Intraduodenal sarcoma recurrence of retroperitoneal origin: an unusual cause for a duodenal obstruction.

Soft tissue sarcomas are uncommon tumors, and intraduodenal soft tissue sarcoma manifestation is even more rare. Only three cases of intraduodenal sarcomas have been reported in the literature thus far. Here, we report a case of an intraduodenal recurrence of a retroperitoneal sarcoma causing bowel obstruction. This unusual recurrence pattern likely relates to the patient's previous resection and radiation treatment, and highlights the benefits, limitations and follow-up strategies after multimodality treatment

Approaches to Sample Size Determination for Multivariate Data:Applications to PCA and PLS-DA of Omics Data

Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA.</p

Anxiously Anticipating! A Parallel Journey to an Art and Equestrian Camp for Children with Disabilities

In many communities, there are few opportunities for children with disabilities to participate in engaging summer camp experiences. This poster will highlight one successful endeavor that provided this much-needed opportunity to children with disabilities. Little has been explored regarding how parents go about preparing their children for the camp experience that is to come; and few studies have documented the planning and preparation by camp staff. This presentation will explore one family’s efforts to prepare and support a child’s first venture into organized summer programming. At the same time, this presentation will detail the preparation (and surprising level of anxiety) of the staff that provided the camp as a service learning project. After careful selection and training, undergraduate students became day camp counselors for an immersive service learning experience where they planned and implemented a two-week day camp for schoolchildren with mild disabilities. Campers, counselor, and volunteers alike learned valuable social and academic enrichment skills during the camp experience, but did report mild to moderate anxiety associated with anticipating their involvement in the project. During the months preceding camp, journal and diary entries detail the ups and downs of camp preparation as well as the actual daily camp experience, describing the growth that occurred in both the campers and the counselors. These journal entries and practical suggestions for camp planning and camper preparation give voice to the camp experience through two perspectives – the camper/parent and the camp team. Service learning can take many forms and serve diverse purposes and populations. This poster documents the process of combining service learning with the provision of summer camp experiences for underserved populations - an exciting venture! This particular service learning experience – an equestrian, art, and science camp – enabled college students to learn new skills, enhance leadership abilities, develop important personal attributes, and widen their understandings of diverse populations. The same project enabled this camper, and many others, to make new friends, develop recreational competencies, and take risks in a safe environment. Perhaps, though, the greatest benefit to all was that intangible, mysterious experience that everyone needs to discover from time to time – fun

Comparison of Estimation Procedures for Multilevel AR(1) Models

To estimate a time series model for multiple individuals, a multilevel model may be used.In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo.Furthermore, we examine the difference between modeling fixed and random individual parameters.To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25), the number of individuals per sample (10 or 25), the mean of the autocorrelation (-0.6 to 0.6 inclusive, in steps of 0.3) and the standard deviation of the autocorrelation (0.25 or 0.40).We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators.The fixed estimators profit slightly more from a higher number of time points than the random estimators.When possible, random estimation is preferred to fixed estimation.The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates).Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures

A tutorial on regression-based norming of psychological tests with GAMLSS

A norm-referenced score expresses the position of an individual test taker in the reference population, thereby enabling a proper interpretation of the test score. Such normed scores are derived from test scores obtained from a sample of the reference population. Typically, multiple reference populations exist for a test, namely when the norm-referenced scores depend on individual characteristic(s), as age (and sex). To derive normed scores, regression-based norming has gained large popularity. The advantages of this method over traditional norming are its flexible nature, yielding potentially more realistic norms, and its efficiency, requiring potentially smaller sample sizes to achieve the same precision. In this tutorial, we introduce the reader to regression-based norming, using the generalized additive models for location, scale, and shape (GAMLSS). This approach has been useful in norm estimation of various psychological tests. We discuss the rationale of regression-based norming, theoretical properties of GAMLSS and their relationships to other regression-based norming models. Based on 6 steps, we describe how to: (a) design a normative study to gather proper normative sample data; (b) select a proper GAMLSS model for an empirical scale; (c) derive the desired normed scores for the scale from the fitted model, including those for a composite scale; and (d) visualize the results to achieve insight into the properties of the scale. Following these steps yields regression-based norms with GAMLSS for a psychological test, as we illustrate with normative data of the intelligence test IDS-2. The complete R code and data set is provided as online supplemental material

Migration aspirations and migration cultures:A case study of Ukrainian migration towards the European Union

An abundant body of research focused on macrolevel, mesolevel, and microlevel factors explaining why individuals move across international borders. In this paper, we aim to complement the existing literature by exploring how, within a single country, mesolevel factors differently impact migration aspirations, focusing on a case study of Ukraine. We particularly focus on how migration aspirations of individuals in two different regions can be explained by their international social networks with family members, on the one hand, and with friends, on the other. Furthermore, we explore whether regional migration characteristics play a role, as well as the interaction of such characteristics with individuals' frequency of contact with transnational networks. Our analyses are based on the EUMAGINE project and suggest that the interplay between regional migration characteristics and transnational social contact are key for explainingthe decline of migration systems over time

Prevalence of Defecation Disorders and their Symptoms is Comparable in Children and Young Adults:Cross-Sectional Study

Purpose: We aimed to compare the prevalence rates and associated symptoms of constipation and fecal incontinence in children and young adults and evaluate how these patient groups cope with these disorders. Methods: A cross-sectional study was performed in which 212 children (8-17 years) and 149 young adults (18-29 years) from the general Dutch population completed a questionnaire about defecation disorders. Results: Constipation occurred in 15.6% of children and 22.8% of young adults (p=0.55), while the prevalence of fecal incontinence was comparable between groups (7%, p=0.91). The symptoms associated with constipation occurred as often in children as in young adults, while most fecal incontinence symptoms occurred more often in young adults. Approximately 43% of children had constipation for more than 5 years, while 26% of young adults experienced constipation since childhood. Only 27% of constipated children and 21% of constipated young adults received treatment (mostly laxatives). For fecal incontinence, 13% of children and 36% of young adults received treatment (mostly antidiarrheal medications or incontinence pads). Conclusion: In contrast to the general belief, the prevalence of defecation disorders and associated symptoms seem to be comparable in children and young adults. Only a few people with defecation disorders receive adequate treatment

Trajectories of Emotion Recognition Training in Virtual Reality and Predictors of Improvement for People with a Psychotic Disorder

Meta-analyses have found that social cognition training (SCT) has large effects on the emotion recognition ability of people with a psychotic disorder. Virtual reality (VR) could be a promising tool for delivering SCT. Presently, it is unknown how improvements in emotion recognition develop during (VR-)SCT, which factors impact improvement, and how improvements in VR relate to improvement outside VR. Data were extracted from task logs from a pilot study and randomized controlled trials on VR-SCT (n = 55). Using mixed-effects generalized linear models, we examined the: (a) effect of treatment session (1-5) on VR accuracy and VR response time for correct answers; (b) main effects and moderation of participant and treatment characteristics on VR accuracy; and (c) the association between baseline performance on the Ekman 60 Faces task and accuracy in VR, and the interaction of Ekman 60 Faces change scores (i.e., post-treatment - baseline) with treatment session. Accounting for the task difficulty level and the type of presented emotion, participants became more accurate at the VR task (b = 0.20, p &lt; 0.001) and faster (b = -0.10, p &lt; 0.001) at providing correct answers as treatment sessions progressed. Overall emotion recognition accuracy in VR decreased with age (b = -0.34, p = 0.009); however, no significant interactions between any of the moderator variables and treatment session were found. An association between baseline Ekman 60 Faces and VR accuracy was found (b = 0.04, p = 0.006), but no significant interaction between difference scores and treatment session. Emotion recognition accuracy improved during VR-SCT, but improvements in VR may not generalize to non-VR tasks and daily life.</p