Mining big data to create a tool for empirical observation of continuous safety improvement in a construction company - A progressive case study in the lean environment

In any iterative process, without a system of measurement, controlled improvement cannot be recorded. This is especially true in the construction industry, where error occurs, often with fatal repercussions. As part of a process to facilitate the establishment of this metric, an entirely new application was created. The goal of this application is to measure the causal factors that lead to incidents, which will allow the user and administration to track the circumstances and types of incidents. This enables the company to focus on these problem areas and improve through training. By analyzing these incident trends over time, the company can conclude the following: if training reduces the total number of incidents for a given category (identified through these trends), then the corrective action is working. If not, the team must then redefine the problem, which is part of the aforementioned iterative process. The purpose of this study was to identify a viable metric that captures safety practice improvement over time, and verify that the company’s records indicate a correlation between quantity of incidents recorded and man-hours of exposure decreasing over time. Live server data was provided and a series of queries were performed on relevant tables. These result sets were then placed into a database created by the researcher and manipulated to display trend lines representing incident rates over time, as well as specifically identifying a metric of incident count per month/man-hours per month (companywide). Descriptive statistics were performed, with results indicating that although the reporting process itself was becoming standardized and the latter half of the trend chart showed comparable numbers, there was simply not enough reported data as of yet to provide conclusive evidence on the impact of lean practices as it relates to incidence quantity. It is the researcher’s belief, however, that the data suggests an inverse relationship, as the quantity of human reported incidents had increased as a result of standardized practices and effectively captured more instances that may have likely previously gone unrecorded

Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions

Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education. This study evaluated the capabilities of leading LLMs, including GPT-4, GPT-3.5, PaLM2, Claude2, and SenseNova, in answering conceptual biology questions. The models were tested on a 108-question multiple-choice exam covering biology topics in molecular biology, biological techniques, metabolic engineering, and synthetic biology. Among the models, GPT-4 achieved the highest average score of 90 and demonstrated the greatest consistency across trials with different prompts. The results indicated GPT-4's proficiency in logical reasoning and its potential to aid biology research through capabilities like data analysis, hypothesis generation, and knowledge integration. However, further development and validation are still required before the promise of LLMs in accelerating biological discovery can be realized

Umbrella review: methodological review of reviews published in peer-reviewed journals with a substantial focus on vocational education and training research

Purpose: The growing public interest in vocational education and training (VET), most recently since the economic crisis of 2007/2008, has led to an exponential increase in articles with a vocational focus, underscoring the need for review studies for the purposes of systematic knowledge aggregation, clarification and interpretation. We assume that review studies follow the same minimum standards as other research methods: the review must be at least reproducible and thus the results verifiable or falsifiable. So far, however, the review methods used in VET research have not been investigated. Our purpose is to review the review procedures and methods used in published reviews of VET research to identify their current methodological quality. Approach: To classify the review studies, we initially developed a conceptual framework to distinguish different types of reviews. We then developed a methodological framework to assess the review methods used. Overall, to accelerate the review process, our review of reviews (or umbrella review) followed the rapid review approach: we limited our search to reviews in English published between 2014 and 2019 in peer-reviewed journals with a substantial VET focus and indexed in Scopus and/or Web of Science. Therefore, we did not examine all existing reviews in the field of VET research. Rather, our specific focus was on a core sector of scientific research: peer-reviewed articles in curated databases. Furthermore, we concentrated on the review procedures and methods used, not on the content of the reviews. Findings: We identified nine journals with a substantial VET focus, yielding a total of 1,283 published articles between 2014 and 2019, of which only 19 articles (1.48%) were literature reviews. Of these 19 reviews, six were excluded from our umbrella review because of unclear methodological procedures. Based on the review typology we developed, five of the remaining 13 reviews were conceptual in nature, four were scoping reviews, three were evidence-oriented, and one was critical in nature. None of the reviews examined focused on meta-syntheses, research methods or meta-analyses. In total, this resulted in current review gaps with respect to theory generation (meta-synthesis), practice of theory elaboration and testing (methodological review) and the determination of overall effects across single studies (meta-analysis). Finally, our examination of the reviews showed that their scope was mostly clearly presented. However, with regard to the process steps ‘data selection’ and ‘data processing’, only a few reviews fully met the requirements of the methodological framework. Conclusion: Our review leads to four conclusions. 1) More systematic syntheses are needed because there is a substantial quantitative gap in review research. 2) In particular, there is a need for review studies with a focus on meta-synthesis, research methods and meta-analysis, as there is a current gap in these areas. 3) Reviews should be based on a review methodology with transparent and reproducible methods and verifiable or falsifiable results. The high number of subjective syntheses with unclear review procedures indicates that this mindset is not yet fully established in the field of VET research. 4) In the studies examined, there is a high degree of heterogeneity regarding to the accuracy and completeness of the methodological steps and data. The conceptual and methodological frameworks developed for the analysis can serve as guidelines for the conduct of reviews, and thus, the frameworks could contribute to the further development of the methodological basis of reviews. (DIPF/Orig.

The RADx Tech Test Verification Core and the ACME POCT in the Evaluation of COVID-19 Testing Devices: A Model for Progress and Change

Faced with the COVID-19 pandemic, the US system for developing and testing technologies was challenged in unparalleled ways. This article describes the multi-institutional, transdisciplinary team of the “RADx SM Tech Test Verification Core” and its role in expediting evaluations of COVID-19 testing devices. Expertise related to aspects of diagnostic testing was coordinated to evaluate testing devices with the goal of significantly expanding the ability to mass screen Americans to preserve lives and facilitate the safe return to work and school. Focal points included: laboratory and clinical device evaluation of the limit of viral detection, sensitivity, and specificity of devices in controlled and community settings; regulatory expertise to provide focused attention to barriers to device approval and distribution; usability testing from the perspective of patients and those using the tests to identify and overcome device limitations, and engineering assessment to evaluate robustness of design including human factors, manufacturability, and scalability

Information Systems and Healthcare XXXIV: Clinical Knowledge Management Systems—Literature Review and Research Issues for Information Systems

Knowledge Management (KM) has emerged as a possible solution to many of the challenges facing U.S. and international healthcare systems. These challenges include concerns regarding the safety and quality of patient care, critical inefficiency, disparate technologies and information standards, rapidly rising costs and clinical information overload. In this paper, we focus on clinical knowledge management systems (CKMS) research. The objectives of the paper are to evaluate the current state of knowledge management systems diffusion in the clinical setting, assess the present status and focus of CKMS research efforts, and identify research gaps and opportunities for future work across the medical informatics and information systems disciplines. The study analyzes the literature along two dimensions: (1) the knowledge management processes of creation, capture, transfer, and application, and (2) the clinical processes of diagnosis, treatment, monitoring and prognosis. The study reveals that the vast majority of CKMS research has been conducted by the medical and health informatics communities. Information systems (IS) researchers have played a limited role in past CKMS research. Overall, the results indicate that there is considerable potential for IS researchers to contribute their expertise to the improvement of clinical process through technology-based KM approaches

A Case Study of the United States Veterans\u27 Disability Compensation Policy Subsystem

In public policy literature, there is a lack of research that integrates social construction theory within the advocacy coalition framework, and far less is known about how these theories address policy change and processes related to programs for disabled veterans.The purpose of this study was to conduct a policy analysis to evaluate how well the needs of veterans are met through the U.S. Veterans\u27 Disability Compensation (USVDC) program. In a case study of a city in the southeastern U.S., gaps between formulation and implementation of USVDC policy were examined. The theoretical frameworks used in this study were Hacker\u27s formulation and implementation gap to analyze policy, Schneider and Ingram\u27s conceptualization of social construction, and Sabatier and Weible\u27s advocacy coalition framework. The central research question for this study explored the extent to which the USVDC program meets the needs of disabled veterans (DVs). Data consisting of over 355 USVDC formulation and implementation documents, from March 2007 through August 2013, were coded using a priori codes and content analysis methodology.Findings indicate the USVDC policy subsystem struggled to manage the claims backlog that grew to over one million claims. Between April 2013 and September 2013, an emphasis to reduce the claims backlog improved stalled policy formulation, resulting in a shift to positive social constructions for DVs.Implications for positive social change include improved collaboration between policy makers, the Veterans\u27 Administration, and recently transitioned target group DVs, to reshape policy formulation and implementation to further improve the quality of life for sick and injured veterans when entering the USVDC policy subsystem

Principles in Patterns (PiP) : User Acceptance Testing of Course and Class Approval Online Pilot (C-CAP)

The PiP Evaluation Plan documents four distinct evaluative strands, the first of which entails an evaluation of the PiP system pilot (WP7:37 – Systems & tool evaluation). Phase 1 of this evaluative strand focused on the heuristic evaluation of the PiP Course and Class Approval Online Pilot system (C-CAP) and was completed in December 2011. Phase 2 of the evaluation is broadly concerned with "user acceptance testing". This entails exploring the extent to which C-CAP functionality meets users' expectations within specific curriculum design tasks, as well as eliciting data on C-CAP's overall usability and its ability to support academics in improving the quality of curricula. The general evaluative approach adopted therefore employs a combination of standard Human-Computer Interaction (HCI) approaches and specially designed data collection instruments, including protocol analysis, stimulated recall and pre- and post-test questionnaire instruments. This brief report summarises the methodology deployed, presents the results of the evaluation and discusses their implications for the further development of C-CAP

Carrying Out Rapid Qualitative Research During a Pandemic: Emerging Lessons From COVID-19

Social scientists have a robust history of contributing to better understandings of and responses to disease outbreaks. The implementation of qualitative research in the context of infectious epidemics, however, continues to lag behind in the delivery, credibility, and timeliness of findings when compared with other research designs. The purpose of this article is to reflect on our experience of carrying out three research studies (a rapid appraisal, a qualitative study based on interviews, and a mixed-methods survey) aimed at exploring health care delivery in the context of COVID-19. We highlight the importance of qualitative data to inform evidence-based public health responses and provide a way forward to global research teams who wish to implement similar rapid qualitative studies. We reflect on the challenges of setting up research teams, obtaining ethical approval, collecting and analyzing data in real-time and sharing actionable findings