Evidence map›Paper›PMID 42792343›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

People Who Identify with All of Humanity Make Less of a Moral Distinction Between Close and Distant People.

Siqi Zhao, Ziyan Wang, Huarong Liu, Qilong Li, Yumeng Sun, Kaiping Peng, Xiaomeng Hu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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

7 authors.

Siqi ZhaoDepartment of Psychology, Renmin University of China, Beijing 100872, China.
Ziyan WangDepartment of Psychology, Renmin University of China, Beijing 100872, China.
Huarong LiuDepartment of Psychology, Renmin University of China, Beijing 100872, China.
Qilong LiDepartment of Psychology, Renmin University of China, Beijing 100872, China.
Yumeng SunDepartment of Psychology, Renmin University of China, Beijing 100872, China.
Kaiping PengDepartment of Psychological and Cognitive Sciences, Tsinghua University, Beijing 100084, China.
Xiaomeng HuDepartment of Psychology, Renmin University of China, Beijing 100872, China.

Funding

Renmin University of China 311216000021
6 · The paper itself

Abstract

In the era of promoting the concept of a "Community with a Shared Future for Mankind," understanding the psychological mechanisms underlying relational morality in Chinese culture holds important theoretical and practical value, particularly given its hierarchical structure of moral obligations. Across four studies, this research innovatively proposes a calculation method for moral differential mode to deeply explore how identification with all humanity (IWAH) influences Chinese people's moral differential mode. Study 1 used questionnaires to preliminarily explore the differential characteristics of Chinese people's moral circles and found that IWAH significantly reduced moral differential mode. Study 2 verified these findings and explored the mediating role of impartial beneficence, initially constructing a mediation model. Study 3 employed experimental methods to manipulate IWAH through priming paradigms, further verifying its causal effect on moral differential mode and the mediating role of impartial beneficence. Study 4 introduced empathy as a moderating variable and found that personal distress and perspective taking moderated the effect of IWAH on moral differentiation mod. Together, these findings provide novel empirical insights into the dynamics of cultural change and social adaptation. They demonstrate how promoting global identification can expand traditional cultural norms, offering psychological pathways to foster inclusive social attitudes crucial for global cooperation and sustainable human development.

Indexed as

empathyidentification with all humanityimpartial beneficencemoral differentiation mode

Identifiers

PMID42792343
PMCPMC13603700

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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.