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Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students
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Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students Young Sook Roh a, Eun Ju Lim a,∗, S. Barry Issenberg b a
Red Cross College of Nursing, Chung-Ang University (CAU), 84 Heukseok-ro Dongjak-gu, Seoul 156-756, Republic of Korea b Michael S. Gordon Center for Research in Medical Education, University of Miami Miller School of Medicine, United States Received 2 March 2013; received in revised form 8 July 2014; accepted 8 October 2014
KEYWORDS Cardiopulmonary resuscitation; Knowledge; Patient simulation; Psychomotor performance; Self-efficacy
∗
Summary Background: This study evaluates the effectiveness of integrated simulation-based resuscitation skills training combined with a clinical practicum by assessing nursing students’ knowledge, psychomotor skills, and self-efficacy. Methods: In a pretest—posttest design, 255 second-year nursing students participated in an emergency nursing clinical course consisting of a two-hour simulation-based resuscitation skills training component along with an 80-hour clinical placement in an emergency department. Knowledge, self-efficacy, and psychomotor skill errors were measured. Analyses of pre- and post-test data were performed on three subgroups: the simulation-only group, the simulation with clinical observation group, and the simulation with clinical performance group. Students were divided into these groups based on resuscitation experiences during their clinical practicum in the emergency department. Results: Mean scores of knowledge (z = −13.879, p < .001) and self-efficacy (z = −10.969, p < .001) significantly improved after the clinical practicum compared to baseline. Knowledge (F = .502, p = .606), psychomotor skill error (F = 1.587, p = .207), and self-efficacy (F = .481, p = .619) did not significantly differ among the three subgroups after controlling for two covariates (age, Basic Life Support certification) in the analysis of covariance models.
Corresponding author. Tel.: +82 2 820 5996; fax: +82 2 824 7961. E-mail address: [email protected] (E.J. Lim).
http://dx.doi.org/10.1016/j.colegn.2014.10.002 1322-7696/© 2014 Australian College of Nursing Ltd. Published by Elsevier Ltd.
Please cite this article in press as: Roh, Y. S., et al. Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students. Collegian (2014), http://dx.doi.org/10.1016/j.colegn.2014.10.002
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Y.S. Roh et al. Conclusion: Integrated simulation-based resuscitation skills training combined with a clinical practicum might be beneficial for enhancing mastery learning and self-efficacy in nursing students through learner engagement and feedback. © 2014 Australian College of Nursing Ltd. Published by Elsevier Ltd.
1. Background
2. Purpose
Cardiopulmonary resuscitation (CPR) is an essential skill required by nursing students for clinical practice, as nurses are frequently first responders in hospital code situations (Kardong-Edgren, Oermann, Odom-Maryon, & Ha, 2010). Studies document that CPR skills among nursing students are lacking (Mäkinen et al., 2010; Oermann, Kardong-Edgren, & Odom-Maryon, 2011). Regardless of how nursing students received their Basic Life Support (BLS) training, their CPR psychomotor skills begin to decline within a few weeks after instruction (Madden, 2006). Research indicates that nursing students can acquire additional CPR knowledge and skill following instructor-led training (Madden, 2006). Some studies demonstrate that practicing CPR skills only 6 min a month helps students maintain or improve their CPR skills over a 12-month period (Kardong-Edgren et al., 2010; Oermann et al., 2011). Simulation-based resuscitation training is an appealing technique for enhancing clinical experience, maximizing learning, and limiting the frequency and impact of medical errors (Weinstock et al., 2005). Some authors believe that simulation should be used alongside clinical practice (Kneebone, Scott, Darzi, & Horrocks, 2004), and that medical simulation complements educational activities based on real patient-care experiences (McGaghie, Siddall, Mazmanian, & Myers, 2009). However, a recent meta-analytic review demonstrated that simulation-based medical education with deliberate practice is superior to traditional clinical medical education for learning specific clinical skills (McGaghie, Issenberg, Cohen, Barsuk, & Wayne, 2011). In a study by Watson et al. (2012), the clinical competencies achieved by physiotherapy students were just as high in the simulated learning environments as in the traditional clinical immersion. A growing body of evidence indicates that simulation-based medical education is superior to traditional clinical education for learning advanced cardiac life-support skills (Wayne et al., 2005, 2006). However, there is little evidence to support simulation as an alternative to traditional real-life clinical practice. Effective medical learning stems from deliberate practice with clinical problems and devices in simulated settings, in addition to patient care experiences (Issenberg, McGaghie, Petrusa, Lee Gordon, & Scalese, 2005). Since 2011, our school has developed and implemented an integrated simulation-based resuscitation curriculum combined with a clinical practicum in the emergency department. In order to develop a better resuscitation curriculum, it is necessary to evaluate the integrated curriculum by measuring the learning outcomes of nursing students. In addition, how to best configure a learning simulation within clinical immersion is unknown; however, since no studies have been conducted with nursing students, there is a need for further research.
The purpose of this study was to evaluate the effectiveness of integrated simulation-based resuscitation skills training combined with a clinical practicum in an emergency department by assessing mastery learning and self-efficacy in nursing students.
3. Methods 3.1. Design A single-group pre-and post-test design was used for this study. Due to the different experiences of students in their practicum, three distinct groups emerged, resulting in a between group analysis (simulation-only group, simulation with clinical observation group, and simulation with clinical performance group) (Fig. 1).
3.2. Setting and participants For the sample size, it was estimated that 66 participants were required to maintain an effect size (d = .5) with 95% power and a significance level of .05 for ANOVA using G*Power 3 (Faul, Erdfelder, Lang, & Buchner, 2007). The effect size was derived based on a pooled effect size of .62 for multiple learning strategies found in a systematic review and meta-analysis of the comparative effectiveness of instructional design features in simulation-based education (Cook et al., 2013). A non-random convenience sample of second year nursing students enrolled in a clinical placement course in the second semester of 2011 (n = 124) and the first semester of 2012 (n = 143) were invited to participate in the study. We selected participants from naturally occurring groups (20—24 students) that rotated through the emergency department clinical placement every two weeks. After the exclusion of 12 questionnaires due to incomplete data, 255 (96%) questionnaires were used in the final analysis.
3.3. Procedure The Ethics Committee of the College of Nursing granted ethical approval for the study. All students agreed to participate in the study and signed the informed consent form, which promised confidentiality, prior to participation. Although, subject anonymity was not possible due to matching the subject’s self-reported questionnaire score with their CPR psychomotor skills performance, subject confidentiality was maintained. We conducted the study from September 2011 to May 2012. All simulation sessions took place in a Nursing
Please cite this article in press as: Roh, Y. S., et al. Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students. Collegian (2014), http://dx.doi.org/10.1016/j.colegn.2014.10.002
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Effects of an integrated simulation-based resuscitation skills training
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Second year nursing students rotated through the emergency department clinical placement (N = 267)
Pre-test (N = 267) -Mastery learning in CPR knowledge: Multiple-choice questionnaires -CPR psychomotor skills: Resusci Anne SkillReporter TM -Resuscitation Self-efficacy Scale Intervention (N = 267) An integrated simulation-based resuscitation skills training combined with clinical practicum -Instructor-led simulation-based resuscitation skills training (2 hr): 30-min lecture, 60-min skill training, 10min testing, 20-min debriefing -Clinical Practicum in an emergency department (80 hr)
Post-test (N = 255) -Mastery learning in CPR knowledge -CPR psychomotor skills -Resuscitation Self-efficacy Scale
Additional subgroup comparison analysis* -Simulation-only group (n = 73) -Simulation with clinical observation group (n = 157) -Simulation with clinical performance group (n = 25) *Students were divided into these subgroups based on resuscitation experiences during a clinical practicum in the emergency department.
Figure 1
Simulation Center at a College of Nursing. Of the 24 nursing students per clinical rotation, two to six students were assigned to one of seven different emergency departments for two weeks each, over a period of two semesters. Each of the seven emergency departments had 22—46 hospital beds. In this study, the integrated simulation-based resuscitation training combined with a clinical practicum consisted of a two-hour CPR practice session with a mannequin and a two-week, 80-hour clinical practicum in an emergency department. The 2-hour simulation-based resuscitation training consisted of a 30-min lecture on BLS principles and the algorithm of a cardiac arrest patient, 60-min BLS task training and 10-min testing sessions, and a 20-min debriefing. An instructor with BLS expertise led the lecture, task training, and testing sessions. A group of 24 nursing students per session was trained and tested throughout the semester. Two teams of 12 nursing students participated in the instructor-led training session. Practice sessions for CPR psychomotor skills training took place one week before the nursing students’ emergency department practicum rotation, at the Nursing Simulation Center. Before the skill session, all participants studied the BLS principles and algorithm. All participants then received a 30-min didactic lecture about the Korea National Adult BLS Guidelines, as well as a one-hour CPR skills training session. The session included hands-on practice using videomediated, practice-while-watching instruction. CPR training was conducted using a static mannequin comprising a torso and head that was placed in a hospital bed. After training, all participants tested their CPR skills on sensor-equipped mannequins (Resusci AnneTM ; Laerdal Medical, Stavanger, Norway). At the end of the session, the instructor gave
Study flowchart.
feedback based on students’ performance data collected from the SkillReporter to reflect and analyze their actions. Those who failed to meet qualifications based on the 2010 American Heart Association Guidelines for CPR were told to participate in more deliberate practice until mastery was reached. After the clinical practicum, participants completed a knowledge test, a self-administered questionnaire, and then tested their CPR skills on sensor-equipped adult mannequins. Three instructors participated in 4 h of clinical teaching in one or two emergency departments. During the 80-hour clinical placement, unit managers in the emergency department were in charge of guiding nursing students according to the guidelines of the practicum course manual.
3.4. Measures Nursing students underwent instructor-led BLS training one week before the clinical placement in an emergency department, and completed testing and self-administered questionnaires before and after the emergency department practicum. 3.4.1. Demographic data These included age, gender, BLS certification, and resuscitation experience during the emergency department’s clinical practicum. 3.4.2. Mastery learning in BLS knowledge This was measured using multiple-choice questionnaires (MCQs) based on the Korean version of the BLS Course
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Y.S. Roh et al.
Pretest Questionnaire (www.kacpr.org), a 10-item, paperand-pencil multiple-choice questionnaire, which included the BLS algorithm and overall principles. Each item was scored as either 0 (false response) or 1 (true response), with a higher score indicating a higher level of knowledge. Out of the 10 items, one pretest item and two posttest items were deleted due to low discrimination indices (D < .2). A minimum acceptable value for the D index is about +.20 or so (Downing & Yudkowsky, 2009). The removed items were as follows: ‘‘You are providing rescue breathing using a bag-mask device. What action will confirm that each of your rescue breaths is adequate?’’ (D = .144); ‘‘Which of the following is the best explanation for the need to train rescuers to perform CPR and use an AED?’’ (D = .101), and ‘‘You are doing CPR on a man who was found in a no-response condition. What is the recommended ratio of compressions to breaths?’’ (D = .058). After deleting these three items, the range for D index on the final pretest and posttest were .203—.652, .217—.710, respectively. Therefore, nine pre-test items and eight post-test items were used for the final analysis after converting the scores to a maximum of 100 points. 3.4.3. Mastery learning in CPR psychomotor skills This was assessed with a CPR performance summary report (statistical data) using a Laerdal Resusci Anne SkillReporter mannequin (Laerdal, Stavanger, Norway), which is regarded as the standard for objectively measuring discrete CPR skills (Kardong-Edgren et al., 2010). In pairs, students performed compressions, ventilations with bag-valve mask, and single-rescuer CPR for 3 min each at all of the time points. Performance was evaluated based on ventilation rate and volume, compression rate, and compression depth. In addition, CPR psychomotor skill errors were calculated using the Numerical Scoring System (Madden, 2006). Value labels were assigned to five skill components: if the skill component was performed correctly, zero error points were given. If the student performed the skill component incorrectly, she/he was given 10 or 20 skill error points depending on the severity of the aberration. Skill error points ranged from 0 to 100, with lower skill error scores indicating better CPR psychomotor skills. 3.4.4. Resuscitation self-efficacy This was measured with the Resuscitation Self-Efficacy Scale (Roh, Issenberg, Chung, & Kim, 2012) to assess nursing
Table 1
Baseline characteristics of participants.
Variable
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
students’ perceptions of their capability to organize and execute a course of action in cardiac arrest situations. The scale consisted of 17 items in four domains: recognition, debriefing and recording, responding and rescuing, and reporting. Participants were asked to respond using a 5-point Likert-type scale. Scores ranged from 1 to 5, with high scores indicating greater perceived self-efficacy. Other studies reported a .914 alpha coefficient for this scale (Roh et al., 2012). The alpha coefficient for the present study was .890 for the pretest, and .835 for the posttest.
3.5. Data analysis Data were analyzed using SPSS version 20.0 (SPSS Inc., Chicago, IL). Wilcoxon signed-rank tests were used to compare the variables at baseline and after the clinical practicum because a Kolmogorov—Smirnov (K—S) test revealed that the distribution of the sample was not normal. Based on the nursing students’ resuscitation experience during the emergency department’s clinical practicum, they were divided into three subgroups: the simulationonly group, the simulation with clinical observation group, and the simulation with clinical performance group. A Kruskal—Wallis one-way analysis of variance was used to compare the study variables among these three subgroups. Adjusted analyses were also performed that included baseline variables (age, BLS certification) that were thought to possibly influence the results, as covariates in the analysis of covariance (ANCOVA) models.
4. Results 4.1. Baseline characteristics of nursing students Almost 91% of the participants were women. The mean age of the participants was 21.81 ± 4.52 years. Approximately 19% of the participants had BLS-provider certificates. Observing (n = 157, 62%) was the most frequent role during emergency department code situations, with only 10% (n = 25) of students having performed CPR skills under the supervision of doctors. A Kruskal—Wallis H test revealed a statistically significant difference in age among the three groups, 2 (2) = 14.696, p < .001. There were no significant differences in gender and percentage of BLS certification holders among the three groups (Table 1).
Simulation with clinical performance group (n = 25)
Total
2
p
22.68 ± 4.84 22 (88.0)
21.81 ± 4.52 232 (91.0)
14.696 .328
<.001 .849
.716
.699
Mean ± SD or N (%) Age Gender (female, %) BLS certification holder
20.97 ± 4.03 67 (91.8) 12 (16.4)
22.05 ± 4.65 143 (91.1) 30 (19.1)
6 (24.0)
48 (18.8)
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Effects of an integrated simulation-based resuscitation skills training Table 2
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Mean differences of knowledge, psychomotor skills, and self-efficacy (N = 255).
Variable
Baseline
After clinical practicum
z
p
Mean ± SD CPR knowledge Self-efficacy Recognition Debriefing and recording Responding and rescuing Reporting CPR psychomotor skills Ventilation volume (ml) Ventilation rate (per min) Compression depth (mm) Compression rate (per min) Incorrect hand placement (%) Inadequate chest recoil (%) Total skill error point
49.15 3.15 3.46 2.90 2.79 3.53
± ± ± ± ± ±
17.00 0.48 0.51 0.58 0.71 0.54
55.29 3.55 3.89 3.25 3.29 3.84
± ± ± ± ± ±
19.12 0.42 0.48 0.49 0.61 0.48
−13.879 −10.969 −9.915 −7.935 −9.783 −7.612
<.001 <.001 <.001 <.001 <.001 <.001
525.06 3.99 46.01 114.91 16.69 0.53 35.35
± ± ± ± ± ± ±
137.69 1.51 5.55 13.79 27.66 2.74 16.09
549.65 4.40 48.78 113.80 7.41 0.74 25.63
± ± ± ± ± ± ±
78.93 1.50 4.66 11.89 13.82 4.76 17.06
−2.161 −3.056 −6.879 −1.556 −4.192 −.555 −7.045
.031 .002 <.001 .120 <.001 .579 <.001
4.2. Comparison of knowledge, self-efficacy, and psychomotor skills After completing the simulation-based resuscitation course in conjunction with the emergency department practicum, the nursing students’ CPR knowledge scores (z = −13.879, p < .001) and self-efficacy (z = −10.969, p < .001) were significantly increased, compared to baseline (Table 2). Furthermore, the average scores in all the self-efficacy subscales increased. The largest average difference was with recognition efficacy (z = −9.915, p < .001); the smallest average difference was with reporting efficacy (z = −7.612, p < .001). Of the CPR psychomotor skills measured by the Resusci Anne SkillReporterTM mannequins, the accuracy of ventilation volume (z = −2.161, p = .031), ventilation
Table 3
rate (z = −3.056, p = .002), compression depth (z = −6.879, p < .001), and hand placement (z = −4.192, p < .001) increased significantly, but compression rate (z = −1.556, p = .120) and chest recoil (z = −.555, p = .579) did not. As shown in Table 3, there were no statistically significant mean differences from Time 1 to Time 2 in knowledge (2 = .586, p = .746), psychomotor skill error (2 = 3.827, p = .148), and self-efficacy (2 = 2.718, p = .257) among the three subgroups as determined by the Kruskal—Wallis one-way analysis of variance. There were no statistically significant mean differences in knowledge (F = .502, p = .606), psychomotor skill error (F = 1.587, p = .207), and self-efficacy (F = .481, p = .619) among the three subgroups after controlling for the two covariates (age, BLS certification) in the analysis of covariance models (Table 4).
Comparison of knowledge, quality of CPR psychomotor skills, and resuscitation self-efficacy (N = 255).
Variable
Categorya
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
Simulation with clinical performance group (n = 25)
2
p
Mean ± SD Knowledge
Psychomotor skill error point
Self-efficacy
a
Time 1 Time 2 Difference Time 1
50.84 57.19 6.35 30.14
± ± ± ±
17.46 19.65 2.18 15.94
48.62 54.70 6.08 37.39
± ± ± ±
16.90 19.01 2.11 16.10
47.56 53.50 5.94 37.92
± ± ± ±
16.52 18.58 2.06 13.18
.586 .586 .586 10.893
.746 .746 .746 .004
Time 2 Difference Time 1 Time 2 Difference
23.47 −6.39 3.25 3.60 0.35
± ± ± ± ±
15.31 18.41 0.51 0.44 0.49
26.69 −10.70 3.08 3.50 0.42
± ± ± ± ±
17.95 20.79 0.45 0.39 0.47
25.20 −13.33 3.23 3.72 0.49
± ± ± ± ±
16.10 18.80 0.55 0.43 0.37
1.344 3.827 6.756 9.571 2.718
.511 .148 .034 .008 .257
Time 1: baseline, Time 2: after clinical practicum.
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Y.S. Roh et al. Table 4
Analysis of covariance for subgroup comparison (N = 255).
Variable
Categorya
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
Simulation with clinical performance group (n = 25)
F
p
Mean ± SD Knowledge
Psychomotor skill error point
Self-efficacy
a
Time 1 Time 2 Difference Time 1
50.62 56.94 6.33 30.28
± ± ± ±
17.48 19.67 2.19 16.01
48.62 54.70 6.08 37.39
± ± ± ±
16.90 19.01 2.11 16.10
47.56 53.50 5.94 37.92
± ± ± ±
16.52 18.58 2.06 13.18
.502 .502 .502 5.175
.606 .606 .606 .006
Time 2 Difference Time 1 Time 2 Difference
23.80 −6.20 3.24 3.60 0.36
± ± ± ± ±
15.15 18.47 0.51 0.45 0.49
26.69 −10.70 3.08 3.50 0.42
± ± ± ± ±
17.95 20.79 0.45 0.39 0.47
25.20 −13.33 3.23 3.72 0.49
± ± ± ± ±
16.10 18.80 0.55 0.43 0.37
.714 1.587 3.193 4.077 .481
.491 .207 .043 .018 .619
Time 1: baseline, Time 2: after clinical practicum.
5. Discussion Our findings increase our understanding of the synergetic effects of simulation-based resuscitation skills training combined with a clinical practicum, by comparing nursing students’ knowledge, self-efficacy, and CPR psychomotor skills, pre and post-interventions. The results of this study demonstrate that after completing the simulation-based resuscitation course in conjunction with the emergency department practicum, there was an increase in CPR skills scores. Previous research demonstrated that a simulation group had a significantly higher mean knowledge score post-test than the control group (Liaw, Scherpbier, Rethans, & Klainin-Yobas, 2011). Our results indicate the importance of simulation training for retaining information, which was a key factor for influencing the combination of simulation learning and clinical practice (Liaw, Chan, Scherpbier, Rethans, & Pua, 2012). In this study, resuscitation self-efficacy significantly increased after the clinical practicum, compared to baseline. Previous research demonstrates that simulation-based resuscitation training for healthcare professionals improved their self-efficacy (Turner, Dierselhuis, Draaisma, & ten Cate, 2007), and nursing students perceived that simulation increased their ability and confidence in their clinical placements (Baillie & Curzio, 2009). One of the possible explanations for this result is that gaining skill proficiency can increase self-efficacy (Bandura, 1997), and successful experiences in resuscitation courses increased perceived self-efficacy (Hunt, Fiedor-Hamilton, & Eppich, 2008). The most effective way to develop a strong sense of efficacy is through mastery experiences (Bandura, 1997); therefore, we suggest that efforts should be made to boost students’ self-efficacy through mastery experiences in their curriculum. Our study demonstrated that the accuracy of CPR psychomotor skills—–ventilation volume, ventilation rate, compression depth, and hand placement—–significantly increased post-intervention, but not compression rate and
chest recoil. Previous studies verified that simulation-based resuscitation training had positive effects on the mastery learning of advanced cardiac life-support skills in residents (Wayne et al., 2005, 2006). Although objective monitoring of repetitive practice is not part of this study, we provided feedback on the quality of CPR psychomotor skills and told nursing students to continue practice to improve their skills at posttest. The combination of feedback, selfdirected practice, and indirect or direct involvement in real hospital code situations may improve the quality of CPR psychomotor skills. In this study, only 10% of students performed CPR skills under the supervision of healthcare professionals during real emergency department code situations. The one-way ANOVA revealed that there were no significant mean differences in study variables among the three groups. One nursing study reported that students with simulation training achieved and maintained higher clinical performance scores more quickly than those without simulation. These findings suggest that patient simulation is a valuable addition to the apprenticeship model (Meyer, Connors, Hou, & Gajewski, 2011). It can be assumed that when students are personally involved in handling an emergency event, this could lead to experiential learning and a positive impact on students’ motivation (Pelaccia et al., 2009). However, it can be argued that traditionally, clinical education is insufficient if the goal is skill acquisition and downstream patient safety (McGaghie et al., 2011) due to limited simulation realism (McKenna et al., 2011). Therefore, the educational effectiveness of simulation combined with clinical practice should be considered for a better resuscitation curriculum. We suggest that integrated simulation-based resuscitation skills training with a clinical practicum might be beneficial for enhancing mastery and self-efficacy in nursing students. One limitation of this study might be the use of a one-group comparison design instead of a randomized controlled trial study. A small sample size for the simulation with clinical performance group increases the possibility for a Type II error.
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Effects of an integrated simulation-based resuscitation skills training
6. Conclusion Simulation-based resuscitation skills training linked with a clinical practicum improved nursing students’ knowledge, self-efficacy, and CPR psychomotor skills through learner engagement and feedback. Educators in schools and hospitals should carefully consider the educational effectiveness of simulation combined with a clinical practicum, take advantage of both learning modalities, and collaborate to facilitate better learning outcomes in resuscitation education. Further studies with a randomized controlled design are needed to verify the effects of simulation combined with clinical practice on graduate nurses’ clinical performance in real code situations and on patient outcomes.
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Mäkinen, M., Axelsson, A., Castrén, M., Nurmi, J., Lankinen, I., & Niemi-Murola, L. (2010). Assessment of CPR-D skills of nursing students in two institutions: Reality versus recommendations in the guidelines. European Journal of Emergency Medicine, 17(4), 237—239. http://dx.doi.org/10.1097/MEJ. 0b013e328331471b McGaghie, W. C., Issenberg, S. B., Cohen, E. R., Barsuk, J. H., & Wayne, D. B. (2011). Does simulation-based medical education with deliberate practice yield better results than traditional clinical education? A meta-analytic comparative review of the evidence. Academic Medicine, 86(6), 706—711. McGaghie, W. C., Siddall, V. J., Mazmanian, P. E., & Myers, J. (2009). Lessons for continuing medical education from simulation research in undergraduate and graduate medical education: Effectiveness of continuing medical education. American College of Chest Physicians Evidence-Based Educational Guidelines. Chest, 135(3), 62—68. McKenna, L., Bogossian, F., Hall, H., Brady, S., Fox-Young, S., & Cooper, S. (2011). Is simulation a substitute for real life clinical experience in midwifery? A qualitative examination of perceptions of educational leaders. Nurse Education Today, 31(7), 682—686. Meyer, M. N., Connors, H., Hou, Q., & Gajewski, B. (2011). The effect of simulation on clinical performance: A junior nursing student clinical comparison study. Simulation in Healthcare, 6(5), 269—277. Oermann, M. H., Kardong-Edgren, S. E., & Odom-Maryon, T. (2011). Effects of monthly practice on nursing students’ CPR psychomotor skill performance. Resuscitation, 82(4), 447—453. Pelaccia, T., Delplancq, H., Triby, E., Bartier, J. C., Leman, C., & Dupeyron, J. P. (2009). Impact of training periods in the emergency department on the motivation of health care students to learn. Medical Education, 43(5), 462—469. Roh, Y. S., Issenberg, S. B., Chung, H. S., & Kim, S. S. (2012). Development and psychometric evaluation of the Resuscitation Self-efficacy Scale for nurses. Journal of Korean Academy of Nursing, 42(7), 1079—1086. Turner, N. M., Dierselhuis, M. P., Draaisma, J. M., & ten Cate, O. T. (2007). The effect of the advanced pediatric life support course on perceived self-efficacy and use of resuscitation skills. Resuscitation, 73(3), 430—436. Watson, K., Wright, A., Morris, N., McMeeken, J., Rivett, D., Blackstock, F., et al. (2012). Can simulation replace part of clinical time? Two parallel randomized controlled trials. Medical Education, 46(7), 657—667. Wayne, D. B., Butter, J., Siddall, V. J., Fudala, M., Lindquist, L., Feinglass, J., et al. (2005). Simulation-based training of internal medicine residents in advanced cardiac life support protocols: A randomized trial. Teaching and Learning in Medicine, 17, 202—208. Wayne, D. B., Butter, J., Siddall, V. J., Fudala, M. J., Wade, L. D., Feinglass, J., et al. (2006). Mastery learning of advanced cardiac life support skills by internal medicine residents using simulation technology and deliberate practice. Journal of General Internal Medicine, 21(3), 251—256. Weinstock, P. H., Kappus, L. J., Kleinman, M. E., Grenier, B., Hickey, P., & Burns, J. P. (2005). Toward a new paradigm in hospital-based pediatric education: The development of an onsite simulator program. Pediatric Critical Care Medicine, 6(6), 635—641.
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Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students Young Sook Roh a, Eun Ju Lim a,∗, S. Barry Issenberg b a
Red Cross College of Nursing, Chung-Ang University (CAU), 84 Heukseok-ro Dongjak-gu, Seoul 156-756, Republic of Korea b Michael S. Gordon Center for Research in Medical Education, University of Miami Miller School of Medicine, United States Received 2 March 2013; received in revised form 8 July 2014; accepted 8 October 2014
KEYWORDS Cardiopulmonary resuscitation; Knowledge; Patient simulation; Psychomotor performance; Self-efficacy
∗
Summary Background: This study evaluates the effectiveness of integrated simulation-based resuscitation skills training combined with a clinical practicum by assessing nursing students’ knowledge, psychomotor skills, and self-efficacy. Methods: In a pretest—posttest design, 255 second-year nursing students participated in an emergency nursing clinical course consisting of a two-hour simulation-based resuscitation skills training component along with an 80-hour clinical placement in an emergency department. Knowledge, self-efficacy, and psychomotor skill errors were measured. Analyses of pre- and post-test data were performed on three subgroups: the simulation-only group, the simulation with clinical observation group, and the simulation with clinical performance group. Students were divided into these groups based on resuscitation experiences during their clinical practicum in the emergency department. Results: Mean scores of knowledge (z = −13.879, p < .001) and self-efficacy (z = −10.969, p < .001) significantly improved after the clinical practicum compared to baseline. Knowledge (F = .502, p = .606), psychomotor skill error (F = 1.587, p = .207), and self-efficacy (F = .481, p = .619) did not significantly differ among the three subgroups after controlling for two covariates (age, Basic Life Support certification) in the analysis of covariance models.
Corresponding author. Tel.: +82 2 820 5996; fax: +82 2 824 7961. E-mail address: [email protected] (E.J. Lim).
http://dx.doi.org/10.1016/j.colegn.2014.10.002 1322-7696/© 2014 Australian College of Nursing Ltd. Published by Elsevier Ltd.
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Y.S. Roh et al. Conclusion: Integrated simulation-based resuscitation skills training combined with a clinical practicum might be beneficial for enhancing mastery learning and self-efficacy in nursing students through learner engagement and feedback. © 2014 Australian College of Nursing Ltd. Published by Elsevier Ltd.
1. Background
2. Purpose
Cardiopulmonary resuscitation (CPR) is an essential skill required by nursing students for clinical practice, as nurses are frequently first responders in hospital code situations (Kardong-Edgren, Oermann, Odom-Maryon, & Ha, 2010). Studies document that CPR skills among nursing students are lacking (Mäkinen et al., 2010; Oermann, Kardong-Edgren, & Odom-Maryon, 2011). Regardless of how nursing students received their Basic Life Support (BLS) training, their CPR psychomotor skills begin to decline within a few weeks after instruction (Madden, 2006). Research indicates that nursing students can acquire additional CPR knowledge and skill following instructor-led training (Madden, 2006). Some studies demonstrate that practicing CPR skills only 6 min a month helps students maintain or improve their CPR skills over a 12-month period (Kardong-Edgren et al., 2010; Oermann et al., 2011). Simulation-based resuscitation training is an appealing technique for enhancing clinical experience, maximizing learning, and limiting the frequency and impact of medical errors (Weinstock et al., 2005). Some authors believe that simulation should be used alongside clinical practice (Kneebone, Scott, Darzi, & Horrocks, 2004), and that medical simulation complements educational activities based on real patient-care experiences (McGaghie, Siddall, Mazmanian, & Myers, 2009). However, a recent meta-analytic review demonstrated that simulation-based medical education with deliberate practice is superior to traditional clinical medical education for learning specific clinical skills (McGaghie, Issenberg, Cohen, Barsuk, & Wayne, 2011). In a study by Watson et al. (2012), the clinical competencies achieved by physiotherapy students were just as high in the simulated learning environments as in the traditional clinical immersion. A growing body of evidence indicates that simulation-based medical education is superior to traditional clinical education for learning advanced cardiac life-support skills (Wayne et al., 2005, 2006). However, there is little evidence to support simulation as an alternative to traditional real-life clinical practice. Effective medical learning stems from deliberate practice with clinical problems and devices in simulated settings, in addition to patient care experiences (Issenberg, McGaghie, Petrusa, Lee Gordon, & Scalese, 2005). Since 2011, our school has developed and implemented an integrated simulation-based resuscitation curriculum combined with a clinical practicum in the emergency department. In order to develop a better resuscitation curriculum, it is necessary to evaluate the integrated curriculum by measuring the learning outcomes of nursing students. In addition, how to best configure a learning simulation within clinical immersion is unknown; however, since no studies have been conducted with nursing students, there is a need for further research.
The purpose of this study was to evaluate the effectiveness of integrated simulation-based resuscitation skills training combined with a clinical practicum in an emergency department by assessing mastery learning and self-efficacy in nursing students.
3. Methods 3.1. Design A single-group pre-and post-test design was used for this study. Due to the different experiences of students in their practicum, three distinct groups emerged, resulting in a between group analysis (simulation-only group, simulation with clinical observation group, and simulation with clinical performance group) (Fig. 1).
3.2. Setting and participants For the sample size, it was estimated that 66 participants were required to maintain an effect size (d = .5) with 95% power and a significance level of .05 for ANOVA using G*Power 3 (Faul, Erdfelder, Lang, & Buchner, 2007). The effect size was derived based on a pooled effect size of .62 for multiple learning strategies found in a systematic review and meta-analysis of the comparative effectiveness of instructional design features in simulation-based education (Cook et al., 2013). A non-random convenience sample of second year nursing students enrolled in a clinical placement course in the second semester of 2011 (n = 124) and the first semester of 2012 (n = 143) were invited to participate in the study. We selected participants from naturally occurring groups (20—24 students) that rotated through the emergency department clinical placement every two weeks. After the exclusion of 12 questionnaires due to incomplete data, 255 (96%) questionnaires were used in the final analysis.
3.3. Procedure The Ethics Committee of the College of Nursing granted ethical approval for the study. All students agreed to participate in the study and signed the informed consent form, which promised confidentiality, prior to participation. Although, subject anonymity was not possible due to matching the subject’s self-reported questionnaire score with their CPR psychomotor skills performance, subject confidentiality was maintained. We conducted the study from September 2011 to May 2012. All simulation sessions took place in a Nursing
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Effects of an integrated simulation-based resuscitation skills training
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Second year nursing students rotated through the emergency department clinical placement (N = 267)
Pre-test (N = 267) -Mastery learning in CPR knowledge: Multiple-choice questionnaires -CPR psychomotor skills: Resusci Anne SkillReporter TM -Resuscitation Self-efficacy Scale Intervention (N = 267) An integrated simulation-based resuscitation skills training combined with clinical practicum -Instructor-led simulation-based resuscitation skills training (2 hr): 30-min lecture, 60-min skill training, 10min testing, 20-min debriefing -Clinical Practicum in an emergency department (80 hr)
Post-test (N = 255) -Mastery learning in CPR knowledge -CPR psychomotor skills -Resuscitation Self-efficacy Scale
Additional subgroup comparison analysis* -Simulation-only group (n = 73) -Simulation with clinical observation group (n = 157) -Simulation with clinical performance group (n = 25) *Students were divided into these subgroups based on resuscitation experiences during a clinical practicum in the emergency department.
Figure 1
Simulation Center at a College of Nursing. Of the 24 nursing students per clinical rotation, two to six students were assigned to one of seven different emergency departments for two weeks each, over a period of two semesters. Each of the seven emergency departments had 22—46 hospital beds. In this study, the integrated simulation-based resuscitation training combined with a clinical practicum consisted of a two-hour CPR practice session with a mannequin and a two-week, 80-hour clinical practicum in an emergency department. The 2-hour simulation-based resuscitation training consisted of a 30-min lecture on BLS principles and the algorithm of a cardiac arrest patient, 60-min BLS task training and 10-min testing sessions, and a 20-min debriefing. An instructor with BLS expertise led the lecture, task training, and testing sessions. A group of 24 nursing students per session was trained and tested throughout the semester. Two teams of 12 nursing students participated in the instructor-led training session. Practice sessions for CPR psychomotor skills training took place one week before the nursing students’ emergency department practicum rotation, at the Nursing Simulation Center. Before the skill session, all participants studied the BLS principles and algorithm. All participants then received a 30-min didactic lecture about the Korea National Adult BLS Guidelines, as well as a one-hour CPR skills training session. The session included hands-on practice using videomediated, practice-while-watching instruction. CPR training was conducted using a static mannequin comprising a torso and head that was placed in a hospital bed. After training, all participants tested their CPR skills on sensor-equipped mannequins (Resusci AnneTM ; Laerdal Medical, Stavanger, Norway). At the end of the session, the instructor gave
Study flowchart.
feedback based on students’ performance data collected from the SkillReporter to reflect and analyze their actions. Those who failed to meet qualifications based on the 2010 American Heart Association Guidelines for CPR were told to participate in more deliberate practice until mastery was reached. After the clinical practicum, participants completed a knowledge test, a self-administered questionnaire, and then tested their CPR skills on sensor-equipped adult mannequins. Three instructors participated in 4 h of clinical teaching in one or two emergency departments. During the 80-hour clinical placement, unit managers in the emergency department were in charge of guiding nursing students according to the guidelines of the practicum course manual.
3.4. Measures Nursing students underwent instructor-led BLS training one week before the clinical placement in an emergency department, and completed testing and self-administered questionnaires before and after the emergency department practicum. 3.4.1. Demographic data These included age, gender, BLS certification, and resuscitation experience during the emergency department’s clinical practicum. 3.4.2. Mastery learning in BLS knowledge This was measured using multiple-choice questionnaires (MCQs) based on the Korean version of the BLS Course
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Y.S. Roh et al.
Pretest Questionnaire (www.kacpr.org), a 10-item, paperand-pencil multiple-choice questionnaire, which included the BLS algorithm and overall principles. Each item was scored as either 0 (false response) or 1 (true response), with a higher score indicating a higher level of knowledge. Out of the 10 items, one pretest item and two posttest items were deleted due to low discrimination indices (D < .2). A minimum acceptable value for the D index is about +.20 or so (Downing & Yudkowsky, 2009). The removed items were as follows: ‘‘You are providing rescue breathing using a bag-mask device. What action will confirm that each of your rescue breaths is adequate?’’ (D = .144); ‘‘Which of the following is the best explanation for the need to train rescuers to perform CPR and use an AED?’’ (D = .101), and ‘‘You are doing CPR on a man who was found in a no-response condition. What is the recommended ratio of compressions to breaths?’’ (D = .058). After deleting these three items, the range for D index on the final pretest and posttest were .203—.652, .217—.710, respectively. Therefore, nine pre-test items and eight post-test items were used for the final analysis after converting the scores to a maximum of 100 points. 3.4.3. Mastery learning in CPR psychomotor skills This was assessed with a CPR performance summary report (statistical data) using a Laerdal Resusci Anne SkillReporter mannequin (Laerdal, Stavanger, Norway), which is regarded as the standard for objectively measuring discrete CPR skills (Kardong-Edgren et al., 2010). In pairs, students performed compressions, ventilations with bag-valve mask, and single-rescuer CPR for 3 min each at all of the time points. Performance was evaluated based on ventilation rate and volume, compression rate, and compression depth. In addition, CPR psychomotor skill errors were calculated using the Numerical Scoring System (Madden, 2006). Value labels were assigned to five skill components: if the skill component was performed correctly, zero error points were given. If the student performed the skill component incorrectly, she/he was given 10 or 20 skill error points depending on the severity of the aberration. Skill error points ranged from 0 to 100, with lower skill error scores indicating better CPR psychomotor skills. 3.4.4. Resuscitation self-efficacy This was measured with the Resuscitation Self-Efficacy Scale (Roh, Issenberg, Chung, & Kim, 2012) to assess nursing
Table 1
Baseline characteristics of participants.
Variable
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
students’ perceptions of their capability to organize and execute a course of action in cardiac arrest situations. The scale consisted of 17 items in four domains: recognition, debriefing and recording, responding and rescuing, and reporting. Participants were asked to respond using a 5-point Likert-type scale. Scores ranged from 1 to 5, with high scores indicating greater perceived self-efficacy. Other studies reported a .914 alpha coefficient for this scale (Roh et al., 2012). The alpha coefficient for the present study was .890 for the pretest, and .835 for the posttest.
3.5. Data analysis Data were analyzed using SPSS version 20.0 (SPSS Inc., Chicago, IL). Wilcoxon signed-rank tests were used to compare the variables at baseline and after the clinical practicum because a Kolmogorov—Smirnov (K—S) test revealed that the distribution of the sample was not normal. Based on the nursing students’ resuscitation experience during the emergency department’s clinical practicum, they were divided into three subgroups: the simulationonly group, the simulation with clinical observation group, and the simulation with clinical performance group. A Kruskal—Wallis one-way analysis of variance was used to compare the study variables among these three subgroups. Adjusted analyses were also performed that included baseline variables (age, BLS certification) that were thought to possibly influence the results, as covariates in the analysis of covariance (ANCOVA) models.
4. Results 4.1. Baseline characteristics of nursing students Almost 91% of the participants were women. The mean age of the participants was 21.81 ± 4.52 years. Approximately 19% of the participants had BLS-provider certificates. Observing (n = 157, 62%) was the most frequent role during emergency department code situations, with only 10% (n = 25) of students having performed CPR skills under the supervision of doctors. A Kruskal—Wallis H test revealed a statistically significant difference in age among the three groups, 2 (2) = 14.696, p < .001. There were no significant differences in gender and percentage of BLS certification holders among the three groups (Table 1).
Simulation with clinical performance group (n = 25)
Total
2
p
22.68 ± 4.84 22 (88.0)
21.81 ± 4.52 232 (91.0)
14.696 .328
<.001 .849
.716
.699
Mean ± SD or N (%) Age Gender (female, %) BLS certification holder
20.97 ± 4.03 67 (91.8) 12 (16.4)
22.05 ± 4.65 143 (91.1) 30 (19.1)
6 (24.0)
48 (18.8)
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Effects of an integrated simulation-based resuscitation skills training Table 2
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Mean differences of knowledge, psychomotor skills, and self-efficacy (N = 255).
Variable
Baseline
After clinical practicum
z
p
Mean ± SD CPR knowledge Self-efficacy Recognition Debriefing and recording Responding and rescuing Reporting CPR psychomotor skills Ventilation volume (ml) Ventilation rate (per min) Compression depth (mm) Compression rate (per min) Incorrect hand placement (%) Inadequate chest recoil (%) Total skill error point
49.15 3.15 3.46 2.90 2.79 3.53
± ± ± ± ± ±
17.00 0.48 0.51 0.58 0.71 0.54
55.29 3.55 3.89 3.25 3.29 3.84
± ± ± ± ± ±
19.12 0.42 0.48 0.49 0.61 0.48
−13.879 −10.969 −9.915 −7.935 −9.783 −7.612
<.001 <.001 <.001 <.001 <.001 <.001
525.06 3.99 46.01 114.91 16.69 0.53 35.35
± ± ± ± ± ± ±
137.69 1.51 5.55 13.79 27.66 2.74 16.09
549.65 4.40 48.78 113.80 7.41 0.74 25.63
± ± ± ± ± ± ±
78.93 1.50 4.66 11.89 13.82 4.76 17.06
−2.161 −3.056 −6.879 −1.556 −4.192 −.555 −7.045
.031 .002 <.001 .120 <.001 .579 <.001
4.2. Comparison of knowledge, self-efficacy, and psychomotor skills After completing the simulation-based resuscitation course in conjunction with the emergency department practicum, the nursing students’ CPR knowledge scores (z = −13.879, p < .001) and self-efficacy (z = −10.969, p < .001) were significantly increased, compared to baseline (Table 2). Furthermore, the average scores in all the self-efficacy subscales increased. The largest average difference was with recognition efficacy (z = −9.915, p < .001); the smallest average difference was with reporting efficacy (z = −7.612, p < .001). Of the CPR psychomotor skills measured by the Resusci Anne SkillReporterTM mannequins, the accuracy of ventilation volume (z = −2.161, p = .031), ventilation
Table 3
rate (z = −3.056, p = .002), compression depth (z = −6.879, p < .001), and hand placement (z = −4.192, p < .001) increased significantly, but compression rate (z = −1.556, p = .120) and chest recoil (z = −.555, p = .579) did not. As shown in Table 3, there were no statistically significant mean differences from Time 1 to Time 2 in knowledge (2 = .586, p = .746), psychomotor skill error (2 = 3.827, p = .148), and self-efficacy (2 = 2.718, p = .257) among the three subgroups as determined by the Kruskal—Wallis one-way analysis of variance. There were no statistically significant mean differences in knowledge (F = .502, p = .606), psychomotor skill error (F = 1.587, p = .207), and self-efficacy (F = .481, p = .619) among the three subgroups after controlling for the two covariates (age, BLS certification) in the analysis of covariance models (Table 4).
Comparison of knowledge, quality of CPR psychomotor skills, and resuscitation self-efficacy (N = 255).
Variable
Categorya
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
Simulation with clinical performance group (n = 25)
2
p
Mean ± SD Knowledge
Psychomotor skill error point
Self-efficacy
a
Time 1 Time 2 Difference Time 1
50.84 57.19 6.35 30.14
± ± ± ±
17.46 19.65 2.18 15.94
48.62 54.70 6.08 37.39
± ± ± ±
16.90 19.01 2.11 16.10
47.56 53.50 5.94 37.92
± ± ± ±
16.52 18.58 2.06 13.18
.586 .586 .586 10.893
.746 .746 .746 .004
Time 2 Difference Time 1 Time 2 Difference
23.47 −6.39 3.25 3.60 0.35
± ± ± ± ±
15.31 18.41 0.51 0.44 0.49
26.69 −10.70 3.08 3.50 0.42
± ± ± ± ±
17.95 20.79 0.45 0.39 0.47
25.20 −13.33 3.23 3.72 0.49
± ± ± ± ±
16.10 18.80 0.55 0.43 0.37
1.344 3.827 6.756 9.571 2.718
.511 .148 .034 .008 .257
Time 1: baseline, Time 2: after clinical practicum.
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Y.S. Roh et al. Table 4
Analysis of covariance for subgroup comparison (N = 255).
Variable
Categorya
Simulation-only group (n = 73)
Simulation with clinical observation group (n = 157)
Simulation with clinical performance group (n = 25)
F
p
Mean ± SD Knowledge
Psychomotor skill error point
Self-efficacy
a
Time 1 Time 2 Difference Time 1
50.62 56.94 6.33 30.28
± ± ± ±
17.48 19.67 2.19 16.01
48.62 54.70 6.08 37.39
± ± ± ±
16.90 19.01 2.11 16.10
47.56 53.50 5.94 37.92
± ± ± ±
16.52 18.58 2.06 13.18
.502 .502 .502 5.175
.606 .606 .606 .006
Time 2 Difference Time 1 Time 2 Difference
23.80 −6.20 3.24 3.60 0.36
± ± ± ± ±
15.15 18.47 0.51 0.45 0.49
26.69 −10.70 3.08 3.50 0.42
± ± ± ± ±
17.95 20.79 0.45 0.39 0.47
25.20 −13.33 3.23 3.72 0.49
± ± ± ± ±
16.10 18.80 0.55 0.43 0.37
.714 1.587 3.193 4.077 .481
.491 .207 .043 .018 .619
Time 1: baseline, Time 2: after clinical practicum.
5. Discussion Our findings increase our understanding of the synergetic effects of simulation-based resuscitation skills training combined with a clinical practicum, by comparing nursing students’ knowledge, self-efficacy, and CPR psychomotor skills, pre and post-interventions. The results of this study demonstrate that after completing the simulation-based resuscitation course in conjunction with the emergency department practicum, there was an increase in CPR skills scores. Previous research demonstrated that a simulation group had a significantly higher mean knowledge score post-test than the control group (Liaw, Scherpbier, Rethans, & Klainin-Yobas, 2011). Our results indicate the importance of simulation training for retaining information, which was a key factor for influencing the combination of simulation learning and clinical practice (Liaw, Chan, Scherpbier, Rethans, & Pua, 2012). In this study, resuscitation self-efficacy significantly increased after the clinical practicum, compared to baseline. Previous research demonstrates that simulation-based resuscitation training for healthcare professionals improved their self-efficacy (Turner, Dierselhuis, Draaisma, & ten Cate, 2007), and nursing students perceived that simulation increased their ability and confidence in their clinical placements (Baillie & Curzio, 2009). One of the possible explanations for this result is that gaining skill proficiency can increase self-efficacy (Bandura, 1997), and successful experiences in resuscitation courses increased perceived self-efficacy (Hunt, Fiedor-Hamilton, & Eppich, 2008). The most effective way to develop a strong sense of efficacy is through mastery experiences (Bandura, 1997); therefore, we suggest that efforts should be made to boost students’ self-efficacy through mastery experiences in their curriculum. Our study demonstrated that the accuracy of CPR psychomotor skills—–ventilation volume, ventilation rate, compression depth, and hand placement—–significantly increased post-intervention, but not compression rate and
chest recoil. Previous studies verified that simulation-based resuscitation training had positive effects on the mastery learning of advanced cardiac life-support skills in residents (Wayne et al., 2005, 2006). Although objective monitoring of repetitive practice is not part of this study, we provided feedback on the quality of CPR psychomotor skills and told nursing students to continue practice to improve their skills at posttest. The combination of feedback, selfdirected practice, and indirect or direct involvement in real hospital code situations may improve the quality of CPR psychomotor skills. In this study, only 10% of students performed CPR skills under the supervision of healthcare professionals during real emergency department code situations. The one-way ANOVA revealed that there were no significant mean differences in study variables among the three groups. One nursing study reported that students with simulation training achieved and maintained higher clinical performance scores more quickly than those without simulation. These findings suggest that patient simulation is a valuable addition to the apprenticeship model (Meyer, Connors, Hou, & Gajewski, 2011). It can be assumed that when students are personally involved in handling an emergency event, this could lead to experiential learning and a positive impact on students’ motivation (Pelaccia et al., 2009). However, it can be argued that traditionally, clinical education is insufficient if the goal is skill acquisition and downstream patient safety (McGaghie et al., 2011) due to limited simulation realism (McKenna et al., 2011). Therefore, the educational effectiveness of simulation combined with clinical practice should be considered for a better resuscitation curriculum. We suggest that integrated simulation-based resuscitation skills training with a clinical practicum might be beneficial for enhancing mastery and self-efficacy in nursing students. One limitation of this study might be the use of a one-group comparison design instead of a randomized controlled trial study. A small sample size for the simulation with clinical performance group increases the possibility for a Type II error.
Please cite this article in press as: Roh, Y. S., et al. Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students. Collegian (2014), http://dx.doi.org/10.1016/j.colegn.2014.10.002
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Effects of an integrated simulation-based resuscitation skills training
6. Conclusion Simulation-based resuscitation skills training linked with a clinical practicum improved nursing students’ knowledge, self-efficacy, and CPR psychomotor skills through learner engagement and feedback. Educators in schools and hospitals should carefully consider the educational effectiveness of simulation combined with a clinical practicum, take advantage of both learning modalities, and collaborate to facilitate better learning outcomes in resuscitation education. Further studies with a randomized controlled design are needed to verify the effects of simulation combined with clinical practice on graduate nurses’ clinical performance in real code situations and on patient outcomes.
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Please cite this article in press as: Roh, Y. S., et al. Effects of an integrated simulation-based resuscitation skills training with clinical practicum on mastery learning and self-efficacy in nursing students. Collegian (2014), http://dx.doi.org/10.1016/j.colegn.2014.10.002