Objective: To analyze the social representations of fibromyalgia based on its symptoms and their influences on diagnosis and therapy.
Methods: Qualitative research with the application of the Theory of Social Representations and snowball sampling method. Semi-structured interviews were conducted with 30 adults diagnosed with fibromyalgia in the city of Rio de Janeiro, Brazil, between April 2020 and January 2021. Statistical and lexicographical analysis was performed using Alceste software.
Results: Pain, as a subjective phenomenon, complicates its legitimacy, diagnosis, and therapy, enhancing suffering. Insufficient information generates judgments, stereotypes, and prejudices.
Final Considerations: Stigmas, prejudices, the variety and invisibility of symptoms make it difficult to objectify the disease within the Cartesian-biomedical frameworks, generating diagnostic pilgrimage, mistakes, and challenges in treatment. Such representations hinder relationships and the management of the disease. Deconstructing them is a way to better care for those with fibromyalgia. Raising awareness and spreading qualified information are important allies.
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http://dx.doi.org/10.1590/0034-7167-2023-0363 | DOI Listing |
J Med Internet Res
January 2025
Cancer Rehabilitation and Survivorship, Department of Supportive Care, Princess Margaret Cancer Centre, Toronto, ON, Canada.
Background: Virtual follow-up (VFU) has the potential to enhance cancer survivorship care. However, a greater understanding is needed of how VFU can be optimized.
Objective: This study aims to examine how, for whom, and in what contexts VFU works for cancer survivorship care.
J Forensic Odontostomatol
December 2024
Department of Medicine and Health Science "Vincenzo Tiberio", University of Molise, AgeEstimation Project, Campobasso, Italy.
Forensic age estimation is performed by assessing pulp chamber constrictions due to physiological age-related changes in dental radiographs; however, the estimated ages occasionally deviate from the actual ages. In particular, long-term steroid users tend to demonstrate pulp chamber constrictions in all teeth. Because this is uncommon among younger age groups, caution should be exercised when evaluating pulp chamber constriction.
View Article and Find Full Text PDFJCO Glob Oncol
January 2025
Auckland Regional Cancer and Blood Service, Te Toka Tumai Auckland, Health New Zealand, Te Whatu Ora, Auckland, New Zealand.
Purpose: In Aotearoa New Zealand, there are inequitable outcomes for Pacific peoples who experience higher rates of preventable cancers and poorer survival compared with other ethnicities. The aim of this study was to explore Pacific peoples lived experience of cancer and its treatment in the Auckland setting.
Methods: Data were collected through semistructured interviews (talanoa) with Pacific patients under the Auckland Regional Cancer and Blood Service.
Urogynecology (Phila)
October 2024
Atrium Wake Forest Baptist Health, Winston-Salem, NC.
Importance: Limited data exist comparing total laparoscopic hysterectomy (TLH) versus laparoscopic supracervical hysterectomy (LSCH) at the time of minimally invasive sacrocolpopexy for uterovaginal prolapse.
Objectives: The objective of this study was to compare TLH versus LSCH at the time of minimally invasive sacrocolpopexy for uterovaginal prolapse, hypothesizing that LSCH would demonstrate a higher proportion of recurrent prolapse, but a lower proportion of mesh exposures.
Study Design: This was a retrospective, secondary analysis comparing a prospective cohort of patients undergoing TLH sacrocolpopexy versus a retrospective cohort of patients who had undergone LSCH sacrocolpopexy.
JCO Clin Cancer Inform
January 2025
Emory University School of Medicine, Atlanta, GA.
Purpose: Immune checkpoint inhibitors (ICIs) have demonstrated promise in the treatment of various cancers. Single-drug ICI therapy (immuno-oncology [IO] monotherapy) that targets PD-L1 is the standard of care in patients with advanced non-small cell lung cancer (NSCLC) with PD-L1 expression ≥50%. We sought to find out if a machine learning (ML) algorithm can perform better as a predictive biomarker than PD-L1 alone.
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