Data handling: ethical principles, guidelines, and recommended practices
Kaplan, Brent A., Gilroy, Shawn P., DeHart, W. Brady, Brown, Jeremiah M., and Koffarnus, Mikahil N. (2023)
Abstract:
Ethical data handling practices are an important—yet often overlooked—aspect of clinical work and research conduct. In this chapter, we briefly describe legal considerations, types of data commonly encountered by behavior analysts (e.g., highly sensitive data, potentially sensitive data, not very sensitive data), and considerations for data collection (e.g., paper, electronic) and storage. We then identify strategies for data validation, analysis, and dissemination. Behavior analysts in clinical and research settings should consider how their organizational data handling practices reflect their ethical duty toward their clients' or research participants' right to confidentiality. Specifically, behavior analysts should arrange environments that increase the likelihood of compliance with ethical data handling practices. For example, research or clinical staff should be trained on the proper use of data collection tools, data should be stored using secure and redundant systems, and work-flow systems should be designed to ensure data validation. Finally, data analysis methods should be free of bias, reproducible, and shareable, enabling other scientists to recreate analyses using deidentified datasets.
Ethical data handling practices are an important—yet often overlooked—aspect of clinical work and research conduct. In this chapter, we briefly describe legal considerations, types of data commonly encountered by behavior analysts (e.g., highly sensitive data, potentially sensitive data, not very sensitive data), and considerations for data collection (e.g., paper, electronic) and storage. We then identify strategies for data validation, analysis, and dissemination. Behavior analysts in clinical and research settings should consider how their organizational data handling practices reflect their ethical duty toward their clients' or research participants' right to confidentiality. Specifically, behavior analysts should arrange environments that increase the likelihood of compliance with ethical data handling practices. For example, research or clinical staff should be trained on the proper use of data collection tools, data should be stored using secure and redundant systems, and work-flow systems should be designed to ensure data validation. Finally, data analysis methods should be free of bias, reproducible, and shareable, enabling other scientists to recreate analyses using deidentified datasets.
Citation:
Kaplan, Brent A., Gilroy, Shawn P., DeHart, W. Brady, Brown, Jeremiah M., and Koffarnus, Mikahil N. (2023). Data handling: ethical principles, guidelines, and recommended practices. Research Ethics in Behavior Analysis, undefined. 191–214
Kaplan, Brent A., Gilroy, Shawn P., DeHart, W. Brady, Brown, Jeremiah M., and Koffarnus, Mikahil N. (2023). Data handling: ethical principles, guidelines, and recommended practices. Research Ethics in Behavior Analysis, undefined. 191–214