Evidence map›Paper›PMID 41551960›Full record

ArticleFrontiers in psychology2025

When dirty work meets social identity: decoding career avoidance intentions of Chinese hospitality students.

Xiaowen Hu, Bingyang Liang, Zichao Chen, Shengsheng Xie, Zhiyong Li

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Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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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

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Xiaowen HuSchool of Tourism Management, Sichuan University, Chengdu, China.
Bingyang LiangSchool of Management, Northwest Minzu University, Lanzhou, China.
Zichao ChenSchool of Sports, Sichuan University, Chengdu, China.
Shengsheng XieSchool of Management, Northwest Minzu University, Lanzhou, China.
Zhiyong LiSchool of Tourism Management, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A long-standing structural imbalance exists between the talent supply of hospitality management programs in China's higher education system and the actual demand of the hotel industry. Integrating Social Identity Theory (SIT) with Face Theory, this study constructs a theoretical model to explore the dual-path mediating effects of dirty work perception and face concern, as well as the moderating role of face concern. Its core objective is to reveal how social identity influences tourism management students' avoidance tendency toward employment in the hotel industry through the mediating chains of dirty work perception and face concern. Methods: Data were collected from 416 Chinese students majoring in tourism management and related fields via online questionnaires. Structural equation modeling (SEM) was employed to test the research hypotheses. Results: The results indicate that dirty work perception and face concern exert a significant serial mediating effect on the relationship between social identity and career choice intention. Additionally, face concern plays a negative moderating role in the association between dirty work perception and career choice intention. The measurement model demonstrates excellent reliability, convergent validity, and discriminant validity. Discussion: Theoretically, this study innovatively integrates Social Identity Theory with Face Theory, delves into the interactive mechanism between social-level and individual-level work cognition, thereby expanding the research boundary in the field of tourism education. Practically, the research findings provide strategic insights for hotel enterprises to optimize job design, for educational institutions to improve vocational guidance systems, and for industry associations to establish mechanisms for eliminating occupational prejudice-all of which are of great significance for promoting the reform of China's tourism talent supply system.

Indexed as

career choice intentionface concernperceived work dirtinesssocial identitytourism management

Identifiers

PMID41551960
PMCPMC12808475

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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.