Toscos T, Drouin M, Flanagan M, Carpenter M, Kerrigan C, Carpenter C, Mere C, Haaff M. Audience Response Systems and Missingness Trends: Using Interactive Polling Systems to Gather Sensitive Health Information From Youth.
JMIR Form Res 2019;
3:e13798. [PMID:
31313658 PMCID:
PMC6664663 DOI:
10.2196/13798]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 05/08/2019] [Accepted: 05/16/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND
The 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.
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.
METHODS
We 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.
RESULTS
Overall, 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.
CONCLUSIONS
Although 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.
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