Mobile Health Technology Evaluation

Abstract

Creative use of new mobile and wearable health information and sensing technologies (mHealth) has the potential to reduce the cost of health care and improve well-being in numerous ways. These applications are being developed in a variety of domains, but rigorous research is needed to examine the potential, as well as the challenges, of utilizing mobile technologies to improve health outcomes. Currently, evidence is sparse for the efficacy of mHealth. Although these technologies may be appealing and seemingly innocuous, research is needed to assess when, where, and for whom mHealth devices, apps, and systems are efficacious. In order to outline an approach to evidence generation in the field of mHealth that would ensure research is conducted on a rigorous empirical and theoretic foundation, on August 16, 2011, researchers gathered for the mHealth Evidence Workshop at NIH. The current paper presents the results of the workshop. Although the discussions at the meeting were cross-cutting, the areas covered can be categorized broadly into three areas: (1) evaluating assessments; (2) evaluating interventions; and, (3) reshaping evidence generation using mHealth. This paper brings these concepts together to describe current evaluation standards, future possibilities and set a grand goal for the emerging field of mHealth research.

Engaging research participants to inform the ethical conduct of mobile imaging, pervasive sensing, and location tracking research

“…Public health researchers are utilizing mobile imaging, pervasive sensing, social media, and location tracking technologies, what we refer to as BMISST,^to measure every day behaviors of research participants in their natural environment [1]. These tools (i.e., devices and phone apps) are worn or carried by participants to objectively measure behavior in context [1][2][3][4][5][6][7].…”

“…These tools (i.e., devices and phone apps) are worn or carried by participants to objectively measure behavior in context [1][2][3][4][5][6][7]. The purpose of location logging, for example, is to assess spatial predictors of behaviors [2,3].…”

A smartphone-based consultation system for acute burns – methodological challenges related to follow-up of the system

“…However, the design has a range of ethical and practical implications. First, the time lag between recruiting the patients and the outcome of the study in a randomized controlled trial may be critical since the technology might be out-of-date before the trial is finalized [11]. Secondly, it is debatable whether it is ethical to introduce randomization of a diagnostic support system in the acute phase of a burn.…”

“…Thirdly, the cost of extensive data collection has to balance out the benefit of the system, especially in an already strained health system [12]. Alternative study designs that can be considered are interrupted time-series or historical cohort design [11]. …”

A framework design for the mHealth system for self-management promotion

“…Mobile health (mHealth) is a novel technology that supports self-management to improve health care outcomes [1]. It integrates the technologies of electronics, sensors, mobile computing, communication and medical services [2,3].…”