Attrition, missing data, compliance, and related biases in randomized controlled trials of rehabilitation interventions: towards improving reporting and conduct
Notice bibliographique
Résumé
INTRODUCTION: Attrition, missing data, compliance, and related biases can influence the magnitude of treatment effects in randomized controlled trials (RCTs). It is unclear which items should be considered when reporting and evaluating the influence of these biases in trial reports in the rehabilitation field. The aim was to describe which individual items considering attrition, missing data, compliance, and related biases are included in quality tools used in rehabilitation research. In addition, we aimed to determine whether the existing reporting guidelines, such as the CONSORT and its extensions include all relevant items related to these biases when reporting RCTs in the area of rehabilitation. EVIDENCE ACQUISITION: Comprehensive literature searches and a systematic approach to identify tools and items looking at attrition, missing data, compliance and related biases in rehabilitation were performed. We extracted individual items linked to these biases from all quality tools. We calculated the frequency of quality items used across tools and compared them to those found in the CONSORT statement and its extensions. A list of items to be potentially added to the CONSORT statement was generated. EVIDENCE SYNTHESIS: Three new tools to assess the conduct and reporting of trials in the rehabilitation field were found. From these tools, 28 items were used to evaluate the reporting as well as the conduct of trials considering attrition, missing data, compliance, and related biases in the rehabilitation field. However, our team found that some of these items lack specificity in the information required and therefore more research is needed to determine a core set of items used for reporting as well as assessing the risk of bias (RoB) of RCT in the rehabilitation field. CONCLUSIONS: Although many items have been described by existing tools and the CONSORT statement (and its extensions) that deal with attrition, missing data, compliance, and related biases, several gaps in reporting were identified. It is crucial that future research investigate a core set of items to be used in the field of rehabilitation to facilitate the reporting as well as the conduct of RCTs.
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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 | 0,520 | 0,859 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,034 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 | 0,000 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».