NIHRDataInsights/HRCSData huggingface dataset:
Title: Investigating a home-based self-administered computerised tool for rehabilitating and assessing spatial neglect after stroke: A feasibility study
Funder: Stroke Association

Abstract: Around 30% (2,3,4) of UK stroke survivors present symptoms of spatial neglect, a debilitating disorder defined as a failure to respond to the side of space opposite to the side of the brain lesion. It is a major predictor of disability (7) and there is no recommended effective treatment (8). Recently, SIGHT (Spatial Inattention Grasping Home-based Therapy) produced a substantive reduction in neglect lasting for at least 4-months post-training in stroke survivors with chronic neglect. SIGHT is a self-administered neurorehabilitation of grasping-to-lift rods at the centre with the unaffected arm (16). Stroke survivors told us “there’s not enough support at home” and that computerized therapy would be more ‘engaging and motivating’. Using this feedback, the fellow developed a computerized SIGHT (C-SIGHT) and Computerized Extrapersonal (far-space) Neglect Test (CENT). This project aims to 1) investigate the feasibility of an RCT using C-SIGHT vs. attention control sham version at home with stroke survivors with spatial neglect; 2) use 1:1 interviews to explore participant’s experience of self-administering C-SIGHT and attention control sham version independently at home; 3) explore responsiveness and diagnostic accuracy of CENT compared to standard pencil-and-paper tests. Findings will inform the design of Phase II RCT for the fellow’s post-doc project.

Lay abstract: Around 30% (2,3,4) of UK stroke survivors present symptoms of spatial neglect, a debilitating disorder defined as a failure to respond to the side of space opposite to the side of the brain lesion. It is a major predictor of disability (7) and there is no recommended effective treatment (8). Recently, SIGHT (Spatial Inattention Grasping Home-based Therapy) produced a substantive reduction in neglect lasting for at least 4-months post-training in stroke survivors with chronic neglect. SIGHT is a self-administered neurorehabilitation of grasping-to-lift rods at the centre with the unaffected arm (16). Stroke survivors told us “there’s not enough support at home” and that computerized therapy would be more ‘engaging and motivating’. Using this feedback, the fellow developed a computerized SIGHT (C-SIGHT) and Computerized Extrapersonal (far-space) Neglect Test (CENT). This project aims to 1) investigate the feasibility of an RCT using C-SIGHT vs. attention control sham version at home with stroke survivors with spatial neglect; 2) use 1:1 interviews to explore participant’s experience of self-administering C-SIGHT and attention control sham version independently at home; 3) explore responsiveness and diagnostic accuracy of CENT compared to standard pencil-and-paper tests. Findings will inform the design of Phase II RCT for the fellow’s post-doc project.

Research activity codes: 5.3 MEDICAL DEVICES
Health categories: STROKE
Title: A Study of Cognitive, Emotional, Physical and Socioeconomic Factors Associated with Patient-Reported Outcome Measures (PROMS) Completion Post-Stroke.
Funder: Stroke Association

Abstract: Background: The evidence base for Patient-Reported Outcomes use with stroke survivors either fails to report or sufficiently evidence sufficient levels of acceptability. Which factors (cognitive, emotional, physical and socioeconomic) most affect acceptability post-stroke is currently unknown. Without primary research into these factors, insufficient PROM acceptability may jeopardise stroke survivors’ ability to voice their perceptions of their health or the outcomes of treatment received. Aim: To understand which factors affect PROM completion post-stroke. Methods: An interlinked 4 part programme of work is proposed to explore cognitive, emotional, physical and socioeconomic factors to PROM completion post-stroke; [1] A ‘Realist Synthesis’ exploring the wider factors which can influence the success of PROMs for stroke survivors and healthcare professionals. [2] Analysis of existing trial data utilising PROMs as an outcome. [3] This 2 phase cohort study will develop and assess the use of an accessible version of the PROMIS-10 based on the factors which decrease PROM completion. [4] Post-study participant interviews to ‘explore the barriers to PROM completion’. Expected outcomes: Evidence of which factors are most associated with PROM completion post-stroke. The results of the work packages, will inform clinicians, policy makers, planners and researchers in the government, public bodies and the third sector.

Lay abstract: Background: The evidence base for Patient-Reported Outcomes use with stroke survivors either fails to report or sufficiently evidence sufficient levels of acceptability. Which factors (cognitive, emotional, physical and socioeconomic) most affect acceptability post-stroke is currently unknown. Without primary research into these factors, insufficient PROM acceptability may jeopardise stroke survivors’ ability to voice their perceptions of their health or the outcomes of treatment received. Aim: To understand which factors affect PROM completion post-stroke. Methods: An interlinked 4 part programme of work is proposed to explore cognitive, emotional, physical and socioeconomic factors to PROM completion post-stroke; [1] A ‘Realist Synthesis’ exploring the wider factors which can influence the success of PROMs for stroke survivors and healthcare professionals. [2] Analysis of existing trial data utilising PROMs as an outcome. [3] This 2 phase cohort study will develop and assess the use of an accessible version of the PROMIS-10 based on the factors which decrease PROM completion. [4] Post-study participant interviews to ‘explore the barriers to PROM completion’. Expected outcomes: Evidence of which factors are most associated with PROM completion post-stroke. The results of the work packages, will inform clinicians, policy makers, planners and researchers in the government, public bodies and the third sector.

Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;7.1 INDIVIDUAL CARE NEEDS
Health categories: STROKE
Title: Interpretable Artificial Intelligence for predicting language recovery after stroke
Funder: Stroke Association

Abstract: Interpretable Artificial Intelligence for predicting language recovery after stroke For most machine learning algorithms, the classifications or predictions made are inscrutable, i.e. no information is given about *how* a decision has been reached. Thus, these machine learning methods are black-boxes. Such black-box algorithms are limited in their value to healthcare. For example, patients, carers and the legal system rightly expect explanations for clinical decisions. Additionally, black-box AI will not temper the public’s concern over such methods. All these issues are pertinent to the application of AI to predicting recovery from stroke. In response, we propose to apply newer white-box AI methods, also called interpretable-AI, to classifying patients and predicting recovery. We will assess the applicability of a range of feature-importance methods, such as, layer-wise relevance analysis, which quantifies how important each neuron in a deep neural-network is for a classification. More ambitiously, we will also determine the applicability of rule-extraction methods. With structural-MRI, such methods might be able to extract rules of the kind, recovery of a particular language function is good if *brain area A is intact or brain areas B and C are both intact*. The proposal fits within the general objective of personalised medicine, since white-box AI methods provide explanations for *individual* patients.

Lay abstract: Interpretable Artificial Intelligence for predicting language recovery after stroke For most machine learning algorithms, the classifications or predictions made are inscrutable, i.e. no information is given about *how* a decision has been reached. Thus, these machine learning methods are black-boxes. Such black-box algorithms are limited in their value to healthcare. For example, patients, carers and the legal system rightly expect explanations for clinical decisions. Additionally, black-box AI will not temper the public’s concern over such methods. All these issues are pertinent to the application of AI to predicting recovery from stroke. In response, we propose to apply newer white-box AI methods, also called interpretable-AI, to classifying patients and predicting recovery. We will assess the applicability of a range of feature-importance methods, such as, layer-wise relevance analysis, which quantifies how important each neuron in a deep neural-network is for a classification. More ambitiously, we will also determine the applicability of rule-extraction methods. With structural-MRI, such methods might be able to extract rules of the kind, recovery of a particular language function is good if *brain area A is intact or brain areas B and C are both intact*. The proposal fits within the general objective of personalised medicine, since white-box AI methods provide explanations for *individual* patients.

Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: STROKE
Title: The development of a goal-setting tool for use in acute stroke rehabilitation
Funder: Stroke Association

Abstract: Background Goal-setting aims to improve stroke rehabilitation outcomes by increasing patient well-being and engagement with rehabilitation and is recommended in national clinical guidelines. A recent systematic review highlighted barriers to implementing goal-setting, particularly during acute rehabilitation. Several methods of goal-setting have been proposed but no gold standard has emerged. Aims To develop a goal-setting tool for use during acute stroke rehabilitation that meets the needs of clinicians, stroke survivors and their families, and is feasible to deliver in clinical practice. Methods The Behaviour Change Wheel will be used to understand the problems around goal-setting and identify ways in which behaviours can be changed. A group of stroke survivors, their family and clinicians will be consulted to develop a tool to support the implementation of goal-setting. The feasibility and acceptability of the tool will be assessed via a case study of its use in stroke rehabilitation units. Expected outcomes This project will produce an evidenced-based, patient-informed goal-setting tool that is feasible to use during acute stroke rehabilitation. It will address the current barriers to using goal-setting during acute rehabilitation to facilitate individualised, patient centred goals.

Lay abstract: Background Goal-setting aims to improve stroke rehabilitation outcomes by increasing patient well-being and engagement with rehabilitation and is recommended in national clinical guidelines. A recent systematic review highlighted barriers to implementing goal-setting, particularly during acute rehabilitation. Several methods of goal-setting have been proposed but no gold standard has emerged. Aims To develop a goal-setting tool for use during acute stroke rehabilitation that meets the needs of clinicians, stroke survivors and their families, and is feasible to deliver in clinical practice. Methods The Behaviour Change Wheel will be used to understand the problems around goal-setting and identify ways in which behaviours can be changed. A group of stroke survivors, their family and clinicians will be consulted to develop a tool to support the implementation of goal-setting. The feasibility and acceptability of the tool will be assessed via a case study of its use in stroke rehabilitation units. Expected outcomes This project will produce an evidenced-based, patient-informed goal-setting tool that is feasible to use during acute stroke rehabilitation. It will address the current barriers to using goal-setting during acute rehabilitation to facilitate individualised, patient centred goals.

Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: STROKE
Title: OxMET: A brief digital Multiple Errands Task to improve screening for executive dysfunction and inform functional outcomes
Funder: Stroke Association

Abstract: Aims: To improve identification of post-stroke executive dysfunction using the Oxford Digital Multiple Errands Test (OxMET), a computer-tablet based test of executive functioning. Background: Executive functioning (i.e., cognitive abilities related to planning, switching, and inhibition amongst others), is commonly affected in stroke patients. Executive dysfunction can negatively impact activities of daily living and effects quality of life as a result, therefore it is critical to identify early in clinical rehabilitation. However, current assessments lack ecological and face validity. Methods: The Oxford Digital Multiple Errands Test (OxMET) is a test of executive function that improves sensitivity and administration time of the commonly used Multiple Errands Test. The OxMET will be administered sub-acutely and participants will be followed up at 6- and 12-months post-stroke. Assessments of activities of daily living and functional review from occupational therapists will be compared to performance on the OxMET to establish the predictive validity of acute OxMET performance. Expected outcomes: Sub-acute performance on the OxMET will be associated with later functional recovery in terms of activities of daily living. The results can show whether the OxMET could be used in clinical practice to established early and targeted rehabilitation to improve functional ability and quality of life.

Lay abstract: Aims: To improve identification of post-stroke executive dysfunction using the Oxford Digital Multiple Errands Test (OxMET), a computer-tablet based test of executive functioning. Background: Executive functioning (i.e., cognitive abilities related to planning, switching, and inhibition amongst others), is commonly affected in stroke patients. Executive dysfunction can negatively impact activities of daily living and effects quality of life as a result, therefore it is critical to identify early in clinical rehabilitation. However, current assessments lack ecological and face validity. Methods: The Oxford Digital Multiple Errands Test (OxMET) is a test of executive function that improves sensitivity and administration time of the commonly used Multiple Errands Test. The OxMET will be administered sub-acutely and participants will be followed up at 6- and 12-months post-stroke. Assessments of activities of daily living and functional review from occupational therapists will be compared to performance on the OxMET to establish the predictive validity of acute OxMET performance. Expected outcomes: Sub-acute performance on the OxMET will be associated with later functional recovery in terms of activities of daily living. The results can show whether the OxMET could be used in clinical practice to established early and targeted rehabilitation to improve functional ability and quality of life.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: STROKE
Title: Understanding therapeutic alliance in the context of supported self-management in community stroke services.
Funder: Stroke Association

Abstract: Background The quality of the therapeutic alliance between patients and clinicians is thought to be an important role in healthcare. However, there is limited research about this concept in relation to physiotherapy and supporting long term self-management of stroke recovery. Aims To understand how important therapeutic alliance is to patients accessing community stroke services, in the context of self-management. To identify aspects of the alliance stroke survivors deem most important to support eliciting self-management behaviours, and manage long-term recovery after stroke. Methods A literature review will inform a working model of the relationship between therapeutic alliance and self-management ability. This will be tested in a quantitative study, exploring patient perceived associations between therapeutic alliance and self-management in community stroke settings. Interviews with stroke survivors will explore these models in more depth, identifying aspects of the alliance that are most important for supporting self-management. Expected outcome This project will better understand therapeutic alliance in the context of supported self-management in community stroke services. It will also identify which aspects of the alliance stroke survivors feel are most important to develop and maintain self-management behaviours. This will inform future research focused on improving healthcare provider communication in the context of stroke self-management.

Lay abstract: Background The quality of the therapeutic alliance between patients and clinicians is thought to be an important role in healthcare. However, there is limited research about this concept in relation to physiotherapy and supporting long term self-management of stroke recovery. Aims To understand how important therapeutic alliance is to patients accessing community stroke services, in the context of self-management. To identify aspects of the alliance stroke survivors deem most important to support eliciting self-management behaviours, and manage long-term recovery after stroke. Methods A literature review will inform a working model of the relationship between therapeutic alliance and self-management ability. This will be tested in a quantitative study, exploring patient perceived associations between therapeutic alliance and self-management in community stroke settings. Interviews with stroke survivors will explore these models in more depth, identifying aspects of the alliance that are most important for supporting self-management. Expected outcome This project will better understand therapeutic alliance in the context of supported self-management in community stroke services. It will also identify which aspects of the alliance stroke survivors feel are most important to develop and maintain self-management behaviours. This will inform future research focused on improving healthcare provider communication in the context of stroke self-management.

Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: STROKE
Title: Improving predictions of upper limb recovery after stroke with structural brain imaging
Funder: Stroke Association

Abstract: SCIENTIFIC: The extent of upper limb recovery after stroke is closely related to initial severity of impairment. This proportional recovery rule applies in those with mild/moderate impairment, but for the one-third of patients presenting with severe upper limb impairment, the outlook is uncertain. Our hypothesis is that predictions of upper limb outcome will dramatically improve by using information about the topology of brain damage derived from routinely acquired brain imaging. We have recently applied Gaussian modelling techniques to whole brain imaging to successfully predict differences in motor ability in chronic stroke patients. We will use the same methodological approach with MRI acquired within 72 hours post-stroke to improve the accuracy of current predictions of upper limb outcome in 200 patients. We will directly compare accuracy of models that use initial severity of impairment with and without MRI data for predicting 6 months outcomes. We will then test the optimal model in an independent cohort of 200 stroke patients. Lastly, we will work with stroke patients to convey the day-to-day meaning of these predictions. The ability to accurately predict functional outcomes after stroke will be useful for patients, for rehabilitation goal setting and for stratification in clinical trials of restorative therapies.

Lay abstract: SCIENTIFIC: The extent of upper limb recovery after stroke is closely related to initial severity of impairment. This proportional recovery rule applies in those with mild/moderate impairment, but for the one-third of patients presenting with severe upper limb impairment, the outlook is uncertain. Our hypothesis is that predictions of upper limb outcome will dramatically improve by using information about the topology of brain damage derived from routinely acquired brain imaging. We have recently applied Gaussian modelling techniques to whole brain imaging to successfully predict differences in motor ability in chronic stroke patients. We will use the same methodological approach with MRI acquired within 72 hours post-stroke to improve the accuracy of current predictions of upper limb outcome in 200 patients. We will directly compare accuracy of models that use initial severity of impairment with and without MRI data for predicting 6 months outcomes. We will then test the optimal model in an independent cohort of 200 stroke patients. Lastly, we will work with stroke patients to convey the day-to-day meaning of these predictions. The ability to accurately predict functional outcomes after stroke will be useful for patients, for rehabilitation goal setting and for stratification in clinical trials of restorative therapies.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: STROKE
Title: Improving outcomes for stroke survivors with visual impairment: a multi-facetted approach
Funder: Stroke Association

Abstract: Visual impairment is common after stroke, but service provision is sub-optimal. Research in this area is a priority for stroke survivors, carers and multidisciplinary healthcare professionals. My lectureship will inform and enhance evidence-based practice internationally through a robust and multifaceted programme of work; Workstream A Interventions for visual impairment: building on my previous work I will conduct a pilot RCT of a promising computer-based intervention for visual field loss. I will also rigorously develop and evaluate two new interventions, one addressing reading difficulties, the other addressing broader long-term unmet needs. Workstream B Improving clinical services for visual impairment: using a participatory approach I will develop and evaluate specialist training interventions for occupational therapists, that will be shared internationally. Within my unique, specialist Neurovision clinic I will determine the best vision assessments, and upskill optometry students in providing care for stroke survivors. Key outputs will include high-quality evidence to inform clinical guidelines, enhance clinical care and increase NHS capacity for stroke-specific vision assessment and management, plus a strong infrastructure to facilitate and enable further research.

Lay abstract: Visual impairment is common after stroke, but service provision is sub-optimal. Research in this area is a priority for stroke survivors, carers and multidisciplinary healthcare professionals. My lectureship will inform and enhance evidence-based practice internationally through a robust and multifaceted programme of work; Workstream A Interventions for visual impairment: building on my previous work I will conduct a pilot RCT of a promising computer-based intervention for visual field loss. I will also rigorously develop and evaluate two new interventions, one addressing reading difficulties, the other addressing broader long-term unmet needs. Workstream B Improving clinical services for visual impairment: using a participatory approach I will develop and evaluate specialist training interventions for occupational therapists, that will be shared internationally. Within my unique, specialist Neurovision clinic I will determine the best vision assessments, and upskill optometry students in providing care for stroke survivors. Key outputs will include high-quality evidence to inform clinical guidelines, enhance clinical care and increase NHS capacity for stroke-specific vision assessment and management, plus a strong infrastructure to facilitate and enable further research.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: STROKE