How to e-mental health: a guideline for researchers and practitioners using digital technology in the context of mental health
C Seiferth, L Vogel, B Aas, I Brandhorst… - Nature mental …, 2023 - nature.com
Despite an exponentially growing number of digital or e-mental health services,
methodological guidelines for research and practical implementation are scarce. Here we …
methodological guidelines for research and practical implementation are scarce. Here we …
Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art
Digital biomarkers that remotely monitor symptoms have the potential to revolutionize
outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by …
outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by …
[HTML][HTML] Acceptance towards digital health interventions–model validation and further development of the unified theory of acceptance and use of technology
Internet-and mobile-based interventions (IMI) offer an effective way to complement health
care. Acceptance of IMI, a key facilitator of their implementation in routine care, is often low …
care. Acceptance of IMI, a key facilitator of their implementation in routine care, is often low …
Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies
Mobile sensing data processed using machine learning models can passively and remotely
assess mental health symptoms from the context of patients' lives. Prior work has trained …
assess mental health symptoms from the context of patients' lives. Prior work has trained …
[HTML][HTML] Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Depression is a prevalent mental disorder. Current clinical and self-reported assessment
methods of depression are laborious and incur recall bias. Their sporadic nature often …
methods of depression are laborious and incur recall bias. Their sporadic nature often …
[Retracted] Psychological Analysis for Depression Detection from Social Networking Sites
Rapid technological advancements are altering people's communication styles. With the
growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have …
growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have …
Opportunities for smartphone sensing in e-health research: a narrative review
Recent years have seen significant advances in the sensing capabilities of smartphones,
enabling them to collect rich contextual information such as location, device usage, and …
enabling them to collect rich contextual information such as location, device usage, and …
[HTML][HTML] The relation between passively collected GPS mobility metrics and depressive symptoms: systematic review and meta-analysis
Background The objective, unobtrusively collected GPS features (eg, homestay and
distance) from everyday devices like smartphones may offer a promising augmentation to …
distance) from everyday devices like smartphones may offer a promising augmentation to …
Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sample
Abstract Major Depressive Disorder (MDD) is a heterogeneous disorder, resulting in
challenges with early detection. However, changes in sleep and movement patterns may …
challenges with early detection. However, changes in sleep and movement patterns may …
Digital health technologies and major depressive disorder
There is an urgent need to improve the clinical management of major depressive disorder
(MDD), which has become increasingly prevalent over the past two decades. Several gaps …
(MDD), which has become increasingly prevalent over the past two decades. Several gaps …