Evidence map›Paper›PMID 41735456›Full record

ArticleScientific reports2026

The combined ADHD profile faces the greatest risk of delay, depletion and disengagement in university students.

Vanessa Müller, Bettina Pikó

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Vanessa MüllerDoctoral School of Education, University of Szeged, Szeged, Hungary. muller.vanessa@med.u-szeged.hu.ORCID http://orcid.org/0000-0003-4027-3452
Bettina PikóDepartment of Behavioral Sciences, University of Szeged, Szeged, Hungary.ORCID http://orcid.org/0000-0002-3072-9615

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attention-deficit/hyperactivity disorder (ADHD) symptoms are increasingly recognized in adulthood, particularly among university students, yet their distinct psychological correlates remain underexplored. Using a cross-sectional design, this study examined Hungarian college students (N = 1,879, aged between 18 and 35 years) who responded online to a set of questionnaires that included the Adult ADHD Self-Report Scale, Procrastination Scale, Higher Education Retention Scale and Ego-Depletion Scale. We applied k-means cluster analysis to classify students into four ADHD-related groups (Combined, Inattentive, Hyperactive-Impulsive, Low-symptom) based on symptom criteria. Consequently, we compared these clusters across six theoretically relevant self-regulatory outcomes: maladaptive and adaptive procrastination, maladaptive and adaptive perfectionism, ego depletion and dropout intention. A multivariate analysis of covariance (MANCOVA), controlling for age and biological sex, revealed significant differences among ADHD clusters on all outcomes. While the Combined group reported the highest levels of maladaptive procrastination and ego depletion, the Hyperactive-Impulsive and Low-symptom groups reported the highest adaptive procrastination scores. These findings suggest that adaptive procrastination may serve as a protective or compensatory strategy in students with certain ADHD profiles, offering constructive reconceptualization of functional delay and self-regulation in academic contexts.

Indexed as

Attention Deficit Disorder with HyperactivityStudentsUniversitiesAdolescentAdultCross-Sectional StudiesFemaleHumansHungaryMaleMental FatiguePerfectionismProcrastinationStudent DropoutsYoung AdultADHDdropout intentionego depletionperfectionismprocrastinationuniversity students

Identifiers

PMID41735456
PMCPMC13031801

What OpenQuestion holds

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Registered trials

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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.