Life quality and health in adolescents and emerging adults with epilepsy during the years of transition: a scoping review
Bibliographic record
Abstract
AIMS: The aims of this study were to (1) search the literature in order to identify the challenges facing adolescents and emerging adults with epilepsy; and (2) categorize these issues within both the framework of the International Classification of Functioning, Disability and Health (ICF) and an empirical model of quality of life (QOL) in childhood epilepsy. METHOD: We systematically searched PsycINFO, Ovid MEDLINE and Web of Science for studies reporting on QOL and health identified in people with epilepsy aged 12 to 29 years. Studies were limited to those that were published in the last 20 years in English, presenting the patient perspective. Data were extracted and charted using a descriptive analytical method. Identified issues were classified according to the ICF and QOL frameworks. RESULTS: Fifty four studies were identified. Another 62 studies with potentially useful information were included as an addendum. The studies highlight a range of psychosocial issues emphasizing peer acceptance, social isolation, and feelings of anxiety, fear, and sadness. INTERPRETATION: The ICF and QOL constructs represent useful starting points in the analytical classification of the potential challenges faced by adolescents with epilepsy. Progress is needed on fully classifying issues not included under these frameworks. We propose to expand these frameworks to include comorbidities, impending medical interventions, and concerns for future education, employment, marriage, dignity, and autonomy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".