Evaluating Digital Health Interventions: Key Questions and Approaches

Digital health interventions have enormous potential as scalable tools to improve health and healthcare delivery by improving effectiveness, efficiency, accessibility, safety, and personalization. Achieving these improvements requires a cumulative knowledge base to inform development and deployment of digital health interventions. However, evaluations of digital health interventions present special challenges. This paper aims to examine these challenges and outline an evaluation strategy in terms of the research questions needed to appraise such interventions. As they are at the intersection of biomedical, behavioral, computing, and engineering research, methods drawn from all of these disciplines are required. Relevant research questions include defining the problem and the likely benefit of the digital health intervention, which in turn requires establishing the likely reach and uptake of the intervention, the causal model describing how the intervention will achieve its intended benefit, key components, and how they interact with one another, and estimating overall benefit in terms of effectiveness, cost effectiveness, and harms. Although RCTs are important for evaluation of effectiveness and cost effectiveness, they are best undertaken only when: (1) the intervention and its delivery package are stable; (2) these can be implemented with high fidelity; and (3) there is a reasonable likelihood that the overall benefits will be clinically meaningful (improved outcomes or equivalent outcomes at lower cost). Broadening the portfolio of research questions and evaluation methods will help with developing the necessary knowledge base to inform decisions on policy, practice, and research

Advancing Models and Theories for Digital Behavior Change Interventions

To be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The "state" is that of the individual based on multiple variables that define the "space" when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature

Risk prediction tools for cancer in primary care.

Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an 'area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.This is the final version of the article. It was first available from NPG via http://dx.doi.org/10.1038/bjc.2015.40

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Annual review article: Is it time to rethink the gender agenda in entrepreneurship research?

This article develops a critique of contemporary approaches to analysing the impact of gender upon entrepreneurial propensity and activity. Since the 1990s, increasing attention has been afforded to the influence of gender upon women’s entrepreneurial behaviour; such analyses have highlighted an embedded masculinity within the entrepreneurial discourse which privileges men as normative entrepreneurial actors. Whilst invaluable in revealing a prevailing masculine bias within entrepreneurship, this critique is bounded by positioning women as a proxy for the gendered subject. This is a potentially limiting analysis that does not fully recognise gender as a human property with myriad articulations enacted throughout entrepreneurial activity. To progress debate, we engage more deeply with the notion of gender as a multiplicity exploring the implications of such for future studies of entrepreneurial activity

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Social cohesion through football: a quasi-experimental mixed methods design to evaluate a complex health promotion program

Social isolation and disengagement fragments local communities. Evidence indicates that refugee families are highly vulnerable to social isolation in their countries of resettlement. Research to identify approaches to best address this is needed. Football United is a program that aims to foster social inclusion and cohesion in areas with high refugee settlement in New South Wales, Australia, through skills and leadership development, mentoring, and the creation of links with local community and corporate leaders and organisations. The Social Cohesion through Football study’s broad goal is to examine the implementation of a complex health promotion program, and to analyse the processes involved in program implementation. The study will consider program impact on individual health and wellbeing, social inclusion and cohesion, as well as analyse how the program by necessity interacts and adapts to context during implementation, a concept we refer to as plasticity. The proposed study will be the first prospective cohort impact study to our knowledge to assess the impact of a comprehensive integrated program using football as a vehicle for fostering social inclusion and cohesion in communities with high refugee settlement

Underpinning Sustainable Vector Control through Informed Insecticide Resistance Management

Background: There has been rapid scale-up of malaria vector control in the last ten years. Both of the primary control strategies, long-lasting pyrethroid treated nets and indoor residual spraying, rely on the use of a limited number of insecticides. Insecticide resistance, as measured by bioassay, has rapidly increased in prevalence and has come to the forefront as an issue that needs to be addressed to maintain the sustainability of malaria control and the drive to elimination. Zambia’s programme reported high levels of resistance to the insecticides it used in 2010, and, as a result, increased its investment in resistance monitoring to support informed resistance management decisions. Methodology/Principal Findings: A country-wide survey on insecticide resistance in Zambian malaria vectors was performed using WHO bioassays to detect resistant phenotypes. Molecular techniques were used to detect target-site mutations and microarray to detect metabolic resistance mechanisms. Anopheles gambiae s.s. was resistant to pyrethroids,DDT and carbamates, with potential organophosphate resistance in one population. The resistant phenotypes were conferred by both target-site and metabolic mechanisms. Anopheles funestus s.s. was largely resistant to pyrethroids and carbamates, with potential resistance to DDT in two locations. The resistant phenotypes were conferred by elevated levels of cytochrome p450s. Conclusions/Significance: Currently, the Zambia National Malaria Control Centre is using these results to inform their vector control strategy. The methods employed here can serve as a template to all malaria-endemic countries striving to create a sustainable insecticide resistance management pla

Streptomyces aridus sp. nov., isolated from a high altitude Atacama Desert soil and emended description of Streptomyces noboritoensis Isono et al. 1957.

A polyphasic study was undertaken to determine the taxonomic status of a Streptomyces strain which had been isolated from a high altitude Atacama Desert soil and shown to have bioactive properties. The strain, isolate H9(T), was found to have chemotaxonomic, cultural and morphological properties that place it in the genus Streptomyces. 16S rRNA gene sequence analyses showed that the isolate forms a distinct branch at the periphery of a well-delineated subclade in the Streptomyces 16S rRNA gene tree together with the type strains of Streptomyces crystallinus, Streptomyces melanogenes and Streptomyces noboritoensis. Multi-locus sequence analysis (MLSA) based on five house-keeping gene alleles showed that isolate H9(T) is closely related to the latter two type strains and to Streptomyces polyantibioticus NRRL B-24448(T). The isolate was distinguished readily from the type strains of S. melanogenes, S. noboritoensis and S. polyantibioticus using a combination of phenotypic properties. Consequently, the isolate is considered to represent a new species of Streptomyces for which the name Streptomyces aridus sp. nov. is proposed; the type strain is H9(T) (=NCIMB 14965(T)=NRRL B65268(T)). In addition, the MLSA and phenotypic data show that the S. melanogenes and S. noboritoensis type strains belong to a single species, it is proposed that S. melanogenes be recognised as a heterotypic synonym of S. noboritoensis for which an emended description is given. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10482-017-0838-2) contains supplementary material, which is available to authorized users