Frontiers in psychology
January 1, 2025
David Martínez-pernía, Alejandro Troncoso, Sergio E Chaigneau et al.
4 citations
ChatGPT can process large qualitative datasets for phenomenological analysis while preserving depth and nuance. The tool follows four stages: preparing phenomenological data, individual analysis highlighting experiential nuances, global analysis synthesizing narratives, and structuring shared experience components. Custom prompts ensure alignment and precision. ChatGPT organizes themes reflecting sensation intensity and variations in empathetic encounters, transforming raw input into detailed phenomenological accounts. Its proficiency combines precision with scalability for consciousness studies. Further research is needed to understand AI's capacity in phenomenological analysis and strengthen the methodological framework.
June 2, 2026
Alejandro Troncoso, Antonia Zepeda, David Martínez-pernía
preprint
Neurophenomenology aims to combine first-person subjective experience with third-person neurobiological measures but still lacks integrated, reproducible workflows. This article introduces Experimental Phenomenological Analysis (EPA), a structured workflow that uses Computer-Assisted Qualitative Data Analysis Software and the R statistical environment to systematically analyze phenomenological data. EPA proceeds through two cycles: foundational phenomenological construction with intersubjective triangulation, and corpus-wide consolidation with computational integration. It articulates lived experience through unified analytic units, diachronic phases and dynamics, synchronic categories, and experiential structures. The workflow includes intersubjective stabilization, agreement analysis, and computational visualization. Its application is illustrated with data from an empathy-for-pain paradigm involving simulated Alzheimer's patient interaction. EPA enables qualitative, quantitative, mixed-methods, and neurophenomenological analyses, supporting transparent and reproducible phenomenological science.
Neuroscience of consciousness
January 1, 2026
María del Carmen Tejada, Antonia Zepeda, Alejandro Troncoso et al.
Empathy relies on bodily processes, but how Parkinson's disease (PD) disrupts this is unclear. Using a neurophenomenological approach, 42 people with PD watched pain-related videos while their self-reports, postural movement, heart rate, and electrodermal activity were recorded. Phenomenological interviews after exposure revealed two distinct empathic modes: Resonance Bodyssence, where emotions tightly couple with bodily sensations and movement, and Marginal Resonance Bodyssence, a more observational, cognitively mediated response with reduced bodily resonance. Integrating first-person data with quantitative measures shows that interindividual variability in motor and physiological responses in PD reflects distinct embodied empathic engagements, advancing an embodied account of empathy as a heterogeneous, dynamically enacted phenomenon.