Using the Person-Based Approach to Co-Create and Optimize an App-Based Intervention to Support Better Sleep for Adolescents in the United Kingdom: Mixed Methods Study.

Background: Poor sleep is a common problem in adolescents aged 14 to 18 years. Difficulties with sleep have been found to have a bidirectional link to mental health problems.

Objective: This new research sought to involve young people in the co-creation of a new app, particularly those from underserved communities.

Remote Patient Monitoring and Machine Learning in Acute Exacerbations of Chronic Obstructive Pulmonary Disease: Dual Systematic Literature Review and Narrative Synthesis.

Background: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with high mortality, morbidity, and poor quality of life and constitute a substantial burden to patients and health care systems. New approaches to prevent or reduce the severity of AECOPD are urgently needed. Internationally, this has prompted increased interest in the potential of remote patient monitoring (RPM) and digital medicine.

Exacerbation predictive modelling using real-world data from the myCOPD app.

Background: Acute exacerbations of COPD (AECOPD) are episodes of breathlessness, cough and sputum which are associated with the risk of hospitalisation, progressive lung function decline and death. They are often missed or diagnosed late. Accurate timely intervention can improve these poor outcomes.

Evaluating the Effectiveness of the SleepTracker App for Detecting Anxiety- and Depression-Related Sleep Disturbances.

This study emphasises the critical role of quality sleep in physical and mental well-being, exploring its impact on bodily recovery and cognitive function. Investigating poor sleep quality in approximately 40% of individuals with insomnia symptoms, the research delves into its potential diagnostic relevance for depression and anxiety, with a focus on intervention in mental health by understanding sleep patterns, especially in young individuals. This study includes an exploration of phone usage habits among young adults during PPI sessions, providing insights for developing the SleepTracker app.