Keyword search (4,163 papers available)

"noise" Keyword-tagged Publications:

Title Authors PubMed ID
1 Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking Gagné N; Greenlaw KM; Coffey EBJ; 40412301
PSYCHOLOGY
2 Auditory working memory mechanisms mediating the relationship between musicianship and auditory stream segregation Liu M; Arseneau-Bruneau I; Farrés Franch M; Latorre ME; Samuels J; Issa E; Payumo A; Rahman N; Loureiro N; Leung TCM; Nave KM; von Handorf KM; Hoddinott JD; Coffey EBJ; Grahn J; Zatorre RJ; 40226491
PSYCHOLOGY
3 Investigating the relationship between physical, cognitive, and environmental factors of ergonomics with the prevalence of musculoskeletal disorders: A case study in a car-parts manufacturing industry Mokhtarinia H; Alimohammadi B; Sadeghi-Yarandi M; Torabi-Gudarzi S; Soltanzadeh A; Nikbakht N; 38489202
ENCS
4 Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN Valevicius D; Beck N; Kasper L; Boroday S; Bayer J; Rioux P; Caron B; Adalat R; Evans AC; Khalili-Mahani N; 37841811
ENCS
5 Decoding of Envelope vs. Fundamental Frequency During Complex Auditory Stream Segregation Greenlaw KM; Puschmann S; Coffey EBJ; 37215227
PSYCHOLOGY
6 Age of Acquisition Modulates Alpha Power During Bilingual Speech Comprehension in Noise Grant AM; Kousaie S; Coulter K; Gilbert AC; Baum SR; Gracco V; Titone D; Klein D; Phillips NA; 35548507
CRDH
7 Zoo soundscape: Daily variation of low-to-high-frequency sounds. Pelletier C, Weladji RB, Lazure L, Paré P 32735724
BIOLOGY
8 Speech perception in tinnitus is related to individual distress level - A neurophysiological study. Jagoda L, Giroud N, Neff P, Kegel A, Kleinjung T, Meyer M 30031353
PSYCHOLOGY
9 Language learning experience and mastering the challenges of perceiving speech in noise Kousaie S; Baum S; Phillips NA; Gracco V; Titone D; Chen JK; Chai XJ; Klein D; 31284145
PSYCHOLOGY
10 Automatic classification and removal of structured physiological noise for resting state functional connectivity MRI analysis. Lee K, Khoo HM, Fourcade C, Gotman J, Grova C 30695721
PERFORM

 

Title:Investigating the relationship between physical, cognitive, and environmental factors of ergonomics with the prevalence of musculoskeletal disorders: A case study in a car-parts manufacturing industry
Authors:Mokhtarinia HAlimohammadi BSadeghi-Yarandi MTorabi-Gudarzi SSoltanzadeh ANikbakht N
Link:https://pubmed.ncbi.nlm.nih.gov/38489202/
DOI:10.3233/WOR-230155
Publication:Work (Reading, Mass.)
Keywords:Musculoskeletal disordersergonomic risk factormental workloadnoise exposurephysical workload
PMID:38489202 Category: Date Added:2024-03-15
Dept Affiliation: ENCS
1 Department of Ergonomics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
2 Department of Occupational Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
3 Department of Occupational Health, School of Public Health, Qom University of Medical Sciences, Qom, Iran.
4 Department of Mechanical, Industrial and Aerospace Engineering, >Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Canada.

Description:

Background: Work-related musculoskeletal disorders (WRMSDs) is a multi-factorial disorder in most occupational setting and it has increased significantly in recent years.

Objective: This study aimed to investigate the relationship between physical, cognitive, and environmental factors of ergonomics with the prevalence of WRMSDs in a car-parts manufacturing industry.

Methods: This cross-sectional study was performed among 220 workers in a milling unit of a car parts manufacturing company in 2021-2022. The prevalence of WRMSDs was assessed using the Extended Version of the Nordic Musculoskeletal Questionnaire. Noise exposure was evaluated using dosimetry method. Mental and physical workload were evaluated by the NASA-TLX and key index methods (KIM-MHO and KIM-LHC), respectively. Data analysis was performed using SPSS version 25.0.

Results: The subjects' mean age and work experience were 36.3±6.5 and 8.35±6.41 years, respectively. Eighty-five percent of the subjects reported WRMSDs in at least one area of the body. The results of mental workload assessment revealed a high workload mean range (73.23±14.89) in all of the subjects. Mean score of KIM-LHC and KIM-MHO were 738.18±336.42 and 201.86±36.41, respectively with odds ratio of 1.32 for KIM-LHC in creating the WRMSDs. There was a significant relationship between the noise exposure, mental and physical workload and the prevalence of WRMSDs (p-value < 0.05).

Conclusion: The results of the present study revealed that environmental, physical and cognitive factors can simultaneously be effective in the prevalence of WRMSDs. Therefore, performing effective control measures requires comprehensive attention to physical, environmental, and cognitive ergonomics in the algorithm of ergonomics management in the workplace.





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University