scholarly journals Use of routinely collected data on psychiatric in-patient care

2003 ◽  
Vol 9 (4) ◽  
pp. 300-307 ◽  
Author(s):  
Gyles Glover
Keyword(s):  
Mental Health ◽  
Set Covering ◽  
Services Research ◽  
Data Set ◽  
Research Issues ◽  
Wide Range ◽  
Policy Work ◽  
Data Source ◽  
Set Up ◽  
Service Data

Since the start of the National Health Service, data have been collected on admissions to psychiatric in-patient units, first as the Mental Health Enquiry, then as part of Hospital Episode Statistics. Some details have changed but many have stayed remarkably consistent. Published literature on the wide range of research and policy work undertaken using this data source is reviewed. Early work was central to the government's deinstitutionalisation policy in the early 1960s. Subsequent studies cover a wide range of epidemiological and health services research issues. A new statistical base, the Mental Health Minimum Data Set, covering individuals receiving all types of health care is currently being set up. This will supplement (but not replace) admission statistics.

Liaison old age psychiatry

2013 ◽  
Author(s):  
John Holmes
Keyword(s):  
Mental Health ◽  
Older People ◽  
General Hospital ◽  
Health Assessment ◽  
Cost Savings ◽  
Liaison Psychiatry ◽  
People With Dementia ◽  
Wide Range ◽  
Part Time ◽  
Set Up

About one-third of general hospital beds are occupied by older people with dementia, delirium or depression. All these conditions bring poorer outcomes for individuals and organisations alike. In response to this, liaison psychiatry services for older people have evolved in order to provide timely mental health assessment, ongoing treatment and signposting to other mental health services. They also provide teaching and training for general hospital colleagues from a wide range of disciplines. There is wide variation in liaison service configurations and activity, from a part-time nurse to a large multidisciplinary team but the best evidence for effectiveness is for the latter. Liaison services can be difficult to set up, requiring agreement from all stakeholders, but once established they can bring improvements in quality as well as cost savings. This chapter explains the case of need for these services, considers different service models, examines service activities and support needs and helps the reader understand how local services can be evaluated.

Early Prediction of University Dropouts – A Random Forest Approach

2020 ◽  
Vol 240 (6) ◽  
pp. 743-789 ◽  
Author(s):  
Andreas Behr ◽  
Marco Giese ◽  
Herve D. Teguim K ◽  
Katja Theune
Keyword(s):  
Student Satisfaction ◽  
Early Stage ◽  
Binary Classification ◽  
Early Warning Systems ◽  
Conditional Inference ◽  
Set Covering ◽  
Study Phase ◽  
Early Prediction ◽  
Data Set ◽  
Wide Range

AbstractWe predict university dropout using random forests based on conditional inference trees and on a broad German data set covering a wide range of aspects of student life and study courses. We model the dropout decision as a binary classification (graduate or dropout) and focus on very early prediction of student dropout by stepwise modeling students’ transition from school (pre-study) over the study-decision phase (decision phase) to the first semesters at university (early study phase). We evaluate how predictive performance changes over the three models, and observe a substantially increased performance when including variables from the first study experiences, resulting in an AUC (area under the curve) of 0.86. Important predictors are the final grade at secondary school, and also determinants associated with student satisfaction and their subjective academic self-concept and self-assessment. A direct outcome of this research is the provision of information to universities wishing to implement early warning systems and more personalized counseling services to support students at risk of dropping out during an early stage of study.

scholarly journals Experimental duration and predator satiation levels systematically affect functional response parameters

2017 ◽  
Author(s):  
Yuanheng Li ◽  
Björn C. Rall ◽  
Gregor Kalinkat
Keyword(s):  
Food Web ◽  
Functional Response ◽  
Large Data ◽  
Handling Time ◽  
Set Covering ◽  
Parameter Estimates ◽  
Functional Responses ◽  
Predator Satiation ◽  
Data Set ◽  
Wide Range

AbstractEmpirical feeding studies where density-dependent consumption rates are fitted to functional response models are often used to parametrize the interaction strengths in models of population or food-web dynamics. However, the relationship between functional response parameter estimates from short-term feeding studies and real-world, long-term, trophic interaction strengths remains largely untested. In a critical first step to address this void, we tested for systematic effects of experimental duration and predator satiation on the estimation of functional response parameters, namely attack rate and handling time. Analyzing a large data set covering a wide range of predator taxonomies and body sizes we show that attack rates decrease with increasing experimental duration, and that handling times of starved predators are consistently shorter than those of satiated predators. Therefore, both the experimental duration and the predator satiation level have a strong and systematic impact on the predictions of population dynamics and food-web stability. Our study highlights potential pitfalls at the intersection of empirical and theoretical applications of functional responses. We conclude our study with some practical suggestions how these implications should be addressed in the future to improve predictive abilities and realism in models of predator-prey interactions.

scholarly journals Chan-Vese Segmentation of SEM FerritePearlite Microstructure and Prediction of Grain Boundary

2019 ◽  
Vol 8 (11) ◽  
pp. 3434-3437
Keyword(s):  
Image Processing ◽  
Grain Boundary ◽  
Phase Region ◽  
Set Covering ◽  
Phase Identification ◽  
Data Set ◽  
Steel Microstructure ◽  
Sem Image ◽  
Wide Range ◽  
Segmentation Task

The image processing of microstructure for design, measure and control of metal processing has been emerging as a new area of research for advancement towards the development of Industry 4.0 framework. However, exact steel phase segmentation is the key challenge for phase identification and quantification in microstructure employing proper image processing tool. In this article, we report effectiveness of a region based segmentation tool, Chan-Vese in phase segmentation task from a ferrite- pearlite steel microstructure captured in scanning electron microscopy image (SEM) image. The algorithm has been applied on microstructure images and the results are discussed in light of the effectiveness of Chan-Vese algorithms on microstructure image processing and phase segmentation application. Experiments on the ferrite perlite microstructure data set covering a wide range of resolution revealed that the Chan-Vese algorithm is efficient in segmentation of phase region and predicting the grain boundary.

scholarly journals Variation in compulsory psychiatric inpatient admission in England: a cross-sectional, multilevel analysis

2014 ◽  
Vol 2 (49) ◽  
pp. 1-90 ◽  
Author(s):  
Scott Weich ◽  
Orla McBride ◽  
Liz Twigg ◽  
Patrick Keown ◽  
Eva Cyhlarova ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Health Services ◽  
Health Services ◽  
Null Model ◽  
Compulsory Admission ◽  
Cross Sectional ◽  
Data Set ◽  
Explanatory Variables ◽  
Significant Variance ◽  
Wide Range

BackgroundRates of compulsory admission have increased in England in recent decades, and this trend is accelerating. Studying variation in rates between people and places can help identify modifiable causes.ObjectivesTo quantify and model variances in the rate of compulsory admission in England at different spatial levels and to assess the extent to which this was explained by characteristics of people and places.DesignCross-sectional analysis using multilevel statistical modelling.SettingEngland, including 98% of Census lower layer super output areas (LSOAs), 95% of primary care trusts (PCTs), 93% of general practices and all 69 NHS providers of specialist mental health services.Participants1,287,730 patients.Main outcome measureThe study outcome was compulsory admission, defined as time spent in an inpatient mental illness bed subject to the Mental Health Act (2007) in 2010/11. We excluded patients detained under sections applying to emergency assessment only (including those in places of safety), guardianship or supervision of community treatment. The control group comprised all other users of specialist mental health services during the same period.Data sourcesThe Mental Health Minimum Data Set (MHMDS). Data on explanatory variables, characterising each of the spatial levels in the data set, were obtained from a wide range of sources, and were linked using MHMDS identifiers.ResultsA total of 3.5% of patients had at least one compulsory admission in 2010/11. Of (unexplained) variance in the null model, 84.5% occurred between individuals. Statistically significant variance occurred between LSOAs [6.7%, 95% confidence interval (CI) 6.2% to 7.2%] and provider trusts (6.9%, 95% CI 4.3% to 9.5%). Variances at these higher levels remained statistically significant even after adjusting for a large number of explanatory variables, which together explained only 10.2% of variance in the study outcome. The number of provider trusts whose observed rate of compulsory admission differed from the model average to a statistically significant extent fell from 45 in the null model to 20 in the fully adjusted model. We found statistically significant associations between compulsory admission and age, gender, ethnicity, local area deprivation and ethnic density. There was a small but statistically significant association between (higher) bed occupancy and compulsory admission, but this was subsequently confounded by other covariates. Adjusting for PCT investment in mental health services did not improve model fit in the fully adjusted models.ConclusionsThis was the largest study of compulsory admissions in England. While 85% of the variance in this outcome occurred between individuals, statistically significant variance (around 7% each) occurred between places (LSOAs) and provider trusts. This higher-level variance in compulsory admission remained largely unchanged even after adjusting for a large number of explanatory variables. We were constrained by data available to us, and therefore our results must be interpreted with caution. We were also unable to consider many hypotheses suggested by the service users, carers and professionals who we consulted. There is an imperative to develop and evaluate interventions to reduce compulsory admission rates. This requires further research to extend our understanding of the reasons why these rates remain so high.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

scholarly journals Chan-Vese segmentation of SEM ferritepearlite microstructure and prediction of grain boundary

2019 ◽  
Vol 8 (10) ◽  
pp. 1495-1498
Keyword(s):  
Image Processing ◽  
Grain Boundary ◽  
Phase Region ◽  
Set Covering ◽  
Phase Identification ◽  
Data Set ◽  
Steel Microstructure ◽  
Sem Image ◽  
Wide Range ◽  
Segmentation Task

The image processing of microstructure for design, measure and control of metal processing has been emerging as a new area of research for advancement towards the development of Industry 4.0 framework. However, exact steel phase segmentation is the key challenge for phase identification and quantification in microstructure employing proper image processing tool. In this article, we report effectiveness of a region based segmentation tool, Chan-Vese in phase segmentation task from a ferrite- pearlite steel microstructure captured in scanning electron microscopy image (SEM) image. The algorithm has been applied on microstructure images and the results are discussed in light of the effectiveness of Chan-Vese algorithms on microstructure image processing and phase segmentation application. Experiments on the ferrite perlite microstructure data set covering a wide range of resolution revealed that the Chan-Vese algorithm is efficient in segmentation of phase region and predicting the grain boundary.

Measuring the use of human resources practices and employee attitudes

2016 ◽  
Vol 4 (2) ◽  
pp. 94-115 ◽  
Author(s):  
Patrick Kampkötter ◽  
Jens Mohrenweiser ◽  
Dirk Sliwka ◽  
Susanne Steffes ◽  
Stefanie Wolter
Keyword(s):  
Human Resources ◽  
Human Resources Management ◽  
Personal Characteristics ◽  
Employee Attitudes ◽  
Set Covering ◽  
Human Resource Research ◽  
Data Set ◽  
Employee Survey ◽  
Content Type ◽  
Wide Range

Purpose – The purpose of this paper is to introduce a new data source available for researchers with interest in human resources management (HRM) and personnel economics, the Linked Personnel Panel (LPP). Design/methodology/approach – The LPP is a longitudinal and representative employer-employee data set covering establishments in Germany and a subset of their workforce and is designed for quantitative empirical human resource research. Findings – The LPP employee survey applies a number of established scales to measure job characteristics and job perceptions, personal characteristics, employee attitudes towards the organization and employee behaviour. This paper gives an overview of both the employer and employee survey and outlines the definitions, origins, and statistical properties of the scales used in the individual questionnaire. Practical implications – The paper describes how researchers can access the data. Originality/value – First, the data set combines employer and employee surveys that can be matched to each other. Second, it can also be linked to a number of additional administrative data sets. Third, the LPP covers a wide range of firms and workers from different backgrounds. Finally, because of its longitudinal dimension, the LPP should facilitate the study of causal effects of HRM practices.

scholarly journals Introducing COSMOS: a web-platform for multimodal game-based psychological assessment geared towards open science practice

2018 ◽  
Author(s):  
Andy Aeberhard ◽  
Leo Gschwind ◽  
Joe Kossowsky ◽  
Gediminas Luksys ◽  
Dominique de Quervain ◽  
...  
Keyword(s):  
Large Scale ◽  
Online Survey ◽  
Short Term Memory ◽  
Measure Theory ◽  
Open Science ◽  
Single Shot ◽  
Data Set ◽  
Wide Range ◽  
Set Up ◽  
Testing Instruments

We have established the COgnitive Science Metrics Online Survey (COSMOS) platform that contains a digital psychometrics toolset in the guise of applied games measuring a wide range of cognitive functions. Here we are outlining this online research endeavor designed for automatized psychometric data collection and scalable assessment: Once set up, the low costs and expenditure associated with individual psychometric testing allow substantially increased study cohorts and thus contribute to enhancing study outcome reliability. We are leveraging gamification of the data acquisition method to make the tests suitable for online administration. By putting a strong focus on entertainment and individually tailored feedback, we aim to maximize subjects’ incentives for repeated and continued participation. The objective of measuring repeatedly is obtaining more revealing multi-trial average scores and measures from various operationalizations of the same psychological construct instead of relying on single-shot measurements. COSMOS is set up to acquire an automatically and continuously growing dataset that can be used to answer a wide variety of research questions.Following the principles of the open science movement, this data set will also be made accessible to other publicly-funded researchers, given that all precautions for individual data protection are fulfilled. We have developed a secure hosting platform and a series of digital gamified testing instruments that can measure theory of mind, attention, working memory, episodic long- and short-term memory, spatial memory, reaction times, eye-hand coordination, impulsivity, humor appreciation, altruism, fairness, strategic thinking, decision making and risk-taking behavior. Furthermore, some of the game-based testing instruments also offer the possibility of using classical questionnaire items. A subset of these gamified tests is already implemented in the COSMOS platform, publicly accessible and currently undergoing evaluation and calibration as normative data is being collected. In summary, our approach can be used to accomplish a detailed and reliable psychometric characterization of thousands of individuals to supply various studies with large-scale neuro-cognitive phenotypes. Our game-based online testing strategy can also guide recruitment for studies as they allow very efficient screening and sample composition. Finally, this setup also allows to evaluate potential cognitive training effects and whether improvements are merely task specific or if generalization effects occur in or even across cognitive domains.

The Consortium of Australian Academic Psychiatrists for Independent Policy Research and Analysis (CAPIPRA): Aims, model, outputs, and implications for clinical academic advocacy

2021 ◽  
pp. 103985622110528
Author(s):  
Jeffrey C.L. Looi ◽  
Stephen Allison ◽  
Tarun Bastiampillai ◽  
Stephen R. Kisely
Keyword(s):  
Mental Health ◽  
Policy Research ◽  
Mental Healthcare ◽  
Evidence Based ◽  
Services Research ◽  
Wide Range ◽  
Population Mental Health ◽  
Policy And Planning ◽  
Research And Policy ◽  
Independent Model

Objective: We describe an independent model of clinical academic mental health services research that is able to provide synthesised views for medico-political organisations that are engaged in advocacy for national and state evidence-based policy and planning of mental healthcare. Conclusions: CAPIPRA focuses on independent research and policy analysis using publicly available datasets on population mental health at national and state/territory levels, published in international and national peer-reviewed journals (>50 papers since 2019). We partner with medico-political organisations in evidence-based advocacy across a wide range of issues.

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