Routinely administered questionnaires for depression and anxiety : systematic review

Objectives To examine the effect of routinely administered psychiatric questionnaires on the recognition, management, and outcome of psychiatric disorders in non-psychiatric settings. Data sources Embase, Medline, PsycLIT, Cinahl, Cochrane Controlled Trials Register,and hand searches of key journals. Methods A systematic review of randomised controlled trials of the administration and routine feedback of psychiatric screening and outcome questionnaires to clinicians in non-psychiatric settings. narrative overview of key design features and end points, together with a random effects quantitative synthesis of comparable studies. Main outcome measures Recognition of psychiatric disorders after feedback of questionnaire results; interventions for psychiatric disorders and outcome of psychiatric disorders. Results Nine randomised studies were identified that examined the use of common psychiatric instruments in primary care and general hospital settings. Studies compared the effect of the administration of these instruments followed by the feedback of the results to clinicians, with administration with no feedback. Meta-analytic pooling was possible for four of these studies (2457 participants), which measured the effect of feedback on the recognition of depressive disorders. Routine administration and feedback of scores for all patients (irrespective of score) did not increase the overall rate of recognition of mental disorders such as anxiety and depression (relative risk of detection of depression by clinician after feedback 0.95, 95% confidence interval 0.83 to 1.09). Two studies showed that routine administration followed by selective feedback for only high scores increased the rate of recognition of depression (relative risk of detection of depression after feedback 2.64, 1.62 to 4.31). This increased recognition, however, did not translate into an increased rate of intervention. Overall, studies of routine administration of psychiatric measures did not show an effect on patient outcome. Conclusions The routine measurement of outcome is a costly exercise. Little evidence shows that it is of benefit in improving psychosocial outcomes of those with psychiatric disorder managed in non-psychiatric settings

Routine administration of Health Related Quality of Life (HRQoL) and needs assessment instruments to improve psychological outcome: a systematic review

Background. Routine administration of Health Related Quality of Life (HRQoL) and needs assessment instruments has been advocated as part of clinical care to aid the recognition of psychosocial problems, to inform clinical decision making, to monitor therapeutic response and to facilitate patient-doctor communication. However, their adoption is not without cost and the benefit of their use is unclear. Method. A systematic review was conducted. We sought experimental studies that examined the addition of routinely administered measures of HRQoL to care in both psychiatric and non-psychiatric settings. We searched the following databases: MEDLINE, EMBASE, CINAHL, PsycLIT and Cochrane Controlled Trials Register (to 2000). Data were extracted independently and a narrative synthesis of results was presented. Results. Nine randomized and quasi-randomized studies conducted in non-psychiatric settings were found. All the instruments used included an assessment of mental well-being, with specific questions relating to depression and anxiety. The routine feedback of these instruments had little impact on the recognition of mental disorders or on longer term psychosocial functioning. While clinicians welcomed the information these instruments imparted, their results were rarely incorporated into routine clinical decision making. No studies were found that examined the value of routine assessment and feedback of HRQoL or patient needs in specialist psychiatric care settings. Conclusions. Routine HRQoL measurement is a costly exercise and there is no robust evidence to suggest that it is of benefit in improving psychosocial outcomes of patients managed in non-psychiatric settings. Major policy initiatives to increase the routine collection and use of outcome measures in psychiatric settings are unevaluated

Patterns of Late Cenozoic exhumation deduced from apatite and zircon U-He ages from Fiordland, New Zealand

New apatite and zircon (U-Th)/He ages from the Fiordland region of New Zealand's South Island expand on earlier results and provide new constraints on patterns of Late Cenozoic exhumation and cooling across this region. Zircon (U-Th)/He cooling ages, in combination with increased density of apatite ages, show that in addition to a gradual northward decrease in cooling ages that was seen during an earlier phase of this study, there is also a trend toward younger cooling ages to the east. Distinct breaks in cooling age patterns on southwestern Fiordland appear to be correlated to the location of previously mapped faults. The northward decrease in ages may reflect asynchronous cooling related to migration in the locus of exhumation driven by subduction initiation, or it may reflect synchronous regional exhumation that exposed different structural levels across Fiordland, or some combination of these effects. In either case, differential exhumation accommodated by major and minor faults that dissect Fiordland basement rocks apparently played an important role in producing the resulting age patterns

Social encounter networks : collective properties and disease transmission

A fundamental challenge of modern infectious disease epidemiology is to quantify the networks of social and physical contacts through which transmission can occur. Understanding the collective properties of these interactions is critical for both accurate prediction of the spread of infection and determining optimal control measures. However, even the basic properties of such networks are poorly quantified, forcing predictions to be made based on strong assumptions concerning network structure. Here, we report on the results of a large-scale survey of social encounters mainly conducted in Great Britain. First, we characterize the distribution of contacts, which possesses a lognormal body and a power-law tail with an exponent of −2.45; we provide a plausible mechanistic model that captures this form. Analysis of the high level of local clustering of contacts reveals additional structure within the network, implying that social contacts are degree assortative. Finally, we describe the epidemiological implications of this local network structure: these contradict the usual predictions from networks with heavy-tailed degree distributions and contain public-health messages about control. Our findings help us to determine the types of realistic network structure that should be assumed in future population level studies of infection transmission, leading to better interpretations of epidemiological data and more appropriate policy decisions

Insights from unifying modern approximations to infections on networks

Networks are increasingly central to modern science owing to their ability to conceptualize multiple interacting components of a complex system. As a specific example of this, understanding the implications of contact network structure for the transmission of infectious diseases remains a key issue in epidemiology. Three broad approaches to this problem exist: explicit simulation; derivation of exact results for special networks; and dynamical approximations. This paper focuses on the last of these approaches, and makes two main contributions. Firstly, formal mathematical links are demonstrated between several prima facie unrelated dynamical approximations. And secondly, these links are used to derive two novel dynamical models for network epidemiology, which are compared against explicit stochastic simulation. The success of these new models provides improved understanding about the interaction of network structure and transmission dynamics

Social encounter networks : characterizing Great Britain

A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact

From Markovian to pairwise epidemic models and the performance of moment closure approximations

Many if not all models of disease transmission on networks can be linked to the exact state-based Markovian formulation. However the large number of equations for any system of realistic size limits their applicability to small populations. As a result, most modelling work relies on simulation and pairwise models. In this paper, for a simple SIS dynamics on an arbitrary network, we formalise the link between a well known pairwise model and the exact Markovian formulation. This involves the rigorous derivation of the exact ODE model at the level of pairs in terms of the expected number of pairs and triples. The exact system is then closed using two different closures, one well established and one that has been recently proposed. A new interpretation of both closures is presented, which explains several of their previously observed properties. The closed dynamical systems are solved numerically and the results are compared to output from individual-based stochastic simulations. This is done for a range of networks with the same average degree and clustering coefficient but generated using different algorithms. It is shown that the ability of the pairwise system to accurately model an epidemic is fundamentally dependent on the underlying large-scale network structure. We show that the existing pairwise models are a good fit for certain types of network but have to be used with caution as higher-order network structures may compromise their effectiveness

Single-shot single-gate RF spin readout in silicon

For solid-state spin qubits, single-gate RF readout can help minimise the number of gates required for scale-up to many qubits since the readout sensor can integrate into the existing gates required to manipulate the qubits (Veldhorst 2017, Pakkiam 2018). However, a key requirement for a scalable quantum computer is that we must be capable of resolving the qubit state within single-shot, that is, a single measurement (DiVincenzo 2000). Here we demonstrate single-gate, single-shot readout of a singlet-triplet spin state in silicon, with an average readout fidelity of $82.9\%$ at a $3.3~\text{kHz}$ measurement bandwidth. We use this technique to measure a triplet $T_-$ to singlet $S_0$ relaxation time of $0.62~\text{ms}$ in precision donor quantum dots in silicon. We also show that the use of RF readout does not impact the maximum readout time at zero detuning limited by the $S_0$ to $T_-$ decay, which remained at approximately $2~\text{ms}$. This establishes single-gate sensing as a viable readout method for spin qubits