Relationship between Simulation in Nursing Education and Medication Safety - Essay Example

Research Critique      Quantitative Study Sears, K., Goldsworthy, S., & Goodman, W. . The relationship between simulation in nursing education and medication safety. Journal of Nursing Education, 49(1), 52-55. DOI: 10.3928/01484834-20090918-12 Problem Problem Statement The problem is identified as a gap in research knowledge where there is a need to demonstrate how skills and knowledge acquired in a simulated environment can be transferable to real clinical situations (Sears et al., 2010, p. 52). Research Question/s The research question was: “Does the use of a simulation by second year BSN students in medical/surgical and maternal child placement environments influence the students’ ability to safely administer medications? (Sears et al., 2010, p. 52)” Hypothesis   The identified directional hypothesis is stated as follows: “The test hypothesis was that students’ experience in the simulation laboratory would increase the students’ abilities to safely administer medications in the clinical area” (Sears et al., 2010, p. 52-53). Independent and dependent variables An independent variable is a variable that the researcher has control over. In this case, the independent variable in the research was the mode of training adopted for nursing education. The manipulation of this variable was attained by assigning differing models of nursing education delivery, which included clinical simulation-based education and actual clinical placement. The dependent variable is the measured element of interest, which is affected in the research, and in this research the dependent variable was the medication errors (Sears et al., 2010, p. 52). Significance of Problem The problem presents an opportunity to bridge the gap in knowledge so as to effectively achieve a reduction in medication errors and make appropriate decisions with regard to placements (Sears et al., 2010, p. 52). Justification of the Study The study was justified by the fact that most Canadian Schools found it hard to acquire enough clinical placements for their students. As such, it was necessary to determine whether simulations were as effective as actual placements. The confirmation of efficiency would mean that the shortage of clinical placements would be solved through implementation of simulations. Literature Review The literature review provided is relevant to the study and it cites the need to bridge an identified gap in knowledge as the rationale behind the study. The connection of the study to previous studies is established, but the previous studies are not critically reviewed. The conceptual framework of the study is clearly stated. However, there is no clear summary of the previous literature. Methods Experimental Design The research design used for this research was a randomized control group, post-test-only design, which is an experimental design (Sear et al., 2010, p. 53). Description of Random Assignment: Random assignment of voluntary participants into three treatment groups was conducted on 54 volunteering students that were ready for placement (Sears et al., 2010, p. 52). Operational definition of interventions and outcome variables The simulation based education was the cited intervention in the study. The outcome variables included two categories of errors-medical errors from maternal units and medical-surgical units. Sample Population: The sampled population is clearly identified as second-year nursing students undertaking a Bachelor of Science degree in nursing (BSN), and about to undertake their placement. Description of Sampling Technique: Prospective participants were informed and invited to participate in the study. The resulting willing participants were randomly assigned to three groups (Sears et al., 2010, p. 52). Description of Random Selection: Random selection and assignment of voluntary participants was conducted on 54 volunteering students that were ready for placement (Sears et al., 2010, p. 52). Subject Recruitment: The recruitment of subjects is extensively highlighted. This included the identification of the population to be sampled as well as the approach to sampling. The acquisition of consent is outlined in the following quote: “In a preliminary session, second-year BSN students who were entering either a medical-surgical or an obstetrical placement were informed about the study and their opportunity to participate voluntarily. The volunteer list became the sampling frame.” Voluntary participation implies consent was obtained. Description of Participants: The participants in the research are not well described within the study because demographic data was not collected. The only fact known about the participants is that they were second-year students undertaking a Bachelor of Science degree in Nursing. The group specifically consisted of participants selected from students about to undertake clinical placement as part of the requirements in their study. Sample size/Number of subjects: The original sample consisted of 54 volunteering students from whom a random selection was done during the sampling process (Sears et al., 2010, p. 52). Number of Subjects: The total number of subjects in the study was 54 students. Subject access: Subject access was obtained by checking the department for students about to undergo placement after their second year of studies. Power Analysis: Power analysis, which denotes the capability to find a significant statistical difference in the test of the hypothesis, was determined by the sample size. This is evidenced within this quote: “For a simple test of whether the treatment group exhibited fewer errors than expected based on the relative numbers of treatment and control participants, the planned sample size could detect a minimum difference of approximately 14% with 70% power” (Sears et al., 2010, p. 53). Subject demographics: The collected demographics included the violated rights in errors, potential and actual severity of the outcome as well as factors contributing to error incidents for each participant (Sears et al., 2010, p. 53). Inclusion and Exclusion Criteria: There is no explicit mention of any exclusion criteria for the study. On the other hand, the inclusion criterion for the study was that prospective participants had to be volunteers from the second-year BSN class and about to undertake their placements. Setting The setting where subjects are obtained is described as medical school institution. However, access to the setting is not described. IRB Review Request: Ethical approval of the study was done by the research ethics board, which is akin to the IRB. Confidentiality: Confidentiality was by the researchers’ act of not collecting demographic data on the subjects. Data Storage: Collected data was stored in a locked cabinet. Data Destruction: The destruction of data is not described in the study. Consent Process: The researchers sought consent from the prospective students by first informing them about the study, and thereafter; seeking their voluntary participation. Participation Incentives: The study did not use any incentives to enhance participation. Instrumentation Data Collection Instrument Survey forms were used as the data collection instruments and these were filled by the instructors and students (Sears et al., 2010, p. 53). Observed medication errors were entered into forms that only bore the instructor’s name in order to preserve the confidentiality of the participating students. Average Instrument Completion Time: There was no information on the average time for completion of the designated data collection instruments. Reliability of Instrument: Information sessions were conducted with the instructors in the clinical set up before the start of the study as a way to establish inter-rater reliability (Sears et al., 2010, p. 53). Validity of Instrument(s): Validity of the instrument used in the study was determined through the dual establishment of content and face validity, which involved a review of other studies and a search for expert opinion (Sears et al., 2010, p. 53). External validity The external validity of the research was low because the research cannot be widely generalized. In spite of randomly selecting the participants, generalization cannot be possible for other populations and locations because all participants were from a single collaborative nursing program. This limitation reduces the external validity, but it can be overcome if the research could be replicated for different populations and locations across different times (Sears et al., 2010, p. 54). Response Rate Description: The response rate was 100% percent because all the 54 participants that volunteered undertook the study, and none left the assigned groups. Data Collection Sequence of Activities: The whole research process is well described and it starts with the informing of participant about the study. Thereafter, consent is sought and the data collection process is sequentially described. It starts with a debriefing phase where participants familiarize themselves with study process before participation and eventual actual data collection. Data Collection Timing: The data collection timing on the study was partially described. Students were granted an hour for preparation and two hours to bridge identified gaps before engaging in the actual exercise to be assessed. Participant Instructions: Participant instructions are well described and they include study information, consent search, debriefing, preparation and actual study exercise instructions. Data Collection Site Description: The data collection sites are well described, and these include a maternal unit and a medical-surgical unit. Attrition of Subjects: The attrition effect was not covered and neither was any information about attrition. Data Analysis Sufficiency of Findings in Answering Research Questions: The findings were able to answer the research question. They proved that that simulation has a significant effect in reducing errors among placement groups regardless of their department in comparison clinical placement. Data Analysis Software: SPSS was used as the data analysis software in the study. Descriptive Statistical Results Descriptive statistics in the study are described, and these offer a brief overview on a number of characteristics of the variables in the study. Descriptive statistics denote quantitative descriptions of the collected data. The critical analysis of the paper considered the following listed descriptive statistics, however, not all of them were found within the paper or study under critique. The considered descriptive statistics included frequency (f), mean (M), median (Mdn), Number sub-sample (n), total number in sample (N), percentage (%), standard deviation (SD) and standard score (z). Identifiable descriptive statistics included the total number of participants in the sample (N), which stood at 54 in number. This included all participants in the two control and two treatment groups. The number of participants in sub-samples (n) (treatment and control groups) was as follows. The sub-samples under maternal placement had 18 participants in the control group and 10 participants in the treatment group (Sears et al., 2010, p. 53). The medical-surgical sub-samples were 12 and 14 under the control and treatment group respectively. Frequency also appears as a descriptive statistic showing number of repeated occurrences per specific time. The frequency statistic was used in measuring the number of errors that occur in a specific time (Sears et al., 2010, p. 54). The frequency statistics was used in showing characteristics of the error rate variable. Other descriptive statistics such as mean, median, percentage, standard deviation and the standard score were evidently missing in the study’s documentation. Inferential Statistical Results Inferential statistics denote analytical measures on sample data aimed at reaching conclusions, which extend beyond the face value of collected data. These measures that show trends that are not easily apparent even through descriptive statistics. The generally reveal trends in the population by analytical review of the sample. The critical analysis of the paper considered the following listed inferential statistics. However, not all of them were found within the paper or study under critique. The considered inferential statistics included the analysis of variance (ANOVA), degrees of freedom, F-test, probability (P), Pearson product-moment correlation (r), non-significant (ns), computed value of t-test (t), multiple correlation (R), multiple correlation squared (R2), sigma (sum), delta (change level), type II error probability (Beta), type I error probability and Chi-Square (X2). Identifiable inferential statistics included chi-square tests, which were used to compare the observed error results in the study in relation to the expected error levels. The chi-square tests compared expected versus actual frequencies. The chi-square test results showed a significant difference between the control and treatment groups for both maternal and clinical placements. The difference was highly significant at a p Read More