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J Korean Acad Psychiatr Ment Health Nurs > Volume 33(4); 2024 > Article
Kim, Lim, and Kim: Assessing the Effectiveness of a Virtual Reality-Based Simulation Program for Mental Health Nursing Practicum

Abstract

Purpose

The COVID-19 pandemic significantly impacted clinical practicums for nursing students, especially in mental health nursing, resulting in cancellations due to infection risks. In response, online and VR simulations emerged as appealing alternatives that cater to the preferences of digital-native learners. This study aimed to evaluate a VR-based mental health nursing simulation program.

Methods

The study utilized a non-equivalent control group pretest-posttest design and was conducted within nursing education institutions. Fifty-four fourth-year nursing students, who had theoretical knowledge but lacked clinical experience, participated after providing informed consent. The program consisted of six thematic modules that simulated real-world scenarios, and its effectiveness was assessed using repeated measures ANOVA.

Results

The findings revealed significant improvements in knowledge related to mental health disorders, learning flow, and overall satisfaction. The program successfully bridged the gap between theoretical and practical learning, enhancing students' skills and confidence in patient interactions and therapeutic nursing interventions.

Conclusion

The simulation education program effectively served as a bridge between theoretical learning and practical application, providing students with a valuable educational experience. By improving students' abilities and confidence in engaging with patients and delivering therapeutic nursing interventions, the program demonstrated its potential to connect classroom learning with real-world clinical practice in mental health nursing.

INTRODUCTION

The extended duration of the coronavirus disease 2019 (COVID-19) pandemic has significant impact on teaching and learning approaches across multiple fields, including nursing education. The widespread transmission of the virus severely constrained possibilities for nursing students to engage in clinical practicums, a fundamental aspect of nursing programs. Clinical practicums provide students with the critical knowledge, skills, and experiential learning essential for their professional development. Notably, the mental health nursing practicum plays a pivotal role in preparing students by enhancing their interpersonal and communication abilities, enabling them to establish positive relationships with individuals facing mental health challenges, and fostering their confidence and trust-building capabilities [1].
However, during the COVID-19 pandemic, all mental health nursing training sessions were suspended due to the heightened risk of widespread epidemics among individuals with mental health illnesses [2]. Furthermore, the shifting landscape of healthcare, which prioritizes the reinforcement of patient rights and the advancement of individualized care, has further limited the availability and scope of clinical practicum opportunities for nursing students [3].
In May 2023, the World Health Organization (WHO) declared the end of the COVID-19 pandemic [4]. However, differences in standards for responding to infectious diseases persisted across countries. In Korea, for instance, the national disaster crisis level related to infectious diseases was downgraded to its lowest level in May 2024, with quarantine measures becoming more autonomous and similar to those used for influenza [5]. Despite the declaration of the pandemic’s end and the relaxation of infectious disease response standards, clinical practice opportunities for nursing students, particularly in psychiatric nursing, remain limited due to the vulnerable environment of closed wards, which pose a higher risk for infectious diseases.
Virtual clinical training programs, particularly those incorporating immersive virtual reality (VR) and augmented reality (AR), have made substantial progress, offering various advantages such as freedom from time and location restrictions, a safe and immersive learning environment, and cost-effectiveness [6]. With the emergence of the fourth industrial revolution, virtual reality (VR) and augmented reality (AR) technologies have gained substantial interest of society. Universities and colleges are increasingly prioritizing the learning demands of the digital-native Generation MZ, who represent a key demographic in higher education and are among its primary consumers [7].
Currently, VR technology is employed in adult and pediatric clinical practicum courses, comprehensive simulations [8], and skill acquisition, such as intravenous injection training [9]. While virtual and digital learning platforms have been introduced in psychiatric nursing practicums [10,11], research on the application of VR in this area remains limited. In mental health nursing clinical practice, Simulation using virtual reality is effective in immersing learning by arousing interest. It enables complete learning for nursing students by repeatedly attempting the process of integration through the application of knowledge and feedback [12].
While virtual reality-driven training programs has demonstrated its benefits for focus and engagement, a formalized structure in nursing education has yet to be implemented [13]. There is a notable lack of research focused on the structured planning and creation of diverse learning elements grounded in theoretical frameworks. Additionally, high-quality intervention studies that use structured methodologies to assess the learning impact of VR-and AR-based online practicums remain scarce [14].
According to Ayres’ learning transfer model, Academic outcomes are primarily shaped by students' motivation to apply and convey understanding, rather than being exclusively determined by their individual attributes or the instructional material itself. The model highlights the pivotal role of students’ drive to acquire knowledge, which includes their goals, choices, and passions, in shaping educational results [15]. Transfer motivation, which denotes the aim to implement acquired expertise and abilities in professional practice, is recognized as a crucial indicator of the core objectives of clinical practicums [16]. Studies have demonstrated that online practicums effectively enhance nursing students’ motivation to learn, satisfaction with the learning experience, confidence in abilities, motivation to apply learning, and problem-solving capabilities [17]. This learning environment promotes and supports learning transfer by providing a supportive framework, either through fellow students or educators. When these essential elements successfully stimulate learning, transfer motivation increases, thereby enhancing learning outcomes.
The purpose of this study, guided by the learning transfer model [15], was to assess the impact of a VR-based psychiatric mental health nursing simulation program by evaluating key factors related to learning and transfer. Specifically, the study examines learning flow and learning self-efficacy (as indicators of learning motivation), transfer motivation (indicating the process of knowledge transfer), mental illness-related knowledge, critical thinking skills and learning satisfaction (knowledge transfer results). Additionally, the research emphasizes the structured progress of each learning component to establish VR-based clinical practicums as viable alternatives to conventional approaches, rather than merely supplementary tools.

1. Aim

The aim of this study was to assess the effectiveness of a virtual reality-based psychiatric mental health nursing simulation program.

2. Hypotheses of Study

The study proposes the following hypotheses: Nursing students who engage in the VR-based psychiatric mental health nursing simulation will show significant differences in 1) learning flow, 2) learning self-efficacy, 3) transfer motivation, 4) mental disorders knowledge, 5) problem-solving, and 6) learning satisfaction compared to those in the control group.

1) NeuroTech dialogue box

This study introduces a VR-based simulation program aimed at preparing nursing students for mental health nursing practicums. Given the limited availability of psychiatric units and the short duration of clinical exposure, students often lack sufficient opportunities to engage with a variety of cases. Our VR simulation fills this gap by providing an immersive environment where students can practice therapeutic communication with virtual patients, modeled after real clinical cases.
For technical audiences, this program combines structured stages, pre- and post-class quizzes, and interactive elements, such as true/false questions and image-based tasks, to enhance students’ knowledge of mental health disorders and increase engagement. The integration of gaming features within the simulation highlights how advanced VR technology can be used effectively to support learning in emotional and cognitive areas such as mental health nursing.
For clinicians, the simulation serves as a valuable tool to help students build confidence and gain experience in therapeutic communication before entering real clinical environments. By simulating patient interactions in a virtual setting, students are better equipped to apply their knowledge in practice. The program also leads to higher levels of learning satisfaction and readiness for clinical practice, underscoring the value of VR simulations as a complement to traditional nursing education.
Introducing VR-based simulations into mental health nursing curricula can better prepare students to face the unique challenges of mental health care, enhancing both their confidence and practical skills.

METHODS

1. Study Design

This quasi-experimental study employs a non-equivalent control group pretest-posttest design to assess the effectiveness of a VR-based simulation program for psychiatric mental health nursing. This study serves as a pilot investigation of the program initially developed during a 3-year development process.

2. Recruitment

The participants of this study were fourth grade nursing students who had previously completed at least one theory course in psychiatric mental health nursing. But had not yet taken any mental health clinical practicum. The students were selected from a single school in each of the three regions included in the study. Only participants who submitted written informed consent via the online platform were included in the study. The sample size was determined using G*Power 3.1.9.7 software. Drawing on previous research, the minimum sample size needed to detect an effect size of 0.25, with a significance level (⍺) of .05 and a power (1-β) of .95 for two repeated measurements, was calculated to be 27 participants per group, resulting in a total of 54 participants. To compensate for possible dropouts, a total of 58 students were recruited, with 29 students assigned to each group.

3. Instruments

1) Learning flow

Learning flow was measured using the Korean Learning Flow Inventory for adults, adapted by Kim et al. [18], which is based on Csikszentmihalyi’s Flow Questionnaire [19]. This questionnaire consisted of 29-item employ a five-point Likert scale. The Cronbach’s ⍺ was .95 at the time of its development and .94 in the current study.

2) Learning self-efficacy

Learning self-efficacy is defined as an individual's confidence in their ability to utilize acquired knowledge [15]. For this study, we employed the tool created by Ayres and modified by Park and Kweon [16]. This 10-item questionnaire uses a seven-point Likert scale, where higher scores reflect higher levels of learning self-efficacy. The Cronbach’s ⍺ was .94 during its original development and .92 in this study.

3) Transfer motivation

Transfer motivation is defined as an individual’s readiness to apply acquired knowledge, skills, and insights in a workplace setting [20]. To assess transfer motivation, we utilized the tool originally developed by Ayres [15] and adapted by Park and Kweon [16]. This 10-item questionnaire uses a seven-point Likert scale, where higher scores signify stronger transfer motivation. The Cronbach’s ⍺ was .80 during its initial development and .92 in this study.

4) Mental disorders knowledge

Based on the study by Han et al. [21], we created 20 items to evaluate individual knowledge for each module. The content validity was confirmed by two mental health nursing professors and an expert with 10 years of experience in psychiatric nursing, resulting in a content validity index exceeding .95 for all items. Higher scores reflect a higher level of knowledge, and the Cronbach’s ⍺ in this study was .73.

5) Problem-solving

Problem-solving was measured using the questionnaire developed by Lee et al. [22], consisting of 30 items divided into five domains: problem clarification (6 items), solution exploration (6 items), decision-making (6 items), solution implementation (6 items), and evaluation and reflection (6 items). Each item is scored on a five-point Likert scale, where higher scores indicate stronger problem-solving skills. The Cronbach’s ⍺ was .93 during its development and remained .93 in this study.

6) Learning satisfaction

Learning satisfaction is defined as the extent to which students feel their learning needs have been met, specifically the extent to which educational content meets their perceived necessities. For this study, we adjusted and customized the Online Educational Service Quality Scale by Bae [23] to be applicable to online classes. This 17-item survey uses a five-point Likert scale, with higher scores reflecting greater learning satisfaction. The Cronbach’s ⍺ was .95 at the time of Bae's development and .92 in the current study.

4. Data Collection

Participants were enrolled via a social media post promoting the study in online communities of nursing colleges across three areas in Korea. Data collection began only after volunteers gave their informed consent to participate. A total number of 58 participants were recruited and allocated to either the experimental group or the control group, with 29 participants in each group. The experimental group received an explanation about the program's content and procedures through video conference, emphasizing that participation was entirely voluntary. The control group received learning materials on the same contents as the program and was given the opportunity to join the VR-based simulation program after the study ended. Both groups completed an online baseline questionnaire, which was later used for the post-test immediately after the program and again six weeks afterward. Data collection occurred from March 14 to July 1, 2022. Both groups filled out an online baseline questionnaire, which served as the pre-test before the program started, the post-test right after the program ended, and a followup test six weeks later. Data collection took place from March 14 to July 1, 2022.

5. Implementation of the VR-based simulation program

The VR program was developed as an online platform for psychiatric mental health nursing practicum. It has six modules: delusion, hallucination, mania, dementia, suicidal ideation, and obsessive-compulsive disorder (OCD). Each module is structured into 11 stages, as outlined in Table 1. As a online-based platform, the program allows students to access it from any location and at any time via the website. Each participant received a unique ID and password to log in and document their academic activities for each stage on the site. The experimental group studied three modules each week, completing the entire set of modules within two weeks. Online debriefing meetings were provided two times a week to address students' questions. The control group received the six module scenarios via email for self-directed learning and attended online meetings twice a week. Upon completion of the study, the control group was given individual passwords and IDs to access the simulation program. In the first week, students were directed to complete the first three modules- dementia, hallucination, and delusion-on days 1, 2, and 4, respectively, with online debriefing sessions scheduled for days 3 and 5. During the second week, they completed the modules on bipolar disorder, suicidal ideation, and OCD on days 1, 2, and 4, with debriefings again held on days 3 and 5.

6. Statistical Analysis

Data were analyzed using the IBM-SPSS 22.0 (IBM Corp., Armonk, NY, USA) statistical package. Participants' demographic characteristics were described using percentages, frequencies, means, and standard deviations. The homogeneity between the two groups was assessed using the x2 test and independent t-test. The effectiveness was evaluated using repeated measures ANOVA.

7. Ethical Considerations

This study was officially approved by the Institutional Review Board at the Gangeung-Wonju National University (GWNUIRB-2022-3-1). Participants were informed about the study's aim and procedures and willingly consented to take part, with the freedom to withdraw at any point. They were also assured that their data would be coded, remain anonymous, and managed according to the Bioethics and Safety Act. All participants of this study voluntarily completed the online consent form, and the control group was given the option to participate in the equal program after all data collection concluded.

RESULTS

1. Participants’ General Characteristics and Homogeneity Testing

Table 2 illustrates the homogeneity of the general characteristics between the two groups. No significant differences were observed between the groups in terms of age (t=-0.07, p=.944), prior experience with virtual classes (x2=1.42, p=.491), clinical practicum experience (x2=2.07, p=.491), perceived information technology device literacy (t=0.37, p=.714), or satisfaction with the major (t=0.00, p>.999) (Table 1).

2. Homogeneity of Dependent Variables

No significant differences were observed between the two groups in transfer climate (t=0.63, p=.534), learning flow (t=1.10, p=.276), learning self-efficacy (t=0.80, p= .429), transfer motivation (t=-0.45, p=.658), mental disorders knowledge (t=1.58, p=.119), problem-solving (t=1.35, p= .182), and learning satisfaction (t=0.72, p=.475) (Table 3).

3. Effectiveness of the VR-Based Simulation Program

After completing the VR-based simulation program, significant differences in learning flow were found between the experimental and control groups (F=6.36, p=.015). Additionally, significant changes were observed between the immediate post-program results and those measured six weeks later (F=4.00, p=.021) A significant interaction between group and time was observed (F=6.86, p=.002). Learning self-efficacy also showed significant differences between the experimental and control groups (F=11.72, p=.001). However, there were no significant differences across time points (F=0.52, p=.598), but a significant group-time interaction was found (F=4.84, p=.010).
Transfer motivation did not show significant differences between the experimental and control groups (F=0.74, p=.394); however, the scores significantly varied over time (F=4.87, p=.011), with a significant interaction between group and time (F=3.49, p=.034). In contrast, mental disorders knowledge revealed significant differences between the two groups (F=24.55, p<.001), across time points (F=11.73, p<.001), and in the group-time interaction (F=12.85, p<.001). Problem-solving showed significant differences between the two groups (F=9.79, p=.003), but no significant changes were observed over time (F=2.75, p=.068). However, a significant interaction between group and time was found (F=3.35, p=.039). Learning satisfaction differed significantly between the groups (F=11.87, p=.001) and across time points (F=8.10, p=.001), with a significant group-time interaction (F=9.23, p<.001). The differences in the study parameters between the two groups at various time points are depicted in Figure 1. The effects of the program persisted up to six weeks following its completion (Table 4).

DISCUSSION

Mental health nursing practicums demand that students work with sensitivity and attentiveness, as they include direct therapeutic interactions with patients dealing with mental health conditions.
Insufficient preparation for patients interviews may cause unfavorable results for both nursing students and clients. According to Kim & Kim [24], many nursing students experience a lack of confidence, along with anxiety and fear, during their first clinical practicums. Simulations offer a potential answer to this issue, as reviewed by Mulcahy et al. [25]. We developed a VR-based simulation for the psychiatric mental health nursing practicum to provide students with essential practical experience before starting real clinical settings. This innovative method enhances traditional nursing education by extending learning beyond classrooms and hospitals to a virtual online platform. These findings illustrate that the program successfully achieved positive educational consequences. The VR-based simulation program for psychiatric mental health nursing demonstrated significant effectiveness in boosting students’ understanding of mental disorders, fostering better learning engagement, and enhancing overall satisfaction with the learning process. The improved comprehension of mental disorders can be credited to the program’s design, which featured 11 distinct stages incorporating pre-class activities, preparation quizzes, and post-class assessments to measure knowledge acquisition after completing the program. Knowledge improvement is widely recognized as a key outcome in simulation-based education.
Learning flow also improved significantly. Kim and Kim [24] propose that the enhanced learning flow observed in virtual simulations may result from their engaging and immersive qualities. Our program incorporated interactive, game-like elements, such as true-or-false questions combined with image cards, to engage students, including those with no previous simulation experience. Furthermore, in stage 4, students engaged with a virtual patient modeled on real clinical scenarios, allowing them to practice therapeutic communication by inputting responses in a natural conversational manner. These interactive components likely played a key role in improving learning flow.
High levels of learning satisfaction following simulation-based education have been consistently reported in prior research. İsmailoğlu et al. [26] reported that participants showed high levels of satisfaction with a VR-based simulation designed for intravenous injection training. Similarly, Chae et al. [27] observed high satisfaction levels, with a score of 4.12 out of 5, among students who participated in a simulation involving a pediatric asthma patient. Studies show that greater satisfaction with simulations is linked to improved confidence in nursing practice. Based on these findings, we suggest incorporating our VR-based simulation program into mental health nursing practicums to better prepare students for clinical practice.
Although no significant changes in problem-solving and learning self-efficacy scores were detected over time, significant differences were observed between the groups. Gholami et al. [28] found that nursing students who participated in an emergency nursing simulation showed improved critical thinking skills and problem-solving abilities. This indicates that simulation-based education not only aids in developing essential nursing skills but also enhances students' cognitive abilities. Lee et al. [29] highlighted that VR-based education allows nursing students to take charge of their learning by recognizing and implementing appropriate nursing practices for specific cases, as well as assessing the results, ultimately boosting their self-efficacy.
Transfer motivation did not significantly differ between groups but varied across time points. Zulkosky et al. [30] highlighted that a major advantage of simulation-based education lies in its interactive learning environment, which delivers holistic learning outcomes across multiple areas, such as mental, cognitive, spiritual, emotional, motor, and affective domains. More recently, the use of haptic sensors in VR-based educational simulations has broadened its applications. These sensors add tactile feedback to visual and auditory stimulation, enhancing immersion and creating a more engaging learning experience.
Drawing on these findings, we emphasize the need for greater adoption of simulation-based education within nursing curricula. The advantages demonstrated by our VR-based psychiatric mental health nursing simulation program emphasize the critical role of virtual simulations in addressing the unique challenges faced in mental health nursing practicums. The limited availability of psychiatric units, coupled with the short duration of practicums-often just one or two weeks-significantly reduces students' exposure to a variety of cases. This limitation diminishes the overall quality of mental health nursing education, making virtual simulations a vital tool for enhancing students' learning experiences.

1. Limitations

While this study provides meaningful insights into the creation and effectiveness of a VR-based simulation program for psychiatric mental health nursing practicums, there are several limitations that should be taken into account. First, the relatively small sample size and the recruitment from a single school in each region may limit the generalizability of the findings to a broader population of nursing students. Additionally, the study’s follow-up period of six weeks was relatively short, which may restrict the ability to assess the long-term impacts on nursing competencies. Technological constraints, such as variations in internet access and device quality, may have also influenced participants’ experiences and outcomes, introducing potential confounding variables. These limitations should be considered when interpreting the results. Future research should aim to address these challenges to strengthen the evidence supporting the use of VR-based simulations in nursing education.

CONCLUSION

This study sought to develop a VR-based simulation program for psychiatric mental health nursing practicums using real-life clinical scenarios and assess its effects on nursing students. The findings revealed significant group and time effects across all six measured parameters. Students who participated in the VR-based simulation program demonstrated enhanced preparedness and gained more diverse experience compared to those in other clinical practicum courses. This was achieved through direct engagement with virtual patients experiencing mental illnesses and opportunities to practice therapeutic communication.
We suggest that this simulation program can function as a bridge between theoretical learning and clinical practice, providing students with an intermediary educational platform. This approach enhances students' competence and confidence in engaging with clients and providing therapeutic nursing care in real clinical settings by supporting self-directed learning before and during clinical practicums.
Building on these findings, we suggest that future research investigate the incorporation of haptic devices into mental health nursing simulations, enabling students to experience both the verbal and physical components of nursing care for a more realistic simulation of real-world situations. While this program was specifically designed for the mental health nursing practicum, future studies could focus on developing simulations aimed at improving clinical reasoning skills. These simulations should cover a diverse range of patient groups, including adults, children, older adults, and communities, while emphasizing nursing management in the scenario design process to promote a holistic approach to patient care.

CONFLICTS OF INTEREST

The authors declared no conflicts of interest.

Notes

AUTHOR CONTRIBUTIONS
Conceptualization or/and Methodology: Kim, GM, Lim, JY, & Kim, J
Data curation or/and Analysis: Kim, GM, Lim, JY, & Kim, J
Funding acquisition: Kim, GM
Investigation: Kim, GM
Project administration or/and Supervision: Kim, GM
Resources or/and Software: Kim, GM & Kim, J
Validation: Kim, GM
Visualization: N/A
Writing: original draft or/and review & editing: Kim, GM, Lim, JY, & Kim, J

Fig. 1.
Differences in the study parameters by time point in the experimental and control groups.
jkpmhn-2024-33-4-431f1.jpg
Table 1.
The Stages of Online VR Simulation Program
Stage Learning activity Contents
Stage 1 Pre-activity Pre-class activity for the mental illness addressed by each module. Includes definition, cause, behavioral characteristics, clinical manifestations, treatment, and nursing care for the mental illness.
Stage 2 Pre-evaluation Pre-class learning is evaluated through a quiz. Students can check correct and wrong answers.
Stage 3 Patient's record review The patient’s chart is presented. The provided information include demographics, psychiatric history, physical assessment, mental health assessment, physician’s orders, medication records, and nursing records.
Stage 4 VR scenario Students run the simulation via VR. The simulation encompasses the patient’s admission management, admission assessment, behavioral characteristics displayed after admission, and the nurse’s interview with the patient. VR videos for each illness of the corresponding module are presented.
Stage 5 Mental health assessment After examining the patient’s scenario, students perform a mental health assessment. Students are able to check and record the assessment results based on each case of the module.
Stage 6 Therapeutic communication analysis VR video interaction between the patient and nurse is presented. After watching the video, students analyze the therapeutic communications used in the conversation.
Stage 7 Nursing diagnosis This is the first step to resolving the patient’s nursing problem. First, the nursing problem is identified. Students then check the nursing problem at hand from a list of options.
Stage 8 Nursing plan Students devise appropriate care plans after performing their nursing assessment for the patient’s nursing problem.
Stage 9 Nursing intervention Students provide therapeutic nursing interventions, including pharmacological treatment, cognitive behavioral therapy, activity therapy, and other nursing interventions. They plan the therapeutic interventions appropriate for each module and record them.
Stage 10 Nursing record Students document their entire nursing process.
Stage 11 Post-evaluation Students take a quiz to be evaluated on their knowledge and skills acquired through the module.
Table 2.
General Characteristics of Participants (N=58)
Characteristics Categories Exp. (n=29)
Cont. (n=29)
x2 or t p
n (%) or M±SD n (%) or M±SD
Age (year) 22.00±3.63 22.07±3.84 -0.07 .944
Type of virtual classes Synchronized online classes 4 (13.8) 6 (20.7) 1.42 .491
Asynchronized online classes (recorded lectures) 1 (3.4) 0 (0.0)
Both 24 (82.8) 23 (79.3)
Clinical practicum experience Yes 29 (100.0) 27 (93.1) 2.07 .491
No 0 (0.0) 2 (6.9)
Information technology device literacy 4.28±0.75 4.21±0.68 0.37 .714
Satisfaction with major 3.86±0.92 3.86±0.79 0.00 >.999

Cont.=control group; Exp.=experimental group; M=mean; SD=standard deviation.

Table 3.
Differences in Dependent Variables between the Groups (N=58)
Characteristics Exp. (n=29)
Cont. (n=29)
t p
M±SD M±SD
Learning flow 3.24±0.51 3.06±0.68 1.10 .276
 Cognitive learning flow 3.55±0.43 3.37±0.68 1.20 .236
 Affective learning flow 2.89±0.72 2.72±0.78 0.86 .392
Learning self-efficacy 5.83±0.62 5.68±0.81 0.80 .429
Transfer motivation 4.86±0.97 4.97±0.98 -0.45 .658
Mental disorders knowledge 11.17±2.87 10.00±2.78 1.58 .119
Problem-solving 119.76±12.01 115.48±12.10 1.35 .182
 Clarification 4.03±0.48 4.10±0.46 -0.51 .612
 Exploration of solutions 4.06±0.46 3.84±0.48 1.71 .093
 Decision making 3.99±0.48 3.77±0.58 1.60 .116
 Application of solution 3.92±0.46 3.78±0.51 1.12 .267
 Evaluation and reflection 3.95±0.52 3.76±0.48 1.48 .143
Learning satisfaction 3.91±0.55 3.81±0.48 0.72 .475
 Systematic organization 3.81±0.58 3.70±0.50 0.75 .455
 Responsiveness 3.85±0.65 3.68±0.69 0.98 .331
 Assurance 4.31±0.55 4.34±0.58 -0.23 .817

Cont.=control group; Exp.=experimental group; M=mean; SD=standard deviation.

Table 4.
Differences in the Study Parameters between the Two Groups by Time Point (N=58)
Category Time Exp. (n=29)
Cont. (n=29)
Source F p
M±SD M±SD
Learning flow Pre 3.24±0.51 3.06±0.68 G 6.36 .015
Post 1 3.39±0.46 3.32±0.68 T 4.00 .021
Post 2 3.66±0.52 3.02±0.52 G*T 6.86 .002
Learning self-efficacy Pre 5.83±0.62 5.68±0.81 G 11.72 .001
Post 1 6.12±0.45 5.55±0.79 T 0.52 .598
Post 2 6.10±0.50 5.42±0.67 G*T 4.84 .010
Transfer motivation Pre 4.86±0.97 4.97±0.98 G 0.74 .394
Post 1 5.26±0.80 5.14±0.87 T 4.87 .011
Post 2 5.47±0.97 5.00±0.68 G*T 3.49 .034
Mental disorders knowledge Pre 11.17±2.87 10.00±2.78 G 24.55 <.001
Post 1 14.45±3.22 10.03±2.91 T 11.73 <.001
Post 2 13.69±3.11 9.69±2.41 G*T 12.85 <.001
Problem-solving Pre 119.76±12.01 115.48±12.10 G 9.79 .003
Post 1 125.86±12.45 116.72±15.47 T 2.75 .068
Post 2 125.86±10.80 113.52±11.79 G*T 3.35 .039
Learning satisfaction Pre 3.91±0.55 3.81±0.48 G 11.87 .001
Post 1 4.28±0.47 3.97±0.56 T 8.10 .001
Post 2 4.37±0.29 3.70±0.56 G*T 9.23 <.001

Cont.=control group; Exp.=experimental group; G=group; M=mean; SD=standard deviation; T=time.

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