Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface.

Objective: UK primary care databases, which contain diagnostic, demographic and prescribing information for millions of patients geographically representative of the UK, represent a significant resource for health services and clinical research. They can be used to identify patients with a specified disease or condition (phenotyping) and to investigate patterns of diagnosis and symptoms. Currently, extracting such information manually is time-consuming and requires considerable expertise. In order to exploit more fully the potential of these large and complex databases, our interdisciplinary team developed generic methods allowing access to different types of user. Materials and methods: Using the Clinical Practice Research Datalink database, we have developed an online user-focused system (TrialViz), which enables users interactively to select suitable medical general practices based on two criteria: suitability of the patient base for the intended study (phenotyping) and measures of data quality. Results: An end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query interface and to explore this information using interactive visualization tools. A usability evaluation of this system produced positive results. Discussion: We present the challenges and results in the development of TrialViz and our plans for its extension for wider applications of clinical research. Conclusions: Our fast search algorithms and simple query algorithms represent a significant advance for users of clinical research databases

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Content validity and methodological considerations in ecological momentary assessment studies on physical activity and sedentary behaviour : a systematic review

Background Ecological momentary assessment (EMA) is a method of collecting real-time data based on repeated measures and observations that take place in participant's daily environment. EMA has many advantages over more traditional, retrospective questionnaires. However, EMA faces some challenges to reach its full potential. The aims of this systematic review are to (1) investigate whether and how content validity of the items (i.e. the specific questions that are part of a larger EMA questionnaire) used in EMA studies on physical activity and sedentary behaviour was assessed, and (2) provide an overview of important methodological considerations of EMA in measuring physical activity and sedentary behaviour. Methods Thirty papers (twenty unique studies) were systematically reviewed and variables were coded and analysed within the following 4 domains: (1) Content validity, (2) Sampling approach, (3) Data input modalities and (4) Degree of EMA completion. Results Only about half of the studies reported the specific items (n = 12) and the source of the items (n = 11). None of the studies specifically assessed the content validity of the items used. Only a minority (n = 5) of the studies reported any training, and one tested the comprehensibility of the EMA items. A wide variability was found in the design and methodology of the EMA. A minority of the studies (n = 7) reported a rationale for the used prompt frequency, time selection, and monitoring period. Retrospective assessment periods varied from 'now' to 'in the last 3.5 hours'. In some studies there was a possibility to delay (n = 6) or deactivate (n = 10) the prompt, and some provided reminders after the first prompt (n = 9). Conclusions Almost no EMA studies reported the content validation of the items used. We recommend using the COSMIN checklist (COnsensus-based Standards for the selection of health Measurement INstruments) to report on the content validity of EMA items. Furthermore, as often no rationale was provided for several methodological decisions, the following three recommendations are made. First, provide a rationale for choosing the sampling modalities. Second, to ensure assessment 'in the moment', think carefully about the retrospective assessment period, reminders, and deactivation of the prompt. Third, as high completion rates are important for representativeness of the data and generalizability of the findings, report completion rates

Good practice characteristics of diet and physical activity interventions and policies : an umbrella review

BACKGROUND: This umbrella review aimed at eliciting good practice characteristics of interventions and policies aiming at healthy diet, increasing physical activity, and lowering sedentary behaviors. Applying the World Health Organization's framework, we sought for 3 types of characteristics, reflecting: (1) main intervention/policy characteristics, referring to the design, targets, and participants, (2) monitoring and evaluation processes, and (3) implementation issues. This investigation was undertaken by the DEDPIAC Knowledge Hub (the Knowledge Hub on the DEterminants of DIet and Physical ACtivity), which is an action of the European Union's joint programming initiative. METHODS: A systematic review of reviews and stakeholder documents was conducted. Data from 7 databases was analyzed (99 documents met inclusion criteria). Additionally, resources of 7 major stakeholders (e.g., World Health Organization) were systematically searched (10 documents met inclusion criteria). Overall, the review yielded 74 systematic reviews, 16 position review papers, and 19 stakeholders' documents. Across characteristics, 25% were supported by ≥ 4 systematic reviews. Further, 25% characteristics were supported by ≥ 3 stakeholders' documents. If identified characteristics were included in at least 4 systematic reviews or at least 3 stakeholders' documents, these good practice characteristics were classified as relevant. RESULTS: We derived a list of 149 potential good practice characteristics, of which 53 were classified as relevant. The main characteristics of intervention/policy (n = 18) fell into 6 categories: the use of theory, participants, target behavior, content development/management, multidimensionality, practitioners/settings. Monitoring and evaluation characteristics (n = 18) were grouped into 6 categories: costs/funding, outcomes, evaluation of effects, time/effect size, reach, the evaluation of participation and generalizability, active components/underlying processes. Implementation characteristics (n = 17) were grouped into eight categories: participation processes, training for practitioners, the use/integration of existing resources, feasibility, maintenance/sustainability, implementation partnerships, implementation consistency/adaptation processes, transferability. CONCLUSIONS: The use of the proposed list of 53 good practice characteristics may foster further development of health promotion sciences, as it would allow for identification of success vectors in the domains of main characteristics of interventions/policies, their implementation, evaluation and monitoring processes

Wildbook: Crowdsourcing, computer vision, and data science for conservation

Photographs, taken by field scientists, tourists, automated cameras, and incidental photographers, are the most abundant source of data on wildlife today. Wildbook is an autonomous computational system that starts from massive collections of images and, by detecting various species of animals and identifying individuals, combined with sophisticated data management, turns them into high resolution information database, enabling scientific inquiry, conservation, and citizen science. We have built Wildbooks for whales (flukebook.org), sharks (whaleshark.org), two species of zebras (Grevy's and plains), and several others. In January 2016, Wildbook enabled the first ever full species (the endangered Grevy's zebra) census using photographs taken by ordinary citizens in Kenya. The resulting numbers are now the official species census used by IUCN Red List: http://www.iucnredlist.org/details/7950/0. In 2016, Wildbook partnered up with WWF to build Wildbook for Sea Turtles, Internet of Turtles (IoT), as well as systems for seals and lynx. Most recently, we have demonstrated that we can now use publicly available social media images to count and track wild animals. In this paper we present and discuss both the impact and challenges that the use of crowdsourced images can have on wildlife conservation.Comment: Presented at the Data For Good Exchange 201