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      Submit your digital health research with an established publisher
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      IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior

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          Abstract

          Developing effective digital interventions to change health behavior has been a challenging goal for academics and industry players alike. Guiding intervention design using the best combination of approaches available is necessary if effective technologies are to be developed. Behavioral theory, design thinking, user-centered design, rigorous evaluation, and dissemination each have widely acknowledged merits in their application to digital health interventions. This paper introduces IDEAS, a step-by-step process for integrating these approaches to guide the development and evaluation of more effective digital interventions. IDEAS is comprised of 10 phases (empathize, specify, ground, ideate, prototype, gather, build, pilot, evaluate, and share), grouped into 4 overarching stages: Integrate, Design, Assess, and Share (IDEAS). Each of these phases is described and a summary of theory-based behavioral strategies that may inform intervention design is provided. The IDEAS framework strives to provide sufficient detail without being overly prescriptive so that it may be useful and readily applied by both investigators and industry partners in the development of their own mHealth, eHealth, and other digital health behavior change interventions.

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          Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials.

          K Schulz, I. Chalmers, R Hayes … (1995)
          To determine if inadequate approaches to randomized controlled trial design and execution are associated with evidence of bias in estimating treatment effects. An observational study in which we assessed the methodological quality of 250 controlled trials from 33 meta-analyses and then analyzed, using multiple logistic regression models, the associations between those assessments and estimated treatment effects. Meta-analyses from the Cochrane Pregnancy and Childbirth Database. The associations between estimates of treatment effects and inadequate allocation concealment, exclusions after randomization, and lack of double-blinding. Compared with trials in which authors reported adequately concealed treatment allocation, trials in which concealment was either inadequate or unclear (did not report or incompletely reported a concealment approach) yielded larger estimates of treatment effects (P < .001). Odds ratios were exaggerated by 41% for inadequately concealed trials and by 30% for unclearly concealed trials (adjusted for other aspects of quality). Trials in which participants had been excluded after randomization did not yield larger estimates of effects, but that lack of association may be due to incomplete reporting. Trials that were not double-blind also yielded larger estimates of effects (P = .01), with odds ratios being exaggerated by 17%. This study provides empirical evidence that inadequate methodological approaches in controlled trials, particularly those representing poor allocation concealment, are associated with bias. Readers of trial reports should be wary of these pitfalls, and investigators must improve their design, execution, and reporting of trials.
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            Mapping mHealth Research: A Decade of Evolution

            Maddalena Fiordelli, Nicola Diviani, Peter J. Schulz (2013)
            Background For the last decade, mHealth has constantly expanded as a part of eHealth. Mobile applications for health have the potential to target heterogeneous audiences and address specific needs in different situations, with diverse outcomes, and to complement highly developed health care technologies. The market is rapidly evolving, making countless new mobile technologies potentially available to the health care system; however, systematic research on the impact of these technologies on health outcomes remains scarce. Objective To provide a comprehensive view of the field of mHealth research to date and to understand whether and how the new generation of smartphones has triggered research, since their introduction 5 years ago. Specifically, we focused on studies aiming to evaluate the impact of mobile phones on health, and we sought to identify the main areas of health care delivery where mobile technologies can have an impact. Methods A systematic literature review was conducted on the impact of mobile phones and smartphones in health care. Abstracts and articles were categorized using typologies that were partly adapted from existing literature and partly created inductively from publications included in the review. Results The final sample consisted of 117 articles published between 2002 and 2012. The majority of them were published in the second half of our observation period, with a clear upsurge between 2007 and 2008, when the number of articles almost doubled. The articles were published in 77 different journals, mostly from the field of medicine or technology and medicine. Although the range of health conditions addressed was very wide, a clear focus on chronic conditions was noted. The research methodology of these studies was mostly clinical trials and pilot studies, but new designs were introduced in the second half of our observation period. The size of the samples drawn to test mobile health applications also increased over time. The majority of the studies tested basic mobile phone features (eg, text messaging), while only a few assessed the impact of smartphone apps. Regarding the investigated outcomes, we observed a shift from assessment of the technology itself to assessment of its impact. The outcome measures used in the studies were mostly clinical, including both self-reported and objective measures. Conclusions Research interest in mHealth is growing, together with an increasing complexity in research designs and aim specifications, as well as a diversification of the impact areas. However, new opportunities offered by new mobile technologies do not seem to have been explored thus far. Mapping the evolution of the field allows a better understanding of its strengths and weaknesses and can inform future developments.
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              MARKING TIME: PREDICTABLE TRANSITIONS IN TASK GROUPS.

              C. Gersick (1989)
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                Author and article information

                Contributors
                Sarah Ann Mummah:
                Stanford Prevention Research CenterDepartment of MedicineStanford University School of Medicine1265 Welch RoadStanford, CA, 94305-5411United States1 650 723 78221 650 725 6247sm885@cam.ac.uk
                ORCID: http://orcid.org/0000-0001-9154-4510
                Journal
                Journal ID (nlm-ta): J Med Internet Res
                Journal ID (iso-abbrev): J. Med. Internet Res
                Journal ID (publisher-id): JMIR
                Title: Journal of Medical Internet Research
                Publisher: JMIR Publications (Toronto, Canada )
                ISSN (Print): 1439-4456
                ISSN (Electronic): 1438-8871
                Publication date Collection: December 2016
                Publication date (Electronic): 16 December 2016
                Volume: 18
                Issue: 12
                Electronic Location Identifier: e317
                Affiliations
                [1] 1Stanford Prevention Research Center Department of Medicine Stanford University School of Medicine Stanford, CAUnited States
                [2] 2Behavioural Science Group Institute of Public Health University of Cambridge CambridgeUnited Kingdom
                [3] 3Stanford Solutions Science Lab Department of Pediatrics Stanford University School of Medicine Stanford, CAUnited States
                [4] 4Division of Epidemiology Department of Health Research & Policy Stanford, CAUnited States
                Author notes
                Corresponding Author: Sarah Ann Mummah sm885@ 123456cam.ac.uk
                Author information
                http://orcid.org/0000-0001-9154-4510
                http://orcid.org/0000-0002-2367-0774
                http://orcid.org/0000-0002-7949-8811
                http://orcid.org/0000-0002-7596-1530
                http://orcid.org/0000-0003-1610-0404
                Article
                Publisher ID: v18i12e317
                DOI: 10.2196/jmir.5927
                PMC ID: 5203679
                PubMed ID: 27986647
                SO-VID: 275aa79b-f1b2-4a6d-a7d2-92290f980609
                Copyright © ©Sarah Ann Mummah, Thomas N Robinson, Abby C King, Christopher D Gardner, Stephen Sutton. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.12.2016.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                Date received : 3 May 2016
                Date revision requested : 16 June 2016
                Date revision received : 25 September 2016
                Date accepted : 12 October 2016
                Categories
                Subject: Viewpoint
                Subject: Viewpoint

                ScienceOpen disciplines: Medicine
                Keywords: health behavior,design thinking,user-centered design,behavioral theory,behavior change techniques,digital interventions,mobile phones,digital health,telemedicine,diet,exercise,weight loss,smoking cessation,medication adherence,sleep,obesity
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: health behavior, design thinking, user-centered design, behavioral theory, behavior change techniques, digital interventions, mobile phones, digital health, telemedicine, diet, exercise, weight loss, smoking cessation, medication adherence, sleep, obesity

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