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      Development of a decision-making checklist tool to support technology selection in digital health research

      1 , 2 , 3 , 4
      Translational Behavioral Medicine
      Oxford University Press (OUP)

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          Abstract

          Researchers use digital technologies to collect health behavior data. These tools are publicly available and under-regulated. An iterative process involving experts informed a checklist tool to aid in responsible selection of technologies for use in health research. Digital technologies offer researchers new approaches to test personalized and adaptive health interventions tailored to an individual. Yet, research leveraging technologies to capture personal health data involve technical and ethical consideration during the study design phase. No guidance exists to facilitate responsible digital technology selection for research purposes. A stakeholder-engaged and iterative approach was used to develop, test, and refine a checklist designed to aid researchers in selecting technologies for their research. First, stakeholders ( n = 7) discussed and informed key decision-making domains to guide app/device selection derived from the American Psychiatric Association’s framework that included safety, evidence, usability, and interoperability. We added “ethical principles” to the APA’s hierarchical model and created a checklist that was used by a small group of behavioral scientists ( n = 7). Findings revealed the “ethical principles” domains of respect, beneficence, and justice cut across each decision-making domains and the checklist questions/prompts were revised accordingly and can be found at thecore.ucsd.edu . The refined checklist contains four decision-making domains with prompts/questions and ethical principles embedded within the domains of privacy, risk/benefit, data management, and access/evidence. This checklist is the first step in leading the narrative of decision-making when selecting digital health technologies for research. Given the dynamic and rapidly evolving nature of digital health technology use in research, this tool will need to be further evaluated for usefulness in technology selection.

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          A Hierarchical Framework for Evaluation and Informed Decision Making Regarding Smartphone Apps for Clinical Care

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            Is Open Access

            Methods for Evaluating the Content, Usability, and Efficacy of Commercial Mobile Health Apps

            Commercial mobile apps for health behavior change are flourishing in the marketplace, but little evidence exists to support their use. This paper summarizes methods for evaluating the content, usability, and efficacy of commercially available health apps. Content analyses can be used to compare app features with clinical guidelines, evidence-based protocols, and behavior change techniques. Usability testing can establish how well an app functions and serves its intended purpose for a target population. Observational studies can explore the association between use and clinical and behavioral outcomes. Finally, efficacy testing can establish whether a commercial app impacts an outcome of interest via a variety of study designs, including randomized trials, multiphase optimization studies, and N-of-1 studies. Evidence in all these forms would increase adoption of commercial apps in clinical practice, inform the development of the next generation of apps, and ultimately increase the impact of commercial apps.
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              Ethical and regulatory challenges of research using pervasive sensing and other emerging technologies: IRB perspectives

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                Author and article information

                Journal
                Translational Behavioral Medicine
                Oxford University Press (OUP)
                1869-6716
                1613-9860
                May 23 2019
                May 23 2019
                Affiliations
                [1 ]Department of Family Medicine and Public Health, School of Medicine, UC San Diego, La Jolla, CA, USA
                [2 ]Center for Wireless and Population Health Systems, UC San Diego, La Jolla, CA, USA
                [3 ]Indiana University School of Nursing, Indianapolis, IN, USA
                [4 ]Beth Israel Deconess Medical Center, Harvard University, Boston, MA, USA
                Article
                10.1093/tbm/ibz074
                7543075
                31120511
                ddde2a63-48e3-447c-98e3-d139cca388f3
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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