Evidence map›Paper›PMID 41578111›Full record

ArticleCognitive, affective & behavioral neuroscience2026

Examining effects of effort and reward magnitude on effort-cost decision-making in people with major depressive disorder.

Alice R Klein, Soobin Hong, Aram Kim, Vikram S Chib, Sanjay G Manohar, Masud Husain, James M Gold, Adam J Culbreth

Abstract read
In one paragraph

Article in Cognitive, affective & behavioral neuroscience, 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. 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

8 authors.

Alice R KleinDepartment of Psychiatry, School of Medicine, Maryland Psychiatric Research Center, University of Maryland, Baltimore, MD, USA.
Soobin HongDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Aram KimDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Vikram S ChibDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Sanjay G ManoharNuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK.
Masud HusainNuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK.
James M GoldDepartment of Psychiatry, School of Medicine, Maryland Psychiatric Research Center, University of Maryland, Baltimore, MD, USA.
Adam J CulbrethDepartment of Psychiatry, School of Medicine, Maryland Psychiatric Research Center, University of Maryland, Baltimore, MD, USA. aculbreth@som.umaryland.edu.

Funding

Computational Mechanisms of Effort-Cost Decision-Making in SchizophreniaK23MH126986 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI CULBRETH, ADAM J. · 2021 to 2025
$827k
NIMH NIH HHS K23 MH126986NIMH NIH HHS MH126986Wellcome TrustWellcome Trust 226645/Z/22/Z
6 · The paper itself

Abstract

Motivational impairment is a primary feature of major depressive disorder (MDD); yet the cognitive mechanisms underlying this deficit remain unclear. Effort-cost decision making is a popular framework for understanding motivation in MDD. This study examined the relative contributions of reward and effort to decision-making in an effort-cost decision-making (ECDM) task. A combined sample (remitted and current) of medicated and nonmedicated individuals with MDD (N = 32) and healthy controls (HC, N = 30) completed the Apple Gathering Task. In this task, reward and effort magnitudes are parametrically manipulated to independently estimate effects of effort and reward on choice. Choice data were analyzed by using conventional analyses, as well as computational models of behavior. Compared with HC, individuals with MDD were less willing to accept offers characterized by low reward and high effort amounts. Computational analyses using hierarchical drift diffusion modeling mirrored these findings, suggesting that evidence accumulation in MDD compared with HC was 1) faster when rejecting high effort options, and 2) faster when accepting high reward options. Additionally, higher fatigue and presence of a current depressive episode was associated with reduced ECDM in those with MDD, for low reward and high effort offers. Our results highlight influences of both reward and effort on reduced ECDM in MDD. Furthermore, our results point to critical symptom (fatigue) and state-based associations (current vs. remitted status).

Indexed as

Decision MakingMajor Depressive DisorderMotivationRewardAdultFatigueFemaleHumansMaleMiddle AgedEffort-cost decision-makingFatigueMajor depressive disorderMotivationReward

Identifiers

PMID41578111
PMCPMC12997560

What OpenQuestion holds

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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.