Introduction: Successful implementation and embedding of new health care practices relies on co-ordinated, collective behaviour of individuals working within the constraints of health care settings. Normalization Process Theory (NPT) provides a theory of implementation that emphasises collective action in explaining, and shaping, the embedding of new practices. To extend the practical utility of NPT for improving implementation success, an instrument (NoMAD) was developed and validated.
Methods: Descriptive analysis and psychometric testing of an instrument developed by the authors, through an iterative process that included item generation, consensus methods, item appraisal, and cognitive testing. A 46 item questionnaire was tested in 6 sites implementing health related interventions, using paper and online completion. Participants were staff directly involved in working with the interventions. Descriptive analysis and consensus methods were used to remove redundancy, reducing the final tool to 23 items. Data were subject to confirmatory factor analysis which sought to confirm the theoretical structure within the sample.
Results: We obtained 831 completed questionnaires, an average response rate of 39% (range: 22-77%). Full completion of items was 50% (n = 413). The confirmatory factor analysis showed the model achieved acceptable fit (CFI = 0.95, TLI = 0.93, RMSEA = 0.08, SRMR = 0.03). Construct validity of the four theoretical constructs of NPT was supported, and internal consistency (Cronbach's alpha) were as follows: Coherence (4 items, α = 0.71); Collective Action (7 items, α = 0.78); Cognitive Participation (4 items, α = 0.81); Reflexive Monitoring (5 items, α = 0.65). The normalisation scale overall, was highly reliable (20 items, α = 0.89).
Conclusions: The NoMAD instrument has good face validity, construct validity and internal consistency, for assessing staff perceptions of factors relevant to embedding interventions that change their work practices. Uses in evaluating and guiding implementation are proposed.
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http://dx.doi.org/10.1186/s12874-018-0591-x | DOI Listing |
PLoS One
December 2024
Faculty of Education, Burapha University, Saen Suk, Chon Buri, Thailand.
Objective: Although aging well and aging in place policies have been encouraged in many countries, a consistent challenge is insufficient evidence on older migrants. This study compared mental well-being models of older adults between aging in place and aging migrant groups. The model included social factors (e.
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November 2024
Universidade Estadual de Maringá, Departamento de Enfermagem, Maringá, PR, Brazil.
Objective: To identify variables related to perceived stress and resilience of international migrants.
Method: Multicenter, observational, cross-sectional study carried out with 403 migrants residing in Brazil, Spain, or Portugal. The following instruments were used to collect data: Perceived Stress Scale and Resilience Scale.
JMIR Public Health Surveill
November 2024
School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD, 21205-2110, United States, 1 4106142669, 1 4432870547.
Forensic Sci Int
December 2024
Department of Medical, Surgical and Advanced Technologies "G.F. Ingrassia", University of Catania, Catania 95121, Italy. Electronic address:
The phenomenon of migration is an international issue that mainly concerns Europe. In Italy, because of its close proximity to Africa, there are many migrant landings, especially on the islands of Lampedusa and Sicily. Migrants and asylum seekers suffer torture on their journey to their destination country, however, most of the time the signs are not always recognizable.
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October 2024
School of Healthcare, University of Leeds, Baines Wing, Leeds, LS2 9JT, UK.
Background: The need for effective non-pharmaceutical infection prevention measures such as contact tracing in pandemics remains in care homes, but traditional approaches to contact tracing are not feasible in care homes. The CONTACT intervention introduces Bluetooth-enabled wearable devices (BLE wearables) as a potential solution for automated contact tracing. Using structured reports and reports triggered by positive COVID-19 cases in homes, we fed contact patterns and trends back to homes to support better-informed infection prevention decisions and reduce blanket application of restrictive measures.
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