Implementation of Virtual Reality to Parent-Child Interaction Therapy for Enhancement of Positive Parenting Skills: Study Protocol for Single-Case Experimental Design With Multiple Baselines.

BACKGROUND: Disruptive behavior is a common reason for young children to be referred to mental health care services worldwide. Research indicates that treatments for child disruptive behavior where parents are the primary agents of change are most impactful. Parent-Child Interaction Therapy (PCIT) is an effective parent management training program currently implemented in therapeutic settings within the Netherlands. Ongoing research into improving the effectiveness of PCIT is being done within these settings. To further promote the key elements of PCIT, this study focuses on creating the opportunity for parents to practice positive parenting skills more outside of the clinical setting by adding virtual reality (VR) as an additional homework element. PCIT has shown to make impactful long-term improvements in parental warmth, responsiveness, and the parent-child relationship. Through VR, parents practice the taught parenting skills out loud in the comfort of their own homes in VR scenarios. We expect that VR addition will innovatively increase the effectiveness of PCIT. OBJECTIVE: This study aimed to evaluate the added value of VR to PCIT by using a multiple baseline single-case experimental design (SCED). We expect to find that PCIT-VR will ameliorate positive parenting skills. By implementing the VR element, we secondarily expected that meeting the skill criteria will be achieved sooner, treatment completion rates will increase, and the parent-child relationship will be better, whereas parental stress and child disruptive behavior will decrease. METHODS: A total of 15 children (aged 2-7 years) with disruptive behavior and their parents will be followed throughout the PCIT-VR treatment. Using a multiple baseline SCED with 3 phases, 15 families will fill out questionnaires weekly, in addition to having pre- and posttreatment and follow-up measurements to monitor their positive parenting skills, child disruptive behavior, parenting stress, and VR progress. Moreover, quantitative information and qualitative interviews will be analyzed visually and statistically and summarized to provide a complete picture of experiences. RESULTS: As of February 2021, 6 families have been enrolled in the study at the moment of submission. Data collection is projected to be completed in 2023. Quantitative and qualitative results are planned to be published in peer-reviewed journals, as well as being presented at national and international conferences. CONCLUSIONS: The SCED-with its phased design, randomization, and the opportunity to replicate and assess both individual and group treatment effects-and adaptability of the VR technology are the strengths of the study. The risks of increased type I errors, maturation effects, or technological failure will be mitigated with the right statistical support. This study aims to magnify the scope of the treatment through additional skill training, ultimately in support of routinely implementing VR within PCIT. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34120.

Multiscale analysis on otolith structural features reveals differences in ontogenesis and sex in Merluccius merluccius in the western Adriatic Sea.

Otolith biomineralization results from biochemical processes regulated by the interaction of internal (physiological) and external (environmental) factors which lead to morphological and ultrastructural variability at intra- and interspecific levels. The aim of this study was to conduct a multi-scale analysis of the sagittal otoliths of the Merlucius merlucius (European hake) from the western Adriatic Sea in order to correlate otolith features with fish ontogeny and sex. We show that otoliths of sexually undifferentiated (non-sexed) individuals having a fish body total length (TL) less than 15 cm had faster growth in length, width, area, perimeter, volume and weight and a higher amount of organic matrix compared with otoliths of sexually differentiated individuals (females and males) having a fish size range of 15-50 cm. Most importantly, with increasing fish TL, female saccular otoliths contained a higher number of protuberances and rougher surface compared with male specimens, which showed more uniform mean curvature density. The differences between females and males discovered in this study could be associated with fish hearing adaptation to reproductive behavioural strategies during the spawning season. The outcomes of this research provide insights on how size and sex-related variations in otolith features may be affected by fish ecological and behavioural patterns.

Integrated support for medical image analysis methods: from development to clinical application.

Computer-aided image analysis is becoming increasingly important to efficiently and safely handle large amounts of high-resolution images generated by advanced medical imaging devices. The development of medical image analysis (MIA) software with the required properties for clinical application, however, is difficult and labor-intensive. Such development should be supported by systems providing scalable computational capacity and storage space, as well as information management facilities. This paper describes the properties of distributed systems to support and facilitate the development, evaluation, and clinical application of MIA methods. First, the main characteristics of existing systems are presented. Then, the phases in a method's lifecycle are analyzed (development, parameter optimization, evaluation, clinical routine), identifying the types of users, tasks, and related computational issues. A scenario is described where all tasks are performed with the aid of computational tools integrated into an ideal supporting environment. The requirements for this environment are described, proposing a grid-oriented paradigm that emphasizes virtual collaboration among users, pieces of software, and devices distributed among geographically dispersed healthcare, research, and development enterprises. Finally, the characteristics of the existing systems are analyzed according to these requirements. The proposed requirements offer a useful framework to evaluate, compare, and improve the existing systems that support MIA development.

Towards a virtual laboratory for FMRI data management and analysis.

Functional Magnetic Resonance Imaging (fMRI) is a popular tool used in neuroscience research to study brain activation due to motor or cognitive stimulation. In fMRI studies, large amounts of data are acquired, processed, compared, annotated, shared by many users and archived for future reference. As such, fMRI studies have characteristics of applications that can benefit from grid computation approaches, in which users associated with virtual organizations can share high performance and large capacity computational resources. In the Virtual Laboratory for e-Science (VL-e) Project, initial steps have been taken to build a grid-enabled infrastructure to facilitate data management and analysis for fMRI. This article presents our current efforts for the construction of this infrastructure. We start with a brief overview of fMRI, and proceed with an analysis of the existing problems from a data management perspective. A description of the proposed infrastructure is presented, and the current status of the implementation is described with a few preliminary conclusions.

A grid architecture for medical applications.

Grid technology can provide medical organisations with powerful tools through which they can gain coordinated access to computational resources that hitherto where inaccessible to them. This paper discusses how several classes of medical applications could benefit from the use of Grid technology. We concentrate on applications that were put forward by partners in the Dutch VL-e project. After describing the difficulties related to the realization of such applications without making use of the Grid, we describe an architecture that allows the applications to use Grid resources. We demonstrate how this architecture can be integrated into existing systems to provide flexible and transparent access to Grid services and show performance results of a test case.

The technologically integrated oncosimulator: combining multiscale cancer modeling with information technology in the in silico oncology context.

This paper outlines the major components and function of the technologically integrated oncosimulator developed primarily within the Advancing Clinico Genomic Trials on Cancer (ACGT) project. The Oncosimulator is defined as an information technology system simulating in vivo tumor response to therapeutic modalities within the clinical trial context. Chemotherapy in the neoadjuvant setting, according to two real clinical trials concerning nephroblastoma and breast cancer, has been considered. The spatiotemporal simulation module embedded in the Oncosimulator is based on the multiscale, predominantly top-down, discrete entity-discrete event cancer simulation technique developed by the In Silico Oncology Group, National Technical University of Athens. The technology modules include multiscale data handling, image processing, invocation of code execution via a spreadsheet-inspired environment portal, execution of the code on the grid, and the visualization of the predictions. A refining scenario for the eventual coupling of the oncosimulator with immunological models is also presented. Parameter values have been adapted to multiscale clinical trial data in a consistent way, thus supporting the predictive potential of the oncosimulator. Indicative results demonstrating various aspects of the clinical adaptation and validation process are presented. Completion of these processes is expected to pave the way for the clinical translation of the system.

Combining epidemiological and genetic networks signifies the importance of early treatment in HIV-1 transmission.

Inferring disease transmission networks is important in epidemiology in order to understand and prevent the spread of infectious diseases. Reconstruction of the infection transmission networks requires insight into viral genome data as well as social interactions. For the HIV-1 epidemic, current research either uses genetic information of patients' virus to infer the past infection events or uses statistics of sexual interactions to model the network structure of viral spreading. Methods for a reliable reconstruction of HIV-1 transmission dynamics, taking into account both molecular and societal data are still lacking. The aim of this study is to combine information from both genetic and epidemiological scales to characterize and analyse a transmission network of the HIV-1 epidemic in central Italy.We introduce a novel filter-reduction method to build a network of HIV infected patients based on their social and treatment information. The network is then combined with a genetic network, to infer a hypothetical infection transmission network. We apply this method to a cohort study of HIV-1 infected patients in central Italy and find that patients who are highly connected in the network have longer untreated infection periods. We also find that the network structures for homosexual males and heterosexual populations are heterogeneous, consisting of a majority of 'peripheral nodes' that have only a few sexual interactions and a minority of 'hub nodes' that have many sexual interactions. Inferring HIV-1 transmission networks using this novel combined approach reveals remarkable correlations between high out-degree individuals and longer untreated infection periods. These findings signify the importance of early treatment and support the potential benefit of wide population screening, management of early diagnoses and anticipated antiretroviral treatment to prevent viral transmission and spread. The approach presented here for reconstructing HIV-1 transmission networks can have important repercussions in the design of intervention strategies for disease control.