Related Experiment Video
Updated: Mar 8, 2026
SECONDs Administration Guidelines: A Fast Tool to Assess Consciousness in Brain-injured Patients
Published on: February 6, 2021
Validation of Finnish Neecham Confusion Scale and Nursing Delirium Screening Scale using Confusion Assessment Method
Satu Poikajärvi1,2, Sanna Salanterä1,3, Jouko Katajisto4
1Department of Nursing Science, Faculty of Medicine, University of Turku, Turku, Finland.
Background:
Delirium is a common clinical problem with acute and fluctuating onset. Early notification of its symptoms can lead to earlier detection and management of this state. Valid and reliable instruments are required for successful nursing practice. The purpose of the study was to psychometrically test the Finnish versions of the Neecham Confusion Scale (NEECHAM) and the Nursing Delirium Screening Scale (Nu-DESC) in surgical nursing care, utilizing the Confusion Assessment Method (CAM) algorithm as a comparison scale.
Methods:
This randomized, blinded, instrument testing study was conducted at one university hospital in one surgical unit. Study patients (n = 112) meeting the pre-set criteria were assessed by the principal investigator (PI) and a registered nurse (RN, n = 18). Internal consistency, inter-rater reliability, and concurrent validity of the scales were calculated and face validity and usability evaluated.
Results:
Internal consistency was from .76 to .86 for all three scales. Inter-rater reliability between PI and RNs was .87 with NEECHAM, .60 with CAM and .47 with Nu-DESC. Concurrent validity was .56 and .59 between CAM and NEECHAM, and .68 and .72 between NEECHAM and Nu-DESC. In the PI group, the correlation between CAM and Nu-DESC was .91, in the RN's group .42. Nu-DESC was evaluated as the most usable scale.
Conclusion:
The findings strengthen the earlier research on the scales and indicate that the Finnish NEECHAM and Nu-DESC correlates with CAM algorithm and with each other. They seem to be clinically viable in assessing patients' delirium in surgical wards but more validity testing is needed.
