Measurement properties of self-reported clinical decision-making instruments in nursing: A COSMIN systematic review
Notice bibliographique
Résumé
Background: Nurses' clinical decision-making, i.e., the data collection, analysis, and evaluation process through which they reach clinical judgements and makes clinical decisions, is at the core of nursing practice and essential to provide safe and quality care. Instruments to assess nurses' perceptions of their clinical decision-making abilities or skills have been developed for research and education. Thus, it is essential to determine the most valid and reliable instruments available to reflect nurses' self-reported clinical decision-making accurately. Objective: To evaluate the measurement properties of self-reported clinical decision-making instruments in nursing. Methods: A systematic review based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) was conducted (PROSPERO registration: CRD42022364549). Five bibliographical databases were searched in July 2022 using descriptors and keywords related to nurses, clinical decision-making, and studies on measurement properties. Two independent reviewers conducted reference selection and data extraction. The evaluation of the instruments' measurement properties involved assessing the quality of the studies, the quality of each measurement property (i.e., validity, reliability, responsiveness), and the quality of evidence based on the COSMIN. Results: Nine instruments evaluated in eleven studies with registered nurses or nursing students from various clinical contexts were identified. Five of the nine instruments were originals; four were translations or adaptations. Most focused on analytical and intuitive decision-making, although some were based on clinical judgment and clinical reasoning theories. Structural validity and internal consistency were the most frequently reported measurement properties; other properties, such as measurement error, criterion validity, and responsiveness, were not assessed for any instruments. A gap was also identified in the involvement of nurses or nursing students in the instrument development process and the content validity assessment. Six instruments appear promising based on the COSMIN criteria, but further studies are needed to confirm their validity and reliability. Conclusions: The evidence regarding instruments to assess nurses' self-reported clinical decision-making is still minimal. Although no instruments could be recommended based on the COSMIN criteria, the Nurses Clinical Reasoning Scale had the most robust supporting evidence, followed by the adapted version of the Clinical Decision Making in Nursing Scale. Future efforts should be made to systematically assess content validity through the involvement of the target population and by ensuring that the results of other measurement properties, such as reliability, measurement error, or hypothesis testing, are rigorously assessed and reported. Tweetable abstract: Despite limited evidence, this COSMIN review identified six promising instruments to assess nurses' clinical #decision-making, especially the Nurses Clinical Reasoning Scale and an adaptation of the Clinical Decision Making in Nursing Scale. #nursingresearch #nursingeducation.
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 | 0,089 | 0,305 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,011 |
| Bibliométrie | 0,011 | 0,014 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».