Evidence map›Paper›PMID 36673868›Full record

ArticleInternational journal of environmental research and public health2023

The Impact of Fitness Influencers on a Social Media Platform on Exercise Intention during the COVID-19 Pandemic: The Role of Parasocial Relationships.

Wenjia Li, Huangyi Ding, Guifen Xu, Jidong Yang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Wenjia LiCollege of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China.
Huangyi DingCollege of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China.
Guifen XuCollege of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China.
Jidong YangSchool of Creativity and Art, Shanghai Tech University, Shanghai 201210, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of COVID-19 pandemic lockdowns, fitness influencers on social media are greatly involved in people's home fitness processes, but there is limited research examining the role of fitness influencers on social media in exercise intention. This study aimed to explore whether people's perceptions of the personal attributes and content quality of fitness influencers can promote a strong emotional connection between the two, thereby influencing people's exercise intentions. Based on the theory of the parasocial relationship, we investigated the influence of social attractiveness (SA), physical attractiveness (PA), task attractiveness (TA), and content quality (CQ) of fitness influencers on the parasocial relationships (PSRs) between viewers and fitness influencers on social media and whether PSRs positively contribute to viewers' exercise intentions (EI). The results revealed that SA, PA, TA, and CQ have positive influences on PSRs and CQ; PSRs directly contribute to EI; and PSRs have a mediating effect between EI and CQ. This study provides new insights into understanding the relationship between fitness influencers and people's online fitness behaviors.

Indexed as

COVID-19Social MediaCommunicable Disease ControlHumansIntentionPandemicsCOVID-19exercise intentionfitness influencerfitness videoparasocial relationshipspersonal attributessocial media

Identifiers

PMID36673868
PMCPMC9858650

What OpenQuestion holds

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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.