Experiences of Children and Adolescents Living with Multiple Sclerosis
Bibliographic record
Abstract
About 5% of people with multiple sclerosis (MS) are diagnosed before age 18. Because pediatric MS is uncommon, little is known about the experiences of children and adolescents living with MS. The purpose of this qualitative study was to learn from these youth what it is like to live with the diagnosis of MS. Twelve patients with clinically definite MS between the ages of 8 and 18 years were interviewed. Initially, they were unfamiliar with MS and had a multitude of feelings about the diagnosis. Over time, they adapted to the temporary or permanent effects and incorporated changes caused by MS into their lives. Most described participation in social and recreational activities typical of their age group. Although they recognized their lives were different because they had MS, in many ways they felt unchanged. Most noted positive and negative changes in their relationships. They described common stressors unique to having MS that made life more challenging, but they used diverse coping strategies to address these stressors. They expressed the need to move forward with life and identified hopes and plans for the future. MS contributed to shaping their self-identities, but their disease remained only one component of who they were. The findings of this study provide a greater understanding of the experiences and views of youth with MS and offer guidance for nurses to enhance care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".