Exploring Sources of Emotional Distress among People Living with Scleroderma: A Focus Group Study
Bibliographic record
Abstract
BACKGROUND: Systemic sclerosis, or scleroderma, is a chronic and rare connective tissue disease with negative physical and psychological implications. Sources of emotional distress and the impact they have on the lives of people with scleroderma are not well understood. OBJECTIVES: To gain an in-depth understanding of the emotional experiences and sources of emotional distress for women and men living with scleroderma through focus group discussions. METHODS: Three semi-structured focus group discussions were conducted (two in English, one in French) with a total of 22 people with scleroderma recruited through the Scleroderma Society of Ontario in Hamilton, Ontario and a scleroderma clinic in Montreal, Canada. Interviews were recorded, transcribed, and then coded for emerging themes using thematic inductive analysis. RESULTS: Core themes representing sources of emotional distress were identified, including: (a) facing a new reality; (b) the daily struggle of living with scleroderma; (c) handling work, employment and general financial burden; (d) changing family roles; (e) social interactions; and (f) navigating the health care system. Collectively, these themes refer to the stressful journey of living with scleroderma including the obstacles faced and the emotional experiences beginning prior to receiving a diagnosis and continuing throughout the participants' lives. CONCLUSION: Scleroderma was portrayed as being an unpredictable and overwhelming disease, resulting in many individuals experiencing multiple sources of emotional distress. Interventions and supportive resources need to be developed to help individuals with scleroderma and people close to them manage and cope with the emotional aspects of the disease.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".