Evidence map›Paper›PMID 36721799›Full record

ArticleJournal of cognition2023

Explicit and Implicit Devaluation Effects of Food-Specific Response Inhibition Training.

Loukia Tzavella, Christopher D Chambers

Abstract read
In one paragraph

Article in Journal of cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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.

Loukia TzavellaCardiff University Brain Research Imaging Centre, CF24 4HQ, UK.ORCID https://orcid.org/0000-0002-1463-9396
Christopher D ChambersCardiff University Brain Research Imaging Centre, CF24 4HQ, UK.ORCID https://orcid.org/0000-0001-6058-4114

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The overvaluation of reward-associated stimuli such as energy-dense foods can drive compulsive eating behaviours, including overeating. Previous research has shown that training individuals to inhibit their responses towards appetitive stimuli can lead to their devaluation, providing a potential avenue for behaviour change. Over two preregistered experiments, we investigated whether training participants to inhibit their responses to specific foods would be effective in reducing their evaluations when these were assessed using both explicit and implicit measures. Participants completed an online session of go/no-go training with energy-dense foods that were consistently associated with either responding (go) or inhibiting a response (no-go). An 'explicit' devaluation effect was expected as a reduction in self-reported liking from pre-to post-training for no-go items compared to both go items and foods that were not presented during training (untrained items). An 'implicit' devaluation effect was then measured using the affective priming paradigm, by comparing differences in reaction times for congruent and incongruent trials (i.e., priming effects) between food primes. Experiment 1 revealed conclusive evidence for small-to-medium devaluation effects both in terms of explicit ratings and priming effects. We also observed that the priming effect for no-go items was close to zero. Experiment 2 successfully replicated most of the preregistered and exploratory outcomes from Experiment 1 except for the priming effect for untrained items. Potential explanations for this discrepancy are discussed but overall, these findings provide further support for a devaluation effect of response inhibition training. To our knowledge, our study provides the first evidence that training-induced devaluation can potentially be captured by affective priming measures, but more research is needed to further assess their sensitivity before they can be used to elucidate the mechanisms of action underlying devaluation effects.

Indexed as

devaluationfoodgo/no-goprimingresponse inhibitiontraining

Identifiers

PMID36721799
PMCPMC9854316

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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.