A5011221393- Mental Health Research Topics
- Digital Mental Health Interventions
- Schizophrenia research and treatment
- COVID-19 and Mental Health
- Functional Brain Connectivity Studies
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Impact of Technology on Adolescents
- Mental Health and Psychiatry
- Health disparities and outcomes
- Psychosomatic Disorders and Their Treatments
- Mobile Health and mHealth Applications
- Heart Rate Variability and Autonomic Control
- Sleep and related disorders
- Mental Health via Writing
- Treatment of Major Depression
- Health, Environment, Cognitive Aging
- Hallucinations in medical conditions
- Eating Disorders and Behaviors
- Neural and Behavioral Psychology Studies
- Gastric Cancer Management and Outcomes
- Sleep and Wakefulness Research
- Mental Health Treatment and Access
- Long-Term Effects of COVID-19
- Circadian rhythm and melatonin
- Emotion and Mood Recognition
Parc Sanitari Sant Joan de Déu
2016-2025
Universitat de Barcelona
2016-2025
Centro de Investigación Biomédica en Red de Salud Mental
2016-2025
Instituto de Salud Carlos III
2018-2024
Institut de Recerca Sant Joan de Déu
2017-2024
Sant Joan de Déu Research Foundation
2017-2024
Universitat Autònoma de Barcelona
2024
King's College London
2021-2023
Centro de Investigación Biomédica en Red
2018-2023
Centro San Giovanni di Dio Fatebenefratelli
2021
Background In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective quantitative means passively monitoring impact response these at local level is needed. Objective We aim to explore utility recently developed open-source mobile health platform Remote Assessment Disease Relapse (RADAR)–base toolbox rapidly test effect NPIs intended limit spread COVID-19. Methods...
Abstract Background Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response treatment identify early indicators relapse. Remote Measurement Technologies (RMT) provide an opportunity transform the measurement management MDD, via data collected from inbuilt smartphone sensors wearable devices alongside app-based questionnaires tasks. A key question for field extent which participants can adhere research protocols completeness...
There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which be biased by dysfunctional perceptions current symptom severity. Predictors relapse include disrupted sleep, reduced sociability, physical activity, changes mood, prosody cognitive function, are all amenable to via RMT. This study aims to: 1) determine...
Mobile technology has the potential to provide accurate, impactful data on symptoms of depression, which could improve health management or assist in early detection relapse. However, for this be achieved, it is essential that patients engage with technology. Although many barriers and facilitators use are common across therapeutic areas types, may specific cultural contexts.This study aimed determine engagement mobile (mHealth) remote measurement depression three Western European...
The Psychotic Symptom Rating Scales (PSYRATS) is an instrument designed to quantify the severity of delusions and hallucinations typically used in research studies clinical settings focusing on people with psychosis schizophrenia. It comprised auditory (AHS) subscales (DS), but these do not necessarily reflect psychological constructs causing intercorrelation between clusters scale items. Identification important some contexts because item clustering may be caused by underlying etiological...
Research in mental health has implicated sleep pathologies with depression. However, the gold standard for assessment, polysomnography, is not suitable long-term, continuous, monitoring of daily sleep, and methods such as diaries rely on subjective recall, which qualitative inaccurate. Wearable devices, other hand, provide a low-cost convenient means to monitor home settings. The main aim this study was devise extract features, from data collected using wearable device, analyse their...
The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction relationships) between depressive symptom severity and phone-measured have yet fully explored.
Abstract Recent growth in digital technologies has enabled the recruitment and monitoring of large diverse populations remote health studies. However, generalizability inference drawn from remotely collected data could be severely impacted by uneven participant engagement attrition over course study. We report findings on long-term retention patterns a multinational observational study for depression containing active (surveys) passive sensor via Android smartphones, Fitbit devices 614...
Background Research in mental health has found associations between depression and individuals’ behaviors statuses, such as social connections interactions, working status, mobility, isolation loneliness. These statuses can be approximated by the nearby Bluetooth device count (NBDC) detected sensors mobile phones. Objective This study aimed to explore value of NBDC data predicting depressive symptom severity measured via 8-item Patient Health Questionnaire (PHQ-8). Methods The used this...
Background Most smartphones and wearables are currently equipped with location sensing (using GPS mobile network information), which enables continuous tracking of their users. Several studies have reported that various mobility metrics, as well home stay, is, the amount time an individual spends at in a day, associated symptom severity people major depressive disorder (MDD). Owing to use small homogeneous cohorts participants, it is uncertain whether findings those generalize broader...
Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study individuals with a history recurrent major depressive disorder (MDD) explored the intra-individual variations HR parameters and their relationship severity.Data from 510 participants (Number observations = 6666) were collected three centres Netherlands, Spain, UK, as part remote assessment disease relapse-MDD study. We analysed between severity, assessed every 2...
A number of challenges exist for the analysis mHealth data: maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold missing data; distinguishing between cross-sectional longitudinal relationships different features to determine their utility in tracking within-individual variation or screening individuals at high risk; heterogeneity with which depression manifests itself behavioral patterns quantified by passive...
Speech contains neuromuscular, physiological and cognitive components, so is a potential biomarker of mental disorders. Previous studies indicate that speaking rate pausing are associated with major depressive disorder (MDD). However, results inconclusive as many small underpowered do not include clinical samples. These have also been unilingual use speech collected in controlled settings. If markers to help understand the onset progress MDD, we need uncover robust language establish...
Visual mental imagery might be critical in the ability to discriminate imagined from perceived pictures. Our aim was investigate neural bases of this specific type reality-monitoring process individuals with high visual abilities.A task administered twenty-six healthy participants using functional magnetic resonance imaging. During encoding phase, 45 words designating common items, and pictures other were presented random order. recall required remember whether a picture item had been...
In the present study, a photoplethysmographic (PPG) waveform analysis for assessing differences in autonomic reactivity to mental stress between patients with Major Depressive Disorder (MDD) and healthy control (HC) subjects is presented.PPG recordings of 40 MDD HC were acquired at basal conditions, during execution cognitive tasks, post-task relaxation period. PPG pulses are decomposed into three waves (a main wave two reflected waves) using pulse decomposition analysis. Pulse...
Prior research has associated spoken language use with depression, yet studies often involve small or non-clinical samples and face challenges in the manual transcription of speech. This paper aimed to automatically identify depression-related topics speech recordings collected from clinical samples. The data included 3919 English free-response via smartphones 265 participants a depression history. We transcribed automatic recognition (Whisper tool, OpenAI) identified principal...
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 real-world settings. Objective This study aims to explore associations severity wearable-measured rhythms while accounting for impacts. Methods Data were sourced from a large longitudinal mHealth study,...
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 way unpick this phenotypic diversity for improved characterisation. We aimed identify depression subtypes longitudinally using Inventory Depressive Symptomatology: Self-Report (IDS-SR). A secondary analysis two-year cohort study called Remote Assessment Disease and Relapse in Disorder (RADAR-MDD), which collected data every three...
<title>Abstract</title> Recent advancements in Large Language Models (LLMs) present promising opportunities for applying these technologies to aid the detection and monitoring of Major Depression Disorder (MDD). However, demographic biases LLMs may challenges extraction key information. This study evaluates commonly used speech health literature, across a cohort comprised English, Spanish, Dutch speakers with recurrent MDD observe effects different imbalances. Results indicate demographics...