The Feasibility and Acceptability of a Gait Training Program Based on Telerehabilitation After Stroke

Stroke is the primary cause of disability and the second cause of death worldwide. In Saudi Arabia, the annual incidence rate is 57.64 per 100,000 people. Stroke-related disabilities may include cognitive dysfunction, sensory deficiencies, and motor difficulties. These impairments can result in weakened postural control, leading to imbalance and gait abnormalities.

Stroke survivors exhibit a slower gait cycle, reduced gait speed, a shorter stance phase, and a longer swing phase on the affected side, as well as differences in step lengths between the affected and unaffected sides. These gait characteristics limit functional movement abilities. Impaired walking abilities in patients with stroke represent a significant barrier to performing daily activities independently. Further, walking problems have been shown to reduce quality of life and limit participation, which, if untreated, leads to social isolation because walking is crucial for functional tasks.

Restoring walking capacity is a key objective of rehabilitation following a stroke, as stroke survivors primarily aim to increase walking safety and speed to prevent falls and enhance their quality of life. Therefore, intensive rehabilitation following a stroke is an essential component of patient care. Most people require rehabilitation after a stroke, which is often provided by medical professionals in hospital or clinic settings to improve patients' functional activities and quality of life. However, the lack of resources in facilities and rising medical costs make rehabilitation difficult, burdening both patients and healthcare policy services that aim for the best possible stroke recovery.

Compared to facility-based services, home-based telerehabilitation may encourage patients to improve their home environment and increase the frequency and intensity of their therapy. It is practical and can be used either as a supplement to or an alternative to traditional treatment, significantly enhancing therapeutic outcomes. Stroke telerehabilitation uses a variety of devices and software and can be delivered asynchronously, synchronously, or through a hybrid approach. Based on the findings from the umbrella review, a total of 28 systematic reviews were included that examined various telerehabilitation interventions after stroke. Simple and complex telerehabilitation interventions such as telephone calls, videoconferencing, smartphone or tablet-based mobile health applications, messaging, virtual and augmented reality, gaming, robot-assisted devices, 3D animation videos, and technology-assisted self-rehabilitation, either as standalone interventions or in combination with others, were included across reviews. These interventions have shown either a significant effect or no significant difference compared to other interventions in improving upper and lower limb motor function, balance, gait, ADLs and quality of life. A recent review found that exercise-based telerehabilitation is a feasible and potentially effective alternative to traditional post-stroke therapy. Improvements were observed in motor function, mobility, balance, and quality of life, while patient satisfaction and adherence remained high.

However, contextual dimensions, such as cultural, physical, social, spatial, organisational, political, or economic features of healthcare and the health system, impact the effectiveness and implementation of complex interventions. A qualitative study (currently under review), involving in-depth interviews with six patients with stroke, six carers, and ten physiotherapists, was conducted to gain deeper insight into their experiences and expectations regarding the implementation of telerehabilitation interventions after stroke in clinical practice in Saudi Arabia. The findings highlighted self-efficacy and motivation, which are influenced by cultural factors and barriers such as digital inequity, low awareness, inadequate training, cultural norms, and a preference for in-person care, all of which affect the adoption of telerehabilitation for patients with stroke in Saudi Arabia. However, telerehabilitation may support continuity of rehabilitation through appropriate training, family involvement, culturally sensitive approaches, and hybrid models.

The findings obtained from qualitative interviews were mapped onto the Behaviour Change Wheel (BCW) and the Theoretical Domains Framework (TDF) to develop a gait training program based on telerehabilitation intervention, Stroke Telerehabilitation for Enhanced Performance in Gait via Technology (STEP-Tech) intervention, as a promising solution to enhance gait quality, adherence and engagement to exercises at home, addressing all identified Behaviour Change Techniques (BCTs). The physiotherapist will deliver the intervention in a hybrid model; in two phases: phase one in the clinic, and phase two home-based. The development of this intervention has followed the UK Medical Research Council (MRC) framework for developing and evaluating complex interventions. The assessment of the feasibility of the intervention and evaluation design is the second phase of this framework, which involves assessing predefined progression criteria that relate to the evaluation design or the intervention itself.

Therefore, the overall aim of this study is to assess the feasibility and acceptability of delivering the STEP-Tech intervention to patients with stroke in the SA healthcare system and to evaluate the feasibility of conducting a future clinical trial to assess the programme's effectiveness.

• 6-Minute Walk Test (6MWT) [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6).]
• Five-Times-Sit-To-Stand Test (FTSTS) [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• Rivermead Mobility Index [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6).]
• The indicator of gait quality (The number of recorded steps) [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6).]
• The indicator of gait quality (Number of good steps) [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: Angular velocity at heel strike [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: Angular velocity at push- off [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: Angular velocity at foot clearance [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: Angular velocity at Power phase [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: Angular velocity at Balance Phase [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: coefficients of variation (CV) of angular velocity (AV): heel strike [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]
• The indicator of gait quality: coefficients of variation (CV) of angular velocity (AV): Push-off [Time frame: at baseline (pre-intervention) and immediately after the intervention (at week 6)]