Introduction
Cardiovascular diseases, especially arrhythmias, are among the leading and most challenging causes of death worldwide, affecting millions of people annually [1, 2]. The correct and timely management of cardiovascular emergencies requires high levels of knowledge and skills in the pre-hospital care team [3–5]. In this regard, emergency medical technicians (EMTs), as clinical first responders, play an important role in the early detection, accurate assessment, and implementation of correct treatment protocols for cardiac arrhythmias [6].
Their ability to make rapid decisions and take effective actions directly impacts the clinical outcome of patients and can make the difference between life and death [7–9]. Despite this serious responsibility, continuous education and continuous updating of clinical knowledge and skills in a rapidly evolving field have always faced numerous obstacles [10, 11].
The increasing volume of medical information, lack of time, geographical constraints, access to experienced professors, and the need to constantly update knowledge in high-pressure work environments are among the main challenges in continuing education programs [12]. Conventional training methods, such as long lectures and intensive workshops, are often unable to fully meet these needs due to their lack of flexibility, insufficient adaptation to individual needs, and varying effectiveness in learning and maintaining knowledge in the long term [13]. This gap between training needs and the effectiveness of current methods highlights the need for new, flexible, and efficient training approaches that can enhance staff’s self-efficacy in addition to improving knowledge.
In recent years, advances in educational technologies have expanded opportunities for strengthening healthcare professionals’ competencies [14].
Among these, microlearning—due to its concise, accessible, and learner-friendly design—has gained growing attention as a modern paradigm [15–17].
Microlearning, as a contemporary educational approach, aligns closely with the principles of cognitive load theory (CLT) It involves delivering content in small, manageable segments, which is particularly effective in minimizing cognitive overload, a key concern in CLT. Over the years, CLT has expanded to incorporate various dimensions of learning [17]. Sweller emphasized the integration of technological advancements with CLT principles to enhance learning efficiency [18].
Overall, the evolution of CLT and its integration with microlearning modules represent a significant advancement in educational methodologies. By acknowledging and adapting to the limitations of human cognitive processing, these approaches offer more effective and efficient learning experiences [17].
By breaking complex topics into short modules (3–10 min) [18] and applying spaced repetition, it reduces cognitive load and enhances long-term retention and active recall [19]. Evidence shows its effectiveness in improving knowledge, skills, and self-efficacy across medical and nursing education [20–26], making it a practical solution for EMTs with limited time who need rapid workplace-based learning [16].
In addition to microlearning, webinars have also rapidly become popular in medical education as an online educational platform due to their ability to reach a wide audience, provide interactive content remotely, and allow for live discussion and Q&A with experienced professors. They enable the updating of specialized information and simultaneous interaction, and can serve as an effective tool for educating large groups of specialists [21, 27]. The literature has also confirmed the effectiveness of webinars in educating nurses and medical students [27].
However, beyond increasing theoretical knowledge, the enhancement of self-efficacy (i.e., an individual’s belief in their ability to perform a given task successfully) is a critical and determining factor in clinical performance, especially in stressful emergency situations [28–30]. An EMT with high self-efficacy makes decisions with greater confidence when faced with complex arrhythmias and performs the necessary actions with greater certainty and precision [31–33]. High self-efficacy can help reduce job stress and increase resilience in stressful environments [34, 35].
However, comparing the effectiveness of modern educational methods, especially microlearning and webinars, on this important psycho-cognitive dimension in EMTs, and examining the sustainability of their effects over time, still requires more detailed studies and can fill a significant research gap.
Microlearning offers unique advantages for EMT training because it delivers content in short, focused modules that can be easily integrated into their demanding schedules. Unlike traditional educational methods that require extended attendance in lectures or workshops, microlearning allows EMTs to review critical information in brief, repetitive sessions, which aligns better with their shift-based work and limited availability. Furthermore, its modular design enables learners to focus on specific competencies, such as recognition and management of cardiac arrhythmias, ensuring that the content directly addresses their professional needs.
This adaptability makes microlearning particularly effective in enhancing both knowledge retention and self-efficacy among EMTs compared to more conventional approaches [21, 36].
Although several international studies have investigated modern educational strategies such as microlearning and webinars in medical training, the evidence remains limited and fragmented, particularly regarding their effectiveness in emergency medicine education and the management of cardiac arrhythmias. Previous works have often focused on general medical students or nursing education rather than EMTs, and few have directly compared these two methods in terms of self-efficacy and knowledge retention. Therefore, this study not only addresses a gap in the Iranian context but also contributes to the broader global discussion by providing comparative evidence from an underexplored setting in parallel with global educational trends.
Given the importance of improving EMTs’ knowledge and self-efficacy, and the lack of direct comparative evidence between microlearning and webinar-based education in this field, this study aimed to evaluate the impact of these two training methods on emergency medical technicians’ ability to diagnose and manage cardiac arrhythmias in Zabol, Iran (2024). To make the purpose of the study more explicit, we have articulated the research hypothesis clearly. The study hypothesizes that microlearning, as a flexible and learner-centered approach, will have a significantly greater positive effect on EMTs’ knowledge and self-efficacy in diagnosing and managing cardiac arrhythmias compared with webinar-based training.
The findings are expected to guide policymakers and educators in designing more effective and evidence-based training strategies to strengthen frontline emergency care.
Methods
Study design
This quasi-experimental study with a nonequivalent control group and pretest–posttest design was conducted among emergency medical technicians (EMTs) working in pre-hospital emergency bases in the Sistan region of Iran in 2024. Participants were recruited using a convenience sampling approach from all available EMTs. To minimize potential contamination between the intervention and control groups, the pre-hospital emergency bases (23 urban and roadside bases in total) were treated as clusters.
These clusters were then randomly assigned to one of three groups (microlearning, webinar, or control) using a lottery-based cluster randomization method, ensuring an equal distribution of urban and roadside bases across the groups.
Participants
Inclusion criteria included completing an informed consent form, willingness to participate in the research, absence of participation in similar cardiac arrhythmia training courses within the past six months, and current employment in pre-hospital emergency bases in Zabol during 2024. The restriction regarding prior participation in similar courses was applied to avoid potential bias and ensure that all participants started the intervention with a comparable baseline level of knowledge and self-efficacy.
Exclusion criteria included withdrawal from further cooperation, absence from training sessions, any change in employment status from operational to headquarters staff, and transfer to other centers. These criteria were selected to maintain consistency in exposure to the intervention and ensure reliable outcome measurement.
The sample size was calculated using the mean comparison formula based on the findings of Shirazi et al. [22]. With a significance level of α = 0.05 and a statistical power of 90% (β = 0.10), the minimum required sample size was estimated to be 13 participants per group. To account for potential attrition and ensure sufficient statistical power, we increased the sample size and recruited 75 eligible EMTs who expressed willingness to participate.
After categorizing EMT personnel into urban and rural groups, convenient sampling was used to identify eligible participants. Subsequently, 75 technicians were selected and randomly assigned—using a lottery method—to three equal groups (microlearning, webinar, and control; 25 participants each). The lottery-based randomization ensured that every participant had an equal probability of being allocated to any group, thereby minimizing selection bias and strengthening the methodological rigor of the study.
Data collection
The tools used in the present work to collect information included the following, all of which were sent to participants and completed electronically:
Demographic information questionnaire
This questionnaire was designed by the researcher and included questions about the participants’ personal and professional characteristics, such as age, gender, marital status, and work experience.
Researcher-made questionnaire on knowledge of diagnosis and treatment of cardiac arrhythmias
This questionnaire included 20 multiple-choice questions designed to assess the theoretical knowledge of technicians in the field of recognition, diagnosis, and correct treatment of cardiac arrhythmias. The content of this test was designed following the guidelines of the American Heart Association (AHA, 2020) and the protocols of the Iranian Emergency Organization. The correct answer to each question was given 1 point, and the wrong answer was given 0 points.
The final score of each individual’s knowledge was calculated from the sum of the correct scores (total score of 0 to 20).
The content and face validity of this questionnaire was confirmed using the content validation method and obtaining the opinions of 10 expert professors (cardiology, emergency medicine, and medical emergency).
The reliability of this tool was calculated using test-retest and correlation coefficient on 20 EMTs (who were not part of the main sample of the study) and with an interval of two weeks. The scores of the knowledge questionnaire on the diagnosis and treatment of cardiac arrhythmias were collected in two time intervals, with an interval of two weeks. Then, the Pearson correlation coefficient between the scores of the first and second tests was calculated, which was obtained to be 0.85.
This value indicates a positive and strong correlation between the two test stages, indicating appropriate stability and high reliability of the questionnaire in measuring the theoretical knowledge of technicians. In other words, the aforementioned tool has high reliability and can be used in subsequent studies.
Self-efficacy questionnaire
In order to measure participants’ self-efficacy, a 20-item questionnaire adapted from the questionnaire of self-efficacy in clinical practice for nursing students was employed. The questionnaire involved three sections: patient assessment (10 questions), care plan implementation (4 questions), and care plan evaluation (6 questions). Responses were scored on a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree), with a total score ranging from 20 to 100; higher scores indicated higher self-efficacy.
The validity of the Persian version of the Clinical Self-Efficacy Questionnaire has been confirmed by numerous studies, including Salimi et al. (2016), who confirmed the validity of the questionnaire in the population of nursing students at Qazvin University of Medical Sciences, Iran, using content and structural validation methods, extracting content validity index (CVI) and content validity ratio (CVR), and performing factor analysis. The internal reliability of this questionnaire has also been reported to be satisfactory, using the Cronbach’s alpha coefficient [37–39].
In the present study, the internal reliability of the self-efficacy questionnaire was calculated using Cronbach’s alpha coefficient; its value was obtained to be 0.92, which indicates an excellent internal consistency of the tool for the measurement of participants’ self-efficacy. This result suggests the appropriate validity and reliability of the adapted questionnaire used in the study.
Educational intervention protocol
After obtaining written informed consent from all participants and completing the pre-test phase, educational interventions were implemented for the relevant groups as follows. All trainings were conducted by the same instructor with expertise in emergency care and cardiac arrhythmias to ensure consistency: 22 short online sessions for the microlearning group, two 55-minute webinars for the webinar group:
Microlearning group
Training was delivered in the form of 22 five-minute modules, three times a day (morning, noon, evening) in a group created on social networks. Educational content (including identification of cardiac arrhythmias, medications and treatment methods, pre-hospital treatment of arrhythmias, and resuscitation protocol) was prepared by the researcher based on the protocols of AHA 2020 and the Iranian Emergency Organization. It was presented purposefully in the form of videos, images, and short texts.
Content design was carried out following the principles of microlearning (Hamelmann & Buchem), including conciseness, reduction of reading material, increasing images and graphics, and simplicity. The educational content consisted of two general sections of theoretical topics and practical methods, and was approved by professors specializing in cardiology and emergency medicine.
Webinar group
The training was held online in the Skyroom Online learning environment in two 55-minute sessions (a total of 110 min) on two consecutive days. The total duration of training in this group was exactly the same as that of the microlearning group. The topics included identification of cardiac arrhythmias, medications and treatment methods, pre-hospital treatment of arrhythmias, and resuscitation protocol with the same educational content as the microlearning group.
The sessions began with questions and issues in the educational video or PowerPoint, and then continued in the form of lectures and group participation of all participants in the discussion.
Control group
In this study, the control group only participated in the routine educational programs of the Emergency Center Training Unit through methods such as lectures and continued their routine professional duties throughout the study period. They were not exposed to microlearning content, webinar sessions. This design ensured that the control group represented standard practice conditions, allowing for a clearer distinction between the outcomes of the experimental groups and usual training procedures.
Data collection was conducted in the following three stages: (1) Pre-test: before the start of any educational intervention; (2) Immediate post-test: immediately after the completion of the educational interventions; (3) Delayed post-test: one month after the completion of the educational interventions, to assess the stability of knowledge and self-efficacy. In all three stages, the knowledge and self-efficacy questionnaires were completed again. All participants in intervention groups provided confirmation of receiving the allocated training.
The participants in different groups were not in contact with each other, and it was ensured that information was not shared by conducting the training sessions separately and at different times.
Statistical analysis
Statistical analyses were performed using SPSS software (version 26). The normality of quantitative variables was assessed using the Kolmogorov–Smirnov test. Descriptive statistics were used to summarize demographic and baseline characteristics.
Inferential analyses included the Chi-square test, Fisher’s Exact Test, One-way ANOVA, Repeated Measures ANOVA, Tukey’s post-hoc test, and Bonferroni post-hoc test, with a 95% confidence level and a significance level of p < 0.05.
For the repeated measures ANOVA, all required statistical assumptions were evaluated. The normal distribution of repeated measures data was examined using the Kolmogorov–Smirnov test. Mauchly’s test of sphericity was conducted to assess the sphericity assumption.
When this assumption was violated, the Greenhouse–Geisser correction was applied to adjust the degrees of freedom accordingly. These procedures ensured the robustness and validity of the longitudinal comparisons across the study groups.
Results
The findings indicated that the majority of the study participants in all three groups were married (18 people [72%] in microlearning group, 21 people [84%] in webinar group, and 20 people [80%] in control group), had a bachelor’s degree (16 people [64%] in microlearning group, 16 people [64%] in webinar group, and 15 people [60%] in control group) and employed in formal type (16 people [64%] in microlearning group, 17 people [68%] in webinar group, and 14 people [56%] in control group).
According to the results of statistical tests, no significant differences were observed between the three study groups in terms of marital status (ᵡ2=1.1, df = 2, P = 0.57), level of education (ᵡ2=0.11, df = 2, P = 0.94), and type of employment (Fisher’s Exact Test = 2.60, P = 0.663). These results indicate the homogeneity of the groups in terms of the aforementioned demographic variables.
In addition, the comparison of mean age and work experience in the three study groups did not indicate any statistically significant difference (for age: F = 0.63, P = 0.54; for work experience: F = 1.24, P = 0.29), confirming the homogeneity of the groups in terms of age and work experience.
The mean knowledge score before the intervention in the three study groups (microlearning: 9.5 ± 2.8; webinar: 11.3 ± 4; control: 12.2 ± 8.4) did not show a statistically significant difference (F = 1.3, P = 0.052). However, immediately after the intervention and one month after the intervention, a statistically significant difference was indicated among the three groups. Immediately after the intervention, the mean knowledge score increased to 17.3 ± 1.2 and 17.5 ± 1.1 in the microlearning group and the webinar group, respectively, while it was 8.8 ± 1.6 in the control group.
One month after the intervention, the mean knowledge scores were 16.7 ± 1.2, 13.2 ± 1.8, and 7.8 ± 1.8 in the microlearning, webinar, and control groups, respectively.
The results of the repeated measures analysis of variance indicated that in the microlearning (F = 160.9, P < 0.001) and webinar (F = 36.8, P < 0.001) groups, a significant increase in the average knowledge score was observed during the three study periods. In contrast, in the control group, a significant decrease in the average knowledge score was observed during the three study periods (F = 14.4, P < 0.001). Tukey’s post hoc test revealed significant differences between the microlearning group and the control group (P < 0.001), as well as between the webinar group and the control group (P < 0.001), in both immediate and one-month post-intervention assessments.
Moreover, a significant difference was observed between the microlearning and webinar groups in the assessment one month after the intervention (P < 0.001, Table 1).
Table 1Comparison of the mean knowledge scores in the microlearning, webinar, and control groups at three time points: pre-test, post-test, and one-month follow-upStudied group forknowledge score\TimeLearning GroupX ± SDVibinar GroupX ± SDControl GroupX ± SDResult of the ANOVA TestResult of Tukey’s Post-Hoc TestBefore the Intervention9.5 ± 2.811.3 ± 412.2 ± 4.8F = 3.1P = 0.052NSImmediately After the Intervention17.3 ± 1.217.5 ± 1.18.8 ± 1.6F = 354.8P < 0.01Microlearning vs. controlP < 0.001Webinar with controlP < 0.001One Month After the Intervention16.7 ± 1.213.2 ± 1.87.8 ± 1.8F = 193.1P < 0.001Microlearning vs. webinarP < 0.001Webinar vs. controlP < 0.001Repeated ANOVA Test ResultF = 160.9P < 0.001F = 36.8P < 0.001F = 14.4P < 0.001Ben Feroni’s Follow-up Test ResultBefore the intervention vs. immediately after the interventionP < 0.001Before the intervention vs. three months after the interventionP < 0.001Before the intervention vs. immediately after the interventionP < 0.001Immediately after the intervention vs. three months after the interventionP < 0.001Before the intervention vs. immediately after the interventionP < 0.005Before the intervention vs. three months after the interventionP < 0.001Pre-test: knowledge score before the intervention; Post-test: knowledge score immediately after the intervention; Follow-up: knowledge score one month after the intervention
In addition, comparison of the mean changes in knowledge scores demonstrated that there was a significant difference in the changes in scores before and immediately after the intervention (F = 37.57, P < 0.001), before and one month after the intervention (F = 48, P < 0.001), and immediately and one month after the intervention (F = 22, P < 0.001) in the three groups. The mean changes in knowledge scores in the microlearning group showed an increasing trend (88 ± 7.48) compared to one month after the intervention, but a decreasing trend (1.47 ± -0.6) compared to one month after the intervention.
The mean score of self-efficacy before the intervention in the three study groups (microlearning: 79.5 ± 8.8; webinar: 78.6 ± 8.2; control: 77.8 ± 11.1) did not show a statistically significant difference (F = 0.19, P = 0.82). However, immediately after the intervention and one month after the intervention, a statistically significant difference was indicated among the three groups.
Immediately after the intervention, the mean self-efficacy score increased to 94.8 ± 1.6 in the microlearning group and to 95.1 ± 2.4 in the webinar group, while it was 80.2 ± 2.4 in the control group. One month after the intervention, the mean self-efficacy scores were reported to be 90.5 ± 3.2, 84.2 ± 4.6, and 77.2 ± 2.9 in the microlearning, webinar, and control groups, in respective order.
The results of the repeated measures analysis of variance indicated that in the microlearning (F = 61.5, P < 0.001) and webinar (F = 64.6, P < 0.001) groups, a significant increase in the mean self-efficacy score was observed during the three study periods. In the control group, no significant changes were observed in the mean self-efficacy score between the three study periods (F = 1.6, P < 0.22).
Tukey’s post hoc test demonstrated that significant differences were observed between the microlearning group and the control group (P < 0.001), as well as between the webinar group and the control group (P < 0.001) immediately after the intervention and one month after the intervention. Moreover, there was a significant difference between the microlearning and webinar groups in the assessment one month after the intervention (P < 0.001, Table 2).
Table 2Comparison of the mean self-efficacy scores in the microlearning, webinar, and control groups at three time points: pre-test, post-test, and one-month follow-upStudy group forself-efficacy\TimeMicrolearning GroupX ± SDVibinar GroupX ± SDControl GroupX ± SDResult of the ANOVA TestResult of Tukey’s Post-Hoc TestBefore the Intervention79.5 ± 8.878.6 ± 8.277.8 ± 11.1F = 0.19P = 0.82NSImmediately After the Intervention94.8 ± 1.695.1 ± 2.480.2 ± 2.4F = 383.4P < 0.001Microlearning vs. controlP < 0.001Webinar with controlP < 0.001One Month After the Intervention90.5 ± 3.284.2 ± 4.677.2 ± 2.9F = 84.1P < 0.001Microlearning vs. webinarP < 0.001Microlearning vs. controlP < 0.001Webinar vs. controlP < 0.001Repeated ANOVA Test ResultF = 61.04P < 0.001F = 64.58P < 0.001F = 1. 6P = 0.22Ben Feroni’s Follow-up Test ResultImmediately after the intervention vs. before the interventionP < 0.001Immediately after the intervention vs. one month after the interventionP < 0.001One month after the intervention vs. before the interventionP < 0.001Immediately after the intervention vs. before the interventionP < 0.001Immediately vs. one month after the interventionP < 0.001One month after the intervention vs. before the interventionp < 0.001NSPre-test: self-efficacy score before the intervention; Post-test: self-efficacy score immediately after the intervention; Follow-up: self-efficacy score one month after the intervention
In addition, comparison of mean changes in self-efficacy scores demonstrated that there was a significant difference in the changes in scores before and immediately after the intervention (F = 16.69, P < 0.001), before and one month after the intervention (F = 10.58, P < 0.001), and immediately and one month after the intervention (F = 25.91, P < 0.001) in the three groups. The mean changes in self-efficacy scores in the microlearning group showed an increasing trend (8.26 ± 11) compared to before and one month after the intervention, but a decreasing trend (3.44 ± -4.32) compared to immediately and one month after the intervention.
Discussion
The findings of the current study confirm the research hypotheses and highlight the high potential of microlearning as a new and effective educational approach in the professional development of medical staff, especially in sensitive areas such as medical emergencies. The significant increase in knowledge and self-efficacy in both intervention groups confirms the effectiveness of new and technology-based educational approaches in improving the professional competencies of medical staff [14].
Both methods leverage the principles of adult learning, such as flexibility, accessibility, and the ability to learn at a time and place of their choice. These features are important for emergency medical personnel with busy schedules, helping them overcome barriers to participation in traditional training [14]. Webinars provide a live interactive environment that allows for questions and answers, group discussions, and clinical simulations, which facilitate deeper, more collaborative learning [40].
On the other hand, microlearning [16] focuses on delivering short, focused, and digestible content, allowing learners to review information repeatedly, which helps consolidate information in long-term memory [24, 25].
The findings of the present study on the effectiveness of microlearning in increasing knowledge are consistent with the study by Ichiuji et al. (2022) [24] who reported improvements in surgical students’ knowledge scores after a microlearning intervention, and also with Albooghobeish et al. (2024) [25] on increasing knowledge and skills in anesthesia nursing students.
These alignments indicate the general effectiveness of the microlearning approach in improving professional knowledge in the health field [16].
The increase in self-efficacy in both training groups (microlearning and webinar) is consistent with several studies that have confirmed the role of structured training in strengthening self-efficacy beliefs [29] in clinical settings [33, 35]. For instance, Van Dinther et al. (2011) [35] have identified various factors influencing students’ self-efficacy in higher education, which confirms the importance of self-efficacy resources in educational processes.
Regarding the effectiveness of webinars, the results of the present study, which indicated that webinars increased knowledge and self-efficacy [40], are consistent with the findings of Sarboozi-Hosseinabadi et al. (2024) [27], Hosseini et al. (2022) [40], and Masinaeinezhad et al.
(2023) [32], who supported the potential of webinars/web-based training in emergency education and cardiac-related topics.
Additionally, the overall effectiveness of these methods in emergency training is comparable to studies, such as Khoshab et al. (2016) [41], that examined the effect of simulation training on cardiopulmonary resuscitation. This alignment with the educational needs and lifestyle of learners justifies the overall effectiveness of these two methods in promoting knowledge and self-efficacy.
Although previous studies have indicated the effectiveness of webinars [20, 32, 41], this study specifically emphasizes the advantage of microlearning in knowledge retention, which is justified due to its design principles (e.g., spaced repetition [19] and cognitive load management [18] that have also been supported in the studies conducted by Albooghobeish and Ichiuji [24, 25]. This finding further highlights the importance of careful educational design that is tailored to the cognitive and environmental characteristics of learners and adds to the scientific literature on the long-term effectiveness of modern educational methods, especially in medical education.
Comparison of learning methods of the current study
The structure of microlearning in this study results in spaced repetition of content, enhances the effectiveness of microlearning in knowledge retention [31], as has been indicated in Albooghobeish and Ichiuji [24, 25]. Technicians can better understand the relationship between clinical symptoms, electrocardiographic findings, and treatment protocols and encode this information in a structured and retrievable form in their long-term memory. This process leads to more meaningful and stable learning, which is evident in delayed (one-month) post-tests.
Successful experiences are the most potent source of self-efficacy [29, 35]. Microlearning provides repeated opportunities for “small but tangible successes” by breaking complex concepts into small and manageable units [16]. Each time a technician successfully completes a microlearning module or fully understands a concept, these accumulated successes strengthen their belief in their abilities to manage arrhythmias.
This sense of ongoing progress gradually but steadily increases clinical self-efficacy.
Micro-learning systems often include automated feedback and motivational messages that act as a form of “verbal encouragement” [29]. This positive feedback is a general confidence booster. As a result, technicians face clinical challenges with greater belief in their abilities.
This finding is consistent with Mafyan et al. (2014), who reported that the hybrid e-learning increased the self-efficacy of nursing students in cardiovascular intensive care courses [33].
Although webinars were also effective in increasing knowledge and self-efficacy, their effectiveness in retention was not as high as microlearning, which can be analyzed from the following aspects.
Webinars and self-efficacy: role of modeling and verbal encouragement
Webinars provide rich opportunities for “substitute experiences” by providing simulated scenarios and the opportunity to observe experienced instructors or colleagues managing complex arrhythmias [29, 35, 40]. Observing the success of others reassures technicians that they are capable of performing similar tasks, which helps to increase their self-efficacy.
Live webinar interactions, including direct Q&A with the instructor and immediate feedback, allow for active “verbal encouragement” [29]. This direct encouragement and guidance can help increase the confidence of technicians. Hosseini et al.
(2022) also confirmed the effectiveness of web-based training on the knowledge and performance of EMTs in pre-hospital care, which is consistent with our results on the effectiveness of webinars [41]. Moreover, Masinaeinezhad et al. (2023) reported that web-based training can increase nursing students’ knowledge and self-efficacy in interpreting cardiac dysrhythmias, which also supports the overall effectiveness of webinars in areas relevant to our research topic [32].
The volume of information presented in a 55-minute webinar session can exceed the optimal processing capacity of working memory [18], especially when compared to small, frequent parts of microlearning. This issue can lead to “shallow learning” and reduced retention of information in long-term memory. Unlike microlearning, which is inherently based on regular repetition, webinars are typically delivered in a single session or at longer intervals.
This lack of regular repetition can lead to faster forgetting of learned information and online fatigue. The length of a webinar and the need for constant focus in a virtual environment can lead to mental fatigue and reduced ability to sustain attention, which in turn negatively impacts learning retention [16, 19].
Despite its promising outcomes, microlearning has several limitations that should be acknowledged. Its effectiveness largely depends on participants’ digital literacy, access to mobile devices or stable internet connections, and their personal motivation to engage with the learning materials. These factors may restrict the applicability of microlearning in settings where technological infrastructure or digital skills are limited.
Moreover, microlearning alone may not fully support the development of complex clinical decision-making skills that require deeper interaction and supervision. Therefore, integrating microlearning with traditional face-to-face or workshop-based methods as part of a blended learning model could provide a more balanced and comprehensive educational approach for emergency medical training [42].
Research limitations
This study faced limitations that could affect the generalizability of the results: the unavailability of all samples simultaneously due to different personnel shift schedules; the possibility of internet outages on personnel shift days or during the webinar workshop; the possibility of personnel being sent on missions during the webinar workshop; limitations in fully controlling intervening variables due to the semi-experimental nature of the study and the inability to randomize individuals in some circumstances; as well as the reliance on participants’ self-reports in the questionnaires, which could be affected by response bias.
The study limitations
This study has several limitations. First, the sample was drawn from a single city and a relatively small group of EMTs, which may limit the generalizability of the findings. Second, a fully randomized controlled trial design was not employed, which could have strengthened internal validity.
Additionally, the online delivery format may have restricted access for participants with limited internet connectivity or limited flexibility to engage with the educational content.
Another important consideration is the variation in digital literacy among EMTs. Differences in familiarity and comfort with digital tools may have influenced the extent to which participants were able to effectively engage with microlearning or webinar-based training. This factor may also limit the generalizability of the results to EMT populations with lower levels of digital readiness.
Future research should address these limitations by conducting multi-center randomized trials, providing offline or more flexible learning options, and exploring the effects of microlearning in other medical domains. Further studies could also compare microlearning with additional educational modalities to identify the most effective strategies for improving knowledge, skills, and self-efficacy among healthcare professionals.
Conclusion
This study demonstrates that both microlearning and webinars effectively enhance EMTs’ clinical knowledge and self-efficacy, with microlearning showing greater durability of learning outcomes. Tailoring educational strategies to learners’ cognitive and environmental needs and integrating microlearning with other contemporary methods can improve the quality of pre-hospital care and strengthen the emergency medical workforce. The findings also offer practical implications for medical education and emergency medicine, including prioritizing microlearning, adopting blended learning approaches, emphasizing self-efficacy, and supporting technological infrastructure.
Future research could build on these findings by examining the long-term impact of microlearning and webinar-based training beyond the one-month follow-up period, as well as exploring the integration of both methods within a blended learning framework. Additionally, conducting fully randomized controlled trials with larger sample sizes is recommended to further strengthen internal validity and broaden the generalizability of the results.