Transpersonal Psychology as a Human Science
Introduction to Transpersonal Psychology November 26, 2021 DOI: 10.4324/9781003196068-6 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that Transpersonal Psychology employs distinct inquiry methods and faces unique ethical and methodological challenges, and that it should be considered a human science rather than a natural science. Highlights limitations in transpersonal testing and assessment, such as issues with conceptual clarity, sample representativeness, and replication, and offers recommendations for improvement. |
Abstract
The focus of this chapter is on Transpersonal Psychology as a scientific field, the methods of disciplined inquiry used to investigate transpersonal experiences and human transformative capacity, and transpersonal testing and assessment. The first part of the chapter begins by examining three transpersonal methods of disciplined inquiry—Integral Inquiry, Intuitive Inquiry, Organic Inquiry—and how these methods differ from more traditional research approaches. It then explores how issues related to the trustworthiness and credibility of the research findings in transpersonal inquiry are addressed. The chapter then examines the hidden assumptions behind the research in Transpersonal Psychology and the special ethical challenges that accompany the use of transpersonal research methods and the study of transpersonal phenomena. The second part of the chapter explores why Transpersonal Psychology is not a traditional physical or natural science but is a basic, translational, and applied human science. This is followed by an examination of the strengths and limitations of transpersonal testing and assessment. This includes issues related to conceptual clarity and operationalization of variables, building a cumulative knowledge base, sample representativeness, internal validity, cross-cultural generalizability, verbal reports as data, and replications of results. The chapter ends by briefly exploring recommendations for improvements.