Evidence map›Paper›PMID 42668311›Full record

ArticleInternational journal of obesity (2005)2026

Identification of cognitive factors that predict behavioural weight-loss intervention outcomes.

Golnaz Arjmand, Filip M Morys, Justin J Sung, Chavonn C Duncan, Xue S Davis, Shilan Heshmati, Xi Fang, Marney A White, Carlos M Grilo, Dana M Small

Registry-linked trialAbstract read
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In one paragraph

Article in International journal of obesity (2005), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04614233 (Targeting the Gut-brain Axis to Facilitate Weight Loss in High Fat Diet Consumers), which is not on this map. Not yet cited in PubMed.

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

NCT04614233 phase4terminatednot on this map

Targeting the Gut-brain Axis to Facilitate Weight Loss in High Fat Diet Consumers

TypeinterventionalSponsorYale UniversityRan2021 to 2024Enrolled64ConditionsOverweight and ObesityArmsRiduZone (90% OEA), Placebo
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

10 authors.

Golnaz ArjmandDepartments of Neurology and Neurosurgery, Medicine, McGill University, Montreal, QC, Canada. golnaz.arjmand@mcgill.ca.
Filip M MorysDepartments of Neurology and Neurosurgery, Medicine, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0001-8996-2676
Justin J SungDepartments of Neurology and Neurosurgery, Medicine, McGill University, Montreal, QC, Canada.
Chavonn C DuncanModern Diet and Physiology Research Center, New Haven, CT, USA.
Xue S DavisModern Diet and Physiology Research Center, New Haven, CT, USA.
Shilan HeshmatiDepartments of Neurology and Neurosurgery, Medicine, McGill University, Montreal, QC, Canada.
Xi FangModern Diet and Physiology Research Center, New Haven, CT, USA.
Marney A WhiteDepartment of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
Carlos M GriloDepartment of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0003-0245-3444
Dana M SmallDepartments of Neurology and Neurosurgery, Medicine, McGill University, Montreal, QC, Canada. dana.small@mcgill.ca.ORCID http://orcid.org/0000-0001-7363-1100

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals vary widely in their response to behavioral weight-loss interventions, suggesting that neurocognitive differences may influence treatment success. We examined whether baseline cognitive performance predicted percent change in body weight over 8 months in a behavioral weight-loss trial. This secondary analysis used data from the Dietary Adaptation for Weight-loss maintenance at Yale (DAWLY) trial, a randomized, double-blind, placebo-controlled study of oleoylethanolamide (OEA) in adults with overweight or obesity. All participants completed a structured lifestyle behavioral weight-loss program (LEARN®) for four months (including dietary and physical activity guidance and behavioral strategies to achieve the lifestyle changes), followed by a four-month maintenance phase. Thirty-one participants completed the 8-month follow-up and a comprehensive neurocognitive battery. Cognitive variables were z-standardized and entered into principal component analysis; component scores were then used in regression models predicting percent weight change, adjusting for baseline weight, age, education, days tracked, sex, and treatment group. The first six components explained 73.8% of the variance in baseline cognition. Sex and PC5, characterized by strong loadings on probabilistic reinforcement learning and spatial working-memory tasks, were significantly associated with percent weight change. Individuals with higher PC5 scores and women showed greater 8-month weight loss. These results suggest that the ability to learn and update value contingencies and to use effective working-memory strategies may contribute to successful weight-loss during behavioral interventions. Clinical trial registration: www.ClinicalTrials.gov , identifier: NCT04614233.

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Registered trials

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.