23 research outputs found
Miners’ return to work following injuries in coal mines
No full textBackground: The occupational injuries in mines are common and result in severe socio-economical consequences. Earlier studies have revealed the role of multiple factors such as demographic factors, behavioral factors, health-related factors, working environment, and working conditions for mine injuries. However, there is a dearth of information about the role of some of these factors in delayed return to work (RTW) following a miner’s injury. These factors may likely include personal characteristics of injured persons and his or her family, the injured person’s social and economic status, and job characteristics. This study was conducted to assess the role of some of these factors for the return to work following coal miners’ injuries. Material and Methods: A study was conducted for 109 injured workers from an underground coal mine in the years 2000–2009. A questionnaire, which was completed by the personnel interviews, included among others age, height, weight, seniority, alcohol consumption, sleeping duration, presence of diseases, job stress, job satisfaction, and injury type. The data was analyzed using the Kaplan-Meier estimates and the Cox proportional hazard model. Results: According to Kaplan-Meier estimate it was revealed that a lower number of dependents, longer sleep duration, no job stress, no disease, no alcohol addiction, and higher monthly income have a great impact on early return to work after injury. The Cox regression analysis revealed that the significant risk factors which influenced miners’ return to work included presence of disease, job satisfaction and injury type. Conclusions: The mine management should pay attention to significant risk factors for injuries in order to develop effective preventive measures. Med Pr 2016;67(6):729–74
Genetic algorithms for feature selection of image analysis-based quality monitoring model: An application to an iron mine
No full textLoglinear Model for Assessment of Risk Factors of Occupational Injuries in Underground Coal Mines
No full textIn this study a loglinear model has been investigated to evaluate the role of various factors in coal mine injuries. Data on the varieties namely age, safety performance, working condition, safety environment, management and supervision, emotional stability, job involvement, job satisfaction, and job stress have been collected through questionnaire survey. The associations of the risk factors with occupational injuries are assessed through adjusted odds ratios (OR). The case study results reveal that significant contributing factors responsible for injuries are emotional stability (OR 2.36, 95% confidence interval(CI) 1.51-3.67), working condition (OR 2.14, 95% CI 1.37-3.35), safety performance (OR 2.04, 95% CI 1.30-3.17), safety environment (OR 1.96, 95% CI 1.25-3.06), and age with two ORs of 1.84 (95% CI 1.04 to 3.28), and 2.38 (95% CI 1.27 to 4.45). Identification of these risk factors of injuries will provide valuable information in injury preventive programs
Assessment of Whole-body Vibration Exposures Among Dumper Operators in Iron Ore Mines: A Comparative Investigation of Haul Truck Activity
No full textThis study aimed to fill the research gap on whole-body vibration (WBV) exposure of dumper operators in India, conducting a comprehensive investigation into specific phases of dumper operations. Results indicated that 59% of operators exceeded lower limits, with 90.8% exposed to vibration levels surpassing the lower limit for A(8) and VDV(8) values. Frequency analysis identified peaks aligning with crucial body parts, corroborating epidemiological findings. Statistical analysis (ANOVA) demonstrated significant differences in WBV exposure across activity groups (p \u3c 0.001), dumper speeds (p \u3c 0.001), and haul road conditions (p \u3c 0.001). Optimising driver speed, improving haul road surfaces, and regular vehicle maintenance are some recommendations to reduce WBV exposure among dumper operators
Causal relationship of some personal and impersonal variates to occupational injuries at continuous miner worksites in underground coal mines
No full textBackground: Studies regarding predictors of underground continuous miner technology-related injuries have been scarce in number, especially from the human error perspective. This study deals with risk factors (personal, including behavioral and work organizational) that influence human error and evaluates those risk factors as predictors of injury occurrences at continuous miner worksites. This study also deals with small sample size and collinearity between predictors. Material and methods: A match case-control study design was adopted. 135 cases were matched with 270 controls using matching criteria age (±5 years) and job occupation maintaining matching ratio of 1:2. A standard protocol was followed, which included: (1) a participation request to the mine management; and (2) administration of the standardized questionnaire, known as a worker\u27s response device questionnaire, to the selected workers for data collection. Four models (statistical and machine learning) were explored through the empirical training–testing approach. Results: Bootstrap integrated conditional logistic regression was found to be the best model based on predictability and interpretability. Results revealed that injury occurrences were associated with multiple factors. Personal factors included big family size (ORa = 3.37, p \u3c 0.001), no formal education (ORa = 2.80, p \u3c 0.01), regular alcohol consumption (ORa = 2.43, p \u3c 0.05), and presence of disease (ORa = 3.87, p \u3c 0.01), along with high risk-taking behavior (ORa = 2.33, p \u3c 0.05) and poor work organization (ORa = 4.75, p \u3c 0.001). Conclusion: Bootstrap integrated conditional logistic model produced efficient results for the study dataset characterized by small sample size and collinearity. Injury occurrences are multifactorial; addressing these issues through appropriate prevention programs would provide a safer workplace
Relationships of Working Conditions and Individual Characteristics to Occupational Injuries: A Case‐Control Study in Coal Miners
No full textRelationships of Job Hazards, Lack of Knowledge, Alcohol Use, Health Status and Risk Taking Behavior to Work Injury of Coal Miners: A Case‐Control Study in India
No full textWhole-body Vibration Exposure of Drill Operators in Iron Ore Mines and Role of Machine-Related, Individual, and Rock-Related Factors
No full textAbstractBackgroundThis study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics.MethodsThe study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration (m/s2)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews.ResultsMore than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient β = −0.052, standard error SE = 0.023), manufacturer (β = 1.093, SE = 0.227), rock hardness (β = 0.045, SE = 0.018), uniaxial compressive strength (β = 0.027, SE = 0.009), and density (β = –1.135, SE = 0.235).ConclusionPrevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system
The role of occupational activities and work environment in occupational injury and interplay of personal factors in various age groups among Indian and French coalminers
No full textObjective: The role of occupational hazards in occupational injury may be mediated by individual factors across various age groups. This study assessed the role of occupational hazards as well as contribution of individual factors to injuries among Indian and French coalminers. Material and Methods: We conducted a case-control study on 245 injured workers and on 330 controls without any injuries from Indian coal mines using face-to-face interviews, and a retrospective study on 516 French coalminers using a self-administered questionnaire including potential occupational and personal factors. Data were analyzed using logistic models. Results: The annual rate of injuries was 5.5% for Indian coalminers and 14.9% for the French ones. Logistic model including all occupational factors showed that major injury causes were: hand-tools, material handling, machines, and environment/work-geological/strata conditions among Indian miners (adjusted oddsratios 2.01 to 3.30) and biomechanical exposure score among French miners (adjusted odds-ratio 3.01 for score the 1-4, 3.47 for the score 5-7, and 7.26 for score ≥ 8, vs. score 0). Personal factors among Indian and French coalminers reduced/exacerbated the roles of various occupational hazards to a different extent depending on workers' age. Conclusion: We conclude that injury roles of occupational hazards were reduced or exacerbated by personal factors depending on workers' age in both populations. This knowledge is useful when designing prevention which should definitely consider workers' age
The Dynamics of Pre‐ and Post‐purchase Service and Consumer Evaluation of Online Retailers: A Comparative Analysis of Dissonance and Disconfirmation Models*
No full textWe thank the senior editor, the associate editor, and the review team for detailed suggestions that have greatly helped improve this article. We particularly thank the editor-in-chief, the senior editor, and the associate editor for their encouragement. We are indebted to Professor A. Parasuraman, James W. McLamore Chair in Marketing, University of Miami, for help with the conceptualization, and to Professor Anol Bhattacherjee, University of South Florida, for his detailed comments that have helped make the article more lucid. The research of the third author was supported in part by the National Science Foundation under grants 0916612 and 1227353. The usual disclaimer applies
