期刊论文详细信息
Implementation Science
Supporting translation of research evidence into practice—the use of Normalisation Process Theory to assess and inform implementation within randomised controlled trials: a systematic review
Systematic Review
Allison Williams1  Grazia Antonacci2  Laura Lennox2  Matthew Harris3 
[1] Department of Primary Care and Public Health, Imperial College London, National Institute of Health Research (NIHR) Applied Research Collaboration (ARC) Northwest London, Charing Cross Campus, W6 8RP, London, UK;Department of Primary Care and Public Health, Imperial College London, National Institute of Health Research (NIHR) Applied Research Collaboration (ARC) Northwest London, Charing Cross Campus, W6 8RP, London, UK;Business School, Centre for Health Economics and Policy Innovation (CHEPI), Imperial College London, Chelsea and Westminster Campus, SW10 9N, London, UK;Department of Primary Care and Public Health, Imperial College London, National Institute of Health Research (NIHR) Applied Research Collaboration (ARC) Northwest London, Charing Cross Campus, W6 8RP, London, UK;Department of Primary Care and Public Health, Imperial College London, London, UK;
关键词: Implementation science;    Randomised controlled trials;    RCT;    Normalisation Process Theory;    NPT;   
DOI  :  10.1186/s13012-023-01311-1
 received in 2023-06-08, accepted in 2023-10-02,  发布年份 2023
来源: Springer
PDF
【 摘 要 】

BackgroundThe status of randomised controlled trials (RCTs) as the ‘gold standard’ for evaluating efficacy in healthcare interventions is increasingly debated among the research community, due to often insufficient consideration for implementation. Normalisation Process Theory (NPT), which focuses on the work required to embed processes into practice, offers a potentially useful framework for addressing these concerns. While the theory has been deployed in numerous RCTs to date, more work is needed to consolidate understanding of if, and how, NPT may aid implementation planning and processes within RCTs. Therefore, this review seeks to understand how NPT contributes to understanding the dynamics of implementation processes within RCTs. Specifically, this review will identify and characterise NPT operationalisation, benefits and reported challenges and limitations in RCTs.MethodsA qualitative systematic review with narrative synthesis of peer-reviewed journal articles from eight databases was conducted. Studies were eligible for inclusion if they reported sufficient detail on the use of NPT within RCTs in a healthcare domain. A pre-specified data extraction template was developed based on the research questions of this review. A narrative synthesis was performed to identify recurrent findings.ResultsSearches identified 48 articles reporting 42 studies eligible for inclusion. Findings suggest that NPT is primarily operationalised prospectively during the data collection stage, with limited sub-construct utilisation overall. NPT is beneficial in understanding implementation processes by aiding the identification and analysis of key factors, such as understanding intervention fidelity in real-world settings. Nearly three-quarters of studies failed to report the challenges and limitations of utilising NPT, though coding difficulties and data falling outside the NPT framework are most common.ConclusionsNPT appears to be a consistent and generalisable framework for explaining the dynamics of implementation processes within RCTs. However, operationalisation of the theory to its full extent is necessary to improve its use in practice, as it is currently deployed in varying capacities. Recommendations for future research include investigation of NPT alongside other frameworks, as well as earlier operationalisation and greater use of NPT sub-constructs.Trial RegistrationThe protocol for this systematic review was accepted for public registration on PROSPERO (registration number: CRD42022345427) on 26 July 2022.

【 授权许可】

CC BY   
© The Author(s) 2023

【 预 览 】
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12936_2017_1963_Article_IEq41.gif 1KB Image download
Fig. 13 402KB Image download
Fig. 3 424KB Image download
Fig. 1 294KB Image download
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