Improving sustainable transportation options will help cities tackle growing challenges related to population health, congestion, climate change and inequity. Interventions supporting active transportation face many practical and political hurdles. Implementation science aims to understand how interventions or policies arise, how they can be translated to new contexts or scales and who benefits. Sustainable transportation interventions are complex, and existing implementation science frameworks may not be suitable. To apply and adapt implementation science for healthy cities, we have launched our mixed-methods research programme, CapaCITY/É. We aim to understand how, why and for whom sustainable transportation interventions are successful and when they are not.

Across nine Canadian municipalities and the State of Victoria (Australia), our research will focus on two types of sustainable transportation interventions: all ages and abilities bicycle networks and motor vehicle speed management interventions. We will (1) document the implementation process and outcomes of both types of sustainable transportation interventions; (2) examine equity, health and mobility impacts of these interventions; (3) advance implementation science by developing a novel sustainable transportation implementation science framework and (4) develop tools for scaling up and scaling out sustainable transportation interventions. Training activities will develop interdisciplinary scholars and practitioners able to work at the nexus of academia and sustainable cities.

This study received approval from the Simon Fraser University Office of Ethics Research (H22-03469). A Knowledge Mobilization Hub will coordinate dissemination of findings via a website; presentations to academic, community organisations and practitioner audiences; and through peer-reviewed articles.

We conducted an updated systematic review and meta-analysis to investigate the effect of colchicine treatment on clinical outcomes in patients with COVID-19.

Systematic review and meta-analysis.

We searched PubMed, Embase, the Cochrane Library, medRxiv and ClinicalTrials.gov from inception to January 2023.

All randomised controlled trials (RCTs) that investigated the efficacy of colchicine treatment in patients with COVID-19 as compared with placebo or standard of care were included. There were no language restrictions. Studies that used colchicine prophylactically were excluded.

We extracted all information relating to the study characteristics, such as author names, location, study population, details of intervention and comparator groups, and our outcomes of interest. We conducted our meta-analysis by using RevMan V.5.4 with risk ratio (RR) and mean difference as the effect measures.

We included 23 RCTs (28 249 participants) in this systematic review. Colchicine did not decrease the risk of mortality (RR 0.99; 95% CI 0.93 to 1.05; I²=0%; 20 RCTs, 25 824 participants), with the results being consistent among both hospitalised and non-hospitalised patients. There were no significant differences between the colchicine and control groups in other relevant clinical outcomes, including the incidence of mechanical ventilation (RR 0.75; 95% CI 0.48 to 1.18; p=0.22; I²=40%; 8 RCTs, 13 262 participants), intensive care unit admission (RR 0.77; 95% CI 0.49 to 1.22; p=0.27; I²=0%; 6 RCTs, 961 participants) and hospital admission (RR 0.74; 95% CI 0.48 to 1.16; p=0.19; I²=70%; 3 RCTs, 8572 participants).

The results of this meta-analysis do not support the use of colchicine as a treatment for reducing the risk of mortality or improving other relevant clinical outcomes in patients with COVID-19. However, RCTs investigating early treatment with colchicine (within 5 days of symptom onset or in patients with early-stage disease) are needed to fully elucidate the potential benefits of colchicine in this patient population.

CRD42022369850.

Understanding human mobility’s role in malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission.

We measure community connectivity across the study area using a respondent driven sampling design among key informants who are at least 18 years of age. 45 initial communities will be selected: 10 in Brazil, 10 in Ecuador and 25 in Peru. Participants will be recruited in each initial node and administered a survey to obtain data on each community’s mobility patterns. Survey responses will be ranked and the 2–3 most connected communities will then be selected and surveyed. This process will be repeated for a third round of data collection. Community network matrices will be linked with each country’s malaria surveillance system to test the effects of mobility on disease risk.

This study protocol has been approved by the institutional review boards of Duke University (USA), Universidad San Francisco de Quito (Ecuador), Universidad Peruana Cayetano Heredia (Peru) and Universidade Federal Minas Gerais (Brazil). Results will be disseminated in communities by the end of the study.

Globally, cardiovascular disease (CVD) remains the leading cause of death, warranting effective management and prevention measures. Risk prediction tools are indispensable for directing primary and secondary prevention strategies for CVD and are critical for estimating CVD risk. Machine learning (ML) methodologies have experienced significant advancements across numerous practical domains in recent years. Several ML and statistical models predicting CVD time-to-event outcomes have been developed. However, it is not known as to which of the two model types—ML and statistical models—have higher discrimination and calibration in this regard. Hence, this planned work aims to systematically review studies that compare ML with statistical methods in terms of their predictive abilities in the case of time-to-event data with censoring.

Original research articles published as prognostic prediction studies, which involved the development and/or validation of a prognostic model, within a peer-reviewed journal, using cohort or experimental design with at least a 12-month follow-up period will be systematically reviewed. The review process will adhere to the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist.

Ethical approval is not required for this review, as it will exclusively use data from published studies. The findings of this study will be published in an open-access journal and disseminated at scientific conferences.

CRD42023484178.

An important obstacle in the fight against diabetic retinopathy (DR) is the use of a classification system based on old imaging techniques and insufficient data to accurately predict its evolution. New imaging techniques generate new valuable data, but we lack an adapted classification based on these data. The main objective of the Evaluation Intelligente de la Rétinopathie Diabétique, Intelligent evaluation of DR (EviRed) project is to develop and validate a system assisting the ophthalmologist in decision-making during DR follow-up by improving the prediction of its evolution.

A cohort of up to 5000 patients with diabetes will be recruited from 18 diabetology departments and 14 ophthalmology departments, in public or private hospitals in France and followed for an average of 2 years. Each year, systemic health data as well as ophthalmological data will be collected. Both eyes will be imaged by using different imaging modalities including widefield photography, optical coherence tomography (OCT) and OCT-angiography. The EviRed cohort will be divided into two groups: one group will be randomly selected in each stratum during the inclusion period to be representative of the general diabetic population. Their data will be used for validating the algorithms (validation cohort). The data for the remaining patients (training cohort) will be used to train the algorithms.

The study protocol was approved by the French South-West and Overseas Ethics Committee 4 on 28 August 2020 (CPP2020-07-060b/2020-A01725-34/20.06.16.41433). Prior to the start of the study, each patient will provide a written informed consent documenting his or her agreement to participate in the clinical trial. Results of this research will be disseminated in peer-reviewed publications and conference presentations. The database will also be available for further study or development that could benefit patients.

NCT04624737

To analyse monthly changes in public access defibrillation (PAD) incidence and outcomes of out-of-hospital cardiac arrest (OHCA) during the 2020–2021 COVID-19 pandemic compared with those during the 2016–2019 prepandemic period with consideration of pandemic-related movement restriction.

Retrospective cohort study.

An extended database was created by combining and reconciling the nationwide Utstein-style OHCA and the emergency medical service (EMS) transportation databases in Japan.

We analysed 226 182 EMS-witnessed, non-newborn and out-of-home OHCA cases in Japan.

The primary outcomes were the PAD incidence and neurologically favourable 1-month survival rate. The secondary outcomes were bystander cardiopulmonary resuscitation (CPR) provision and dispatcher-assisted CPR attempts.

The proportion of out-of-home OHCA cases slightly decreased during the pandemic (from 33.7% to 31.9%). Although the pandemic was associated with a decreased PAD incidence, 2-year trend analyses by an interaction test showed that the PAD incidence was lower during the first nationwide declaration of a state of emergency (p

Prolonged and repeated movement restrictions during the COVID-19 pandemic worsened the OHCA outcomes concurrently with disturbed BLS actions, including the reduced PAD incidence in out-of-home settings. Maintaining BLS training, re-arranging automated external defibrillator placement and establishing a local alert system for recruiting well-trained citizens to the scene are essential.

Inadequate counselling of pregnant women regarding pregnancy danger signs contributes to a delay in deciding to seek care, which causes up to 77% of all maternal deaths in developing countries. However, its spatial variation and region-specific predictors have not been studied in Ethiopia. Hence, the current study aimed to model its predictors using geographically weighted regression analysis.

The 2019 Ethiopian Mini Demographic and Health Survey data were used. A total weighted sample of 2922 women from 283 clusters was included in the final analysis. The analysis was performed using ArcGIS Pro, STATA V.14.2 and SaTScan V.10.1 software. The spatial variation of inadequate counselling was examined using hotspot analysis. Ordinary least squares regression was used to identify factors for geographical variations. Geographically weighted regression was used to explore the spatial heterogeneity of selected variables to predict inadequate counselling.

Significant hotspots of inadequate counselling regarding pregnancy danger signs were found in Gambella region, the border between Amhara and Afar regions, Somali region and parts of Oromia region. Antenatal care provided by health extension workers, late first antenatal care initiation and antenatal care follow-up at health centres were spatially varying predictors. The geographically weighted regression model explained about 66% of the variation in the model.

Inadequate counselling service regarding pregnancy danger signs in Ethiopia varies across regions and there exists within country inequality in the service provision and utilisation. Prioritisation and extra efforts should be made by concerned actors for those underprivileged areas and communities (as shown in the maps), and health extension workers, as they are found in the study.

Unintended teenage pregnancies have become a global public health challenge, particularly in sub-Saharan Africa. There is a notably high prevalence of unintended pregnancies among unmarried teenagers in Uganda. This study will develop an intervention programme using mobile money shops (vendors) as a platform to deliver sexual and reproductive health and rights (SRHR) services to teenagers and assess its effectiveness and scalability in Uganda.

This hybrid study comprises two integral components: an intervention study to assess the effectiveness of vendor-mediated intervention and implementation research to evaluate the implementation process. 30 vendors will be recruited for both intervention and control arms in 2 municipalities in Eastern Uganda, which have a high unintended pregnancy prevalence rate among unmarried teens aged 15–19 years. A preintervention and postintervention repeated survey involving 600 participants for each arm will be conducted over 4 months. The primary outcome is the rate of condom users among teenage vendor users. The secondary outcomes include the rate of preference for receiving SRHR services at vendors and knowledge regarding SRHR. A difference-in-differences analysis will be used to determine the effectiveness of the intervention. The Bowen model will be employed to evaluate the implementation design.

Ethical approval was obtained from the Ethics Review Committee of Uganda Christen University and JICA Ogata Sadako Research Institute for Peace and Development in Japan. The findings will be widely disseminated. This study was registered with the University Hospital Medical Information Network in Japan (UMIN000053332) on 12 January 2024.

UMIN000053332.

Mental Health Literacy (MHL) is important for improving mental health and reducing inequities in treatment. The Mental Health Literacy Scale (MHLS) is a valid and reliable assessment tool for MHL. This systematic review will examine and compare the measurement properties of the MHLS in different languages, enabling academics, clinicians and policymakers to make informed judgements regarding its use in assessments.

The review will adhere to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology for systematic reviews of patient-reported outcome measures and the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis and will be presented following the Preferred Reporting Items for Systematic reviews and Meta-Analysis 2020 checklist. The review will be conducted in four stages, including an initial search confined to PubMed, a search of electronic scientific databases PsycINFO, CINAHL, Scopus, MEDLINE, Embase (Elsevier), PubMed (NLM) and ERIC, an examination of the reference lists of all papers to locate relevant publications and finally contacting the MHLS original author to identify validation studies that the searches will not retrieve. These phases will assist us in locating studies that evaluate the measurement properties of MHLS across various populations, demographics and contexts. The search will focus on articles published in English between May 2015 and December 2023. The methodological quality of the studies will be evaluated using the COSMIN Risk of Bias checklist, and a comprehensive qualitative and quantitative data synthesis will be performed.

Ethics approval is not required. The publication will be in peer-reviewed journals and presented at national and international conferences.

CRD42023430924.

Deep brain stimulation (DBS) can be used to treat several neurological and psychiatric conditions such as Parkinson’s disease, epilepsy and obsessive-compulsive disorder; however, limited work has been done to assess the disparities in DBS access and implementation. The goal of this scoping review is to identify sources of disparity in the clinical provision of DBS.

A scoping review will be conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-extension for Scoping Reviews methodology. Relevant studies will be identified from databases including MEDLINE/PubMed, EMBASE and Web of Science, as well as reference lists from retained articles. Initial search dates were in January 2023, with the study still ongoing. An initial screening of the titles and abstracts of potentially eligible studies will be completed, with relevant studies collected for full-text review. The principal investigators and coauthors will then independently review all full-text articles meeting the inclusion criteria. Data will be extracted and collected in table format. Finally, results will be synthesised in a table and narrative report.

No institutional board review or approval is necessary for the proposed scoping review. The findings will be submitted for publication to relevant peer-reviewed journals and conferences.

This protocol has been registered prospectively on the Open Science Framework (https://osf.io/cxvhu).

Time is a fundamental component of acute stroke and transient ischaemic attack (TIA) care, thus minimising prehospital delays is a crucial part of the stroke chain of survival. COVID-19 restrictions were introduced in Ireland in response to the pandemic, which resulted in major societal changes. However, current research on the effects of the COVID-19 pandemic on prehospital care for stroke/TIA is limited to early COVID-19 waves. Thus, we aimed to investigate the effect of the COVID-19 pandemic on ambulance time intervals and suspected stroke/TIA call volume for adults with suspected stroke and TIA in Ireland, from 2018 to 2021.

We conducted a secondary data analysis with a quasi-experimental design.

We used data from the National Ambulance Service in Ireland. We defined the COVID-19 period as ‘1 March 2020–31 December 2021’ and the pre-COVID-19 period ‘1 January 2018–29 February 2020’.

We compared five ambulance time intervals: ‘allocation performance’, ‘mobilisation performance’, ‘response time’, ‘on scene time’ and ‘conveyance time’ between the two periods using descriptive and regression analyses. We also compared call volume for suspected stroke/TIA between the pre-COVID-19 and COVID-19 periods using interrupted time series analysis.

We included all suspected stroke/TIA cases ≥18 years who called the National Ambulance Service from 2018 to 2021.

40 004 cases were included: 19 826 in the pre-COVID-19 period and 19 731 in the COVID-19 period. All ambulance time intervals increased during the pandemic period compared with pre-COVID-19 (p

A ’shock' like a pandemic has a negative impact on the prehospital phase of care for time-sensitive conditions like stroke/TIA. System evaluation and public awareness campaigns are required to ensure maintenance of prehospital stroke pathways amidst future healthcare crises. Thus, this research is relevant to routine and extraordinary prehospital service planning.

A shared consensus on the safety about physical agent modalities (PAMs) practice in physiotherapy and rehabilitation is lacking. We aimed to develop evidence-informed and consensus-based statements about the safety of PAMs.

A RAND-modified Delphi Rounds’ survey was used to reach a consensus. We established a steering committee of the Italian Association of Physiotherapy (Associazione Italiana di Fisioterapia) to identify areas and questions for developing statements about the safety of the most commonly used PAMs in physiotherapy and rehabilitation. We invited 28 National Scientific and Technical Societies, including forensics and lay members, as a multidisciplinary and multiprofessional panel of experts to evaluate the nine proposed statements and formulate additional inputs. The level of agreement was measured using a 9-point Likert scale, with consensus in the Delphi Rounds assessed using the rating proportion with a threshold of 75%.

Overall, 17 (61%) out of 28 scientific and technical societies participated, involving their most representative members. The panel of experts mainly consisted of clinicians (88%) with expertise in musculoskeletal (47%), pelvic floor (24%), neurological (18%) and lymphatic (6%) disorders with a median experience of 30 years (IQR=17–36). Two Delphi rounds were necessary to reach a consensus. The final approved criteria list comprised nine statements about the safety of nine PAMs (ie, electrical stimulation neuromodulation, extracorporeal shock wave therapy, laser therapy, electromagnetic therapy, diathermy, hot thermal agents, cryotherapy and therapeutic ultrasound) in adult patients with a general note about populations subgroups.

The resulting consensus-based statements inform patients, healthcare professionals and policy-makers regarding the safe application of PAMs in physiotherapy and rehabilitation practice. Future research is needed to extend this consensus on paediatric and frail populations, such as immunocompromised patients.

To examine the relative importance of the drivers of mental health care-seeking intention and how these, along with intention itself, are geographically distributed across integrated care systems (ICS) and health boards (HBs) in the UK. Also, to examine the degree of acceptance of virtual modes of care.

Community-based cross-sectional survey.

A national online survey of 17 309 adults between August and September 2021 recruited via a research technology company, Lucid. Sample size quotas were set to ensure coverage across the UK and match population distributions for gender, age and ethnicity. After exclusions, 16 835 participants remained (54% female, 89% white).

Care-seeking intention, using a continuous measure of likelihood and a categorical measure of estimated time to seek professional help for a future mental health difficulty.

20.5% (95% CI 19.8% to 21.2%) reported that they would significantly delay or never seek mental healthcare, ranging from 8.3% to 25.7% across ICS/HBs. Multilevel regression analysis showed mental health knowledge was the most predictive of care-seeking intention, followed by attitudes towards others with mental illness and a combination of stigma, negative attitudes to treatment and instrumental barriers to accessing care. The model explained 17% of the variance. There was substantial geographical variation in prevalence of preclinical symptoms of depression and anxiety, attitudes to mental health, and barriers to care, leading to complex ICS/HB profiles. Remote and self-guided therapies did not pose as a major barrier to care with more than half of respondents likely or very likely to use them.

Our locally relevant and actionable findings suggest possible interventions that may improve care-seeking intention and indicate which of these interventions need to be geographically tailored to have maximal effect.

For artificial intelligence (AI) to help improve mental healthcare, the design of data-driven technologies needs to be fair, safe, and inclusive. Participatory design can play a critical role in empowering marginalised communities to take an active role in constructing research agendas and outputs. Given the unmet needs of the LGBTQI+ (Lesbian, Gay, Bisexual, Transgender, Queer and Intersex) community in mental healthcare, there is a pressing need for participatory research to include a range of diverse queer perspectives on issues of data collection and use (in routine clinical care as well as for research) as well as AI design. Here we propose a protocol for a Delphi consensus process for the development of PARticipatory Queer AI Research for Mental Health (PARQAIR-MH) practices, aimed at informing digital health practices and policy.

The development of PARQAIR-MH is comprised of four stages. In stage 1, a review of recent literature and fact-finding consultation with stakeholder organisations will be conducted to define a terms-of-reference for stage 2, the Delphi process. Our Delphi process consists of three rounds, where the first two rounds will iterate and identify items to be included in the final Delphi survey for consensus ratings. Stage 3 consists of consensus meetings to review and aggregate the Delphi survey responses, leading to stage 4 where we will produce a reusable toolkit to facilitate participatory development of future bespoke LGBTQI+–adapted data collection, harmonisation, and use for data-driven AI applications specifically in mental healthcare settings.

PARQAIR-MH aims to deliver a toolkit that will help to ensure that the specific needs of LGBTQI+ communities are accounted for in mental health applications of data-driven technologies. The study is expected to run from June 2024 through January 2025, with the final outputs delivered in mid-2025. Participants in the Delphi process will be recruited by snowball and opportunistic sampling via professional networks and social media (but not by direct approach to healthcare service users, patients, specific clinical services, or via clinicians’ caseloads). Participants will not be required to share personal narratives and experiences of healthcare or treatment for any condition. Before agreeing to participate, people will be given information about the issues considered to be in-scope for the Delphi (eg, developing best practices and methods for collecting and harmonising sensitive characteristics data; developing guidelines for data use/reuse) alongside specific risks of unintended harm from participating that can be reasonably anticipated. Outputs will be made available in open-access peer-reviewed publications, blogs, social media, and on a dedicated project website for future reuse.