Abstract

BackgroundThe widespread availability and cost-effectiveness of new-wave software-based audience response systems (ARSs) have expanded the possibilities of collecting health data from hard-to-reach populations, including youth. However, with all survey methods, biases in the data may exist because of participant nonresponse.ObjectiveThe aims of this study were to (1) examine the extent to which an ARS could be used to gather health information from youths within a large-group school setting and (2) examine individual- and survey-level response biases stemming from this Web-based data collection method.MethodsWe used an ARS to deliver a mental health survey to 3418 youths in 4 high schools in the Midwestern United States. The survey contained demographic questions, depression, anxiety, and suicidality screeners, and questions about their use of offline resources (eg, parents, peers, and counselors) and Web-based resources (ie, telemental health technologies) when they faced stressful life situations. We then examined the response rates for each survey item, focusing on the individual- and survey-level characteristics that related to nonresponse.ResultsOverall, 25.39% (868/3418) of youths answered all 38 survey questions; however, missingness analyses showed that there were some survey structure factors that led to higher rates of nonresponse (eg, questions at the end of survey, sensitive questions, and questions for which precise answers were difficult to provide). There were also some personal characteristics that were associated with nonresponse (eg, not identifying as either male or female, nonwhite ethnicity, and higher levels of depression). Specifically, a multivariate model showed that male students and students who reported their gender as other had significantly higher numbers of missed items compared with female students (B=.30 and B=.47, respectively, P<.001). Similarly, nonwhite race (B=.39, P<.001) and higher depression scores (B=.39, P<.001) were positively related to the number of missing survey responses.ConclusionsAlthough our methodology-focused study showed that it is possible to gather sensitive mental health data from youths in large groups using ARSs, we also suggest that these nonresponse patterns need to be considered and controlled for when using ARSs for gathering population health data.

Highlights

  • Audience response systems (ARSs) are hardware- or software-based systems that allow presenters to interact with participants in real time, with audience members responding to questions posed by the presenter on handheld devices, and, in most cases, having their anonymous answers displayed on screen to the entire audience

  • 3418 high school students participated in the survey events

  • Response rate was not measured in this study, we were able to gather health data from a wide variety of youths with different socioeconomic and mental health backgrounds

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Summary

Introduction

BackgroundAudience response systems (ARSs) are hardware- or software-based systems that allow presenters to interact with participants in real time, with audience members responding to questions posed by the presenter on handheld devices, and, in most cases, having their anonymous answers displayed on screen to the entire audience. The latest versions of ARSs (eg, Mentimeter and TurningPoint) are cloud software-based programs that allow for audience members to respond via their own connected devices, such as phones, tablets, or laptops This transition from hardware- to software-based ARSs has increased the accessibility of these systems, expanding the possibilities of interactive education and real-time data gathering beyond traditional education environments. Objective: The aims of this study were to (1) examine the extent to which an ARS could be used to gather health information from youths within a large-group school setting and (2) examine individual- and survey-level response biases stemming from this Web-based data collection method. Conclusions: our methodology-focused study showed that it is possible to gather sensitive mental health data from youths in large groups using ARSs, we suggest that these nonresponse patterns need to be considered and controlled for when using ARSs for gathering population health data

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