Evidence map›Paper›PMID 41355926›Full record

ArticleFrontiers in child and adolescent psychiatry2025

Network analysis of school absence: central symptoms and their functions.

Katarina Alanko, David Heyne, Martin Lagerström, Martin Knollman

Abstract read
In one paragraph

Article in Frontiers in child and adolescent psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Katarina AlankoCentre for Learning Analytics, University of Turku, Turku, Finland.
David HeyneSchool of Psychology, Faculty of Health, Deakin University, Burwood, VIC, Australia.
Martin LagerströmDepartment of Humanities, The Faculty of Human and Social Sciences, Åbo Akademi University, Turku, Finland.
Martin KnollmanDepartment for Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, LVR Clinic Dusseldorf, Heinrich-Heine University Dusseldorf, Dusseldorf, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: School attendance problems (SAPs) often develop and persist through complex interactions among numerous influences. This study used network analysis to identify: (i) the most central symptoms reported by youths with SAPs; (ii) the most central functions underlying those symptoms; and (iii) the relationships among symptoms and among functions. Method: Self-reported symptoms and their functions were assessed via an online survey comprising the Inventory of School Attendance Problems. We analysed data from Finnish middle school students ( Results: Results indicated complex networks among the symptoms and among the functions. Depression emerged as the descriptively most central node in both networks. In the symptoms network, it showed moderate links to Performance Anxiety, Aggression, and Social Anxiety. In the functions network, its strongest links were to School Aversion/Attractive Alternatives and Social Anxiety. Social Anxiety was also highly central in the functions network, with links to Agoraphobia/Panic and Problems with Peers. All 13 nodes were interlinked in both the symptoms and functions networks, reflecting widespread co-occurrence among symptoms and among functions. Conclusions: Depression's central position across both the symptom and function networks may make it a valuable intervention target, even when other symptoms are also salient.

Indexed as

adolescencefunctionsinventory of school attendance problemsnetwork analysisschool absencesymptoms

Identifiers

PMID41355926
PMCPMC12675184

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.