Published October 28, 2021 | Version v1
Project deliverable Open

Development of the Autonomous Technologies in Nursing Practice Scale: Preliminary Results

Description

Aims: The aim of the study was to develop and psychometrically test the Autonomous Technologies in Nursing Practice scale for measuring self-assessed ability of nurses to deal with autonomous technologies in nursing practice.

Design: Cross-sectional survey design was used for data collection. 

Methods: Item generation and selection was conducted based on cultural decentring principle by nursing experts in Germany, Hungary, and the Netherlands. The data was collected in Germany (n = 104) in June 2020 and Hungary (n = 700) in November 2019 - January 2020, the participants were nurses and nursing undergraduates. The best functioning items were selected in the process of item analysis and differential item functioning analysis, and psychometric properties of the resulting scale were evaluated.

Results: The resulting scale is a 16-item unidimensional instrument demonstrating good item functioning, homogeneity and internal consistency reliability. 

Conclusion: The current version of the scale, which showed good psychometric properties, can be used by nursing professionals to evaluate their self-assessed ability to deal with autonomous technologies in nursing practice, or can be further developed by researchers.

Impact:  This study addresses the problem of lack of psychometric instruments evaluating self-assessed ability of nurses to deal with autonomous technologies. A unidimensional scale, the Autonomous Technologies in Nursing Practice scale, was developed and psychometrically tested by the authors. The scale can be useful for nursing professionals, while researchers might benefit from our data analytic procedures outlined in the text and in our freely available R script. 

Notes

Co-funded by the Erasmus+ Programme of the European Union. NursingAI project id: 2018-1-DE02-KA202-005101

Files

ATNP_Validation.pdf

Files (2.7 MB)

Name Size Download all
md5:c36bc04ec757554d3eaa526b195f5b6a
2.7 MB Preview Download