Should health professionals screen women for domestic violence? : systematic review

Objective To assess the evidence for the acceptability and effectiveness of screening women for domestic violence in healthcare settings. Design Systematic review of published quantitative studies. Search strategy Three electronic databases (Medline, Embase, and CINAHL) were searched for articles published in the English language up to February 2001. Included studies Surveys that elicited the attitudes of women and health professionals on the screening of women in health settings; comparative studies conducted in healthcare settings that measured rates of identification of domestic violence in the presence and absence of screening; studies measuring outcomes of interventions for women identified in health settings who experience abuse from a male partner or ex­partner compared with abused women not receiving an intervention. Results 20 papers met the inclusion criteria. In four surveys, 43­85% of women respondents found screening in healthcare settings acceptable. Two surveys of health professionals' views found that two thirds of physicians and almost half of emergency department nurses were not in favour of screening. In nine studies of screening compared with no screening, most detected a greater proportion of abused women identified by healthcare professionals. Six studies of interventions used weak study designs and gave inconsistent results. Other than increased referral to outside agencies, little evidence exists for changes in important outcomes such as decreased exposure to violence. No studies measured quality of life, mental health outcomes, or potential harm to women from screening programmes. Conclusion Although domestic violence is a common problem with major health consequences for women, implementation of screening programmes in healthcare settings cannot be justified. Evidence of the benefit of specific interventions and lack of harm from screening is needed

Impact of deprivation and comorbidity on outcomes in emergency general surgery: an epidemiological study.

BACKGROUND: The impact of socioeconomic deprivation and comorbidities on the outcome of patients who require emergency general surgery (EGS) admission is poorly understood. The aim of this study was to examine the effect of deprivation and comorbidity on mortality, discharge destination and length of hospital stay (LOS) in patients undergoing EGS in Scotland. METHODS: Prospectively collected data from all Scottish adult patients (aged >15 years) requiring EGS admitted between 1997 and 2016 were obtained from the Scottish Government. Data included age, sex, Scottish Index of Multiple Deprivation (SIMD), 5-year Charlson Comorbidity Index (CCI), whether an operation took place and outcomes including mortality, discharge destination and LOS. Logistic regression was used for the analysis of mortality and discharge destination and Poisson regression was used for LOS. RESULTS: 1 477 810 EGS admissions were analyzed. 16.2% were in the most deprived SIMD decile and 5.6% in the least deprived SIMD decile. 75.6% had no comorbidity, 20.3% had mild comorbidity, 2.5% had moderate comorbidity and 1.6% had severe comorbidity. 78.6% were discharged directly home. Inpatient, 30-day, 90-day and 1-year crude mortality was 1.7%, 3.7%, 7.2% and 12.4%, respectively. Logistic regression showed that severe comorbidity was associated with not being discharged directly to home (OR 0.38, 95% CI 0.37 to 0.39) and higher inpatient mortality (OR 13.74, 95% CI 13.09 to 14.42). Compared with the most affluent population, the most deprived population were less likely to be discharged directly to home (OR 0.97, 95% CI 0.95 to 0.99) and had higher inpatient mortality (OR 1.36, 95% CI 1.8 to 1.46). Poisson analysis showed that severe comorbidity (OR 1.69, 95% CI 1.68 to 1.69) and socioeconomic deprivation (OR 1.11, 95% CI 1.11 to 1.12) were associated with longer LOS. DISCUSSION: Increased levels of comorbidity and, to a lesser extent, socioeconomic deprivation are key drivers of mortality, discharge destination and LOS following admission to an EGS service. LEVEL OF EVIDENCE: III (prospective/retrospective with up to two negative criteria). STUDY TYPE: Epidemiological/prognostic

Evaluating and monitoring analgesia and sedation in the intensive care unit

Management of analgesia and sedation in the intensive care unit requires evaluation and monitoring of key parameters in order to detect and quantify pain and agitation, and to quantify sedation. The routine use of subjective scales for pain, agitation, and sedation promotes more effective management, including patient-focused titration of medications to specific end-points. The need for frequent measurement reflects the dynamic nature of pain, agitation, and sedation, which change constantly in critically ill patients. Further, close monitoring promotes repeated evaluation of response to therapy, thus helping to avoid over-sedation and to eliminate pain and agitation. Pain assessment tools include self-report (often using a numeric pain scale) for communicative patients and pain scales that incorporate observed behaviors and physiologic measures for noncommunicative patients. Some of these tools have undergone validity testing but more work is needed. Sedation-agitation scales can be used to identify and quantify agitation, and to grade the depth of sedation. Some scales incorporate a step-wise assessment of response to increasingly noxious stimuli and a brief assessment of cognition to define levels of consciousness; these tools can often be quickly performed and easily recalled. Many of the sedation-agitation scales have been extensively tested for inter-rater reliability and validated against a variety of parameters. Objective measurement of indicators of consciousness and brain function, such as with processed electroencephalography signals, holds considerable promise, but has not achieved widespread implementation. Further clarification of the roles of these tools, particularly within the context of patient safety, is needed, as is further technology development to eliminate artifacts and investigation to demonstrate added value

Emergency general surgery: impact of distance and rurality on mortality

Funding This work was made possible by a grant from NHS Grampian and NHS Highlands Endowment Funding. No funding was received from the National Institutes of Health (NIH); Wellcome Trust; or Howard Hughes Medical Institute (HHMI). Acknowledgements The authors acknowledge the support of the eDRIS Team (Public Health Scotland) for their involvement in obtaining approvals, provisioning, and linking data, and the use of the secure analytical platform within the National Safe Haven. We also acknowledge P. Murchie for support with contextualizing the work within the rural medical practitioner literature.Peer reviewedPublisher PD

Pupil dilation as an index of preferred mutual gaze duration

Most animals look at each other to signal threat or interest. In humans, this social interaction is usually punctuated with brief periods of mutual eye contact. Deviations from this pattern of gazing behaviour generally make us feel uncomfortable and are a defining characteristic of clinical conditions such as autism or schizophrenia, yet it is unclear what constitutes normal eye contact. Here, we measured, across a wide range of ages, cultures and personality types, the period of direct gaze that feels comfortable and examined whether autonomic factors linked to arousal were indicative of people’s preferred amount of eye contact. Surprisingly, we find that preferred period of gaze duration is not dependent on fundamental characteristics such as gender, personality traits or attractiveness. However, we do find that subtle pupillary changes, indicative of physiological arousal, correlate with the amount of eye contact people find comfortable. Specifically, people preferring longer durations of eye contact display faster increases in pupil size when viewing another person than those preferring shorter durations. These results reveal that a person’s preferred duration of eye contact is signalled by physiological indices (pupil dilation) beyond volitional control that may play a modulatory role in gaze behaviour

Item response analysis of the Positive and Negative Syndrome Scale

<p>Abstract</p> <p>Background</p> <p>Statistical models based on item response theory were used to examine (a) the performance of individual Positive and Negative Syndrome Scale (PANSS) items and their options, (b) the effectiveness of various subscales to discriminate among individual differences in symptom severity, and (c) the appropriateness of cutoff scores recently recommended by Andreasen and her colleagues (2005) to establish symptom remission.</p> <p>Methods</p> <p>Option characteristic curves were estimated using a nonparametric item response model to examine the probability of endorsing each of 7 options within each of 30 PANSS items as a function of standardized, overall symptom severity. Our data were baseline PANSS scores from 9205 patients with schizophrenia or schizoaffective disorder who were enrolled between 1995 and 2003 in either a large, naturalistic, observational study or else in 1 of 12 randomized, double-blind, clinical trials comparing olanzapine to other antipsychotic drugs.</p> <p>Results</p> <p>Our analyses show that the majority of items forming the Positive and Negative subscales of the PANSS perform very well. We also identified key areas for improvement or revision in items and options within the General Psychopathology subscale. The Positive and Negative subscale scores are not only more discriminating of individual differences in symptom severity than the General Psychopathology subscale score, but are also more efficient on average than the 30-item total score. Of the 8 items recently recommended to establish symptom remission, 1 performed markedly different from the 7 others and should either be deleted or rescored requiring that patients achieve a lower score of 2 (rather than 3) to signal remission.</p> <p>Conclusion</p> <p>This first item response analysis of the PANSS supports its sound psychometric properties; most PANSS items were either very good or good at assessing overall severity of illness. These analyses did identify some items which might be further improved for measuring individual severity differences or for defining remission thresholds. Findings also suggest that the Positive and Negative subscales are more sensitive to change than the PANSS total score and, thus, may constitute a "mini PANSS" that may be more reliable, require shorter administration and training time, and possibly reduce sample sizes needed for future research.</p

A Learning Management System-Based Early Warning System for Academic Advising in Undergraduate Engineering

This chapter describes a design-based research project that developed an early warning system for an undergraduate engineering mentoring program. Using near real-time data from a university’s learning management system, we provided academic advisors with timely and targeted data on students’ academic progress. We discuss the development of the early warning system and detail how academic advisors used it. Our findings point to the value of providing academic advisors with performance data that can be used to direct students to appropriate sources of support.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107974/1/Krumm_etal_2014_LA.pd

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Microarray data analysis in neoadjuvant biomarker studies in estrogen receptor-positive breast cancer

Microarray data have been widely utilized to discover biomarkers predictive of response to endocrine therapy in estrogen receptor-positive breast cancer. Typically, these data have focused on analyses conducted on the diagnostic specimen. However, dynamic temporal changes in gene expression associated with treatment may deliver significant improvements to the current generation of predictive models. We present and discuss some statistical issues relevant to the paper by Taylor and colleagues, who conducted studies to model the prognostic potential of gene expression changes that occur after endocrine treatment