The Experience of Persons With Multiple Sclerosis Using MS INFoRm: An Interactive Fatigue Management Resource
Bibliographic record
Abstract
We aimed to understand participants' experiences with a self-guided fatigue management resource, Multiple Sclerosis: An Interactive Fatigue Management Resource ( MS INFoRm), and the extent to which they found its contents relevant and useful to their daily lives. We recruited 35 persons with MS experiencing mild to moderate fatigue, provided them with MS INFoRm, and then conducted semistructured interviews 3 weeks and 3 months after they received the resource. Interpretive description guided the analysis process. Findings indicate that participants' experience of using MS INFoRm could be understood as a process of change, influenced by their initial reactions to the resource. They reported experiencing a shift in knowledge, expectations, and behaviors with respect to fatigue self-management. These shifts led to multiple positive outcomes, including increased levels of self-confidence and improved quality of life. These findings suggest that MS INFoRm may have a place in the continuum of fatigue management interventions for people with MS.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".