This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (2219) e-Mental Health and Cyberpsychology (1116)

Published on in Vol 15 , No 7 (2013) :July

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Authors of this article:

John D Piette 1 ;   Jeremy B Sussman 1 ;   Paul N Pfeiffer 2 ;   Maria J Silveira 1 ;   Satinder Singh 3 ;   Mariel S Lavieri 4
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