LIVING WITH SYSTEMIC LUPUS ERYTHEMATOSUS IN MAURITIUS: A NARRATIVE STUDY OF PATIENT EXPERIENCES
Bibliographic record
Abstract
PV176 / #700 Poster Topic: AS19 - Patient-Reported Outcome Measures Background/Purpose Systemic Lupus Erythematosus (SLE), commonly known as Lupus, is a complex, chronic autoimmune disease characterized by the immune system attacking healthy tissue and organs. The condition presents a broad spectrum of physical, psychological, and social challenges, significantly affecting patients’ quality of life. While advances in clinical research have improved diagnostic and therapeutic strategies, the personal and social dimensions of living with SLE remain underexplored, particularly in regions such as Mauritius where public awareness and systemic support may be limited. This study aimed to investigate the lived experiences of individuals diagnosed with SLE in Mauritius, focusing on their emotional, social, and practical challenges. Methods Employing a narrative methodology, data were collected through in-depth telephone interviews with 60 participants diagnosed with SLE. The interviews were designed to capture rich qualitative data on sociodemographic characteristics and personal reflections using open-ended questions. Participants represented diverse backgrounds, ensuring a comprehensive exploration of experiences. The analysis involved meticulous transcription, iterative reading, and thematic coding. The data were structured around 3 key domains informed by both existing literature and study findings: Pre-Diagnosis: Participants described the prolonged diagnostic journeys marked by misdiagnosis, lack of awareness, and frustration with the healthcare system. Response to Diagnosis: While receiving a diagnosis brought relief and validation of symptoms, it also elicited fear, denial, and anxiety about managing a lifelong condition. Daily Challenges and Coping Mechanisms: Six overarching themes emerged from these domains: Pain and Fatigue: The pervasive physical symptoms disrupted daily routines and social engagement. Changes in Appearance: Visible manifestations such as skin rashes and hair loss impacted participants’ self-esteem and social confidence. Impact on Relationships: Strain on familial, social, and professional relationships was widely reported, with many citing stigma and lack of understanding from others. Emotional Burden: Participants experienced fear of disease progression, frustration with medical uncertainty, and struggles with mental health. Economic Strain: The financial burden of lifelong treatment, frequent medical visits, and reduced work capacity added significant stress. Support Networks: Many participants emphasized the absence of sufficient emotional and practical support from family, employers, and even healthcare providers. Results The findings underscore the multifaceted impact of SLE on patients’ lives, highlighting systemic gaps in awareness, early diagnosis, and support mechanisms. Participants called for enhanced public education about SLE, greater sensitivity from employers and medical professionals, and the establishment of community-based support groups. Conclusions This study contributes to the growing body of research on chronic illness in underrepresented populations, emphasizing the need for tailored interventions in Mauritius and across the African continent. Enhanced public health initiatives and patient-centered care models are crucial to addressing the unmet needs of individuals with SLE, fostering greater inclusion, and improving their quality of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".