Abstract

BackgroundInternet and mobile health (mHealth) apps hold promise for expanding the reach of evidence-based health interventions. Research in this area is rapidly expanding. However, these studies may experience problems with recruitment and retention. Web-based and mHealth studies are in need of a wide-reaching and low-cost method of recruitment that will also effectively retain participants for the duration of the study. Online recruitment may be a low-cost and wide-reaching tool in comparison to traditional recruitment methods, although empirical evidence is limited.ObjectiveThis study aims to review the literature on online recruitment for, and retention in, mHealth studies.MethodsWe conducted a review of the literature of studies examining online recruitment methods as a viable means of obtaining mHealth research participants. The data sources used were PubMed, CINAHL, EbscoHost, PyscINFO, and MEDLINE. Studies reporting at least one method of online recruitment were included. A narrative approach enabled the authors to discuss the variability in recruitment results, as well as in recruitment duration and study design.ResultsFrom 550 initial publications, 12 studies were included in this review. The studies reported multiple uses and outcomes for online recruitment methods. Web-based recruitment was the only type of recruitment used in 67% (8/12) of the studies. Online recruitment was used for studies with a variety of health domains: smoking cessation (58%; 7/12) and mental health (17%; 2/12) being the most common. Recruitment duration lasted under a year in 67% (8/12) of the studies, with an average of 5 months spent on recruiting. In those studies that spent over a year (33%; 4/12), an average of 17 months was spent on recruiting. A little less than half (42%; 5/12) of the studies found Facebook ads or newsfeed posts to be an effective method of recruitment, a quarter (25%; 3/12) of the studies found Google ads to be the most effective way to reach participants, and one study showed better outcomes with traditional (eg in-person) methods of recruitment. Only one study recorded retention rates in their results, and half (50%; 6/12) of the studies recorded survey completion rates.ConclusionsAlthough online methods of recruitment may be promising in experimental research, more empirical evidence is needed to make specific recommendations. Several barriers to using online recruitment were identified, including participant retention. These unique challenges of virtual interventions can affect the generalizability and validity of findings from Web-based and mHealth studies. There is a need for additional research to evaluate the effectiveness of online recruitment methods and participant retention in experimental mHealth studies.

Highlights

  • CDC Health Disparities and Inequalities Report — United States, 2013Pamela A

  • When data were available and suitable analyses were possible for the topic area, disparities were examined for population characteristics that included race and ethnicity, sex, sexual orientation, age, disability, socioeconomic status, and geographic location

  • In the 2011 population aged ≥25 years, statistically significant absolute disparities in noncompletion of high school were identified for all the characteristics studied (Table 1)

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Summary

Introduction

CDC Health Disparities and Inequalities Report — United States, 2013Pamela A. CDC Health Disparities and Inequalities Report — United States, 2013. The factors that influence the socioeconomic position of individuals and groups within industrial societies influence their health [1,2]. Socioeconomic position has continuous and graded effects on health that are cumulative over a lifetime. The socioeconomic conditions of the places where persons live and work have an even more substantial influence on health than personal socioeconomic position [3,4]. In the United States, educational attainment and income are the indicators that are most commonly used to measure the effect of socioeconomic position on health. Research indicates that substantial educational and income disparities exist across many measures of health [1,5,6,7,8]. Notable disparities defined by race/ethnicity, socioeconomic factors, disability status, and geographic location were identified for 2005 and 2009, with no evidence of a temporal decrease in racial/ethnic disparities, whereas socioeconomic and disability disparities increased from 2005 to 2009

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