There is limited evidence on whether having pre-existing cardiovascular disease (CVD) or risk factors for CVD such as diabetes, ensures greater knowledge of risk factors important for motivating preventative behaviours. Our objective was to compare knowledge among the Australian public participating in a health check program and their risk status. Data from the Stroke Foundation ‘Know your numbers’ program were used. Staff in community pharmacies provided opportunistic health checks (measurement of blood pressure and diabetes risk assessment) among their customers. Participants were categorised: 1) CVD ± risk of CVD: history of stroke, heart disease or kidney disease, and may have risk factors; 2) risk of CVD only: reported having high blood pressure, high cholesterol, diabetes or atrial fibrillation; and 3) CVD risk free (no CVD or risk of CVD). Multivariable logistic regression analyses were performed including adjustment for age and sex. Among 4,647 participants, 12% had CVD (55% male, 85% aged 55+ years), 47% were at risk of CVD (40% male, 72% 55+ years) and 41% were CVD risk free (33% male, 27% 55+ years). Participants with CVD (OR: 0.66; 95% CI: 0.55, 0.80) or risk factors for CVD (OR: 0.65; 95% CI: 0.57, 0.73) had poorer knowledge of the risk factors for diabetes/CVD compared to those who were CVD risk free. After adjustment, only participants with risk factors for CVD (OR: 0.80; 95% CI: 0.69, 0.93) had poorer knowledge. Older participants (55+ years) and men had poorer knowledge of diabetes/CVD risk factors and complications of diabetes. Participants with poorer knowledge of risk factors were older, more often male or were at risk of developing CVD compared with those who were CVD risk free. Health education in these high risk groups should be a priority, as diabetes and CVD are increasing in prevalence throughout the world.

Objective: To describe stroke research activity in Australian acute public hospitals and determine if participation in research provides better quality of care and outcomes for patients with stroke. Methods: This was an observational study using data from hospitals that participated in the National Stroke Foundation (Australia) acute services audit program in 2009, 2011, and 2013. This included self-reported organizational features and a retrospective clinical audit of up to 40 medical records of patients with stroke from each hospital. Multilevel random effects logistic regression with level defined as hospital and adjustments for hospital, demographic, clinical, and stroke severity factors were undertaken. Results: A total of 240 hospitals submitted organizational data. Hospitals with a stroke unit (70% vs 7%, p < 0.001) and >200 stroke admissions per year (80% vs 17%, p < 0.001) reported greater involvement in research studies. Of 9,537 patients audited at 129 hospitals, 469 (5%) consented to participate in research. Patients who participated in research compared to nonparticipants were likely to be younger (median age 73 years; 25th percentile [Q1]: 63, 75th percentile [Q3]: 80, vs median age 76 years Q1: 64, Q3: 83; p < 0.001) and receive important clinical practices such as a swallow screen/assessment prior to oral intake (62% vs 56%; p < 0.01). An independent association with reduced in-hospital mortality (adjusted odds ratio 0.30, 95% confidence interval 0.12, 0.76) was evident if participating in research regardless of access to stroke unit care. Conclusions: Patients who participate in stroke research receive better in-hospital care and are more likely to survive compared to nonresearch participants. Classification of evidence: This study provides Class III evidence that patients with stroke who participate in research receive better quality of care and have reduced in-hospital mortality.

Stroke coordinators have been inconsistently used in various countries to support stroke care in hospital. To investigate the association between stroke coordinators and the provision of evidence-based care and patient outcomes in hospitals with acute stroke units. Observational study using cross-sectional data from the 2015 National Acute Services Audit Program (Australia): including a retrospective medical record audit (40 records from each hospital) and a self-reported survey of organizational resources for stroke. Multilevel random effects logistic regression for patient outcomes including complications, independence on discharge, and death. Median regression for length of stay comparisons. A total of 109 hospitals submitted 4060 cases; 59 (54%) had a stroke coordinator. Compared with patients from stroke unit hospitals with no stroke coordinator (N = 33, 1333 cases), patients in stroke unit hospitals with a stroke coordinator (N = 53, 2072 cases) were more likely to receive clinical practices including rehabilitation therapy within 48 hours of initial assessment (88 vs. 82%, p < 0.001), risk factor modification advice (62 vs. 55%, p = 0.003) and receive a discharge care plan (65 vs. 48%, p < 0.001). No differences in complications, independence on discharge, or deaths were evident. Patients from hospitals with a stroke coordinator were more likely to access inpatient rehabilitation (adjusted odds ratio 1.8, 95% confidence interval 1.1–2.8) and have a reduced length of acute stay if discharged (median 14 h, p = 0.03). Presence of stroke coordinators was associated with reduced length of stay and improved delivery of evidence-based care in hospitals with a stroke unit.

Since 2007, the Australian Know your numbers (KYN) program has been used in community settings to raise awareness about blood pressure and stroke. In 2011, the program was modified to include assessment for type 2 diabetes risk. However, it is unclear which approach for assessing diabetes risk in pharmacies is best. We compared two methods: random (non-fasting) blood glucose testing (RBGT); and the Australian type 2 diabetes risk assessment tool (AUSDRISK); according to 1) identification of ‘high risk’ participants including head-to-head sensitivity and specificity; 2) number of referrals to doctors; and 3) feasibility of implementation. 117 Queensland pharmacies voluntarily participated and were randomly allocated to RBGT and AUSDRISK or AUSDRISK only. Although discouraged, pharmacies were able to change allocated group prior to commencement. AUSDRISK is a validated self-administered questionnaire used to calculate a score that determines the 5-year risk of developing type 2 diabetes. AUSDRISK (score 12+) or RBGT (≥5.6 mmol/I) indicates a high potential risk of diabetes. Median linear regression was used to compare the two measures. Staff from 68 pharmacies also participated in a semi-structured interview during a site visit to provide feedback. Data were submitted for 5,483 KYN participants (60% female, 66% aged >55 years, 10% history of diabetes). Approximately half of the participants without existing diabetes were identified as ‘high risk’ based on either RBGT or AUSDRISK score. Among participants who undertook both measures, 32% recorded a high RBGT and high AUSDRISK. There was a significant association between RBGT and AUSDRISK scores. For every one point increase in AUSDRISK score there was a half point increase in RBGT levels (coefficient 0.55, 95% CI: 0.28, 0.83). Pharmacy staff reported that AUSDRISK was a simple, low cost and efficient method of assessing diabetes risk compared with RBGT, e.g. since management of sharps is not an issue. In a large, community-based sample of Australians about half of the participants without diabetes were at ‘high risk ‘of developing diabetes based on either AUSDRISK or RBGT results. AUSDRISK was considered to be an acceptable method for assessing the risk of diabetes using opportunistic health checks in community pharmacies.

Background: Co‐design helps to align research with end‐user needs, but there is no consistent method for reporting co‐design methodology and evaluation. We share our experiences co‐designing the Love Your Brain digital platform for stroke prevention. We evaluated the core attributes that guided our co‐design approach, including recruitment, focus group coordination, participant engagement and satisfaction. Methods: Online co‐design focus groups were conducted fortnightly (May 2023 to March 2024) with two cohorts (health knowledge experts and community members; n = 8 sessions per cohort) to design the content and structure of Love Your Brain. Snowballing methods and purposive sampling were used to recruit participants in Australia. Coordination involved tracking the time spent by the research team for one round of focus groups. Participant engagement was measured through focus group attendance and survey feedback and analysed using descriptive statistics and thematic analysis. Count and length of verbal and/or written contributions during focus groups were summarised with descriptive statistics as a measure of engagement, with differences between cohorts assessed using χ ² /Wilcoxon rank‐sum tests. Participant satisfaction was evaluated using survey responses and input at a final evaluative focus group. Results: Sixteen health knowledge experts (clinicians/researchers) and 28 community members expressed interest, of which 10 health knowledge experts and 12 community members (including 9 people with lived experience of stroke) participated. Conducting two identical focus groups required 29 h of project manager/coordinator time, 8–11 h for facilitators and 6.5–8.5 h for chief investigators. Most participants (86%) attended ≥ 5/8 focus groups. Engagement was enhanced through pre‐reading material, structured/well‐organised focus groups and experienced facilitators. All participants contributed at each focus group, with varying levels of input. Health knowledge experts preferred written contributions over verbal contributions and wrote longer messages compared to community members. Community members spoke for a longer duration than health knowledge experts. Participant satisfaction was high, with participants reporting that the research team ‘always valued our opinions’. Importance was placed on a final evaluative focus group, and participants stated that their contributions were incorporated into the final product. Conclusion: Our research emphasises relationships between coordination, participant engagement and satisfaction and the importance of considering resourcing requirements for successful co‐design of digital health projects. Patient or Public Contribution: People with lived experience, including caregivers of people with stroke, and members of the public, participated in the co‐design focus groups. The Love Your Brain Management Committee includes people with lived experience of stroke who contributed to the oversight of this study and the preparation of this manuscript.