Medical terminology and interpretation of results in plain language summaries published by oncology journals.
Notice bibliographique
Résumé
e18653 Background: Plain language summaries (PLS) are increasingly added to published scientific manuscripts in oncology, either as an abstract or standalone manuscript, to increase transparency in medical research. We evaluated PLS published in oncology journals by publication type and institution for criteria deemed essential to adequately inform laypeople. Methods: PLS published in oncology journals in 2021 or 2022 were identified in PubMed using prespecified search terms. Two medical writers independently reviewed and scored PLS based on use of medical terminology, language level, and adequate interpretation of data (i.e., a lay reader would be able to put the data adequately in context). Scoring discrepancies were resolved by a third reviewer. Established Flesch readability statistics were compared to the reviewers’ scoring. Scoring results were evaluated between institutions (academia or pharmaceutical companies) using Fisher's exact tests in R. Results: 63 PLS were analyzed in 9 oncology journals; scoring results are displayed in the table. All PLS manuscripts were written by pharmaceutical companies; PLS abstracts were provided by both pharmaceutical companies and academia. Only 5% of all PLS were graded as understandable at the pre-university level. Flesch readability statistics provided similar results, and reviewers’ scores correlated with Flesch readability statistics (n = 38, W = 0.599, r = 66.5, P= .002). Medical terminology was avoided or explained in all PLS manuscripts and in 23% of PLS abstracts. Similarly, data were adequately interpreted in all PLS manuscripts and 17% of PLS abstracts. PLS provided by pharmaceutical companies avoided or explained medical terminology ( P< 0.001 ) and adequately interpreted all data more often than PLS written in academia ( P< 0.001). Importantly, 6 PLS (10%) were found to overstate results. Conclusions: PLS published in oncology journals, particularly as abstracts, frequently had inadequate data interpretation and often used language only accessible for people with advanced scientific or medical training, both when written by academic investigators or within pharmaceutical companies, limiting their intended purpose. We recommend scientists in academia and pharma to adapt easily interpretable language in PLS, which would allow PLS to be used to advance equal access to healthcare research. [Table: see text]
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».