To what extent does severity of loneliness vary among different mental health diagnostic groups: A cross-sectional study.

Loneliness is a common and debilitating problem in individuals with mental health disorders. However, our knowledge on severity of loneliness in different mental health diagnostic groups and factors associated with loneliness is poor, thus limiting the ability to target and improve loneliness interventions. The current study investigated the association between diagnoses and loneliness and explored whether psychological and social factors were related to loneliness. This study employed a cross-sectional design using data from a completed study which developed a measure of social inclusion. It included 192 participants from secondary, specialist mental health services with a primary diagnosis of psychotic disorders (n = 106), common mental disorders (n = 49), or personality disorders (n = 37). The study explored differences in loneliness between these broad diagnostic groups, and the relationship to loneliness of: affective symptoms, social isolation, perceived discrimination, and internalized stigma. The study adhered to the STROBE checklist for observational research. People with common mental disorders (MD = 3.94, CI = 2.15 to 5.72, P < 0.001) and people with personality disorders (MD = 4.96, CI = 2.88 to 7.05, P < 0.001) reported higher levels of loneliness compared to people with psychosis. These differences remained significant after adjustment for all psychological and social variables. Perceived discrimination and internalized stigma were also independently associated with loneliness and substantially contributed to a final explanatory model. The severity of loneliness varies between different mental health diagnostic groups. Both people with common mental disorders and personality disorders reported higher levels of loneliness than people with psychosis. Addressing perceived mental health discrimination and stigma may help to reduce loneliness

Tendency to Maximum Complexity in a Non-Equilibrium Isolated System

The time evolution equations of a simplified isolated ideal gas, the "tetrahe- dral" gas, are derived. The dynamical behavior of the LMC complexity [R. Lopez-Ruiz, H. L. Mancini, and X. Calbet, Phys. Lett. A 209, 321 (1995)] is studied in this system. In general, it is shown that the complexity remains within the bounds of minimum and maximum complexity. We find that there are certain restrictions when the isolated "tetrahedral" gas evolves towards equilibrium. In addition to the well-known increase in entropy, the quantity called disequilibrium decreases monotonically with time. Furthermore, the trajectories of the system in phase space approach the maximum complexity.Comment: 22 pages, 0 figures. Published in Phys. Rev. E 63, 066116(9) (2001

Optimising paediatric afferent component early warning systems : a hermeneutic systematic literature review and model development

Objective: To identify the core components of successful early warning systems for detecting and initiating action in response to clinical deterioration in paediatric inpatients. Methods: A hermeneutic systematic literature review informed by translational mobilisation theory and normalisation process theory was used to synthesise 82 studies of paediatric and adult early warning systems and interventions to support the detection of clinical deterioration and escalation of care. This method, which is designed to develop understanding, enabled the development of a propositional model of an optimal afferent component early warning system. Results: Detecting deterioration and initiating action in response to clinical deterioration in paediatric inpatients involves several challenges, and the potential failure points in early warning systems are well documented. Track and trigger tools (TTT) are commonly used and have value in supporting key mechanisms of action but depend on certain preconditions for successful integration into practice. Several supplementary interventions have been proposed to improve the effectiveness of early warning systems but there is limited evidence to recommend their wider use, due to the weight and quality of the evidence; the extent to which systems are conditioned by the local clinical context; and the need to attend to system component relationships, which do not work in isolation. While it was not possible to make empirical recommendations for practice, the review methodology generated theoretical inferences about the core components of an optimal system for early warning systems. These are presented as a propositional model conceptualised as three subsystems: detection, planning and action. Conclusions: There is a growing consensus of the need to think beyond TTTs in improving action to detect and respond to clinical deterioration. Clinical teams wishing to improve early warning systems can use the model to consider systematically the constellation of factors necessary to support detection, planning and action and consider how these arrangements can be implemented in their local context

The XMM Cluster Survey: Evidence for energy injection at high redshift from evolution of the X-ray luminosity-temperature relation

We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with spectroscopic redshifts drawn from the XMM Cluster Survey first data release (XCS-DR1). This is the first study spanning this redshift range using a single, large, homogeneous cluster sample. Using an orthogonal regression technique, we find no evidence for evolution in the slope or intrinsic scatter of the relation since z~1.5, finding both to be consistent with previous measurements at z~0.1. However, the normalisation is seen to evolve negatively with respect to the self-similar expectation: we find E(z)^{-1} L_X = 10^{44.67 +/- 0.09} (T/5)^{3.04 +/- 0.16} (1+z)^{-1.5 +/- 0.5}, which is within 2 sigma of the zero evolution case. We see milder, but still negative, evolution with respect to self-similar when using a bisector regression technique. We compare our results to numerical simulations, where we fit simulated cluster samples using the same methods used on the XCS data. Our data favour models in which the majority of the excess entropy required to explain the slope of the L_X-T relation is injected at high redshift. Simulations in which AGN feedback is implemented using prescriptions from current semi-analytic galaxy formation models predict positive evolution of the normalisation, and differ from our data at more than 5 sigma. This suggests that more efficient feedback at high redshift may be needed in these models.Comment: Accepted for publication in MNRAS; 12 pages, 6 figures; added references to match published versio

Linear Estimation of Location and Scale Parameters Using Partial Maxima

Consider an i.i.d. sample X^*_1,X^*_2,...,X^*_n from a location-scale family, and assume that the only available observations consist of the partial maxima (or minima)sequence, X^*_{1:1},X^*_{2:2},...,X^*_{n:n}, where X^*_{j:j}=max{X^*_1,...,X^*_j}. This kind of truncation appears in several circumstances, including best performances in athletics events. In the case of partial maxima, the form of the BLUEs (best linear unbiased estimators) is quite similar to the form of the well-known Lloyd's (1952, Least-squares estimation of location and scale parameters using order statistics, Biometrika, vol. 39, pp. 88-95) BLUEs, based on (the sufficient sample of) order statistics, but, in contrast to the classical case, their consistency is no longer obvious. The present paper is mainly concerned with the scale parameter, showing that the variance of the partial maxima BLUE is at most of order O(1/log n), for a wide class of distributions.Comment: This article is devoted to the memory of my six-years-old, little daughter, Dionyssia, who leaved us on August 25, 2010, at Cephalonia isl. (26 pages, to appear in Metrika

Quantum Algorithms for Fermionic Simulations

We investigate the simulation of fermionic systems on a quantum computer. We show in detail how quantum computers avoid the dynamical sign problem present in classical simulations of these systems, therefore reducing a problem believed to be of exponential complexity into one of polynomial complexity. The key to our demonstration is the spin-particle connection (or generalized Jordan-Wigner transformation) that allows exact algebraic invertible mappings of operators with different statistical properties. We give an explicit implementation of a simple problem using a quantum computer based on standard qubits.Comment: 38 pages, 2 psfigur

Dynamical suppression of decoherence in two-state quantum systems

The dynamics of a decohering two-level system driven by a suitable control Hamiltonian is studied. The control procedure is implemented as a sequence of radiofrequency pulses that repetitively flip the state of the system, a technique that can be termed quantum "bang-bang" control after its classical analog. Decoherence introduced by the system's interaction with a quantum environment is shown to be washed out completely in the limit of continuous flipping and greatly suppressed provided the interval between the pulses is made comparable to the correlation time of the environment. The model suggests a strategy to fight against decoherence that complements existing quantum error-correction techniques.Comment: 15 pages, RevTeX style, 3 figures. Submitted to Phys. Rev.

Acute day units in non-residential settings for people in mental health crisis: the AD-CARE mixed-methods study

BACKGROUND: For people in mental health crisis, acute day units provide daily structured sessions and peer support in non-residential settings as an alternative to crisis resolution teams. OBJECTIVES: To investigate the provision, effectiveness, intervention acceptability and re-admission rates of acute day units. DESIGN: Work package 1 – mapping and national questionnaire survey of acute day units. Work package 2.1 – cohort study comparing outcomes during a 6-month period between acute day unit and crisis resolution team participants. Work package 2.2 – qualitative interviews with staff and service users of acute day units. Work package 3 – a cohort study within the Mental Health Minimum Data Set exploring re-admissions to acute care over 6 months. A patient and public involvement group supported the study throughout. SETTING AND PARTICIPANTS: Work package 1 – all non-residential acute day units (NHS and voluntary sector) in England. Work packages 2.1 and 2.2 – four NHS trusts with staff, service users and carers in acute day units and crisis resolution teams. Work package 3 – all individuals using mental health NHS trusts in England. RESULTS: Work package 1 – we identified 27 acute day units in 17 out of 58 trusts. Acute day units are typically available on weekdays from 10 a.m. to 4 p.m., providing a wide range of interventions and a multidisciplinary team, including clinicians, and having an average attendance of 5 weeks. Work package 2.1 – we recruited 744 participants (acute day units, n = 431; crisis resolution teams, n = 312). In the primary analysis, 21% of acute day unit participants (vs. 23% of crisis resolution team participants) were re-admitted to acute mental health services over 6 months. There was no statistically significant difference in the fully adjusted model (acute day unit hazard ratio 0.78, 95% confidence interval 0.54 to 1.14; p = 0.20), with highly heterogeneous results between trusts. Acute day unit participants had higher satisfaction and well-being scores and lower depression scores than crisis resolution team participants. The health economics analysis found no difference in resource use or cost between the acute day unit and crisis resolution team groups in the fully adjusted analysis. Work package 2.2 – 36 people were interviewed (acute day unit staff, n = 12; service users, n = 21; carers, n = 3). There was an overwhelming consensus that acute day units are highly valued. Service users found the high amount of contact time and staff continuity, peer support and structure provided by acute day units particularly beneficial. Staff also valued providing continuity, building strong therapeutic relationships and providing a variety of flexible, personalised support. Work package 3 – of 231,998 individuals discharged from acute care (crisis resolution team, acute day unit or inpatient ward), 21.4% were re-admitted for acute treatment within 6 months, with women, single people, people of mixed or black ethnicity, those living in more deprived areas and those in the severe psychosis care cluster being more likely to be re-admitted. Little variation in re-admissions was explained at the trust level, or between trusts with and trusts without acute day units (adjusted odds ratio 0.96, 95% confidence interval 0.80 to 1.15). LIMITATIONS: In work package 1, some of the information is likely to be incomplete as a result of trusts’ self-reporting. There may have been recruitment bias in work packages 2.1 and 2.2. Part of the health economics analysis relied on clinical Health of the Nations Outcome Scale ratings. The Mental Health Minimum Data Set did not contain a variable identifying acute day units, and some covariates had a considerable number of missing data. CONCLUSIONS: Acute day units are not provided routinely in the NHS but are highly valued by staff and service users, giving better outcomes in terms of satisfaction, well-being and depression than, and no significant differences in risk of re-admission or increased costs from, crisis resolution teams. Future work should investigate wider health and care system structures and the place of acute day units within them; the development of a model of best practice for acute day units; and staff turnover and well-being (including the impacts of these on care). FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 18. See the NIHR Journals Library website for further project information

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Ethnic inequalities and pathways to care in psychosis in England: a systematic review and meta-analysis

© The Author(s). 2018Background: As part of a national programme to tackle ethnic inequalities, we conducted a systematic review and meta-analysis of research on ethnic inequalities in pathways to care for adults with psychosis living in England and/or Wales. Methods: Nine databases were searched from inception to 03.07.17 for previous systematic reviews, including forward and backward citation tracking and a PROSPERO search to identify ongoing reviews. We then carried forward relevant primary studies from included reviews (with the latest meta-analyses reporting on research up to 2012), supplemented by a search on 18.10.17 in MEDLINE, Embase, PsycINFO and CINAHL for primary studies between 2012 and 2017 that had not been covered by previous meta-analyses. Results: Forty studies, all conducted in England, were included for our updated meta-analyses on pathways to care. Relative to the White reference group, elevated rates of civil detentions were found for Black Caribbean (OR = 3.43, 95% CI = 2.68 to 4.40, n = 18), Black African (OR = 3.11, 95% CI = 2.40 to 4.02, n = 6), and South Asian patients (OR = 1.50, 95% CI 1.07 to 2.12, n = 10). Analyses of each Mental Health Act section revealed significantly higher rates for Black people under (civil) Section 2 (OR = 1.53, 95% CI = 1.11 to 2.11, n = 3). Rates in repeat admissions were significantly higher than in first admission for South Asian patients (between-group difference p < 0.01). Some ethnic groups had more police contact (Black African OR = 3.60, 95% CI = 2.15 to 6.05, n = 2; Black Caribbean OR = 2.64, 95% CI = 1.88 to 3.72, n = 8) and criminal justice system involvement (Black Caribbean OR = 2.76, 95% CI = 2.02 to 3.78, n = 5; Black African OR = 1.92, 95% CI = 1.32 to 2.78, n = 3). The White Other patients also showed greater police and criminal justice system involvement than White British patients (OR = 1.49, 95% CI = 1.03 to 2.15, n = 4). General practitioner involvement was less likely for Black than the White reference group. No significant variations over time were found across all the main outcomes. Conclusions: Our updated meta-analyses reveal persisting but not significantly worsening patterns of ethnic inequalities in pathways to psychiatric care, particularly affecting Black groups. This provides a comprehensive evidence base from which to inform policy and practice amidst a prospective Mental Health Act reform. Trial registration: CRD42017071663Peer reviewedFinal Published versio