Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search

Author index

Page Path
HOME > Browse articles > Author index
Search
Amir Adibzadeh 1 Article
Predicting needlestick and sharps injuries and determining preventive strategies using a Bayesian network approach in Tehran, Iran
Hamed Akbari, Fakhradin Ghasemi, Hesam Akbari, Amir Adibzadeh
Epidemiol Health. 2018;40:e2018042.   Published online August 20, 2018
DOI: https://doi.org/10.4178/epih.e2018042
  • 19,064 View
  • 287 Download
  • 26 Web of Science
  • 27 Crossref
AbstractAbstract PDFSupplementary Material
Abstract
OBJECTIVES
Recent studies have shown that the rate of needlestick and sharps injuries (NSIs) is unacceptably high in Iranian hospitals. The aim of the present study was to use a systematic approach to predict and reduce these injuries.
METHODS
This cross-sectional study was conducted in 5 hospitals in Tehran, Iran. Eleven variables thought to affect NSIs were categorized based on the Human Factors Analysis and Classification System (HFACS) framework and modeled using a Bayesian network. A self-administered validated questionnaire was used to collect the required data. In total, 343 cases were used to train the model and 50 cases were used to test the model. Model performance was assessed using various indices. Finally, using predictive reasoning, several intervention strategies for reducing NSIs were recommended.
RESULTS
The Bayesian network HFACS model was able to predict 86% of new cases correctly. The analyses showed that safety motivation and fatigue were the most important contributors to NSIs. Supervisors’ attitude toward safety and working hours per week were the most important factors in the unsafe supervision category. Management commitment and staffing were the most important organizational-level factors affecting NSIs. Finally, promising intervention strategies for reducing NSIs were identified and discussed.
CONCLUSIONS
To reduce NSIs, both management commitment and sufficient staffing are necessary. Supervisors should encourage nurses to engage in safe behavior. Excessive working hours result in fatigue and increase the risk of NSIs.
Summary

Citations

Citations to this article as recorded by  
  • Portfolio of interventions to mature human organizational dimensions of food safety culture in food businesses
    Pauline Spagnoli, Peter Vlerick, Kaat Pareyn, Pauline Foubert, Liesbeth Jacxsens
    Food Control.2025; 168: 110937.     CrossRef
  • Analysis of factors associated with needlestick injuries of clinical nurses by applying a human factor analysis and classification system: A nationwide cross‐sectional survey
    Huimin Gao, Mengyuan Liu, Yanan Su, Yinglan Li, Lingyun Tian
    Journal of Clinical Nursing.2024; 33(6): 2178.     CrossRef
  • Causal analysis of radiotherapy safety incidents based on a hybrid model of HFACS and Bayesian network
    Haiping He, Xudong Peng, Dashuang Luo, Weige Wei, Jing Li, Qiang Wang, Qing Xiao, Guangjun Li, Sen Bai
    Frontiers in Public Health.2024;[Epub]     CrossRef
  • Resilience, job satisfaction, occupational stress, and occupational accidents among healthcare professionals: A Bayesian network analysis
    Taleb Askaripoor, Morteza Siadat, Elahe Saleh, Hamed Aghaei
    Work.2024; 79(3): 1357.     CrossRef
  • Psychological detachment from work during nonwork time as a moderator and mediator of the relationship of workload with fatigue and sleep in hospital nurses
    Hyeonmi Cho, Linsey M. Steege, Katie U. Pavek
    Sleep Health.2024; 10(5): 558.     CrossRef
  • Effects of positive and negative cyberloafing on safety behaviors and occupational incidents during the COVID-19 pandemic: a Bayesian network analysis
    Harun Yildiz, Bora Yildiz
    International Journal of Occupational Safety and Ergonomics.2024; : 1.     CrossRef
  • Shift work organization on nurse injuries: A scoping review
    Christopher C. Imes, Nicole J. Barthel, Eileen R. Chasens, Jacqueline Dunbar-Jacob, Sandra J. Engberg, Christine A. Feeley, Laura A. Fennimore, Cassandra M. Godzik, Mary Lou Klem, Faith S. Luyster, Dianxu Ren, Lynn Baniak
    International Journal of Nursing Studies.2023; 138: 104395.     CrossRef
  • Exposure to needle stick injuries among health care workers in hemodialysis units in the southwest of Iran: a cross-sectional study
    Jamshid Roozbeh, Leila Malekmakan, Mina Mashayekh, Anahita Dehghani, Soroush Ansari, Hossein Akbarialiabad, Mehdi Mahmudpour
    BMC Health Services Research.2023;[Epub]     CrossRef
  • Determination and prioritization of factors affecting the occurrence of needle stick injuries among healthcare workers using techniques of Delphi and fuzzy analytical hierarchy process (FAHP)
    Seyed Mahdi Mousavi, Saeid Yazdanirad, Sara Althubiti, Masoud Askari Majdabadi, Faranak Najarian, Parvin Sepehr
    BMC Public Health.2023;[Epub]     CrossRef
  • Analysis of occupational accidents among nurses working in hospitals based on safety climate and safety performance: a Bayesian network analysis
    Fakhradin Ghasemi, Hamed Aghaei, Taleb Askaripoor, Farhad Ghamari
    International Journal of Occupational Safety and Ergonomics.2022; 28(1): 440.     CrossRef
  • Prediction of human error probability during the hydrocarbon road tanker loading operation using a hybrid technique of fuzzy sets, Bayesian network and CREAM
    Fakhradin Ghasemi, Arash Ghasemi, Omid Kalatpour
    International Journal of Occupational Safety and Ergonomics.2022; 28(3): 1342.     CrossRef
  • Fatigue profile among petrochemical firefighters and its relationship with safety behavior: the moderating and mediating roles of perceived safety climate
    Fakhradin Ghasemi, Hemn Zarei, Mohammad Babamiri, Omid Kalatpour
    International Journal of Occupational Safety and Ergonomics.2022; 28(3): 1822.     CrossRef
  • Work schedule characteristics and occupational fatigue/recovery among rotating‐shift nurses: A cross‐sectional study
    Ari Min, Hye Chong Hong, Young Man Kim
    Journal of Nursing Management.2022; 30(2): 463.     CrossRef
  • Human and organizational failures analysis in process industries using FBN-HFACS model: Learning from a toxic gas leakage accident
    Fakhradin Ghasemi, Kamran Gholamizadeh, Amirhasan Farjadnia, Alireza Sedighizadeh, Omid Kalatpour
    Journal of Loss Prevention in the Process Industries.2022; 78: 104823.     CrossRef
  • Occupational fatigue, workload and nursing teamwork in hospital nurses
    Hyeonmi Cho, Knar Sagherian, Linda D. Scott, Linsey M. Steege
    Journal of Advanced Nursing.2022; 78(8): 2313.     CrossRef
  • Dynamic risk analysis of hydrogen gas leakage using Bow-tie technique and Bayesian network
    H. Borgheipour, G. M. Tehrani, T. Eskandari, O. C. Mohammadieh, I. Mohammadfam
    International Journal of Environmental Science and Technology.2021; 18(11): 3613.     CrossRef
  • Education and training for preventing sharps injuries and splash exposures in healthcare workers
    Shelley Cheetham, Hanh TT Ngo, Juha Liira, Helena Liira
    Cochrane Database of Systematic Reviews.2021;[Epub]     CrossRef
  • Risk Factors of Needlestick and Sharp Injuries among Health Care Workers at Sanglah Tertiary Hospital
    I Komang Widarma Atmaja, I Made Ady Wirawan, I Ketut Suarjana
    Jurnal Berkala Epidemiologi.2021; 9(1): 36.     CrossRef
  • Comparison of Job Satisfaction and Job Stress Among Nurses, Operating Room and Anesthesia Staff
    Ramin Rahmani, Ali Ebrazeh, Farzad Zandi, Roghayeh Rouhi, Shirdel Zandi
    Journal of Ergonomics.2021; 8(4): 103.     CrossRef
  • Nurse Fatigue and Nurse, Patient Safety, and Organizational Outcomes: A Systematic Review
    Hyeonmi Cho, Linsey M. Steege
    Western Journal of Nursing Research.2021; 43(12): 1157.     CrossRef
  • Multicenter cross-sectional study on the reporting status and influencing factors of needlestick injuries caused by insulin injection devices among nurses in Peking, China
    Yingyue Dong, Fangfang Li, Jing Li, Rui Li, Qun Wang
    American Journal of Infection Control.2020; 48(7): 805.     CrossRef
  • Prevalence of needlestick injuries among health-care workers in iranian hospitals: An updated systematic review and meta-analysis
    Yousef Alimohamadi, Maryam Taghdir, Mojtaba Sepandi, Leila Kalhor, Fahimeh Abedini
    Archives of Trauma Research.2020; 9(2): 47.     CrossRef
  • Predictors of Blood and Body Fluid Exposure and Mediating Effects of Infection Prevention Behavior in Shift-Working Nurses: Application of Analysis Method for Zero-Inflated Count Data
    Jae Geum Ryu, Smi Choi-Kwon
    Journal of Korean Academy of Nursing.2020; 50(5): 658.     CrossRef
  • A new scoring system for the Rapid Entire Body Assessment (REBA) based on fuzzy sets and Bayesian networks
    Fakhradin Ghasemi, Neda Mahdavi
    International Journal of Industrial Ergonomics.2020; 80: 103058.     CrossRef
  • The Relationships Among Occupational Safety Climate, Patient Safety Climate, and Safety Performance Based on Structural Equation Modeling
    Hamed Aghaei, Zahra Sadat Asadi, Mostafa Mirzaei Aliabadi, Hassan Ahmadinia
    Journal of Preventive Medicine and Public Health.2020; 53(6): 447.     CrossRef
  • Analysis of the severity of occupational injuries in the mining industry using a Bayesian network
    Mostafa Mirzaei Aliabadi, Hamed Aghaei, Omid kalatpuor, Ali Reza Soltanian, Asghar Nikravesh
    Epidemiology and Health.2019; 41: e2019017.     CrossRef
  • The links among workload, sleep quality, and fatigue in nurses: a structural equation modeling approach
    Fakhradin Ghasemi, Parnia Samavat, Fatemeh Soleimani
    Fatigue: Biomedicine, Health & Behavior.2019; 7(3): 141.     CrossRef

Epidemiol Health : Epidemiology and Health
TOP