Abstract
Psychosomatic psychology has historically contributed to overcoming biomedical reductionism by emphasizing the role of psychological and relational factors in somatic illness. However, when examined through a rigorous epistemological lens, this tradition reveals a persistent structural vulnerability: the systematic proposition of arbitrary symbolic interpretations unsupported by empirical evidence. This situation represents both an epistemological weakness and a potential iatrogenic risk when applied in the clinical context. This article argues that when plausible and arbitrary interpretations fail to pass the test of valid empirical evidence, psychosomatic models can quickly slide from scientific explanation to hermeneutic closure. Drawing on the principles of scientific epistemology, confirmation bias, and falsifiability, this analysis critically examines how the selective validation of confirmatory clinical narratives compromises explanatory robustness. A more epistemologically coherent conceptual framework is proposed, in line with current developments in psychoneuroimmunology, systems biology, and microbiota research. This perspective does not deny the connection between psychological, physiological, and cellular aspects but rather proposes placing hypotheses within a testable context to reduce undue interpretations. Only within this epistemological framework can psychosomatic psychology be scientifically legitimized and assert its clinical utility.
Full text
621 characters
· extracted from
oa-doi-fallback
· click to expand
There is a newer version available for this {{ publicationType }}. View latest version
{{ publication.field_name }}
{{ publication.subfield_name }}
Copyright: © {{ publicationYear }} {{ publication.presentation_authors[0].full_name + (publication.presentation_authors.length > 1 ? ' et al' : '') }}. This is an open access publication distributed under the terms of the CC BY 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Check the {{ publicationType | capitalize }} Source for copyright and license information.
Listen on
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.