Journal of Preventive Medicine and Public Health

Original Article

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; J Prev Med Public Health. 2020;53(6):447-454. Published online October 22, 2020; DOI: https://doi.org/10.3961/jpmph.20.350

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Objectives
The aim of the present study was to investigate the relationships among hospital safety climate, patient safety climate, and safety outcomes among nurses.
Methods
In the current cross-sectional study, the occupational safety climate, patient safety climate, and safety performance of nurses were measured using several questionnaires. Structural equation modeling was applied to test the relationships among occupational safety climate, patient safety climate, and safety performance.
Results
A total of 211 nurses participated in this study. Over half of them were female (57.0%). The age of the participants tended to be between 20 years and 30 years old (55.5%), and slightly more than half had less than 5 years of work experience (51.5%). The maximum and minimum scores of occupational safety climate dimensions were found for reporting of errors and cumulative fatigue, respectively. Among the dimensions of patient safety climate, non-punitive response to errors had the highest mean score, and manager expectations and actions promoting patient safety had the lowest mean score. The correlation coefficient for the relationship between occupational safety climate and patient safety climate was 0.63 (p<0.05). Occupational safety climate and patient safety climate also showed significant correlations with safety performance.
Conclusions
Close correlations were found among occupational safety climate, patient safety climate, and nurses’ safety performance. Therefore, improving both the occupational and patient safety climate can improve nurses’ safety performance, consequently decreasing occupational and patient-related adverse outcomes in healthcare units.

Summary

Citations

Citations to this article as recorded by

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Journal of Safety Research.2024; 89: 160. CrossRef
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Keiko Ishii, Katsumi Fujitani, Hironobu Matsushita
International Journal of Risk & Safety in Medicine.2024; 35(3): 217. CrossRef
Rethinking frontline health workers’ safety performance in times of pandemic: the role of spiritual leadership
Francisca Arboh, Baozhen Dai, Prince Ewudzie Quansah, Stephen Addai-Dansoh, Samuel Atingabilli, Esther Agyeiwaa Owusu, Ebenezer Larnyo, Baaba Boadziwa Sackey
International Journal of Occupational Safety and Ergonomics.2024; 30(2): 506. CrossRef
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European Journal of Oncology Nursing.2024; 70: 102595. CrossRef
A fuzzy Bayesian network DEMATEL model for predicting safety behavior
Mohsen Mahdinia, Iraj Mohammadfam, Ahmad Soltanzadeh, Mostafa Mirzaei Aliabadi, Hamed Aghaei
International Journal of Occupational Safety and Ergonomics.2023; 29(1): 36. CrossRef
Fatigue in nurses and medication administration errors: A scoping review
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Journal of Clinical Nursing.2023; 32(17-18): 5445. CrossRef
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Sofia Guerra-Paiva, Maria João Lobão, Diogo Godinho Simões, Joana Fernandes, Helena Donato, Irene Carrillo, José Joaquín Mira, Paulo Sousa
BMJ Open.2023; 13(12): e078118. CrossRef
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Yu Mei Li, Yi Fan Luo
International Journal of Qualitative Studies on Health and Well-being.2022;[Epub] CrossRef
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Sibel Gülen, Ülkü Baykal, Nilgün Göktepe
Journal of Nursing Management.2022; 30(7): 3264. CrossRef
Survey of the health, safety and environment climate and its effects on occupational accidents
Behzad Fouladi Dehaghi, Gholamheidar Teimori-Boghsani, Davood Rahmani, Leila Ibrahimi Ghavamabadi, Sajad Zare
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The Influence of Safety Communications and Safety Promotion Policies on Safety Performance among Nurses in The Emergency Department at a Tertiary Hospital in Surabaya, Indonesia
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Brief Report

Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model?: Siavosh Abedi, Ghasem Janbabaei, Mahdi Afshari, Mahmood Moosazadeh, Masoumeh Rashidi Alashti, Akbar Hedayatizadeh-Omran, Reza Alizadeh-Navaei, Ehsan Abedini; J Prev Med Public Health. 2019;52(2):140-144. Published online February 18, 2019; DOI: https://doi.org/10.3961/jpmph.17.090

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Abstract PDF

Objectives
Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer.
Methods
In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups.
Results
Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively.
Conclusions
Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.

Summary

Citations

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Risk factors of inability to live independently in the course of lung cancer
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Biology of NSCLC: Interplay between Cancer Cells, Radiation and Tumor Immune Microenvironment
Slavisa Tubin, Mohammad K. Khan, Seema Gupta, Branislav Jeremic
Cancers.2021; 13(4): 775. CrossRef
Immune Infiltration Profiling in Nonsmall Cell Lung Cancer and Their Clinical Significance: Study Based on Gene Expression Measurements
Fangyao Chen, Yuhui Yang, Yaling Zhao, Leilei Pei, Hong Yan
DNA and Cell Biology.2019; 38(11): 1387. CrossRef

Research Support, Non-U.S. Gov't

Reliability and Data Integration of Duplicated Test Results Using Two Bioelectrical Impedence Analysis Machines in the Korean Genome and Epidemiology Study.: Boyoung Park, Jae Jeong Yang, Ji Hyun Yang, Jimin Kim, Lisa Y Cho, Daehee Kang, Chol Shin, Young Seoub Hong, Bo Youl Choi, Sung Soo Kim, Man Suck Park, Sue K Park; J Prev Med Public Health. 2010;43(6):479-485.; DOI: https://doi.org/10.3961/jpmph.2010.43.6.479

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Abstract PDF

OBJECTIVES
The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. METHODS: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October 2007 and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. RESULTS: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low R2 values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all R2>0.9). CONCLUSIONS: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.

Summary

Citations

Citations to this article as recorded by

Nutritional Consequences and Management After Gastrectomy
Jae-Moon Bae
Hanyang Medical Reviews.2011; 31(4): 254. CrossRef

Original Article

Estimation of Joint Risks for Developing Uterine Cervix Cancer in Korea.: Hachung Yoon, Aesun Shin, Sue Kyung Park, Myung Jin Jang, Keun Young Yoo; Korean J Prev Med. 2002;35(3):263-268.

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Abstract PDF: OBJECTIVE
This study was aiming at estimating the joint effects of various risk factors associated with uterine cervix cancer in Korea. METHODS: Data obtained from a case-control study were analyzed with a multiplicative model. RESULTS: After adjustment for age and husband's educational attainments, the family history of cervical cancer (OR=2.1, 95% CI=1.2-3.9), unstable marital status due to separation, by death or divorce, etc. (OR=2.8, 95% CI=1.7-4.6), and a large number of deliveries (> or = 3 vs. nulliparous OR=6.5, 95% CI=1.4-29.9) increased the risk of uterine cervix cancer. Conversely, first sexual intercourse at an older age (> or = 25 years vs. <19 years OR=0.4, 95% CI=0.2-0.6) and husband's circumcision (OR=0.7, 95% CI=0.5-1.0) decreased the risk. In the multiplicative model, the highest joint risk (OR=39.2, 95% CI 5.9-258.9) was observed in women with a family history of uterine cervical cancer, an unstable marital status, where the ex-husband was not circumcised, with 3 or more delivery experiences, and having her first sexual intercourse when younger than 19 years of age. However, women without a family history of uterine cervix cancer, married to a circumcised husband, having had her first sexual intercourse at 25 years or older, and nulliparous, showed the lowest joint effect (OR=0.3, 95% CI=0.1-0.5). CONCLUSION: As carcinogenesis is a complex action involving various factors, we consider a joint effects approach to be appropriate in an epidemiological study on risk factors for uterine cervix neoplasms.cervix neoplasm.; Summary

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