The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

MRI-based assessment of the pineal gland in a large population of children aged 0-5 years and comparison with pineoblastoma: part I, the solid gland.

INTRODUCTION: Differentiation between normal solid (non-cystic) pineal glands and pineal pathologies on brain MRI is difficult. The aim of this study was to assess the size of the solid pineal gland in children (0-5 years) and compare the findings with published pineoblastoma cases. METHODS: We retrospectively analyzed the size (width, height, planimetric area) of solid pineal glands in 184 non-retinoblastoma patients (73 female, 111 male) aged 0-5 years on MRI. The effect of age and gender on gland size was evaluated. Linear regression analysis was performed to analyze the relation between size and age. Ninety-nine percent prediction intervals around the mean were added to construct a normal size range per age, with the upper bound of the predictive interval as the parameter of interest as a cutoff for normalcy. RESULTS: There was no significant interaction of gender and age for all the three pineal gland parameters (width, height, and area). Linear regression analysis gave 99 % upper prediction bounds of 7.9, 4.8, and 25.4 mm(2), respectively, for width, height, and area. The slopes (size increase per month) of each parameter were 0.046, 0.023, and 0.202, respectively. Ninety-three percent (95 % CI 66-100 %) of asymptomatic solid pineoblastomas were larger in size than the 99 % upper bound. CONCLUSION: This study establishes norms for solid pineal gland size in non-retinoblastoma children aged 0-5 years. Knowledge of the size of the normal pineal gland is helpful for detection of pineal gland abnormalities, particularly pineoblastoma.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

Assessment of construct validity of a virtual reality laparoscopy simulator.

BACKGROUND: The aim of this study was to assess whether virtual reality (VR) can discriminate between the skills of novices and intermediate-level laparoscopic surgical trainees (construct validity), and whether the simulator assessment correlates with an expert's evaluation of performance. METHODS: Three hundred and seven (307) participants of the 19th-22nd Davos International Gastrointestinal Surgery Workshops performed the clip-and-cut task on the Xitact LS 500 VR simulator (Xitact S.A., Morges, Switzerland). According to their previous experience in laparoscopic surgery, participants were assigned to the basic course (BC) or the intermediate course (IC). Objective performance parameters recorded by the simulator were compared to the standardized assessment by the course instructors during laparoscopic pelvitrainer and conventional surgery exercises. RESULTS: IC participants performed significantly better on the VR simulator than BC participants for the task completion time as well as the economy of movement of the right instrument, not the left instrument. Participants with maximum scores in the pelvitrainer cholecystectomy task performed the VR trial significantly faster, compared to those who scored less. In the conventional surgery task, a significant difference between those who scored the maximum and those who scored less was found not only for task completion time, but also for economy of movement of the right instrument. CONCLUSIONS: VR simulation provides a valid assessment of psychomotor skills and some basic aspects of spatial skills in laparoscopic surgery. Furthermore, VR allows discrimination between trainees with different levels of experience in laparoscopic surgery establishing construct validity for the Xitact LS 500 clip-and-cut task. Virtual reality may become the gold standard to assess and monitor surgical skills in laparoscopic surgery.

Risk of cardiovascular disease in a traditional African population with a high infectious load: a population-based study.

BACKGROUND: To test the inflammatory origin of cardiovascular disease, as opposed to its origin in western lifestyle. Population-based assessment of the prevalences of cardiovascular risk factors and cardiovascular disease in an inflammation-prone African population, including electrocardiography and ankle-arm index measurement. Comparison with known prevalences in American and European societies. METHODOLOGY/PRINCIPAL FINDINGS: Traditional population in rural Ghana, characterised by adverse environmental conditions and a high infectious load. Population-based sample of 924 individuals aged 50 years and older. Median values for cardiovascular risk factors, including waist circumference, BMI, blood pressure, and markers of glucose and lipid metabolism and inflammation. Prevalence of myocardial infarction detected by electrocardiography and prevalence of peripheral arterial disease detected by ankle-arm index. When compared to western societies, we found the Ghanaians to have more proinflammatory profiles and less cardiovascular risk factors, including obesity, dysglycaemia, dyslipidaemia, and hypertension. Prevalences of cardiovascular disease were also lower. Definite myocardial infarction was present in 1.2% (95%CI: 0.6 to 2.4%). Peripheral arterial disease was present in 2.8% (95%CI: 1.9 to 4.1%). CONCLUSIONS/SIGNIFICANCE: Taken together, our data indicate that for the pathogenesis of cardiovascular disease inflammatory processes alone do not suffice and additional factors, probably lifestyle-related, are mandatory.

Adolescent Drug Abuse Diagnosis (ADAD) vs. Health of Nation Outcome Scale for Children and Adolescents (HoNOSCA) in clinical outcome measurement.

BACKGROUND: The Adolescent Drug Abuse Diagnosis (ADAD) and Health of Nation Outcome Scales for Children and Adolescents (HoNOSCA) are both measures of outcome for adolescent mental health services. AIMS: To compare the ADAD with HoNOSCA; to examine their clinical usefulness. METHODS: Comparison of the ADAD and HoNOSCA outcome measures of 20 adolescents attending a psychiatric day care unit. RESULTS: ADAD change was positively correlated with HoNOSCA change. HoNOSCA assesses the clinic's day-care programme more positively than the ADAD. The ADAD detects a group for which the mean score remains unchanged whereas HoNOSCA does not. CONCLUSIONS: A good convergent validity emerges between the two assessment tools. The ADAD allows an evidence-based assessment and generally enables a better subject discrimination than HoNOSCA. HoNOSCA gives a less refined evaluation but is more economic in time and possibly more sensitive to change. Both assessment tools give useful information and enabled the Day-care Unit for Adolescents to rethink the process of care and of outcome, which benefited both the institution and the patients.

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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.

A new neuropsychological instrument measuring effects of age and drugs on fitness to drive: development, reliability, and validity of MedDrive

Background: Current guidelines underline the limitations of existing instruments to assess fitness to drive and the poor adaptability of batteries of neuropsychological tests in primary care settings. Aims: To provide a free, reliable, transparent computer based instrument capable of detecting effects of age or drugs on visual processing and cognitive functions. Methods: Relying on systematic reviews of neuropsychological tests and driving performances, we conceived four new computed tasks measuring: visual processing (Task1), movement attention shift (Task2), executive response, alerting and orientation gain (Task3), and spatial memory (Task4). We then planned five studies to test MedDrive's reliability and validity. Study-1 defined instructions and learning functions collecting data from 105 senior drivers attending an automobile club course. Study-2 assessed concurrent validity for detecting minor cognitive impairment (MCI) against useful field of view (UFOV) on 120 new senior drivers. Study-3 collected data from 200 healthy drivers aged 20-90 to model age related normal cognitive decline. Study-4 measured MedDrive's reliability having 21 healthy volunteers repeat tests five times. Study-5 tested MedDrive's responsiveness to alcohol in a randomised, double-blinded, placebo, crossover, dose-response validation trial including 20 young healthy volunteers. Results: Instructions were well understood and accepted by all senior drivers. Measures of visual processing (Task1) showed better performances than the UFOV in detecting MCI (ROC 0.770 vs. 0.620; p=0.048). MedDrive was capable of explaining 43.4% of changes occurring with natural cognitive decline. In young healthy drivers, learning effects became negligible from the third session onwards for all tasks except for dual tasking (ICC=0.769). All measures except alerting and orientation gain were affected by blood alcohol concentrations. Finally, MedDrive was able to explain 29.3% of potential causes of swerving on the driving simulator. Discussion and conclusions: MedDrive reveals improved performances compared to existing computed neuropsychological tasks. It shows promising results both for clinical and research purposes.

Opioid maintenance therapy in Switzerland: an overview of the Swiss IMPROVE study.

BACKGROUND/AIMS: Switzerland's drug policy model has always been unique and progressive, but there is a need to reassess this system in a rapidly changing world. The IMPROVE study was conducted to gain understanding of the attitudes and beliefs towards opioid maintenance therapy (OMT) in Switzerland with regards to quality and access to treatment. To obtain a "real-world" view on OMT, the study approached its goals from two different angles: from the perspectives of the OMT patients and of the physicians who treat patients with maintenance therapy. The IMPROVE study collected a large body of data on OMT in Switzerland. This paper presents a small subset of the dataset, focusing on the research design and methodology, the profile of the participants and the responses to several key questions addressed by the questionnaires. METHODS: IMPROVE was an observational, questionnaire-based cross-sectional study on OMT conducted in Switzerland. Respondents consisted of OMT patients and treating physicians from various regions of the country. Data were collected using questionnaires in German and French. Physicians were interviewed by phone with a computer-based questionnaire. Patients self-completed a paper-based questionnaire at the physicians' offices or OMT treatment centres. RESULTS: A total of 200 physicians and 207 patients participated in the study. Liquid methadone and methadone tablets or capsules were the medications most commonly prescribed by physicians (60% and 20% of patient load, respectively) whereas buprenorphine use was less frequent. Patients (88%) and physicians (83%) were generally satisfied with the OMT currently offered. The current political framework and lack of training or information were cited as determining factors that deter physicians from engaging in OMT. About 31% of OMT physicians interviewed were ≥60 years old, indicating an ageing population. Diversion and misuse were considered a significant problem in Switzerland by 45% of the physicians. CONCLUSION: The subset of IMPROVE data presented gives a present-day, real-life overview of the OMT landscape in Switzerland. It represents a valuable resource for policy makers, key opinion leaders and drug addiction researchers and will be a useful basis for improving the current Swiss OMT model.

A neuropsychological instrument measuring age-related cerebral decline in older drivers: development, reliability, and validity of MedDrive.

When facing age-related cerebral decline, older adults are unequally affected by cognitive impairment without us knowing why. To explore underlying mechanisms and find possible solutions to maintain life-space mobility, there is a need for a standardized behavioral test that relates to behaviors in natural environments. The aim of the project described in this paper was therefore to provide a free, reliable, transparent, computer-based instrument capable of detecting age-related changes on visual processing and cortical functions for the purposes of research into human behavior in computational transportation science. After obtaining content validity, exploring psychometric properties of the developed tasks, we derived (Study 1) the scoring method for measuring cerebral decline on 106 older drivers aged ≥70 years attending a driving refresher course organized by the Swiss Automobile Association to test the instrument's validity against on-road driving performance (106 older drivers). We then validated the derived method on a new sample of 182 drivers (Study 2). We then measured the instrument's reliability having 17 healthy, young volunteers repeat all tests included in the instrument five times (Study 3) and explored the instrument's psychophysical underlying functions on 47 older drivers (Study 4). Finally, we tested the instrument's responsiveness to alcohol and effects on performance on a driving simulator in a randomized, double-blinded, placebo, crossover, dose-response, validation trial including 20 healthy, young volunteers (Study 5). The developed instrument revealed good psychometric properties related to processing speed. It was reliable (ICC = 0.853) and showed reasonable association to driving performance (R (2) = 0.053), and responded to blood alcohol concentrations of 0.5 g/L (p = 0.008). Our results suggest that MedDrive is capable of detecting age-related changes that affect processing speed. These changes nevertheless do not necessarily affect driving behavior.

Myocardial flow reserve by Rb-82 cardiac PET improves the selection of patients eligible for invasive coronary angiography

Aim: We asked whether myocardial flow reserve (MFR) by Rb-82 cardiac PET improve the selection of patients eligible for invasive coronary angiography (ICA). Material and Methods: We enrolled 26 consecutive patients with suspected or known coronary artery disease who performed dynamic Rb-82 PET/CT and (ICA) within 60 days; 4 patients who underwent revascularization or had any cardiovascular events between PET and ICA were excluded. Myocardial blood flow at rest (rMBF), at stress with adenosine (sMBF) and myocardial flow reserve (MFR=sMBF/rMBF) were estimated using the 1-compartment Lortie model (FlowQuant) for each coronary arteries territories. Stenosis severity was assessed using computer-based automated edge detection (QCA). MFR was divided in 3 groups: G1:MFR<1.5, G2:1.5≤MFR<2 and G3:2≤MFR. Stenosis severity was graded as non-significant (<50% or FFR ≥0.8), intermediate (50%≤stenosis<70%) and severe (≥70%). Correlation between MFR and percentage of stenosis were assessed using a non-parametric Spearman test. Results: In G1 (44 vessels), 17 vessels (39%) had a severe stenosis, 11 (25%) an intermediate one, and 16 (36%) no significant stenosis. In G2 (13 vessels), 2 (15%) vessels presented a severe stenosis, 7 (54%) an intermediate one, and 4 (31%) no significant stenosis. In G3 (9 vessels), 0 vessel presented a severe stenosis, 1 (11%) an intermediate one, and 8 (89%) no significant stenosis. Of note, among 11 patients with 3-vessel low MFR<1.5 (G1), 9/11 (82%) had at least one severe stenosis and 2/11 (18%) had at least one intermediate stenosis. There was a significant inverse correlation between stenosis severity and MFR among all 66 territories analyzed (rho= -0.38, p=0.002). Conclusion: Patients with MFR>2 could avoid ICA. Low MFR (G1, G2) on a vessel-based analysis seems to be a poor predictor of severe stenosis severity. Patients with 3-vessel low MFR would benefit from ICA as they are likely to present a significant stenosis in at least one vessel.

Diagnostic de la maladie coronarienne stable par FFR non invasive, mythe ou réalité [Diagnosis of stable coronary artery disease with non-invasive FFR: myth or reality?].

Decision to revascularize a patient with stable coronary artery disease should be based on the detection of myocardial ischemia. If this decision can be straightforward with significant stenosis or in non-significant stenosis, the decision with intermediate stenosis is far more difficult and require invasive measures of functional impact of coronary stenosis on maximal blood (flow fractional flow reserve=FFR). A recent computer based method has been developed and is able to measure FFR with data acquired during a standard coronary CT-scan (FFRcT). Two recent clinical studies (DeFACTO and DISCOVER-FLOW) show that diagnostic performance of FFRcT was associated with improved diagnostic accuracy versus standard coronary CT-scan for the detection of myocardial ischemia although FFRcT need further development.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.