Management of multiple sclerosis in adolescents – current treatment options and related adherence issues
Bibliographic record
Abstract
Multiple sclerosis (MS) is a progressive inflammatory demyelinating disorder of the central nervous system that is increasingly recognized in children and adolescents. This realization comes with additional concerns about existing therapeutic options and the impact of the disease on health-related outcomes of adolescents with MS. This five-part review provides an update on management strategies relevant to the pediatric MS population. The first section gives an overview on the epidemiology and natural history of early onset MS. The second section outlines currently available MS treatments, including medications during acute relapses and long-term immunomodulatory therapies. The third section highlights adherence issues pertaining to MS, including the challenges uniquely faced by adolescents. The fourth section provides a summary of research into quality of life and psychosocial consequences of pediatric onset MS. Attention is drawn to the grief experience of affected adolescents and the importance of peer relationships. Finally, the family resilience framework is presented as a conceptual model to facilitate optimal adaptation of adolescents with MS. Healthcare professionals can promote resilience and treatment adherence by ensuring that these individuals and their families are sufficiently informed about available MS treatments, providing instrumental support for managing potential medication side effects, and addressing age-appropriate developmental needs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".