Evidence map›Paper›PMID 38562605›Full record

ArticleNeuroscience of consciousness2024

Feeling our place in the world: an active inference account of self-esteem.

Mahault Albarracin, Gabriel Bouchard-Joly, Zahra Sheikhbahaee, Mark Miller, Riddhi J Pitliya, Pierre Poirier

Abstract read
In one paragraph

Article in Neuroscience of consciousness, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

6 authors.

Mahault AlbarracinDépartement d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada.ORCID https://orcid.org/0000-0003-0916-4645
Gabriel Bouchard-JolyDépartement d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada.
Zahra SheikhbahaeeCHU Sainte-Justine Research Center, University of Montreal, 5757, Av. Decelles bureau 500, Montreal, QC H3S 2C3, Canada.
Mark MillerMonash Centre for Consciousness and Contemplative Studies, Monash University, Melboume, Australia.
Riddhi J PitliyaDepartment of Experimental Psychology Oxford University, Oxford OX1 2JD, United Kingdom.
Pierre PoirierDépartement d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-esteem, the evaluation of one's own worth or value, is a critical aspect of psychological well-being and mental health. In this paper, we propose an active inference account of self-esteem, casting it as a sociometer or an inferential capacity to interpret one's standing within a social group. This approach allows us to explore the interaction between an individual's self-perception and the expectations of their social environment.When there is a mismatch between these perceptions and expectations, the individual needs to adjust their actions or update their self-perception to better align with their current experiences. We also consider this hypothesis in relation with recent research on affective inference, suggesting that self-esteem enables the individual to track and respond to this discrepancy through affective states such as anxiety or positive affect. By acting as an inferential sociometer, self-esteem allows individuals to navigate and adapt to their social environment, ultimately impacting their psychological well-being and mental health.

Indexed as

active inferencemodelself-esteemsociometer

Identifiers

PMID38562605
PMCPMC10984624

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.