A Comparative Analysis of Data Quality in Online Zoom Versus Phone Interviews

An Example of Youth With and Without Disabilities

Dados Bibliográficos

ID4181870
AutoresSally Lindsay (0000-0002-5903-290X, University of Toronto, autor correspondente)
Ano2022
Volume12
Fascículo4
Data de publicação2022-10-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoSAGE Open (JOURNAL)
Identificadores do periódicoISSN: 2158-2440 • E-ISSN: 2158-2440
EditoraSAGE Publications Inc (PUBLISHER)
DOI10.1177/21582440221140098
OpenAlexW4312441025
IdiomaEN
Citações recebidas8
Referências citadas34

Qualitative researchers are increasingly using online data collection methods, especially during the COVID-19 pandemic. I compared the data quality (i.e., interview duration, average number of themes and sub-themes, and inaudible words) of 34 interviews (29 conducted by Zoom (16 with camera on, 13 camera off) and 5 conducted by phone) drawn from a study focusing on youth's coping experiences during the pandemic. Findings showed that phone interviews had a longer duration compared to Zoom. However, phone interviews had a similar average word count to Zoom interviews (with the camera on). Zoom interviews conducted with the camera off were shorter in duration than interviews with the camera on. The number of themes was similar across the different interview formats but there were fewer sub-themes for Zoom interviews with the camera off. The findings suggest that Zoom interviews conducted with the camera off could affect the data quality. This research also emphasizes the importance of giving participants choice in the format of their interview to allow for optimal sharing of experiences while enhancing the equity, diversity and inclusion of the participants

Camera phone · Data collection · Phone · Qualitative property · Qualitative research · Semi-structured interview · Sociology · Zoom · Applied Psychology · Computer Science · Engineering · Focus Groups and Qualitative Methods · Psychology · Social Media and Politics · Telemedicine and Telehealth Implementation · Artificial Intelligence