Evidence map›Paper›PMID 35898188›Full record

ArticleEvolutionary psychology : an international journal of evolutionary approaches to psychology and behavior

Vocal Characteristics Influence Women's Perceptions of Infidelity and Relationship Investment in China.

Jing Zhang, Shuli Tao

Abstract read
In one paragraph

Article in Evolutionary psychology : an international journal of evolutionary approaches to psychology and behavior. 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. Gender Role Attitudes Influence Vocal Masculine Preferences Among Gay Men in China.Evolutionary psychology : an international journal of evolutionary approaches to psychology and behavior
    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

2 authors.

Jing ZhangSchool of Psychology, 66331Sichuan Normal University, Chengdu, China.ORCID https://orcid.org/0000-0003-3939-2964
Shuli TaoSchool of Psychology, 66331Sichuan Normal University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vocal characteristics are important cues to form social impressions. Previous studies indicated that men with masculine voices are perceived as engaging in higher rates of infidelity and being less committed to their relationship. In the current study, we examined how women in China perceive information regarding infidelity and relationship investment conveyed by the voices (voice pitch and vocal tract length) of males, and whether different vocal characteristics play a similar role in driving these impressions. In addition, we examined whether these perceptions are consistent in Chinese and English language contexts. The results indicated that women perceived men with more masculine voices (lower voice pitch and longer vocal tract length) as showing a lower likelihood of infidelity and higher relationship investment; further, women who preferred more masculine voices in long-term relationships, but not in short-term relationships, were more likely to perceive men with masculine voices as less likely to engage in infidelity and more likely to invest in their relationship. Moreover, the participants formed very similar impressions irrespective of whether the voices spoke native (Chinese) or foreign (English) languages. These results provide new evidence for the role of the voice in women's choices in selecting long-term partners.

Indexed as

VoiceChinaCuesFemaleHumansMaleMarriageinfidelityinvestmentMasculinemate preferencevoice

Identifiers

PMID35898188
PMCPMC10303567

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.