Methodological guidance for the conduct of mixed methods systematic reviews
Notice bibliographique
Résumé
OBJECTIVE: The objective of this paper is to outline the updated methodological approach for conducting a JBI mixed methods systematic review with a focus on data synthesis, specifically, methods related to how data are combined and the overall integration of the quantitative and qualitative evidence. INTRODUCTION: Mixed methods systematic reviews provide a more complete basis for complex decision-making than that currently offered by single method reviews, thereby maximizing their usefulness to clinical and policy decision-makers. Although mixed methods systematic reviews are gaining traction, guidance regarding the methodology of combining quantitative and qualitative data is limited. In 2014, the JBI Mixed Methods Review Methodology Group developed guidance for mixed methods systematic reviews; however, since the introduction of this guidance, there have been significant developments in mixed methods synthesis. As such, the methodology group recognized the need to revise the guidance to align it with the current state of knowledge on evidence synthesis methodology. METHODS: Between 2015 and 2019, the JBI Mixed Methods Review Methodology Group undertook an extensive review of the literature, held annual face-to-face meetings (which were supplemented by teleconferences and regular email correspondence), sought advice from experts in the field, and presented at scientific conferences. This process led to the development of guidance in the form of a chapter in the JBI Manual for Evidence Synthesis, the official guidance for conducting JBI systematic reviews. In 2019, the guidance was ratified by the JBI International Scientific Committee. RESULTS: The updated JBI methodological guidance for conducting a mixed methods systematic review recommends that reviewers take a convergent approach to synthesis and integration whereby the specific method utilized is dependent on the nature/type of questions that are posed in the systematic review. The JBI guidance is primarily based on Hong et al. and Sandelowski's typology on mixed methods systematic reviews. If the review question can be addressed by both quantitative and qualitative research designs, the convergent integrated approach should be followed, which involves data transformation and allows reviewers to combine quantitative and qualitative data. If the focus of the review is on different aspects or dimensions of a particular phenomenon of interest, the convergent segregated approach is undertaken, which involves independent synthesis of quantitative and qualitative data leading to the generation of quantitative and qualitative evidence, which are then integrated together. CONCLUSIONS: The updated guidance on JBI mixed methods systematic reviews provides foundational work to a rapidly evolving methodology and aligns with other seminal work undertaken in the field of mixed methods synthesis. Limitations to the current guidance are acknowledged, and a series of methodological projects identified by the JBI Mixed Methods Review Methodology Group to further refine the methodology are proposed. Mixed methods reviews offer an innovative framework for generating unique insights related to the complexities associated with health care quality and safety.
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 | 0,659 | 0,830 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,011 |
| Méta-épidémiologie (sens large) | 0,012 | 0,022 |
| Bibliométrie | 0,034 | 0,029 |
| Études des sciences et des technologies | 0,006 | 0,012 |
| Communication savante | 0,020 | 0,013 |
| Science ouverte | 0,013 | 0,015 |
| Intégrité de la recherche | 0,020 | 0,026 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,022 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex 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 ».