ArticleFrontiers in psychology2026
Multidimensional mechanisms of occupational stress among healthcare workers: a structural equation modeling analysis from the seventh Guangxi health service survey.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The issue of work-related stress among medical personnel has become a key factor affecting the quality of healthcare services and the sustainable development of the medical industry. Taking healthcare workers in Guangxi as the research object, this study aims to systematically explore the multidimensional influencing factors and intrinsic action mechanisms of their occupational stress based on the structural equation model (SEM), clarify the direct and indirect effects among variables, and thus provide theoretical support and empirical evidence for formulating scientific and effective stress intervention strategies for Guangxi and other regions with similar characteristics. Method: Based on the dataset of medical staff in the Guangxi Zhuang Autonomous Region from the Seventh National Health Service Survey of China, 916 healthcare professionals from various medical institutions in Guangxi were selected as the research sample. A structured questionnaire was used to collect measurement data on latent variables including work environment, professional environment, job characteristics and personal characteristics, work experience, and work pressure. SPSS 26.0 was adopted for reliability analysis (Cronbach's Results: The model fitting results showed that all adaptation indices reached the ideal level (χ Conclusion: In view of the characteristics of concentrated ethnic minorities and unbalanced urban-rural distribution of medical resources in Guangxi, efforts should be made to optimize the physical and social aspects of the work environment of medical staff, build a harmonious doctor-patient relationship to improve the professional environment, and enhance professional identity and career growth experience to strengthen work satisfaction. It is necessary to build a multi-stakeholder collaborative intervention system involving the government, medical institutions and society, implement resource inclination and differentiated policies for grassroots and ethnic minority medical and health institutions in Guangxi, and formulate targeted pressure reduction measures combined with regional and ethnic characteristics. This can provide practical guidance for alleviating the work pressure of healthcare workers in Guangxi, stabilizing the local medical talent team, and promoting the sustainable development of the medical and health industry in ethnic minority areas.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.