Evidence map›Paper›PMID 42416623›Full record

ArticleJCPP advances2026

Transdiagnostic symptom networks in adolescent psychopathology: A longitudinal panel network analysis.

Xenia A Häfeli, Larisa Morosan, Anja Hirsig, Stefanie J Schmidt

Abstract read
In one paragraph

Article in JCPP advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xenia A HäfeliDivision of Clinical Child and Adolescent Psychology University of Bern Bern Switzerland.ORCID https://orcid.org/0009-0000-3230-8999
Larisa MorosanDivision of Clinical Child and Adolescent Psychology University of Bern Bern Switzerland.ORCID https://orcid.org/0000-0003-0148-2948
Anja HirsigDivision of Clinical Child and Adolescent Psychology University of Bern Bern Switzerland.
Stefanie J SchmidtDivision of Clinical Child and Adolescent Psychology University of Bern Bern Switzerland.ORCID https://orcid.org/0000-0002-2369-5920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Understanding symptom patterns of emerging psychopathology is essential for early detection and intervention. Network analysis offers a promising approach by conceptualizing emerging psychopathology as dynamic interactions between symptoms over time. This study aims to explore the structure of a transdiagnostic symptom network in adolescents. Methods: A one-year prospective study was conducted with a general population sample of 1186 Swiss adolescents with no current or past mental disorders (data collection: February 2021-March 2024; age 11-17 years ( Results: In the contemporaneous network, anxiety, depressive, and eating disorder symptoms, particularly excessive worry (EI = 1.08), body dissatisfaction (EI = 1.03), and low self-esteem (EI = 1.01), exhibited the highest EI. Irritability (BEI = 0.80/BB = 0.58) and low self-esteem (BEI = 0.57/BB = 0.50) acted as important bridge symptoms within the network. In the temporal network, uncontrollable worry ( Conclusion: Worry, body dissatisfaction and weight concerns play a pivotal role in emerging psychopathology by linking multiple disorder domains and shaping symptom dynamics over time. These findings may enhance early detection by identifying high-risk adolescents and may inform prevention strategies, such as interventions targeting excessive worry and negative body image, to reduce symptom escalation and improve long-term mental health outcomes.

Indexed as

adolescenceearly detectionmental healthnetworkpreventionsubclinicaltransdiagnostic

Identifiers

PMID42416623
PMCPMC13339512

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.