Objectives To: i) Translate and adapt the original British instrument the Normalisation Process Theory Measure (NoMAD) into the Swedish version S-NoMAD, and ii) Evaluate its basic psychometric properties, including pilot-testing for validity in a health care context including in-hospital, primary, and community care in a region of northern Sweden.
The NoMAD instrument is based on Normalisation Process Theory, and its four core constructs: Coherence, Cognitive Participation, Collective Action and Reflexive Monitoring. They represent ways of thinking about implementation and are focused on how interventions can become part of everyday practice and how different groups of people need to work together to achieve it.
Method A systematic approach with a four step process was utilised, including forward and backward translation and expert reviews for the test and improvement of content validity of the S-NoMAD in different stages of development. The final S-NoMAD version was then used for process evaluation in a pilot study aimed at implementation of a new working method for individualised and coordinated care planning. The pilot was executed in a county council and fourteen municipalities, and supported by a specifically designed IT-solution. The S-NoMAD pilot results were analysed for validity by the use of confirmatory factor analysis, i.e. a one factor model fitted for each of the four constructs of the NoMAD. Cronbach’s alpha was used to ascertain the internal consistency reliability.
Results In the pilot study S-NoMAD data were collected from 144 individuals of different health care professions as well as managers, working at in-hospital, primary and community care. The initial factor analysis model showed very good fit for two of the constructs (Coherence and Cognitive Participation) and unsatisfactory fit for the remaining two (Collective Action and Reflexive Monitoring) due to three problematic items. Deleting those items from the model yielded a very good fit. Then the internal consistency reliability was shown to be good (alphas between 0.78 and 0.83). However, estimation of correlations between the factors showed that the factor Reflexive Monitoring was highly correlated (around 0.9) with the factors Coherence and Collective Action.
Conclusions Careful translation and adaptation in several steps is essential for the maintenance of psychometric qualities. Still cultural (language) differences may have caused poor fit for three items of the S-NoMAD, indicating low construct validity. After deleting these items, a good fit was obtained and overall good factor reliability was shown. Still, high correlation between constructs (factors) may indicate a psychometric problem, but may also be due to a small sample size. More extensive studies in different health care contexts are needed for further evaluation and development of the S-NoMAD.
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