Unit 8 Nursing Research
Author
Institution
“Were Type I and Type II errors avoided or minimized?” (Polit & Beck, 2010, p. 100)
Introduction
Statistics have been incorporated into almost every field of study. This is especially when there are studies to be carried out. It is well understood that statistical studies and results are obtained from research after making certain assumptions, as well as trying to prove or disapprove a certain hypothesis. In most cases, errors are inevitable. There are, fundamentally, two types of errors that are quite common in statistical results. These are type I and type II errors. A Type I error occurs in instances where researches reject the null hypothesis whereas it was, in fact, true. In the study provided, the type I error would occur in case the researchers reject the hypothesis that informing breast surgery patients on the effects of analgesics does not influence the postoperative mobilization and postoperative pain levels. This error is also known as false-positive error. A type II error, on the other hand, results when researchers accept a false, null hypothesis, or rather make a false negative conclusion (Polit & Beck, 2009). It is worth noting that Type II errors are not considered as truly an error since when statistical tests are not significant, it only means that the data does not offer strong evidence as to the false nature of the null hypothesis.
In essence, the lack of significance does not support the conclusion as to the true nature of the null hypothesis. In essence, researchers would not conclude that the null hypothesis was true while the statistical test is not significant, rather they would consider the tests inconclusive. While it is desirable to minimize the risk of type I and Type II errors, it is worth noting that the reducing the risk of a Type I error heightens the risk of Type II error (Polit & Beck, 2009). An increase in the strictness of the criterion for rejecting a null hypothesis increases the likelihood of accepting a false, null hypothesis (Polit & Beck, 2009).
In my opinion, the study on whether informing patients about the effects of analgesics influences the postoperative pain levels made efforts to minimize the type I error. Type I error is minimized by ensuring that the level of significance is low. The level of significance is given the symbol α (alpha) and shows the probability of making a type I error. It is worth noting that the level of significance usually takes the value 0.5 or 0.1. The minimum acceptable level of significance (alpha) is 0.05. For the two levels of significance used (0.01 and 0.5), the risk of making Type I error is lowest in 0.01, where researchers run the risk of wrongly rejecting the null hypothesis in only one sample for every 100 samples. It is worth noting that the differences in the pain intensities (PID) between the control group and the test group were not significant (p=0.574). In addition, the mean for the Pain intensities for the test group were lower than in the case of the control group at 2, 3,4,5, and 6 hours, while their differences were p=0.05, which means they were statistically significant (Sayin & Aksoy, 2012). As much as the Pain Intensities’ mean for the test group was lower than the paint intensity of the control group before discharge, the difference is not significantly significant. The low significance levels for the pain intensities mean that the risk for running a Type I error was significantly reduced.
As stated, a reduction in type I error triggers an increase in the risk for Type II errors. However, the risk of type II error may be reduced by increasing the sample size (Polit & Beck, 2009). However, it is not evident that the researchers made an effort to increase the sample sizes.
References
Sayin, Y. & Aksoy, G. (2012). The effect of analgesic education on pain in patients undergoing breast surgery: Within 24 hours after the operation. Journal of Clinical Nursing
Polit, D.F., & Beck, C.T. (2009). Essentials of nursing research: Appraising evidence for nursing practice (7th ed.). Philadelphia: Lippincott Williams &Wilkins.
(Sayin & Aksoy, 2012) (Polit & Beck, 2009)
