Abstract
Background
The rapid growth of technology forced enormous changes in the provision of healthcare services. Different strategies are used to keep nurses up to date with rapid changes in health systems. Microlearning is one of the new methods of teaching professional skills to health workers. This method is effective in care settings that have many limitations in terms of time and place. However, it is very important to test the acceptability of this method among nurses before practical measures are taken for its widespread use. This study aimed to determine nurses’ acceptance rate of quick response code as a microlearning tool in workplace.
Method
This is a cross-sectional study was conducted in medical and surgical wards in hospitals affiliated to Guilan University of Medical Sciences. 185 nurses participated in the study. A number of selected medical devices were labeled with quick response codes containing educational content. The eligible nurses were instructed how to use the QR codes. After two months, they were asked to complete a questionnaire adapted from the technology acceptance model 3. SPSS 21 software was used to analyze the data.
Results
166 nurses and 19 head nurses with mean age of 34.26 ± 8.17 years and mean work experience of 10.46 ± 7.64 years completed the questionnaires. Most participants were female, married, with a bachelor’s degree, worked on rotating shifts, in medical wards. The findings showed that the acceptance of the quick response code as a learning tool was at a moderate level (M = 66.1, SD = 16.6). Statistically, there was no significant relationship between nurses’ demographic characteristics and the total acceptance rate (P > 0.05). However, the analyses at the multivariate level, using multiple linear regression, showed a significant superiority of the total acceptance score in head nurses compared to nurses (b = 7.97, P = 0.047) and in nurses who had previous experience of using quick response codes, compared to colleagues without such experience (b = 5.18, P = 0.036). Based on the coefficient of determination, only 6.1% of the changes in the total acceptance score of quick response codes of nurses are explained by their personal-occupational characteristics (R2 = 0.061).
Conclusions
The provision of QR code requirements such as necessary infrastructure and training by the health authorities could increase the acceptance of this tool as a microlearning measure.
Keywords: Microlearning, Quick response code, Medical equipment, Technology acceptance model, Nurses
Background
In recent years, the rapid and significant growth of technology has transformed all areas of human life, including medical devices and equipment [1] leading to the emergence of complex medical devices in the fields of diagnosis, therapy and rehabilitation [2, 3]. In this regard, healthcare services providers, specifically nurses, the largest population of healthcare providers, are forced to make changes in line with the use of new technologies in their profession [1]. The World Health Organization has stated that development in the field of health relies on proper planning to manage medical devices safely and in a compatible manner with the clinical environment [4]. Therefore, nurses must be able to use medical devices correctly to increase the quality of care for patients and maintain their safety [5].
Despite the impressive impact of the quality of nursing services on the overall quality of healthcare, some studies show that nurses do not have good practical skills in using medical equipments [3, 6]. According to the study by Park et al., nurses relate functional defects in the use of devices to a lack of knowledge of how to use them correctly [7]. Furthermore, nurses found it necessary to constantly receive educational information about the devices used in the clinical environment [5]. In this kind of circumstances, due to the limitations in the use of conventional education methods such as the passive reception of information by the learner [8], and the lack of time and space in the clinical environment [9], nurses should undergo continuous learning using technology to improve their knowledge and performance [9, 10]. The setting in which this study was conducted is university hospitals where use advanced devices and equipment for patient care and whose staff must be regularly trained in the use of these devices. In their experiences and observations, the researchers of this study have found that many training methods used for employees lack the necessary efficiency due to time and space constraints. On the other hand, access to new technologies such as smartphones and knowledge of how to use these devices is fortunately very good among employees. These are the reasons that encourage the researchers to conduct this study.
In this context, various methods may have been invented and introduced to make learning in the workplace more efficient. Microlearning as one of these methods has received a lot of attention in recent years [11]. Taylor defined it as “learning from content accessed in short bursts, content which is relevant to the individual, and repeated over time to ensure retention and build conceptual understanding” [12], it also is focused on meet of learners immediate needs [13]. Digital microlearning is a method of delivering short, focused learning modules through digital platforms such as mobile apps, online courses, or videos. This approach allows learners to engage with bite-sized content that is easy to consume, often incorporating elements like quizzes, interactive exercises, and videos to reinforce learning [14]. There are many tools available to execute digital microlearning including QR codes.
QR codes are commonly used in marketing and advertising to provide easy access to websites, promotions, and discounts. They can also be used for tracking inventory, making payments, and sharing information quickly and efficiently. Quick Response (QR) codes are popular because they can store a lot of information in a small space and can be easily scanned using a mobile device. They are versatile and can be customized to fit different needs and branding requirements [15]. Overall, QR codes are a convenient and effective tool for sharing information and engaging with customers.
The use of QR codes is one of the creative methods of microlearning using technology that makes information available to everyone just-in-time [16, 17]. However, the success of the widespread use of a new technology depends on its acceptance by the target population [18]. Therefore, the present study aimed to determine the acceptance status among medical and surgical wards nurses of the QR code mediated learning program on proper medical device usage.
Although the use of smartphones may no longer be considered a technological tool for learning, it should be considered that it is a mainstream and ubiquitous way of learning [19]. In this regard, many people are developing creative learning experiences using smartphones, one of the emerging technologies in this field is QR codes [17]. QR codes, two-dimensional matrix codes, were first introduced by Denso wave in Japan to store information in the automotive industry, and then due to the expansion of the use of smartphones, they were used in various fields such as manufacturing, military industries, E-commerce, media, tourism, and authentication [20]. The main value of these codes is the ease and speed of providing information in such a way that to access the Uniform Resource Locator (URL), Global Positioning System (GPS), contact information, postal address, or payment instructions, you only need to scan with your smartphone [21]. The ability to use QR codes at any time and place makes it a suitable technology for providing educational information for nurses in clinical environments [16]. The study by Del Rosario-Raymundo determined that QR codes are a useful, acceptable, and usable tool whose potential for continuous learning in the clinical setting has been underappreciated [22]. However, it is not possible to use new technology in any field, including continuous learning, without considering the users’ point of view, and its acceptance or rejection will have a profound effect on learning [18].
Acceptance is a function in users of the desired technology that means a positive decision to use innovative technology. Due to the importance of the topic, many theories and models have been created to examine technology acceptance [23]. The technology acceptance model (TAM), proposed for the first time by Fred Davis in 1985, is one of the most widely used models in this field [24]. The main concepts of TAM are determined based on perceived usefulness (PU) and perceived ease of use (PEOU). PU refers to the prospective subjective view of the user regarding the impact of technology on improving job performance, and PEOU refers to the potential expectation of the user regarding the effortless use of the desired technology [25]. Over the years and in trying to evolve TAM, researchers succeeded in presenting TAM3 by combining four determinants for PU and PEOU consisting of individual differences, technology characteristics, social impact, and facilitating conditions [26].
Considering that TAM is a suitable theoretical tool for understanding the acceptance of technology users [7], and it is necessary to measure its acceptance for the development of successful QR codes, this study aimed to determine nurses’ acceptance rate of QR code as a microlearning tool in workplace and deals with the following questions:
What is the status of acceptance of QR codes on proper medical device usage according to different areas of TAM3?
Is there a significant relationship between the total acceptance score and the demographic characteristics of nurses?
Methods
Study design, setting and sampling
This is a quasi-experimental study was conducted in medical and surgical wards in hospitals affiliated to Guilan University of Medical Sciences. In these hospitals provide general and special health care services to public using many regular and advanced equipment. Subjects were enrolled through convenience sampling method.
Participants
In the present study, the research population was all the nurses present in 27 medical or surgical wards. This study utilized the convenience sampling method. To determine the sample size according to the rule of linear regression analysis, 20 subjects were for each independent variable [27]. For this study with nine independent variables, a sample size of 180 nurses, which corresponds to 20 observations per variable, indicating that sample size is adequate for performing regression analysis. However, this study was performed with participation of 185 nurses, which exceeds the guideline for regression analysis.
Eligibility criteria
Participated nurses should have all below criteria:
Requirement of at least a bachelor’s degree in nursing.
Employment in medical and surgical departments.
Having a smartphone with internet access.
Willingness to participate in the study.
Process
In first step the study focused on developing educational content for the proper use of commonly used medical devices and equipment in internal and surgical departments at Guilan university of medical sciences in Iran. The process involved identifying these devices, creating educational materials using scientific sources and catalogs, and obtaining approval from approprate faculty members for the content, with necessary amendments made thereafter.
Then a series of QR codes were developed to guide users to the proposed educational resources. The development followed the ADDIE model in five phases: Analysis, Design, Development, Implementation and Evaluation [28].
Analysis
In the analysis phase, our investigation focused on assessing the educational requirements of nurses regarding the proper utilization of medical devices. In this regard, in addition to using experiences and reviewing the literature, a council was formed, consisting of the research team and five members of the nursing faculty. After several meetings, it was decided to develop and evaluate QR codes for ten devices consisting of electronic thermometer, blood glucose meter, pulse oximeter, infusion pump, syringe pump, suction device (central and portable), central oxygen device, electrocardiograph, electroshock device and monitoring system.
Design
In the design phase, the research team discussed the strategy of the implementation and evaluation. Collecting the necessary content for QR codes was done through the manuals for each device. It was decided that the content used in QR codes will be placed on a website and its URL will be pasted on the devices or placed next to them in the form of a card after being converted into a QR code. Also, it was decided to prepare posters and stick them in the clinical environment to learn how QR code works. The use of these QR codes is voluntary and nurses were given two months to use them.
Development
In the development phase, designing and building a website, preparing stickers/cards containing QR code and preparing questionnaires were done. The content related to the correct use of the ten mentioned devices was written, consisting of the following sections: introduction, components, settings, how to use, alarms and how to fix them, maintenance, and cleaning. Educational content was prepared in the form of text, photos, and videos and uploaded on our website. Finally, more than 1200 stickers/cards containing QR code were printed and ready to use.
Implementation
In the implementation phase, QR codes prepared in the form of stickers and cards were ready for use in 27 wards and five selected university hospitals in Rasht, Iran. After pasting the QR codes in each ward, training on how to use these codes was given to head nurses or their substitutes, and guide posters were also placed in the nursing station and treatment room.
Evaluation
In the evaluation phase, after two months of QR codes being placed in the clinical environment, the acceptance status of QR codes was checked by the questionnaire of demographic characteristics and the tool adapted from the technology acceptance model 3 [26].
Survey instrument measures
Data collection in this study was done using the Demographic Profile Questionnaire and tools adapted from the Technology Acceptance Model 3 [26].
Demographic information
The demographic characteristics questionnaire consisted of age, sex, marital status, level of education, job position, work experience, type of ward, type of work shift, and previous QR code use.
Technology acceptance questionnaire
The researchers made a QR codes acceptance score tool by adapting the technology acceptance model 3 [26]. Among the constructs proposed in the technology acceptance model 3, thirteen constructs were used, including perceived usefulness (4 items), perceived ease of use (4 items), perceptions of external control (4 items), computer playfulness (2 items), computer anxiety (3 items), perceived enjoyment (3 items), subjective norm (1 item), voluntariness (3 items), job relevance (3 items), output quality (2 items), results demonstrability (4 items), behavioral intention (3 items), and actual use (1 item). All 37 items were scored using a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree). In the actual use item, nurses were asked to state their use of QR codes between 1 and 7 times. The scores were obtained from all the structures and subsequently the total acceptance score was converted into a range of 0 to 100, and the acceptance status was divided into three levels: poor (0 to 50), moderate (51 to 75), and desirable (76 to 100). The content validity of the tool was done using the opinions of nine faculty members. The first draft of questionnaire with 47 items was sent to the panel of experts. All items with a content validity ratio (CVR) lower than 0.75 and a content validity index (CVI) lower than 0.78 were removed. In the final questionnaire with 37 items, S-CVI/Ave was determined as 0.982. Reliability was calculated by participation of 31 medical surgical nurses, using Cronbach’s alpha coefficient and the value was 0.949.
Data collection
The process of data collection was executed in April to May 2023 and the questionnaires were provided to the participants in printed formats. Normally, this questionnaire was completed by nurses in about 15 min.
Data analysis
In this study, IBM SPSS 21 was used for data analysis. In calculating the demographic characteristics of nurses, the mean and standard deviation were used for quantitative variables, and the qualitative variables were reported as frequencies and percentages. Kolmogorov-Smirnov and Shapiro-Wilk tests were performed to check the assumption of normality. In univariate analysis, an independent t-test and Pearson’s correlation coefficient were used to investigate the relationship between the total acceptance score and demographic characteristics. Independent t-test was used to detect relationship of dichotomous variables including sex, marital status, level of education, job position, work shift, ward, and previous QR code use with subjects’ total acceptance score. Also, pearson’s correlation coefficient was used to investigate the correlation of age and work experience of participants with their total acceptance score. In the multivariate analysis, multiple linear regression was used to determine the individual-occupational factors related to the total acceptance score. The level of significance in this study was considered 0.05.
Results
Participant characteristics
As presented in Table 1, the 185 subjects included in the study consisted of 168 females (90.81%), 115 married (62.16%), 13 master of science in nursing (7.03%), and 19 head nurses (10.27%). The average age and work experience of all participants were 34.35 (SD = 8.17) years and 10.46 (SD = 7.64) years respectively. The majority of participants (56.22%) were from medical wards and their work shift were rotating (77.30%). Among the participants, only 77 (41.62%) had previous experience of using QR codes.
Table 1.
Demographic characteristics of nurses
| Variables | Mean ± SD or n (%) | |
|---|---|---|
| Age, years | 34.35 ± 8.17 | |
| Work experience, years | 10.46 ± 7.64 | |
| Sex | Male | 17 (9.19) |
| Female | 168 (90.81) | |
| Marital status | Single | 70 (37.84) |
| Married | 115 (62.16) | |
| Level of education | Bachelor | 172 (92.97) |
| Master | 13 (7.03) | |
| Job position | Nurse | 166 (89.72) |
| Head nurse | 19 (10.28) | |
| Work shift | Rotation | 143 (77.29) |
| Fixed | 42 (22.71) | |
| Ward | Medical | 104 (56.21) |
| Surgical | 81 (43.79) | |
| Previous QR code use | Yes | 77 (41.62) |
| No | 108 (57.38) | |
Descriptive data
The mean and standard deviation of the total acceptance score of QR codes and its constructs are presented in Table 2. The mean total score of QR codes acceptance among nurses was 66.08 (SD = 16.62), which is at a moderate level. The highest mean acceptance score obtained according to constructs belonged to perceived ease of use (M = 72.11; SD = 21.20), perceived usefulness (M = 69.77; SD = 20.14), and behavioral intention (M = 68.82; SD = 22.94), respectively. Furthermore, the constructs of perceptions of external control (M = 64.75; SD = 20.02), result demonstrability (M = 62.77; SD = 18.96), and actual use (M = 26.39; SD = 30.07) obtained the lowest acceptance mean score. The scores obtained from all constructs were at a moderate level, except for the structure of actual use, which was at a poor level.
Table 2.
QR Code acceptance score of nurses
| Constructs | Score (Mean ± SD) |
|---|---|
| Perceived usefulness (PU) | 69.77 ± 20.14 |
| Perceived ease of use (PEOU) | 72.11 ± 21.20 |
| Perceptions of external control (PEC) | 64.75 ± 20.02 |
| Computer playfulness (CPLAY) | 68.42 ± 22.10 |
| Computer anxiety (CANX) | 68.01 ± 23.10 |
| Perceived enjoyment (ENJ) | 65.34 ± 21.53 |
| Subjective norm (SN) | 58.46 ± 27.53 |
| Voluntariness (VOL) | 66.57 ± 19.91 |
| Job relevance (REL) | 68.79 ± 22.15 |
| Output quality (OUT) | 66.48 ± 22.26 |
| Result demonstrability (RES) | 62.77 ± 18.96 |
| Behavioral intention (BI) | 68.82 ± 22.94 |
| Actual use (USE) | 26.39 ± 30.07 |
| Total acceptance | 66.08 ± 16.62 |
Note The possible range for all constructs was 0 to 100
Univariate relationship between total acceptance score and nurses’ characteristics
As shown in Table 3, Pearson’s correlation coefficient and independent t-test were used in conducting univariate analysis to determine the relationship between the total acceptance score and nurses’ characteristics. None of the individual and job variables had a significant relationship with the total acceptance score (p > 0.05).
Table 3.
Univariate relationship between demographic characteristics of nurses and their total acceptance
| Variables | Total acceptance score | ||||
|---|---|---|---|---|---|
| Mean ± SD | r or t (df) | 95% CI | P Value | ||
| Age | ▬ | 0.08 | ▬ | 0.233 | |
| Work experience | ▬ | 0.05 | ▬ | 0.468 | |
| Sex | Male | 60.65 ± 14.08 | -1.41 (183) | -14.30–2.34 | 0.158 |
| Female | 66.63 ± 16.79 | ||||
| Marital status | Single | 64.69 ± 15.65 | -0.88 (183) | -7.20–2.74 | 0.378 |
| married | 66.92 ± 17.19 | ||||
| Level of education | Bachelor | 66.10 ± 16.62 | 0.18 (183) | -9.11–9.79 | 0.943 |
| Master | 65.76 ± 17.23 | ||||
| Job position | Nurse | 65.28 ± 16.65 | -1.93 (183) | -15.61–0.15 | 0.055 |
| Head nurse | 73.02 ± 15.02 | ||||
| Work shift | Rotation | 65.54 ± 16.12 | 0.81 (183) | -3.38–8.14 | 0.416 |
| Fixed | 67.92 ± 18.30 | ||||
| Ward | Medical | 67.61 ± 15.43 | 1.42 (183) | -1.34–8.34 | 0.156 |
| Surgical | 64.11 ± 17.94 | ||||
| Previous QR code use | Yes | 68.48 ± 15.26 | -1.66 (183) | -8.98–0.75 | 0.097 |
| No | 64.36 ± 17.39 | ||||
Note: The possible range for total acceptance score was 0 to 100
r: Pearson correlation coefficient
t: Independent T-test
Multivariate relationship between total acceptance score and nurses’ characteristics
As shown in Table 4, multiple linear regression was used in conducting multivariate analysis to determine the relationship between the total acceptance score and nurses’ characteristics. To perform multivariate analysis, the variables that had a p-value < 0.2 in the univariate analysis were entered into the model, including sex, job position, ward, and previous QR code use. According to the regression coefficients, the total score of QR codes acceptance in head nurses was significantly higher than in nurses (b = 7.97; p = 0.047). In addition, participants who had previous use of QR codes had a higher score of total QR codes acceptance than those without previous experience (b = 5.18; p = 0.036). Overall, the coefficient of determination indicated that 6.1% of the variance in the total score of QR codes acceptance among nurses was explained by their personal and occupational characteristics (R2 = 0.061).
Table 4.
Multivariate relationship between demographic characteristics of nurses and their total acceptance
| Variables | Unstandardized coefficients (b) | Standard error | Standardized coefficients (β) | t | P |
|---|---|---|---|---|---|
| Sex (Female to Male) | 5.71 | 4.20 | 0.09 | 1.36 | 0.176 |
| Job position (Head nurse to Nurse) | 7.97 | 3.98 | 0.14 | 2.00 | 0.047 |
| Ward (Surgical to Medical) | -3.51 | 2.46 | -0.10 | -1.45 | 0.149 |
| Previous QR code use (Yes to No) | 5.18 | 2.46 | 0.15 | 2.11 | 0.036 |
Discussion
This study developed QR codes on proper medical device usage and examined its acceptance status among nurses in medical and surgical wards. In this research, the results determined that the acceptance of QR codes among nurses is at a moderate level. Among the acceptance constructs, only actual use was at a poor level, while the other constructs were at a moderate level. Despite identifying no significant relationship in univariate analysis between nurses’ characteristics and acceptance of QR codes, multivariate analysis indicated a significant superiority of the obtained acceptance score based on previous QR code use and job position.
The successful integration of learning with a useful technology with various advantages requires favorable acceptance in the target community [18]. In confirming the benefits of using QR as a method for teaching or learning, previous studies had promising results. The study of Liu et al. showed that providing educational content through QR codes has improved the ability to use neurosurgery equipment nurses [29]. Also, in the study of Park et al., it was found that the development of an educational program based on QR codes has increased the competence of recovery and operative room nurses in the use of medical equipment [7]. The findings of Habibzadeh et al. confirmed the effectiveness of this method of providing educational content on the grades of medical and emergency residents [30]. Furthermore, in the study of Traser et al., it was found that QR codes are successful in teaching anatomy and the majority of students considered this method more suitable than traditional methods [31]. In this kind of circumstances, due to not achieving the desired level of QR codes acceptance in the present study, it is imperative for the managers of nursing education to identify and remove the hinders impeding each of the structures of the acceptance by making appropriate decisions so that the total result will also increase.
In the present study, it was found that the scores obtained from the two constructs of perceived usefulness and perceived ease of use are at a moderate level. Few studies in the past pointed to the usefulness and ease of using QR codes in the fields of medication error prevention [32] and pharmacology education [16]. Perhaps as some of the devices that had been included in the educational content of the QR codes are not available in all medical and surgical ward, these nurses may have no much desire to learn how to use them, and this explain the moderate level of these constructs. Therefore, considering that perceived usefulness and ease of use are two important constructs of technology acceptance [33, 34] and have a direct role in determining behavioral intention [26], it is recommended for future studies to conduct a similar research with the participation of nurses from all wards.
The results of the present study showed that the scores of the behavioral tendency construct were not successful in achieving the desired level. Previous studies in this field confirmed that subjects have a intention to use QR codes and want to expand their use [16, 17]. Since the behavioral intention to use a technology is directly related to its actual use [26], it needs to be given more attention in order to achieve the desired overall acceptance. In order to maximize the behavioral intention of nurses, it is suggested to the policymakers to decide on granting the necessary resources. Facilitating the conditions of using new technology and perceived support from the organization can increase the intention to use.
QR codes can be used in many areas of learning [35]. However, the results of this research showed that the actual use of QR codes on proper medical device usage was at a poor level. In the professions related to the provision of healthcare services, the efficiency of new technology does not happen without organizational support and investment [36]. Organizations will be able to promote intention by allocating resources and practical support, such as involving people in the development process of the desired technology and making it easier to use [33]. However, the use of new technology in work environments is always associated with initial resistance to its use, which can be caused by a lack of trust in it. It is necessary to solve this problem by making a special policy to familiarize talented people with its practical benefits.
Being at a moderate level in any of the acceptance constructs can be caused by reasons that need to be addressed. For example, the subjective norm is influenced by the feeling of support from the respective organization [26], and the job relevance decreases with individuals’ ignorance about the benefits of new technology in the workplace [37]. The output quality will increase in line with the improvement of the quality of the received content by using the desired technology. In line with this goal, needs assessment studies can be used in the target community. The existing conditions in the clinical environment minimize the possibility of transfer experience regarding the use of QR codes, and subsequently, the undesired result demonstrability construct is an expected outcome. The compatibility of new technology with existing facilities in the environment, uncertainty about security in connecting to the network, temperamental characteristics of learners, pleasant feelings during use, and voluntary participation respectively affect the constructs of perceptions of external control, computer anxiety, computer playfulness, perceived enjoyment, and voluntariness.
The present study’s results have shown no significant relationship between nurses’ characteristics and the adoption of QR codes. Contrary to these results, the study of Song et al. indicated a significant relationship between demographic characteristics and acceptance of QR codes in the prevention of medication errors [32]. The conflict can be caused by the scope of using QR codes and the differences in work policies. However, QR codes acceptance scores were significantly higher in head nurses than nurses, which could be due to their less participation in clinical work. Also, QR codes acceptance scores were higher in people who had previous QR codes use. Previous studies support this finding and believe that increasing the use of technology by promoting the perception of its usefulness and ease of use affects overall acceptance [7, 32, 38]. In such a situation, head nurses can increase acceptance among nurses by sharing their positive experiences regarding the use of QR codes. Furthermore, future research with a longitudinal method can investigate the role of frequency of use on acceptance.
Limitations
This study had several limitations. The ability and knowledge of nurses regarding the proper use of devices is different, which affects their intention to use QR codes, which was not investigated in our study. Also convenience sampling and using self-reported questionnaire may affect the results and limit the external and internal validity of this study.
Conclusions
The results of the present study indicate that gaining favorable acceptance towards the use of new technology in learning is a result of factors such as perceived usefulness, perceived ease of use, and job relevance, along with paying attention to subjective norms, result demonstrability, and Perceptions of External Control. To promote the acceptance and the subsequent increase in the amount of real use, the necessary investigations should be done regarding the obstacles and their removal. By transferring their more successful experience and applying appropriate policies, head nurses will play a significant role in creating desire and enthusiasm for using new technologies and improve continuing education in medical disciplines. It should be noted that increasing the use of novel technology has a significant impact on the acceptance of its use and can lead to the expansion of the use of such methods. In current era of rapid changes in medical sciences, time constraints and high workload, adoption of this technology as a microlearning tool for medical students and staff learning can improve the efficacy of educational efforts.
Acknowledgements
The authors gratefully acknowledge the nurses who participated in this study.
Author contributions
A.M.: Conceptualization, Methodology, Software, Validation, investigation, Resources, Data curation, Writing-Original draft. R.T.: Conceptualization, Methodology, Validation, Writing-Review & Editing, Supervision, Project administration. S.M.: Methodology, Formal analysis, Data curation. M.S.S.: Conceptualization, Writing-Review & Editing.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Data availability
Data that support the findings of this study are available from the corresponding author upon request.
Declarations
Ethics approval and consent to participate
This study adhered to the ethical principles for medical research involving human subjects, as outlined in the Declaration of Helsinki. Ethics approval (IR.GUMS.REC.1401.318) was obtained from the Research Ethics Committee of Guilan University of Medical Sciences and Health Services. Informed consent was obtained from all participants prior to data collection. To obtain informed consent, the principal investigator explained the general purpose and method of the study to the nurses and handed them the questionnaire after they signed the informed consent form.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data that support the findings of this study are available from the corresponding author upon request.