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Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing

BACKGROUND: Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice....

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Autores principales: Freund, Johanna, Piotrowski, Alexandra, Bührmann, Leah, Oehler, Caroline, Titzler, Ingrid, Netter, Anna-Lena, Potthoff, Sebastian, Ebert, David Daniel, Finch, Tracy, Köberlein-Neu, Juliane, Etzelmüller, Anne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578017/
https://www.ncbi.nlm.nih.gov/pubmed/37845776
http://dx.doi.org/10.1186/s43058-023-00505-4
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author Freund, Johanna
Piotrowski, Alexandra
Bührmann, Leah
Oehler, Caroline
Titzler, Ingrid
Netter, Anna-Lena
Potthoff, Sebastian
Ebert, David Daniel
Finch, Tracy
Köberlein-Neu, Juliane
Etzelmüller, Anne
author_facet Freund, Johanna
Piotrowski, Alexandra
Bührmann, Leah
Oehler, Caroline
Titzler, Ingrid
Netter, Anna-Lena
Potthoff, Sebastian
Ebert, David Daniel
Finch, Tracy
Köberlein-Neu, Juliane
Etzelmüller, Anne
author_sort Freund, Johanna
collection PubMed
description BACKGROUND: Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs. METHODS: Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to. RESULTS: A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤ α ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10). CONCLUSIONS: The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings. TRIAL REGISTRATION: Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43058-023-00505-4.
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spelling pubmed-105780172023-10-17 Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing Freund, Johanna Piotrowski, Alexandra Bührmann, Leah Oehler, Caroline Titzler, Ingrid Netter, Anna-Lena Potthoff, Sebastian Ebert, David Daniel Finch, Tracy Köberlein-Neu, Juliane Etzelmüller, Anne Implement Sci Commun Research BACKGROUND: Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs. METHODS: Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to. RESULTS: A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤ α ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10). CONCLUSIONS: The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings. TRIAL REGISTRATION: Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43058-023-00505-4. BioMed Central 2023-10-16 /pmc/articles/PMC10578017/ /pubmed/37845776 http://dx.doi.org/10.1186/s43058-023-00505-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Freund, Johanna
Piotrowski, Alexandra
Bührmann, Leah
Oehler, Caroline
Titzler, Ingrid
Netter, Anna-Lena
Potthoff, Sebastian
Ebert, David Daniel
Finch, Tracy
Köberlein-Neu, Juliane
Etzelmüller, Anne
Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title_full Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title_fullStr Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title_full_unstemmed Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title_short Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing
title_sort validation of the german normalisation process theory measure g-nomad: translation, adaptation, and pilot testing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578017/
https://www.ncbi.nlm.nih.gov/pubmed/37845776
http://dx.doi.org/10.1186/s43058-023-00505-4
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