Making Professional Decisions in Research: Measurement and Key Predictors

The professional decision-making in research (PDR) measure was administered to 400 National Institutes of Health (NIH)-funded and industry-funded investigators, along with measures of cynicism, moral disengagement, compliance disengagement, impulsivity, work stressors, knowledge of responsible conduct of research (RCR), and socially desirable response tendencies. Negative associations were found for the PDR and measures of cynicism, moral disengagement, and compliance disengagement, while positive associations were found for the PDR and RCR knowledge and positive urgency, an impulsivity subscale. PDR scores were not related to socially desirable responding, or to measures of work stressors and the remaining impulsivity subscales. In a multivariate logistic regression analysis, lower moral disengagement scores, higher RCR knowledge, and identifying the United States as one’s nation of origin emerged as key predictors of stronger performance on the PDR. The implications of these findings for understanding the measurement of decision-making in research and future directions for research and RCR education are discussed.     

Biomechanics-based active control of bedding support properties and its influence on sleep

Proper body support plays an import role in the recuperation of our body during sleep. Therefore, this study uses an automatically adapting bedding system that optimises spinal alignment throughout the night by altering the stiffness of eight comfort zones. The aim is to investigate the influence of such a dynamic sleep environment on objective and subjective sleep parameters. The bedding system contains 165 sensors that measure mattress indentation. It also includes eight actuators that control the comfort zones. Based on the measured mattress indentation, body movements and posture changes are detected. Control of spinal alignment is established by fitting personalized human models in the measured indentation. A total of 11 normal sleepers participated in this study. Sleep experiments were performed in a sleep laboratory where subjects slept three nights: a first night for adaptation, a reference night and an active support night (in counterbalanced order). Polysomnographic measurements were recorded during the nights, combined with questionnaires aiming at assessing subjective information. Subjective information on sleep quality, daytime quality and perceived number of awakenings shows significant improvements during the active support (ACS) night. Objective results showed a trend towards increased slow wave sleep. On the other hand, it was noticed that % N1-sleep was significantly increased during ACS night, while % N2-sleep was significantly decreased. No prolonged N1 periods were found during or immediately after steering.     

The General Segmented Distribution

We develop a distribution supported on a bounded interval with a probability density function that is constructed from any finite number of linear segments. With an increasing number of segments, the distribution can approach any continuous density function of arbitrary form. The flexibility of the distribution makes it a useful tool for various modeling purposes. We further demonstrate that it is capable of fitting data with considerable precision—outperforming distributions recommended by previous studies. We suggest that this distribution is particularly effective in fitting data with sufficient observations that are skewed and multimodal.     

Gambling Participation and Social Support Among Older Adults: A Longitudinal Community Study

The purpose of this preliminary study was to examine associations between leaving home to engage in bingo or gambling activity and indices of physical and mental health and social support among a representative community cohort of 1016 elderly people. Cross-sectional and longitudinal data gathered from a prospective epidemiological study in a rural, low socio-economic status, area of Pennsylvania was employed. The cohort had a mean age of 78.8 (SD = 5.1) (range 71–97) and participated in three consecutive biennial waves of data collection. Nearly half (47.7) of the cohort reported gambling. To predict gambling, the independent variables included age, sex, education, employment, social support, depressive symptoms, self-rated health, alcohol use, cigarette use, and cognitive functioning. In cross-sectional, univariate analyses, gambling was associated with younger age, sex (male), fewer years of education, greater social support, lower depression scores, better self-rated health, alcohol use in the past year, and higher cognitive functioning. In a cross-sectional multiple regression model, younger age, greater social support, and alcohol use in the past year remain strongly and independently associated with gambling activity. Longitudinally, age, sex, social support, alcohol use, and gambling are predictive of future gambling activity. The results revealed that gambling may offer a forum of social support to older adults who are often isolated as they age.     

Modeling material stress using integrated Gaussian Markov random fields

The equations of a physical constitutive model for material stress within tantalum grains were solved numerically using a tetrahedrally meshed volume. The resulting output included a scalar vonMises stress for each of the more than 94,000 tetrahedra within the finite element discretization. In this paper, we define an intricate statistical model for the spatial field of vonMises stress which uses the given grain geometry in a fundamental way. Our model relates the three-dimensional field to integrals of latent stochastic processes defined on the vertices of the one- and two-dimensional grain boundaries. An intuitive neighborhood structure of the said boundary nodes suggested the use of a latent Gaussian Markov random field (GMRF). However, despite the potential for computational gains afforded by GMRFs, the integral nature of our model and the sheer number of data points pose substantial challenges for a full Bayesian analysis. To overcome these problems and encourage efficient exploration of the posterior distribution, a number of techniques are now combined: parallel computing, sparse matrix methods, and a modification of a block update strategy within the sampling routine. In addition, we use an auxiliary variables approach to accommodate the presence of outliers in the data.     

Automatic sleep stage classification based on easy to register signals as a validation tool for ergonomic steering in smart bedding systems

Ergonomic sleep studies benefit from long-term monitoring in the home environment to cope with daily variations and habituation effects. Polysomnography allows to asses sleep accurately, but is costly, time-consuming and possibly disturbing for the sleeper. Actigraphy is cheap and user friendly, but for many studies lacks accuracy and detailed information. This proof-of-concept study investigates Least-Squares Support Vector Machines as a tool for automatic sleep stage classification (Wake-N1-Rem to N2-N3 separation), using automatic trainingset-specific filtered features as derived from three easy to register signals, namely heart rate, breathing rate and movement. The algorithms are trained and validated using 20 nights out of a 600 night database from over 100 different healthy persons. Different training and test set strategies were analyzed leading to different results. The more person-specific the training nights to the test nights, the better the classification accuracy as validated against the hypnograms scored by experts from the full polysomnograms. In the limit of complete person-specific training, the accuracy of the algorithm on the test set reached 94%. This means that this algorithm could serve its use in long-term monitoring sleep studies in the home environment, especially when prior person-specific polysomnographic training is performed.     

Guidelines for Conducting a Victim-Sensitive Interview

Victim sensitive interviews allow the adult investigator to gather vital facts from a child. Within these interviews, the investigator is provided with an opportunity to elicit responses from the child regarding allegations that have taken place. These allegations often have many origins and may involve sexual impropriety, abuse, taunting, and torture of a physical nature, verbal nature, or both. The purpose of this article is to provide standardized guidelines that can assist individuals from various occupational fields in conducting victim sensitive interviews. The standardized guidelines provided offer an assemblage of general principles that have consistently appeared within literature as well as in manuals provided by various jurisdictions. These guidelines refer to a practice of conduct that is recommended; however, variance with implementation is allowed. It is assumed that the reader brings a level of clinical experience to the material provided in this article.