Defining the methodological challenges and opportunities for an effective science of sociotechnical systems and safety

An important part of the application of sociotechnical systems theory (STS) is the development of methods, tools and techniques to assess human factors and ergonomics workplace requirements. We focus in this paper on describing and evaluating current STS methods for workplace safety, as well as outlining a set of six case studies covering the application of these methods to a range of safety contexts. We also describe an evaluation of the methods in terms of ratings of their ability to address a set of theoretical and practical questions (e.g. the degree to which methods capture static/dynamic aspects of tasks and interactions between system levels). The outcomes from the evaluation highlight a set of gaps relating to the coverage and applicability of current methods for STS and safety (e.g. coverage of external influences on system functioning; method usability). The final sections of the paper describe a set of future challenges, as well as some practical suggestions for tackling these. Practitioner Summary: We provide an up-to-date review of STS methods, a set of case studies illustrating their use and an evaluation of their strengths and weaknesses. The paper concludes with a ‘roadmap’ for future work

Contribution of copy number variants (CNVs) to congenital, unexplained intellectual and developmental disabilities in Lebanese patients

International audienceBackground: Chromosomal microarray analysis (CMA) is currently the most widely adopted clinical test for patients with unexplained intellectual disability (ID), developmental delay (DD), and congenital anomalies. Its use has revealed the capacity to detect copy number variants (CNVs), as well as regions of homozygosity, that, based on their distribution on chromosomes, indicate uniparental disomy or parental consanguinity that is suggestive of an increased probability of recessive disease. Results: We screened 149 Lebanese probands with ID/DD and 99 healthy controls using the Affymetrix Cyto 2.7 M and SNP6.0 arrays. We report all identified CNVs, which we divided into groups. Pathogenic CNVs were identified in 12.1% of the patients. We review the genotype/phenotype correlation in a patient with a 1q44 microdeletion and refine the minimal critical regions responsible for the 10q26 and 16q monosomy syndromes. Several likely causative CNVs were also detected, including new homozygous microdeletions (9p23p24.1, 10q25.2, and 8p23.1) in 3 patients born to consanguineous parents, involving potential candidate genes. However, the clinical interpretation of several other CNVs remains uncertain, including a microdeletion affecting ATRNL1. This CNV of unknown significance was inherited from the patient's unaffected-mother; therefore, additional ethnically matched controls must be screened to obtain enough evidence for classification of this CNV. Conclusion: This study has provided supporting evidence that whole-genome analysis is a powerful method for uncovering chromosomal imbalances, regardless of consanguinity in the parents of patients and despite the challenge presented by analyzing some CNVs

Policies, Political-Economy, and Swidden in Southeast Asia

For centuries swidden was an important farming practice found across the girth of Southeast Asia. Today, however, these systems are changing and sometimes disappearing at a pace never before experienced. In order to explain the demise or transitioning of swidden we need to understand the rapid and massive changes that have and are occurring in the political and economic environment in which these farmers operate. Swidden farming has always been characterized by change, but since the onset of modern independent nation states, governments and markets in Southeast Asia have transformed the terms of swiddeners’ everyday lives to a degree that is significantly different from that ever experienced before. In this paper we identified six factors that have contributed to the demise or transformation of swidden systems, and support these arguments with examples from China (Xishuangbanna), Laos, Thailand, Malaysia, and Indonesia. These trends include classifying swiddeners as ethnic minorities within nation-states, dividing the landscape into forest and permanent agriculture, expansion of forest departments and the rise of conservation, resettlement, privatization and commoditization of land and land-based production, and expansion of market infrastructure and the promotion of industrial agriculture. In addition we note a growing trend toward a transition from rural to urban livelihoods and expanding urban-labor markets

Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details

Osteoporosis-related fracture case definitions for population-based administrative data

<p>Abstract</p> <p>Background</p> <p>Population-based administrative data have been used to study osteoporosis-related fracture risk factors and outcomes, but there has been limited research about the validity of these data for ascertaining fracture cases. The objectives of this study were to: (a) compare fracture incidence estimates from administrative data with estimates from population-based clinically-validated data, and (b) test for differences in incidence estimates from multiple administrative data case definitions.</p> <p>Methods</p> <p>Thirty-five case definitions for incident fractures of the hip, wrist, humerus, and clinical vertebrae were constructed using diagnosis codes in hospital data and diagnosis and service codes in physician billing data from Manitoba, Canada. Clinically-validated fractures were identified from the Canadian Multicentre Osteoporosis Study (CaMos). Generalized linear models were used to test for differences in incidence estimates.</p> <p>Results</p> <p>For hip fracture, sex-specific differences were observed in the magnitude of under- and over-ascertainment of administrative data case definitions when compared with CaMos data. The length of the fracture-free period to ascertain incident cases had a variable effect on over-ascertainment across fracture sites, as did the use of imaging, fixation, or repair service codes. Case definitions based on hospital data resulted in under-ascertainment of incident clinical vertebral fractures. There were no significant differences in trend estimates for wrist, humerus, and clinical vertebral case definitions.</p> <p>Conclusions</p> <p>The validity of administrative data for estimating fracture incidence depends on the site and features of the case definition.</p

Hidden in the Middle : Culture, Value and Reward in Bioinformatics

Bioinformatics - the so-called shotgun marriage between biology and computer science - is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised 'outputs' in academia are often defined and rewarded by discipline. Bioinformatics, as an interdisciplinary bricolage, incorporates experts from various disciplinary cultures with their own distinct ways of working. Perceived problems of interdisciplinarity include difficulties of making explicit knowledge that is practical, theoretical, or cognitive. But successful interdisciplinary research also depends on an understanding of disciplinary cultures and value systems, often only tacitly understood by members of the communities in question. In bioinformatics, the 'parent' disciplines have different value systems; for example, what is considered worthwhile research by computer scientists can be thought of as trivial by biologists, and vice versa. This paper concentrates on the problems of reward and recognition described by scientists working in academic bioinformatics in the United Kingdom. We highlight problems that are a consequence of its cross-cultural make-up, recognising that the mismatches in knowledge in this borderland take place not just at the level of the practical, theoretical, or epistemological, but also at the cultural level too. The trend in big, interdisciplinary science is towards multiple authors on a single paper; in bioinformatics this has created hybrid or fractional scientists who find they are being positioned not just in-between established disciplines but also in-between as middle authors or, worse still, left off papers altogether

Patient Safety in the Cardiac Operating Room: Human Factors and Teamwork: A Scientific Study from the American Heart Association

The cardiac surgical operating room (OR) is a complex environment in which highly trained subspecialists interact with each other using sophisticated equipment to care for patients with severe cardiac disease and significant comorbidities. Thousands of patient lives have been saved or significantly improved with the advent of modern cardiac surgery. Indeed, both mortality and morbidity for coronary artery bypass surgery have decreased during the past decade. Nonetheless, the highly skilled and dedicated personnel in cardiac ORs are human and will make errors. Refined techniques, advanced technologies, and enhanced coordination of care have led to significant improvements in cardiac surgery outcomes