Network analysis of occupational stress and job satisfaction among radiologists

被引:3
作者
Ji, Juan [1 ]
He, Bosheng [1 ]
Gong, Shenchu [1 ]
Sheng, Meihong [1 ]
Ruan, Xiwu [1 ]
机构
[1] Nantong Univ, Peoples Hosp Nantong 1, Dept Radiol, Affiliated Hosp 2, Nantong, Jiangsu, Peoples R China
关键词
occupational stress; job satisfaction; radiologists; network analysis; intricate relationships; HEALTH; DOCTORS; BURNOUT;
D O I
10.3389/fpubh.2024.1411688
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Occupational stress and job satisfaction significantly impact the well-being and performance of healthcare professionals, including radiologists. Understanding the complex interplay between these factors through network analysis can provide valuable insights into intervention strategies to enhance workplace satisfaction and productivity.Method In this study, a convenience sampling method was used to recruit 312 radiologists for participation. Data on socio-demographic characteristics, job satisfaction measured by the Minnesota job satisfaction questionnaire revised short version (MJSQ-RSV), and occupational stress assessed using the occupational stress scale. Network analysis was employed to analyze the data in this study.Results The network analysis revealed intricate patterns of associations between occupational stress and job satisfaction symptoms among radiologists. Organizational management and occupational interests emerged as crucial nodes in the network, indicating strong relationships within these domains. Additionally, intrinsic satisfaction was identified as a central symptom with high connectivity in the network structure. The stability analysis demonstrated robustness in the network edges and centrality metrics, supporting the reliability of the findings.Conclusion This study sheds light on the complex relationships between occupational stress and job satisfaction in radiologists, offering valuable insights for targeted interventions and support strategies to promote well-being and job satisfaction in healthcare settings.
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页数:8
相关论文
共 35 条
[1]   Hospital nurses' job satisfaction, individual and organizational characteristics [J].
Adams, A ;
Bond, S .
JOURNAL OF ADVANCED NURSING, 2000, 32 (03) :536-543
[2]  
[Anonymous], 1996, GRAPHICAL MODELS
[3]   Job Demands-Resources theory and self-regulation: new explanations and remedies for job burnout [J].
Bakker, Arnold B. ;
de Vries, Juriena D. .
ANXIETY STRESS AND COPING, 2021, 34 (01) :1-21
[4]   Network analysis of depression and anxiety symptom relationships in a psychiatric sample [J].
Beard, C. ;
Millner, A. J. ;
Forgeard, M. J. C. ;
Fried, E. I. ;
Hsu, K. J. ;
Treadway, M. T. ;
Leonard, C. V. ;
Kertz, S. J. ;
Bjoegvinsson, T. .
PSYCHOLOGICAL MEDICINE, 2016, 46 (16) :3359-3369
[5]   Harmonious Passion at Work: Personal Resource for Coping with the Negative Relationship between Burnout and Intrinsic Job Satisfaction in Service Employees [J].
Benitez, Miriam ;
Orgambidez, Alejandro ;
Cantero-Sanchez, Francisco J. ;
Leon-Perez, Jose M. .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2023, 20 (02)
[6]   Ergonomics in the Development and Prevention of Musculoskeletal Injury in Interventional Radiologists [J].
Benjamin, Jamaal L. ;
Meisinger, Quinn C. .
TECHNIQUES IN VASCULAR AND INTERVENTIONAL RADIOLOGY, 2018, 21 (01) :16-20
[7]   Network Analysis: An Integrative Approach to the Structure of Psychopathology [J].
Borsboom, Denny ;
Cramer, Angelique O. J. .
ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 9, 2013, 9 :91-121
[8]  
Chen J., 2009, The development and application of the clinical Physicians' sources of work stress scale
[9]   State of the aRt personality research: A tutorial on network analysis of personality data in R [J].
Costantini, Giulio ;
Epskamp, Sacha ;
Borsboom, Denny ;
Perugini, Marco ;
Mottus, Rene ;
Waldorp, Lourens J. ;
Cramer, Angelique O. J. .
JOURNAL OF RESEARCH IN PERSONALITY, 2015, 54 :13-29
[10]   Estimating psychological networks and their accuracy: A tutorial paper [J].
Epskamp, Sacha ;
Borsboom, Denny ;
Fried, Eiko I. .
BEHAVIOR RESEARCH METHODS, 2018, 50 (01) :195-212