Evidence map›Paper›PMID 35596072›Full record

SynthesisExperimental brain research2022

No self-advantage in recognizing photographs of one's own hand: experimental and meta-analytic evidence.

Nicholas P Holmes, Charles Spence, Yves Rossetti

Abstract readMeta-Analysis
In one paragraph

Synthesis in Experimental brain research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Nicholas P HolmesSchool of Psychology, University of Nottingham, Nottingham, NG7 2RD, UK. npholmes@neurobiography.info.ORCID http://orcid.org/0000-0001-9268-4179
Charles SpenceDepartment of Experimental Psychology, University of Oxford, Oxford, UK.
Yves RossettiEquipe 'Trajectoires', Centre de Recherche en Neurosciences de Lyon, Inserm UMR-S 1028, CNRS UMR 5292, Université de Lyon, Université Lyon 1, Bron, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visually recognising one's own body is important both for controlling movement and for one's sense of self. Twenty previous studies asked healthy adults to make rapid recognition judgements about photographs of their own and other peoples' hands. Some of these judgements involved explicit self-recognition: "Is this your hand or another person's?" while others assessed self-recognition implicitly, comparing performance for self and other hands in tasks unrelated to self-other discrimination (e.g., left-versus-right; match-to-sample). We report five experiments with three groups of participants performing left-versus-right (Experiment 1) and self-versus-other discrimination tasks (Experiments 2 to 5). No evidence was found for better performance with self than with other stimuli, but some evidence was found for a self-disadvantage in the explicit task. Manipulating stimulus duration as a proxy for task difficulty revealed strong response biases in the explicit self-recognition task. Rather than discriminating between self and other stimuli, participants seem to treat self-other discrimination tasks as self-detection tasks, raising their criterion and consistently responding 'not me' when the task is difficult. A meta-analysis of 21 studies revealed no overall self-advantage, and suggested a publication bias for reports showing self-advantages in implicit tasks. Although this may appear counter-intuitive, we suggest that there may be no self-advantage in hand recognition.

Indexed as

HandRecognition, PsychologyAdultHumansJudgmentMovementHand perceptionMeta-analysisReaction timeSelf-recognition

Identifiers

PMID35596072
PMCPMC9458563

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.