Situation Simulation in Nursing | Research

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27th Nov 2017 Nursing Reference this

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INTRODUCTION

Background

In nursing education, simulation is a mainstay for clinical learning (Tanner, 2006), particularly in the areas of safety, problem solving, and communication (Durham & Alden, 2008). Also simulation-based education leads to improved self-confidence in performance (Cant and Cooper, 2010)

According to Jefferies (2005), successful learning using simulation requires alignment of the design, teaching activities, competencies, and learning outcomes. The case scenario, including simulations of actual clinical problems, provides an interactive learning environment, engaging students in the learning process and encouraging them to make connections between and among concepts. Environmental interactivity and feedback typically is achieved through the use of a high-fidelity patient simulator supplemented with role-play techniques (Good, 2003).

Although simulation has been used successfully, more recently, in medical and nursing education programs (King & Reising 2011; Tan, Ti, Ho, & Lee, 2002), its use as an evaluative tool is still not fully developed. Student performance evaluation is a very important step during simulation-based practice. There is limited research in the use of simulation in nursing education and the evaluation of student competency (Reed, 2010).

The instrument, developed by Jenkins (1985), is a self-report measure in which respondents are asked to identify processes or strategies used in deriving clinical decisions. Because one used for evaluating the quality, the validity of a general self-report measure would be questionable.

Faculty evaluation of student performance was found to be the primary evaluation method, with student report of performance second and evaluation of videotaped performance third (Nehring & Lashley,2004). Radhakrishnan et al.(2007) described using simulation to evaluate clinical skill performance in several areas: safety, basic assessment, prioritization, problem-focused assessment, ensuing interventions, delegation, and communication.

Lasater (2007) also developed Lasater Clinical Judgment Rubric (LCJR) based on Tanner’s Clinical Judgment Model (noticing, interpreting, responding, and reflecting). The LCJR defines what is meant by noticing, interpreting, responding, and reflecting with 11 dimensions with four scale levels. Although, LCJR has relevance for all clinical contexts, including acute care, long-term care, and community health (Lasater, 2007), for simulation evaluation with emergency situation such as asthma, competency evaluation in clinical decision making should be undertaken. It is reported in both the nursing and medical literature (Edwards, 2007; Ottestad, Boulet, & Lighthall, 2007) that real-time observation may be necessary to appropriately evaluate clinical decision making because it can reveal contextual and communication factors that may not otherwise be uncovered. Furthermore, to enhance the effectiveness of simulations in nursing education, a reliable and valid evaluation instrument is needed to measure students’ performance.

Asthma mostly leads to emergency conditions because it shows spasmodic respiratory relapses and unpredictable occurrences. Especially, if asthma continues for a long time, it can progress into chronic lung disease and patient can experience suffering (Ko et al., 2010). Therefore it has to be considered as first priority problem in nursing care and nursing students must be prepared to provide emergency nursing care with high-fidelity simulation experiences for caring patients with asthma. Accordingly, simulation modules may help to provide a comprehensive understanding of asthma and asthma management. The purpose of this article are ; (a) to develop a scenario for patients with asthma for simulation education of nursing students, (b) to develop the evaluation checklist, and (c) to evaluate students’ performances.

METHODS

Design

This study is a methodological study to evaluate students’ performance according to developing and applying of simulation scenario for patients with asthma in emergency units.

Context and Participants

The study was conducted at a regional school of nursing that offers a Bachelor of Nursing program in South Korea. In 2013, following ethics approval, third year (N=112) nursing students undertaking their first simulated learning experience were informed about the study. Total participants were divided 28 groups and the member of each group was 4 students (the role of doctor, nurse1, nurse2, family). The allocation of team and participants` role was assigned by randomization.

The participants’ ages ranged from 20 to 24 years. The majority of students (88.9%) were women.

Development process of asthma scenario with algorithm and evaluation checklist

nursing journals (Poirier et al., 2000; Sarrell et al., 2002; Walsh et al. 2006). Issues included signs and symptoms of dyspnea, coughing with sputum, and anxiety related to the validity of the simulation evaluation by expert review. This scenario was based on a real dyspnea case with asthma that had occurred in emergency center of general hospital.

To evaluate student performance in simulation, a team of researcher developed a template of an evaluation tool to include key elements from simulation course objectives. The following three main contents were identified: patient safety (infection control and error identification), communication, and critical thinking related to patient assessment, problem identification with nursing diagnosis, and intervention with evaluation. The items of evaluation checklists were selected, reviewed, and analyzed by 9 expert panel including 2 internal medicine doctors, 3 emergency center nurses, and 4 nursing educators. All items of checklist include a core set of key behaviors expected in this simulation course. The evaluation checklist based on three main contents (patient safety, communication and critical thinking) was formulated according to nursing process

Finally, 4 items were deleted and 24 items reached by consensus (Table 1). The preparation subdomain consisted of three checkpoints, while the assessment subdomain was divided into seven checkpoints. Three nursing problems were included in the problem identification subdomain. The intervention with evaluations subdomain consisted of eleven checkpoints (Table 1). The evaluation checklist score was based on a 3-point Likert scale (1: not fulfill, 2: partially fulfill, 3: fulfill). The higher the evaluation checklist score, the higher the performance rating.

Content validity is an important part of scale development because the results gained from an instrument with high representative nature are more reliable (Waltz & Bausell, 1981). Content Validity Index (CVI) is a commonly used indicator of scale validity and in particular content validity. A content validity test was conducted with 10 nurses who worked in a medical-surgical unit in one of the three general hospitals sampled; each had at least three years of experience in the unit. According to Lynn (1986), an expert panel ideally includes about ten people. Each expert checked validity using the 4-point Likert scale; 1 means ‘not validate at al’, 2 means ‘not validate’, 3 means ‘validate’ and 4 means ‘very validate’. There were 24 items in total; the mean score of each item ranged from 3.30 to 3.90. The results of the Content Validity Index were above 80% (Waltz & Bausell, 1981).

Data collection

A 20 minute scenario requiring students to use their clinical reasoning ability to identify and respond to a deteriorating ‘patient’ with asthma was presented. Four nursing students were engaged in the simulation at the same time. One operator and one instructor observed the simulations from the control room. Evaluators had simulation exercise for conformity degree of evaluation using two group students selected for evaluation practice. The evaluation of students’ performance was completed two times, immediately following simulation practice and reviewing of video-recording by two instructors. For accurate evaluation, evaluators rechecked and discussed item by item to decrease evaluation bias replaying video. Their performance was evaluated as a group.

Data analysis method

Collected data were analyzed using SPSS 18.0 for Windows (SPSS Inc, Chicago, IL) to calculate descriptive and t-test statistics for the evaluation checklist.

RESULTS

Algorithm with a scenario of simulation-based asthma management

The simulation-based asthma scenario in this study was developed to identify and solve patient’s problems applying nursing skills and utilizing critical thinking. Development of this scenario was based on a real dyspnea case with asthma that had occurred in an emergency center.

1. Learning objective

Learning objectives were formulated as follows:

  1. Explain pathophysiology of asthma
  2. Assessment of asthma patient
  3. Explain medication and effects of asthma drug
  4. Identified nursing diagnosis based on critical thinking
  5. Effectively communicate with the patient and colleague
  6. Implementation of evidenced based adequate nursing interventions

2. Development of a simulation-based asthma scenario

The contents of scenario based on four steps was formulated; preparation, assessment, problem identification, interventions and evaluation. The preparation subdomain was consisted of the preparation content that should be cared for patients who admitted to emergency unit. The assessment subdomain were included in check the chief complaint, identify symptom related to chief complaint (dyspnea pattern, cyanosis, delayed expiration, pallor, color of mucus membrane, check SpO2, identify vital signs, auscultate respiratory sounds, check EKG rhythm with cardiorespiratory monitoring equipment), and identify past history. Problem identification subdomain organized that student can be present nursing diagnosis related to asthma; 1) Ineffective airway clearance related to excessive secretion, 2) Ineffective breathing pattern related to airway obstruction, 3) Anxiety related to dyspnea.

Intervention and evaluation were organized focusing on the nursing process for dyspnea care(high fowler`s position), encourage of deep breathing (pursed-lip breathing, abdominal breathing), notify doctor and receive treatment order, administration of O2 and medication, nursing care for dyspnea control(drainage sputum with coughing), reassess patient`s condition(vital signs repeatedly, SaO2, EKG monitoring, respiratory status, physical examination, , SpO2, ABGA), educate coping behavior when symptoms are aggravated(deep breathing, coughing, drinking water, and aging nurses), support patient and family with therapeutic communication(explain easy, listening, relieve anxiety, communicate clearly with peers), arrange materials and instruments and wash hands, and record the nursing implementations.

3. Development of algorithm

The algorithm proceeded as follows: patient safety (Step 1) and critical thinking and communication(Step 2)(Figure 1).

Evaluation checklist

The evaluation checklist consisted of four subdomains based on nursing processes: preparation, assessment, problem identification, intervention, and evaluations. The mean score of each subdomain is shown in Table 1.

Table 1. Means of Items of Developed Evaluation Checklist

The total mean score of the evaluation checklist was 2.39 (± .15). The mean score of each subdomain was as follows: preparation 2.05(±.49), assessment 2.52 (± .33); problem identification 2.74 (± .33); intervention and evaluation 2.22 (± .30).

The interobserver reliability between evaluators (Cohen`s Kappa score) was 0.949 % and there were no statistical significant differences among each item.

The evaluation of students performance

In the subdomain of preparation, students showed the highest mean score in the item ‘identify patient by name care and asking’ (2.46±.54) while the lowest item was ‘introducing self to the patient & his/her parent(s)’ (1.68±.86). In the subdomain of assessment, the strong practice areas that student was well done were ‘identify vital signs’ (2.93±.26) while the lowest mean score was ‘auscultate respiratory sounds’ (2.11±.73). In the subdomain of problem identification, the highest mean score was ‘ineffective breathing pattern related to airway obstruction’ (2.93±.83) while the lowest mean score was ‘ineffective airway clearance related to excessive secretion’ (2.55±.74). In the subdomain of interventions and evaluations, the highest mean score was ‘notify doctor and receive treatment order if needed’ while the lowest mean score was ‘educate coping behaviors when symptoms are aggravated’ (1.93±.60).

DISCUSSION

In this study, the contents of simulation was formulated with asthma situation which is the most high frequency and required nursing care with education to improve an appropriate coping ability of nursing students. For this, the 3rd year students who have experienced only theoretical learning about respiratory care were selected to identify clinical performance ability according to learning objectives. So, the contents of scenario in this study was focused to achieve clinical performance ability of nursing students with three main contents (patient safety, communication and critical thinking)

There are few studies which was dealt with respiratory problem. A simulation scenario for emergency care of patients with dyspnea used by Hur & Park (2012) included only contents to train theoretical education as the nursing process. In case of other research dealing with simulation case for patients with asthma in emergency units (Ko et al, 2010), the contents of scenario was formulated into five categories as follows: problem recognition, focused assessment, nursing diagnosis, intervention and problem resolution. However, there was a limitation about testing clinical performance ability.

We suggest that three domains and contents of a scenario developed in this study are more suitable to improve students’ clinical performance.

Lindsay(2010) suggest that measuring the performance of nursing care directly is more effective than using psychological variables as testing the effect of simulation learning.

The evaluation checklist used in this study was developed to examine students’ critical thinking as well as their knowledge and skills in proper nursing care and validated by expert panels. The evaluation domain, which fully implements high-fidelity simulations, offers information to nursing educators about students’ learning outcomes. The use of simulations to evaluate clinical ability provides a more direct correlation to actual clinical settings than other commonly used forms of evaluation. The evaluation indicated that the focus was on performance rather than learning. The study’s evaluation checklist would also be a useful and established guide for nursing educators evaluating student performance through simulations. This checklist describes the overall evaluation process and clarifies the evaluation’s target subject and procedure. This encourages students to repeat checkpoint reviews, leading to the correction of earlier mistakes. The effect of reviewing past checkpoints creates an integrative, rather than a static learning experience (Reed, 2010).

To test evaluation validity, the consensus between evaluators was identified and showed almost similar evaluation results with no statistical significant difference.

In the domain of patient safety, students showed the highest mean score in the item ‘identify patient by name care and asking, while the lowest item was ‘introducing self to the patient & his/her parent(s)’. This result implies that addressing to introduce oneself to patient before caring patients as a part of simulation education is necessary. The research (Kim et al., 2013) which was developed simulation-based fever management module and evaluated student performance showed that ‘introducing self to the patient & his/her parent(s)’ was identified as the lower mean score among other evaluation items. These similar results suggest that noticing themselves to the patient is so important to protect patient’s safety.

In the domain of critical thinking and communication, the strong practice areas that student was well done were ‘identify vital signs’ in assessment, ‘ineffective breathing pattern related to airway obstruction’ in problem identification, and ‘notify doctor & receive treatment order if needed’ in interventions and evaluations. However the weak practice areas which education and practice will be needed were ‘auscultate respiratory sounds’ in assessment, ‘ineffective airway clearance related to excessive secretion’ in problem identification, ‘educate coping behaviors when symptoms are aggravated’ in interventions and evaluations.

It is required that students needs high level practice of assessment and performance skill with critical thing. Jeffries (2005) suggests that simulation education through direct participation and prompt feedback is effective learning method to reinforce clinical performance ability. In this study, theoretical class and orientation about simulation situation was given before simulation practice to find more effective nursing intervention. As a next step, students could enhance the strong point and make up week areas in the process applying nursing care with direct participation. Based on this result, we suggest that integrated simulation approach after learning of theoretical knowledge and nursing skill training could be effective education method to improve clinical performance ability and critical thinking of nursing students. The study of Kim et al (2007) supports these aspects that simulation education is more effective than lecture focused on knowledge and simple skill practice in acquisition clinical performance skill of nursing students.

CONCLUSION

This study could provide a clinical performance or starting point for educators who desire to introduce simulation as teaching-learning strategy with high-fidelity simulation experiences for caring patients with asthma. The results provide evidence to support the integration of simulation as an effective teaching strategy that helps to improve nursing students` safety, problem solving, and communication in applying clinical skills using evaluation checklist.

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