Factors influencing healthy aging with multiple sclerosis: a qualitative study
Bibliographic record
Abstract
Purpose: The purpose of this study was to describe the factors influencing healthy aging from the perspective of the older person with multiple sclerosis (MS) in order to build curricula for MS self-management programs. Method: We sourced participants, older than 55 years with MS for more than 20 years, from a database of MS clinic and outpatient rehabilitation visits. Recruitment continued until data saturation was reached (n = 18). Semi-structured interviews explored perspectives on aging and health and lifestyle habits. Demographic, lifestyle and perceived health status information was also gathered. We analyzed the transcribed text for themes and theme relationships. Results: Work and social engagement, effective and accessible health care, healthy lifestyle habits, and maintaining independence at home were found to be critical proximal factors for healthy aging. The presence of financial flexibility, social support, cognitive and mental health, and resilience provided a supporting foundation to these critical proximal factors. These factors comprised a two-tiered model of healthy aging with MS. Conclusions: This two-tiered conceptual model of health aging, based on the perspectives of older persons with MS, provides a potential framework for the development of MS self-management program curricula aimed at optimizing quality of life. Further empirical testing may validate its utility in predicting healthy aging with MS.Implications for RehabilitationThe views of older people with Multiple Sclerosis (MS), as experts in managing the long term challenges of living with MS, should be considered in the design of self-management programs.Health care, social engagement, lifestyle and independence make critical contributions to health-related quality of life among older people with MS.This contribution depends on less-commonly addressed factors: financial flexibility, mental and cognitive health, resilience and social support.Strategies that target factors are important components of a comprehensive approach to rehabilitation and self-management of MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".