Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Digital Phenotyping of Anxiety-Depression Comorbidity in Tele-Mental Health: Severity Coupling and Resource-Use Signatures in a Real-World Cohort.

Medical sciences (Basel, Switzerland) - 2 Jul 2026

Zoriy Anastácia, Dionísio Ana, Pinto Filipe, Vale Nuno

Abstract excerpt

Background: Anxiety and depression are major contributors to mental-health burden and frequently co-occur in clinical practice. In tele-mental health, routinely captured operational variables such as consultation duration, visit frequency, and follow-up cadence may provide clinical digital phenotypes that complement conventional symptom scales. This study aimed to characterize anxiety-depression comorbidity in a...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Aged
Share to Anxiety
Share to Cohort Studies

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Comorbidity

Share to Depression

Share to Mental Health

Share to Patient Acceptance of Health Care

Share to Severity of Illness Index

Source

Open in PubMed Open full text

Identifiers

PMID: 42506337
DOI: 10.3390/medsci14030368
PMCID: PMC13414095

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 9 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Digital Phenotyping of Anxiety-Depression Comorbidity in Tele-Mental Health: Severity Coupling and Resource-Use Signatures in a Real-World Cohort.PMID 42506337Read ↗

Passive Digital Phenotyping for Identifying Dynamic Symptom Patterns: Toward Precision Monitoring in PsychiatrySemantic proximity Read ↗

Passive Digital Phenotyping for Identifying Dynamic Symptom Patterns: Toward Precision Monitoring in PsychiatrySemantic proximity Read ↗

Evaluating Clinical Outcomes in Patients Being Treated Exclusively via TelepsychiatrySemantic proximity Read ↗

Using Smartphone-Tracked Behavioral Markers to Recognize Depression and Anxiety Symptoms: Cross-Sectional Digital Phenotyping Study.Semantic proximity Read ↗

Patients with affective disorders profit most from telemedical treatment: Evidence from a naturalistic patient cohort during the COVID-19 pandemicSemantic proximity Read ↗

Demographic and clinical characteristics associated with anxiety and depressive symptom outcomes in users of a digital mental health intervention incorporating a relational agentSemantic proximity Read ↗

Development of the NeuroFlow Severity Score and Comparison With Validated Measures for Depression and AnxietySemantic proximity Read ↗

Assessing the feasibility of large-scale digital sensing for depression and anxiety: The Digital Mental Health StudySemantic proximity Read ↗

Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxietySemantic proximity Read ↗

Transdiagnostic phenotyping of psychopathology in a help-seeking population (PhenoNetz): A study protocol for an experience sampling studySemantic proximity Read ↗

Profiles of inpatient psychiatry referrals: A 4-year analysis in a Consultation-Liaison Psychiatry ServiceSemantic proximity Read ↗

Mental distress and health-related quality of life among somatic inpatients: social gradients and hospital mental health implications based on the SomPsyNet study populationSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.