The Path to Self-Management: A Qualitative Study Involving Older People with Multiple Sclerosis
Bibliographic record
Abstract
PURPOSE: This qualitative study sought to explore older people's experience of ageing with multiple sclerosis (MS) and to describe the natural history of self-management from their points of view. METHODS: Eighteen people over age 55 and living with MS for at least 20 years were recruited from an MS clinic and rehabilitation outpatient records. Interviews (60-80 min), using open-ended questions, explored participants' lifelong experiences of MS. Following interview transcription, data were coded and analyzed; themes, subthemes, and their relationships were described based on consensus. RESULTS: Participants recounted their diagnosis process, their life experience with MS, and how they eventually accepted their disease, adapted, and moved toward self-management. The findings included vivid descriptions of social relationships, health care interactions, overcoming barriers, and the emotions associated with living with MS. A conceptual model of phases of self-management, from diagnosis to integration of MS into a sense of self, was developed. CONCLUSIONS: Study participants valued self-management and described its phases, facilitators, and inhibitors from their points of view. Over years and decades, learning from life experiences, trial and error, and interactions with health care professionals, participants seemed to consolidate MS into their sense of self. Self-determination, social support, strong problem-solving abilities, and collaborative relationships with health professionals aided adaptation and coping. Findings from this study make initial steps toward understanding how MS self-management evolves over the life course and how self-management programmes can help people with MS begin to manage wellness earlier in their lives.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".