Evidence map›Paper›PMID 40815479›Full record

ArticleAddiction biology2025

Forward Planning in a Population-Based Alcohol Use Disorder Sample.

Johannes Steffen, Pascale C Fischbach, Lorenz Gönner, Stefan J Kiebel, Michael N Smolka

Abstract read
In one paragraph

Article in Addiction biology, 2025. 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

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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. 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

5 authors.

Johannes SteffenDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Pascale C FischbachDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Lorenz GönnerDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Stefan J KiebelFaculty of Psychology, Technische Universität Dresden, Dresden, Germany.
Michael N SmolkaDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0001-5398-5569

Funding

German Research Foundation 178 833 530 (SFB 940)German Research Foundation 402 170 461 (TRR 265)German Research Foundation 454 245 598 (IRTG 2773)German Research Foundation 521 379 614 (TRR 393)
6 · The paper itself

Abstract

backgroundEtiological theories of addictive behaviour postulate a key role for decision-making mechanisms. However, current research is lacking compelling computational models for decision-making in multistep forward planning scenarios to identify underlying mechanisms and make derived hypotheses testable.

methodsWe used a recently developed planning task and computational model to investigate performance, planning time and inferred forward planning parameters like planning depth and decision noise in 30 individuals diagnosed with mostly mild-to-moderate alcohol use disorder (AUD) relative to 32 healthy control participants, both sampled from the general population.

resultsContrary to our hypothesis, we did not observe reduced planning depth in participants with AUD but found that participants with AUD showed a higher performance in the planning task. Group differences could be explained by planning time and general cognitive performance. Importantly, participants with AUD invested more time for planning, showed a higher correlation of planning depth with incentive value and showed lower response noise, potentially indicative of higher choice consistency.

conclusionThe significant differences in planning time, moderation of planning depth by incentive value and choice consistency may reflect higher motivation and willingness to exert effort among participants with AUD compared to healthy controls. Overall, our findings do not support the notion that mild-to-moderate alcohol use disorder is associated with impairments in forward planning across multiple steps.

Indexed as

AlcoholismDecision MakingAdultCase-Control StudiesFemaleHumansMaleMiddle AgedMotivationYoung Adult

Identifiers

PMID40815479
PMCPMC12356142

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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.