The objective of this work is to advance the understanding of helicopter accidents by examining and quantifying the association between helicopter-specific configurations (number of main rotor blades, number of engines, rotor diameter, and takeoff weight) and the likelihood of accidents. We leverage a dataset of 8,338 turboshaft helicopters in the U.S. civil fleet and 825 accidents from 2005 to 2015. We use the dataset to develop a logistic regression model using the method of purposeful selection, which we exploit for inferential purposes and highlight the novel insights it reveals. For example, one important question for the design and acquisition of helicopters is whether twin-engine turboshaft helicopters exhibit a smaller likelihood of accidents than their single-engine counterparts, all else being equal. The evidence-based result we derive indicates that the answer is contingent on other covariates, and that a tipping point exists in terms of the rotor diameter beyond which the likelihood of accidents of twin-engines is higher (worse) than that of their single-engine counterparts. Another important result derived here is the association between the number of main rotor blades and likelihood of accidents. We found that for single-engine turboshaft helicopters, the four-bladed ones are associated with the lowest likelihood of accidents. We also identified a clear coupling between the number of engines and the rotor diameter in terms of likelihood of accidents. In summary, we establish important relationships between the different helicopter configurations here considered and the likelihood of accident, but these are associations, not causal in nature. The causal pathway, if it exists, may be confounded or mediated by other variables not accounted for here. The results provided here lend themselves to a rich set of interpretive possibilities, and because of their significant safety implications they deserve careful attention from the rotorcraft community.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957302 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227334 | PLOS |
BMC Geriatr
January 2025
Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Background: Fall-prevention interventions are efficient but resource-requiring and should target persons at higher risk of falls. We need to ensure that fall risk is systematically assessed in everyday practice. We conducted a quality improvement (QI) intervention to systematize fall risk assessment and prevention in older adults hospitalized on general internal medicine wards.
View Article and Find Full Text PDFInt J Nurs Stud
January 2025
Finnish Institute of Occupational Health (FIOH), Helsinki and Oulu, Finland.
Background: Short intervals between shifts, known as quick returns, have been linked to adverse health effects, and increased risk of occupational accidents, particularly among healthcare employees. To safeguard employee health, the 2020 reform of Working Time Act in Finland limited rest periods under 11 h in irregular shift work.
Objective: To evaluate the changes in quick returns following the 2020 reform of the Working Time Act in Finland and their association with sickness absence among public healthcare employees.
Purpose: To develop a predictive model for fall risk in pre-frail older adults, providing a basis for early identification and prevention of falls among this population.
Method: This was a multicenter prospective cohort study. A total of 473 pre-frail older adults were included, 335 as the training set and 142 as the test set.
BMC Public Health
January 2025
Department of Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Study Objectives: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.
Study Design: A cross-sectional design was employed using data from the DRYAD public database.
Research Methods: The study utilized data from the Fukushima Medical University Hospital Cohort Study, obtained from the DRYAD public database.
J Pak Med Assoc
January 2025
Department of Pathology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan.
Objective: To explore the different causes of sudden death among serving government employees.
Methods: The audit study was conducted at the Pathology Department of a tertiary care hospital Combined Military Hospital (CMH) Jhelum, Pakistan, and comprised data of all autopsies between January 2017 and June 2021. Sampling was done by non probability purposive sampling technique which requires no statistical method calculation.
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