Evidence map›Paper›PMID 40800220›Full record

ArticleSSM - population health2025

The relationship between social networking site body talk and college students' physical Activity: The role of upward appearance comparisons and self-compassion.

Xingyi Li, Changzhou Chen, Junjun Sun

Abstract read
In one paragraph

Article in SSM - population health, 2025. 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

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

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

3 authors.

Xingyi LiDepartment of Sport and Health, Shinhan UniversityGyeonggi Province, Republic of Korea.
Changzhou ChenSchool of Physical Education, Shanghai University of Sport, Shanghai, China.
Junjun SunSchool of Foreign Languages, Shandong Vocational and Technical University of International Studies, Rizhao City, Shandong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing penetration of social networking sites into daily life, college students are engaging more frequently in body-related expressions and interactions on these platforms, referred to as social networking site body talk. Although previous studies have indicated potential links between social networking sites, body image, and health behaviors, the relationship between social networking sites body talk and physical activity, as well as the underlying mechanisms, remain unclear. Therefore, this study focuses on examining the relationship between social networking sites body talk and physical activity among college students, and tests the mediating role of upward appearance comparison and the moderating role of self-compassion. Empirical analysis was conducted on data collected from 1189 Chinese college students (604 males and 585 females). The results showed that social networking site body talk was significantly and positively associated with physical activity. Further analysis revealed that upward appearance comparison mediated the association between social networking sites body talk and physical activity. Moreover, this mediating effect was moderated by levels of self-compassion, with the mediation being more pronounced among individuals with higher self-compassion. The findings of this study enrich the literature on social media and health behaviors, and have important practical implications for designing interventions aimed at promoting physical activity among college students.

Indexed as

College studentsPhysical activitySelf-compassionSocial networking site body talkUpward appearance comparisons

Identifiers

PMID40800220
PMCPMC12341524

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.