Welcome to my next post in this series on building engagement in rehab. As you’ve probably begun to understand, I’m a huge believer in the behavioural aspects of neurological rehab and see huge benefits in addressing these properly if we’re to deliver effective evidence-based rehabilitation interventions.

In my last post, I introduced the ACT Now toolkit, which is a useful resource to support a person living with stroke to engage in, and sustain, meaningful physical activity. Within the ACT Now toolkit, there is a questionnaire looking at a person’s readiness for change using the stages of change model. The Act Now toolkit gives some strategies for identifying where a person is at in their readiness to engage in regular physical activity, from which you can identify barriers and enablers to facilitate behaviour change (using the COM-B). If you haven’t read my last post on this, you can find it here.

For this next post, I thought we would delve a little deeper into motivational interviewing and understanding the stages of change model (the transtheoretical model).

Just for some background on my experience with the stages of change model and motivational interviewing: I was really fortunate when I first starting working for Rehabilitation in the Home, that RITH had won a grant to deliver a large-scale motivational interviewing training program in 2012 and 2013. This was also used in conjunction with a service-wide goal-setting program, which involved several workshops facilitated by a clinical psychologist with expertise in motivational interviewing, as well as going through goal setting with Lynne Turner-Stokes, particularly using the Goal Attainment Scale. This was revolutionary to my practice, and I apply motivational interviewing principles in all aspects of my rehab, from therapy planning to goal setting, problem solving, home exercise programs, you name it.

But enough about me and back to the post.

The Stages of Change model allows you to identify where a person currently sits with respect to engaging in rehab, from which you can use motivational interviewing strategies to help them to move towards the next stage. There are five (or six if you include relapse/termination) stages of change outlined within model.

1. Pre-contemplation

   1. A person has no intention to change

   2. They might be unaware or dismissive of the problem, or

   3. The negatives of changing are outweigh any perceived benefits

2. Contemplation

   1. The person acknowledges there is a problem and is considering change in behaviour

   2. They are weighing up the pros and cons of behaviour change

3. Planning

   1. Begin small steps such as planning, researching, and setting goals

   2. Getting ready to take action and to change behaviour

4. Action

   1. Actively modifying their behaviour in line with agreed-upon goals or recommendations

5. Maintenance

   1. The behaviour is now a habit, and there’s sustained change

People can sit at different stages for different behaviours. For example, you might have someone who’s in the action stage of medication compliance but in the pre-contemplation stage of physical activity. I want to highlight, though, that the stages of change model merely a reflection of where they sit in response to that specific behaviour, not their personality.

Before you think that there’s no role for motivational interviewing in your clinical practice, just think of these scenarios, which I’m sure you’ve encountered or heard of in your own clinical practice or discussion with colleagues:

• You’ve got two patients, both with similar levels of disability.

  • One: engages in everything during therapy, does all their extra practice, is in the gym for independent practice, and they do so much of their home program both by themselves and with family.

  • The other: comes to the gym reluctantly, with not much practice outside of that, and generally seems quite disengaged.

• Your client has funding for an extensive amount of therapy, but there’s no engagement in therapy in practice outside of therapy, and they’re not making any progress. They’re seeing you because they HAVE funding for therapy, not because they WANT therapy.

• Your client is more focused on maximising their funding for their next NDIS plan rather than focusing on becoming as independent as possible. (Becoming more independent may lead to a loss of funding.)

So what’s wrong in these scenarios?

• Is it all the person’s fault that they’re not willing to engage?

• Are we wasting our time trying to deliver therapy to these people when it could be used on more people who are more motivated and likely to improve?

• Or do we just keep delivering therapy knowing that they’re funded for it? You can still bill for it, and the person will still keep coming. (Although how rewarding is that for us as clinicians? And that’s not even considering the ethical aspects of it.)

In reality, in all of these scenarios, that person is in the pre-contemplation stage in respect to engaging in rehabilitation. Trying to do neuro rehab (i.e., physical exercises, gait training, balance training, etc.) should not be the priority in this situation. Our input should focus on how we shift them from pre-contemplation into the preparation and action phases.

Before putting the blame on your client, we must remember to recognise that neuro-rehab is really tough. We’re asking people to exercise for hours a day when life is already hard.

And that’s where we come in. I think what’s really understated is the therapist’s capacity to motivate the person they’re working with to engage in rehab.

Once you’ve identified what stage a person is currently sitting in, we can use our skills as clinicians, along with motivational interviewing strategies, to build long-term behavior change and engagement in their rehabilitation programs.

Motivational interviewing strategies will be the focus of the next post, and I’ll be talking more in depth about that there.

With that, thanks for reading.

Ashan

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So, this is the first post in a new series, where I want to move from the theory into the practical on building engagement in rehab. I’m a clinician at heart, and I’m going to walk through tools and strategies that I actually use- not just research examples of using behavioral frameworks which are incredibly difficult for the average clinician to implement.

One example I’d love to share with you, which uses behavioural theory to build engagement, is the ACT Now toolkit.

Where this toolkit came from

ACT Now was developed by Dr Tamina Levy and her team at Flinders University and the Southern Adelaide Local Health Network. The problem Tam was trying to solve is one every neuro clinician will recognise: poor long-term adherence to physical activity and exercise after stroke. We send people home with a program and then adherence drops away once our involvement ends.

This is a well-known issue. Adherence to physical activity after stroke is poor, and the research linking adherence exercise with functional outcomes is strong. Tam, with a background in implementation science, recognised that improving adherence means changing behaviour, and that behaviour change requires more than handing someone a sheet of exercises and wishing them luck.

The development of this toolkit was extensive. It started with a systematic review of existing adherence toolkits for chronic conditions, which found that nothing recommended a clear toolkit design, and that nothing existed specifically for stroke survivors. From there, surveys and focus groups explored what stroke survivors, carers, and health professionals actually believed and experienced around exercise adherence. A stakeholder working group reviewed those findings and shaped the toolkit’s development, and then it went through piloting with both clinicians and stroke survivors before it was finalised. This is not a toolkit assembled from a literature review and good intentions. It went through the kind of process we’d expect from any properly developed clinical resource, with co-design at its heart.

Why COM-B sits at the centre of it

ACT Now is built on the COM-B model, the same framework I’ve been writing about in this series. For a behaviour to change, we need to understand a person’s capability, opportunity, and motivation related to that behaviour. What I like about the COM-B being embedded in this toolkit is that it can actually structure the conversation you have with your client.

The toolkit doesn’t stop at COM-B either. It sits the model within a broader flow that starts with motivational interviewing and incorporates the stages of change model, so you’re not just identifying barriers, you’re meeting the person at the stage of readiness they’re actually at. (We’ll come back to motivational interviewing properly in a future post in this series, because it’s an area I care about a great deal, but for now it’s worth knowing it’s there as the entry point.)

How it actually works

The toolkit opens with an initial conversation, guided by a motivational interviewing approach and a quick five-question assessment to get to know the person. From there, you’re assessing readiness using a stages of change questionnaire, which places someone from precontemplation through to maintenance, with a sixth stage covering relapse that’s easy to forget about (but important if you’re working with anyone over an extended period).

I think the real strength is the COM-B assessment tool. It gives you a structured way to ask what’s actually getting in the way. The lead-in question is simple: when it comes to doing this amount of activity, what would it take for you to manage it? From there the person identifies specific barriers across the capability, opportunity and motivation domains, with concrete prompts to guide the discussion. Not having the time or money to get to a gym sits under opportunity. Not knowing how to be more active sits under capability. Not believing exercise is worth doing sits under motivation. This is the COM-B model doing exactly what it should, helping you see that adherence problems are rarely just about whether someone wants to do something.

From there the toolkit moves into specific change strategies, things like prompting, self-monitoring, personalised messaging and goal setting, matched to whatever stage of change the person is at. There’s a SMART goal-setting process and a full action plan covering who, what, when, where, with whom and for how long, plus the obstacles that are likely to come up and the strategies to deal with them. The plan is signed off by the client, which gives it something close to the structure of a behavioural contract, a tool I have a lot of time for and could (and will) probably write an entire post on by itself.

What this tells us about implementation science in practice

I think the real value of ACT Now isn’t just that it’s a good toolkit, although it is. It’s what it demonstrates about taking implementation science out of the research setting and putting it directly into clinicians’ hands. The history of behaviour change research in rehabilitation has tended to produce findings that are difficult for the average clinician to translate without significant additional resources and research expertise. ACT Now was designed by someone who understood the theory deeply enough to build it properly and then developed and tested it with the people who’d actually have to use it.

I’ve used this toolkit with my own clients, and I was fortunate enough to be involved in some of its development (which is how I know about it). It’s one of the clearest examples I can point to of implementation science being clinician-led rather than clinician-facing, and that distinction matters more than it might first appear. A massively useful tool for us clinicians to use in our practice!

Where this is going next

This is the first post in what I’m planning as an ongoing series on building patient engagement in neurorehabilitation, looking at the tools and strategies that translate behaviour change theory into something usable in everyday practice. Next, I want to properly unpack motivational interviewing, because so much of what makes ACT Now work depends on how that initial conversation is handled, and it deserves its own dedicated treatment rather than a passing mention.

With that, thanks for reading!

Ashan

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My earlier posts looked at why clinicians and services struggle to deliver evidence-based neurological rehabilitation. We used the Theoretical Domains Framework to map therapist factors: knowledge, skills, and beliefs; and institutional factors: resources, leadership, culture, and funding. That analysis is useful, but it only tells part of the story.

In one of my earlier papers, we identified patient factors as another important layer of the picture. Even when a clinician has the skills and the service has the resources to deliver an evidence-based intervention, it’s the patient’s own factors that can determine whether that intervention is taken up, persisted with, or quietly abandoned. And yet in clinical practice, we often reduce this to a motivation problem. The patient isn’t ready. They’re not trying. They don’t understand the importance. The reality is more complicated than that.

This is the final piece on my introductory series on implementation science before we get into some more practical territory, which will include building patient engagement and motivation, goal setting, the transfer package, and then a closer look at how implementation science applies to specific neurological interventions. Here, I want to lay some further foundations in implementation science by viewing patient factors through the lens of the Capability, Opportunity, Motivation- Behaviour (COM-B) model. I used this behavioural framework in my qualitative study investigating stroke survivor and carer experiences of CIMT (Weerakkody, Godecke & Singer, 2024), as part of my PhD.

The COM-B model sits at the hub of the Behaviour Change Wheel (Michie, van Stralen & West, 2011; Michie, Atkins & West, 2014). It proposes that for any behaviour to occur, three conditions need to be in place:

1. The person needs the Capability - the physical and psychological capacity to perform the behaviour.

2. They need the Opportunity - what the physical environment provides, and what the social context enables.

3. They need the Motivation - both the conscious, deliberate side and the emotional, habitual side.

For those already using the TDF in practice, the COM-B organises those fourteen domains into a higher-order structure. It provides useful starting point for understanding patient behaviour before deciding what to do about it. Each subcomponent below. The aim of this article isn’t to be exhaustive, but to show that patient engagement in neurological rehabilitation is multi-factorial, and that identifying which COM-B component is the operative barrier points you toward a different category of response.

Physical Capability

Physical capability is about what the body can do. Think: strength, endurance, and the motor skill required to perform a behaviour, but also the ways that pain and fatigue negatively influence this. In neurorehabilitation, the impairment itself is the obvious starting point, but secondary physical factors are often what actually determines whether participation is possible day to day.

In my research on the acceptability of CIMT in an early-supported discharge service, fatigue was one of the most consistently reported barriers (Weerakkody, Godecke & Singer, 2024). Coming home from hospital significantly increased the physical demands on stroke survivors. The activities that had previously been managed on the ward were now their responsibility, and that cumulative load left some participants with very little capacity remaining for an intensive upper limb program. Shoulder pain in the stroke-affected arm was a further confounding factor. Those participants were not less motivated than others, they were more physically constrained. And those are not the same problem.

Psychological Capability

Psychological capability is about the knowledge, beliefs, and cognitive frameworks that allow someone to make sense of and engage meaningfully with a behaviour. In rehabilitation, this means not just whether a patient has received information about their condition, but whether they have the conceptual frameworks to make sense of what treatment is actually asking of them, the cognitive skills to learn and problem-solve across sessions, and the mental stamina to sustain that engagement over what are often long and demanding programs. This is more complex for neuro rehab in particular. Many of the conditions we treat directly affect the cognitive resources that psychological capability depends on. Attention, memory, processing speed, and cognitive fatigue may all be compromised. A stroke survivor with significant cognitive fatigue might not retain what was discussed in a session. A person with a TBI may have limited insight into their own deficits, making self-directed practice difficult to sustain. These are psychological capability problems rather than motivation ones, and they need a different response.

Physical Opportunity

Physical opportunity is what the environment actually makes possible, such as the equipment, time, structure, and physical cues that enable a behaviour to happen. This is relevant when trying to translate practice from clinic sessions to home outside of scheduled therapy. Are there safe spaces to practice? Does the person have the relevant equipment required? Are they trying to fit in employment, parenting and other life roles alongside rehabilitation? This is a domain clinicians commonly underestimate, and poor engagement outside of therapy may be due to the environment rather than motivation.

Social Opportunity

Social opportunity refers to the interpersonal context that shapes whether behaviours are supported and feasible, such as the influence of family, carers, culture, and the dynamics of the clinical relationship. A clear example is the person who needs support to carry out their home exercise program or reminders to engage in self-directed practice. Here, the influence of family and carers is crucial in shaping behaviour toward agreed-upon goals.

Reflective Motivation

Reflective motivation is the deliberate, conscious side of motivation. These are the person’s goals, intentions, and beliefs about what is worth pursuing. Most clinicians think about patient engagement primarily through this lens, which is reasonable as a starting point, but it’s incomplete on its own. For reflective motivation to be sustained, patients need a clear and shared understanding of what they’re working toward and how they’ll know when they’ve made progress, along with agreed upon metrics for success. Without that clarity, reflective motivation is difficult to maintain. The answer is usually not more encouragement. It’s a clearer shared framework from the outset.

Automatic Motivation

Automatic motivation operates below the level of conscious deliberation. It includes emotional responses, habitual patterns, desires, and avoidance tendencies that shape behaviour without being planned. This is the domain clinical practice most consistently overlooks, because it doesn’t respond to the tools we tend to reach for first, such as education, goal setting, written plans.

Where This Series Is Heading

As you can see, the six subcomponents of COM-B give us a richer way of understanding the complex interplay between individual capabilities, contextual opportunities, and motivational factors that influence engagement in rehabilitation. Framing patient factors this way is far more useful than defaulting to “the patient isn’t motivated”, because it tells us where to look, and more importantly, what to do.

Future articles will get into the practical tools that target these subcomponents: motivational interviewing, goal setting, and the transfer package. These are, in COM-B terms, the behaviour change strategies we have available for working with the motivational domains in particular.

Alongside that, I’ll also be starting a “My Favourite Papers” series — sharing the papers that have genuinely changed the way I think about and deliver neurological rehabilitation, and how implementation science fits within that. I’m looking forward to that one.

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As always, thanks for reading.

Ashan

References:

Michie, S., et al. (2011). “The behaviour change wheel: A new method for characterising and designing behaviour change interventions.” Implementation Science 6: 42.

Michie, S., et al. (2014). The Behaviour Change Wheel: A guide to designing interventions. Great Britain, Silverback Publishing

Weerakkody, A., et al. (2024). “Translating acceptability to sustained delivery: Clinician and manager perspectives on implementing modified constraint-induced movement therapy in an early-supported discharge rehabilitation service.” Aust Occup Ther J 72(1).

This post focuses on institutional factors. I’m talking about the organisational, policy, and structural determinants that shape whether evidence-based neurological rehabilitation is delivered at scale in the real world. Using the Theoretical Domains Framework (TDF) as a lens, I want to explore how the environments in which clinicians work can become barriers to the care they are trying to provide, BUT also how those same environments can be structured to actively enable it.

Let’s be honest... The institutional landscape for neurological rehabilitation in Australia is under genuine strain, and I do not think we serve clinicians or patients well by pretending otherwise. But strain is not the whole story. There are services, organisations, and leaders doing this well, and understanding what they are doing differently is just as useful as understanding what goes wrong.

So with that, this piece will outline some current issues I’ve seen in neurological rehabilitation and demonstrate how these real-life examples map to the TDF.

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Acute care crowding out rehabilitation

Public health systems face an uncomfortable structural reality. Acute hospitals, emergency departments, and surgical services capture political attention, media coverage, and funding priority in ways that rehabilitation does not. When health system budgets tighten, rehabilitation services are frequently asked to absorb the impact first.

In Australia, this is not hypothetical. Over the course of the CIMT implementation program I conducted within Rehabilitation in the Home (RITH), a large early-supported discharge service in Perth, referrals to the service increased by 49% over the study period — yet staffing grew by just 3% in the same timeframe [1]. New service models were introduced, caseloads expanded, and clinicians were increasingly expected to manage more acute and complex patients with the same or fewer resources. The context-specific CIMT protocol we developed had been designed to fit the service as it existed in 2018 [2]. By 2021, that service looked very different.

This pattern is not unique to RITH. Across Australian public health, resources are being redirected toward acute services in response to growing demand, while community-based rehabilitation operates with constrained funding and limited capacity to implement new evidence-based programs. When rehabilitation is positioned as a lower-tier priority, the downstream effects are predictable: reduced staffing, less time for clinical supervision, fewer opportunities for skill development, and a service culture where productivity targets dominate over quality improvement.

TDF domains implicated: barriers

Environmental context and resources is the most obvious domain here, and it is worth being specific about what resource deprivation actually means for implementation. It is not simply that clinicians lack equipment, although that also matters. It means that the staffing ratios, session lengths, and organisational infrastructure required to deliver complex interventions are absent or inadequate. Implementing CIMT, for example, requires interdisciplinary collaboration, joint home visits, protected time for training, and a manageable caseload. When referrals increase by almost 50% with no corresponding staffing increase, every one of those conditions becomes harder to meet.

Goals operates more subtly but is equally important. In a service under pressure, the immediate goal becomes seeing enough patients to manage the caseload. This inevitably crowds out longer-term goals such as skill development, quality improvement, or the sustained implementation of a complex intervention. Clinicians do not abandon their values; they deprioritise them because the environment makes it impossible to act on them consistently.

Social influences are shaped by this dynamic in ways that accumulate over time. When a service operates in survival mode and the organisational message, explicitly or implicitly, is that throughput matters most: the social norms within teams shift accordingly. Implementing something new, or something that takes more time and coordination than usual care, begins to feel like a deviation from what the team expects rather than an expression of professional responsibility.

Reinforcement is undermined when resource constraints prevent clinicians from completing programs with adequate fidelity to observe meaningful outcomes. If clinicians attempt to deliver a complex intervention in a depleted environment and the results are disappointing (because the dose was insufficient, the support was absent, or the patient withdrew due to logistical barriers), they are less likely to try again. The intervention becomes associated with difficulty and failure rather than benefit.

TDF domains implicated: enablers

Not all services are trapped in this dynamic, and the differences between those that manage to implement well despite resource constraints and those that do not are instructive.

Organisational commitment and leadership support operate through the TDF domain of social/professional role and identity and social influences. In the RITH service, the managers who actively endorsed CIMT and made it clear that delivering evidence-based upper limb rehabilitation was a professional expectation, had a measurable effect on adoption rates at their sites [1]. Clinicians in those teams were more likely to offer the intervention, more likely to seek training, and more likely to persevere when they encountered patient or logistical challenges. Leadership does not compensate for insufficient staffing, but it shapes the social norms within which clinicians make decisions, and those norms matter.

Protected time for clinical supervision and professional development, even modest amounts, dramatically changes what is possible within environmental context and resources. Services that have deliberately structured caseload management to allow joint visits, peer observation, and regular case discussion report better implementation outcomes than those that treat clinical supervision as an add-on contingent on spare time. When organisations treat supervision as a core operational function rather than a luxury, clinicians develop the skills and confidence to deliver complex interventions even in resource-constrained environments.

Audit and feedback mechanisms engage the TDF domain of reinforcement in the opposite direction to the barrier described above. Services that systematically collect data on which patients are eligible for evidence-based interventions, how many are offered them, and how many receive them create a visible accountability structure that reinforces implementation behaviour. In our process evaluation, audit and feedback was identified as one of the most powerful enablers of sustained CIMT delivery [1, 3]. It was also one of the most underutilised, primarily due to time constraints and the logistical difficulty of accessing medical records across multiple sites. Where it was deployed, even on a single occasion, it prompted tangible changes in clinical practice.

The NDIS funding crisis and its consequences for complex neurological rehabilitation

The National Disability Insurance Scheme was designed as a transformational investment in Australia’s disability sector. For many people with neurological conditions: acquired brain injury, spinal cord injury, progressive neurological disease, stroke; it has provided access to allied health services that simply did not exist before. That access has been genuinely life-changing for many participants.

But the scheme is under severe and growing strain. Physiotherapy price limits were frozen for five consecutive years, and from July 2025, the NDIA implemented a $10 per hour reduction in physiotherapy rates (or almost $40 per hour for those in some states), bringing the rate to $183.99 per hour. This was alongside a 50% reduction in travel reimbursement and the removal of rural and remote price loadings. These decisions were made without meaningful consultation with the allied health sector and against a backdrop of rising operational costs, inflation, and extraordinary care complexity.

The consequences are already being felt. Allied health services have exited the NDIS market following the most recent pricing decision. Profit margins are below sustainable levels with many providers reporting operating at a loss. Providers in regional and remote areas, who typically deliver therapy in participants’ homes across large geographic areas, face the greatest pressure. Eight allied health peak bodies issued a joint statement describing the changes as financially unsustainable and a direct threat to participant safety.

For neurorehabilitation specifically, the implications are significant. Neurological conditions are among the most complex and resource-intensive presentations in the NDIS. Delivering best-practice care: whether that is intensive upper limb training, gait retraining, cognitive strategy training, or managing long-term complications, all require time, expertise, and a multidisciplinary team. When pricing does not reflect that complexity, providers are forced to make difficult choices: reduce clinical time, eliminate supervision, stop accepting NDIS referrals, or exit the scheme entirely.

TDF domains implicated: barriers

Environmental context and resources in the NDIS context takes on a particular character. The resource constraint here is not primarily about equipment, it is about time. Pricing that does not reflect the complexity of neurological presentations forces clinicians to compress sessions, reduce frequency, or eliminate non-face-to-face activities such as case coordination, interdisciplinary liaison, and documentation. For complex interventions that depend on dose and frequency to produce meaningful neuroplastic change, compressed clinical time directly compromises effectiveness.

Skills deteriorate when investment in professional development is removed. Clinical skill in complex neurological rehabilitation must be actively maintained through practice, supervision, and exposure to a range of presentations. When NDIS pricing makes clinical supervision economically unviable and continuing professional development is eliminated from organisational budgets, clinicians’ skills do not simply plateau, they erode.

Beliefs about capabilities: a clinician’s confidence in their own ability to deliver an intervention effectively is closely linked to skill maintenance. Clinicians who have fewer opportunities to deliver complex interventions, observe expert peers, and receive feedback on their practice report lower confidence over time. In our research, interdisciplinary collaboration was one of the most powerful enablers of confidence [3]. When funding models make that collaboration economically unviable, this enabler disappears.

Social/professional role and identity is disrupted when an organisation’s survival becomes its primary focus. Clinicians who enter neurological rehabilitation with a strong sense of professional identity, a belief that their role is to deliver effective, evidence-based care, experience significant psychological strain when funding models force them to compromise that identity. The result is not just dissatisfaction, but a gradual erosion of the professional values that motivate high-quality practice.

TDF domains implicated: enablers

Despite the funding pressures, there are organisational strategies that protect the conditions required for evidence-based practice.

Interdisciplinary collaboration and shared workloads, where organisational structures actively support joint delivery of complex interventions, engage beliefs about capabilities and environmental context and resources simultaneously. In the RITH service, CIMT programs delivered collaboratively by physiotherapists, occupational therapists, and therapy assistants were more likely to be completed with full protocol fidelity than those delivered by a single clinician. Shared delivery reduced the individual burden, increased session frequency, and created a team accountability structure that reinforced consistent practice. Organisations that deliberately build interdisciplinary workflows into their service model, rather than treating collaboration as an informal arrangement, create structural conditions that enable evidence-based practice to survive resource constraint. I should acknowledge the additional challenges associated with the fragmented service provision across private services, but greater communication and collaboration can still be viable strategies.

Organisational advocacy and professional identity can also operate as enablers through social/professional role and identity. Services and clinical leaders that publicly advocate for appropriate funding; through peak bodies, professional associations, and direct engagement with policymakers, contribute to a broader culture in which evidence-based practice is positioned as a professional expectation and a policy priority. The joint statement issued by eight allied health peak bodies in response to NDIS pricing decisions in 2025 is an example of this, and I know the APA have invested significantly in government advocacy ahead of the upcoming NDIS pricing guide. Collective professional advocacy does not immediately reverse pricing decisions, but it creates a clear public record of what evidence-based neurological rehabilitation actually requires, and it strengthens the professional identity of clinicians working under pressure.

Technology and cognitive load

There is something deeply ironic about the way technology is reshaping clinical work. The tools designed to make healthcare more efficient: electronic medical records, digital workflows, reporting systems, communication platforms, have in many cases added substantially to the cognitive burden on clinicians, rather than reducing it. And that’s before we even start on AI!

In the RITH service, we observed this directly. During 2021, the organisation commenced a large-scale implementation of a new ICT solution to manage referrals, workflows, and patient flow. This was a genuine service improvement initiative. But it required multiple clinical champions per site to learn complex new systems and train their colleagues. Many of whom were the same clinicians we had identified as mCIMT champions. The result was that mCIMT implementation momentum stalled, not because clinicians had lost interest, but because their finite capacity for change had been absorbed by something else.

Managers in our focus groups captured this precisely. One described her team as having “so many systems and processes” that “it’s actually very hard to remember to do something. So, you kind of do have to make it common sense or a clear role, otherwise it will fall off.” [3]

The broader trend is accelerating. Artificial intelligence tools, digital documentation requirements, telehealth platforms, outcome measurement software, and increasingly complex EMR systems are all demanding attentional resources from clinicians who are already operating at or near capacity.

TDF domains implicated: barriers

Memory, attention, and decision processes is the domain most acutely affected by cognitive overload. Evidence-based practice is not automatic. It requires clinicians to consciously recall eligibility criteria, intervention protocols, outcome measures, and decision-making processes at the point of clinical contact. When cognitive bandwidth is consumed by navigating new technology and competing administrative demands, the working memory available for evidence-based clinical reasoning is reduced. Clinicians revert to habitual practice, not because they have forgotten the evidence, but because deliberate decision-making requires cognitive resources that are no longer available.

Behavioural regulation is similarly compromised. Sustaining a new clinical behaviour requires ongoing self-monitoring, reflection, and adjustment. In a working environment crowded with technology change and administrative burden, the space required for reflective practice diminishes, and with it the capacity to maintain new clinical behaviours.

Emotions plays an important role here that is sometimes overlooked. Technology change can generate frustration, anxiety, and a sense of loss of control. These emotional responses directly influence motivation, confidence, and the willingness to engage with additional change, even when that change is clinically valuable.

Intentions, the conscious commitment to perform a specific behaviour, are also undermined by competing demands. Even a clinician who has formed a genuine intention to offer an evidence-based intervention may fail to act on it when they arrive at the clinical setting and find their attentional resources already depleted. Implementation intentions (specific if-then plans tied to environmental cues) are far more likely to survive a cognitively demanding environment. Without those structured cues, even well-motivated clinicians default to routine.

TDF domains implicated: enablers

Technology is not inherently an implementation barrier. When designed thoughtfully and introduced with adequate support, it can actively enable evidence-based practice.

Clinical decision support tools and prompts embedded within EMR systems engage memory, attention, and decision processes in a positive direction. Flagging eligible patients at the point of referral, prompting eligibility screening at intake, and embedding outcome measurement tools into routine documentation reduce the cognitive effort required to initiate evidence-based interventions. In our RITH implementation, adding an CIMT flag to the intake process was identified as one of the most practical and low-cost strategies for increasing adoption. It worked not by adding to clinician load but by reducing it; the decision cue was built into the workflow rather than left to individual memory.

Sequencing and pacing of change is an organisational strategy that protects behavioural regulation and emotions. Services that deliberately stagger implementation priorities reduce the cognitive competition that disrupts adoption. The conflict we observed between CIMT implementation and ICT rollout in RITH could not have been entirely avoided, but more deliberate sequencing and explicit protection of CIMT champions from competing change roles would have mitigated its impact. Organisations that recognise the finite nature of change capacity, and plan accordingly, create conditions in which individual improvement initiatives are far more likely to succeed.

Failing to de-implement ineffective practices

Implementing evidence-based practice is only half the challenge. The other half is stopping what does not work, and that is a conversation the rehabilitation community is only beginning to have.

Clinicians’ time is finite. When ineffective or low-value interventions continue to be delivered alongside new evidence-based approaches, they compete for the same limited resource. In neuro rehab, this is a genuine issue. Passive modalities, compensatory strategies applied without therapeutic intensity, and interventions that have consistently failed rigorous evaluation continue to occupy session time in many services. The reasons are understandable. Habits are hard to break, patients expect familiar treatments, and de-implementation requires just as much deliberate effort as implementation. But, the consequence is that evidence-based interventions are crowded out before they gain traction.

TDF domains implicated: barriers

Social/professional role and identity is perhaps the most underappreciated barrier to de-implementation. Stopping an intervention that has been part of a clinician’s practice for years carries identity implications. Clinicians who have used a particular approach throughout their career may experience the suggestion that it is ineffective as a challenge to their professional competence and to the value of the care they have previously provided. In team environments, this resistance is amplified: de-implementing a widely used approach challenges shared professional norms, and navigating that challenge requires careful facilitation and leadership. We need better language and strategies in addressing this issue, otherwise we risk alienating a bunch of dedicated clinicians who will just double-down on their approach and dismiss evidence-based practice as not living in the real-world.

Beliefs about consequences operates powerfully here. Clinicians may hold beliefs that stopping a familiar treatment will result in worse patient outcomes, even when the evidence does not support this. In complex neurological populations, where individual responses to treatment are genuinely difficult to predict, this conservatism is understandable. But it represents a significant barrier to the reallocation of clinical time toward evidence-based alternatives.

Intentions are directly implicated. Forming an intention to stop doing something familiar is psychologically different from forming an intention to adopt something new. Stopping requires a conscious and repeated decision to override an ingrained habit, often in the middle of a busy clinical session, without an external prompt or reminder.

Environmental context and resources connects to de-implementation in ways that are less obvious but equally important. Many low-value interventions persist because the systems within which clinicians work continue to support them: equipment remains available, session plans are structured around familiar treatments, and outcome measures do not distinguish between time spent on effective and ineffective components of care. De-implementation requires actively redesigning these environmental structures.

Knowledge is also implicated. What is often absent is specific, actionable knowledge about which components of current practice should be discontinued and what should replace them. Identifying an ineffective intervention without providing a clear and feasible alternative creates a knowledge gap that many clinicians resolve by continuing what they know.

TDF domains implicated: enablers

Organisational audit processes that make the distribution of clinical time visible. Breaking down what proportion of sessions are spent on which interventions engage environmental context and resources and behavioural regulation as enablers. When clinicians and managers can see clearly how clinical time is being allocated, conversations about de-implementation become grounded in data rather than perception. This is more likely to result in deliberate, managed reallocation of clinical effort than relying on individual clinicians to make these decisions in isolation during busy clinical days.

Leadership endorsement and explicit clinical governance around de-implementation addresses social/professional role and identity by repositioning the act of stopping an ineffective practice not as a criticism of past care but as an expression of professional responsibility and intellectual honesty. Services led by managers and senior clinicians who frame de-implementation as a mark of clinical rigour create cultures in which the evidence base is treated as a living document, and practice evolves accordingly.

What this means in practice and why the TDF matters

Having worked through barriers and enablers across these institutional themes, I want to step back and address a question that some readers may be asking: why bother with a framework like the TDF at all? Why not simply identify a problem and try to fix it?

The answer lies in what happens when we do not use a framework, and what decades of failed implementation attempts in healthcare tell us about the limits of intuition-based change.

The most common approach to implementation in rehabilitation services has historically been education. Identify a practice gap, deliver a training session, and assume that knowledge will translate into behaviour. This approach has been tried repeatedly, evaluated rigorously, and is NOT EFFECTIVE [4]. In my own experience, the first attempt to increase CIMT delivery in the RITH service: two education sessions delivered to over thirty clinicians, produced no measurable change in practice twelve months later. Education was there. The behaviour change was not.

The reason is that knowledge is only one of many determinants of behaviour. A clinician who: knows that CIMT is evidence-based but lacks the skills to deliver the transfer package; works in a team where the social norms do not support intensive upper limb therapy; is managing a caseload that leaves no time for joint visits; and has never been reinforced for attempting a complex new program: well, that clinician is not going to change their practice because of a training session.

The TDF matters because it provides a systematic, theory-informed structure for identifying which determinants are actually operating in a given context, across all of the relevant domains. When we map barriers and enablers to the TDF, we stop guessing about what is preventing implementation and start identifying it with specificity. We can see that the barrier is not primarily knowledge but confidence. Or not primarily confidence but access to peer modelling. Or not primarily peer modelling but the competing cognitive demands of a simultaneous technology rollout.

That specificity matters, because different determinants require different strategies. Confidence is addressed through supervised practice and graduated exposure, not through more education. Cognitive load is addressed through environmental redesign and decision cues, not through motivational messaging. Social norms are addressed through leadership endorsement and communities of practice, not through individual training. The TDF, used systematically, allows us to match the strategy to the actual problem. That matching is what separates implementation programs that produce sustained behaviour change from those that produce a temporary increase in knowledge and nothing else.

For clinicians, the practical value of this framework extends beyond formal research and implementation programs. It provides a structured way to think about your own practice setting, to evaluate why a particular evidence-based intervention is not being delivered consistently, and to identify which behaviour change strategies are most likely to make a difference. Is the barrier that clinicians do not know how to deliver the intervention? Then the strategy is training and supervised practice. Is it that the team does not value it? Then the strategy involves social influence and leadership endorsement. Is it that the environment does not support it? Then the strategy requires organisational change, adjusted caseloads, protected time, or redesigned workflows.

The TDF does not make implementation easy. The barriers described in this post are real, and some of them are not resolved by a framework alone. They require policy change, investment, and institutional commitment that goes beyond what any individual clinician or service can deliver unilaterally.

But the TDF gives us the language, the structure, and the evidence base to make that case. It allows us to articulate why a funding model that eliminates clinical supervision undermines skills development. Why a technology rollout without adequate change sequencing disrupts behavioural regulation. Why burnout is not a personal failing but an institutional condition with predictable and documented consequences for the adoption of evidence-based practice.

Used well, the TDF moves the conversation from “why aren’t clinicians doing this?”, which places the burden of failure on individual practitioners, to “what conditions are preventing this from happening?”. This frames the conversation on the systems within which those practitioners work. That shift in framing provides the foundation for an implementation that is sustainable, equitable, and honest about where the real work needs to happen.

I hope you’ve enjoyed and learned from my introduction to using the TDF to identify determinants across therapist and institutional factors. In my next post, I will turn to the third category of determinants: patient factors, and how the Capability, Opportunity, Motivation- Behaviour (COM-B) model helps us understand why even the most evidence-based and well-delivered intervention may not be accepted or sustained by the people it is designed to help.

And with that, thanks for reading.

Ashan

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References

1. Weerakkody, A., E. Godecke, and B. Singer, Implementing modified constraint-induced movement therapy after stroke in an early-supported discharge rehabilitation service: a process evaluation using RE-AIM QuEST. BMC Health Serv Res, 2025. 25(1): p. 1086.

2. Weerakkody, A., et al., Unlocking the restraint-Development of a behaviour change intervention to increase the provision of modified constraint-induced movement therapy in stroke rehabilitation. Australian Occupational Therapy Journal, 2023. 70(6): p. 661-677.

3. Weerakkody, A., E. Godecke, and B. Singer, Translating acceptability to sustained delivery: Clinician and manager perspectives on implementing modified constraint-induced movement therapy in an early-supported discharge rehabilitation service. Aust Occup Ther J, 2024. 72(1).

4. Bird, M.L., et al., Moving stroke rehabilitation evidence into practice: a systematic review of randomized controlled trials. Clin Rehabil, 2019: p. 269215519847253.

Those domains included knowledge, skills, social and professional role, beliefs about capabilities, beliefs about consequences, and motivation and goals. Together, they help explain why delivering best-practice care is not simply a matter of telling clinicians what the evidence says.

In this second post, I want to finish the discussion of therapist factors by looking at the remaining TDF domains that are particularly relevant to neuro rehab.

Again, my aim here is not to provide a theoretical lecture. It is to make these ideas practical enough that clinicians can use them to reflect on their own practice and the settings they work in.

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So, with that, let’s go through the other domains…

Memory, Attention and Decision Processes

This domain relates to how clinicians remember information, where they direct their attention, and how they make decisions in the moment. In busy clinical environments, therapists are constantly processing information: patient safety, movement quality, time pressures, documentation requirements, and competing treatment priorities. Under these conditions, decision-making is often rapid and shaped by habits rather than deliberate reflection.

A simple example is a therapist defaulting to familiar treatment approaches because they are easier to recall and implement quickly. This does not necessarily mean those interventions are ineffective, but it does mean that newer or more evidence-based approaches may be overlooked simply because they are not yet embedded in the clinician’s routine thinking. If evidence-based practice is to become routine, it needs to become easier to remember, prioritise, and apply under real-world pressure.

Environmental Context and Resources

Although this domain clearly overlaps with broader service and institutional factors, it is still highly relevant to individual therapist behaviour. Clinicians do not work in a vacuum. Their ability to deliver evidence-based care is shaped by time, staffing, equipment, space, policies, referral patterns, and access to training.

For example, mechanically assisted gait training may be strongly supported by the evidence, but a therapist working in home-based rehabilitation may have no access to the necessary equipment. Similarly, a clinician may understand that higher repetition and intensity are important, but if appointment times are short and travel demands are high, delivering that dose becomes difficult. In these situations, the barrier is not lack of knowledge or motivation. It is the practical environment in which the clinician is being asked to work.

Social Influences

Therapists are strongly influenced by the people around them. This includes colleagues, senior clinicians, managers, educators, professional networks, and even the expectations of patients and families. Practice is often shaped socially long before it is shaped explicitly by a guideline.

If a team values reflective practice, discusses evidence openly, and supports clinicians to try new interventions, it becomes easier to adopt evidence-based care. On the other hand, if the dominant workplace culture is to do what has always been done, change becomes much harder. A clinician may know the evidence, but still hesitate to deliver an intervention if they feel it is not supported by the team around them. This is one reason why local champions, mentoring, and peer support are often so important in implementation.

Emotion

Emotion is sometimes overlooked in discussions of evidence-based practice, but it can have a powerful influence on clinician behaviour. Therapists may feel anxious about trying a new intervention, concerned about patient risk, frustrated by service constraints, or discouraged when they are unable to deliver care in the way they believe they should.

For example, a therapist may avoid pushing intensity during gait retraining because they are worried about falls, fatigue, or the patient becoming overwhelmed (this could also come under ‘Beliefs about consequences’!). Those concerns may be entirely understandable, but they can still influence practice in ways that reduce fidelity to the evidence.

Emotions also work in the other direction. Positive experiences, such as seeing a patient make meaningful gains with a more intensive or structured intervention, can strengthen a clinician’s willingness to use that approach again.

Reinforcement

Reinforcement refers to the ways behaviour is strengthened or weakened over time. If clinicians experience positive outcomes from delivering an intervention, they are more likely to continue using it. If the behaviour is difficult, poorly supported, or appears to produce little benefit, it is less likely to be sustained.

In practice, reinforcement can come from several sources. It may come from seeing patient improvements, from positive feedback from colleagues or managers, or from audit and outcome data showing that a new approach is working. The opposite is also true. If clinicians are asked to change their behaviour but receive no feedback, no visible benefits, and no recognition for the effort involved, the change is unlikely to last. This is one reason why implementation cannot rely on education alone. New behaviours need to be supported and reinforced over time.

Behavioural Regulation

This domain relates to the strategies clinicians use to monitor, adjust, and sustain their own behaviour. It includes things such as self-reflection, action planning, prompts, audit and feedback, supervision, and goal setting. In many ways, this is the domain that turns insight into action.

For example, a clinician may recognise that their upper limb therapy after stroke has become too impairment-focused and not task-specific enough. Behavioural regulation is what helps bridge that gap. It may involve setting a specific practice goal, reviewing session plans, seeking supervision, or auditing whether treatment actually aligns with the intended evidence-based approach. Without these deliberate strategies, even motivated clinicians can drift back toward familiar habits.

Optimism

Another domain worth considering is optimism: the extent to which clinicians believe that change is possible and that their efforts will make a difference. This matters more than we sometimes acknowledge. In pressured clinical environments, it is easy for therapists to become resigned to the idea that best-practice care is unrealistic. If clinicians begin to believe that meaningful implementation is not possible in their setting, motivation can erode quickly.

We’ve all seen that cynical clinician who dismisses every new idea! I hate to admit it, but I’ve been there too… and very glad to be far away from that now

On the other hand, where there is a sense that change is achievable, even small wins can build momentum. Optimism is not about ignoring real barriers. It is about maintaining enough belief in the possibility of improvement that clinicians remain willing to keep trying.

Intentions

Intentions refer to a person’s conscious decision or commitment to perform a behaviour. This may seem obvious, but it is an important distinction. A clinician may agree with the evidence in principle, but not actually form a clear intention to change their practice.

For example, a therapist may leave a professional development course or session convinced that they should increase the amount of task-specific practice they deliver. But unless that intention becomes explicit and linked to concrete action, it may never translate into changed behaviour. How often do you leave a course energised and motivated to deliver a new intervention, only to revert back to your old practice after a couple of months?

Good intentions are common in rehabilitation. Converting them into consistent practice is much harder.

What This Means in Practice

When you look across these domains, a clear pattern emerges: therapist behaviour is shaped by far more than evidence alone. Knowledge matters, but so do confidence, habits, emotions, workplace culture, available resources, reinforcement, and the clinician’s own capacity to regulate and sustain behaviour change.

This is important because it shifts the conversation. If a clinician is not delivering an evidence-based intervention, the answer is not always that they need more education. They may need skills practice. They may need mentoring. They may need support from colleagues, better systems, clearer prompts, or simply a more realistic service environment in which to work.

That is one of the reasons I find implementation science so useful. It helps move us away from simplistic explanations and towards a more structured understanding of why good evidence does or does not translate into practice.

I also genuinely believe that we, as clinicians, all want to deliver the best possible care. Why that doesn’t happen isn’t all to blame on those ‘dinosaur therapists’ who refuse to change (although they do exist as well)- there’s so much more to it, and the odds seem to be stacking higher and higher against us. But…. we can’t wave the white flag either.

In the next post, I will move beyond therapist factors and look at the broader institutional factors that influence the delivery of evidence-based neurorehabilitation.

And with that, thanks for reading!

Ashan

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Putting ideas out into the public domain is always slightly nerve-wracking. You wonder whether anyone is interested in what you have to say. So, I’m very grateful to everyone who has read the articles so far and joined the discussion.

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In my last post, I wrote about the tension between what the evidence tells us is best practice in neurorehabilitation and the realities of delivering that care in clinical environments. In the next series of posts, I want to unpack this further by exploring why delivering evidence-based care can be so difficult.

When we talk about evidence-based practice, there are several interacting pieces of the puzzle.

First, there are therapist factors: the beliefs, skills, and behaviours of clinicians themselves.

Second, there are institutional factors: things like funding models, service structures, equipment, and management support.

Third, there are patient factors, including preferences, goals, knowledge, and expectations.

These factors rarely act independently. They interact and influence each other in complex ways.

In this series, I’m going to examine these influences through an implementation science lens. Implementation science focuses on understanding the barriers and enablers that affect whether evidence-based practices are adopted in real-world settings. It’s a field of research concerned with translating research findings into clinical practice.

In my PhD research I used several frameworks to understand how clinicians adopt evidence-based interventions. One of the most widely used frameworks is the Theoretical Domains Framework (TDF). The TDF groups behavioural determinants into 14 domains that help us identify why clinicians do (or don’t) adopt particular practices.

In this post we’ll explore some of the therapist factors within the TDF. The remaining domains will be discussed in the next post.

Knowledge

The first domain is Knowledge, which refers to awareness and understanding of something.

Clinicians may know that a guideline exists, but not understand the details of how an intervention should be delivered. Procedural knowledge is knowing the how and why something should be done, and this is often the missing piece.

An example from my research is constraint-induced movement therapy (CIMT). Many clinicians were aware that CIMT has strong support in the stroke guidelines. However, far fewer felt confident about how to deliver the intervention in practice; particularly the transfer package or how to implement the program within a resource-constrained health service.

Knowledge of the task environment is also important. For example, the evidence supports mechanically assisted gait training after stroke. But if you are working in a community rehabilitation setting and visiting patients in their homes, the practical question becomes: is this intervention feasible in this environment?

Skills

The second domain is Skills, which refers to the ability or proficiency required to deliver an intervention.

Clinicians may understand the theory behind an intervention but lack the opportunity to develop the practical skills required to deliver it confidently.

This is particularly relevant in complex neurological populations. A therapist working in community practice may only see one or two people with spinal cord injury per year. Even if they understand the evidence for particular interventions, limited exposure makes it difficult to build the experience needed to deliver those interventions confidently.

Social / Professional Role and Identity

This domain relates to how clinicians see their professional role and how that influences their behaviour.

Do clinicians believe that delivering evidence-based interventions is part of their professional responsibility? Do they view research evidence as credible and relevant to their work? Or do they see clinical experience as more important?

Group identity also plays a role. Clinicians are influenced by the practices of their colleagues and the expectations of their workplace. If a team strongly values evidence-based practice, clinicians are more likely to adopt new interventions. Conversely, if a workplace culture emphasises tradition or routine, change can be much slower.

Beliefs About Capabilities

This domain relates to a clinician’s confidence in their ability to deliver an intervention successfully.

Even when clinicians understand the evidence and believe an intervention is beneficial, they may hesitate to implement it if they do not feel capable of delivering it effectively.

For example, increasing therapy intensity after neurological injury is strongly supported by the literature. However, clinicians may feel uncertain about how to safely push intensity with patients who have complex co-existing impairments. Without confidence in their own skills, therapists may default to lower-intensity therapy even when they know the evidence suggests otherwise.

Beliefs About Consequences

Beliefs about consequences refer to what clinicians expect will happen if they deliver a particular intervention.

If clinicians believe an intervention will produce meaningful improvements in patient outcomes, they are more likely to adopt it. If they anticipate negative outcomes, such as patient frustration, fatigue, or risk of harm, they may avoid it.

For instance, therapists may hesitate to increase walking practice after stroke because they worry about fatigue or falls. Yet the evidence suggests that progressive, task-specific walking practice is beneficial for recovery. Balancing perceived risks with evidence-based benefits is a constant challenge in clinical decision-making.

I’ve also seen it where clinicians worry that focussing on upper limb rehabilitation means taking away from gait retraining. This is the consequence of adopting a particular intervention.

Goals

Clinicians often work in environments where multiple priorities compete for their attention. Even when therapists value evidence-based practice, other goals may take precedence during a busy clinical day.

For example, an intervention may require focused, repetitive practice over a longer therapy session. However, if a service model prioritises rapid patient turnover, clinicians may prioritise efficiency over the intervention that best aligns with the evidence.

This is best demonstrated with the rush to teach one-handed compensatory strategies after stroke to facilitate independence in ADLs with the push for earlier discharges home, rather than focussing on intensive practice of the stroke-affected upper limb. In some cases, this may be entirely appropriate. For others, this goal comes at the expense missing the optimal window for neuroplastic recovery.

These domains highlight that adopting evidence-based practice involves far more than simply knowing the evidence.

In the next post we will explore the remaining domains of the Theoretical Domains Framework and how they influence therapist behaviour in neurorehabilitation.

I’ll also finish that post with why this is useful for clinicians to consider as part of their clinical practice, and not just for those conducting research!

With that, thank you for reading and see you for the next one.

Ashan

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The evidence base supporting what we do has expanded enormously. We now have high-quality clinical practice guidelines (CPGs) for stroke, including the:

• Australian Living Stroke Guidelines [1],

• UK and Ireland National Clinical Guideline for Stroke (updated in 2023) [2],

• Canadian Stroke Best Practice Recommendations [3], and

• European Stroke Organisation guideline on motor rehabilitation [4], and

• Spasticity management using botulinum toxin [5].

Across other neurological conditions, the guidance available to clinicians has also grown rapidly. We’ve recently seen:

• the first CPG for physiotherapy management in spinal cord injury in Australia and New Zealand [6],

• CPGs for a range of vestibular conditions [7, 8],

• clinical management guidelines for Friedreich’s ataxia [9],

• consensus recommendations for physiotherapy management of functional neurological disorder [10],

• along with several guideline relating to traumatic brain injury and physical activity [11]- among many others.

The volume of research in neurorehabilitation has exploded over the past decade. In many ways, this is deeply validating. It confirms that rehabilitation works when tested under the rigours of randomised trials, systematic reviews, and guideline development. As clinicians, we have never had more information available to guide and support our practice. What we do matters AND makes a difference to people living with neurological conditions!

And yet, I have a growing sense that it has never been harder to deliver best-practice care in the current rehabilitation environment.

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The evidence has grown, but the system has not

The first challenge is that the strain on health and disability systems is increasing, not easing.

In Australia (an experience that will be familiar across many countries), publicly funded health services are under unprecedented pressure. Resources are often shifted toward acute care, where demand is visible and immediate, while rehabilitation services compete for what remains. Inpatient rehabilitation care has become more time-limited, with the focus on discharging home to community services as soon as possible. Yet, community-based rehabilitation funding has also come under increasing constraint, despite earlier acuity and rising complexity of patient need.

We’ve also seen a devaluing of skilled neurological input. The recent NDIS price cap reductions for physiotherapy, combined with reduced capacity building funding for new plans (with an expectation that untrained support workers are able to deliver therapy programs at the same level as clinicians), means there is less money to deliver quality neurological physiotherapy for those living with permanent disability in the community.

For many organisations across health and disability, this has created an environment where survival is the priority. Investment in clinical supervision, service development, and innovation almost impossible. Productivity dominates, and the resources required for reflective, high-quality practice shrinks.

Rehabilitation is widely recommended. But the conditions required to deliver it well are increasingly fragile.

Research Often Doesn’t Reflect Real-World Rehabilitation

A second challenge is that much of the research evidence does not map neatly onto how neuro rehabilitation is actually delivered.

We know that effective rehabilitation is typically high-dose, high-intensity, and personalised. Yet many interventions are studied in isolation and compared against “usual care”, whatever that is. A clinical trial may examine a discrete component, such as sit-to-stand retraining, and demonstrate improvement in that specific task. These studies are valuable, but they can miss the reality that therapy is rarely one thing.

In practice, rehabilitation is a complex intervention: sit-to-stand training sits alongside gait retraining, balance work, cardiovascular conditioning, strength and power development, upper limb practice, building self-efficacy, and participation-focused goals. These components interact. The whole is not simply the sum of its parts.

This complexity is one reason why translating evidence into practice is rarely straightforward.

Fidelity: When What We Deliver Isn’t What Was Tested

Even when the evidence is strong, another challenge emerges: what is delivered in practice may not resemble what was tested in the trial.

This is the issue of treatment fidelity: the extent to which an intervention is delivered as intended.

Electrical stimulation is a good example. It has evidence as an adjunct intervention to motor training for improving upper limb function after stroke [1, 2, 3, 12]. But in real-world practice from my own observations of working with hundreds of clinicians, it’s often used as the only upper limb intervention, particularly when there is no active hand movement. That is not necessarily what the evidence supports to improve upper limb function. Does this mean we abandon the intervention? Not at all. But it highlights how nuanced evidence interpretation becomes when clinical realities intervene.

The question is rarely “does this work?” The question is often “under what conditions, for whom, and alongside what else?”

In my PhD thesis, I spoke a lot about treatment fidelity, as constraint-induced movement therapy has many misconceptions which has influenced the real and perceived outcomes reported both in clinical and research settings (mitt anyone?!). I’ll speak more about that in future posts, but in the meantime, enjoy one of my favourite journal titles:

Guidelines Tell Us What to Do, Not Always How

Clinical practice guidelines are essential, but they can also leave clinicians with unanswered questions.

For example, the spinal cord injury guidelines recommend wheelchair skills training for new wheelchair users [6]. This is entirely sensible. But what does wheelchair skills training look like in practice? How is it taught? At what dose? Over what timeframe? How do we measure success?

Heterogeneity, prognostication and clinical reasoning matter

Neurological rehabilitation is heterogenous, no two patients or treatment plans are the same. Patients vary enormously in impairment, recovery potential, context, comorbidities, and goals. Even well-designed trials may include populations for whom meaningful change is unlikely, leading to null findings that can be misinterpreted.

This is where clinical reasoning remains central. Evidence is critical, but evidence alone cannot replace judgement about prognosis, appropriateness, and individualisation.

Why I’m Writing This

These tensions are exactly why I started Cortex Neuro Education.

I believe we must be firmly guided by evidence in delivering high-quality neurorehabilitation. But I also believe we need to be honest about the barriers: the system pressures, the complexity of rehabilitation, the challenges of fidelity, and the gap between research conditions and clinical reality.

In future posts, I want to explore these issues through an implementation science lens. We’ll work on identifying why best practice is difficult, what helps, and how clinicians and services can move closer to what the evidence supports.

I am not presenting myself as a final authority. But I do think these conversations matter, and I hope this space can contribute to them.

If you are a clinician, educator, or manager navigating these same challenges, I would welcome you here.

Feel free to share your own insights on any tension you feel in your practise/service on delivering evidence-based rehabilitation.

Thanks for reading.

Ashan

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References:

1. Stroke Foundation, Living Clinical Guidelines for Stroke Management. 2026.

2. Intercollegiate Stroke Working Party, National Clinical Guideline for Stroke for the UK and Ireland. 2023: London.

3. Teasell, R., et al., Canadian Stroke Best Practice Recommendations: Rehabilitation, Recovery, and Community Participation following Stroke. Part One: Rehabilitation and recovery following stroke; 6th Edition Update 2019. International Journal of Stroke, 2020. 15(7): p. 763-788.

4. Alt Murphy, M., et al., European Stroke Organisation (ESO) guideline on motor rehabilitation. Eur Stroke J, 2025. 10(4): p. 1160-1188.

5. Royal College of Physicians, et al., Spasticity in adults: management using botulinum toxin. National guidelines. 2018, RCP: London.

6. Glinsky, J.V., L.A. Harvey, and Australian and New Zealand Physiotherapy Clinical Practice Guidelines consortium, Australian and New Zealand Clinical Practice Guideline for the physiotherapy management of people with spinal cord injury. 2022.

7. Hall, C.D., et al., Vestibular Rehabilitation for Peripheral Vestibular Hypofunction: An Updated Clinical Practice Guideline From the Academy of Neurologic Physical Therapy of the American Physical Therapy Association. J Neurol Phys Ther, 2022. 46(2): p. 118-177.

8. Bhattacharyya, N., et al., Clinical Practice Guideline: Benign Paroxysmal Positional Vertigo (Update). Otolaryngol Head Neck Surg, 2017. 156(3_suppl): p. S1-S47.

9. Corben, L.A., et al., Clinical management guidelines for Friedreich ataxia: best practice in rare diseases. Orphanet J Rare Dis, 2022. 17(1): p. 415.

10. Nielsen, G., et al., Physiotherapy for functional motor disorders: a consensus recommendation. J Neurol Neurosurg Psychiatry, 2015. 86(10): p. 1113-9.

11. Hassett, L., et al., A Physical Activity Clinical Practice Guideline for People With Moderate to Severe Traumatic Brain Injury. Clinical and Public Health Guidelines, 2025. 2(4).

12. Scrivener, K., et al., Electrical stimulation of the motor system after stroke. Cochrane Database Syst Rev, 2025. 12(12): p. CD015338.

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Who am I?

I’m Ashan Weerakkody. I’m an APA Titled Neurological Physiotherapist, APA Titled Research Physiotherapist, a PhD-trained clinician-researcher, and the owner of Cortex Neuro Rehab in Perth, Western Australia. I’ve spent the past 15 years working almost exclusively in neurological rehabilitation, predominantly in community settings across subacute and chronic periods of disability.

My clinical work has always sat at the intersection of evidence, clinical-reasoning, and real-world constraints. Like many clinicians, I was trained to value best practice, yet repeatedly encountered the gap between what the literature recommends and what services can realistically deliver. That tension between evidence and implementation has shaped much of my professional journey.

I undertook my PhD to better understand that gap and find ways to change clinical practice to deliver the interventions we should be delivering. My doctoral work focused on the large-scale implementation of constraint-induced movement therapy within an early supported discharge rehabilitation service. It was a multi-year process that involved clinicians, managers, stroke survivors, and carers, and it required grappling with complexity rather than controlling for it.

This work reinforced a reality many clinicians already sense: evidence does not fail because it is weak, but because implementation is hard (but not impossible!).

Being a clinician-researcher meant living in both worlds simultaneously. I continued to treat patients while designing behaviour-change interventions, conducting qualitative research, analysing service-level data, and negotiating the practical realities of workforce capacity, caseload pressure, and competing priorities. That dual role fundamentally changed how I read and interpret research, how I clinically reason, and how I think about service design.

Alongside clinical practice and research, I have always been drawn to education and mentorship. I enjoy working with clinicians who want to think deeply about what they do and the type of clinician they want to become. I’m passionate about developing skills for clinicians to understand when to choose certain interventions, how to adapt evidence to suit their clinical context, and develop confidence without oversimplification. Over time, teaching, supervision, and mentoring have become an increasingly important part of my work, not as an adjunct to practice, but as a core professional responsibility.

One unexpected outcome of my PhD was developing a love for writing. Writing became a way to think clearly, to synthesise ideas, and to communicate nuance; especially the nuance that is often lost in guidelines, protocols, or social media summaries which aren’t easy for clinicians to then take forward into the real world. I came to see writing not just as academic output, but as a form of knowledge translation and professional dialogue.

Why this blog?

Since completing my PhD, I’ve spent the past 6 months focussing on my clinical work with Cortex Neuro Rehab, whilst maintaining a small clinical supervision and mentoring load, and running ad hoc professional development courses in Perth.

I love my clinical work. I love the clients that I work with and the complexity of my caseload. But something’s been missing…

Alongside clinical practice, my other passion has been developing clinicians, teaching the how and why of good neurological rehabilitation, ensuring evidence-based practice is accessible and deliverable, and helping clinicians feel confidence managing complexity in the real world.

In both my formal and informal mentoring, the feedback I’ve received has been concerning regarding the state of neurological clinician development. Young clinicians are burnt out, with large caseloads, minimal support and often feeling like they aren’t making a difference. Others report that they do the same generic exercises with every client, regardless of how the impairments are impacting function. I also get contacted by international physiotherapists wanting insights into how neurological rehabilitation is practiced in Australia.

Enter Cortex Neuro Education- Evidence into Practice

Cortex Neuro Education exists because there is space, and need, for slower, more thoughtful conversations about neurorehabilitation. This is a place to explore evidence, clinical reasoning, and implementation honestly: what works, what doesn’t, and why. It is not a substitute for peer-reviewed research or formal education, but a complement to both.

I aim to capture the full breadth of neurological rehabilitation practice, reflecting my clinical caseload and experience, combined with the latest evidence and practical guidance on delivering best-practice care. Whilst I’m a physio, and content will be biased towards physiotherapy, there will be much applicable across many disciplines working in neurological rehabilitation.

This blog will include:

• Guideline and consensus recommendation summaries

• Literature reviews

• Critical appraisals of important papers (including how to do critical appraisals in the first place)

• Deep dives into a range neurological conditions

• Clinical reasoning and therapy planning

• Implementation science and the challenges to deliver evidence-based practice

• Tips on career planning and progression, and,

• Anything else that readers think would help them become a more confident clinician.

I’ve set myself a goal of writing content fortnightly this year, so you can expect at least 2 pieces published each month!

If you’re a clinician, student, educator, or manager interested in evidence-informed neurological practice that acknowledges real-world complexity, I hope you’ll find this useful.

Thanks for reading,

Ashan