Preventing suicide by young people

Introduction In 2013, 2,522 people died by suicide in Australia. Twenty-two of these were children aged 5- 14 years, 148 were adolescents aged 15-19 years, and a further 200 were young people aged 20-24 years. Although the suicide rate for children and adolescents is lower than that for some older age groups, suicide is the leading cause of death in children and young people. Suicide has immense effects on the families, friends, and communities of people who die by suicide, causing long lasting grief and guilt. Arguably, these effects are even greater when the person who died by suicide is young. It is estimated that suicide costs the Australian economy more than $17 billion per year. Researchers and policy makers recognise that suicide is preventable, yet suicide rates have changed little in the past 10 years. This discussion paper aims to focus a spotlight on the unique experience of young people. It does this by providing a critical analysis of existing policy and evidence based responses relevant to young people

Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review

Background: The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools. Objective: This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults. Methods: We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF). Results: Of the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E). Conclusions: Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

The effectiveness of mHealth interventions for maternal, newborn and child health in low- and middle-income countries:Protocol for a systematic review and meta-analysis

Rates of maternal, newborn and child (MNCH) mortality and morbidity are vastly greater in low– than in high–income countries and represent a major source of global health inequity. A host of systemic, economic, geopolitical and sociocultural factors have been implicated. Mobile information and communication technologies hold potential to ameliorate several of these challenges by supporting coordinated and evidence–based care, facilitating community based health services and enabling citizens to access health information and support. mHealth has attracted considerable attention as a means of supporting maternal, newborn and child health in developing countries and research to assess the impacts of mHealth interventions is increasing. While a number of expert reviews have attempted to summarise this literature, there remains a need for a fully systematic review employing gold standard methods of evidence capture, critical appraisal and meta–analysis, in order to comprehensively map, quality assess and synthesise this body of knowledge

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

Re-thinking technology and its growing role in enabling patient empowerment

© The Author(s) 2018. The presence and increase of challenges to eHealth in today’s society have begun to generate doubts about the capability of technology in patient empowerment, especially within the frameworks supporting empowerment. Through the review of existing frameworks and articulation of patient demands, weaknesses in the current application of technology to support empowerment are explored, and key constituents of a technology-driven framework for patient empowerment are determined. This article argues that existing usage of technology in the design, development and implementation of patient empowerment in the healthcare system, although well intentioned, is insufficiently constituted, primarily as a result of fragmentation. Systems theory concepts such as holism and iteration are considered vital in improving the role of technology in enabling patient empowerment