Mental health issues such as depression and anxiety are highly and disproportionally prevalent among university students. Beyond the academic rigour, stressors imposed by a new environment result in them being vulnerable to the onset and manifestation of mental health symptomatology. Leveraging smartphones and wearables for digital phenotyping capabilities is an innovative approach for monitoring and intervening in the mental health conditions of university students. This provides a unique opportunity to collect and identify digital and behavioural biomarkers, subsequently enabling the development of predictive models to identify university students at risk.

This study—Brightline—will employ an observational study design over a 6-month period, recruiting 500 students from a major public university in Singapore. Passive data collection will occur continuously throughout the monitoring period through a wearable device (Fitbit Charge 6) and smartphone sensors via the Brightline app, which uses a digital phenotyping data collection platform. Active data collection will consist of self-report questionnaires to be completed at the beginning of the study and follow-up assessments at 1, 3 and 6 months after. The passive and active data collected will be analysed to identify the digital biomarkers associated with depression, anxiety, stress, loneliness and affect among university students. Predictive models of these mental health issues will also be developed.

This study was approved by the Nanyang Technological University Institutional Review Board (IRB-2023-894). Findings from this study will be published in peer-reviewed journals and presented at academic conferences.

NCT06770075.

To provide bottom-up guidance on improving post-COVID care using patients’ experiences with received care and their perceived health

Qualitative study design using focus group interviews

30 patients with post-COVID condition recruited through purposive sampling based on patient complexity and diversity

Three dimensions for potential improvements of post-COVID care were identified: (1) building, supporting and maintaining patient resilience, (2) redesigning healthcare pathways to meet patient needs and (3) embedding post-COVID care in health systems and organisations. A conceptual framework that could guide improvements in post-COVID care was developed.

This study revealed several opportunities for improving and implementing post-COVID care following a person-centred approach in multidisciplinary integrated care pathways with an integrative vision of health.

Despite global efforts, gender disparities in oncology may persist. Understanding these disparities within the context of major conferences can inform strategies to promote gender inclusiveness in the field. This study evaluates the participation of women and men at the American Society of Clinical Oncology (ASCO) 2024 congress, focusing on chairs, speakers and audience questioners.

Observational study.

152 recorded sessions of the ASCO 2024 annual meeting, one of the largest conferences in the field of oncology, available on the ASCO website.

Individuals serving as chairs, speakers and audience members who asked questions.

In this observational study, gender for chairs, speakers and audience questioners across 152 sessions of the ASCO 2024 congress was assessed by two independent reviewers using audio and video recordings. Speaking times for questions and responses were also evaluated. Statistical analyses, including ² and unpaired t-tests, were conducted to analyse the data.

Women were well represented as chairs (n=124) and speakers (n=402) in 66% and 95% of sessions, respectively. However, only 21% of questions from the audience were posed by women, while 37% of questions were asked by men and 42% online or by chairs/speakers. Women were more likely to pose questions when the sessions were chaired by women (71% vs 53%; p=0.047). There were no statistically significant gender disparities concerning speaking time (questions: p=0.30; responses: 0.53). The response dynamics indicated a pattern of gender homogeneity, with individuals more frequently responding to questions from their own gender.

While the balanced representation of women in leadership roles at the ASCO 2024 congress reflects positive development in gender equality, disparities in active participation persist. These findings underscore the need for strategies that not only promote women in visible roles but also foster an environment that supports their active engagement in scientific discussions.

During the COVID-19 pandemic, a substantial decrease was observed in hospital admissions and in-hospital procedures for patients with acute cardiovascular diseases (CVDs). The extent to which measures to prevent COVID-19 transmission, for example, lockdowns, affected the outpatient care of patients at higher cardiovascular risk remains unclear. We aimed to compare outpatient department (OPD) attendance, cardiovascular risk management (CVRM) and cardiovascular health (CVH) of patients at higher cardiovascular risk referred to an OPD of a tertiary care centre between preCOVID-19, during and postCOVID-19 periods.

We included all adult patients at higher cardiovascular risk referred to the cardiology, vascular medicine, diabetology, geriatrics, nephrology or multidisciplinary vascular surgery OPDs of the University Medical Centre Utrecht, the Netherlands, between March 2019 and December 2022, in a prospective cohort study.

We assessed trends in the number of first and follow-up appointments and in the completeness of extractable CVRM indicators from the electronic health record (EHR) as a proxy for CVRM guideline adherence. CVH was determined using the Life’s Essential 8 metric (score 0–100, the higher score, the better). We investigated whether CVH differed between COVID-19 periods compared with the reference period (ie, 2019) and stratified by OPDs, using multivariable linear regression, adjusted for age, gender, CVD history and whether the patient had a previous appointment before the reference period.

Among 15 143 patients, we observed a 33% reduction in the weekly number of first appointments during the COVID-19 pandemic, with the largest reductions in the cardiology and nephrology OPDs, with no differences between women and men. Follow-up appointments conducted remotely, compared with before the COVID-19 pandemic, increased significantly for all OPDs. CVRM indicators were up to 11% less extractable during the first lockdown yet returned to prepandemic levels directly after the first lockdown period. The CVH score of patients visiting the nephrology, vascular medicine and geriatrics OPDs during the first lockdown was 11.23 (95% CI 2.74 to 19.72), 5.68 (95% CI 0.82 to 10.54) and 5.66 (95% CI 0.01 to 11.31) points higher, respectively, compared with the prepandemic period. In between the second and third lockdowns, the CVH score was comparable to the preCOVID reference period, yet for the cardiology OPD it was significantly higher (5.54, 95% CI 2.04 to 9.05).

During the COVID-19 pandemic, weekly numbers of first appointments to OPDs decreased, and a population with a higher CVH score (ie, better CVH) visited certain OPDs, especially during the first lockdown period. These suggest that patients with poorer CVH more often avoided or were unable to visit OPDs, which might have resulted in missed opportunities to control cardiovascular risk factors and potentially may have led to preventable disease outcomes. For future epidemics and pandemics, it seems vital to develop a strategy that includes an emphasis on seeking healthcare when needed, with specific attention to patients at higher CVD risk.

Ethiopia, the second most populous country in Africa, faces significant demographic transitions, with fertility rates playing a central role in shaping economic and healthcare policies. Family planning programmes face challenges due to funding limitations. The recent suspension of the US Agency for International Development funding exacerbates these issues, highlighting the need for accurate birth forecasting to guide policy and resource allocation. This study applied time-series and advanced machine-learning models to forecast future birth trends in Ethiopia.

Secondary data from the Ethiopian Demographic and Health Survey from 2000 to 2019 were used. After data preprocessing steps, including data conversion, filtering, aggregation and transformation, stationarity was checked using the Augmented Dickey-Fuller (ADF) test. Time-series decomposition was then performed, followed by time-series splitting. Seven forecasting models, including Autoregressive Integrated Moving Average, Prophet, Generalised Linear Models with Elastic Net Regularisation (GLMNET), Random Forest and Prophet-XGBoost, were built and compared. The models’ performance was evaluated using key metrics such as root mean square error (RMSE), mean absolute error (MAE) and R-squared value.

GLMNET emerged as the best model, explaining 77% of the variance with an RMSE of 119.01. Prophet-XGBoost performed reasonably well but struggled to capture the full complexity of the data, with a lower R-squared value of 0.32 and an RMSE of 146.87. Forecasts were made for both average monthly births and average births per woman over a 10-year horizon (2025–2034). The forecast for average monthly births indicated a gradual decline over the projection period. Meanwhile, the average births per woman showed an increasing trend but fluctuated over time, influenced by demographic shifts such as changes in fertility preferences, age structure and migration patterns.

This study demonstrates the effectiveness of combining time-series models and machine learning, with GLMNET and Prophet XGBoost emerging as the most effective. While average monthly births are expected to decline due to demographic transitions and migration, the average births per woman will remain high, reflecting persistent fertility preferences within certain subpopulations. These findings underscore the need for policies addressing both population trends and sociocultural factors.

While survival rates following neonatal surgery for congenital heart disease (CHD) have improved over the years, neurodevelopmental delays are still highly prevalent in these patients. After correcting for the CHD subtype, the severity of developmental impairment is dependent on multiple factors, including intraoperative brain injury, which is more frequent and more severe in those undergoing aortic arch repair with deep hypothermic circulatory arrest (DHCA). It is proposed that brain injury may be reduced if cooling is stopped at the point of electrocerebral inactivity (ECI) on electroencephalogram (EEG), but there is limited evidence to support this as few centres perform perioperative EEG routinely. This study aims to assess the feasibility of EEG monitoring during neonatal aortic arch repair and investigate the relationship between temperature and EEG to inform the design of a future clinical trial.

Single-centre prospective observational cohort study in a UK specialist children’s hospital, aiming to recruit 74 neonates (≤4 weeks corrected age) undergoing aortic arch repair with DHCA. EEG will be acquired at least 1–3 hours before surgery, and brain activity will be monitored continuously until 24 hours following admission to intensive care. Demographic, clinical, surgical and outcome variables will be collected. Feasibility will be measured by the number of patients recruited, data collection procedures, technically successful EEG recordings and adverse events. The main outcomes are the temperature at which ECI is achieved and its duration, EEG patterns at key perioperative steps and neurodevelopmental outcomes at 24 months postsurgery.

The study was approved by the Yorkshire and The Humber Sheffield National Health Service Research Ethics Committee (20/YH/0192) on 18 June 2020. Written informed consent will be obtained from the participant’s parent/guardian prior to surgery. Findings will be disseminated to the academic community through peer-reviewed publications and presentations at conferences. Parents/guardians will be informed of the results through a newsletter in conjunction with local charities.

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality worldwide. Despite the organised CRC screening programme, the uptake rate of the population-based CRC screening was still low. Thus, we will conduct a randomised controlled trial in a community setting to evaluate the effectiveness of a theory-based chatbot in promoting CRC screening uptake.

A total of 500 eligible participants will be randomly assigned to a WhatsApp Messenger-initiated chatbot outreach group or a standard text reminder group at a ratio of 1:1. The intervention group will deliver Chinese culturally tailored education texts and videos developed based on the Health Belief Model and the Trans-Theoretical Model. The control group will deliver a standard text reminder of information about the Hong Kong organised CRC screening programme. In addition to the baseline assessment and postintervention assessment, all subjects will be followed up for 3 months and 6 months, respectively. The primary outcome will be the CRC screening uptake rate at the 3 month and 6 month follow-up. The secondary outcomes will be the intention to undergo CRC screening uptake, time interval to participate in and complete screening after recruitment, and reasons for not participating in screening at the 3 month and 6 month follow-up. Quantitative data will be analysed using Student’s t-test, Pearson’s ² test or Fisher’s exact test. Qualitative data will be analysed by thematic analysis.

Ethical approval of this trial was granted by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (2022.614). Written informed consent will be obtained from study participants before enrolment. The findings will be disseminated through peer-reviewed journals.

The study was registered on clinicaltrials.gov (NCT06192862).

Our study was designed to assess whether paired normal-tumour testing increased access to targeted therapy, clinical trials and influenced cancer screening recommendations given to patients and their families.

Prospective cohort study.

Academic cancer centre in the Pacific Northwest region of the USA.

Patients newly diagnosed between 01 January 2021 and 31 December 2022 with cancers of the oesophagus, gastro-oesophageal junction and stomach (CEGEJS) were included. All other cancer diagnoses such as head and neck, duodenal and lower gastrointestinal tract cancers were excluded.

Paired germline and tumour genetic test within 90 days of new patient visit.

Number of targeted therapies received (or not) when eligible, follow-up treatment data and number of inherited predispositions to cancers identified. No secondary outcome measures.

Of 42 patients, 32 (76.2%) were eligible for at least one targeted therapy. 19 patients received immunotherapy, when 16 had a biomarker predicting immunotherapy benefit, and benefit of immunotherapy was unclear for 3. Another 11 did not have this biomarker, and 6 of them received immunotherapy. Six pathogenic variants were identified in four high-risk genes. By 01 January 2024, 18 patients (42.9%) had died of complications of cancer.

More than 75% of patients who received tumour testing were eligible for a targeted therapy regardless of their stage at diagnosis, emphasising the need to expand access to testing with staging workup to improve survival outcomes. Six families received personalised screening recommendations, thanks to this study.