Participation in physical activity (PA) is a cornerstone of the secondary prevention of stroke. Given the heterogeneous nature of stroke, PA interventions that are adaptive to individual performance capability and associated co-morbidity levels are recommended. Mobile health (mHealth) has been identified as a potential approach to supporting PA post-stroke. To this end, we used a Sequential Multiple Assignment Randomised Trial design to develop an adaptive, mHealth intervention to improve PA post-stroke – The Adaptive Physical Activity programme in Stroke (TAPAS) (Clinicaltrials.Gov NCT05606770). As the first trial in stroke recovery literature to use this design, there is an opportunity to conduct a process evaluation for this type of adaptive intervention. The aim of this process evaluation is to examine the implementation process, mechanism of change and contextual influences of TAPAS among ambulatory people with stroke in the community.

Guided by the Medical Research Council Framework for process evaluations, qualitative and quantitative methods will be used to examine the (1) implementation process and the content of TAPAS (fidelity adaptation, dose and reach); (2) mechanisms of change (participants’ response to the intervention; mediators; unexpected pathways and consequences) and (3) influence of the context of the intervention. Quantitative data will be presented descriptively, for example, adherence to exercise sessions. Qualitative data will be collected among TAPAS participants and the interventionist using semi-structured one-to-one or focus group interviews. Transcribed interviews will be analysed using reflexive thematic analysis. Key themes and sub-themes will be developed.

Ethical approval has been granted by the Health Service Executive Mid-Western Ethics Committee (REC Ref: 026/2022) (25/03/2024). The findings will be submitted for publication and presented at relevant national and international academic conferences.

Women with gestational diabetes mellitus (GDM) are at seven-fold to ten-fold increased risk of type 2 diabetes mellitus (T2DM) when compared with those who experience a normoglycaemic pregnancy, and the cumulative incidence increases with the time of follow-up post birth. This protocol outlines the development and validation of a risk prediction model assessing the 5-year and 10-year risk of T2DM in women with a prior GDM diagnosis.

Data from all birth mothers and registered births in Victoria and South Australia, retrospectively linked to national diabetes data and pathology laboratory data from 2008 to 2021, will be used for model development and validation of GDM to T2DM conversion. Candidate predictors will be selected considering existing literature, clinical significance and statistical association, including age, body mass index, parity, ethnicity, history of recurrent GDM, family history of T2DM and antenatal and postnatal glucose levels. Traditional statistical methods and machine learning algorithms will explore the best-performing and easily applicable prediction models. We will consider bootstrapping or K-fold cross-validation for internal model validation. If computationally difficult due to the expected large sample size, we will consider developing the model using 80% of available data and evaluating using a 20% random subset. We will consider external or temporal validation of the prediction model based on the availability of data. The prediction model’s performance will be assessed by using discrimination (area under the receiver operating characteristic curve, calibration (calibration slope, calibration intercept, calibration-in-the-large and observed-to-expected ratio), model overall fit (Brier score and Cox-Snell R2) and net benefit (decision curve analysis). To examine algorithm equity, the model’s predictive performance across ethnic groups and parity will be analysed. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis-Artificial Intelligence (TRIPOD+AI) statements will be followed.

Ethics approvals have been received from Deakin University Human Research Ethics Committee (2021–179); Monash Health Human Research Ethics Committee (RES-22-0000-048A); the Australian Institute of Health and Welfare (EO2022/5/1369); the Aboriginal Health Research Ethics Committee of South Australia (SA) (04-23-1056); in addition to a Site-Specific Assessment to cover the involvement of the Preventative Health SA (formerly Wellbeing SA) (2023/SSA00065). Project findings will be disseminated in peer-reviewed journals and at scientific conferences and provided to relevant stakeholders to enable the translation of research findings into population health programmes and health policy.

The COVID-19 pandemic dramatically affected schools. However, there are insufficient data on the chronic physical and mental health consequences of the pandemic in school workers.

To determine the prevalence and the functional and mental health impact of pandemic-related chronic health symptoms among school workers towards the end of the COVID-19 pandemic.

Cross-sectional analysis of health questionnaires and serology testing data (nucleocapsid, N antibodies) collected between January and April 2023, within a cohort of school workers.

Three large school districts (Vancouver, Richmond, Delta) in the Vancouver metropolitan area, Canada (representing 186 elementary and secondary schools in total).

Active school staff employed in these three school districts.

COVID-19 infection history by self-reported viral and/or nucleocapsid antibody testing.

Self-reported, new-onset pandemic-related chronic health symptoms that started within the past year, lasting at least 3 months, after a positive viral test among those with a known infection.

Of 1128 school staff enrolled from 185/186 (99.5%) schools, 1086 (96.3%) and 998 (88.5%) staff completed health questionnaires and serology testing, respectively. The N-seroprevalence adjusted for clustering by school and test sensitivity and specificity was 84.7% (95% Credible Interval (95% CrI): 79.2% to 91.8%) compared with 85.4% (95% CrI: 81.6% to 90.3%) in a community-matched sample of blood donors. Overall, 31.1% (95% CI: 28.4% to 34.0%) staff reported new-onset chronic symptoms. These symptoms were more frequently reported in staff with viral test-confirmed infections (38.0% (95% CI: 34.3% to 41.9%)) compared with those with positive serology who were unaware that they had COVID-19 (14.3% (95% CI: 7.6% to 23.6%); p

The pandemic had major health impacts on school workers. To our knowledge, this study is among the first to concurrently quantify a broad range of chronic physical and mental health impacts, highlighting the need for further research and targeted health programmes to address this significant burden.