Learning From Mistakes: Impact of Careless Responses on Counseling Research Using Amazon’s Mechanical Turk

Abstract

We investigated the effect of careless or insufficient effort (C/IE) responses in a study using Amazon’s Mechanical Turk. A factor mixture model was used to identify latent classes based on the pattern of responses with biases and examine the effect of C/IE responses on the fit of the theoretical model.

Keywords:

• Careless responses
• insufficient effort responses
• data cleaning
• M-Turk
• factor mixture modeling
• Mechanical Turk

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Nayoung Kim

Nayoung Kim, PhD, is a tenure-earning assistant professor in the counselor education program at New York Institute of Technology and a National Certified Counselor (NCC). She earned her doctoral degree in counselor education at the University of Central Florida and master’s degree in educational counseling at Seoul National University. She is currently working on multiple projects regarding counselor education, counselor wellness, and multicultural counseling competencies. Dr. Kim has experience providing counseling services to diverse client populations and supervised counselors-in-training in school and community-based mental health settings.

JungSu Oh

JungSu Oh, PhD, is an assistant professor in the department of psychology at the Eastern Illinois University.