Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis.

Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR).

Evaluating a Smart Textile Loneliness Monitoring System for Older People: Co-Design and Qualitative Focus Group Study.

Background: Previous studies have explored how sensor technologies can assist in in the detection, recognition, and prevention of subjective loneliness. These studies have shown a correlation between physiological and behavioral sensor data and the experience of loneliness. However, little research has been conducted on the design requirements from the perspective of older people and stakeholders in technology development.

Understanding Early Treatment Response in Brief CBT for Nonunderweight Eating Disorders: A Mixed Methods Study.

Objective: Early change in eating disorder psychopathology is the most robust predictor of treatment outcomes in eating disorders. However, little is known about what predicts early change. Using mixed-methodology, this study explored predictors of early change in the first four sessions of 10-session cognitive behavioral therapy (CBT-T) for nonunderweight eating disorders.

Pre- and post-COVID 19 outbreak relationship between physical activity and depressive symptoms in Spanish adults with major depressive disorder: a secondary analysis of the RADAR-MDD cohort study.

Aim: To evaluate the longitudinal association of sedentary behavior, light and moderate-to-vigorous physical activity (MVPA) participation with depressive symptoms and whether their possible association changed depending on the pandemic phase.

Methods: This longitudinal study conducted secondary analysis from the Spanish cohort of the Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study. Depressive symptoms were assessed by the Patient Health Questionnaire (PHQ-8).

Qualitative exploration of the lived experiences of loneliness in later life to inform technology development.

Purpose: Loneliness is a negative emotional state which is common in later life. The accumulative effects of loneliness have a significant impact on the physical and mental health of older adults. We aim to qualitatively explore the experiences of loneliness in later life and identify relevant behaviours and indicators which will inform novel methods of loneliness detection and intervention.

A framework for remotely enabled co-design with young people: its development and application with neurodiverse children and their caregivers.

Introduction: This paper describes an innovative Framework for Remotely Enabled Co-Design with Young people (FREDY), which details an adaptable four-stage process for generating design concepts with children and other key stakeholders in a naturalistic and inclusive way.

Methods: Recommendations from existing patient engagement and design methodologies were combined to provide research teams with procedures to capture and analyse end-user requirements rapidly. Resulting insights were applied through iterative design cycles to achieve accelerated and user-driven innovation.

The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder.

Background: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

Background: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings.

Objective: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts.

Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial.

Background: Multiparametric remote measurement technologies (RMTs), which comprise smartphones and wearable devices, have the potential to revolutionize understanding of the etiology and trajectory of major depressive disorder (MDD). Engagement with RMTs in MDD research is of the utmost importance for the validity of predictive analytical methods and long-term use and can be conceptualized as both objective engagement (data availability) and subjective engagement (system usability and experiential factors). Positioning the design of user interfaces within the theoretical framework of the Behavior Change Wheel can help maximize effectiveness.

The association between persistent cognitive difficulties and depression and functional outcomes in people with major depressive disorder.

Background: Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes.

Methods: This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; = 623).

Multilingual markers of depression in remotely collected speech samples: A preliminary analysis.

Background: Speech contains neuromuscular, physiological and cognitive components, and so is a potential biomarker of mental disorders. Previous studies indicate that speaking rate and pausing are associated with major depressive disorder (MDD). However, results are inconclusive as many studies are small and underpowered and do not include clinical samples.

What impacts the acceptability of wearable devices that detect opioid overdose in people who use opioids? A qualitative study.

Introduction: Drug-related deaths involving an opioid are at all-time highs across the United Kingdom. Current overdose antidotes (naloxone) require events to be witnessed and recognised for reversal. Wearable technologies have potential for remote overdose detection or response but their acceptability among people who use opioids (PWUO) is not well understood.

Stakeholder-led understanding of the implementation of digital technologies within heart disease diagnosis: a qualitative study protocol.

Introduction: Cardiovascular diseases are highly prevalent among the UK population, and the quality of care is being reduced due to accessibility and resource issues. Increased implementation of digital technologies into the cardiovascular care pathway has enormous potential to lighten the load on the National Health Service (NHS), however, it is not possible to adopt this shift without embedding the perspectives of service users and clinicians.

Methods And Analysis: A series of qualitative studies will be carried out with the aim of developing a stakeholder-led perspective on the implementation of digital technologies to improve holistic diagnosis of heart disease.

Understanding the psychological experiences of loneliness in later life: qualitative protocol to inform technology development.

Objectives: Loneliness is a public health issue impacting the health and well-being of older adults. This protocol focuses on understanding the psychological experiences of loneliness in later life to inform technology development as part of the 'Design for health ageing: a smart system to detect loneliness in older people' (DELONELINESS) study.

Methods And Analysis: Data will be collected from semi-structured interviews with up to 60 people over the age of 65 on their experiences of loneliness and preferences for sensor-based technologies.

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity.

Background: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.

Methods: Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study.

Antidepressants for the treatment of depression in people with cancer.

Background: Major depression and other depressive conditions are common in people with cancer. These conditions are not easily detectable in clinical practice, due to the overlap between medical and psychiatric symptoms, as described by diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). Moreover, it is particularly challenging to distinguish between pathological and normal reactions to such a severe illness.

The Impact of COVID-19 Lockdown on Adults with Major Depressive Disorder from Catalonia: A Decentralized Longitudinal Study.

The present study analyzes the effects of each containment phase of the first COVID-19 wave on depression levels in a cohort of 121 adults with a history of major depressive disorder (MDD) from Catalonia recruited from 1 November 2019, to 16 October 2020. This analysis is part of the Remote Assessment of Disease and Relapse-MDD (RADAR-MDD) study. Depression was evaluated with the Patient Health Questionnaire-8 (PHQ-8), and anxiety was evaluated with the Generalized Anxiety Disorder-7 (GAD-7).

Patient preferences for key drivers and facilitators of adoption of mHealth technology to manage depression: A discrete choice experiment.

Background: In time, we may be able to detect the early onset of symptoms of depression and even predict relapse using behavioural data gathered through mobile technologies. However, barriers to adoption exist and understanding the importance of these factors to users is vital to ensure maximum adoption.

Method: In a discrete choice experiment, people with a history of depression (N = 171) were asked to select their preferred technology from a series of vignettes containing four characteristics: privacy, clinical support, established benefit and device accuracy (i.

Examining the acceptability of actigraphic devices in children using qualitative and quantitative approaches: protocol for a systematic review and meta-analysis.

Introduction: Actigraphy is commonly used to record free living physical activity in both typically and atypically developing children. While the accuracy and reliability of actigraphy have been explored extensively, research regarding young people's opinion towards these devices is scarce. This review aims to identify and synthesise evidence relating to the acceptability of actigraphic devices in 5-11 year olds.

Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study.

Recent growth in digital technologies has enabled the recruitment and monitoring of large and diverse populations in remote health studies. However, the generalizability of inference drawn from remotely collected health data could be severely impacted by uneven participant engagement and attrition over the course of the study. We report findings on long-term participant retention and engagement patterns in a large multinational observational digital study for depression containing active (surveys) and passive sensor data collected via Android smartphones, and Fitbit devices from 614 participants for up to 2 years.

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis.

Background: Remote measurement technologies (RMTs) have the potential to revolutionize major depressive disorder (MDD) disease management by offering the ability to assess, monitor, and predict symptom changes. However, the promise of RMT data depends heavily on sustained user engagement over extended periods. In this paper, we report a longitudinal qualitative study of the subjective experience of people with MDD engaging with RMTs to provide insight into system usability and user experience and to provide the basis for future promotion of RMT use in research and clinical practice.

The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement.

Background: Remote measurement technologies (RMTs) such as smartphones and wearables can help improve treatment for depression by providing objective, continuous, and ecologically valid insights into mood and behavior. Engagement with RMTs is varied and highly context dependent; however, few studies have investigated their feasibility in the context of treatment.

Objective: A mixed methods design was used to evaluate engagement with active and passive data collection via RMT in people with depression undergoing psychotherapy.