Effect of occupational health nursing practice on musculoskeletal pains among hospital nursing staff in South Korea

Kim, Yeon-Ha; Jung, Minsoo

doi:10.1080/10803548.2015.1078046

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…However, our study results showed that nurses working in excess of three hours of overtime per week did have a significantly higher level of near-miss error experiences, aligning with certain aspects of earlier research [ 25 ] that indicated an increase in medication errors when overtime exceeded four hours. Previous study reported that nurses’ long work hours related with job stress [ 26 ]. Since nurses’ job stress was a significant factor influencing the occurrence of near-miss errors, long work hours might be a potential factor influencing the occurrence of near-miss errors.…”

Section: Discussionmentioning

confidence: 99%

The Association of Job Stress, Quality of Sleep, and the Experience of Near-Miss Errors among Nurses in General Hospitals

Kwak,

Ahn,

Kim

2024

Healthcare

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This study investigated the association of job stress, quality of sleep, and near-miss error experiences among nurses working in general hospitals. A convenience sample of 195 nurses with over 3 months of work experience in a general hospital participated in the study. Statistical analyses were performed using SPSS 27.0. Factors influencing experiences of near-miss errors were examined through univariable and multivariate logistic regression. In total, 58.5% of nurses in a general hospital had experienced near-miss errors. Nurses in the upper job stress tertile (≥118) were 2.24 times more likely to encounter near-miss errors (95% CI: 1.07–4.69) and particularly 2.58 times (95% CI: 1.26–5.26) in falls and medical equipment-related near-miss errors. Nurses working more than 3 h of overtime per week had a 2.72 times higher (95% CI: 1.35–5.48) likelihood of experiencing near-miss errors related to falls and medical equipment and 4.03 times higher (95% CI: 1.92–8.45) likelihood of experiencing near-miss errors associated with examination procedures. To prevent near-miss errors among nurses in general hospitals, effective management of organizational job stress is crucial. Particularly for departments with a high level of overtime work (more than 3 h/week), it is essential to provide and manage educational programs on patient safety.

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Section: Discussionmentioning

confidence: 99%

The Association of Job Stress, Quality of Sleep, and the Experience of Near-Miss Errors among Nurses in General Hospitals

Kwak,

Ahn,

Kim

2024

Healthcare

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“…Particularly in the healthcare sector, ML has been utilized for targeting specific hazards. For instance, ANNs have been used to approach the burnout process [27] and statistical analysis has been employed to identify factors of musculoskeletal disorders in nursing staff [28] and to improve the management of indoor air quality in the hospital workplace [29]. Correlation methods have been used to assess the Quality of Work-Life (QWL) for the nursing profession in China [30].…”

Section: Imentioning

confidence: 99%

Utilization of Machine Learning in Supporting Occupational Safety and Health Decisions in Hospital Workplace

Koklonis

Sarafidis

Vastardi

et al. 2021

Eng. Technol. Appl. Sci. Res.

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The prediction of possible future incidents or accidents and the efficiency assessment of the Occupational Safety and Health (OSH) interventions are essential for the effective protection of healthcare workers, as the occupational risks in their workplace are multiple and diverse. Machine learning algorithms have been utilized for classifying post-incident and post-accident data into the following 5 classes of events: Needlestick/Cut, Falling, Incident, Accident, and Safety. 476 event reports from Metaxa Cancer Hospital (Greece), during 2014-2019, were used to train the machine learning models. The developed models showed high predictive performance, with area under the curve range 0.950-0.990 and average accuracy of 93% on the 10-fold cross set, compared to the safety engineer’s study reports. The proposed DSS model can contribute to the prediction of incidents or accidents and efficiency evaluation of OSH interventions.

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“…17 Além disso, há associação entre a jornada semanal de trabalho e a ocorrência de dores nos ombros e pescoço. 18 Portanto, verificou-se que precarização no processo de trabalho da enfermagem repercute diretamente na assistência prestada e na qualidade do cuidado, influenciando negativamente na saúde dos trabalhadores que participaram da pesquisa.…”

Section: Repercussões Da Precarização Na Saúde Do Trabalhadorunclassified

Influência da precarização no processo de trabalho e na saúde do trabalhador de enfermagem

et al. 2018

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Objetivo: descrever a influência da precarização no processo de trabalho e na saúde do trabalhador de enfermagem. Método: estudo qualitativo realizado em um hospital universitário. Participaram 21 trabalhadores de enfermagem. Utilizou-se a entrevista semiestruturada, e os dados foram analisados por meio da análise de conteúdo. Resultados: emergiram duas categorias denominadas a influência da precarização no processo de trabalho, caracterizada pela falta de insumos e recursos humanos com consequente queda na qualidade do serviço; e as repercussões da precarização na saúde do trabalhador, acarretando em desgaste físico e psíquico ao trabalhador Conclusão: há necessidade de sensibilização dos gestores institucionais no que se refere à precarização do processo de trabalho de enfermagem, tendo por base a saúde do trabalhador e a garantia de uma qualidade da assistência de enfermagem.

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Effect of occupational health nursing practice on musculoskeletal pains among hospital nursing staff in South Korea

Abstract: Administration strategies for nurses to adjust work-time within 46 h/week should be considered.

Cited by 5 publications

References 23 publications

The Association of Job Stress, Quality of Sleep, and the Experience of Near-Miss Errors among Nurses in General Hospitals

The Association of Job Stress, Quality of Sleep, and the Experience of Near-Miss Errors among Nurses in General Hospitals

Utilization of Machine Learning in Supporting Occupational Safety and Health Decisions in Hospital Workplace

Influência da precarização no processo de trabalho e na saúde do trabalhador de enfermagem

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