A New Design of Flicker Photometer for Laboratory Colored Light Photometry

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New two-sided bound on the isotropic Lorentz-violating parameter of modified Maxwell theory

There is a unique Lorentz-violating modification of the Maxwell theory of photons, which maintains gauge invariance, CPT, and renormalizability. Restricting the modified-Maxwell theory to the isotropic sector and adding a standard spin-one-half Dirac particle p^\pm with minimal coupling to the nonstandard photon \widetilde{\gamma}, the resulting modified-quantum-electrodynamics model involves a single dimensionless "deformation parameter," \widetilde{\kappa}_{tr}. The exact tree-level decay rates for two processes have been calculated: vacuum Cherenkov radiation p^\pm \to p^\pm \widetilde{\gamma} for the case of positive \widetilde{\kappa}_{tr} and photon decay \widetilde{\gamma} \to p^+ p^- for the case of negative \widetilde{\kappa}_{tr}. From the inferred absence of these decays for a particular high-quality ultrahigh-energy-cosmic-ray event detected at the Pierre Auger Observatory and an excess of TeV gamma-ray events observed by the High Energy Stereoscopic System telescopes, a two-sided bound on \widetilde{\kappa}_{tr} is obtained, which improves by eight orders of magnitude upon the best direct laboratory bound. The implications of this result are briefly discussed.Comment: 18 pages, v5: published version in preprint styl

Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review

Copyright \ua9 2023 Milne-Ives, Homer, Andrade and Meinert.Introduction: Lack of engagement is a common challenge for digital health interventions. To achieve their potential, it is necessary to understand how best to support users’ engagement with interventions and target health behaviors. The aim of this systematic review was to identify the behavioral theories and behavior change techniques being incorporated into mobile health apps and how they are associated with the different components of engagement. Methods: The review was structured using the PRISMA and PICOS frameworks and searched six databases in July 2022: PubMed, Embase, CINAHL, APA PsycArticles, ScienceDirect, and Web of Science. Risk of bias was evaluated using the Cochrane Collaboration Risk of Bias 2 and the Mixed Methods Appraisal Tools. Analysis: A descriptive analysis provided an overview of study and app characteristics and evidence for potential associations between Behavior Change Techniques (BCTs) and engagement was examined. Results: The final analysis included 28 studies. Six BCTs were repeatedly associated with user engagement: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. There was insufficient data reported to examine associations with specific components of engagement, but the analysis indicated that the different components were being captured by various measures. Conclusion: This review provides further evidence supporting the use of common BCTs in mobile health apps. To enable developers to leverage BCTs and other app features to optimize engagement in specific contexts and individual characteristics, we need a better understanding of how BCTs are associated with different components of engagement. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022312596

Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review

Introduction: Lack of engagement is a common challenge for digital health interventions. To achieve their potential, it is necessary to understand how best to support users’ engagement with interventions and target health behaviors. The aim of this systematic review was to identify the behavioral theories and behavior change techniques being incorporated into mobile health apps and how they are associated with the different components of engagement. Methods: The review was structured using the PRISMA and PICOS frameworks and searched six databases in July 2022: PubMed, Embase, CINAHL, APA PsycArticles, ScienceDirect, and Web of Science. Risk of bias was evaluated using the Cochrane Collaboration Risk of Bias 2 and the Mixed Methods Appraisal Tools. Analysis: A descriptive analysis provided an overview of study and app characteristics and evidence for potential associations between Behavior Change Techniques (BCTs) and engagement was examined. Results: The final analysis included 28 studies. Six BCTs were repeatedly associated with user engagement: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. There was insufficient data reported to examine associations with specific components of engagement, but the analysis indicated that the different components were being captured by various measures. Conclusion: This review provides further evidence supporting the use of common BCTs in mobile health apps. To enable developers to leverage BCTs and other app features to optimize engagement in specific contexts and individual characteristics, we need a better understanding of how BCTs are associated with different components of engagement. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022312596

The conceptualisation and measurement of engagement in digital health.

Digital tools are an increasingly important component of healthcare, but their potential impact is commonly limited by a lack of user engagement. Digital health evaluations of engagement are often restricted to system usage metrics, which cannot capture a full understanding of how and why users engage with an intervention. This study aimed to examine how theory-based, multifaceted measures of engagement with digital health interventions capture different components of engagement (affective, cognitive, behavioural, micro, and macro) and to consider areas that are unclear or missing in their measurement. We identified and compared two recently developed measures that met these criteria (the Digital Behaviour Change Intervention Engagement Scale and the TWente Engagement with Ehealth Technologies Scale). Despite having similar theoretical bases and being relatively strongly correlated, there are key differences in how these scales aim to capture engagement. We discuss the implications of our analysis for how affective, cognitive, and behavioural components of engagement can be conceptualised and whether there is value in distinguishing between them. We conclude with recommendations for the circumstances in which each scale may be most useful and for how future measure development could supplement existing scales

Unstable Giants

We find giant graviton solutions in Frolov's three parameter generalization of the Lunin-Maldacena background. The background we study has $\tilde{\gamma}_1=0$ and $\tilde{\gamma}_2=\tilde{\gamma}_3=\tilde{\gamma}$. This class of backgrounds provide a non-superymmetric example of the gauge theory/gravity correspondence that can be tested quantitatively, as recently shown by Frolov, Roiban and Tseytlin. The giant graviton solutions we find have a greater energy than the point gravitons, making them unstable states. Despite this, we find striking quantitative agreement between the gauge theory and gravity descriptions of open strings attached to the giant.Comment: 1+24 pages, 2 figures; v2: coupling to NSNS B field included, refs added and typos corrected; v3 new results on stability of giants included, presentation improved, refs added; v4 final version to appear in Phys. Rev.

The conceptualisation and measurement of engagement in digital health

\ua9 2024Digital tools are an increasingly important component of healthcare, but their potential impact is commonly limited by a lack of user engagement. Digital health evaluations of engagement are often restricted to system usage metrics, which cannot capture a full understanding of how and why users engage with an intervention. This study aimed to examine how theory-based, multifaceted measures of engagement with digital health interventions capture different components of engagement (affective, cognitive, behavioural, micro, and macro) and to consider areas that are unclear or missing in their measurement. We identified and compared two recently developed measures that met these criteria (the Digital Behaviour Change Intervention Engagement Scale and the TWente Engagement with Ehealth Technologies Scale). Despite having similar theoretical bases and being relatively strongly correlated, there are key differences in how these scales aim to capture engagement. We discuss the implications of our analysis for how affective, cognitive, and behavioural components of engagement can be conceptualised and whether there is value in distinguishing between them. We conclude with recommendations for the circumstances in which each scale may be most useful and for how future measure development could supplement existing scales

Random replicators with high-order interactions

We use tools of the equilibrium statistical mechanics of disordered systems to study analytically the statistical properties of an ecosystem composed of N species interacting via random, Gaussian interactions of order p >= 2, and deterministic self-interactions u <= 0. We show that for nonzero u the effect of increasing the order of the interactions is to make the system more cooperative, in the sense that the fraction of extinct species is greatly reduced. Furthermore, we find that for p > 2 there is a threshold value which gives a lower bound to the concentration of the surviving species, preventing then the existence of rare species and, consequently, increasing the robustness of the ecosystem to external perturbations.Comment: 7 pages, 4 Postscript figure

Associations between Behavior Change Techniques and Engagement with Mobile Health Apps: Protocol for a Systematic Review

\ua9 2022 JMIR Publications Inc.. All right reserved. Background: Digitally enabled care along with an emphasis on self-management of health is steadily growing. Mobile health apps provide a promising means of supporting health behavior change; however, engagement with them is often poor and evidence of their impact on health outcomes is lacking. As engagement is a key prerequisite to health behavior change, it is essential to understand how engagement with mobile health apps and their target health behaviors can be better supported. Although the importance of engagement is emphasized strongly in the literature, the understanding of how different components of engagement are associated with specific techniques that aim to change behaviors is lacking. Objective: The purpose of this systematic review protocol is to provide a synthesis of the associations between various behavior change techniques (BCTs) and the different components and measures of engagement with mobile health apps. Methods: The review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the PICOS (Population, Intervention, Comparator, Outcome, and Study type) frameworks. The following seven databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, APA PsycInfo, ScienceDirect, Cochrane Library, and Web of Science. Title and abstract screening, full-text review, and data extraction will be conducted by 2 independent reviewers. Data will be extracted into a predetermined form, any disagreements in screening or data extraction will be discussed, and a third reviewer will be consulted if consensus cannot be reached. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 and the Risk Of Bias In Non-Randomized Studies - of Interventions (ROBINS-I) tools; descriptive and thematic analyses will be conducted to summarize the relationships between BCTs and the different components of engagement. Results: The systematic review has not yet started. It is expected to be completed and submitted for publication by May 2022. Conclusions: This systematic review will summarize the associations between different BCTs and various components and measures of engagement with mobile health apps. This will help identify areas where further research is needed to examine BCTs that could potentially support effective engagement and help inform the design and evaluation of future mobile health apps