Background: Careful development of interventions using principles of co-production is now recognized as an important step for clinical trial development, but practical guidance on how to do this in practice is lacking. This paper aims (1) provide practical guidance for researchers to co-produce interventions ready for clinical trial by describing the 4-stage process we followed, the challenges experienced and practical tips for researchers wanting to co-produce an intervention for a clinical trial; (2) describe, as an exemplar, the development of our intervention package. Method: We used an Integrated Knowledge Translation (IKT) approach to co-produce a telehealth-delivered exercise program for people with stroke. The 4-stage process comprised of (1) a start-up planning phase with the co-production team. (2) Content development with knowledge user informants. (3) Design of an intervention protocol. (4) Protocol refinement. Results and reflections: The four stages of intervention development involved an 11-member co-production team and 32 knowledge user informants. Challenges faced included balancing conflicting demands of different knowledge user informant groups, achieving shared power and collaborative decision making, and optimising knowledge user input. Components incorporated into the telehealth-delivered exercise program through working with knowledge user informants included: increased training for intervention therapists; increased options to tailor the intervention to participant’s needs and preferences; and re-naming of the program. Key practical tips include ways to minimise the power differential between researchers and consumers, and ensure adequate preparation of the co-production team. Conclusion: Careful planning and a structured process can facilitate co-production of complex interventions ready for clinical trial. Graphical

Background: The aim of this trial was to evaluate the effectiveness of an online health behaviour change intervention—Prevent 2nd Stroke (P2S)—at improving health-related quality of life (HRQoL) amongst stroke survivors at 6 months of follow-up. Methods and findings: A prospective, blinded-endpoint randomised controlled trial, with stroke survivors as the unit of randomisation, was conducted between March 2018 and November 2019. Adult stroke survivors between 6 and 36 months post-stroke with capacity to use the intervention (determined by a score of ≥4 on the Modified Rankin Scale) and who had access and willingness to use the internet were recruited via mail-out invitations from 1 national and 1 regional stroke registry. Participants completed baseline (n = 399) and 6-month follow-up (n = 356; 89%) outcome assessments via computer-assisted telephone interviewing (CATI). At baseline the sample had an average age of 66 years (SD 12), and 65% were male. Randomisation occurred at the end of the baseline survey; CATI assessors and independent statisticians were blind to group allocation. The intervention group received remote access for a 12-week period to the online-only P2S program (n = 199; n = 28 lost at follow-up). The control group were emailed and posted a list of internet addresses of generic health websites (n = 200; n = 15 lost at follow-up). The primary outcome was HRQoL as measured by the EuroQol Visual Analogue Scale (EQ-VAS; self-rated global health); the outcome was assessed for differences between treatment groups at follow-up, adjusting for baseline measures. Secondary outcomes were HRQoL as measured by the EQ-5D (descriptive health state), diet quality, physical activity, alcohol consumption, smoking status, mood, physical functioning, and independent living. All outcomes included the variable ‘stroke event (stroke/transient ischaemic attack/other)’ as a covariate, and analysis was intention-to-treat. At 6 months, median EQ-VAS HRQoL score was significantly higher in the intervention group than the control group (85 vs 80, difference 5, 95% CI 0.79–9.21, p = 0.020). The results were robust to the assumption the data were missing at random; however, the results were not robust to the assumption that the difference in HRQoL between those with complete versus missing data was at least 3 points. Significantly higher proportions of people in the intervention group reported no problems with personal care (OR 2.17, 95% CI 1.05–4.48, p = 0.0359) and usual activities (OR 1.66, 95% CI 1.06–2.60, p = 0.0256) than in the control group. There were no significant differences between groups on all other secondary outcomes. The main limitation of the study is that the sample comprises mostly ‘well’ stroke survivors with limited to no disability. Conclusions: The P2S online healthy lifestyle program improved stroke survivors’ self-reported global ratings of HRQoL (as measured by EQ-VAS) at 6-month follow-up. Online platforms represent a promising tool to engage and support some stroke survivors. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12617001205325.

Clopidogrel, which is one of the most prescribed antiplatelet medications in the world, is given to stroke survivors for the prevention of secondary cardiovascular events. Clopidogrel exerts its antiplatelet activity via antagonism of the P2Y12 receptor (P2RY12). Although not widely known or considered during the initial clinical trials for clopidogrel, P2RY12 is also expressed on microglia, which are the brain’s immune cells, where the receptor facilitates chemotactic migration toward sites of cellular damage. If microglial P2RY12 is blocked, microglia lose the ability to migrate to damaged sites and carry out essential repair processes. We aimed to investigate whether administering clopidogrel to mice post-stroke was associated with (i) impaired motor skills and cognitive recovery; (ii) physiological changes, such as survival rate and body weight; (iii) changes in the neurovascular unit, including blood vessels, microglia, and neurons; and (iv) changes in immune cells. Photothrombotic stroke (or sham surgery) was induced in adult male mice. From 24 h post-stroke, mice were treated daily for 14 days with either clopidogrel or a control. Cognitive performance (memory and learning) was assessed using a mouse touchscreen platform (paired associated learning task), while motor impairment was assessed using the cylinder task for paw asymmetry. On day 15, the mice were euthanized and their brains were collected for immunohistochemistry analysis. Clopidogrel administration significantly impaired learning and memory recovery, reduced mouse survival rates, and reduced body weight post-stroke. Furthermore, clopidogrel significantly increased vascular leakage, significantly increased the number and appearance of microglia, and significantly reduced the number of T cells within the peri-infarct region post-stroke. These data suggest that clopidogrel hampers cognitive performance post-stroke. This effect is potentially mediated by an increase in vascular permeability post-stroke, providing a pathway for clopidogrel to access the central nervous system, and thus, interfere in repair and recovery processes.

Background: eHealth applications for stroke are a growing area of research that has yielded promising results. However, little is known about how stroke survivors engage with the internet, social media, and other digital technologies on a day-to-day basis. Objective: This study had three main objectives: to describe the type, frequency, and purpose of technology use among a cohort of low-morbidity stroke survivors; to investigate associations between social media use and participant factors, including sociodemographics, physical function, and independence in activities of daily living; and to investigate associations between stroke-related health risk factors and the use of the internet to search for health and medical information. Methods: This study is a secondary analysis of data obtained during a national randomized controlled trial—Prevent 2nd Stroke. The participants were stroke survivors recruited from 2 Australian stroke registries who completed 2 telephone-administered surveys to collect data on demographics and stroke characteristics; health risk factors (diet quality, physical activity, blood pressure medication, alcohol intake, anxiety and depression, and smoking status); physical functioning; independence in activities of daily living; and questions about what technology they had access to, how often they used it, and for what purposes. Participants were eligible if they had no more than a moderate level of disability (modified Rankin score ≤3) and had access to the internet. Multivariable logistic regression was used to assess the associations between social media use and sociodemographics, physical function, and independence in activities of daily living as well as associations between stroke-related health risk factors and the use of the internet to search for health and medical information. Results: Data from 354 participants were included in the analysis. Approximately 79.1% (280/354) of participants used the internet at least daily, 40.8% (118/289) accessed social media on their phone or tablet daily, and 46.4% (134/289) looked up health and medical information at least monthly. Women were 2.7 times more likely to use social media (adjusted odds ratio 2.65, 95% CI 1.51-4.72), and people aged >75 years were significantly less likely to use social media compared with those aged <55 years (adjusted odds ratio 0.17, 95% CI 0.07-0.44). Health risk factors were not found to be associated with searching for health- or medical-related information. Conclusions: The internet appears to be a viable platform to engage with stroke survivors who may not be high-morbidity to conduct research and provide information and health interventions. This is important given that they are at high risk of recurrent stroke regardless of their level of disability. Exploring the technology use behaviors and the possibility of eHealth among survivors who experience higher levels of morbidity or disability because of their stroke is an area of research that warrants further study.

Background: Following total knee arthroplasty (TKA), 10% to 20% of patients report dissatisfaction with procedural outcomes. There is growing recognition that postsurgical satisfaction is shaped not only by the quality of surgery but also by psychological and social factors. Surprisingly, information on the psychological and social determinants of surgical outcomes is rarely collected before surgery. A comprehensive collection of biopsychosocial information could assist clinicians in making recommendations in relation to rehabilitation, particularly if there is robust evidence to support the ability of presurgical constructs to predict postsurgical outcomes. Clinical decision support tools can help identify factors influencing patient outcomes and support the provision of interventions or services that can be tailored to meet individuals’ needs. However, despite their potential clinical benefit, the application of such tools remains limited. Objective: This study aims to develop a clinical decision tool that will assist with patient stratification and more precisely targeted clinical decision-making regarding prehabilitation and rehabilitation for TKA, based on the identified individual biopsychosocial needs. Methods: In this prospective observational study, all participants provided written or electronic consent before study commencement. Patient-completed questionnaires captured information related to a broad range of biopsychosocial parameters during the month preceding TKA. These included demographic factors (sex, age, and rurality), psychological factors (mood status, pain catastrophizing, resilience, and committed action), quality of life, social support, lifestyle factors, and knee symptoms. Physical measures assessing mobility, balance, and functional lower body strength were performed via video calls with patients in their home. Information related to preexisting health issues and concomitant medications was derived from hospital medical records. Patient recovery outcomes were assessed 3 months after the surgical procedure and included quality of life, patient-reported knee symptoms, satisfaction with the surgical procedure, and mood status. Machine learning data analysis techniques will be applied to determine which presurgery parameters have the strongest power for predicting patient recovery following total knee replacement. On the basis of these analyses, a predictive model will be developed. Predictive models will undergo internal validation, and Bayesian analysis will be applied to provide additional metrics regarding prediction accuracy. Results: Patient recruitment and data collection commenced in November 2019 and was completed in June 2022. A total of 1050 patients who underwent TKA were enrolled in this study. Conclusions: Our findings will facilitate the development of the first comprehensive biopsychosocial prediction tool, which has the potential to objectively predict a patient’s individual recovery outcomes following TKA once selected by an orthopedic surgeon to undergo TKA. If successful, the tool could also inform the evolution rehabilitation services, such that factors in addition to physical performance can be addressed and have the potential to further enhance patient recovery and satisfaction. International Registered Report Identifier (IRRID): DERR1-10.2196/48801