Recruiting diverse participants for NeuroIS studies is a major research challenge. The requirement for physical participation in NeuroIS labs poses geographical, physical, and financial barriers to many equity deserving groups, such as older adults, people with disabilities, and patients with mental or physical diseases. As a result, many such equity deserving user groups are excluded from NeuroIS research and are consequently unable to inform the research and development of technologies. This is extremely unfortunate, since their input would inform the designs of technologies that can potentially improve the quality of their lives, if they are afforded an equitable opportunity to partake in NeuroIS research activities. We present a case where these challenges were faced by our research team. We propose two potential solutions to tackle this significant Equity, Diversity, and Inclusion (EDI) challenge: (1) mobile NeuroIS labs; and (2) data collection in the field.

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Recruitment and EDI Challenges in NeuroIS Research: A Case for Mobile Research Infrastructure

  • Nour El Shamy,
  • Khaled Hassanein,
  • Milena Head

摘要

Recruiting diverse participants for NeuroIS studies is a major research challenge. The requirement for physical participation in NeuroIS labs poses geographical, physical, and financial barriers to many equity deserving groups, such as older adults, people with disabilities, and patients with mental or physical diseases. As a result, many such equity deserving user groups are excluded from NeuroIS research and are consequently unable to inform the research and development of technologies. This is extremely unfortunate, since their input would inform the designs of technologies that can potentially improve the quality of their lives, if they are afforded an equitable opportunity to partake in NeuroIS research activities. We present a case where these challenges were faced by our research team. We propose two potential solutions to tackle this significant Equity, Diversity, and Inclusion (EDI) challenge: (1) mobile NeuroIS labs; and (2) data collection in the field.