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

Multidimensional analysis of smartphone overuse in insomnia: Integrating digital phenotyping with clinical assessment.

Journal of behavioral addictions - 2 Apr 2026

Matsushita Emma, Kim Hyungju, Kim Minji, Yoon Seojin, Kim Sujin, Yeom Ji Won, Pack Seung Pil, Lee Heon-Jeong, Cheong Taesu, Cho Chul-Hyun

Abstract excerpt

Background and aims: This study aimed to identify the differences in characteristics between high- and low-risk smartphone users among individuals with insomnia symptoms using digital phenotyping and clinical assessments. Methods: A total of 246 participants with insomnia symptoms (M = 31.14, SD = 10.09) were monitored for four weeks using the smartphone application and wearable devices. The participants were...

Topics

Humans
Male
Sleep Initiation and Maintenance Disorders
Female
Adult
Smartphone
Phenotype
Middle Aged
Wearable Electronic Devices
Young Adult
Internet Addiction Disorder

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Anxiety

Depression

Stress, Psychological

Source

Open in PubMed Open full text

Identifiers

PMID: 41493477
DOI: 10.1556/2006.2025.00093
PMCID: PMC13132408

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 29 Aug 2026. Prepared record publication-41493477-2026-08-29.1. Manifest publication-graph-cohort-2026-08-29.1.

Source receipt: PubMed via Helena Literature Corpus, retrieved 29 Aug 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

0

discussions

0

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Multidimensional analysis of smartphone overuse in insomnia: Integrating digital phenotyping with clinical assessment.PMID 41493477Read ↗

Smartphone-Derived Biobehavioral Rhythms and Their Associations with Depression, Anxiety, and Sleep DisturbanceSemantic proximity Read ↗

Interindividual differences in digital phenotypes of major depressive disorder: A passive sensing study using smartphone and wearable sensor data.Semantic proximity Read ↗

Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review.Semantic proximity Read ↗

Digital Phenotyping for Stress, Anxiety, and Mild Depression: Systematic Literature Review.Semantic proximity Read ↗

Passive smartphone sensors for detecting psychopathologySemantic proximity Read ↗

Passive smartphone sensors for detecting psychopathologySemantic proximity Read ↗

Severity of Depression and Anxiety Symptoms Manifest in Physiological and Behavioral Metrics Collected from a Consumer-Grade Wearable RingSemantic proximity Read ↗

Advancing psychiatry with transdiagnostic targets for digital phenotypingSemantic proximity Read ↗

Severity of Depression and Anxiety Symptoms Manifest in Physiological and Behavioral Metrics Collected from a Consumer-Grade Wearable RingSemantic proximity Read ↗

Cohort profile: The<i>SmartSleep Study</i>, Denmark Triangulation of evidence from survey, clinical and tracking dataSemantic proximity Read ↗

Monitoring Kleine-Levin Syndrome Recovery Using Human-Smartphone Interactions: A Digital Phenotyping Approach.Semantic proximity Read ↗

Technical feasibility and acceptance of the Remote Monitoring Application in Psychiatry (ReMAP)Semantic proximity Read ↗

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