Evidence map›Paper›PMID 42086986›Full record

ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2026

Computational phenotyping of effort-based decision-making in type-2 diabetes on and off semaglutide.

Sara Z Mehrhof, Hugo Fleming, Camilla L Nord

Abstract read
In one paragraph

Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Sara Z MehrhofMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK. sara.mehrhof@mrc-cbu.cam.ac.uk.
Hugo FlemingMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-5421-8222
Camilla L NordMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-9281-3417

Funding

AXA Research Fund (Le Fonds AXA pour la Recherche) G102329DH | National Institute for Health Research (NIHR) BRC-1215-20014RCUK | Medical Research Council (MRC) MC_UU_00030/12Wellcome TrustWellcome Trust (Wellcome) 226490/Z/22/Z
6 · The paper itself

Abstract

Motivation plays a fundamental role in human behaviour. Dopaminergic pathways have long been implicated in individual differences in motivation. Emerging evidence suggests such neural mechanisms interact with metabolic processes to coordinate energy expenditure with energy resources, thereby linking motivation with metabolic health. We ask whether a cognitive-computational index of motivation-reliably linked to neuropsychiatric symptoms-is altered in the context of type-2 diabetes and treatment with a GLP-1 agonist (semaglutide). In a pre-registered experiment, we quantified computational effort-based decision-making parameters in participants with diabetes on (N = 58) or off (N = 54) semaglutide treatment, compared to two groups of matched controls without diabetes (N = 58 each). Subjects with type-2 diabetes showed a blunted acceptance bias, a computational parameter describing the bias to accept effort for reward. This effect was not driven by neuropsychiatric comorbidity or antidepressant use. Across all participants, we found that increasing diabetes risk linearly predicted reduced acceptance bias. Participants with diabetes treated with semaglutide did not show restored motivation. Metabolic ill-health is associated with reduced acceptance bias during motivational decision-making. This blunting mirrors-but is largely independent of-neuropsychiatric motivational deficits. This suggests metabolic ill-health is accompanied by a cognitive shift towards energy conservation, potentially contributing to comorbidity between metabolic ill-health and mental illness.

Indexed as

Decision MakingDiabetes Mellitus, Type 2Glucagon-Like PeptidesHypoglycemic AgentsMotivationAgedFemaleHumansMaleMiddle AgedPhenotypeRewardSemaglutideGlucagon-Like PeptidesHypoglycemic AgentsSemaglutide

Identifiers

PMID42086986
PMCPMC13597482

What Socratic 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 Socratic graph.