Evidence map›Paper›PMID 39602476›Full record

ArticlePloS one2024

Development and validation of an unsafe behavior checklist for workers.

Myung-Hee Kim, Jin-Hyuk Hong, Byung-Jo Moon, Woo-Je Lee, Jin-Woo Jung

Abstract readValidation Study
In one paragraph

Article in PloS one, 2024. 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

5 authors.

Myung-Hee KimDepartment of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.ORCID 0000-0003-3487-4016
Jin-Hyuk HongDepartment of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Byung-Jo MoonDepartment of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Woo-Je LeeDepartment of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Jin-Woo JungDepartment of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.ORCID 0000-0003-1809-0326

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study is to develop and validate a simple unsafe behavior checklist to assess the extent of unsafe behavior among workers in an industrial setting. The checklist was developed using Focus Group Interview (FGI) and Analytical Hierarchy Process (AHP) analysis methodology. Preliminary testing was conducted with an unspecified sample and the correlation between unsafe behavior and accident experience was validated. The analyzed and compared the correlation between the type of unsafe behavior and accident experience and demonstrated the suitability of the unsafe behavior checklist. A risk sensitivity and risk-taking checklist was employed to identify five types of unsafe behavior. This study concludes that the unsafe behavior checklist can be used to predict accident concerns among workers with high types of dangerous behavior. This can help improve unsafe behavior and reduce the frequency of incidents. Therefore, the "Unsafe behavior Checklist" developed in this study can be used as an early indicator of the extent to which workers are aware of dangers in industrial workplaces in order to prevent accidents.

Indexed as

ChecklistAccidents, OccupationalAdultDangerous BehaviorFemaleFocus GroupsHumansMaleOccupational HealthRisk-TakingSurveys and QuestionnairesWorkplace

Identifiers

PMID39602476
PMCPMC11602037

What OpenQuestion holds

Textmetadata
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.