Effects of Customized Communication Training on Nonviolent Communication, Nonverbal Communication, and Self-Acceptance: Evidence from Korean Nursing Students.
Iranian Journal of Public Health, 2023, 52(9), p. 1942.
Jung, H., Lee, Y. H., & Park, J. H.
DOI : 10.18502/ijph.v52i9.13576
Full article: link
Abstract:
The aim of this study was to examine the effects of CNV training on non-verbal communication, self-acceptance and the level of Non-Violent Communication, in Korean nursing students. The study involved a total of 74 participants, including a test group of 38 students and a control group of 36 students. The test group received 6.5 hours of CNV training. Compared with the control group, the test group showed a significant improvement after the intervention in the area of non-violence. However, there were no significant differences between the groups in non-verbal communication or self-acceptance scores after the intervention.
Comment: The authors use a pre-post experimental design, i.e. they test students before and after NVC training. They also use a control group, an essential step in ruling out test-retest bias.
However, as the authors concede in the discussion section of their article, they studied the results of the training at the very end. These are therefore very short-term effects.
They also add that, as the questionnaires are self-reported, they are subject to participant bias. For example, since the stakes of the training are quite obvious, it seems easy for the test group to fall victim to confirmation bias, by “unconsciously” answering in such a way as to increase their scores on the NVC tests.
Thus, it would seem that this study validates rather an understanding of NVC following NVC training, than implicitly acquired skills.
Perspective: This study invites us to look at the longer-term effects of NVC training (e.g. at 3 months, 6 months, 1 year), to evaluate the effects. And it would be interesting to see whether the lack of effect of this training on self-acceptance and non-verbal communication is statistically significant, which can be done with the use of other statistical tools (e.g. Bayesian factors).