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  • Street triage services in England: service models, national provision and the opinions of police.

    16 November 2018

    Aims and methodStreet triage services are increasingly common and part of standard responses to mental health crises in the community, but little is understood about them. We conducted a national survey of mental health trusts to gather detailed information regarding street triage services alongside a survey of Thames Valley police officers to ascertain their views and experiences. RESULTS: Triage services are available in most areas of the country and are growing in scope. There is wide variation in levels of funding and modes of operation, including hours covered. Police officers from our survey overwhelmingly support such services and would like to see them expanded.Clinical implicationsMental health crises now form a core part of policing and there are compelling reasons for the support of specialist services. Recent changes to the law have heightened this need, with a requirement for specialist input before a Section 136 is enacted. Those who have experienced triage services report it as less stigmatising and traumatic than a traditional approach, but there remains little evidence on which to base decisions.Declaration of interestNone.

  • Internalizing symptoms and dating violence perpetration in adolescence.

    3 November 2018

    BACKGROUND: Increasing evidence suggests an association between internalizing symptoms and violence against others. It remains unknown whether this link exists in the context of romantic relationships. In the current study, we tested whether anxiety and depression were associated over time with adolescent dating violence perpetration. METHODS: The sample included 238 Canadian adolescents (42% boys). Using a longitudinal design, their anxiety, depressive symptoms, and dating violence perpetration were annually assessed from age 14 to 15 years. RESULTS: Cross-lagged analyses revealed effects from anxiety and depressive symptoms to dating violence one year later (β = 0.27, p < .001; and β = 0.14, p = .04, respectively). No reversed cross-lagged paths were found from dating violence to subsequent anxiety or depression. CONCLUSIONS: Our findings underscore the predictive value of internalizing symptoms on dating violence perpetration. Reducing internalizing symptoms and improving coping strategies are important targets for the prevention of dating violence.

  • Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study.

    5 November 2018

    BACKGROUND: Objective behavioral markers of mental illness, often recorded through smartphones or wearable devices, have the potential to transform how mental health services are delivered and to help users monitor their own health. Linking objective markers to illness is commonly performed using population-level models, which assume that everyone is the same. The reality is that there are large levels of natural interindividual variability, both in terms of response to illness and in usual behavioral patterns, as well as intraindividual variability that these models do not consider. OBJECTIVE: The objective of this study was to demonstrate the utility of splitting the population into subsets of individuals that exhibit similar relationships between their objective markers and their mental states. Using these subsets, "group-personalized" models can be built for individuals based on other individuals to whom they are most similar. METHODS: We collected geolocation data from 59 participants who were part of the Automated Monitoring of Symptom Severity study at the University of Oxford. This was an observational data collection study. Participants were diagnosed with bipolar disorder (n=20); borderline personality disorder (n=17); or were healthy controls (n=22). Geolocation data were collected using a custom Android app installed on participants' smartphones, and participants weekly reported their symptoms of depression using the 16-item quick inventory of depressive symptomatology questionnaire. Population-level models were built to estimate levels of depression using features derived from the geolocation data recorded from participants, and it was hypothesized that results could be improved by splitting individuals into subgroups with similar relationships between their behavioral features and depressive symptoms. We developed a new model using a Dirichlet process prior for splitting individuals into groups, with a Bayesian Lasso model in each group to link behavioral features with mental illness. The result is a model for each individual that incorporates information from other similar individuals to augment the limited training data available. RESULTS: The new group-personalized regression model showed a significant improvement over population-level models in predicting mental health severity (P<.001). Analysis of subgroups showed that different groups were characterized by different features derived from raw geolocation data. CONCLUSIONS: This study demonstrates the importance of handling interindividual variability when developing models of mental illness. Population-level models do not capture nuances in how different individuals respond to illness, and the group-personalized model demonstrates a potential way to overcome these limitations when estimating mental state from objective behavioral features.

  • Functional brain imaging and connectivity in dementia

    13 January 2019

    © 2017 by Taylor & Francis Group, LLC. Although several dierent image modalities will be described, neuroimaging studies of brain function in dementia largely fall into two categories: (1) the study of resting blood ow and (2) measurement of brain changes due to a specic task. is chapter starts with a brief description of methods of emission tomography, functional magnetic resonance imaging (fMRI) and diusion tensor imaging (DTI) before describing applications in patients.

  • Neuroscience: Intracranial Recordings of Value.

    15 November 2018

    The role of orbitofrontal cortex in value-based choice is well-established from animal research, but there are challenges in relating neurophysiological recordings from animals to equivalent data from humans: a new study bridges this gap.

  • Effect of Digital Cognitive Behavioral Therapy for Insomnia on Health, Psychological Well-being, and Sleep-Related Quality of Life: A Randomized Clinical Trial.

    27 November 2018

    Importance: Digital cognitive behavioral therapy (dCBT) is a scalable and effective intervention for treating insomnia. Most people with insomnia, however, seek help because of the daytime consequences of poor sleep, which adversely affects quality of life. Objectives: To investigate the effect of dCBT for insomnia on functional health, psychological well-being, and sleep-related quality of life and to determine whether a reduction in insomnia symptoms was a mediating factor. Design, Setting, and Participants: This online, 2-arm, parallel-group randomized trial comparing dCBT for insomnia with sleep hygiene education (SHE) evaluated 1711 participants with self-reported symptoms of insomnia. Participants were recruited between December 1, 2015, and December 1, 2016, and dCBT was delivered using web and/or mobile channels plus treatment as usual; SHE comprised a website and a downloadable booklet plus treatment as usual. Online assessments took place at 0 (baseline), 4 (midtreatment), 8 (posttreatment), and 24 (follow-up) weeks. Programs were completed within 12 weeks after inclusion. Main Outcomes and Measures: Primary outcomes were scores on self-reported measures of functional health (Patient-Reported Outcomes Measurement Information System: Global Health Scale; range, 10-50; higher scores indicate better health); psychological well-being (Warwick-Edinburgh Mental Well-being Scale; range, 14-70; higher scores indicate greater well-being); and sleep-related quality of life (Glasgow Sleep Impact Index; range, 1-100; higher scores indicate greater impairment). Secondary outcomes comprised mood, fatigue, sleepiness, cognitive failures, work productivity, and relationship satisfaction. Insomnia was assessed with the Sleep Condition Indicator (range: 0-32; higher scores indicate better sleep). Results: Of the 1711 participants included in the intention-to-treat analysis, 1329 (77.7%) were female, mean (SD) age was 48.0 (13.8) years, and 1558 (91.1%) were white. Use of dCBT was associated with a small improvement in functional health compared with SHE (adjusted difference [95% CI] at week 4, 0.90 [0.40-1.40]; week 8, 1.76 [1.24-2.28]; week 24, 1.76 [1.22-2.30]) and psychological well-being (adjusted difference [95% CI] at week 4, 1.04 [0.28-1.80]; week 8, 2.68 [1.89-3.47]; week 24, 2.95 [2.13-3.76]), and with a large improvement in sleep-related quality of life (at week 4, -8.76 [-11.83 to -5.69]; week 8, -17.60 [-20.81 to -14.39]; week 24, -18.72 [-22.04 to -15.41]) (all P < .01). A large improvement in insomnia mediated these outcomes (range mediated, 45.5%-84.0%). Conclusions and Relevance: Use of dCBT is effective in improving functional health, psychological well-being, and sleep-related quality of life in people reporting insomnia symptoms. A reduction in insomnia symptoms mediates these improvements. These results confirm that dCBT improves both daytime and nighttime aspects of insomnia, strengthening existing recommendations of CBT as the treatment of choice for insomnia. Trial Registration: identifier: ISRCTN60530898.

  • Large-scale roll out of electronic longitudinal mood-monitoring for research in affective disorders: Report from the UK bipolar disorder research network.

    15 January 2019

    BACKGROUND: Electronic longitudinal mood monitoring has been shown to be acceptable to patients with affective disorders within clinical settings, but its use in large-scale research has not yet been established. METHODS: Using both postal and email invitations, we invited 4080 past research participants with affective disorders who were recruited into the Bipolar Disorder Research Network (BDRN) over a 10 year period to participate in online weekly mood monitoring. In addition, since January 2015 we have invited all newly recruited BDRN research participants to participate in mood monitoring at the point they were recruited into BDRN. RESULTS: Online mood monitoring uptake among past participants was 20%, and among new participants to date was 46% with participants recruited over the last year most likely to register (61%). More than 90% mood monitoring participants engaged for at least one month, with mean engagement period greater than one year (58 weeks) and maximum engagement for longer than three years (165 weeks). There were no significant differences in the proportion of past and new BDRN participants providing data for at least 4 weeks (91%, 92% respectively), 3 months (78%, 82%), 6 months (65%, 54%) or one year (51%, 44%). LIMITATIONS: Our experiences with recruiting participants for electronic prospective mood monitoring may not necessarily generalise fully to research situations that are very different from those we describe. CONCLUSIONS: Large-scale electronic longitudinal mood monitoring in affective disorders for research purposes is feasible with uptake highest among newly recruited participants.

  • Widespread grey matter pathology dominates the longitudinal cerebral MRI and clinical landscape of amyotrophic lateral sclerosis.

    3 November 2018

    Diagnosis, stratification and monitoring of disease progression in amyotrophic lateral sclerosis currently rely on clinical history and examination. The phenotypic heterogeneity of amyotrophic lateral sclerosis, including extramotor cognitive impairments is now well recognized. Candidate biomarkers have shown variable sensitivity and specificity, and studies have been mainly undertaken only cross-sectionally. Sixty patients with sporadic amyotrophic lateral sclerosis (without a family history of amyotrophic lateral sclerosis or dementia) underwent baseline multimodal magnetic resonance imaging at 3 T. Grey matter pathology was identified through analysis of T1-weighted images using voxel-based morphometry. White matter pathology was assessed using tract-based spatial statistics analysis of indices derived from diffusion tensor imaging. Cross-sectional analyses included group comparison with a group of healthy controls (n = 36) and correlations with clinical features, including regional disability, clinical upper motor neuron signs and cognitive impairment. Patients were offered 6-monthly follow-up MRI, and the last available scan was used for a separate longitudinal analysis (n = 27). In cross-sectional study, the core signature of white matter pathology was confirmed within the corticospinal tract and callosal body, and linked strongly to clinical upper motor neuron burden, but also to limb disability subscore and progression rate. Localized grey matter abnormalities were detected in a topographically appropriate region of the left motor cortex in relation to bulbar disability, and in Broca's area and its homologue in relation to verbal fluency. Longitudinal analysis revealed progressive and widespread changes in the grey matter, notably including the basal ganglia. In contrast there was limited white matter pathology progression, in keeping with a previously unrecognized limited change in individual clinical upper motor neuron scores, despite advancing disability. Although a consistent core white matter pathology was found cross-sectionally, grey matter pathology was dominant longitudinally, and included progression in clinically silent areas such as the basal ganglia, believed to reflect their wider cortical connectivity. Such changes were significant across a range of apparently sporadic patients rather than being a genotype-specific effect. It is also suggested that the upper motor neuron lesion in amyotrophic lateral sclerosis may be relatively constant during the established symptomatic period. These findings have implications for the development of effective diagnostic versus therapeutic monitoring magnetic resonance imaging biomarkers. Amyotrophic lateral sclerosis may be characterized initially by a predominantly white matter tract pathological signature, evolving as a widespread cortical network degeneration.

  • Diagnostic accuracy of diffusion tensor imaging in amyotrophic lateral sclerosis: a systematic review and individual patient data meta-analysis.

    3 November 2018

    RATIONALE AND OBJECTIVES: There have been a large number of case-control studies using diffusion tensor imaging (DTI) in amyotrophic lateral sclerosis (ALS). The objective of this study was to perform an individual patient data (IPD) meta-analysis for the estimation of the diagnostic accuracy measures of DTI in the diagnosis of ALS using corticospinal tract data. MATERIALS AND METHODS: MEDLINE, EMBASE, CINAHL, and Cochrane databases (1966-April 2011) were searched. Studies were included if they used DTI region of interest or tractography techniques to compare mean cerebral corticospinal tract fractional anisotropy values between ALS subjects and healthy controls. Corresponding authors from the identified articles were contacted to collect individual patient data. IPD meta-analysis and meta-regression were performed using Stata. Meta-regression covariate analysis included age, gender, disease duration, and Revised Amyotrophic Lateral Sclerosis Functional Rating Scale scores. RESULTS: Of 30 identified studies, 11 corresponding authors provided IPD and 221 ALS patients and 187 healthy control subjects were available for study. Pooled area under the receiver operating characteristic curve (AUC) was 0.75 (95% CI: 0.66-0.83), pooled sensitivity was 0.68 (95% CI: 0.62-0.75), and pooled specificity was 0.73 (95% CI: 0.66-0.80). Meta-regression showed no significant differences in pooled AUC for each of the covariates. There was moderate to high heterogeneity of pooled AUC estimates. Study quality was generally high. Data from 19 of the 30 eligible studies were not ascertained, raising possibility of selection bias. CONCLUSION: Using corticospinal tract individual patient data, the diagnostic accuracy of DTI appears to lack sufficient discrimination in isolation. Additional research efforts and a multimodal approach that also includes ALS mimics will be required to make neuroimaging a critical component in the workup of ALS.

  • Committees and Management

    22 August 2018

    The Department has a range of working groups, committees and staff networks that we encourage you to get involved with. Committee/working group membership is a great way to meet other members of the Department and contribute to Department strategy and decision-making. Although membership can be an addition to individual workload, it is a valued pathway for career progression, playing a key role in our Awards for Excellence, PDR, and Recognition of Distinction processes. We aim to achieve a fair and accurate representation of our Department members by gender, staff type and students on all our committees. If you have ideas about how we can do this better, please do get in touch.

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    19 July 2018

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    20 June 2018

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