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Pharmaceutical Drugs as well as Organic Restorative Goods for the Treatment of Diabetes type 2 symptoms Mellitus.
BACKGROUND Face-to-face individual cognitive behavioral therapy (CBT) and internet-based CBT (ICBT) without videoconferencing are known to have long-term effectiveness for obsessive-compulsive disorder (OCD), panic disorder (PD), and social anxiety disorder (SAD). However, videoconference-delivered CBT (VCBT) has not been investigated regarding its long-term effectiveness and cost-effectiveness. OBJECTIVE The purpose of this study was to investigate the long-term effectiveness and cost-effectiveness of VCBT for patients with OCD, PD, or SAD in Japan via a 1-year follow-up to our previous 16-week single-arm study. METHODS Written informed consent was obtained from 25 of 29 eligible patients with OCD, PD, and SAD who had completed VCBT in our clinical trial. Participants were assessed at baseline, end of treatment, and at the follow-up end points of 3, 6, and 12 months. Outcomes were the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Panic Disorder Severity Scale (PDSS), Liebowitz Social Anxiety Scale (LSAS), 89,500 ($1723, €1579, and £1354) calculated based on willingness to pay in Japan. CONCLUSIONS VCBT was a cost-effective way to effectively treat Japanese patients with OCD, PD, or SAD. TRIAL REGISTRATION University Hospital Medical Information Network Clinical Trials Registry UMIN000026609; https//upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000030495. ©Kazuki Matsumoto, Sayo Hamatani, Kazue Nagai, Chihiro Sutoh, Akiko Nakagawa, Eiji Shimizu. Originally published in JMIR Mental Health (http//mental.jmir.org), 23.04.2020.BACKGROUND Web-based developmental surveillance programs may be an innovative solution to improving the early detection of childhood developmental difficulties, especially within disadvantaged populations. OBJECTIVE This review aimed to identify the acceptability and effectiveness of web-based developmental surveillance programs for children aged 0 to 6 years. METHODS A total of 6 databases and gray literature were searched using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-informed protocol. Data extraction included variables related to health equity. RESULTS In total, 20 studies were identified. Most papers implemented web-based versions of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up screener for autism spectrum disorder or Parent Evaluation of Developmental Status screeners for broad developmental delay. Caregivers and practitioners indicated a preference for web-based screeners, primarily for user-friendliness, improved follow-up accuracy, time, and training efficiencies. CONCLUSIONS Although evidence is limited as to the necessity of web- versus face-to-face-based developmental screening, there are clear efficiencies in its use. TRIAL REGISTRATION PROSPERO CRD42019127894; https//www.crd.york.ac.uk/prospero/display_record.php?RecordID=127894. ©Jess Baker, Jane Kohlhoff, Se-Inyenede Onobrakpor, Sue Woolfenden, Rebecca Smith, Constanze Knebel, Valsamma Eapen. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 23.04.2020.BACKGROUND Health education emerged as an important intervention for improving the awareness and self-management abilities of chronic disease patients. The development of information technologies has changed the form of patient educational materials from traditional paper materials to electronic materials. To date, the amount of patient educational materials on the internet is tremendous, with variable quality, which makes it hard to identify the most valuable materials by individuals lacking medical backgrounds. OBJECTIVE The aim of this study was to develop a health recommender system to provide appropriate educational materials for chronic disease patients in China and evaluate the effect of this system. METHODS A knowledge-based recommender system was implemented using ontology and several natural language processing (NLP) techniques. The development process was divided into 3 stages. In stage 1, an ontology was constructed to describe patient characteristics contained in the data. In stage 2, an algorithent original data to the ontology vector space. The recommender system was implemented as a separate Web service connected with patients' smartphones. According to the evaluation results, our system can achieve a macro precision up to 0.970 for the top 1 recommendation and an overall MAP score up to 0.628. CONCLUSIONS This study demonstrated that a knowledge-based health recommender system has the potential to accurately recommend educational materials to chronic disease patients. Traditional NLP techniques combined with improvement strategies for specific language and domain proved to be effective for improving system performance. One direction for future work is to explore the effect of such systems from the perspective of patients in a practical setting. ©Zheyu Wang, Haoce Huang, Liping Cui, Juan Chen, Jiye An, Huilong Duan, Huiqing Ge, Ning Deng. Originally published in JMIR Medical Informatics (http//medinform.jmir.org), 23.04.2020.BACKGROUND There is a strong link between sleep and major depression; however, the causal relationship remains unclear. In particular, it is unknown whether changes in depression core symptoms precede or follow changes in sleep, and whether a longer or shorter sleep duration is related to improvements of depression core symptoms. OBJECTIVE The aim of this study was to investigate temporal associations between sleep and depression in patients suffering from major depressive disorder using an idiographic research approach. METHODS Time-series data of daily sleep assessments (time in bed and total sleep time) and self-rated depression core symptoms for an average of 173 days per patient were analyzed in 22 patients diagnosed with recurrent major depressive disorder using a vector autoregression model. Granger causality tests were conducted to test for possible causality. Impulse response analysis and forecast error variance decomposition were performed to quantify the temporal mutual impact of sleep and depression. RESULTS Overall, 11 positive and 5 negative associations were identified between time in bed/total sleep time and depression core symptoms. Granger analysis showed that time in bed/total sleep time caused depression core symptoms in 9 associations, whereas this temporal order was reversed for the other 7 associations. Most of the variance (10%) concerning depression core symptoms could be explained by time in bed. Changes in sleep or depressive symptoms of 1 SD had the greatest impact on the other variable in the following 2 to 4 days. CONCLUSIONS Longer rather than shorter bedtimes were associated with more depression core symptoms. However, the temporal orders of the associations were heterogeneous. ©Noah Lorenz, Christian Sander, Galina Ivanova, Ulrich Hegerl. DLin-KC2-DMA Originally published in JMIR Mental Health (http//mental.jmir.org), 23.04.2020.BACKGROUND Assistive technologies have become more important owing to the aging population, especially when they foster healthy behaviors. Because of their natural interface, virtual agents are promising assistants for people in need of support. To engage people during an interaction with these technologies, such assistants need to match the users´ needs and preferences, especially with regard to social outcomes. OBJECTIVE Prior research has already determined the importance of an agent's appearance in a human-agent interaction. As seniors can particularly benefit from the use of virtual agents to maintain their autonomy, it is important to investigate their special needs. However, there are almost no studies focusing on age-related differences with regard to appearance effects. METHODS A 2×4 between-subjects design was used to investigate the age-related differences of appearance effects in a human-agent interaction. In this study, 46 seniors and 84 students interacted in a health scenario with a virtual agebonding when interacting with the cartoon-stylized humanoid agent. CONCLUSIONS In health-related interactions, target group-related differences exist with regard to a virtual assistant's appearance. When elderly individuals are the target group, a humanoid virtual assistant might trigger specific social responses and be evaluated more positively at least in short-term interactions. ©Carolin Straßmann, Nicole C Krämer, Hendrik Buschmeier, Stefan Kopp. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 23.04.2020.Novel treatment options for eating disorders (EDs) are critically needed to enhance treatment outcomes and reduce the rates of treatment dropouts. On average, only 50% of individuals receiving evidence-based care remit, whereas 24% drop out before treatment completion. One particularly promising direction involves integrating virtual reality (VR) with existing evidence-based treatments (EBTs) such as cue exposure therapy (CET). Across psychiatric disorders, VR-based interventions are demonstrating at least preliminary efficacy and noninferiority to traditional treatments. Furthermore, VR technology has become increasingly portable, resulting in improved acceptance, increased access, and reductions in cost. However, more efficient research processes may be needed to uncover the potential benefits of these rapid technological advances. This viewpoint paper reviews existing empirical support for integrating VR with EBTs (with a focus on its use with EDs) and proposes key next steps to more rapidly bring this innovative technology-based intervention into real-world clinic settings, as warranted. VR-CET for EDs is used to illustrate a suggested process for developing such treatment enhancements. We recommend following a deployment-focused model of intervention development and testing to enable rapid implementation of robust, practice-ready treatments. In addition, our review highlights the need for a comprehensive clinical protocol that supports clinicians and researchers in the implementation and testing of VR-CET and identifies key missing protocol components with rationale for their inclusion. Ultimately, this work may lead to a more complete understanding of the full potential of the applications and integrations of VR into mental health care globally. ©Theresa Brown, Emily Nauman Vogel, Sarah Adler, Cara Bohon, Kim Bullock, Katherine Nameth, Giuseppe Riva, Debra L Safer, Cristin D Runfola. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 23.04.2020.BACKGROUND Social media is an integral part of human social life. More than 90% of young people use social media daily. Current theories, models, and measures are primarily based on face-to-face conceptions, leaving research out of sync with current social trends. This may lead to imprecise diagnoses and predictions. OBJECTIVE To develop a theoretically based empirical model of current social interfaces to inform relevant measures. METHODS A three-stage, qualitative, data-collection approach included anonymous individual Post-it notes, three full-class discussions, and 10 focus groups to explore 82 adolescents' relational practices. Data analysis followed a meaning-condensation procedure and a field-correspondence technique. RESULTS We developed an empirical model that categorizes adolescents' social interactions into five experiential positions. Four positions result from trajectories relating to social media and face-to-face social interaction. Positions are described by match or mismatch dynamics between preferred and actual social platforms used.
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