Collecting health-related research data using consumer-based wireless smart scales

Background: Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population’s health. They can present us with a picture of our metabolism, body health, and disease risks. Combining body composition data with physical activity measurements from devices such as smart watches could contribute to building a human digital twin. Objective: The objectives of this study were to (1) investigate the evolution of smart scales in the last decade, (2) map status and supported sensors of smart scales, (3) get an overview of how smart scales have been used in research, and (4) identify smart scales for current and future research. Method: We searched for devices through web shops and smart scale tests/reviews, extracting data from the manufacturer’s official website, user manuals when available, and data from web shops. We also searched scientific literature databases for smart scale usage in scientific papers. Result: We identified 165 smart scales with a wireless connection from 72 different manufacturers, released between 2009 and end of 2021. Of these devices, 49 (28%) had been discontinued by end of 2021. We found that the use of major variables such as fat and muscle mass have been as good as constant over the years, and that minor variables such as visceral fat and protein mass have increased since 2015. The main contribution is a representative overview of consumer grade smart scales between 2009 and 2021. Conclusion: The last six years have seen a distinct increase of these devices in the marketplace, measuring body composition with bone mass, muscle mass, fat mass, and water mass, in addition to weight. Still, the number of research projects featuring connected smart scales are few. One reason could be the lack of professionally accurate measurements, though trend analysis might be a more feasible usage scenario

Decision Science for Future Earth

This open access book provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation. Based on these case studies and comprehensive reviews of relevant works, including lessons learned from past failures for predictable surprises and successes in adaptive co-management, the book provides the reader with new perspectives on how we can co-design collaborative projects with various conflicts of interest and how we can transform our society for a sustainable future. The book makes a valuable contribution to the global research initiative Future Earth, promoting transdisciplinary studies to bridge the gap between science and society in knowledge generation processes and supporting efforts to achieve the UN’s Sustainable Development Goals (SDGs). Compared to other publications on transdisciplinary studies, this book is unique in that evolutionary biology is used as an integrator for various areas related to human decision-making, and approaches social changes as processes of adaptive learning and evolution. Given its scope, the book is highly recommended to all readers seeking an integrated overview of human decision-making in the context of social transformation

A holistic view of the social and technical factors that Influence the assimilation of an mHealth tool in developing countries

The integration of smartphones and mobile devices into healthcare systems has been proposed to address some of the physical barriers to healthcare delivery in rural areas of developing countries. This has prompted a number of intervention initiatives to develop novel mHealth tools for specific regions. However, despite all the research and the investment, there has been slow practical progress. This thesis attributes this slow progress to compartmentalised thinking and limited holistic exploration. In order to understand these problems, this thesis undertook a number of studies, i.e., a review-focused, a past-focused, a future-focused, and policy-focused studies to understand how an mHealth tool could be assimilated in rural areas of developing countries. These studies took place in the context of an mHealth app being explored for introduction to assist with the diagnosis and treatment of sick children under the age of five in Enugu State, Nigeria. Therefore, the objective of this thesis is to create a more socially and technologically holistic understanding of the factors that influence the introduction of mHealth tools into rural areas of developing countries. First, findings from the review-focused study illustrate two key trends in existing research. Most strikingly, little research has looked at the role of patient-to-patient interactions. Furthermore, the interactions between system developers and the other stakeholder groups are notably under-represented. Second, findings from the past-focused study indicate that, (i) at the social-level, there is a perceived limitation of services, human resources and a sense of exclusion from the urban health system; (ii) at ‘material-level, observations were made of the significant infrastructural and technological limitations that discourage rural healthcare workers (RHCWs) and parents/guardians (PGs) from spending prolonged periods at the rural health centres; (iii) at the ‘practice-level’, there is the formal diagnosis treatment method practiced by the RHCWs in the midst of the PGs diagnosis and treatment practices and African traditional healing practices, and (iv) at ‘imbrication-level’, the entanglement of phones with internet access have exposed PGs to a range of health information outside the control or guidance of health professionals. Third, from the future-focused study, findings show a set of factors which are bound as an emerging explanatory model which influence primary appraisal of an mHealth tool in a new context. These factors describe a set of individual and social influences that governments, funding bodies and non-governmental organisations should consider before the introduction of an mHealth tool. Fourth, from the policy-focused study, a framework is proposed that differentiates between interventions targeting traits and states, the latter being situation-specific, and the former which seeks to improve individual’s abilities, job knowledge, and skills as they relate to an mHealth tool. Furthermore, the framework differentiates between individual and social interventions, the former being resilient to personnel change, and the latter seeking to improve crucial situations that would otherwise cause social systems to break down around an mHealth tool. These findings have implications for theory, practice, and future research. These implications are discussed in the final chapter of this thesis