Background
Mastering the medication administration procedure (MAP) is a complex competence that challenges nursing students [1] and represents 40% of the nurse’s activity [2]. Jarvill (2018) declared that only one-third of the students in their study accurately demonstrated proficiency in the MAP [3]. Nurse administrators globally report that newly qualified nurses are inadequately prepared to assume responsibilities for medication administration [4]. Indeed, nurses highlight insufficient training in MAP and drug dosage calculation (DDC) as a significant factor contributing to medication errors [2], which, in turn, exert substantial and widespread impacts on healthcare systems [5].
Undergraduate nursing curricula include essential medication administration skills, integrated into multiple modules such as basic nursing and pharmacology. This is due to the complex nature of MAP, which entails several steps including verifying the “rights,” preparing medications, and calculating dosages [6]. Global research underscores the efficacy of simulation [7‐9] in enhancing nursing students’ MAP competence [1, 3].
Anzeige
Over time, the evolution of simulation has shown that high-fidelity simulation can authentically replicate reality and provide students with similar experience as in clinical settings [4]. Simultaneously, Virtual simulation (VS) generated similar learning outcomes when compared to manikin-based simulation [8]. In fact, high-fidelity simulation is a costly solution due to its intensive nature in terms of human and material resources, whereas VS is less costly [10] and can offer students opportunities for repeated practice in a safe, reproducible, and accessible environment [11], for both them and the patient [12]. Through VS, nursing students can encounter diverse care scenarios not readily available in a clinical setting [10]. Teaching institutions can increase the number of clinical situations accessible for student instruction by utilizing VS, which addresses the challenges associated with managing laboratory space.
Knowledge as well as satisfaction, self-confidence in learning and anxiety are considered indicators of the effectiveness of pedagogical approaches, which are recurrently explored when implementing a new teaching strategy [13]. In this respect, self-confidence is mentioned by nursing students as a possible cause of medication errors [14].
Rare are the studies that have verified the superiority of VS tools on face-to-face simulation or on traditional learning methods in acquiring new knowledge and skills. The aim of this study is to evaluate the effectiveness of a screen-based simulation (SBS) tool in enhancing knowledge and skills related to medication administration and dosage calculation in nursing students. The impact on satisfaction, self-confidence in learning, and anxiety will also be explored.
Methods
Design
This is a multicenter, randomized controlled trial with a 1:1 allocation ratio, employing a pre-post-test design. The trial is stratified, and evaluators are single-blind, ensuring they remain unaware of students’ group affiliations. The trial was registered at the Pan African Clinical Trial Registry (registration number PACTR202305505743210) prior to participant enrollment.
Anzeige
Participants and settings
This study included second-year nursing students from three Moroccan schools. To be included, participants needed to provide online informed consent and have the following specializations: general nursing, anesthesia and resuscitation nursing, emergency and critical care nursing, and neonatology nursing. The only exclusion criterion was refusing to sign the online consent form. The study, conducted between January and October 2023, adhered to CONSORT guidelines for health care simulation research [15].
Intervention
The intervention group underwent training in MAP and DDC using the SBS platform SIMDOSE® (SimforHeath, France). This training consists of five phases, each followed by formative feedback: (a) prescription verification, (b) dosage calculation, (c) material selection for preparation, (d) labeling, and (e) medication administration. Final feedback includes exercise time, points gained or lost on each step, and total score.
Data collection procedure
Upon inclusion, participants completed a socio-academic survey and a pretest to gauge baseline knowledge. Participants were then clustered based on their pretest scores, and random allocation to either the SBS group (intervention group - IG) or the traditional training group (control group - CG) was performed within these clusters. A timetable for traditional and SBS sessions, collaboratively established with pedagogical coordinators, considered factors like student availability, computer room access, and computer quantity at each research location. The learning objectives of these sessions are to calculate drug dosages and prepare different perfused drugs safely and securely.
Intervention group
The SBS session, lasting one and a half to two hours, involved three phases: prebriefing, simulation, and self-debriefing. In the prebriefing, the principal investigator (PI) expressed gratitude to participating students, introduced the platform via a tutorial video, and indicated the order of the four perfusion clinical cases (Antibiotherapy; Hydro-caloric intake; Insulin therapy; Anti-arrhythmic). During this phase, the PI implemented necessary measures to enhance students’ psychological safety [16], a crucial element in healthcare simulation. The second phase focused on engaging in the self-directed, interactive SBS. The PI, acting as simulation instructor, was present throughout the sessions to ensure smooth progression, maintain the order of the exercises and resolve technical problems. In the third stage, each student carried out a self-debriefing, answering five open-ended questions in writing [17].
Control group
The CG students individually tackled the same four clinical cases traditionally, employing the paper-and-pencil method. Like the virtual sessions, the PI explained the session method and aided students facing difficulties. Following each exercise, students received a correction sheet to review their results and identify any knowledge gaps.
Promoting safe and standardized communication was an additional educational goal, addressed through the French version of the SBAR method (“Situation, Background, Assessment, Recommendation”) [18]. Both groups observed and debriefed a brief role-play depicting interprofessional communication. Subsequently, they received an information sheet (Fig. 1) about the SBAR method.
Fig. 1
The SBAR method information sheet
×
![]()
After the intervention and control sessions, students completed the knowledge post-test, the State Anxiety Scale [19], and the Student Satisfaction and Self-Confidence in Learning Scale [20]. To gather data on medication preparation and DDC skills, a random sample of students from both groups underwent objective structured clinical examination (OSCE) sessions. The randomization for the OSCE was not stratified. It was conducted using the Random function in Microsoft Excel. During these sessions, comprising three 10-minute stations, evaluators scored each student using nominative grids.
Outcomes measures
Primary outcomes
Demographic characteristics
To ensure participant pseudonymization, a code in the format X0102Y was provided by each student, where X represents the initial of the student’s name, 0102 denotes the birthdate (day and month), and Y is a student-selected letter. Importantly, the research team didn’t have any access to students’ birth dates, further enhancing privacy protection. This code linked the student’s data across all study steps. Although this method minimizes the likelihood of identification, it does not guarantee complete anonymity, as it is theoretically possible to link data to individual participants. Eight socio-demographic characteristics were recorded, including gender, age, previous education, nursing specialty, video gaming activity, mathematical skills level, prior knowledge, and experience in MAP and DDC.
Knowledge acquisition
A pre-post-test assessed students’ knowledge of MAP and DDC before and after the intervention. The 13-item MAP questionnaire, designed for similar research [21], evaluates conceptual elements, practical applications, and decision-making abilities. Cronbach alpha analysis indicated strong internal consistency (α = 0.78) [21]. The DDC section, comprising five questions, gauges knowledge in areas like unit conversion, dilution, and perfusion rate determination. The study compares knowledge acquisition in MAP and DDC between groups based on the difference in pretest and post-test mean scores.
Skills evaluation through OSCE
MAP and DDC skills acquisition were assessed using an evaluation grid for each of the three OSCE stations: medical prescription verification, medication material preparation and DDC, and medication administration. Three prescriptions (P1: Antibiotherapy; P2: Hydro-caloric intake; P3: Insulin therapy) were subject to these 3 stations. Evaluation grids generated numerous scores corresponding to items in Fig. 2, allowing for a comparison between IG and CG. These grids, developed by the PI, were based on two validated tools: the MEDICORRECT 10-item tool, possessing suitable psychometric properties for assessing practical skills in the MAP [22], and the Medication Administration Observation Tool (MAOT), employed for collecting data on observed medication administration actions [23].
Fig. 2
The OSCE items description
×
![]()
Secondary outcomes
Satisfaction and self-confidence
Student satisfaction and self-confidence in learning were measured using the National League for Nursing’s Student Satisfaction and Self-Confidence in Learning Scale [20]. This 13-item instrument (five for satisfaction, eight for self-confidence) employs a five-point Likert-type scale (1 = strongly disagree to 5 = strongly agree). Reliability tested using Cronbach’s alpha coefficient, gave: satisfaction = 0.94; self-confidence = 0.87 [24]. Content validity for the French version was confirmed by Simoneau et al. (2012), with an internal consistency coefficient of 0.87.
Anxiety
The State-Trait Anxiety Inventory (STAI Form Y), developed by Spielberger et al. [19], is widely utilized in clinical and research settings, including the assessment of anxiety problems in high-school students and the evaluation of counseling, psychotherapy, substance abuse treatment, and behavior modification programs. Focusing on state anxiety (S-anxiety), the STAI Form Y-1 comprises 20 items measuring the respondent’s current feelings on a 4-point scale (1 = not at all, 2 = a little, 3 = moderately, 4 = a lot). Scores range from 20 to 80, with higher scores indicating elevated anxiety levels. The French translation used in this study has been validated with nursing students by Simoneau et al. (2012).
Sample size
The sample size for this study was determined based on a significance level of 0.05, a computed effect size of 0.189, and a desired power of 0.8. Using these parameters, the calculated optimal sample size for each group was 219, resulting in a total sample size of 438 participants (i.e., two groups). This sample size was chosen to ensure adequate power to detect the expected effect size while maintaining a significance level of 0.05. The OSCE phase was subjected to simple random sampling, with the same number of students randomly selected from each of the intervention and control groups. Given the lack of funding and for ecological reasons, two 3-hour OSCE sessions involving 3 volunteer teachers (1 teacher per station) would enable 30 students per research site to be assessed.
Randomization
To rigorously assess VS effectiveness, a 1:1 allocation randomization was stratified, ensuring equal distribution of potential pre-existing knowledge variations between study groups. The PI employed pretest scores for allocation generation, sorting results from highest to lowest. Student codes were then manually included alternately into two groups (IG and CG), at each site and specialty. This approach guaranteed consistency and standardization across all sites.
Blinding
OSCE assessors were blinded to participant allocation (intervention or control group). Blinding the PI or participants wasn’t feasible due to the nature of the training intervention.
Statistical methods
Data were electronically entered using Google Forms, cleaned with Microsoft Excel Office, and analyzed using Jamovi software (version 2.3.18) [25]. Categorical variables were presented as frequencies and percentages, with the Chi-squared test comparing proportions between groups. Quantitative variables were expressed as mean and standard deviation or median and interquartile range. Data were compared using the Wilcoxon test for paired data and the Mann–Whitney U test for independent data. Effect size was calculated for the knowledge gained. A p-value less than 0.05 was considered statistically significant.
Ethics
Approved by the Ethics Committee of Mohammed VI University of Health and Sciences (Casablanca, Morocco) with reference number CE/UM6SS/07/23. A signed online informed consent form was also obtained from each participant after the purpose and methods of the research, the confidentiality of personal information and their right to voluntarily participate in or withdraw from the study had been explained to them.
Anzeige
Results
Demographic characteristics
Out of the initial pool of 480 participants screened for eligibility, 351 were randomized, with 172 assigned to the IG and 179 to the CG. However, for the final analysis, only 177 participants (110 from the IG and 67 from the CG) completed both pre- and post-tests, and these are the participants reported in most of the results (Tables 1, 2 and 3). Particularly, 39 participants from the IG and 27 from the CG accepted to participate in the OSCE sessions (Table 2). Anxiety, satisfaction, and self-confidence survey results are independent of pre- and post-test completion, resulting in different participant numbers: IG n = 140 and CG n = 104 for satisfaction and self-confidence, and IG n = 125 and CG n = 101 for anxiety (Tables 2 and 4). Figure 3 is a CONSORT diagram for this investigation.
Fig. 3
The CONSORT diagram of this study
×
![]()
There was no statistically significant difference between the IG and CG regarding their demographic characteristics’ distribution (p > 0.05) (Table 1). Most were women (IG = 80.9%; CG = 77.6%) with a Median [IQR] age of 20 years old [19‐21]. A majority declared to have good (IG = 47.3%; CG = 44.8%) to average (IG = 42.7%; CG = 31.3%) math skills. One-third of each group had never played a video game before. In all groups, over 50% had MAP previous knowledge. Respectively, 39.1% and 29.9% of IG and CG had never practiced MAP.
Table 1
Participants’ socio-educational characteristics
Variable | Intervention group (n = 110) | Control group (n = 67) | p-value | |
|---|---|---|---|---|
Age in years (Median [IQR]) | 20 [19–21] | 20 [19–21] | 0.788† | |
Gender (%[n]) | Female | 80.9% (89) | 77.6% (52) | 0.597* |
Male | 19.1% (21) | 22.4% (15) | ||
Study location (%[n]) | Casablanca | 57.3% (63) | 67.2% (45) | 0.201* |
Meknes | 12.7% (14) | 14.9% (10) | ||
Oujda | 30.0% (33) | 17.9% (12) | ||
Previous education (%[n]) | Yes | 80% (88) | 77.6% (52) | 0.705* |
No | 20% (22) | 22.4% (15) | ||
Nursing specialty (%[n]) | General nursing | 36.4% (41) | 43.3% (29) | 0.475* |
Anesthetist Nursing | 37.3% (40) | 38.8% (26) | ||
Intensive care nursing | 13.6% (15) | 11.9% (8) | ||
Neonatology nursing | 12.7% (14) | 6.0% (4) | ||
Video gaming frequency (%[n]) | Never | 39.1% (43) | 28.4% (19) | 0.119* |
Daily | 24.5% (27) | 19.4% (13) | ||
Weekly | 24.5% (27) | 25.4% (17) | ||
Monthly | 7.3% (8) | 17.9% (12) | ||
Undefined | 4.5% (5) | 9.0% (6) | ||
Math skills level (%[n]) | Excellent | 8.2% (9) | 10.4% (7) | 0.101* |
Good | 47.3% (52) | 44.8% (30) | ||
Average | 42.7% (47) | 31.3% (21) | ||
Weak | 0.9% (1) | 10.4% (7) | ||
Bad | 0.9% (1) | 3.0% (2) | ||
MAP previous knowledge (%[n]) | Never | 20.9% (23) | 22.4.0% (15) | 0.816* |
In class | 54.5% (60) | 55.2% (37) | 0.930* | |
Social media | 10.0% (11) | 6.0% (4) | 0.350* | |
Documentary research | 4.5% (5) | 10.4% (7) | 0.130* | |
Practical training | 46.4% (51) | 40.3% (27) | 0.431* | |
MAP practice frequency (%[n]) | Never | 39.1% (43) | 29.9% (20) | 0.189* |
Daily | 20.9% (23) | 11.9% (8) | ||
Weekly | 15.5% (17) | 19.4% (13) | ||
Monthly | 14.5% (16) | 22.4% (15) | ||
Undefined | 10.0% (11) | 16.4% (11) |
Anzeige
Knowledge acquisition
Independent comparisons revealed no significant differences between the two groups’ pre- and post-test results (Table 2). Concerning paired comparisons, all the differences obtained between knowledge scores weren’t significant, except for DDC score which significantly improved after the SBS intervention (post – pre = 1.00 (20%); p = 0.004) (Table 3). The latter comparison showed a positive effect size (z = 0.499), which means that the SBS intervention is associated with an increase in DDC scores. Quantitatively, MAP scores showed a decrease from pre- to post-test for both groups (Table 3).
Table 2
Pretest, posttest, OSCE, satisfaction, self-confidence in learning, and anxiety mean/median scores between-groups comparisons
Variable | Intervention group (IG) | Control group (CG) | p-value | |
|---|---|---|---|---|
Pretest scores (Median [IQR]) IG (n = 110); CG (n = 67) | MAP | 9.0 [7.50–10.40] | 9.0 [8.00-10.50] | 0.286 † |
DDC | 2.0 [1.00–3.00] | 2.0 [1.00–3.00] | 0.675 † | |
Pretest total score | 11.0 [9.00–13.00] | 11.0 [9.50–13.00] | 0.678 † | |
Post-test scores (Median [IQR]) IG (n = 110); CG (n = 67) | MAP | 8.5 [6.63-10.00] | 9.5 [7.25–10.50] | 0.113 † |
DDC | 2.0 [2.00–3.00] | 3.0 [2.00-3.50] | 0.351 † | |
Post-test total score | 11.0 [9.00–13.00] | 12.0 [9.25-14.00] | 0.128 † | |
OSCE scores (Mean ± SD) IG (n = 39); CG (n = 27) | OSCE total score (0–30) | 11.66 ± 3.69 | 9.97 ± 3.72 | 0.077 * |
Station 1 total score (0–10) | 5.89 ± 1.75 | 5.82 ± 1.51 | 0.680 † | |
Station 2 total score (0–10) | 1.86 ± 1.43 | 1.22 ± 1.18 | 0.070 † | |
Station 3 total score (0–10) | 3.90 ± 0.250 | 2.94 ± 2.23 | 0.133 † | |
Station 2 prescription 2 score (0–10) | 1.05 ± 1.49 | 0.43 ± 0.98 | 0.043 ‡ | |
Station 2 prescription 3 score (0–10) | 1.54 ± 1.92 | 0.57 ± 1.20 | 0.013 ‡ | |
Station 2 DDC skill score (0–10) | 1.92 ± 1.89 | 0.92 ± 1.75 | 0.013 † | |
Satisfaction and self-confidence in learning score (Mean ± SD) IG (n = 140); CG (n = 104) | Satisfaction score | 21.3 ± 4.50 | 19.9 ± 4.70 | 0.002 † |
Self-confidence in learning score | 33.0 ± 6.51 | 31.6 ± 6.21 | 0.020 † | |
Satisfaction and self-confidence in learning score | 54.3 ± 10.69 | 51.5 ± 10.50 | 0.004 † | |
Anxiety Score (Mean ± SD) IG (n = 125); CG (n = 101) | 49.7 ± 6.00 | 48.6 ± 5.29 | 0.161 * |
Table 3
Pre- and post-test score comparisons within intervention and control groups (Mean ± SD)
Intervention group (n = 67) | Control group (n = 110) | |||||||
|---|---|---|---|---|---|---|---|---|
Pre-intervention | Post-intervention | P-value* | Effect Size (z) | Pre-intervention | Post-intervention | P-value* | Effect Size (z) | |
MAP score | 9.20 ± 1.91 | 8.84 ± 2.48 | 0.314 | -0.149 | 8.79 ± 2.30 | 8.35 ± 2.45 | 0.096 | -0.192 |
DDC score | 2.13 ± 1.30 | 2.64 ± 1.40 | 0.004 | 0.499 | 2.26 ± 1.31 | 2.45 ± 1.15 | 0.192 | 0.164 |
Overall score | 11.34 ± 2.65 | 11.48 ± 3.36 | 0.404 | 0.121 | 11.05 ± 2.99 | 10.79 ± 3.04 | 0.578 | -0.066 |
Skills evaluation through OSCE
In a list of 25 OSCE items between-groups comparisons, three significant differences were found in the second station scores (Table 2). Students who participated in the SBS performed better than control group participants in preparing medication and calculating drug dosages for two medical prescriptions (P2, (p = 0.043); P3, (p = 0.013)). The total score of DDC item on all prescriptions was significantly higher within the IG (p = 0.013).
Anzeige
Satisfaction and self-confidence
Participants in the IG reported higher levels of satisfaction and excellent self-confidence compared to the CG, with 90.7% of IG participants versus 87.8% of CG participants agreeing or strongly agreeing with the scale affirmations (p < 0.001) (Table 4). The IG participants’ greatest satisfaction (agree and strongly agree) was towards the fact that the simulation provided them with a variety of learning materials and activities to promote MAP and DDC learnings (IG 87.1% vs. CG 78.9% ; p = 0.014)). Regarding self-confidence section, majority (85.7%) of the IG students agree and strongly agree that they had the responsibility as students to learn what they need to know from this SBS activity.
Anxiety
All research participants had a moderate anxiety degree (IG: 49.7 ± 6.00; CG: 48.6 ± 5.29) with no significant difference among the two groups (p = 0.161) (Table 2).
Table 4
Student satisfaction and self-confidence in learning scale : frequency distributions and between-group comparisons
Group type IG (n = 140); CG (n = 104) | Sd n(%) | D n(%) | U n(%) | A n(%) | Sa n(%) | P-value* | |
|---|---|---|---|---|---|---|---|
“Satisfaction” construct - OVERALL | IG CG | 3(2.1) 1(1.0) | 3(2.1) 5(4.8) | 8(5.7) 10(9.6) | 26(18.6) 38(36.5) | 100(71.4) 50(48.1) | 0.003 |
1. The teaching methods used in this simulation were helpful and effective. | IG CG | 7(5.0) 8(7.7) | 3(2.1) 5(4.8) | 13(9.3) 16(15.4) | 45(32.1) 40(38.5) | 72(51.4) 35(33.7) | 0.065 |
2. The simulation provided me with a variety of learning materials and activities to promote my MAP and DDC learnings. | IG CG | 4(2.9) 4(3.8) | 3(2.1) 7(6.7) | 11(7.9) 11(10.6) | 42(30.0) 45(43.3) | 80(57.1) 37(35.6) | 0.014 |
3. I enjoyed how my professor taught through the simulation. | IG CG | 6(4.3) 6(5.8) | 4(2.9) 6(5.8) | 11(7.9) 10(9.6) | 26(18.6) 36(34.6) | 93(66.4) 46(44.2) | 0.012 |
4. The teaching materials used in this simulation were motivating and helped me to learn. | IG CG | 5(3.6) 5(4.8) | 4(2.9) 6(5.8) | 12(8.6) 10(9.6) | 39(27.9) 43(41.3) | 80(57.1) 40(41.3) | 0.061 |
5. The simulation was suitable to the way I learn. | IG CG | 9(6.4) 3(2.9) | 4(2.9) 5(4.8) | 25(17.9) 22(21.2) | 40(28.6) 37(35.6) | 62(44.3) 37(35.6) | 0.340 |
“Self-confidence in Learning” construct - OVERALL | IG CG | 2(1.4) 0(0.0) | 4(2.9) 4(3.8) | 10(7.1) 10(9.6) | 36(25.7) 43(41.3) | 88(62.9) 47(45.2) | 0.041 |
6. I am confident that I am mastering the content of the simulation. | IG CG | 7(5.0) 5(4.8) | 8(5.7) 5(4.8) | 20(14.3) 22(21.2) | 51(36.4) 48(46.2) | 54(38.6) 24(21.1) | 0.107 |
7. I am confident that this simulation covered critical content necessary for the mastery of MAP and DDC. | IG CG | 4(2.9) 1(1.0) | 7(5.0) 10(9.6) | 13(9.3) 12(11.5) | 45(32.1) 41(39.4) | 71(50.7) 40(38.5) | 0.197 |
8. I am confident that I am developing the skills and obtaining the required knowledge from the simulation to perform necessary tasks in a clinical setting. | IG CG | 5(3.6) 2(1.9) | 3(2.1) 7(6.7) | 16(11.4) 19(18.3) | 47(33.6) 43(41.3) | 69(49.3) 33(31.7) | 0.027 |
9. My instructor used helpful resources to teach the simulation. | IG CG | 4(2.9) 3(2.9) | 5(3.6) 8(7.7) | 24(17.1) 19(18.3) | 51(36.4) 42(40.4) | 56(40.0) 32(30.8) | 0.463 |
10. It is my responsibility as the student to learn what I need to know from this simulation activity. | IG CG | 2(1.4) 3(2.9) | 4(2.9) 3(2.9) | 14(10.0) 10(9.6) | 40(28.6) 40(38.5) | 80(57.1) 48(46.2) | 0.437 |
11. I know how to get help when I do not understand the concepts covered in the simulation. | IG CG | 8(5.7) 2(1.9) | 9(6.4) 10(9.6) | 22(15.7) 14(13.5) | 39(27.9) 42(40.4) | 62(44.3) 36(34.6) | 0.121 |
12. I know how to use simulation activities to learn critical aspects of these skills. | IG CG | 3(2.1) 4(3.8) | 7(5.0) 7(6.7) | 18(12.9) 15(14.4) | 46(32.9) 41(39.4) | 66(47.1) 37(35.6) | 0.458 |
13. It is the instructor’s responsibility to tell me what I need to learn of the simulation activity content during class time. | IG CG | 9(6.4) 9(8.7) | 7(5.0) 6(5.8) | 25(17.9) 15(14.4) | 40(28.6) 39(37.5) | 59(42.1) 35(33.7) | 0.481 |
Student satisfaction and self-confidence in learning - OVERALL | IG CG | 2(1.4) 0(0.0) | 4(2.9) 4(3.8) | 7(5.0) 9(8.7) | 24(17.1) 40(38.5) | 103(73.6) 51(49.0) | < 0.001 |
Discussion
The data obtained supports the use of the SIMDOSE® tool as a supplementary teaching method of DDC for nursing students. The IG showed a significant improvement in both knowledge and skill acquisition of DDC. In addition, the same group showed significant high levels of satisfaction and self-confidence with the training received.
The demographic survey showed that immersive and virtual methods of learning are welcomed by the nursing student community, with half using video games in their daily/weekly lives. On a sample of 426 undergraduate nursing students, Padilha et al. [26] highlighted a perceived ease, usefulness, and intention to employ clinical VS as a supplementary pedagogical method.
Knowledge acquisition
SBS enabled a 20% improvement in students’ knowledge of DDC in the context of this study. These findings corroborate those of prior research, in which the authors discovered that knowledge increased after a VS learning experience. These studies carried out with different VS platforms focused on nursing education of MAP [21], detection and response to rapidly deteriorating patient [27, 28], leadership styles [8], blood transfusion [29], pediatric nursing care, and nursing fundamentals [30].
The quantitatively negative and non-significant findings of MAP knowledge acquisition are likely due to the MAP questionnaire items not corresponding to the intervention content. Also, the important drop out of CG participants (\({\raise0.5ex\hbox{$\scriptstyle 2$}\kern-0.1em/\kern-0.15em\lower0.25ex\hbox{$\scriptstyle 3$}}\)) from the post-test could be behind these results. In fact, the SBS platform is primarily designed for training in medication preparation and drug dosage calculation [31]. As well, traditional teaching methods and the SBS may not have been engaging or interactive enough, leading to confusion and lower scores in MAP knowledge. Additionally, external factors such as stress or insufficient practice time could have influenced the results. This underlines the need for further research to optimize teaching strategies.
Skill development
Significant high scores were obtained by the intervention group regarding their practical competences related to medication preparation and DDC. Our results support the claims that VS can serve as a tool to improve nursing students’ skills, such as intravenous catheter insertion [32], rapid patient deterioration management [28], and nursing fundamentals [30].
During a review of related literature, two RCTs conducted in 2003 and 2008 revealed respectively that traditional methods of teaching are more effective than computer-based education [33] and that “students from the traditional group were more competent administering live IV cannulation” [34]. This might demonstrate how nursing students’ learning preferences and styles have changed across the generations, which was highlighted by Cant and Cooper in their integrative review in 2014 [9].
Other researchers have assessed the influence of repeating SBSs on knowledge improvement [13, 35]. Zaragoza-Garcia et al. (2021) discovered that students must practice virtual scenarios at least twice to achieve appropriate scores. In our scenario, the IG repeated the MAP four times for distinct clinical cases, during a single simulation session. This might explain not just the favorable outcomes on DDC skills and knowledge, but also the high degree of satisfaction and self-confidence observed when utilizing the SIMDOSE® platform.
Interprofessional communication is one of the mean scores for which there is no significant difference between IG and CG. This might be because both groups were educated in the same manner, through role-playing. What’s more, neither the SBS nor the written clinical cases allow practicing the SBAR method.
Satisfaction and self-confidence
SBS also increases nursing students’ satisfaction with their learning experience. These findings highlight the relevance of SBS to the expectations and learning styles of the forthcoming generation. VS tools integrate gaming and problem-based learning strategies using dynamic, interactive 3-dimensional technology, which boosts students’ sense of achievement. This significant satisfaction might be explained by the fact that students can pursue this kind of learning at their own pace and get customized feedback after each VS phase. These findings complement the body of research [32] opposing the conclusions of a meta-analysis [30], which indicated no difference between satisfaction in learning emerging from virtual reality simulation interventions and that arising from control conditions.
Greater self-confidence in learning arising from this SBS of drug preparation and dosage calculation is already documented by other studies, such as a randomized controlled trial [36] comparing a VS of blood transfusion care with traditional learning methods. The authors hypothesized that students are more confident in their learning because the SBS allows them to visualize themselves practicing in a real clinical setting and being able to perform preparing medications and calculating its dosages. In addition to some research works [32, 33, 37], the previously mentioned meta-analysis [30] continue neutralizing VS impact also on self-confidence in learning. Further qualitative research should be conducted to investigate the reasons behind our sample’s satisfaction and self-confidence in learning utilizing VS.
Anxiety
Although the S-anxiety scores of the IG were quantitatively higher than those of the CG, the difference between the two groups was not significant (P = 0.316). In a study design comparing virtual to face-to-face clinical simulation, anxiety mean scores were significantly higher in the virtual settings, owing perhaps to a first exposure to VS without sufficient information about how to use the program [37]. Meanwhile, a sample of nursing students reported less stress and anxiety in a four-country study [27] (Canada, England, Scotland, and Australia) using six open-access VS cases that were time-spaced (two per week), debriefed and followed simulation best practices [38]. Even when physical symptoms of stress and anxiety were used, it was discovered that scores of cold and sweaty hands, significant restlessness, and tight muscles were lower in the VS group [32]. Generally, VS is associated with a low level of anxiety [39], unless in circumstances of one-time use or when technical issues are not prevented through a good prebriefing [8, 40].
Limitations and perspectives
One of the most limitations of this VS is the lack of a real debriefing session after the cases, what was similarly pointed by Wright et al. [35]. Only self-debriefing [17] was used. Further studies should be conducted to analyze the use of self-debriefing. Moreover, a single course with content related only to the MAP was the subject of this study. Other courses targeting more complex competencies should be handled by SBSs. The SBSs were played once. This might be a reason behind any negative or insignificant finding. The study involved different numbers of participants responding to different questionnaires, which may have influenced the results. Concerningly, about \({\raise0.5ex\hbox{$\scriptstyle 2$}\kern-0.1em/\kern-0.15em\lower0.25ex\hbox{$\scriptstyle 3$}}\) of the CG’s participants and \({\raise0.5ex\hbox{$\scriptstyle 1$}\kern-0.1em/\kern-0.15em\lower0.25ex\hbox{$\scriptstyle 3$}}\) of the IG’s participants dropped out of the post-test. It seems that this study needs more stratification based on test scores for the OSCE phase. This could introduce sample bias due to small group sizes. Future studies should consider stratifying participants by initial test scores to ensure balanced comparisons.
Conclusion
The strength of this study is that it assessed nursing students’ knowledge and skills acquisition in the MAP through real formative practice. Although most of the quantitative results were not statistically significant, SBS participants overwhelmingly justified not only a gain in their DDC knowledge and skills, but also a high degree of satisfaction and confidence in their learning. No previous publication has evaluated the acquisition of knowledge and skills with the SIMDODE® platform in nursing students. Further studies on this subject should enrich the state of the art to guide educators in the use of this pedagogical innovation.
Acknowledgements
The authors extend their gratitude to Mohammed VI University of Health and Sciences (UM6SS) of Casablanca, as well as the Higher Institutes of Nursing and Health Techniques (ISPITS) of Meknes and Oujda, for their crucial support and collaboration. Special thanks to Mr. BOUTERFASS Noureddine, Mr. BELOUACHI Fouad, Mr. DIDOUH Mostafa, Mrs. TOUJAMI Zineb, Mrs. BENAMMI Dounia, Mr. DAHBI Najib, Mr. MAHOU Youssef, Mrs. EZ-ZANAGUY Hanae, Pr. CHAHBOUNI Mohammed, Mr. RABHAOUI El Mahjoub, Pr. FARES Rachid, Mr. LAGHNADI Oussama, Mr. BOUDAROUA Mouad, Mr. BADISY Imad, Mrs. LASRI Soumia, Mrs. MESSNAOUI Assia, Mr. ACHAFAR Abdelaziz, Mr. SAOUDI Hatim, Mr. ZAMMOURI Hamza, Mr. KHEDROUF Taha, and Mrs. EL BOUBRAHIMI Boutaina.
Declarations
Ethics approval and consent to participate
This trial was approved by the Ethics Committee of Mohammed VI University of Health and Sciences (Casablanca, Morocco) with reference number CE/UM6SS/07/23. All the participants provided online informed consent and were informed of the right to withdraw from participation at any time during the research until publication. Data confidentiality was ensured, and the results were provided to the participants at their request.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
