Schema therapy in adults with autism spectrum disorder: A scoping review.

BACKGROUND: Schema therapy (ST) in adults with autism spectrum disorder (ASD) have gained increasing interest in clinical practice and research. However, to date, there has been no synthesis of the literature on ST as treatment for adults with ASD. Through a scoping review, we aim to summarize the emerging research and literature on ST for adults with ASD. METHODS: A comprehensive literature search of three electronic databases was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Publications were included that examined ST in adults with ASD and non-clinical adults with autistic traits. RESULTS: Systematic searches identified a total of 11 publications, all published since 2014, with the majority being conducted by Dutch and Japanese researchers. Of the 11 publications, 1 described an ST-informed social interaction training, 1 was an ST protocol, 2 described conceptual ST models, 2 were case examples, 2 examined early maladaptive schemas (EMSs) and 3 investigated the effectiveness of ST interventions. In summary, the theoretical exploration, practical examples of the application of ST and research findings with preliminary evidence of ST, EMSs and schema modes (SMs) in adults with ASD point towards the potential of ST for the treatment of adults with ASD. DISCUSSION: The current scoping review highlights preliminary research findings and offers valuable suggestions for clinicians treating adults with ASD. This review underscores the need for development of and research in specialized ST protocols and programmes tailored to adults with ASD with chronic mental conditions, such as personality disorders (PDs).

The Effectiveness of a Motivational Interviewing Treatment for Help-Seeking Problem Gamblers in a Community Organization.

Motivational Interviewing (MI) has been used as an approach to enhance readiness for change and behavior modification in a range of addiction and substance use disorders. Large meta-analyses comparing MI with non-MI interventions point to mixed conclusions about the short-term and long-term effectiveness of MI, with participant, outcome, and delivery factors being important moderators. The current study aimed to assess the immediate (1-2 weeks) and long-term (18 months) effectiveness of MI when delivered at the first point of client contact at a community gambling help counselling service and to investigate whether practitioners' MI adherent and non-adherent behaviors were significant predictors of change in client outcomes. There were 146 individuals presenting for gambling help counselling at an Australian not-for-profit organization who participated in this research. From the overall sample, 55% completed the 18 months follow-up assessment. Multilevel modelling showed a significant reduction in participants' problem gambling severity and psychological distress, which was a small effect size change in the short-term and large effect size change by the 18 months follow-up. While MI adherent practitioner behaviors were not found to be significant predictors of improvement in participants' problem gambling severity and psychological distress, MI non-adherent practitioner behaviors were significant predictors of deterioration in participants' problem gambling severity and psychological distress. This study highlights the importance of excluding MI non-adherent (confront and persuade) practitioner behaviors in order to prevent deterioration in client outcomes.

Accelerating Surgical Simulation Development via OpenSurgSim: Burr Hole Trainer.

The first complete simulation based on OpenSurgSim (OSS) is used as a case study for analyzing how the toolkit can accelerate the development of surgical simulations. The Burr Hole Trainer (BHT) is designed to train non-neurosurgeons to drill holes in the skull to relieve intracranial pressure, and the majority of its simulation functionality is provided by OSS. Based on code size, using OSS cut the development time in half, reduced the necessary size of the development team by two-thirds, and saved millions of US dollars.

Ovalbumin sensitization of guinea pig at birth prevents the ontogenetic decrease in airway smooth muscle responsiveness.

Airway smooth muscle (ASM) displays a hyperresponsive phenotype at young age and becomes less responsive in adulthood. We hypothesized that allergic sensitization, which causes ASM hyperresponsiveness and typically occurs early in life, prevents the ontogenetic loss of the ASM hyperresponsive phenotype. We therefore studied whether neonatal allergic sensitization, not followed by later allergen challenges, alters the ontogenesis of ASM properties. We neonatally sensitized guinea pigs to ovalbumin and studied them at 1 week, 3 weeks, and 3 months (adult). A Schultz-Dale response in isolated tracheal rings confirmed sensitization. The occurrence of inflammation was evaluated in the blood and in the submucosa of large airways. We assessed ASM function in tracheal strips as ability to produce force and shortening. ASM content of vimentin was also studied. A Schultz-Dale response was observed in all 3-week or older sensitized animals. A mild inflammatory process was characterized by eosinophilia in the blood and in the airway submucosa. Early life sensitization had no effect on ASM force generation, but prevented the ontogenetic decline of shortening velocity and the increase in resistance to shortening. Vimentin increased with age in control but not in sensitized animals. Allergic sensitization at birth without subsequent allergen exposures is sufficient to prevent normal ASM ontogenesis, inducing persistence to adulthood of an ASM hyperresponsive phenotype.

Outcomes associated with virtual reality in psychological interventions: where are we now?

The impending commercial release of affordable VR systems is likely to accelerate both the opportunity and demand for VR applications that specifically target psychological conditions. The aim of this study was to conduct a meta-analysis of outcomes associated with VR psychological interventions and to examine the methodological rigour used in these interventions. Literature search was conducted via Ovid, ProQuest Psychology Journals and ScienceDirect (Psychology) databases. Interventions were required to: be published between 1980 to 2014; use a randomised controlled trial design; be published in a scholarly journal; focused primarily on psychological/behavioural intervention; include validated measures; include reported means and standard deviations of outcome measures; and include one group with clinical/subclinical disorders, syndromes or distressing behaviours. Thirty eligible studies were identified. Random effects meta-analysis found an overall moderate effect size for VR interventions. Individual meta-analyses found an overall large effect size against non-intervention wait-lists and an overall moderate effect size against active interventions. No correlation was found between treatment outcomes and methodological rigour. Limitations may include limited study numbers, the use of a single coder, a need for more in-depth analyses of variation in form VR intervention, and omission of presence as a moderating factor. The current review supports VR interventions as efficacious, promising forms of psychological treatment. Use of reporting guidelines such as the CONSORT and CONSORT-EHEALTH statements should promote greater emphasis on methodological rigour, providing a firm foundation for the further development of clinical VR applications.

Arbor: comparative analysis workflows for the tree of life.

We describe our efforts to develop a software package, Arbor, that will enable scientific research in all aspects of comparative biology. This software will enable developmental biologists, geneticists, ecologists, geographers, paleobiologists, educators, and students to analyze diverse types of comparative data at multiple phylogenetic and spatiotemporal scales using an intuitive visual interface. Arbor's user-defined workflows will be exported and shared so that entire analyses can be quickly replicated with new or updated data. Arbor will also be designed to easily and seamlessly expand to include novel analytical tools as they are developed. Here we describe the core components of Arbor, as well as provide details of one proposed test case to illustrate the software's key functionality.

An open-source toolkit for the volumetric measurement of CT lung lesions.

An open source lesion sizing toolkit has been developed with a general architecture for implementing lesion segmentation algorithms and a reference algorithm for segmenting solid and part-solid lesions from lung CT scans. The CT lung lesion segmentation algorithm detects four three-dimensional features corresponding to the lung wall, vasculature, lesion boundary edges, and low density background lung parenchyma. These features form boundaries and propagation zones that guide the evolution of a subsequent level set algorithm. User input is used to determine an initial seed point for the level set and users may also define a region of interest around the lesion. The methods are validated against 18 nodules using CT scans of an anthropomorphic thorax phantom simulating lung anatomy. The scans were acquired under differing scanner parameters to characterize algorithm behavior under varying acquisition protocols. We also validated repeatability using six clinical cases in which the patient was rescanned on the same day (zero volume change). The source code, data sets, and a running application are all provided under an unrestrictive license to encourage reproducibility and foster scientific exchange.

An analysis of early studies released by the Lung Imaging Database Consortium (LIDC).

RATIONALE AND OBJECTIVES: To analyze radiologist lung nodule segmentations in the Lung Imaging Database Consortium (LIDC) database and to apply statistical tools to generate estimates of ground truth. This investigation expands on earlier work by considering a larger number of cases from the LIDC database, and results were generated on a per-nodule basis, as opposed to a per-case basis as was done previously. MATERIALS AND METHODS: We analyzed nodule data drawn from the 41 most recent computed tomography exams released by the LIDC. We combined radiologist segmentations for a given nodule using different consensus schemes: union, intersection, and simultaneous truth and performance level estimation (STAPLE). We also generated three-dimensional models of the manual segmentations using discrete marching cubes to visualize features of the data. RESULTS: Using the union as the consensus scheme produced the greatest number of nodule-positive voxels while using the intersection produced the fewest. Considering only nodules for which all readers agreed on nodule presence, STAPLE computed sensitivity averages for readers one, two, three, and four were 0.91, 0.83, 0.90, and 0.77, respectively. Specificity averages were 0.97, 0.98, 0.97, and 0.97. Considering cases for which there was disagreement about nodule presence, sensitivity results become 0.67, 0.74, 0.60, and 0.37. Specificity results in this case are 0.95, 0.95, 0.95, and 0.98. STAPLE-generated pmaps exhibited probability values tightly grouped below the 0.25 and above the 0.75 probability levels. Three-dimensional models of manually segmented nodules revealed step-artefacts in the segmentation data. CONCLUSIONS: Radiologists often disagree about nodule presence. Ideally, knowing each reader's sensitivity and specificity a priori is preferred for optimal STAPLE results. Knowing these values and developing manual segmentation tools and imaging protocols that mitigate unwanted segmentation features (such as step artefacts) can result in more accurate estimates of ground truth. Furthermore, a computer-aided detection algorithm's performance is a function of the ground truth estimate by which it is scored.

Computer-aided forensics: facial reconstruction.

The 3D reconstruction of facial features from skeletal remains is a key component to the identification of missing persons and victims of violent crime. A comprehensive Computed Tomography (CT) head-scan database is currently being collected which will enable a new approach to forensic facial reconstruction. Using this unique resource, we show how a face space can be tailored to a specific unknown, or questioned skull. A set of database derived estimates of the questioned face is constructed by first computing non-rigid transformations between the known head-scan skulls and the questioned skull followed by application of these transformations to the known head-scan faces. This effectively factors out influences due to skeletal variation. A tailored face space is formed by applying Principal Component Analysis (PCA) to this ensemble of estimates of the questioned face. Thus, the face space is a direct approximation of correlated soft tissue variance indicative of the population. Ours is the first mathematical representation of the face continuum associated with a given skull. Embedded in this space resides the elements needed for recognition.

Part-based local shape models for colon polyp detection.

This paper presents a model-based technique for lesion detection in colon CT scans that uses analytical shape models to map the local shape curvature at individual voxels to anatomical labels. Local intensity profiles and curvature information have been previously used for discriminating between simple geometric shapes such as spherical and cylindrical structures. This paper introduces novel analytical shape models for colon-specific anatomy, viz. folds and polyps, built by combining parts with simpler geometric shapes. The models better approximate the actual shapes of relevant anatomical structures while allowing the application of model-based analysis on the simpler model parts. All parameters are derived from the analytical models, resulting in a simple voxel labeling scheme for classifying individual voxels in a CT volume. The algorithm's performance is evaluated against expert-determined ground truth on a database of 42 scans and performance is quantified by free-response receiver-operator curves.

An analysis of early studies released by the Lung Imaging Database Consortium (LIDC).

Lung cancer remains an ongoing problem resulting in substantial deaths in the United States and the world. Within the United states, cancer of the lung and bronchus are the leading causes of fatal malignancy and make up 32% of the cancer deaths among men and 25% of the cancer deaths among women. Five year survival is low, (14%), but recent studies are beginning to provide some hope that we can increase survivability of lung cancer provided that the cancer is caught and treated in early stages. These results motivate revisiting the concept of lung cancer screening using thin slice multidetector computed tomography (MDCT) protocols and automated detection algorithms to facilitate early detection. In this environment, resources to aid Computer Aided Detection (CAD) researchers to rapidly develop and harden detection and diagnostic algorithms may have a significant impact on world health. The National Cancer Institute (NCI) formed the Lung Imaging Database Consortium (LIDC) to establish a resource for detecting, sizing, and characterizing lung nodules. This resource consists of multiple CT chest exams containing lung nodules that seveal radiologists manually countoured and characterized. Consensus on the location of the nodule boundaries, or even on the existence of a nodule at a particular location in the lung was not enforced, and each contour is considered a possible nodule. The researcher is encouraged to develop measures of ground truth to reconcile the multiple radiologist marks. This paper analyzes these marks to determine radiologist agreement and to apply statistical tools to the generation of a nodule ground truth. Features of the resulting consensus and individual markings are analyzed.

Model-based analysis of local shape for lesion detection in CT scans.

Thin-slice computer tomography provides high-resolution images that facilitate the diagnosis of early-stage lung cancer. However, the sheer size of the CT volumes introduces variability in radiological readings, driving the need for automated detection systems. The main contribution of this paper is a technique for combining geometric and intensity models with the analysis of local curvature for detecting pulmonary lesions in CT. The local shape at each voxel is represented via the principal curvatures of its associated isosurface without explicitly extracting the isosurface. The comparison of these curvatures to values derived from analytical shape models is then used to label the voxel as belonging to particular anatomical structures, e.g., nodules or vessels. The algorithm was evaluated on 242 CT exams with expert-determined ground truth. The performance of the algorithm is quantified by free-response receiver-operator characteristic curves, as well as by its potential for improvement in radiologist sensitivity.