98%
921
2 minutes
20
Purpose: Tic disorders (TD) are common neurodevelopmental disorders characterized by heterogeneous tic symptoms in children, making diagnostic classification difficult. This complexity requires accurate subtyping using data-driven computational methods to identify patterns within clinical data. This systematic review primarily summarizes the current evidence for the classification of TD using a data-driven approach.
Patients And Methods: We conducted a systematic literature search on PubMed and Web of Science up to December 2023 and identified 16 publications analyzing 14 unique samples, totaling approximately 6000 subjects.
Results: Nine studies classified different subtypes of TD based on symptoms and behavior. Seven studies identified novel factor structures based on TD and its complex comorbidity patterns. Seven studies highlighted associations between TD symptom patterns and genetics, reflecting the diversity of underlying genetic mechanisms underlying TD.
Conclusion: This systematic review reveals significant variability in research on the classification of TD, which limits the application of findings for accurate diagnosis and guiding treatment strategies in pediatric psychiatry. Further research incorporating multidimensional information (such as genetic, neuroimaging, and environmental and social factors) is essential to improve the understanding of TD subtypes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11697672 | PMC |
http://dx.doi.org/10.2147/NDT.S499080 | DOI Listing |
JMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
J Med Internet Res
September 2025
School of Pharmacy, Sungkyunkwan University, Gyeonggi-do, Republic of Korea.
Background: Owing to the unique characteristics of digital health interventions (DHIs), a tailored approach to economic evaluation is needed-one that is distinct from that used for pharmacotherapy. However, the absence of clear guidelines in this area is a substantial gap in the evaluation framework.
Objective: This study aims to systematically review and compare the economic evaluation literature on DHIs and pharmacotherapy for the treatment of depression.
JAMA Psychiatry
September 2025
Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville.
Importance: Behavioral variant frontotemporal dementia (bvFTD), the most common subtype of FTD, is a leading form of early-onset dementia worldwide. Accurate and timely diagnosis of bvFTD is frequently delayed due to symptoms overlapping with common psychiatric disorders, and interest has increased in identifying biomarkers that may aid in differentiating bvFTD from psychiatric disorders.
Objective: To summarize and critically review studies examining whether neurofilament light chain (NfL) in cerebrospinal fluid (CSF) or blood is a viable aid in the differential diagnosis of bvFTD vs psychiatric disorders.
JAMA Netw Open
September 2025
Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla.
Importance: Janus kinase (JAK) inhibitors are highly effective medications for several immune-mediated inflammatory diseases (IMIDs). However, safety concerns have led to regulatory restrictions.
Objective: To compare the risk of adverse events with JAK inhibitors vs tumor necrosis factor (TNF) antagonists in patients with IMIDs in head-to-head comparative effectiveness studies.