Developing a Test-bed for Distributed Search by Mobile Sensors

Abstract-- The goal of this Systems and Information Engineering Capstone project is to develop a physical test-bed in order to analyze the efficiency of swarmbased distributed search algorithms. This test-bed demonstrates a distributed search system using actual moving search agents and target detection. The goal of this test-bed is to provide a tool that can be used in future research to better understand swarm-based distributed search by mobile sensors. I

Disseminating health research to public health policy-makers and practitioners: a survey of source, message content and delivery modality preferences

Abstract Background Understanding the views of policy-makers and practitioners regarding how best to communicate research evidence is important to support research use in their decision-making. Aim To quantify and describe public health policy-makers and practitioners’ views regarding the source, content and form of messages describing public health research findings to inform their decision-making. We also sought to examine differences in preferences between public health policy-makers and practitioners. Methods A cross sectional, value-weighting survey of policy-makers and practitioners was conducted. Participants were asked to allocate a proportion of 100 points across different (i) sources of research evidence, (ii) message content and (iii) the form in which evidence is presented. Points were allocated based on their rating of influence, usefulness and preference when making decisions about health policy or practice. Results A total of 186 survey responses were received from 90 policy-makers and 96 practitioners. Researchers and government department agencies were the most influential source of research evidence based on mean allocation of points, followed by knowledge brokers, professional peers and associations. Mean point allocation for perceived usefulness of message content was highest for simple summary of key findings and implications, and then evidence-based recommendations and data and statistical summaries. Finally, based on mean scores, policy-makers and practitioners preferred to receive research evidence in the form of peer-reviewed publications, reports, evidence briefs and plain language summaries. There were few differences in scores between policy-makers and practitioners across source, message content or form assessments or those with experience in different behavioural areas. Conclusions The findings should provide a basis for the future development and optimization of dissemination strategies to this important stakeholder group

Optimisation: defining and exploring a concept to enhance the impact of public health initiatives

Background: Repeated, data-driven optimisation processes have been applied in many fields to rapidly transform the performance of products, processes and interventions. While such processes may similarly be employed to enhance the impact of public health initiatives, optimisation has not been defined in the context of public health and there has been little exploration of its key concepts. Methods: We used a modified, three-round Delphi study with an international group of researchers, public health policy-makers and practitioners to (1) generate a consensus-based definition of optimisation in the context of public health and (2i) describe key considerations for optimisation in that context. A pre-workshop literature review and elicitation of participant views regarding optimisation in public health (round 1) were followed by a daylong workshop and facilitated face-to-face group discussions to refine the definition and generate key considerations (round 2); finally, post-workshop discussions were undertaken to refine and finalise the findings (round 3). A thematic analysis was performed at each round. Study findings reflect an iterative consultation process with study participants. Results: Thirty of 33 invited individuals (91%) participated in the study. Participants reached consensus on the following definition of optimisation in public health: “A deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints”. A range of optimisation considerations were explored. Optimisation was considered most suitable when existing public health initiatives are not sufficiently effective, meaningful improvements from an optimisation process are anticipated, quality data to assess impacts are routinely available, and there are stable and ongoing resources to support it. Participants believed optimisation could be applied to improve the impacts of an intervention, an implementation strategy or both, on outcomes valued by stakeholders or end users. While optimisation processes were thought to be facilitated by an understanding of the mechanisms of an intervention or implementation strategy, no agreement was reached regarding the best approach to inform decisions about modifications to improve impact. Conclusions: The study findings provide a strong basis for future research to explore the potential impact of optimisation in the field of public health.Other UBCNon UBCReviewedFacult

Additional file 2 of The effectiveness of implementation strategies in improving preconception and antenatal preventive care: a systematic review

Additional file 2. Search Strategy

Additional file 3 of The effectiveness of implementation strategies in improving preconception and antenatal preventive care: a systematic review

Additional file 3. Characteristics of Included Studies