The influence of diagnostic resources on the communication of nurses with simulated patients during admission interviews
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NANDA International 2012 Conference Abstract
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Session 2.5
Education & Implementation Track

Author
Wolter Paans

Question
The aim of this study was to explore whether diagnostic rescources influences nurses' communication during an assessment interview. What is the influence of diagnostic resources for nursing diagnoses on nurses’ communication during an assessment interview?

Results / Findings
As we focus on communication toward the eleven functional health patterns,  three out of eleven items score significant differences between groups: Cognitive/Perceptual pattern (p= 0.007), Sexual/Reproductive pattern (p= 0.004) and Coping/Stress/Tolerance (p= 0.003). As we center affective communication we see that reassurance (p= 0.041) and asking for reassurance (p= 0.005) appeared to be as a significant contrast, except direct approval (0.023) no significant differences between groups were found. We did not find significant differences in domains as ‘Closed questions’ and ‘Open-ended questions’, ‘Communication related to information’ or ‘Advice’.

Discussion / Conclusion
Knowledge sources influence the nurse-patient communication on several aspects, although it is not evidently that these sources improve the communication.

Method
A randomized, controlled trial design(RCT) was used to determine how diagnostic resources affect nurses’ communication in an admission interview, using case histories and simulated patients. Clinical nurses,29 in Group A, and 31 in Group B, were invited to derive diagnoses based on an assessment interview with a simulated patient (a professional actor) using a standardized script. Participants were randomly allocated to one of the two groups – group A could use an assessment format with Functional Health Patterns and standard nursing diagnoses(labels),handbooks nursing diagnoses and a predefined record structure in the PES-format. The other group (B) acted as the control group and used no resources at all. Qualitative data coding based on the RIAS-instrument was applied by using ATLAS TI, version 6.0, software for qualitative data analysis. For the following statistics we used SPSS, version 16.0. Inter-observer agreement of the RIAS-instrument was estimated by Pearson’s product moment correlation coefficients of 6 transcribed video recordings. The t-test was used to estimate differences in groups along with  means and standard deviations.

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