Stroke is one of the leading causes of disability and death, with ‘approximately 100 000 people suffering a stroke within the UK each year’, which equates to around ‘one every 5 minutes’ (Stroke Association, 2018).
The condition has numerous outcomes, including disability and death, which affect family, carers and healthcare providers as well as the patients themselves, and it can recur (Ferguson et al, 2016). This has resulted in a continued focus on increasing national programmes to develop clinical knowledge around the prevention, identification and management of stroke and stroke-like symptoms (Stroke Association, 2015).
Through a variety of campaigns (e.g. FAST), the intention is that everybody should have a basic understanding of early warning signs to help identify a potential stroke and reduce its impact (Stroke Association, 2015; 2018). This then allows early assessment by health professionals such as ambulance staff to ascertain whether a patient is presenting with a stroke or an alternative complaint through reference to current guidelines, such as the Joint Royal Colleges Ambulance Liaison Committee (JRCALC) guidelines by the Association of Ambulance Chief Executives (AACE) (2019), and those from the National Institute of Health and Care Excellence (NICE) (2019) and the Royal College of Physicians (2016). To facilitate enhanced assessments and initiate a treatment pathway, health professionals must be able to identify the key signs and symptoms (Wolf et al, 2016).
Healthcare education and training have developed in response to changing needs and updates in knowledge, skills, equipment and drugs within both structured prequalification and postgraduate programmes and continual professional development initiatives. These changes to education and training require a greater level of flexibility around how learning events are delivered while maintaining a suitable level of knowledge transfer, support and guidance from experienced teaching staff (Mohanna, 2007).
In response to this, several learning initiatives have been used to assist clinical staff develop their knowledge and ability to deliver high-quality care. One is the use of e-learning to develop how practitioners manage patients experiencing acute stroke and stroke mimics. E-learning has been generally accepted as an effective platform from which to deliver a range of training and educational content, and its ability to be flexible and cost effective has resulted in its adoption by numerous organisations and institutions (Cook et al, 2010; Regmi and Jones, 2020).
This use of e-learning is seen especially within the healthcare environment as it can reduce the amount of time health professionals spend away from their role while helping them to maintain an appropriate level of knowledge and skill (Sholl et al, 2017).
This study uses an established e-learning course focusing on acute stroke and stroke mimics that can be used to develop clinical staff in a range of healthcare environments. By looking at practitioner knowledge development and engagement with the course, it will examine whether this learning environment allows effective development in the subject matter and highlight areas that may need further investigation or development.
Aim
The study aimed to assess the effectiveness of e-learning to develop ambulance staff in the management of acute stroke and stroke mimics.
Objectives
The objectives of this study were to:
Methodology
This study ran between December 2014 and July 2015 and used an online e-learning package to deliver a programme focusing on acute stroke and stroke mimics to prehospital clinical staff.
Questionnaires before and after the course were used to ascertain practitioners' knowledge base before they engaged with the learning materials and following course completion to ascertain the amount of knowledge retained.
This study sits within the area of evaluation so ethical approval was not required as the Health Research Authority states, although local research and development approval was sought from the ambulance trust and all procedures were performed in compliance with local and national guidance.
Participants
Clinical staff in a UK ambulance service were identified as the potential sample group. To maximise engagement and increase diversity, staff of all grades were approached to participate using a distributed poster followed by direct emails.
Selection was based upon a non-probability sample (first come), and the sample was divided between the following clinical groups: emergency care support workers; ambulance technicians; paramedics; paramedic practitioners; critical care paramedics; and undergraduate paramedics in the last 4 months of their course.
Materials
An e-learning course developed for UK ambulance staff by a private training provider with the support of an NHS trust was used. Based on an established American course developed by the University of Miami, the programme contained nine modules that were designed to take approximately 30 minutes each to complete, resulting in a total course time of 4½–5 hours. Each module contained embedded assessment questions and used a range of multimedia focusing on key areas of stroke, including pathophysiology, assessment, treatment and associated conditions.
The before and after questionnaires were separate from the course although they had been developed and validated by the University of Miami for their own stroke management course. With the questionnaires primarily focusing on anatomy and physiology with a secondary focus on assessment skills and expected treatment, they were suitable for UK participants as the majority of the knowledge was transferable.
Each questionnaire contained 20 multiple choice questions and, while the questionnaires were not modified, some of the grammar and terminology was altered before use, mainly because of transatlantic differences.
Procedure
Once identified, the participants received an email via their trust accounts that contained an electronic copy of the pre-study questionnaire and a link to the course. Each participant was asked to return the questionnaire before starting the course so the results were not skewed by the course content.
Although the course is designed for no more than 6 weeks, it was decided to keep it open for longer because of the nature of shift work which made it more difficult for staff to undertake such courses outside their working hours. In the end, the course remained open for 12 weeks in total because of some unforeseen changes at the trust that could have affected the participants' ability to complete the course and its associated tasks.
Six weeks after the closing date, the post-course questionnaire was sent out electronically to all participants. This time frame was chosen to give them the opportunity to consolidate their learning away from the study environment, which reduced the likelihood of them just regurgitating the material without any real-world consideration.
Analysis
Data were collected from the before-and-after questionnaires and the in-course assessment. To understand the participants' level of engagement with the study materials, course completion time was also recorded.
These data provided measures of base knowledge, the effectiveness of course materials, levels of participant engagement and insight into whether the course objectives were being realised.
All questionnaire and in-course data were recorded and reported as percentages. Data are summarised in a table to allow a clear comparison between the three assessed elements of the study and to give an understanding of the time taken to complete the course. The data are supported by additional group comparisons that are not identifiable within the summarised data.
Results
Of the 50 staff members recruited to the study, 41 provided analysable data by completing a suitable proportion of the course to pass as well as both pre and post-course questionnaires.
After calculating the average grades for the different groups (Table 1), an overall combined average of each clinical group could be allocated to each stage of the study. This shows: an average pre-course questionnaire score of 65%; an average course assessment score of 93%; an average post-course questionnaire score of 67%; and an average course completion time of 3 hours 6 minutes.
| No of participants per group | Average pre-course questionnaire score | Average assessment score during the course | Average post-course questionnaire score | Average course completion time (hrs/mins) | |
|---|---|---|---|---|---|
| Emergency care support workers | 4 | 59% | 93% | 70% | 2:50 |
| Ambulance technician | 4 | 63% | 96% | 55% | 1:23 |
| Paramedic | 12 | 67% | 92% | 70% | 3:54 |
| Paramedic practitioner | 6 | 68% | 92% | 65% | 3:12 |
| Critical care paramedic | 6 | 72% | 92% | 71% | 4:29 |
| Undergraduate paramedic | 9 | 61% | 94% | 70% | 2:48 |
Group comparisons
The initial data showed several additional comparisons that are not identifiable within the summarised figures. These provide some context around how the different clinical grades performed on the course and in the before and after questionnaires. They showed:
Discussion
The data collected before, during and after the course provide an opportunity to compare and contrast how the participants have engaged with the material and to what level they have both developed their knowledge and retained it 6 weeks after the taught component of the course.
While the in-course results show a positive level of engagement and knowledge attainment, the retention of this knowledge was shown to be less than may be expected across the range of prehospital clinicians.
It is known that motivated teachers encourage greater student engagement and that a structured approach means a better learning environment (Cents-Boonstra et al, 2020). From the results achieved by all individuals taking this course, it may be inferred that it was structured appropriately to its target audience and actively engaged the students, or that the participants already had a good understanding of the course content. However, while this may have been the case during the programme, knowledge retained after the course was found to be lacking, raising the question as to why this dichotomy occurred.
Most e-learning courses are designed to take place over a certain number of weeks so as not to impact on the student's life by allowing them to access content as and when possible (Roddy et al, 2017). However, because of their structure and overall learning objectives, many online courses contain barriers to student learning that cause engagement to falter if not addressed appropriately (Becker et al, 2013). These include poor IT skills, a lack of support, difficulty learning in this way and weak time management (O'Doherty et al, 2018), which includes students starting courses late and having to rush through the requirements in attempts to achieve the desired outcome (Onah et al, 2014). This often results in a reduced level of knowledge attainment as students have not spent enough time reading or absorbing the full course materials (Mukerji and Tripathi, 2010).
Looking at the time frames associated with this course, it can be seen that participants took an average of 3 hours 06 minutes to complete the programme of study, which is less than the expected time frame suggested for each module in the course documentation. Only nine participants took longer than the expected completion time frame to complete the course, which may explain the low post-course scores demonstrated by some of the participants.
Through learning, students gain a greater level of appreciation of key topics and themes. As Easteal and Biddell (2016) state, without a suitable amount of consolidation time, this knowledge and understanding cannot be retained, and this often results in a rapid loss of newly acquired knowledge and dependence on past exposure to the subject matter (Custers, 2010).
As a delivery method, e-learning has several barriers that can hold back learners. These barriers seem to have come into play with this study; participants stated within their general feedback that, for the most part, they did not have time to complete the various elements because of time constraints around their work. This is something Roddy et al (2017) and O'Doherty (2018) identify as being a risk to effective learning and, while it could be rectified by the employer providing specific time to complete the workload, e-learning is often used in place of face-to-face events to reduce time away from work (Pollard and Hillage, 2001).
Limitations
Although the six clinical grades were represented, the numbers in each group were not equal, resulting in low levels of comparable data for analysis. So, although trends are suggested, the level of evaluation was limited as were any inferences drawn. In addition, people in different clinical grades had varying levels of knowledge on starting the course and are expected to work at different levels in practice, so the comprehension of the course materials for some may have been more difficult, especially as they may not have had the opportunity to transition this theory into practice.
Participants were managing stroke patients according to the current JRCALC guidelines at the time of study (AACE, 2013), which did not focus as much on the type, location and modified treatment options addressed within the online course. This may have resulted in certain areas covered by the course not being considered routinely by clinicians in practice, resulting in an element of knowledge fade around these additional areas.
Conclusion
This study has not been able to definitively state whether e-learning is an appropriate method of developing ambulance staff in the area of acute stroke and stroke mimics.
The results provide more detail around how individuals interact with the e-learning processes as opposed to the clinical subject itself, which has taken more of a secondary role during the analysis.
The data relevant to the e-learning element demonstrate that, for the most part, the time afforded by participants to complete the course fell short of that expected. While the reasoning behind this is unclear, it likely did not allow a suitable level of engagement and subsequent knowledge retention to occur. This has resulted in staff who may have gained knowledge of the subject matter in the short term but appear to have gone through a degree of knowledge fade shortly after completing the course.
It is also possible that those who sped through the course may have also sped through the final questionnaire and not given themselves sufficient time to understand the questions and consider the options. This could explain why some participants had lower scores after than before the course.
As with any learning event, sufficient time needs to be devoted to e-learning by both those developing the course and the students undertaking it. Failure to do this on either side may result in disparities between expectation, perception and practice.
Recommendations
To fully understand the role of e-learning and how it can be used effectively to develop a range of clinicians in the areas of acute stroke and stroke mimics, further research is needed. The focus needs to be on not only the content, but also its delivery so that it engages students and allows them time to fully absorb the learning materials.
E-learning needs to be as effective as a didactic session delivered face-to-face in a classroom so, while the content may be of a high standard and appropriate to the audience, the areas surrounding its use need to be recognised to allow staff the time to complete the programme of study and consolidate their development afterwards. This is now more important than ever due to rapid developments in knowledge, skills, equipment and drugs that staff need to keep up to date with.