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Assessment of the Psychometric Characteristics of the Italian Version of the Nurse Manager Actions Scale.

Marzia LommiRosario CarusoGianluca ConteArianna MagonBarbara PorcelliAlessandro StievanoGennaro RoccoIppolito NotarnicolaLaura SabatinoRoberto LatinaMaddalena De MariaEmanuele Di SimoneAnna De BenedictisRaffaella GualandiDaniela TartagliniDhurata Ivziku
Published in: Nursing reports (Pavia, Italy) (2023)
Nurse managers play a vital role in healthcare organizations, wielding the ability to substantially enhance work environments, foster nurses' autonomy, and bolster retention within workplaces. In this context, this study focuses on the Nurse Manager Actions scale, aiming to evaluate its items' scalability as well as the scale's validity and reliability among nurses and nurse managers operating within the Italian healthcare context. The study protocol was not registered. To ensure linguistic and cultural alignment, an iterative and collaborative translation process was undertaken. Subsequently, a multi-center cross-sectional design was adopted. Using a web-survey approach, data were collected among 683 nurses and 188 nurse managers between August 2022 and January 2023. The Nurse Manager Actions scale was found to be a valid and reliable instrument in Italian after a Mokken Scale Analysis. For nurses ( H T = 0.630, Molenaar-Sijtsma rho = 0.890), the scale included 6 items, while 11 items were confirmed for nurse managers ( H T = 0.620, Molenaar-Sijtsma rho = 0.830). Nurse Manager Actions scale scores were correlated with increased satisfaction and decreased intention to leave for both nurses and nurse managers. The employed validation process enhanced the scale validity for use in Italy and provided a model for other researchers to follow when assessing similar measures in different populations. Measuring and empowering nurse manager actions in work contexts is essential to improve the general well-being and retention of nurses, especially in the current nursing shortage.
Keyphrases
  • healthcare
  • primary care
  • mental health
  • cross sectional
  • randomized controlled trial
  • magnetic resonance imaging
  • quality improvement
  • big data
  • patient reported outcomes
  • double blind