Related Experiment Video
Updated: Jul 16, 2025

08:05
Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
10.7K
Fatal fall-from-height accidents: Statistical treatment using the Human Factors Analysis and Classification System -
Sabrina Santiago Oliveira1, Willames de Albuquerque Soares1, Bianca M Vasconcelos1
1Polytechnic School of Pernambuco, University of Pernambuco, Recife, Brazil.
Journal of Safety Research
|September 17, 2023
Summary
Falls from height are a leading cause of death in construction. This study identified specific conditions, like roofer age and time of day, that increase fatality risk, highlighting organizational factors as critical.
Area of Science:
- Occupational Safety and Health
- Civil Engineering
- Risk Management
Background:
- The civil construction industry (CCI) is a high-risk sector for occupational accidents.
- Falls from height are the primary cause of fatalities in construction.
- Understanding causal factors is crucial for accident prevention.
Purpose of the Study:
- To analyze combinations of causal factors with the highest likelihood of fatal falls from height in construction.
- To provide data-driven insights for improved decision-making in occupational safety.
Main Methods:
- Analysis of fatal fall-from-height accident reports in the United States (1997-2020).
- Methodology involved accident data collection, analysis, and probability determination.
- Utilized the HFACS (Fallen from Height Accident Causation System) method categories.
Main Results:
- Highest fatality probability identified for roofers aged 31-44 working between 10:00-11:59 am.
- Top causal factors: organizational process (97.7%), poor worker resource management (96.6%), and organizational climate (95.4%).
- 68% of fatal accidents occurred with 18-34 causal factors identified via HFACS.
Conclusions:
- Specific demographic and temporal factors correlate with increased risk of fatal falls.
- Organizational factors are highly prevalent in fatal fall accidents.
- The findings aid in targeted interventions to reduce construction-related fatalities.
Related Concept Videos
Hazard Rate
134
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
134
Design Consideration
206
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
The factor of safety is another key...
206
Introduction To Survival Analysis
273
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
273
Hypothesis Test for Test of Independence
3.6K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
3.6K
Assumptions of Survival Analysis
153
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
153
Survival Tree
105
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
105

