How well are implementation strategies and target healthcare professional behaviors reported? A secondary analysis of 204 implementation trials using the TIDieR checklist and AACTT framework
Notice bibliographique
Résumé
BACKGROUND: Clear specification and reporting of implementation strategies and their targeted healthcare professional behaviors are essential for replication, adaptation, and cumulative learning in implementation science. However, critical gaps remain in the consistent use of reporting frameworks. This study aimed to: (1) assess the completeness of implementation strategy reporting using the Template for Intervention Description and Replication (TIDieR) checklist; (2) examine trends in implementation strategy reporting over time; and (3) assess the completeness of the reporting of healthcare professional behaviors targeted for change using the Action, Actor, Context, Target, Time (AACTT) framework. METHODS: We conducted a secondary analysis of 204 trials included in a systematic review of implementation strategies aimed at changing healthcare professional behavior. Implementation strategies were assessed using the 12-item TIDieR checklist; target behaviors were characterized using the five AACTT domains. Two independent reviewers extracted and coded the data. Descriptive statistics were used to summarize reporting patterns. Data were synthesized narratively and presented in tables, with trends illustrated via a scatterplot. RESULTS: Assessment of implementation strategy reporting using TIDieR showed that procedural details (98%), materials used (95%), and modes of delivery (88%) were frequently reported. Critical elements such as strategy tailoring (28%), fidelity assessment (19% planned; 17% actual), and modifications (10%) were often missing. A modest improvement in reporting was observed after the publication of TIDieR, with median scores increasing from 15.0 (IQR: 13.0-16.0) pre-2014 to 16.0 (IQR: 15.0-18.0) post-2014. Assessment of target healthcare professional behavior reporting using AACTT indicated that actions (e.g., "assess illness") and actors (e.g., nurses) were generally well reported at a high level. However, key contextual and temporal details were largely absent. While physical context was documented in all studies, the emotional and social contexts of behaviors were rarely reported. Crucial information on the duration, frequency, and period of behaviors was rarely reported. CONCLUSIONS: Implementation strategies and target behaviors are not consistently or sufficiently reported in trials. Increased adoption of structured reporting tools such as TIDieR and AACTT is essential to enhance transparency. Incorporating these frameworks during protocol development could strengthen intervention evaluation and reporting, advancing implementation science and fostering cumulative knowledge. TRIAL REGISTRATION: PROSPERO CRD42019130446.
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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 | 0,371 | 0,644 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,009 | 0,016 |
| Bibliométrie | 0,014 | 0,016 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».