Evidence map›Paper›PMID 42555622›Full record

ArticlePloS one2026

Scenario-based occupational risk assessment for power grid maintenance workers.

Wan Wang, Xinghao Zhao, Lei Wang, Tingxin Qin

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wan WangDepartment of Public Safety, China National Institute of Standardization, Beijing, P. R. China.ORCID https://orcid.org/0000-0002-5662-9989
Xinghao ZhaoDepartment of Public Safety, China National Institute of Standardization, Beijing, P. R. China.
Lei WangTraining Department No. 2, Cadre Training College of the Ministry of Emergency Management of the People's Republic of China, Beijing, P. R. China.
Tingxin QinDepartment of Public Safety, China National Institute of Standardization, Beijing, P. R. China.ORCID https://orcid.org/0009-0006-4597-4249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSafety is the fundamental guarantee of power production. The safety of power operation personnel is closely related to public welfare and the sustained and stable development of the power industry. However, factors endangering the safety of power operation personnel cover multiple dimensions, including personnel operation, equipment status, working environment, and management system, which pose considerable challenges to the comprehensiveness and accuracy of risk identification.

methodsThis study integrates scenario construction theory into power operation practice. Based on the grey relational degree and Bayesian network method, a risk assessment method suitable for power operation personnel is constructed and applied in typical power operation scenarios.

resultsIn this paper, risk assessment methods are used to identify risk factors, calculate their weights, and conduct logical analysis for the operation of live-line connecting branch leads on 10 kV overhead lines. Through scenario construction, the operation is divided into four key stages with distinct dominant risk factors in each stage. The results show that human factors and environmental factors account for relatively high overall weights, which is consistent with the pattern of actual accidents. Among them, the impact of operators' physical and mental health is unexpected and requires special attention. Meanwhile, there is a significant risk transmission effect among procedures, and the quality of preceding procedures directly determines the safety of subsequent operations.

conclusionsThe calculated results provide direct data support and a reference for decision-making on the precise control of power operation safety, thereby improving the scientific rigor and effectiveness of safety prevention and control measures for power operations.

Indexed as

Occupational HealthPower Plant OperatorsPower PlantsBayes TheoremHumansRisk AssessmentRisk FactorsWorking Conditions

Identifiers

PMID42555622
PMCPMC13440883

What OpenQuestion holds

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LicenceCC BY
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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.