusers report feelings of disengagement from their careplanning; 3) late detection of symptoms delay interventionsand increase the risk of relapse; and 4) care systems are heldback by the costs of unscheduled hospital admissions thatcould have been avoided with earlier detection andintervention. The ClinTouch system was developed to close theloop between service users and health professionals.ClinTouch is an end-to-end secure platform, providing avalidated mobile assessment technology, a web interface toview symptom data and a clinical algorithm to detect risk ofrelapse. ClinTouch integrates high-resolution, continuouslongitudinal symptom data into mental health care servicesand presents it in a form that is easy to use for targeting carewhere it is needed. The architecture and methodology can beeasily extended to other clinical domains, where the paradigmof targeted clinical interventions, triggered by the earlydetection of decline, can improve health outcomes

    Cross-sectional study comparing cognitive function in treatment responsive versus treatment non-responsive schizophrenia: evidence from the STRATA study

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    Background 70%–84% of individuals with antipsychotic treatment resistance show non-response from the first episode. Emerging cross-sectional evidence comparing cognitive profiles in treatment resistant schizophrenia to treatment-responsive schizophrenia has indicated that verbal memory and language functions may be more impaired in treatment resistance. We sought to confirm this finding by comparing cognitive performance between antipsychotic non-responders (NR) and responders (R) using a brief cognitive battery for schizophrenia, with a primary focus on verbal tasks compared against other measures of cognition. Design Cross-sectional. Setting This cross-sectional study recruited antipsychotic treatment R and antipsychotic NR across four UK sites. Cognitive performance was assessed using the Brief Assessment of Cognition in Schizophrenia (BACS). Participants One hundred and six participants aged 18–65 years with a diagnosis of schizophrenia or schizophreniform disorder were recruited according to their treatment response, with 52 NR and 54 R cases. Outcomes Composite and subscale scores of cognitive performance on the BACS. Group (R vs NR) differences in cognitive scores were investigated using univariable and multivariable linear regressions adjusted for age, gender and illness duration. Results Univariable regression models observed no significant differences between R and NR groups on any measure of the BACS, including verbal memory (ß=−1.99, 95% CI −6.63 to 2.66, p=0.398) and verbal fluency (ß=1.23, 95% CI −2.46 to 4.91, p=0.510). This pattern of findings was consistent in multivariable models. Conclusions The lack of group difference in cognition in our sample is likely due to a lack of clinical distinction between our groups. Future investigations should aim to use machine learning methods using longitudinal first episode samples to identify responder subtypes within schizophrenia, and how cognitive factors may interact within this
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