Questionnaire design and validation: perception of clinical simulation in nutrition and dietetics students

doi:10.21203/rs.3.rs-3897671/v1

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Questionnaire design and validation: perception of clinical simulation in nutrition and dietetics students

https://doi.org/10.21203/rs.3.rs-3897671/v1

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Background:

Clinical simulation is a strategy that forms part of new learning styles where students are placed at the center, where they are able to integrate different types of knowledge and develop skills and abilities that contribute to their training process.

Objective:

The objective of the study is to design and validate a questionnaire through expert judgment to assess the perception of clinical simulation in nutrition and dietetics students.

Methods

The questionnaire was applied to 90 nutrition and dietetics students and validated by expert judgment (22 experts). For construct validity, a factor analysis was performed using principal component analysis with Varimax rotation. Cronbach’s alpha was used to determine internal consistency.

Results

Kaiser-Meyer-Olkin sampling adequacy estimates (KMO = 0.857) and Bartlett’s statistical significance (p = 0.000) were calculated, where all questions were accepted as valid to the questionnaire. The principal component analysis method was used to obtain five components, accounting for 71,68% of the total variance explained, obtaining a percentage of explanation at appropriate acceptance levels. Each item was included in a single factor, based on its factorial load, establishing a minimum saturation criterion of 0.50. VARIMAX-based rotated factorial solutions formed a well-defined structure without overlapping. A Cronbach’s alpha value of 0.913 was obtained to evaluate the internal consistency of the questionnaire.

Conclusions

The questionnaire that was designed and validated reports high validity and reliability, where students express a high degree of satisfaction. This makes it a useful instrument for the teaching and learning process in clinical simulation.

questionnaire

simulation

validity

reliability

learning

students

Clinical simulation is a teaching-learning strategy that is complementary to traditional methods and is currently used in the training of health professionals (Astudillo et al., 2017). It generates an interactive learning experience, where theoretical knowledge combines with practical knowledge in a simulated context (Espinoza et al., 2020), allowing the student to develop clinical skills in a safe context, providing the opportunity to perform a practice similar to the real context (Zambrano et al., 2020; Perez & Luna, 2021).

This strategy forms part of new learning styles, where students are placed at the center and are able to integrate different types of knowledge and develop clinical skills and abilities that contribute to their own learning and subsequent professional performance (Bodowski et al., 2021; Roberts et al., 2019). In this scenario, teachers play the role of learning facilitator, favoring autonomous work and self-learning (Astudillo et al., 2017; Yanetsi et al., 2018). Advances in education have forced teachers to look for new quality learning experiences such as simulation, which also reduces the existing gap with clinical practice (Killam & Luctkar-Flude, 2021).

The literature shows evidence that the outcome of the learning process directly correlates to the intrinsic motivation shown by the student. Simulation-based education promotes this motivation during the learning process, through practical experiences in simulated contexts, bringing it closer to its authentic performance (Campos et al., 2020; Olive et al, 2018).

This learning method develops skills and qualities, stimulates reflective critical thinking, improves clinical judgment, decision-making processes, and provides confidence and self-efficacy to students, enabling them to address different clinical situations but in a safe environment (Killam & Luctkar-Flude, 2021; Zambrano et al., 2020; Jallad & Işık, 2022).

One of the advantages of simulation is to demonstrate the development of certain elements that constitute the competencies that allow the student to apply theoretical knowledge in clinical practice and thus interact with the patient in the real context. This becomes a powerful tool that systematically prepares them for their subsequent performance with a real patient (Foog et al, 2020).

New learning strategies such as simulation, used in the training of health students in areas such as medicine and nursing, and more recently in careers such as nutrition and dietetics, can provide efficiency and speed in learning. They can even contribute to the improvement of clinical activities that are developed. Because of this and the usefulness it has in clinical practice, it is important to understand the perception that students have on the use of clinical simulation during their training process (George & Trujillo, 2018), given the relevance it has in training nutrition and dietetics students. A questionnaire was designed, specifically a measurement instrument, which must be simple and affordable to be considered valid. There are various instruments to assess student satisfaction in relation to clinical simulation (Alconero-Camarero et al., 2016), however there is a lack of validated instruments to know the perception of nutrition students and diet for this is built It must also be unbiased and suitable for the problem under study, the dimensions must be clearly defined and must adequately reflect the concept being measured. For the instrument to be considered of good quality, it must be valid and reliable, and to ensure the quality of the instrument, a validation process with a group of experts is necessary (Luque-Vara et al., 2020; Contreras-Yáñez et al., 2019).

For this study, a questionnaire was developed to identify the perception of students on the simulation from 3 dimensions: 1. structure of the simulation, 2. learning, 3. feedback for learning. This questionnaire is a contribution to the students’ teaching-learning process and aims to contribute to both the academic training and the design and implementation of new instruments. It was designed by the researchers, and its development is part of a process of dialogue and ongoing feedback.

This study aims to design and validate a questionnaire through expert judgment to assess the perception of clinical simulation in nutrition and dietetics students.

Reliability analysis and questionnaire validity

The construct validity of the questionnaire was calculated through factor analysis using principal component extraction and Varimax rotation with Kaiser. Each variable was included in a single factor, according to their factor loading, by setting minimum saturation criteria of 0.50.

Kaiser–Meyer–Olkin sampling adequacy estimates (KMO; range 0–1) and Bartlett’s statistical significance (if its value is close to the unit and is significant p < 0.05, it indicates that the analysis with reduced variables is appropriate) were calculated. The reliability of the questionnaire was calculated by analyzing internal consistency, using Cronbach’s alpha, which should be interpreted as an indicator of the internal consistency of the items, because it is calculated from the covariance between them.

Quantitative data analysis

The strength and direction of a possible linear correlation between quantitative variables were calculated using Spearman’s Rho. A level of statistical significance of 0.05 was considered and all tests were two-sided. Statistical analysis of data was performed using SPSS v.22.0 software.

Research was carried out through the design of a questionnaire to measure the perception of nutrition and dietetics students on clinical simulation. This procedure was followed by the validity and reliability of the instrument (Aliaga Pacora et al., 2021). This process involved experts on the subject, as well as members of the sample group that the questionnaire was applied to.

Sample

The sample of this study is non-probabilistic and consisted of 22 experts with a minimum of 3 years of university teaching experience and 90 students (78 women and 12 men) in the nutrition and dietetics program who have had some previous experience in clinical simulation during their training process.

Questionnaire design

A questionnaire was designed to determine the perception of nutrition and dietetics students on clinical simulation. A questionnaire is an instrument composed of a list of standardized questions that make it possible to collect information from a group of individuals (D’Ancona, 1997).

The questionnaire was initially composed of 21 questions grouped into 3 dimensions: structure of the simulation (7 questions), learning (7 questions), feedback for learning (6 questions), on a Likert scale: Strongly disagree (1), Disagree (2), Neither agree nor disagree (3), Agree (4), Strongly agree (5). This type of scale was used because it has the ability to measure the intensity of an attitude, where the score per item makes it possible to specify the degree of presence of the study variables in research (George & Trujillo, 2018). This instrument was sent by e-mail to a group of 22 experts to analyze content validity. Categories and qualification indicators were established, such as sufficiency, clarity, coherence and relevance, and a Likert scale was used to assess the level of compliance of the different items, specifically: 1. does not meet the criterion / 2. low level / 3. moderate level / 4. high level. The final questionnaire was given in person to 90 students in the nutrition and dietetics program who have had some previous experience during their training process with clinical simulation.

Ethical considerations

The study was authorized by the ethics committee of the Universidad Católica de Temuco and the students who participated gave informed consent.

Reliability analysis and questionnaire validity

The first result corresponds to the revision conducted by the group of experts, who undertook a complete analysis of the instrument. Two questions were eliminated, an open-ended question was added, and grammatical changes were made. A new version of the questionnaire was structured around the same 3 dimensions, specifically dimension 1 (6 questions), dimension 2 (7 questions) and dimension 3 (5 questions), and an open-ended question was added. The new version was sent back to the experts for their feedback on the changes made. Kaiser–Meyer–Olkin sampling adequacy estimates (KMO = 0.857) and Bartlett’s statistical significance (p = 0.000) were calculated. Communalities analysis indicated that all items are above 0.5, and therefore all questions were accepted as valid to the questionnaire (Table 1).

Table 1

Communalities.
Items		Extraction
1.	The simulation is related to the contents developed in the subjects studied.	0.767
2.	The information previously provided in the clinical file is related to the assigned case.	0.747
3.	The information provided allowed me to put my performance into practice.	0.706
4.	The characterization of the patient favors the case to be simulated.	0.532
5.	I consider the time allotted to carry out the simulation adequate.	0.777
6.	The material and infrastructure resources used favor the development of the simulation.	0.429
7.	Working with simulation has allowed me to integrate the theoretical and practical contents in my performance.	0.740
8.	The simulation strategy allowed me to develop the learning results of the evaluated subject.	0.727
9.	The simulation has favored my clinical reasoning and decision-making.	0.808
10.	The simulation has favored effective communication with the user and/or accompanying family member.	0.768
11.	The simulation has allowed me to develop confidence and security in my performance.	0.711
12.	The simulation has allowed me to respect the cultural and social diversity of people.	0.785
13.	Simulation as a teaching method has favored my own learning.	0.743
14.	The teacher's feedback after the simulation has been carried out contributes to my learning.	0.808
15.	The simulated patient's feedback after the simulation has been carried out contributes to my learning.	0.779
16.	You would like to participate in the simulation again in other subjects.	0.656
17.	Simulation has been a motivating activity in my professional training process.	0.846
18.	The simulated cases are in accordance with the level of professional training in which I find myself.	0.575

The principal component analysis method was used to obtain five major components or factors with eigenvalues greater than 1, which account for 71.68% of the total variance explained, obtaining a percentage of explanation at appropriate acceptance levels (Table 2). These factors are classified as: Factor 1. Learning, Factor 2. Simulation structure, Factor 3. General features, Factor 4. Duration time, Factor 5. Feedback. Each item was included in a single factor, based on its factor loading, by establishing a minimum saturation criterion of 0.50. VARIMAX-based rotated factor solutions formed a well-defined structure without overlapping. Table 3 shows the scale items with their respective factor weights in each of the 5 factors.

Table 2

Total variance explained.
	Rotation sums of squared loadings
Component	Total	% of variance	% cumulative
1	5.150	28.6	28.6
2	2.555	14.2	42.8
3	2.188	12.2	55.0
4	1.527	8.5	63.4
5	1.483	8.2	71.7
These factors would be classified as:
Factor 1. Learning.
Factor 2. Simulation structure.
Factor 3. General features.
Factor 4. Duration time.
Factor 5. Feedback.

Table 3

Results of exploratory factor analysis and factorial saturation items after Varimax rotation with Kaiser normalization.
	Factor
	1	2	3	4	5
Simulation has been a motivating activity in my professional training process.	0.865	0.099	0.198	-0.003	0.224
The simulation has favored my clinical reasoning and decision-making.	0.816	0.326	0.131	0.133	-0.015
The simulation has favored effective communication with the user and/or accompanying family member.	0.815	-0.010	0.178	0.183	0.195
Simulation as a teaching method has favored my own learning.	0.797	0.158	0.239	0.141	0.080
The simulation strategy allowed me to develop the learning results of the evaluated subject.	0.757	0.290	0.202	0.145	0.092
Working with simulation has allowed me to integrate the theoretical and practical contents in my performance.	0.736	0.382	0.210	0.022	0.090
The simulation has allowed me to develop confidence and security in my performance.	0.659	0.119	0.389	0.163	-0.289
The simulation is related to the contents developed in the subjects studied.	0.041	0.850	0.065	-0.113	0.165
The information previously provided in the clinical file is related to the assigned case.	0.262	0.716	-0.045	0.394	0.089
The information provided allowed me to put my performance into practice.	0.316	0.633	0.411	0.174	-0.077
The characterization of the patient favors the case to be simulated.	0.314	0.613	0.116	-0.051	0.202
The simulation has allowed me to respect the cultural and social diversity of people.	0.233	0.051	0.816	-0.240	0.065
The simulated cases are in accordance with the level of professional training in which I find myself.	0.376	0.140	0.598	0.223	0.082
The material and infrastructure resources used favor the development of the simulation.	0.143	0.068	0.536	0.286	0.186
You would like to participate in the simulation again in other subjects.	0.463	0.216	0.513	0.342	-0.124
I consider the time allotted to carry out the simulation adequate.	0.252	0.008	0.117	0.835	0.056
The simulated patient's feedback after the simulation has been carried out contributes to my learning.	0.349	0.189	0.065	-0.142	0.773
The teacher's feedback after the simulation has been carried out contributes to my learning.	-0.063	0.219	0.159	0.430	0.739

A Cronbach’s alpha value of 0.913 was obtained to assess the internal consistency of the questionnaire. This value was not improved by eliminating some of the items, therefore all items were maintained. The item-total correlation values ranged from 0.52 to 0.73. 100% of the questions were answered (Table 4).

Table 4

Internal consistency of the scale and the 5 factors.
		α
Scale		0.913
Factor 1.	Learning.	0.931
Factor 2.	Simulation structure.	0.914
Factor 3.	General features.	0.917
Factor 4.	Duration time.	0.911
Factor 5.	Feedback.	0.908
As a result of the validation process a final questionnaire consisting of 18 items, closed questions Likert response scale, that determine five factors was obtained. The questionnaire has shown a good factorial structure, good predictive capacity and high internal consistency.

As a result of the validation process a final questionnaire was obtained, consisting of 18 items involving Likert scale closed-ended questions, which determine five factors. The questionnaire has shown a good factorial structure, good predictive capacity and high internal consistency.

Quantitative analysis

A total of 90 students participated from the Nutrition & Dietetic degree program. Of these, 86.67% were women and 13.33% were men, with an average age of 21.37 years. In terms of the questionnaire, a frequency analysis of the variables studied shows statistically significant results. To simplify the interpretation of the results, given the similarity between them, we have grouped the assessment items “strongly disagree” and “disagree” together, and have also grouped together “totally agree” and “agree” (Table 5). The frequency analysis shows significant results, and in the assessment, the “strongly agree” and “agree” responses are higher than 82% in the satisfaction degree, with the exception of item 15, which obtained 68.9% satisfaction.

Table 5

Satisfaction between simulation groups.
Item	Strongly disagree/ In disagreement	Neutral	Totally agree/ In agreement
The simulation is related to the contents developed in the subjects studied.	17.8%	0.0%	82.2%
The information previously provided in the clinical file is related to the assigned case.	1.1%	7.8%	91.1%
The information provided allowed me to put my performance into practice.	4.4%	5.6%	90.0%
The characterization of the patient favors the case to be simulated.	7.8%	12.2%	80.0%
I consider the time allotted to carry out the simulation adequate.	15.6%	16.7%	67.8%
The material and infrastructure resources used favor the development of the simulation.	6.7%	16.7%	76.7%
Working with simulation has allowed me to integrate the theoretical and practical contents in my performance.	2.2%	9.0%	88.8%
The simulation strategy allowed me to develop the learning results of the evaluated subject.	3.3%	12.2%	84.4%
The simulation has favored my clinical reasoning and decision-making.	3.3%	7.8%	88.9%
The simulation has favored effective communication with the user and/or accompanying family member.	2.2%	13.3%	84.4%
The simulation has allowed me to develop confidence and security in my performance.	6.7%	7.8%	85.6%
The simulation has allowed me to respect the cultural and social diversity of people.	3.3%	5.6%	91.1%
Simulation as a teaching method has favored my own learning.	3.3%	3.3%	93.3%
The teacher's feedback after the simulation has been carried out contributes to my learning.	1.1%	8.9%	90.0%
The simulated patient's feedback after the simulation has been carried out contributes to my learning.	7.8%	23.3%	68.9%
You would like to participate in the simulation again in other subjects.	3.3%	5.6%	91.1%
Simulation has been a motivating activity in my professional training process.	4.4%	7.8%	87.8%
The simulated cases are in accordance with the level of professional training in which I find myself.	3.3%	4.4%	92.2%

The objective of this research was to design and validate a questionnaire through expert judgment to assess the perception of clinical simulation in nutrition and dietetics students. This takes into consideration the importance of clinical simulation as a teaching and learning strategy in the training of health science professionals.

The final questionnaire presents a good factorial structure, good predictive ability and high internal consistency, obtaining similar results to other studies with adequate psychometric tests (Alconero et al. 2016; Franklin et al., 2014), making it a viable and reliable tool that makes it possible to identify the perception of students on clinical simulation as a teaching and learning strategy (George & Trujillo, 2018). The results suggest that simulation is beneficial for student learning, which is consistent with what has been stated in other studies (Borg Sapiano et al., 2018).

Content validation was also performed by 22 experts, through an evaluative judgment (Delphi technique) that considered the sufficiency, clarity, coherence and relevance of the items in the three dimensions, which allowed for adjustments in the number of items and correction of grammatical aspects, obtaining a reliable consensus of the final version of the instrument (Luque-Vara et al., 2020; Contreras-Yáñez et al., 2019). The Delphi technique proved to be appropriate and advantageous since it allows for the participation of professional experts in the topic researched, who contributed towards the analysis, coherence, clarity and relevance of the proposed items (Gonzalez et al., 2021; Lopez, 2018).

In recent years, the field of education has witnessed a significant shift toward innovative teaching methodologies that engage students actively and enhance their learning experiences. One such approach gaining prominence is the use of simulations as a strategy to facilitate student training. Simulations offer a unique learning environment that replicates real-world scenarios, allowing students to apply theoretical knowledge in practical contexts. This study designed and validated a questionnaire through expert judgment to assess the perception of clinical simulation in nutrition and dietetics students, trying to explore the most relevant aspects of the simulation strategy and its contributions to student training.

In relation to the study objective, the results show that participants declare a high degree of satisfaction with the clinical simulation strategy, given that the frequency analysis of the variables applied to the questionnaire reveals statistically significant results where it is evident that the items “totally agree” and “agree” represent greater than 80%, making it feasible for the instrument to be used again (Espinoza et al., 2022).

In particular, question 13 was more widely accepted among all, it is relevant for the construction of the questionnaire, reflecting the value that students assign to their own learning from theoretical-practical knowledge, essential for the acquisition of knowledge and professional training.

In this context, simulations promote active learning by encouraging students to actively participate and make decisions within the simulated environment. Ours findings are in line with Freeman et al. (2014) who indicates that active learning enhances student engagement, motivation, and retention of knowledge. By immersing students in realistic scenarios, simulations stimulate critical thinking, problem-solving, and decision-making skills. Learners become active agents in their own learning process, enabling them to develop a deeper understanding of complex concepts.

On the other hand, simulations facilitate experiential learning, which emphasizes the acquisition of knowledge through direct experience. As students engage in simulated activities, they gain practical skills that can be transferred to real-world situations. This transfer of knowledge is supported by the theory of situated cognition, which suggests that learning is best achieved when the context of learning closely resembles the context of application (Brown, Collins, & Duguid, 1989). Simulations bridge the gap between theory and practice, preparing students for future professional challenges. All this is particular relevant in health area because simulations provide a safe and risk-free environment for students to explore and experiment without fear of real-life consequences. Errors can have severe implications, simulations offer a controlled setting for students to practice and refine their skills. Research demonstrates that simulation-based training can improve performance outcomes and reduce errors (Issenberg et al., 2011). By allowing students to make mistakes and learn from them, simulations foster a growth mindset and promote self-confidence.

In our opinion, others relevant aspect of simulation are the collaborative learning and communication skills involved. Students appreciate to work in teams, to solve problems or achieve common goals. This collaborative aspect encourages the development of teamwork, communication, and interpersonal skills. Students learn to effectively communicate, delegate tasks, and negotiate with others, mirroring real-life professional environments. Collaboration within simulations promotes a deeper understanding of diverse perspectives, enhances empathy, and improves decision-making through collective intelligence advancing important aspects of working life in interdisciplinary health teams.

In terms of customizability and flexibility, simulations offer a high degree of customizability, allowing instructors to tailor learning experiences to meet specific learning objectives. Educators can modify parameters, scenarios, and variables within the simulation to align with desired learning outcomes. Additionally, simulations provide flexibility in terms of time and location, enabling students to access the learning experience at their convenience. This flexibility accommodates different learning styles and promotes student autonomy.

The simulation strategy is part of new learning styles that contribute to student training. The questionnaire assessing the perception of nutrition and dietetics students has shown internal validity and reliability, demonstrating that the instrument is a valuable tool for the teaching-learning process. The existence of a validated and reliable instrument for the collection of information is recognized as a strength. It is a supporting tool that contributes to the ongoing improvement of learning. A limitation to consider is that it was applied to students from only one institution of higher education.

We can conclude that the simulation strategy presents a valuable approach to student training, fostering active learning, experiential learning, and the development of critical skills. By providing realistic and risk-free environments, simulations empower students to apply theoretical knowledge, make informed decisions, and develop proficiency in various domains. The collaborative nature of simulations also enhances communication and teamwork skills. With its customizability and flexibility

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Author Contribution

V.E.: Conceptualization; Project administration; Visualization; Original draft; Writing; L.M.: Data curation; Formal analysis; Investigation; Methodology; S.V.: Funding acquisition; Resources; Supervision; Validation; Writing - review & editing.

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No competing interests reported.

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Questionnaire design and validation: perception of clinical simulation in nutrition and dietetics students

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Abstract

Background:

Objective:

Methods

Results

Conclusions

Introduction

Material and methods

Reliability analysis and questionnaire validity

Quantitative data analysis

Sample

Questionnaire design

Ethical considerations

Results

Reliability analysis and questionnaire validity

Quantitative analysis

Discussion

Conclusion

Declarations

Data availability

Author Contribution

References

Additional Declarations

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