Using Mobile Technologies for Qualitative Data Collection: A Multiple-Case Study

Background and Purpose. Technology has emerged as a useful data analysis tool among qualitative researchers, but emerging research suggests that new technologies may address common challenges to qualitative data collection as well, such as distance from participants or the time-intensive nature of the process. In addition, mobile technologies like tablets and smartphones may empower research participants to report experiences in real-time. To date, though, scant literature documents best practices for using mobile technologies to gather qualitative data. The following case study explores the implementation of a custom-designed app to study transportation vulnerability among transportation-disadvantaged populations. Our research questions center on how participants used the app to report qualitative data, and challenges with design and implementation.

Methods. This study utilizes a multiple-case study design with two older adult participants. (Both participants are Caucasian; the female participant was 72-years-old and the male participant was 68-years-old.) The data were collected as part of a pilot study testing the feasibility of using a tablet-based app to collect longitudinal data through an ecological momentary assessment design. Qualitative data included: 1) a real-time text messaging feature embedded in the app, and 2) user-feedback surveys using a web-based tool. The text-messaging feature included six interview questions across three domains of transportation-based social exclusion. One author sent the participants the questions via text messages across two weeks. The user feedback surveys collected data related to participants’ experiences with the app. To encourage responses, one author regularly contacted the participants and provided instruction and support as needed. For the purposes of this study, the authors utilize qualitative content analysis of the user feedback survey, as well as data related to their frequency of using the text-messaging feature, to answer the research questions.

Results. Participants demonstrated noticeable differences in acceptance and use. The first participant used the text-messaging feature regularly. He was an experienced mobile-device user and found the feature easy to use. On average, he responded to a text message in five minutes, but he did note occasional technological and design difficulties that inhibited his full acceptance of the technology. The second participant used the text messaging feature less consistently, citing unfamiliarity with mobile devices. She reported that regular contact with the researcher was her favorite feature of the app because of the social interaction it provided. For both participants, app features related to ongoing researcher contact helped them remain engaged with the project.

Conclusions and Implications. While the use of technology may mitigate common qualitative data collection challenges, researchers may encounter new challenges related to participants’ technology acceptance. This case study involved older adults, however, and younger participants may report higher levels of baseline technology acceptance. Still, researchers may maximize the effectiveness of technology for collecting qualitative data by borrowing from the tenets of the Technology Acceptance Model and ensuring ongoing, meaningful social interactions between participants and researchers. Although this case study is exploratory in nature, results point towards best practices for developing and implementing novel, tech-based qualitative data collection tools for various scientific inquiries.