Identifying and characterizing clinical subgroups in individuals with endometriosis
(2025) In Frontiers in Pain Research 6.- Abstract
Background: Classification attempts and treatment strategies for endometriosis have been predominantly biomedical. Symptom profiles observed in individuals with endometriosis are multidimensional and may be more effectively captured by a biopsychosocial model. Methods: The aim of this study was to identify distinct subgroups of individuals with endometriosis based on their biopsychosocial profiles, using Latent Class Analysis. In a subsequent phase, the identified subgroups were compared in terms of sociodemographic characteristics and various indices of functioning. Results: Two distinct subgroups were identified: Class 2, representing a high biopsychosocial burden (BPS) group characterized by both significant psychological strain and... (More)
Background: Classification attempts and treatment strategies for endometriosis have been predominantly biomedical. Symptom profiles observed in individuals with endometriosis are multidimensional and may be more effectively captured by a biopsychosocial model. Methods: The aim of this study was to identify distinct subgroups of individuals with endometriosis based on their biopsychosocial profiles, using Latent Class Analysis. In a subsequent phase, the identified subgroups were compared in terms of sociodemographic characteristics and various indices of functioning. Results: Two distinct subgroups were identified: Class 2, representing a high biopsychosocial burden (BPS) group characterized by both significant psychological strain and severe pain characteristics, and Class 1, representing a low BPS group with low scores on these indicators. The high BPS group reported worse control/powerlessness and greater deficits in social support. Conclusion: Moving forward, clinical assessment of patients with endometriosis may benefit from integrating core principles from the biopsychosocial model. This approach can help identify individuals facing significant psychosocial challenges who may require multidisciplinary interventions alongside evidence-based biological treatments.
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- author
- Åkerblom, Sophia LU ; Peppler Jönsson, Ingrid ; Ringqvist, Åsa LU ; Nordengren, Johanna and Zhao, Xiang
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- anxiety, biopsychosocial model, depression, endometriosis, pain catastrophizing, pain extent, pain intensity
- in
- Frontiers in Pain Research
- volume
- 6
- article number
- 1610109
- publisher
- Frontiers Media S. A.
- external identifiers
-
- scopus:105026770128
- pmid:41458251
- ISSN
- 2673-561X
- DOI
- 10.3389/fpain.2025.1610109
- language
- English
- LU publication?
- yes
- id
- 676e5c93-bf47-47cb-91df-f2d7c9d8a838
- date added to LUP
- 2026-02-16 12:11:48
- date last changed
- 2026-02-17 03:00:05
@article{676e5c93-bf47-47cb-91df-f2d7c9d8a838,
abstract = {{<p>Background: Classification attempts and treatment strategies for endometriosis have been predominantly biomedical. Symptom profiles observed in individuals with endometriosis are multidimensional and may be more effectively captured by a biopsychosocial model. Methods: The aim of this study was to identify distinct subgroups of individuals with endometriosis based on their biopsychosocial profiles, using Latent Class Analysis. In a subsequent phase, the identified subgroups were compared in terms of sociodemographic characteristics and various indices of functioning. Results: Two distinct subgroups were identified: Class 2, representing a high biopsychosocial burden (BPS) group characterized by both significant psychological strain and severe pain characteristics, and Class 1, representing a low BPS group with low scores on these indicators. The high BPS group reported worse control/powerlessness and greater deficits in social support. Conclusion: Moving forward, clinical assessment of patients with endometriosis may benefit from integrating core principles from the biopsychosocial model. This approach can help identify individuals facing significant psychosocial challenges who may require multidisciplinary interventions alongside evidence-based biological treatments.</p>}},
author = {{Åkerblom, Sophia and Peppler Jönsson, Ingrid and Ringqvist, Åsa and Nordengren, Johanna and Zhao, Xiang}},
issn = {{2673-561X}},
keywords = {{anxiety; biopsychosocial model; depression; endometriosis; pain catastrophizing; pain extent; pain intensity}},
language = {{eng}},
publisher = {{Frontiers Media S. A.}},
series = {{Frontiers in Pain Research}},
title = {{Identifying and characterizing clinical subgroups in individuals with endometriosis}},
url = {{http://dx.doi.org/10.3389/fpain.2025.1610109}},
doi = {{10.3389/fpain.2025.1610109}},
volume = {{6}},
year = {{2025}},
}