Readability analysis and concept mapping of <scp>PROMs</scp> used for headache disorders
Notice bibliographique
Résumé
OBJECTIVE: To assess the readability and the comprehensiveness of patient-reported outcome measures (PROMs) utilized in primary headache disorders literature. BACKGROUND: As the health-care landscape has evolved toward a patient-centric model, numerous PROMs have been developed to capture treatment outcomes in patients with headache disorders. For these PROMs to advance our understanding of headache disorders and their treatment impact, they must be easy to understand (i.e., reading grade level 6 or less) and comprehensively capture what matters to patients with headache. The aim of this study was to (a) assess the readability of PROMs utilized in headache disorders literature, and (b) assess the comprehensiveness of PROMs by mapping their content to a health-related quality of life framework. METHODS: In this scoping review, recently published systematic reviews were used to identify PROMs used in primary headache disorders literature. Readability analysis was performed at the level of individual items and full PROM using established readability metrics. The content of the PROMs was mapped against a health-related quality-of-life framework by two independent reviewers. RESULTS: In total, 22 PROMs (15 headache disorders related, 7 generic) were included. The median reading grade level varied between 7.1 (interquartile range [IQR] 6.3-7.8) and 12.7 (IQR 11.8-13.2). None of the PROMs were below the recommended reading grade level for patient-facing material (grade 6). Three PROMs, the Migraine-Treatment Assessment Questionnaire, the Eurolight, and the European Quality of Life 5 Dimensions 3 Level Version, were between reading grade levels 7 and 8; the remaining 19 PROMs were above reading grade level 8. In total, the PROMs included 425 items. Most items (n = 134, 32%) assessed physical function (e.g., work, activities of daily living). The remaining items assessed physical symptoms (n = 127, 30%; e.g., pain, nausea), treatment effects on symptoms (n = 65, 15%; e.g., accompanying symptoms relief, headache relief), treatment impact (n = 56, 13%; e.g., function, side effects), psychological well-being (n = 41, 10%; e.g., anger, frustration), social well-being (n = 29, 7%; e.g., missing out on social activities, relationships), psychological impact (n = 14, 3%; e.g., feeling [not] in control, feeling like a burden), and sexual well-being (n = 3, 1%; e.g., sexual activity, sexual interest). Some of the items pertained to treatment (n = 27, 6%), of which most were about treatment type and use (n = 12, 3%; e.g., medication, botulinum toxin), treatment access (n = 10, 2%; e.g., health-care utilization, cost of medication), and treatment experience (n = 9, 2%; e.g., treatment satisfaction, confidence in treatment). CONCLUSION: The PROMs used in studies of headache disorders may be challenging for some patients to understand, leading to inaccurate or missing data. Furthermore, no available PROM comprehensively measures the health-related quality-of-life impact of headache disorders or their treatment, resulting in a limited understanding of patient-reported outcomes. The development of an easy-to-understand, comprehensive, and validated headache disorders-specific PROM is warranted.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,185 | 0,480 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,012 |
| Bibliométrie | 0,038 | 0,026 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».