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¶ … DNP student gained much from the immersion project, especially from interacting with clinicians specializing in oncology and the cancer patients. The planning, executing, and analyzing the DNP project provided additional experience into clinical research, especially concerning the self-efficacy of patient coping before and after implementing a psychoeducational intervention. While the DNP student expressed concern over failing to reach the goal of 40 patients participating in the study or statistical significance, I imagine that much was gained by the experience as a whole.
Given a p value of 0.607, it seems unlikely that reaching the goal of 40 patients would have made much difference in the statistical outcome. Additionally, this p value does not predict whether a larger sample size would result in a statistically-significant difference between pre- and post-treatment groups, because p values alone provide no information about effect sizes (Motulsky, 2014, p. 1020; Sullivan, 2012). If it can be assumed that the goal of 40 participants would have provided enough statistical power to reveal a meaningful difference due to the intervention, then the most conservative conclusion is that the intervention was not beneficial in terms of patient coping self-efficacy. This conclusion would be supported if the effect size was small, because a bigger sample size does alter effect size (Sullivan, 2012). Put another way: even if statistical significance was achieved, would the intervention be worth the time and money if the benefits were marginal at best? Even negative results are productive, however, because it allows researchers to move forward and begin to examine the efficacy of other interventions.
References
Heitzmann, C.A., Merluzzi, T.V., Jean-Pierre, P., Roscoe, J.A., Kirsh, K.L., & Passik, S.D. (2011). Assessing self-efficacy for coping with cancer: Development and psychometric analysis of the brief version of the Cancer Behavior Inventory (CBI-B). Psychooncology, 20(3), 302-12.
Motulsky, H.J. (2014). Common misconceptions about data analysis and statistics. Naunyn-Schmiedeberg's Archives of Pharmacology, 387(11), 1017-23.
Sullivan, G.M., & Feinn, R. (2012). Using effect size -- or why the P. value is not enough. Journal of Graduate Education, 4(3), 279-82.
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