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Quantifying App Store Dynamics: Longitudinal Tracking of Mental Health Apps

Quantifying App Store Dynamics: Longitudinal Tracking of Mental Health Apps

(b) This process is repeated for each day of the study, shown as different-colored time series (only 4 used to illustrate). (c) The time series shifted to begin at a common time point, such that the day of the search equals day 1.

Mark Erik Larsen, Jennifer Nicholas, Helen Christensen

JMIR Mhealth Uhealth 2016;4(3):e96


Metadata Correction: Direct Adherence Measurement Using an Ingestible Sensor Compared With Self-Reporting in High-Risk Cardiovascular Disease Patients Who Knew They Were Being Measured: Prospective Intervention

Metadata Correction: Direct Adherence Measurement Using an Ingestible Sensor Compared With Self-Reporting in High-Risk Cardiovascular Disease Patients Who Knew They Were Being Measured: Prospective Intervention

Thompson et al, “Direct Adherence Measurement Using an Ingestible Sensor Compared With Self-Reporting in High-Risk Cardiovascular Disease Patients Who Knew They Were Being Measured: A Prospective Intervention” (JMIR Mhealth Uhealth 2017;5(6):e76), author Nicholas

David Thompson, Teresa Mackay, Maria Matthews, Judith Edwards, Nicholas S Peters, Susan B Connolly

JMIR Mhealth Uhealth 2018;6(4):e13