Six children ranging in age from 2 to 10 years who harbored deep benign astrocytomas were operated upon using a computer- and robot-assisted system. A radical excision was achieved in all cases with no significant morbidity nor any mortality. The system consists of an interactive, three-dimensional display of computed tomographic image contours and digitized cerebral angiograms taken using the Brown-Roberts-Wells stereotactic frame. The surgical retractor is held and manipulated using a PUMA 200 robot. The position and orientation of the surgical retractor is displayed on the three-dimensional display. Preoperative planning and simulation are important features of this system. Movement of the brain after removal of the tumor and cerebrospinal fluid is substantial, so the tumor removal is based on visually defined margins. Enhanced computer graphics and robotic devices are important adjuncts to neurosurgical procedures and will find increasing use in the future.

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Cognitive behavioral therapy (CBT) is one of the most effective psychotherapy modalities used to treat depression and anxiety disorders. Homework is an integral component of CBT, but homework compliance in CBT remains problematic in real-life practice. The popularization of the mobile phone with app capabilities (smartphone) presents a unique opportunity to enhance CBT homework compliance; however, there are no guidelines for designing mobile phone apps created for this purpose. Existing literature suggests 6 essential features of an optimal mobile app for maximizing CBT homework compliance: (1) therapy congruency, (2) fostering learning, (3) guiding therapy, (4) connection building, (5) emphasis on completion, and (6) population specificity. We expect that a well-designed mobile app incorporating these features should result in improved homework compliance and better outcomes for its users.

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BackgroundAnxiety and mood disorders are the most common mental illnesses, peaking during adolescence and affecting approximately 25% of Canadians aged 14-17 years. If not successfully treated at this age, they often persist into adulthood, exerting a great social and economic toll. Given the long-term impact, finding ways to increase the success and cost-effectiveness of mental health care is a pressing need. Cognitive behavior therapy (CBT) is an evidence-based treatment for mood and anxiety disorders throughout the lifespan. Mental health technologies can be used to make such treatments more successful by delivering them in a format that increases utilization. Young people embrace technologies, and many want to actively manage their mental health. Mobile software apps have the potential to improve youth adherence to CBT and, in turn, improve outcomes of treatment.ObjectiveThe purpose of this project is to improve homework adherence in CBT for youth anxiety and/or depression. The objectives are to (1) design and optimize the usability of a mobile app for delivering the homework component of CBT for youth with anxiety and/or depression, (2) assess the app’s impact on homework completion, and (3) implement the app in CBT programs. We hypothesize that homework adherence will be greater in the app group than in the no-app group.MethodsPhase 1: exploratory interviews will be conducted with adolescents and therapists familiar with CBT to obtain views and perspectives on the requirements and features of a usable app and the challenges involved in implementation. The information obtained will guide the design of a prototype. The prototype will be optimized via think-aloud procedures involving an iterative process of evaluation, modification, and re-evaluation, culminating in a fully functional version of the prototype that is ready for optimization in a clinical context. Phase 2: a usability study will be conducted to optimize the prototype in the context of treatment at clinics that provide CBT treatment for youth with anxiety and/or depression. This phase will result in a usable app that is ready to be tested for its effectiveness in increasing homework adherence. Phase 3: a pragmatic clinical trial will be conducted at several clinics to evaluate the impact of the app on homework adherence. Participants in the app group are expected to show greater homework completion than those in the no-app group.ResultsPhase 3 will be completed by September 2019.ConclusionsThe app will be a unique adjunct to treatment for adolescents in CBT, focusing on both anxiety and depression, developed in partnership with end users at every stage from design to implementation, customizable for different cognitive profiles, and designed with depression symptom tracking measures for youth made interoperable with electronic medical records.

Background: Premenstrual mood symptoms are considered common in women, but such prevailing attitudes are shaped by social expectations about gender, emotionality and hormonal influences. There are few prospective, community studies of women reporting mood data from all phases of the menstrual cycle (MC). We aimed (i) to analyze daily mood data over 6 months for MC phase cyclicity and (ii) to compare MC phase influences on a woman’s daily mood with that attributable to key alternate explanatory variables (physical health, perceived stress and social support). Method: A random sample of Canadian women aged 18–40 years collected mood and health data daily over 6 months, using telemetry, producing 395 complete MCs for analysis. Results: Only half the individual mood items showed any MC phase association; these links were either with the menses phase alone or the menses plus the premenstrual phase. With one exception, the association was not solely premenstrual. The menses-follicular-luteal MC division gave similar results. Less than 0.5% of the women’s individual periodogram records for each mood item showed MC entrainment. Physical health, perceived stress and social support were much stronger predictors of mood (p < 0.0001 in each case) than MC phase. Conclusions: The results of this study do not support the widespread idea of specific premenstrual dysphoria in women. Daily physical health status, perceived stress and social support explain daily mood better than MC phase.

Standard clinical trial methodology in depression does not allow for careful examination of early changes in symptom intensity. The purpose of this study was to use daily "Mental Health Telemetry" (MHT) to prospectively record change in depressive and anxiety symptoms for depressed patients receiving augmentation treatment, and determine the extent and predictive capacity of early changes. We report results of a 6-week, open-label study of the addition of quetiapine XR (range, 50-300 mg) for adult patients (n = 26) with major depressive disorder who were nonresponsive to antidepressant treatment. In addition to regular study visits, all participants completed daily, wirelessly transmitted self-report ratings of symptoms on a Smartphone. Daily and 3-day moving average mean scores were calculated, and associations between early symptom change and eventual response to treatment were determined. Improvement in depressive and anxiety symptoms was identified as early as day 1 of treatment. Of the total decline in depression severity over 6 weeks, 9% was present at day 1, 28% at day 2, 39% at days 3 and 4, 65% at day 7, and 80% at day 10. Self-report rating of early improvement (≥20%) in depressive symptoms at day 7 significantly predicted responder status at week 6 (P = 0.03). Clinician-rated depressive and anxiety symptoms only became significantly associated with responder status at day 14. In conclusion, very early changes in depressive symptoms were identified using MHT, early changes accounted for most of total change, and MHT-recorded improvement as early as day 7 significantly predicted response to treatment at study end point.