Abstract
Objective: This systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform. Materials and Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants. Results: Thirty-six unique ResearchKit apps were identified. The majority of the apps were used to conduct observational studies on general citizens and generate large datasets for secondary research. Nearly half of the apps were focused on chronic conditions in adults. Discussion: The ability to generate large biomedical datasets on diverse populations that can be broadly shared and re-used was identified as a promising feature of mHealth research apps. Common challenges were low participation retention, uncertainty regarding how use patterns influence data quality, need for data validation, and privacy concerns. Conclusion: ResearchKit and other mHealth-based studies are well positioned to enhance development and validation of novel digital biomarkers as well as generate new biomedical knowledge through retrospective studies. However, in order to capitalize on these benefits, mHealth research studies must strive to improve retention rates, implement rigorous data validation strategies, and address emerging privacy and security challenges.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1685-1695 |
| Number of pages | 11 |
| Journal | Journal of the American Medical Informatics Association : JAMIA |
| Volume | 25 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 1 2018 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Health Informatics
Cite this
Leveraging mobile health applications for biomedical research and citizen science : a scoping review. / Schmitz, Hannah; Howe, Carol L.; Armstrong, David G; Subbian, Vignesh.
In: Journal of the American Medical Informatics Association : JAMIA, Vol. 25, No. 12, 01.12.2018, p. 1685-1695.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Leveraging mobile health applications for biomedical research and citizen science
T2 - a scoping review
AU - Schmitz, Hannah
AU - Howe, Carol L.
AU - Armstrong, David G
AU - Subbian, Vignesh
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Objective: This systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform. Materials and Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants. Results: Thirty-six unique ResearchKit apps were identified. The majority of the apps were used to conduct observational studies on general citizens and generate large datasets for secondary research. Nearly half of the apps were focused on chronic conditions in adults. Discussion: The ability to generate large biomedical datasets on diverse populations that can be broadly shared and re-used was identified as a promising feature of mHealth research apps. Common challenges were low participation retention, uncertainty regarding how use patterns influence data quality, need for data validation, and privacy concerns. Conclusion: ResearchKit and other mHealth-based studies are well positioned to enhance development and validation of novel digital biomarkers as well as generate new biomedical knowledge through retrospective studies. However, in order to capitalize on these benefits, mHealth research studies must strive to improve retention rates, implement rigorous data validation strategies, and address emerging privacy and security challenges.
AB - Objective: This systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform. Materials and Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants. Results: Thirty-six unique ResearchKit apps were identified. The majority of the apps were used to conduct observational studies on general citizens and generate large datasets for secondary research. Nearly half of the apps were focused on chronic conditions in adults. Discussion: The ability to generate large biomedical datasets on diverse populations that can be broadly shared and re-used was identified as a promising feature of mHealth research apps. Common challenges were low participation retention, uncertainty regarding how use patterns influence data quality, need for data validation, and privacy concerns. Conclusion: ResearchKit and other mHealth-based studies are well positioned to enhance development and validation of novel digital biomarkers as well as generate new biomedical knowledge through retrospective studies. However, in order to capitalize on these benefits, mHealth research studies must strive to improve retention rates, implement rigorous data validation strategies, and address emerging privacy and security challenges.
UR - http://www.scopus.com/inward/record.url?scp=85058596401&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058596401&partnerID=8YFLogxK
U2 - 10.1093/jamia/ocy130
DO - 10.1093/jamia/ocy130
M3 - Article
C2 - 30445467
AN - SCOPUS:85058596401
VL - 25
SP - 1685
EP - 1695
JO - Journal of the American Medical Informatics Association : JAMIA
JF - Journal of the American Medical Informatics Association : JAMIA
SN - 1067-5027
IS - 12
ER -