| Title |
Simplified Novel Application (SNApp) framework: a guide to developing and implementing second-generation mobile applications for behavioral health research
|
|---|---|
| Published in |
Translational Behavioral Medicine, December 2015
|
| DOI | 10.1007/s13142-015-0363-7 |
| Pubmed ID | |
| Authors |
Jennifer Fillo, B. Lynette Staplefoote-Boynton, Angel Martinez, Lisa Sontag-Padilla, William G. Shadel, Steven C. Martino, Claude M. Setodji, Daniella Meeker, Deborah Scharf |
| Abstract |
Advances in mobile technology and mobile applications (apps) have opened up an exciting new frontier for behavioral health researchers, with a "second generation" of apps allowing for the simultaneous collection of multiple streams of data in real time. With this comes a host of technical decisions and ethical considerations unique to this evolving approach to research. Drawing on our experience developing a second-generation app for the simultaneous collection of text message, voice, and self-report data, we provide a framework for researchers interested in developing and using second-generation mobile apps to study health behaviors. Our Simplified Novel Application (SNApp) framework breaks the app development process into four phases: (1) information and resource gathering, (2) software and hardware decisions, (3) software development and testing, and (4) study start-up and implementation. At each phase, we address common challenges and ethical issues and make suggestions for effective and efficient app development. Our goal is to help researchers effectively balance priorities related to the function of the app with the realities of app development, human subjects issues, and project resource constraints. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 1% |
| Unknown | 68 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 25% |
| Researcher | 9 | 13% |
| Student > Ph. D. Student | 7 | 10% |
| Student > Bachelor | 5 | 7% |
| Professor > Associate Professor | 3 | 4% |
| Other | 9 | 13% |
| Unknown | 19 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 16% |
| Computer Science | 10 | 14% |
| Nursing and Health Professions | 8 | 12% |
| Psychology | 5 | 7% |
| Business, Management and Accounting | 4 | 6% |
| Other | 10 | 14% |
| Unknown | 21 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 December 2015.
All research outputs
#13,465,399
of 22,994,508 outputs
Outputs from Translational Behavioral Medicine
#601
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Outputs of similar age
#185,996
of 388,522 outputs
Outputs of similar age from Translational Behavioral Medicine
#16
of 28 outputs
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