Evidence map›Paper›PMID 31892270›Full record

ArticleInternational journal of environmental research and public health2019

Exploring the Impact of Unsafe Behaviors on Building Construction Accidents Using a Bayesian Network.

Shengyu Guo, Jiali He, Jichao Li, Bing Tang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Research Paradigm of Network Approaches in Construction Safety and Occupational Health.International journal of environmental research and public health · 2022
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Semantic Network Analysis Using Construction Accident Cases to Understand Workers' Unsafe Acts.International journal of environmental research and public health · 2021
    Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shengyu GuoSchool of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China.
Jiali HeSchool of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China.
Jichao LiSchool of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China.
Bing TangSchool of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unsafe behavior is a critical factor leading to construction accidents. Despite numerous studies supporting this viewpoint, the process by which accidents are influenced by construction workers' unsafe behaviors and the extent to which unsafe behaviors are involved in this process remain poorly discussed. Therefore, this paper selects cases from Chinese building construction accidents to explore the probabilistic transmission paths from unsafe behaviors to accidents using a Bayesian network. First, a list of unsafe behaviors is constructed based on safety standards and operating procedures. Second, several chains of unsafe behaviors are extracted from 287 accident cases within four types (fall, collapse, struck-by and lifting) to form a Bayesian network model. Finally, two accidents are specifically analyzed to verify the rationality of the proposed model through forward reasoning. Additionally, critical groups of unsafe behaviors leading to the four types of accidents are identified through backward reasoning. The results show the following: (i) The time sequence of unsafe behaviors in a chain does not affect the final posterior probability of an accident, but the accident attribute strength of an unsafe behavior, affects the growth rate of the posterior probability of an accident. (ii) The four critical groups of unsafe behaviors leading to fall, collapse, struck-by, and lifting are identified. This study is of theoretical and practical significance for on-site behavioral management and accident prevention.

Indexed as

Bayes TheoremAccident PreventionAccidents, OccupationalConstruction IndustryHumansOccupational HealthProblem Solvingaccident preventionBayesian networkbuilding constructionchains of unsafe behaviorsprobabilistic transmission path

Identifiers

PMID31892270
PMCPMC6981992

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.