Methods and Tools for Objective Assessment of Psychomotor Skills in Laparoscopic Surgery

Training and assessment paradigms for laparoscopic surgical skills are evolving from traditional mentor–trainee tutorship towards structured, more objective and safer programs. Accreditation of surgeons requires reaching a consensus on metrics and tasks used to assess surgeons’ psychomotor skills. Ongoing development of tracking systems and software solutions has allowed for the expansion of novel training and assessment means in laparoscopy. The current challenge is to adapt and include these systems within training programs, and to exploit their possibilities for evaluation purposes. This paper describes the state of the art in research on measuring and assessing psychomotor laparoscopic skills. It gives an overview on tracking systems as well as on metrics and advanced statistical and machine learning techniques employed for evaluation purposes. The later ones have a potential to be used as an aid in deciding on the surgical competence level, which is an important aspect when accreditation of the surgeons in particular, and patient safety in general, are considered. The prospective of these methods and tools make them complementary means for surgical assessment of motor skills, especially in the early stages of training. Successful examples such as the Fundamentals of Laparoscopic Surgery should help drive a paradigm change to structured curricula based on objective parameters. These may improve the accreditation of new surgeons, as well as optimize their already overloaded training schedules.

A Language to Formalize and to Operationalize Problem-solving Strategies of Structured Knowledge Models

This paper describes a proposal of a language called Link which has been designed to formalize and operationalize problem solving strategies. This language is used within a software environment called KSM (Knowledge Structure Manager) which helps developers in formulating and operationalizing structured knowledge models. The paper presents both its syntax and dynamics, and gives examples of well-known problem-solving strategies of reasoning formulated using this language.

A Structure of Problem Solving Methods for Real Time Decision Support in Traffic Control

This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona.

Structuring research methods and data with the research object model: genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

Short structured feedback training is equivalent to a mechanical feedback device in two-rescuer BLS: a randomised simulation study.

BACKGROUND Resuscitation guidelines encourage the use of cardiopulmonary resuscitation (CPR) feedback devices implying better outcomes after sudden cardiac arrest. Whether effective continuous feedback could also be given verbally by a second rescuer ("human feedback") has not been investigated yet. We, therefore, compared the effect of human feedback to a CPR feedback device. METHODS In an open, prospective, randomised, controlled trial, we compared CPR performance of three groups of medical students in a two-rescuer scenario. Group "sCPR" was taught standard BLS without continuous feedback, serving as control. Group "mfCPR" was taught BLS with mechanical audio-visual feedback (HeartStart MRx with Q-CPR-Technology™). Group "hfCPR" was taught standard BLS with human feedback. Afterwards, 326 medical students performed two-rescuer BLS on a manikin for 8 min. CPR quality parameters, such as "effective compression ratio" (ECR: compressions with correct hand position, depth and complete decompression multiplied by flow-time fraction), and other compression, ventilation and time-related parameters were assessed for all groups. RESULTS ECR was comparable between the hfCPR and the mfCPR group (0.33 vs. 0.35, p = 0.435). The hfCPR group needed less time until starting chest compressions (2 vs. 8 s, p < 0.001) and showed fewer incorrect decompressions (26 vs. 33 %, p = 0.044). On the other hand, absolute hands-off time was higher in the hfCPR group (67 vs. 60 s, p = 0.021). CONCLUSIONS The quality of CPR with human feedback or by using a mechanical audio-visual feedback device was similar. Further studies should investigate whether extended human feedback training could further increase CPR quality at comparable costs for training.

Electronic structure methods applied to gas-carbon reactions

A review is given on the fundamental studies of gas-carbon reactions using electronic structure methods in the last several decades. The three types of electronic structure methods including semi-empirical, ab initio and density functional theory, methods are briefly introduced first, followed by the studies on carbon reactions with hydrogen and oxygen-containing gases (non-catalysed and catalysed). The problems yet to solve and possible promising directions are discussed. (C) 2002 Elsevier Science Ltd. All rights reserved.

Improving the physical status and quality of life of women treated for breast cancer: A pilot study of a structured exercise intervention

Background and Objectives: This pilot project assessed the acceptability of a mixed-type, moderate-intensity exercise programme following breast cancer treatment, and the impact on presence of lymphoedema, fitness, body composition, fatigue, mood and quality of life. Methods: Ten women completed the programme and measures of fitness (submaximal ergometer test), body composition (bio-electrical impedance), lympoedema (bio-electrical impedance and arm circumferences), fatigue (revised Piper Fatigue Scale), mood (Hospital Anxiety and Depression Scale), quality of life (FACT-B) and general well-being, at baseline, completion of the programme, and 6-week and 3-month follow-up. Results: Participation in the programme caused no adverse effect on the presence of lymphoedema. There was a trend towards reduction in fatigue and improved quality of life across the testing phases. Women rated the programme extremely favourably, citing benefits of the support of other women, trained guidance, and the opportunity to experience different types of exercise. Conclusions: A mixed-type, moderate-intensity exercise program in a group format is acceptable to women following breast cancer treatment, with the potential to reduce fatigue and improve quality of life, without exacerbating or precipitating lymphoedema. This pilot work needs to be confirmed in larger randomised studies. (C) 2004 Wiley-Liss, Inc.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Practices and views on fetal heart monitoring:A structured observation and interview study

Objective: To assess and explain deviations from recommended practice in National Institute for Clinical Excellence (NICE) guidelines in relation to fetal heart monitoring. Design: Qualitative study. Setting: Large teaching hospital in the UK. Sample: Sixty-six hours of observation of 25 labours and interviews with 20 midwives of varying grades. Methods: Structured observations of labour and semistructured interviews with midwives. Interviews were undertaken using a prompt guide, audiotaped, and transcribed verbatim. Analysis was based on the constant comparative method, assisted by QSR N5 software. Main outcome measures: Deviations from recommended practice in relation to fetal monitoring and insights into why these occur. Results: All babies involved in the study were safely delivered, but 243 deviations from recommended practice in relation to NICE guidelines on fetal monitoring were identified, with the majority (80%) of these occurring in relation to documentation. Other deviations from recommended practice included indications for use of electronic fetal heart monitoring and conduct of fetal heart monitoring. There is evidence of difficulties with availability and maintenance of equipment, and some deficits in staff knowledge and skill. Differing orientations towards fetal monitoring were reported by midwives, which were likely to have impacts on practice. The initiation, management, and interpretation of fetal heart monitoring is complex and distributed across time, space, and professional boundaries, and practices in relation to fetal heart monitoring need to be understood within an organisational and social context. Conclusion: Some deviations from best practice guidelines may be rectified through straightforward interventions including improved systems for managing equipment and training. Other deviations from recommended practice need to be understood as the outcomes of complex processes that are likely to defy easy resolution. © RCOG 2006.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

Appraising qualitative research for inclusion in systematic reviews:A quantitative and qualitative comparison of three methods

Objective: Qualitative research is increasingly valued as part of the evidence for policy and practice, but how it should be appraised is contested. Various appraisal methods, including checklists and other structured approaches, have been proposed but rarely evaluated. We aimed to compare three methods for appraising qualitative research papers that were candidates for inclusion in a systematic review of evidence on support for breast-feeding. Method: A sample of 12 research papers on support for breast-feeding was appraised by six qualitative reviewers using three appraisal methods: unprompted judgement, based on expert opinion; a UK Cabinet Office quality framework; and CASP, a Critical Appraisal Skills Programme tool. Papers were assigned, following appraisals, to 1 of 5 categories, which were dichotomized to indicate whether or not papers should be included in a systematic review. Patterns of agreement in categorization of papers were assessed quantitatively using κ statistics, and qualitatively using cross-case analysis. Results: Agreement in categorizing papers across the three methods was slight (κ =0.13; 95% CI 0.06-0.24). Structured approaches did not appear to yield higher agreement than that by unprompted judgement. Qualitative analysis revealed reviewers' dilemmas in deciding between the potential impact of findings and the quality of the research execution or reporting practice. Structured instruments appeared to make reviewers more explicit about the reasons for their judgements. Conclusions: Structured approaches may not produce greater consistency of judgements about whether to include qualitative papers in a systematic review. Future research should address how appraisals of qualitative research should be incorporated in systematic reviews. © The Royal Society of Medicine Press Ltd 2007.

Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

Investigating mental health risk assessment in primary care and the potential role of a structured decision support tool, GRiST

Aim: To explore current risk assessment processes in general practice and Improving Access to Psychological Therapies (IAPT) services, and to consider whether the Galatean Risk and Safety Tool (GRiST) can help support improved patient care. Background: Much has been written about risk assessment practice in secondary mental health care, but little is known about how it is undertaken at the beginning of patients' care pathways, within general practice and IAPT services. Methods: Interviews with eight general practice and eight IAPT clinicians from two primary care trusts in the West Midlands, UK, and eight service users from the same region. Interviews explored current practice and participants' views and experiences of mental health risk assessment. Two focus groups were also carried out, one with general practice and one with IAPT clinicians, to review interview findings and to elicit views about GRiST from a demonstration of its functionality. Data were analysed using thematic analysis. Findings Variable approaches to mental health risk assessment were observed. Clinicians were anxious that important risk information was being missed, and risk communication was undermined. Patients felt uninvolved in the process, and both clinicians and patients expressed anxiety about risk assessment skills. Clinicians were positive about the potential for GRiST to provide solutions to these problems. Conclusions: A more structured and systematic approach to risk assessment in general practice and IAPT services is needed, to ensure important risk information is captured and communicated across the care pathway. GRiST has the functionality to support this aspect of practice.

Systemological Knowledge-based Technology for Solving Complete Ill-structured Problems

Original method and technology of systemological «Unit-Function-Object» analysis for solving complete ill-structured problems is proposed. The given visual grapho-analytical UFO technology for the fist time combines capabilities and advantages of the system and object approaches and can be used for business reengineering and for information systems design. UFO- technology procedures are formalized by pattern-theory methods and developed by embedding systemological conceptual classification models into the system-object analysis and software tools. Technology is based on natural classification and helps to investigate deep semantic regularities of subject domain and to take proper account of system-classes essential properties the most objectively. Systemological knowledge models are based on method which for the first time synthesizes system and classification analysis. It allows creating CASE-toolkit of a new generation for organizational modelling for companies’ sustainable development and competitive advantages providing.