Toward an Objective Assessment of Implementation Processes for Innovations in Health Care: Psychometric Evaluation of the Normalization Measure Development (NoMAD) Questionnaire Among Mental Health Care Professionals

Christiaan Vis, Jeroen Ruwaard, Tracy Finch, Tim Rapley, Derek de Beurs, Henk van Stel, Britt van Lettow, Mayke Mol, Annet Kleiboer, Heleen Riper, Jan Smit

Research output: Contribution to JournalArticleAcademicpeer-review


BACKGROUND: Successfully implementing eMental health (eMH) interventions in routine mental health care constitutes a major challenge. Reliable instruments to assess implementation progress are essential. The Normalization MeAsure Development (NoMAD) study developed a brief self-report questionnaire that could be helpful in measuring implementation progress. Based on the Normalization Process Theory, this instrument focuses on 4 generative mechanisms involved in implementation processes: coherence, cognitive participation, collective action, and reflexive monitoring. OBJECTIVE: The aim of this study was to translate the NoMAD questionnaire to Dutch and to confirm the factor structure in Dutch mental health care settings. METHODS: Dutch mental health care professionals involved in eMH implementation were invited to complete the translated NoMAD questionnaire. Confirmatory factor analysis (CFA) was conducted to verify interpretability of scale scores for 3 models: (1) the theoretical 4-factor structure, (2) a unidimensional model, and (3) a hierarchical model. Potential improvements were explored, and correlated scale scores with 3 control questions were used to assess convergent validity. RESULTS: A total of 262 professionals from mental health care settings in the Netherlands completed the questionnaire (female: 81.7%; mean age: 45 [SD=11]). The internal consistency of the 20-item questionnaire was acceptable (.62≤alpha≤.85). The theorized 4-factor model fitted the data slightly better in the CFA than the hierarchical model (Comparative Fit Index=0.90, Tucker Lewis Index=0.88, Root Mean Square Error of Approximation=0.10, Standardized Root Mean Square Residual=0.12, χ22=22.5, P≤.05). However, the difference is small and possibly not outweighing the practical relevance of a total score and subscale scores combined in one hierarchical model. One item was identified as weak (λCA.2=0.10). A moderate-to-strong convergent validity with 3 control questions was found for the Collective Participation scale (.47≤r≤.54, P≤.05). CONCLUSIONS: NoMAD's theoretical factor structure was confirmed in Dutch mental health settings to acceptable standards but with room for improvement. The hierarchical model might prove useful in increasing the practical utility of the NoMAD questionnaire by combining a total score with information on the 4 generative mechanisms. Future research should assess the predictive value and responsiveness over time and elucidate the conceptual interpretability of NoMAD in eMH implementation practices.

Original languageEnglish
Article numbere12376
Pages (from-to)1-16
Number of pages16
JournalJournal of Medical Internet Research
Issue number2
Early online date20 Feb 2019
Publication statusPublished - Feb 2019


The authors would like to express their gratitude to the MasterMind and the ImpleMentAll projects for supporting this work. The MasterMind project was partially funded under the ICT Policy Support Programme (ICT PSP) as part of the Competitiveness and Innovation Framework Programme (CIP) by the European Community (Grant Agreement number: 621000). The ImpleMentAll project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 733025. These funding bodies had no influence on the design, execution, analysis, or interpretation of the results of this study.

FundersFunder number
Competitiveness and Innovation Framework Programme
European Community621000
Horizon 2020 Framework Programme
Horizon 2020733025


    • eHealth
    • eMental health
    • implementation assessment
    • implementation science
    • normalization process theory
    • psychometrics


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