AI clinical

Comment: How do we learn to work with intelligent machines?

I discussed something related to this earlier this year (the algorithmic de-skilling of clinicians) and thought that this short presentation added something extra. It’s not just that AI and machine learning have the potential to create scenarios in which qualified clinical experts become de-skilled over time; they will also impact on our ability to teach and learn those skills in the first place.

We’re used to the idea of a novice working closely with a more experienced clinician, and learning from them through observation and questioning (how closely this maps onto reality is a different story). When the tasks usually performed by more experienced clinicians are outsourced to algorithms, who does the novice learn from?

Will clinical supervision consist of talking undergraduate students through the algorithmic decision-making process? Discussing how probabilistic outputs were determined from limited datasets? How to interpret confidence levels of clinical decision-support systems? When clinical decisions are made by AI-based systems in the real-world of clinical practice, what will we lose in the undergraduate clinical programme, and how do we plan on addressing it?

AI clinical

Translating AI into the clinical setting at UC Irvine – AI Med

Ultimately, many of these shortcomings exist because few if any physicians are actively engaged in developing the next generation of technology, AI or otherwise. It is interesting to note the vast majority of medical startup companies are founded with limited if any physician involvement or oversight.Without experts that deeply understand both the medical and technical aspects of the problem, there is currently a significant gap in translating cutting-edge AI technology to healthcare.

Source: Translating AI into the clinical setting at UC Irvine – AI Med

I’m preparing an article on machine learning for clinicians and one of the recommendations I make is that we must ensure that the 21st century healthcare agenda is not driven by venture capital and software engineers. Even though private corporations and government are probably not malevolent, when surveillance and profit are your core concerns it’s unlikely that you’re going to develop something that truly works in the patients’ best interest. We really do need clinicians to be more involved in guiding the progression of AI integration in the clinical context.

See also: AMA passes first policy guidelines on augmented intelligence.

Note: If you’re interested in this topic, I’ve shared the first draft of my introduction to machine learning for clinicians on ResearchGate and would appreciate any feedback you may have.

AI clinical education

An introduction to artificial intelligence in clinical practice and education

Two weeks ago I presented some of my thoughts on the implications of AI and machine learning in clinical practice and health professions education at the 2018 SAAHE conference. Here are the slides I used (20 slides for 20 seconds each) with a very brief description of each slide. This presentation is based on a paper I submitted to OpenPhysio, called: “Artificial intelligence in clinical practice: Implications for physiotherapy education“.

The graph shows how traffic to a variety of news websites changed after Facebook made a change to their Newsfeed algorithm, highlighting the influence that algorithms have on the information presented to us, and how we no longer really make real choices about what to read. When algorithms are responsible for filtering what we see, they have power over what we learn about the world.

The graph shows the near flat line of social development and population growth until the invention of the steam engine. Before that all of the Big Ideas we came up with had relatively little impact on our physical well-being. If your grandfather spent his life pushing a plough there was an excellent chance that you’d spend your life pushing one too. But once we figured out how to augment our physical abilities with machines we saw significant advances in society and industry and an associated improvement in everyones quality of life.

The emergence of artificial intelligence in the form of narrowly constrained machine learning algorithms has demonstrated the potential for important advances in cognitive augmentation. Basically, we are starting to really figure out how to use computers to enhance our intelligence. However, we must remember that we’ve been augmenting our cognitive ability for a long time, from exporting our memories onto external devices, to performing advanced computation beyond the capacity of our brains.

The enthusiasm with which modern AI is being embraced is not new. The research and engineering aspects of artificial intelligence have been around since the 1950s, while fictional AI has an even longer history. The field has been through a series of highs and lows (called AI Winters). The developments during these cycles were fueled by what has become known as Good Old Fashioned AI; early attempts to explicitly design decision-making into algorithms by hard coding all possible variations of the interactions in a closed-environment. Understandably, these systems were brittle and unable to adapt to even small changes in context. This is one of the reasons that previous iterations of AI had little impact in the real world.

There are 3 main reasons why it’s different this time. The first is the emergence of cheap but powerful hardware (mainly central and graphics processing units), which has seen computational power growing by a factor of 10 every 4 years. The second characteristic is the exponential growth of data, and massive data sets are an important reason that modern AI approaches have been so successful. The graph in the middle column is showing data growth in Zettabytes (10 to the power of 21). At this rate of data growth we’ll run out metric system in a few years (Yotta is the only allocation after Zetta). The third characteristic of modern AI research is the emergence of vastly improved machine learning algorithms that are able to learn without being explicitly told what to learn. In the example here, the algorithm has coloured in the line drawings to create a pretty good photorealistic image, but without being taught any of the concepts i.e. human, face, colour, drawing, photo, etc.

We’re increasingly seeing evidence that in some very narrow domains of practice (e.g. reasoning and information recall), machine learning algorithms can outdiagnose experienced clinicians. It turns out that computers are really good at classifying patterns of variables that are present in very large datasets. And diagnosis is just a classification problem. For example, algorithms are very easily able to find sets of related signs and symptoms and put them into a box that we call “TB”. And increasingly, they are able to do this classification better than the best of us.

It is estimated that up to 60% of a doctors time is spent capturing information in the medical record. Natural language processing algorithms are able to “listen” to the ambient conversation between a doctor and patient, record the audio and transcribe it (translating it in the process if necessary). It then performs semantic analysis of the text (not just keyword analysis) to extract meaningful information which it can use to populate an electronic health record. While the technology is in a very early phase and not yet safe for real world application it’s important to remember that this is the worst it’s ever going to be. Even if we reach some kind of technological dead end with respect to machine learning and from now on we only increase efficiency, we are still looking at a transformational technology.

An algorithm recently passed the Chinese national medical exam, qualifying (in theory) as a physician. While we can argue that practising as a physician is more than writing a text-based exam, it’s hard not to acknowledge the fact that – at the very least – machines are becoming more capable in the domains of knowledge and reasoning that characterise much of clinical practice. Again, this is the worst that this technology is ever going to be.

This graph shows the number of AI applications under development in a variety of disciplines, including medicine (on the far right). The green segment shows the number of applications where AI is outperforming human beings. Orange segments show the number of applications that are performing relatively well, with blue highlighting areas that need work. There are two other points worth noting: medical AI is the area of research that is clearly showing the most significant advances (maybe because it’s the area where companies can make the most money); and all the way at the far left of the graph is education, showing that there may be some time before algorithms are showing the same progress in teaching.

Contrary to what we see in the mainstream media, AI is not a monolithic field of research; it consists it consists of a wide variety of different technologies and philosophies that are each sometimes referred to under the more general heading of “AI”. While much of the current progress is driven by machine learning algorithms (which is itself driven by the 3 characteristics of modern society highlighted earlier), there are many areas of development, each of which can potentially contribute to different areas of clinical practice. For the purposes of this presentation, we can define AI as any process that is able to independently achieve an objective within a narrowly constrained domain of interest (although the constraints are becoming looser by the day).

Machine learning is a sub-domain of AI research that works by exposing an algorithm to a massive data set and asking it to look for patterns. By comparing what it finds to human-tagged patterns in the data, developers can fine-tune the algorithm (i.e. “teach it) before exposing it to untagged data and seeing how well it performs relative to the training set. This generally describes the “learning” process of machine learning. Deep learning is a sub-domain of machine learning that works by passing data through many layers, allocating different weights to the data at each layer, thereby coming up with a statistical “answer” that expresses an outcome in terms of probability. Deep learning neural networks underlie many of the advances in modern AI research.

Because machine and deep learning algorithms are trained on (biased) human-generated datasets, it’s easy to see how the algorithms themselves will have an inherent bias embedded in the outputs. The Twitter screenshot shows one of the least offensive tweets from Tay, an AI-enabled chatbot created by Microsoft, which learned from human interactions on Twitter. In the space of a few hours, Tay became a racist, sexist, homophobic monster – because this is what it learned from how we behave on Twitter. This is more of an indictment of human beings than it is of the algorithm. The other concern with neural networks is that, because of the complexity of the algorithms and the number of variables being processed, human beings are unable to comprehend how the output was computed. This has important implications when algorithms are helping with clinical decision-making and is the reason that resources are being allocated to the development of what is known as “explainable AI”.

As a result of the changes emerging from AI-based technologies in clinical practice we will soon need to stop thinking of our roles in terms of “professions” and rather in terms of “tasks”. This matters because increasingly, many of the tasks we associate with our professional roles will be automated. This is not all bad news though, because it seems probable that increased automation of the repetitive tasks in our repertoire will free us up to take on more meaningful tasks, for example, having more time to interact with patients. We need to start asking what are the things that computers are better at and start allocating those tasks to them. Of course, we will need to define what we mean by “better”; more efficient, more cost-effective, faster, etc.

Another important change that will require the use of AI-based technologies in clinical practice will be the inability of clinicians to manage – let alone understand – the vast amount of information being generated by, and from, patients. Not only are all institutional tests and scans digital but increasingly, patients are creating their own data via wearables – and soon, ingestibles – all of which will require that clinicians are able to collect, filter, analyse and interpret these vast streams of information. There is evidence that, without the help of AI-based systems, clinicians simply will not have the cognitive capacity to understand their patients’ data.

The impact of more patient-generated health data is that we will see patients being in control of their data, which will exist on a variety of platforms (cloud storage, personal devices, etc.), none of which will be available to the clinician by default. This means that power will move to the patient as they make choices about who to allow access to their data in order to help them understand it. Clinicians will need to come to terms with the fact that they will no longer wield the power in the relationship and in fact, may need to work within newly constituted care teams that include data scientists, software engineers, UI designers and smart machines. And all of these interactions will be managed by the patient who will likely be making choices with inputs from algorithms.

The incentives for enthusiastic claims around developments in AI-based clinical systems are significant; this is an acdemic land grab the likes of which we have only rarely experienced. The scale of the funding involved puts pressure on researchers to exaggerate claims in order to be the first to every important milestone. This means that clinicians will need to become conversant with the research methods and philosophies of the data scientists who are publishing the most cutting edge research in the medical field. The time will soon come when it will be difficult to understand the language of healthcare without first understanding the language of computer science.

The implications for health professions educators are profound, as we will need to start asking ourselves what we are preparing our graduates for. When clinical practice is enacted in an intelligent environment and clinicians are only one of many nodes in vast information networks, what knowledge and skills do they need to thrive? When machines outperform human beings in knowledge and reasoning tasks, what is the value of teaching students about disease progression, for example? We may find ourselves graduating clinicians who are well-trained, competent and irrelevant. It is not unreasonable to think that the profession called “doctor” will not exist in 25 years time, having been superseded by a collective of algorithms and 3rd party service providers who provide more fine-grained services at a lower cost.

There are three new literacies that health professions educators will need to begin integrating into our undergraduate curricula. Data literacy, so that healthcare graduates will understand how to manage, filter, analyse and interpret massive sets of information in real-time; Technological literacy, as more and more of healthcare is enacted in digital spaces and mediated by digital devices and systems; and Human literacy, so that we can become better at developing the skillsets necessary to interact more meaningfully with patients.

There is evidence to suggest that, while AI-based systems outperform human beings on many of the knowledge and reasoning tasks that make up clinical practice, the combination of AI and human originality results in the most improved outcomes of all. In other words, we may find that patient outcomes are best when we figure out how to combine human creativity and emotional response with machine-based computation.

And just when we’re thinking that “creativity” and “originality” are the sole province of human beings, we’re reminded that AI-based systems are making progress in those areas as well. It may be that the only way to remain relevant in a constantly changing world is to develop our ability to keep learning.


Virtual reality in clinical education: A research project outline

I was lucky enough to spend some time chatting with Ben Ellis from Oxford Brookes University, about the possibilities of using VR for clinical education. A decade ago virtual reality was something that only the military and high end research labs could afford. But recently, thanks to initiatives like Google’s Cardboard, Daydream and Jump, pretty good VR experiences can be created and shared for relatively low cost. The purpose of this post is to – very briefly – explore what a VR research project in clinical education might look like.

Google's Jump camera rig.
Google’s Jump camera rig.

Establish a clinical / educational problem that is difficult to address in a traditional educational context. There are many examples but the one I always think about is the undergraduate student who is working with a patient who goes into cardiac arrest. That’s a situation we can’t plan for and that no amount of theoretical study will prepare the student for. A less extreme example might be the novice student who goes into the ICU for the first time.

Highlight the learning context. I would take this in the direction that learning in these situations is about exploring the emotional response that students experience when exposed to traumatic or at least, difficult, clinical encounters. Imagine debriefing a student after a variety of controlled exposures to very challenging clinical experiences. For example, what possibilities exist for designing those experiences to introduce students into situations where they may be morally compromised?

Describe how virtual reality can be used to work on the problem. There’s enough literature to show that exposure to situations that look and sound real (i.e. have high fidelity) can lead to a visceral response from students. We could create scenarios that are impossible to plan for in the real world, and then work with students in those controlled contexts to help them learn how to respond later.

Create the VR experiences using relatively low cost gear e.g. Google’s Jump camera rig. The research proposal would budget for buying the cameras needed to create the experiences. We’d collaboratively design the experiences across departments in different countries, so that the experiences students are exposed to could be quite diverse in nature. With 2-3 camera rigs we could probably put together a small library of experiences from several different placements.

Run the project. Expose students from a variety of different departments to those simulated clinical encounters and conduct debriefing sessions afterwards. Record the sessions (obviously we’d have consent, etc. since this would be a registered research protocol) and conduct analysis on the transcriptions. Share the outcomes and responses between the collaborating institutions.

Use the interpreted data to develop a model of engagement in these contexts. Prepare a worksheet – or something like that – to enable others to prepare students in advance, guide the debriefing, etc. Publish the models on an open access repository (e.g. Physiopedia), along with the VR experiences themselves, allowing anyone with a phone to go through the same experiences.

OK, so it’s not complete and there are probably a ton of problems with the idea so far, but I wanted to get it out there as a base to work from. If you’re interested in the potential of VR in clinical education, please get in touch.

education physiotherapy technology

Physiotherapy in 2050: Ethical and clinical implications

This post describes a project that I began earlier this week with my 3rd year undergraduate students as part of their Professional Ethics module. The project represents a convergence of a few ideas that have been bouncing around in my head for a couple of years and are now coming together as a result of a proposal that I’m putting together for a book chapter for the Critical Physiotherapy Network. I’m undecided at this point if I’ll develop it into a full research proposal, as I’m currently feeling more inclined to just have fun with it rather than turn it into something that will feel more like work.

The project is premised on the idea that health and medicine – embedded within a broader social construct – will be significantly impacted by rapidly accelerating changes in technology. The question we are looking to explore in the project is: What are the moral, ethical, legal, and clinical implications for physiotherapy practice when the boundaries of medical and health science are significantly shifted as a result of technological advances?

The students will work in small groups that are allocated an area of medicine and health where we are seeing significant change as a result of the integration of advanced technology. Each week in class I will present an idea that is relevant to our Professional Ethics module (for example, the concept of human rights) and then each group will explore that concept within the framework of their topic. So, some might look at how gene therapy could influence how we think about our rights, while others might ask what it even means to be human. I’m not 100% how this is going to play out and will most likely adapt the project as we progress, taking into account student feedback and the challenges we encounter. I can foresee some groups having trouble with certain ethical constructs simply because it may not be applicable to their topic.

Exoskeletons are playing an increasingly important role in neurological rehabilitation.
Exoskeletons playing an increasingly important role in neurological rehabilitation.
The following list and questions aim to stimulate the discussion and to give some idea of what we are looking at (this list is not exhaustive and I’m still playing around with ideas – suggestions are welcome):

  1. Artificial intelligence and algorithmic ethical decision-making. Can computers be ethical? How is ethical reasoning incorporated into machines? How will ethical algorithms impact health, for example, when computers make decisions about organ transplant recipients? Can ethics programmed into machines?
  2. Nanotechnology. As our ability to manipulate our world at the atomic level advances, what changes can we expect to see for physiotherapists and physiotherapy practice? How far can we go with integrating technology into our bodies before we stop being “human”?
  3. Gene therapy. What happens when genetic disorders that provide specialisation areas for physiotherapists are eradicated through gene therapy? What happens when we can “fix” the genetic problems that lead to complications that physiotherapists have traditionally had a significant role in. For example, what will we do when cystic fibrosis is cured? What happens when we have a vaccine for HIV? Or when ALS is little more than an inconvenience?
  4. Robotics. What happens when patients who undergo amputations are fitted with prosthetics that link to the nervous system? When exoskeletons for paralysed patients are common? How much of robotic systems will students need to know about? Will exoskeletons be the new wheelchairs?
  5. Aging. What happens when the aging population no longer ages? How will physiotherapy change as the human lifespan is extended? There is an entire field of physiotherapy devoted to the management of the aging population; what will happen to that? How will palliative care change?
  6. Augmented reality. When we can overlay digital information onto our visual field, what possibilities exist for effective patient management? For education? What happens when that information is integrated with location-based data, so that patient-specific information is presented to us when we are near that patient?
  7. Virtual reality. What will it mean for training when we can build entire hospitals and patient interactions in the virtual world? When we can introduce students to the ICU in their first year? This could be especially useful when we have challenges with finding enough placements for students who need to do clinical rotations.
  8. 3D printing. What happens when we can print any equipment that we need, that is made exactly to the patient’s specifications? How will this affect the cost of equipment distribution to patients? Can 3D printed crutches be recycled? Reused by other patients? What new kinds of equipment can be invented when we are not constrained by the production lines of the companies who traditionally make the tools we use?
  9. Brain-computer interfaces. When patients are able to control computers (and by extension, everything linked to the computer) simply by thinking about it, what does that mean for their roles in the world? What does it mean when someone with a C7 complete spinal cord injury can still be a productive member of society? What does it mean for community re-integration? How will “rehabilitation” change if computer science is a requirement to even understand the tools our patients use?
  10. Quantified self. As we begin to use sensors close to our bodies (inside our phones, watches, etc.) and soon – inside our bodies – we will have access to an unprecedented amount of personal (very personal) data about ourselves. We will be able to use that data to inform decision making about our health and well-being, which will change the patient-therapist relationship. This will most likely have the effect of modifying the power differential between patients and clinicians. How will we deal with that? Are we training students to know what to do with that patient information? To understand how these sensors work?
  11. Processing power. While this is actually something that is linked to every other item in the list, it might warrant it’s own topic purely because everything else depends on the continuous improvements in processing power and parallel reduction in cost.
  12. The internet. I’m not sure about this. While the architecture of the internet itself is unlikely to change much in the next few decades (disregarding the idea that the internet as we know it might be supplanted with something better), who has access to it and how we use it will most certainly change.

An artist's depiction of a nanobot that is smaller than blood cells.
Nanobot smaller than blood cells.
I should state that we will be working under certain assumptions:

  • That the technology will not be uniformly integrated into society and health systems i.e. that wealth disparity or income inequality will directly affect implementation of certain therapies. This will,obviously have ethical and moral implications.
  • That the technology will not be freely available i.e. that corporations will license certain genetic therapies and withhold their use on those who cannot pay the license.
  • That technological progression will continue over time i.e. that regulations will not prevent, for example, further research into stem cell therapy.
  • …we may have to make additional assumptions as we move forward but this is all I can think of now

We’ll probably find that there will be significant overlap in the above topics, since some are specific technologies that will have an influence on other areas. For example, gene therapy and nanotechnology may have an impact on aging; artificial intelligence will impact many areas, as will robotics and computing power. The idea isn’t that these topics are discrete and separate, but that they provide a focus point for discussion and exploration, with the understanding that overlap is inevitable. In fact, overlap is preferable, since it will help us explore relationships between the different areas and to find connections that we maybe were not previously aware of.

Giving patients bad news in virtual spaces where we can control the interaction.
Giving patients bad news in virtual spaces where we can control the interaction.
The activities that the students engage in during this project are informed by the following ideas, which overlap with each other:

  • Authentic learning is a framework for designing learning tasks that lead to deeper engagement by students. Authentic tasks should be complex, collaborative, ill-defined, and completed over long periods.
  • Inquiry-based learning suggests that students should identify challenging questions that are aimed at addressing gaps in their understanding of complex problems. The research that they conduct is a process they go through in order to achieve outcomes, rather than being an end in itself.
  • Project-based learning is the idea that we can use full projects – based in the real world – to discuss and explore the disciplinary content, while simultaneously developing important skills that are necessary for learning in the 21st century.

I should be clear that I’m not really sure what the outcome of this project will be. I obviously have objectives for my students’ learning that relate to the Professional Ethics module but in terms of what we cover, how we cover it, what the final “product” is…these are all still quite fluid. I suppose that, ideally, I would like for us as a group (myself and the students) to explore the various concepts together and to come up with a set of suggestions that might help to guide physiotherapy education (or at least, physiotherapy education as practiced by me) over the next 5-10 years.

Augmented reality has significant potential for education.
Augmented reality has significant potential for education.
So much of physiotherapy practice – and therefore, physiotherapy education – is premised on the idea that what has been important over the last 50 years will continue to be important for the next 50. However, as technology progresses and we see incredible advances in the integration of technology into medicine and health systems, we need to ask if the next 50 years are going to look anything like the last 50. In fact, it almost seems as if the most important skill we can teach our students is how to adapt to a constantly changing world. If this is true, then we may need to radically change what we prioritise in the curriculum, as well as how we teach students to learn. When every fact is instantly available, when algorithms influence clinical decision-making, when amputees are fitted with robotic prosthetics controlled directly via brain-computer interfaces…where does that leave the physiotherapist? This project is a first step (for me) towards at least beginning to think about these kinds of questions.


education physiotherapy

Physiotherapy education for the 21st century

Note: This article was first posted on the Critical Physiotherapy Network. Thanks to CPN for permission to cross-post here.

The beginning of the 21st century has seen more technological advances than any other time in our history, at an accelerating rate of change. At the time of writing, we are seeing the introduction of robotics, gene therapy and nanotechnology into larger and larger aspects of health care which, when combined with advances in computing power that will soon exceed the processing power of the human brain, we seem poised on the brink of a shift in our understanding of what it means to be human. In addition to the obvious influence of information and communication technology on social structures, we are also experiencing a shift from vertical communication structures that privilege hierarchies of control, to horizontal structures – like networks – that embody coordination, cooperation and collaboration (Bleakley, Bligh, Browne & Brice Browne. 2011). Regardless of what we call this cultural shift in perspective (postmodernity, late modernity, and posthumanism are all used somewhat interchangably), what matters is how we orient ourselves to the future (ibid.).

Given the scope of these changes and their inevitable impact on health professions education – embedded as it is within a broader socio-cultural context – we should expect to see a significant shift in how physiotherapists are prepared for practice. Yet, physiotherapy education continues to follow traditional lines of thinking and implementation, based in a historical model that not only ignores our understanding of how people learn but also fails to consider the changing needs of the communities we serve (Frenk et al., 2010). In addition, the focus on increasing the intake of health professional programmes that aims to graduate more therapists is insufficient to create a health workforce who are equipped with the appropriate competencies to respond to its evolving needs (WHO, 2013). The education of health professionals is often isolated from service delivery needs and does not adapt to the rapidly changing profile of the population. For example, an excessive focus on hospital-based education, together with education that segregates students into professional silos does not prepare them to work effectively in teams, nor to develop the leadership skills required in 21st century health services (ibid.).

Instead, physiotherapy educators must seek to adapt their curricula in order to produce professionals who have the capacity to identify and adjust to new environments in a continuous process of learning and adapting their competencies (WHO, 2013). As society and the health systems within it become increasingly complex and the needs of populations change accordingly, it seems appropriate to ask if our current education system is capable of preparing physiotherapy graduates to not only work in such environments, but to thrive.

In order to graduate young professionals who are capable of adapting to dynamic and complex systems, we cannot afford to continue learning in spaces that have not changed in 500 years. There is little evidence that physiotherapy educators have acknowledged society’s changing conceptions of therapy and health, nor that they have adapted their teaching practices accordingly. In order to bring about transformative learning experiences for health professions students, Frenk et al., (2010) suggest three fundamental shifts:

  1. from fact memorisation to searching, analysis, and synthesis of information for decision making
  2. from seeking professional credentials to achieving core competencies for effective teamwork in health systems
  3. from non-critical adoption of educational models to creative adaptation of global resources to address local priorities

We need to ask ourselves what attributes health care professionals require in order for them to effectively negotiate the challenges of future working environments and whether or not our current teaching and learning spaces help students become capable, effective leaders in complex health systems? As we develop a more nuanced vision of what it means to be human in an increasingly complex world, we must ask critical questions that challenge the profession to think differently about what it means to be a physiotherapist and consequently, how physiotherapy education needs to change.


  • Bleakley, A., Bligh, J., Browne, J., & Brice Browne, J. (2011). Medical Education for the Future: Identity, Power and Location. Springer.
  • Frenk, J., Chen, L., Bhutta, Z. A., Cohen, J., Crisp, N., Evans, T., … Zurayk, H. (2010). Health professionals for a new century: transforming education to strengthen health systems in an interdependent world. Lancet, 376(9756), 1923–58.
  • Gordijn, B., & Chadwick, R. (2008). Medical enhancement and posthumanity. Springer.
  • World Health Organization (2013). Transforming and scaling up health professionals’ education and training.

Proposal abstract: Training in the ICU for physiotherapy students with a visual impairment (a case study)

Abstract for a project proposal that I submitted for ethics review earlier this week. If it gets approved we’ll begin data collection on our first visually impaired undergraduate student placement in the intensive care unit.

The Department of Physiotherapy at the University of the Western Cape (UWC) began accepting students with visual impairments (VI) into the undergraduate programme in 1996. To date, eight students with visual impairments have graduated with degrees in physiotherapy, all of whom have gone on to successful employment in the health system. In this area, the department has played an important role in leading transformative change, not only in the broader context of higher education but specifically in the area of providing equal opportunities for professional training for all South Africans.

While the department has done well to provide equal opportunities to students with VI in the general undergraduate course, we have yet to place a student with VI into the ICU setting as part of their clinical rotations. Early in 2015 however, the department engaged in a series of discussions with one of our final year students with VI, as well as clinicians and lecturers and decided to explore the possibility of placing the student into the ICU. This would enable us to align ourselves with national policies and priorities. As part of this process of placing a student in the ICU setting we want to describe the facilitators and barriers that exist, as seen from the perspective of those involved in the process. The aim of the study is therefore to explore the experiences of the student, clinicians, academics and peers, with the placement of a student with a VI in the ICU.

How do you negotiate this environment when you can’t see very well?

The project will make use of a case study design that aims to describe the process of placing an undergraduate physiotherapy student with VI in an ICU setting as part of a clinical practice rotation. The case study will include data gathered from the student’s reflective clinical diary as well as in-depth interviews with the student, clinical supervisor, VI and clinical coordinators in the physiotherapy department at UWC, and the clinician who is responsible for overseeing the student in the ICU. Peers who have engaged with the student during the specific clinical placement will also be included, and will be identified during the process.

The interviews will be audio recorded and then sent away for transcription. The transcribed interviews will be anonymised and thematically analysed in order to determine themes related to barriers and facilitators that are relevant to the student’s learning. The transcripts – along with the analyses – will be shared with participants in order to ensure that the themes that emerged are consistent with the meaning that they had intended during the interviews.

curriculum ethics

Developing empathy in clinical education

This post was originally written for the Clinical Teacher iPad app, and can be downloaded there as well.


Empathy is the ability to understand the emotional context of other people and respond to them appropriately. It has been identified as the cornerstone of the clinician-patient relationship and is recognised as one of the most important characteristics of health care professionals that influence the patient’s outcomes and levels of satisfaction. However, even though it is clear that empathy is an essential aspect of clinical practice, there is evidence that empathy actually decreases as a result of medical education and clinical training. In fact, the greatest decrease in empathy seems to coincide with introduction of patient contact into the curriculum. If empathy really is valued in health care professionals, what changes need to take place in the health care curriculum in order to maintain the caring attitudes that students bring with them into their undergraduate training? How should clinical educators respond to the decline in empathy that seems to be a direct result of the clinical education process? This article explores the role of empathy in health care professional practice, as well as briefly identifies some strategies to further develop and maintain a caring attitude towards patients.

What is empathy?

Empathy is the action of understanding, being aware of, being sensitive to, and vicariously experiencing the feelings, thoughts and experiences of another human being, without having those feelings, thoughts and experiences communicated in an explicit manner. It is the capacity to share and understand another’s emotional state of mind and is often described as the ability to “put yourself into another’s shoes” (Ioannidou & Konstantikaki, 2008). In essence, empathy is the ability to understand the emotional makeup of other people and respond to them appropriately.

There are three types of empathy (Goleman, 2007):

  • Cognitive: knowing how another person feels and what they might be thinking
  • Emotional: physically feeling what another person is feeling
  • Compassionate: not only understanding a person’s situation and feeling with them, but being moved to help them

We can’t begin being empathetic when another person arrives. We have to already have made a space in our lives where empathy can thrive. And that means being open—truly open—to feeling emotions we may not want to feel. It means allowing another’s experiences to gut us. It means ceding control. Empathy begins with vulnerability. And being vulnerable, especially in our work, is terrifying. – Sara Watchter Boehner

See the video below for a presentation by Joan Halifax, a Buddhist who works with the terminally ill and those on death row, on the link between compassion and empathy.

Development of empathy in children

By the time that children are two years old they normally begin demonstrating empathy by responding emotionally to someone else’s emotional state. At this stage, toddlers will sometimes try to comfort others or show concern for them. Children between the ages of 7 and 12 appear to be naturally inclined to feel empathy for others in pain, a finding that is consistent with functional MRI studies of pain empathy among adults. Researchers have also determined that other areas of the brain were activated when young children saw another person intentionally hurt by another individual, including regions involved in moral reasoning (Goleman, 1995). The evidence seems to be that from a very young age, children are predisposed towards feeling an emotional response when confronted with another person’s suffering. This would seem to suggest that the emergence of empathy is an inherent characteristic of human development and which occurs spontaneously.

Empathy in clinical practice

Empathy, in the context of health care, is the “…ability to communicate an understanding of a client’s world” and is a crucial aspect of all interactions between clinicians and patients (Reynolds, Scott & Jessiman, 1999). It is the clinicians way of saying (Egan, 1986, pg. 99):

I’m with you, I’ve been listening carefully to what you’ve been saying and expressing, and I’m checking if my understanding is accurate.

It is considered to be an appreciation of the patient’s emotions and associated expression of that awareness to the patient. Empathy is also believed to significantly influence patient satisfaction, adherence to medical recommendations, clinical outcomes, and professional satisfaction. In the clinical setting, the common definition of empathy has been expanded to include emotive, moral, cognitive and behavioral dimensions (Stepien & Baernstein, 2006):

  • Emotive: the ability to imagine patients’ emotions and perspectives
  • Moral: the physician’s internal motivation to empathise
  • Cognitive: the intellectual ability to identify and understand patients’ emotions and perspectives
  • Behavioral: the ability to convey an understanding of those emotions and perspectives back to the patient

These additional features of empathy highlight that emotional engagement and not just intellectual understanding is an important aspect of effective empathy. However, some have suggested that the emotional aspect of empathy brings it closer to sympathy. Confusing the two is a conceptual challenge whereby the clinician actually experiences the other person’s emotions, as opposed to simply appreciating that they exist. This is problematic because when clinicians sympathise with patients and share their suffering, it may lead to decreased objectivity, emotional fatigue and subsequent burnout.

During medical education, we first teach the students science, and then we teach them detachment. To these barriers to human understanding, they later add the armor of pride and the fortress of a desk between themselves and their patients. – Howard Spiro

Decline in empathy during medical training

Empathy has been identified as one of the most important characteristics of medical professionals and is routinely screened for among students. However, while the development of empathy seems to be an essential aspect of positive health care relationships, there is some evidence that as medical students move through the curriculum, their scores on tests of empathy drop, with the largest decrease occurring at about the same time that they begin to see patients. Studies show that the empathy scores of students in their preclinical years were higher than in their clinical years. In addition, gender was a significant predictor of empathy, with women having higher scores on tests of empathy than men. Students with high baseline empathy showed a smaller decrease in empathy scores than students with low baseline empathy during medical education. Self-reported empathy for patients, which is potentially a critical factor in good patient-centered care, seems to wane as students progress in their clinical training, particularly among those entering technology-oriented specialties (Chen et al., 2012).

What we need in medical schools is not to teach empathy, as much as to preserve it – the process of learning huge volumes of information about disease, of learning a specialised language, can ironically make one lose sight of the patient one came to serve; empathy can be replaced by cynicism – Abraham Verghese

There are good reasons for the decrease in empathy, including the fact that students work in high-stress environments that place significant pressure on them with heavy workloads, intense time pressures and a diminished sense of autonomy in the healthcare system. In many health systems productivity is valued and rewarded financially and doctors who don’t see as many patients as their peers are sometimes seen as slow and inefficient.The stress of studying and working in the clinical environment may eventually take its toll on students and clinicians in terms of their time, and physical and emotional well-being, all of which make it difficult for them to be empathic. The focus on science and rationality during medical training tends to emphasise detachment and objective clinical neutrality, and prioritises the technologic over the humanistic. Trying to find the right balance can be tricky (Lim, 2013).

In addition, the focus of medical education seems to devalue the patient as a human being. We often talk about the “case” rather than the person. The style of writing is “objective” and impersonal, where that which can be seen is given more importance than that which can be heard. Often the patient is seen as a model, a body to be treated, or a good “teaching case” that illustrates a point (Shapiro, 1992). If we accept that decreased empathy as a direct result of participation in the medical curriculum is undesirable, we need to ask how we can address the problem.

We start with students who are very caring but have no diagnostic skills, and end up with physicians with great diagnostics skill but who don’t care. – Richard Frankel

Developing empathy in clinical education

It seems that empathy can be developed and it should therefore be possible to design a curriculum aimed at maintaining empathy during the third year of medical school. A curriculum where students are encouraged to discuss their patient reactions and emotional response in a safe environment during their clerkships may contribute to the preservation of empathy. Students can also be introduced to the idea that doctors can be taught that empathy is a skill that can be developed and maintained, as opposed to an inherent, unchangeable personality trait. Another strategy that can affect the development of empathy in students is the introduction of the Longitudinal Integrated Clerkship, which has been shown to have a positive impact on the patient-doctor relationship (Ogur et al., 2007).

An interesting perspective on developing empathy in medical education has also been to introduce modules that incorporate literature, movies, drama and poetry into the medical education curriculum. Some medical schools have gone so far as to integrate studies of the Humanities into their curricula, suggesting that the study of literature can help to achieve the following objectives (Shapiro & Rucker, 2003):

  • Stimulate skills of close observation and careful interpretation of patients’ language and behavior
  • Develop imagination and curiosity about patients’ experiences
  • Enhance empathy for patients’ and family members’ perspectives
  • Encourage relationships and emotional connections with patients
  • Emphasise a whole-person understanding of patients
  • Promote reflection on experience and its meaning

There is evidence that empathy and attitudes toward the Humanities in general improved significantly after participation in a literature-based module. In addition, students’ understanding of the patient’s perspective became more detailed and complex after the intervention. They were also more likely to note the ways in which reading literature might help them to cope with study-related stress (Shapiro et al., 2004).

Other strategies include interventions like role-playing and video analysis to try and preserve empathy during the challenging medical education process. Studies of these interventions, particularly the use of communication skill workshops, indicate that the behavioral dimension of empathy can be influenced through curriculum change (Stepien & Baernstein, 2006). In addition, programmes that aim to validate humanism in medicine (such as the Gold Humanism Honor Society) may reverse the decline in empathy (Rosenthal et al., 2011).

Studying the humanities may also be used to combat a perceived loss of empathy that may occur over the course of medical training. – Schwartz et al., 2009

It should be noted however, that current studies on empathy in medical students are challenged by varying definitions of empathy, small sample sizes, lack of adequate control groups, and variation among existing empathy measurement instruments (Stepien, 2006). Some of the empathy measures available have been assessed for research use among medical students and practising medical doctors. These studies have shown that empathy measures can be used as tools for investigating the role of empathy in medical education and clinical training. However, no empathy measures have been found with sufficient evidence of predictive validity for use as selection tools for entry into medical school (Hemmerdinger, 2007).

In the era of new health care policy and primary care shortages, research on empathy in medical students may have implications for the medical education system and admission policy for training institutions (Chen et al., 2012).

What we know matters, but who we are matters more. Being rather than knowing requires showing up and letting ourselves be seen. It requires us to dare greatly, to be vulnerable…Vulnerability is the birthplace of love, belonging, joy, courage, empathy, accountability, and authenticity. If we want greater clarity in our purpose or deeper and more meaningful spiritual lives, vulnerability is the path. – Brene Brown


There is clear evidence that empathy is an essential aspect of developing and maintaining effective clinician-patient relationships. However, there is also evidence to suggest that the process of clinical and medical education may actually lead to a decrease in empathy as a direct result of the way that clinical training is structured. Incorporating a range of strategies from the Humanities may help to maintain empathy in health care professional students, including using literature, poetry, art and music as ways for students to explore various aspects of empathic engagement. While it seems that the ability to measure empathy would have a significant influence on curriculum design, current studies of empathy have been criticised for a variety of reasons, indicating that stronger evidence is needed if we are to integrate the teaching and assessment of empathy in clinical education.


Chen, D.C., Kirshenbaum, D.S., Yan, J., Kirshenbaum, E. & Aseltine, R.H. (2012). Characterizing changes in student empathy throughout medical school. Medical Teacher, 34(4): 305-11. doi: 10.3109/0142159X.2012.644600.

Chen, D., Lew, R., Hershman, W. & Orlander. J. (2007). A cross-sectional measurement of medical student empathy. Journal of General Internal Medicine, October, 22(10): 1434-1438.

Ducharnme, J. (2013). Medical students diagnosed with low empathy. Boston Magazine.

Egan, G (1986). The skilled helper. Brooks-Cole, Monterey, CA.

Goleman, D. (1995). Emotional intelligence: Why it can matter more than IQ. Bantam Books. ISBN: 055338371X.

Hemmerdinger, J.M., Stoddart, S. & Lilford, R.J. (2007). A systematic review of tests of empathy in medicine. BMC Medical Education, 7:24, doi:10.1186/1472-6920-7-24.

Ioannidou, F., & Konstantikaki, V. (2008). Empathy and emotional intelligence: What is it really about? International Journal of Caring Sciences, 1(3), 118–123.

Lim, J. (2013). Empathy, the real measure of a doctor. Today Magazine.

Ogur, B., Hirsh, D., Krupat, E. & Bor, D. (2007). The Harvard Medical School-Cambridge integrated clerkship: an innovative model of clinical education. Academic Medicine, April, 82(4): 397-404.

Poncelet, A., Bokser, S., Calton, B., Hauer, K.E., Kirsch, H., Jones, T., Lai, C.J., Mazotti, L., Shore, W., Teherani, A., Tong, L., Wamsley, M. & Robertson, P. (2011). Development of a longitudinal integrated clerkship at an academic medical center. Medical Education Online, 16:10. Published online 2011 April 4. doi: 10.3402/meo.v16i0.5939.

Reynolds, W. J., Scott, B., & Jessiman, W. C. (1999). Empathy has not been measured in clients’ terms or effectively taught: A review of the literature. Journal of advanced nursing, 30(5): 1177–85.

Rosenthal, S., Howard, B., Schlussel, Y.R., Herrigel, D., Smolarz, G., Gable, B., Vasquez, J., Grigo, H. & Kaufman, M. (2011). Preserving empathy in third-year medical students. Academic Medicine, 86(3): 350-358.

Schwartz, A. W., Abramson, J. S., Wojnowich, I., Accordino, R., Ronan, E. J., & Rifkin, M. R. (2009). Evaluating the impact of the humanities in Medical Education. Mount Sinai Journal of Medicine, 76, 372–380. doi:10.1002/MSJ

Spiro, H. (1992). What is empathy and can it be taught? Annals of Internal Medicine, 116(10): 843–6.

Shapiro, J., Duke, A., Boker, J., & Ahearn, C. S. (2005). Just a spoonful of humanities makes the medicine go down: Introducing literature into a family medicine clerkship. Medical Education, 39(6): 605–12. doi:10.1111/j.1365-2929.2005.02178.x

Shapiro, J., Morrison, E., & Boker, J. (2004). Teaching empathy to first year medical students: evaluation of an elective literature and medicine course. Education for Health, 17(1): 73–84. doi:10.1080/13576280310001656196

Shapiro, J., & Rucker, L. (2003). Can poetry make better doctors? Teaching the humanities and arts to medical students and residents at the University of California, Irvine, College of Medicine. Academic medicine. Journal of the Association of American Medical Colleges, 78(10): 953–7.

Stepien, K.A. & Baernstein, A. (2006). Educating for empathy: A review. Journal of General Internal Medicine, 21(5): 524–530. doi: 10.1111/j.1525-1497.2006.00443.x

ethics pht402 social media technology

PHT402 Ethics course: Developing an online professional identity

This post was written for the participants of the #pht402 Professional Ethics course. For many of our participants working online has been a new and interesting experience but for most it will probably won’t progress much more than that. This post is intended to highlight how the blogs that have been created as part of the course can form the foundation of an online professional identity that can be carried forward as evidence of learning in a variety of contexts.

digital_identityIn an increasingly connected and digital world, it often seems that too much is happening, too quickly. Every week another online service, app or device is competing for your time and it can be overwhelming to decide where to focus your attention. Even in our professional lives as clinicians or academics, there’s an increasing sense that “being” online is important, even if we don’t know exactly “how” to be, or “where” to be. There is a move towards the sharing of clinical experiences and resources that can add value to your professional life, if the available services and tools are used effectively. The clinical context is so dynamic, complex and challenging that we owe it to ourselves, our colleagues and our professions to share what we know.

The Internet offers a perfect platform for this professional interaction, particularly through the use of social media. “Social media” is an umbrella term for a range of online services that facilitate the creation, curation and sharing of user-generated content. It is increasingly being tied in to mobile devices (i.e. smartphones and tablets) that make it easy to share many aspects of our personal and professional lives. Some examples of the types of technologies that come under this term are: blogs (like we’re seeing in this course), microblogs (e.g. Twitter), wikis (e.g. Wikipedia, Physiopedia), podcasts, discussion forums, virtual social worlds (e.g. Second Life), gaming worlds (e.g. World of Warcraft) and social networks (e.g. Google+ and Facebook). As you can see, the term “social media” covers a lot of ground, which is why it’s sometimes difficult to figure out what exactly someone means when they talk mention it.

While the main theme of this post is to highlight the benefits of creating and maintaining an online professional presence, bear in mind that it’s not enough to simply “be” online. The main advantage of having an online professional identity is that it allows you to interact and engage with others in your field. Twenty years ago, academics and clinicians could only rely on the (very slow) process of publication and citation to learn about changes in the field. Now, with the affordances that the web provides, crafting a professional online identity can happen very quickly. However, it’s the interaction and engagement through conversation and discussion that builds reputation and a sense of presence, rather than simply “being there”.

You might be feeling that this is all a bit overwhelming and that you don’t have possibly have the time to get involved with all of these services. And you’d be right. Try to think of this as a developmental process, one that is going to take time to evolve. You didn’t emerge from university as a fully-formed, well-rounded clinical practitioner or researcher. It took time for you to develop the confidence to engage with colleagues, to share your ideas and to contribute to professional dialogue. Establishing an online identity is no different.

Whether you decide to continue updating your blog, or to start tweeting, the point is that you start somewhere, and start small. As your confidence grows, you’ll want to begin experimenting with other services, integrating them with each other and building them into your workflow. This is the most crucial part because if you think of this as just another thing you have to do, or another place you have to go, you’ll find yourself resenting it. Build a foundation in one space at a time, and only use services and applications that you feel provide you with value.

In the beginning, you may feel more comfortable “lurking” on social media sites, listening to the conversation without really contributing. This is OK and is likened to a form of Wenger’s concept of legitimate peripheral participation. Over time, as you gain confidence you may begin to feel that you have something to say. This may be as simple as posting your own content (e.g. a tweet, a blog post, a status update), sharing the content of others, or agreeing / disagreeing with something that someone else has said. Whatever it is, don’t feel pressured to say something profound or clever. Just give your sincere input to the conversation.

In case you’re wondering if there are any rules or regulations in terms of using social media as a health care professional, that’s hard to say. Many organisations and institutions do have a set of policies that can inform practice when it comes to employees using social media, although it’s hard to say if these are rules or guidelines. One of the biggest difficulties is that as a health care professional, the public often perceives you as always being “on duty”. A physio is always a physio, whether you’re working or not, which makes it difficult to determine what is appropriate to share, and when. The following list of health-related social media policies may help you to tread the fine line between your personal and professional online identities.

Developing an online professional identity and presence is an essential aspect of modern scholarship and increasingly, clinical practice. Not only does it allow you to connect and engage with researchers, academics and other clinicians in your field of interest, but it helps to develop your professional reputation by giving you an international platform to share your work and your ideas.

There are many services and platforms already available, with more becoming available all the time. While it’s not necessary to have a presence and to participate in all possible online spaces, it helps to be aware of what is available and how the different services can be used in the development of your own professional identity. Finally, while developing a professional presence is advisable, be aware that what you share and how you share will have as much of an impact on whether your share or not. There are some guidelines that are particularly relevant for health care professionals and researchers, but even then, the area is under such rapid development that it’s difficult for institutional social media policies to keep up. If in doubt, always check with your employer and colleagues.

physiotherapy research social media technology

Design principles for clinical reasoning

graphic_design smallerClinical reasoning is hard to do, and even harder to facilitate in novice practitioners who lack the experience and patterns of thinking that enable them to establish conceptual relationships that are often non-trivial. Experienced clinicians have developed, over many years and many patients, a set of thinking patterns that influence the clinical decisions they make, and which they are often unaware of. The development of tacit knowledge and its application in the clinical context is largely done unconsciously, which is why experienced clinicians often feel like they “just know” what to do.

Developing clinical reasoning is included as part of clinical education, yet it is usually implicit. Students are expected to “do” clinical reasoning, yet we find it difficult to explain just what we mean by that. How do you model a way of thinking?

One of the starting points is to ask what we mean when we talk about clinical education. Traditionally, clinical education describes the teaching and learning experiences that happen in a clinical context, maybe a hospital, outpatient or clinic setting. However, if we redefine “clinical education” to mean activities that stimulate the patterns of thinking needed to think and behave in the real world, then “clinical education” is something that can happen anywhere, at any time.

My PhD was about exploring the possibilities for change that are made available through the integration of technology into clinical education. The main outcome of the project was the development of a set of draft design principles that emerged through a series of research projects that included students, clinicians and clinical educators. These principles can be used to design online and physical learning spaces that create opportunities for students to develop critical thinking as part of clinical reasoning. Each top-level principle is associated with a number of “facets” that further describe the application of the principles.

Here are the draft design principles (note that the supporting evidence and additional discussion are not included here):

1. Facilitate interaction through enhanced communication

  • Interaction can be between people and content
  • Communication is iterative and aims to improve understanding through structured dialogue that is conducted over time
  • Digital content is not inert, and can transform interactions by responding and changing over time
  • Content is a framework around which a process of interaction can take place – it is a means to an end, not an end in itself
  • When content is distributed over networks, the “learning environment” becomes all possible spaces where learning can happen
  • Interaction is possible in a range of contexts, and not exclusively during scheduled times

2. Require articulation

  • Articulation gives form and substance to abstract ideas, thereby exposing understanding
  • Articulation is about committing to a statement based on personal experience, that is supported by evidence
  • Articulation is public, making students accountable for what they believe
  • Articulation allows students’ thinking to be challenged or reinforced
  • Incomplete understanding is not a point of failure, but a normal part of moving towards understanding

3. Build relationships

  • Knowledge can be developed through the interaction between people, content and objects, through networks
  • Relationships can be built around collaborative activity where the responsibility for learning is shared
  • Facilitators are part of the process, and students are partners in teaching and learning
  • Facilitators are not gatekeepers – they are locksmiths
  • Create a safe space where “not knowing” is as important as “knowing”
  • Teaching and learning is a dynamic, symbiotic relationship between people
  • Building relationships takes into account both personal and professional development
  • Building relationships means balancing out power so that students also have a say in when and how learning happens

4. Embrace complexity

  • Develop learning spaces that are more, not less, complex
  • Change variables within the learning space, to replicate the dynamic context of the real world
  • Create problems that have poorly defined boundaries and which defy simple solutions

5. Encourage creativity

  • Students must identify gaps in their own understanding, and engage in a process of knowledge creation to fill those gaps
  • These products of learning are created through an iterative activity that includes interaction through discussion and feedback
  • Learning materials created should be shared with others throughout the process, to enable interaction around both process and product
  • Processes of content development should be structured according to the ability of the students

6. Stimulate reflection

  • Learning activities should have reflection built in
  • Completing the reflection should have a real consequence for the student
  • Reflection should be modelled for students
  • Reflections should be shared with others
  • Feedback on reflections should be provided as soon after the experience as possible
  • Students need to determine the value of reflection for themselves, it cannot be told to them

7. Acknowledge emotion

  • Create a safe, non­judgemental space for students to share their personal experiences and thoughts, as well as their emotional responses to those experiences
  • Facilitators should validate students’ emotional responses
  • These shared experiences can inform valuable teaching moments
  • Facilitators are encouraged to share personal values and their own emotional responses to clinical encounters, normalising and scaffolding the process
  • Sensitive topics should be covered in face­to­face sessions
  • Facilitators’ emotional responses to teaching and learning should be acknowledged, as well their emotional responses to the clinical context

8. Flexibility

  • The learning environment should be flexible enough to adapt to the changing needs of students, but structured enough to scaffold their progress
  • The components of the curriculum (i.e. the teaching strategies, assessment tasks and content) should be flexible and should change when necessary
  • Facilitators should be flexible, changing schedules and approaches to better serve students’ learning

9. Immersion

  • Tasks and activities should be “cognitively real”, enabling students to immerse themselves to the extent that they think and behave as they would be expected to in the real world
  • Tasks and activities should use the “tools” of the profession to expose students to the culture of the profession
  • Technology should be transparent, adding to, and not distracting from the immersive experience

We have implemented these draft design principles as part of a blended module that made significant use of technology to fundamentally change teaching and learning practices in our physiotherapy department. We’re currently seeing very positive changes in students’ learning behaviours, and clinical reasoning while on placements, although the real benefits of this approach will only really emerge in the next year or so. I will continue to update these principles as I continue my research.

Note: The thesis is still under examination, and these design principles are still very much in draft. They have not been tested in any context other than in our department and will be undergoing refinement as I continue doing postdoctoral work in this area.