Evidence map›Paper›PMID 35805481›Full record

ArticleInternational journal of environmental research and public health2022

ICF-Based Job Performance Predictors for South Korean Industrial Accident Workers: Population-Based 3-Year Longitudinal Analysis.

Gayeong Eom, Seonjae Been, Haewon Byeon

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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
0.5field-weighted citation impact, top 37% of its field
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, 3 citations in OpenAlex.

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

3 authors at 1 institution in 1 country.

Gayeong EomDepartment of Statistics, Graduate School, Inje University, Gimhae 50834, Korea.
Seonjae BeenDepartment of Digital Anti-Aging Healthcare (BK21), Graduate School, Inje University, Gimhae 50834, Korea.
Haewon ByeonDepartment of Digital Anti-Aging Healthcare (BK21), Graduate School, Inje University, Gimhae 50834, Korea.ORCID 0000-0002-3363-390X
Inje University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since workers who have experienced industrial accidents may have a physical impairment, their workload is very likely to be less than before the industrial accident. This epidemiological study identified ICF-based predictive factors affecting the work performance of South Korean workers who were economically active after undergoing medical treatment (rehabilitation) related to injuries caused by industrial accidents by using the Panel Study of Worker's Compensation Insurance (2018-2020) as a reference. We analyzed 1383 subjects who were engaged in economic activities. The explanatory variables included participation factors, activity factors, personal factors, physical function factors, and rehabilitation service factors. The outcome variables were defined by subjective evaluations of current job performance (0 and 10 points). This study analyzed the trajectory of change in work performance and change function predictors over time by using latent growth modeling (LGM). This study found mental activity, indoor activity, occupational activity, disability grade, socioeconomic status, the length of recuperation, self-esteem, and self-efficacy as significant predictors. The results of this study suggested that it would be necessary to prepare a systematic program that considers activity factors to support the independent daily life activities and social participation of workers injured by industrial accidents.

Indexed as

Accidents, OccupationalWork PerformanceHumansIncomeRepublic of KoreaWorkers' CompensationICFindustrial accident workersjob performancelatent growth modeling

Identifiers

PMID35805481
PMCPMC9266148
OpenAlexW4283588709

What OpenQuestion holds

Textmetadata
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.