Measures of organizational culture, organizational climate, and implementation climate in behavioral health: A systematic review
Notice bibliographique
Résumé
Background: Organizational culture, organizational climate, and implementation climate are key organizational constructs that influence the implementation of evidence-based practices. However, there has been little systematic investigation of the availability of psychometrically strong measures that can be used to assess these constructs in behavioral health. This systematic review identified and assessed the psychometric properties of measures of organizational culture, organizational climate, implementation climate, and related subconstructs as defined by the Consolidated Framework for Implementation Research (CFIR) and Ehrhart and colleagues. Methods: Data collection involved search string generation, title and abstract screening, full-text review, construct assignment, and citation searches for all known empirical uses. Data relevant to nine psychometric criteria from the Psychometric and Pragmatic Evidence Rating Scale (PAPERS) were extracted: internal consistency, convergent validity, discriminant validity, known-groups validity, predictive validity, concurrent validity, structural validity, responsiveness, and norms. Extracted data for each criterion were rated on a scale from -1 ("poor") to 4 ("excellent"), and each measure was assigned a total score (highest possible score = 36) that formed the basis for head-to-head comparisons of measures for each focal construct. Results: = 2). Psychometric evidence was most frequently available for internal consistency and norms. Information about other psychometric properties was less available. Median ratings for psychometric properties across categories of measures ranged from "poor" to "good." There was limited evidence of responsiveness or predictive validity. Conclusion: While several promising measures were identified, the overall state of measurement related to these constructs is poor. To enhance understanding of how these constructs influence implementation research and practice, measures that are sensitive to change and predictive of key implementation and clinical outcomes are required. There is a need for further testing of the most promising measures, and ample opportunity to develop additional psychometrically strong measures of these important constructs. Plain Language Summary: Organizational culture, organizational climate, and implementation climate can play a critical role in facilitating or impeding the successful implementation and sustainment of evidence-based practices. Advancing our understanding of how these contextual factors independently or collectively influence implementation and clinical outcomes requires measures that are reliable and valid. Previous systematic reviews identified measures of organizational factors that influence implementation, but none focused explicitly on behavioral health; focused solely on organizational culture, organizational climate, and implementation climate; or assessed the evidence base of all known uses of a measure within a given area, such as behavioral health-focused implementation efforts. The purpose of this study was to identify and assess the psychometric properties of measures of organizational culture, organizational climate, implementation climate, and related subconstructs that have been used in behavioral health-focused implementation research. We identified 21 measures of organizational culture, 36 measures of organizational climate, 2 measures of implementation climate, 2 measures of tension for change, 6 measures of compatibility, 2 measures of relative priority, 3 measures of organizational incentives and rewards, 3 measures of goals and feedback, and 2 measures of learning climate. Some promising measures were identified; however, the overall state of measurement across these constructs is poor. This review highlights specific areas for improvement and suggests the need to rigorously evaluate existing measures and develop new measures.
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 | 0,027 | 0,113 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,008 |
| Bibliométrie | 0,015 | 0,018 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| 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 ».