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Posted on Dec 28, 2017 in Perspective Pieces | 0 comments

Theory Driven Mobile-Based Interventions: A Scoping Review

Theory Driven Mobile-Based Interventions: A Scoping Review

Jenna Brager, PhDc, BSN-RN, MS1, Melissa Pinto, PhD2, RN, FAAN, Adam Kaplin, MD, PhD3

1Johns Hopkins University, School of Nursing, Baltimore, MD, USA
2Emory University, Nell Hodgson Woodruff School of Nursing and Rollins School of Public Health
3Johns Hopkins University, School of Medicine, Baltimore, MD, USA

Corresponding Author: Melissa.d.pinto@emory.edu

Journal MTM 6:3:48–65, 2017

doi:10.7309/jmtm.6.3.8


Background: Mobile technology is a rapidly evolving field allowing healthcare providers to reach patients outside of a traditional face-to-face setting. Fortunately, interventions are now becoming readily available via mobile devices such as mobile phones, smart phones, and tablets, yet there has been little attention to the design of these interventions so that they are theoretically-driven (informed according to a behavioral theory or model) and ethically performed.

Objective: To provide data on theoretically-driven interventions that were empirically tested and to analyze the features and strategies used to implement these interventions.

Review Methods: This study employed a scoping review methodology according to the Joann Briggs Institute. An electronic database search yielded 20 eligible articles.

Results: The participants spanned various health domains: cardiovascular (weight control, physical activity, diabetes), cancer (pap testing), prenatal care, substance use (alcohol recovery, smoking cessation), and HIV and/or sexual risk assessment. Social Cognitive Theory, Health Belief Model, and Transtheoretical Model were applied most frequently to guide interventions.

Conclusion: Future work should focus on the application of theory and how various implementation techniques translate to the overall effectiveness of the intervention.

Keywords: mobile technology; theory; model; mhealth; mobile application; text-messaging


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Posted on Apr 21, 2017 in Perspective Pieces | 0 comments

Perspectives Piece: Realizing the Potential for Digital Health Technology in Behavioral Medicine

Perspectives Piece: Realizing the Potential for Digital Health Technology in Behavioral Medicine

Brandon S. Aylward, Ph.D.1, Timothy D. Nelson, Ph.D.2, Kevin A. Hommel, Ph.D.3

1Emory University School of Medicine, Department of Pediatrics, Atlanta, GA; 2University of Nebraska-Lincoln, Department of Psychology, Lincoln, NE; 3Cincinnati Children’s Hospital Medical Center, Division of Behavioral Medicine and Clinical Psychology, Cincinnati, OH

Corresponding Author: baylwar@emory.edu

Journal MTM 6:1:46–48, 2017

doi:10.7309/jmtm.6.1.7


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Posted on Apr 21, 2017 in Perspective Pieces | 0 comments

“The BUS Framework: A comprehensive tool in creating an mHealth App utilizing Behavior Change Theories, User-Centered Design, and Social Marketing”

“The BUS Framework: A comprehensive tool in creating an mHealth App utilizing Behavior Change Theories, User-Centered Design, and Social Marketing”

Sajani Patel1, Monisha Arya2,3,4

1School of Social Sciences, Rice University, Houston, Texas; 2Department of Medicine Section of Infectious Diseases, Baylor College of Medicine, Houston, TX; 3Department of Medicine Section of Health Services Research, Baylor College of Medicine, Houston, Texas; 4Center for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey VA Medical Center, Houston, Texas

Corresponding Author: sajani.patel@alumni.rice.edu

Journal MTM 6:1:39–45, 2017

doi:10.7309/jmtm.6.1.6


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Posted on Apr 21, 2017 in Perspective Pieces | 0 comments

mHealth: Vehicle for Health System Strengthening in Sri Lanka

mHealth: Vehicle for Health System Strengthening in Sri Lanka

Dr. Madapathage Gayan Buddhika Senanayake, MBBS, MD1, Dr. Gunasena Sunil Senanayake, MBBS, MD2

1Junior Public Health Professional – Health System Management, Department of Health System Development, South East Asian Regional Office for World Health Organization, New Delhi, India; 2Regional Advisor – Health System Management and Patient Safety, Department of Health System Development, South East Asian Regional Office for World Health Organization, New Delhi, India

Corresponding Author: buddhikaoffice@gmail.com

Journal MTM 6:1:34–38, 2017

doi:10.7309/jmtm.6.1.5


Sri Lanka has a unique primary healthcare system with diverse community based healthcare services. Emerging health challengers in sustainable development era needs to be addressed with special emphasis on universal health coverage.

mHealth technology is an evidence based intervention to cater the novel healthcare priorities. mHealth needs to be integrated into the existing health system functions, rather stand-alone resolutions. mHealth applications are used for behaviour change communication, point-of-care diagnosis, vital event registration, data collection, electronic health records, provider-to-provider communication, human resource management and supply chain management initiatives. Incorporating these mHealth interventions at community level are essential in resolving future health challengers in Sri Lanka.


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Posted on Jul 28, 2016 in Perspective Pieces | 0 comments

The Future of Automated Mobile Eye Diagnosis

Cassie A. Ludwig, BS1, Mia X. Shan, BS, BAH1, Nam Phuong H. Nguyen1, Daniel Y. Choi, MD1, Victoria Ku, BS1, Carson K. Lam, MD1

1Byers Eye Institute, Stanford University School of Medicine 2405 Watson Drive, Palo Alto, CA, USA 94305

Corresponding Author: carsonl@stanford.edu

Journal MTM 5:2:44–50, 2016

doi: 10.7309/jmtm.5.2.7


The current model of ophthalmic care requires the ophthalmologist’s involvement in data collection, diagnosis, treatment planning, and treatment execution. We hypothesize that ophthalmic data collection and diagnosis will be automated through mobile devices while the education, treatment planning, and fine dexterity tasks will continue to be performed at clinic visits and in the operating room by humans. Comprehensive automated mobile eye diagnosis includes the following steps: mobile diagnostic tests, image collection, image recognition and interpretation, integrative diagnostics, and user-friendly, mobile platforms. Completely automated mobile eye diagnosis will require improvements in each of these components, particularly image recognition and interpretation and integrative diagnostics. Once polished and integrated into greater medical practice, automated mobile eye diagnosis has the potential to increase access to ophthalmic care with reduced costs, increased efficiency, and increased accuracy of diagnosis.


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