Noise exposure and mental workload: Evaluating the role of multiple noise exposure metrics among surface miners in the US Midwest

Risk perception or hazard perception? Examining misperceptions of miners' personal exposures to noise

While perceptions of risk have been examined in the workplace to understand safety behavior, hazard perception has been overlooked, particularly for chemical, physical, and biological agents. This study sought to establish the prevalence of one type of mismatch in hazard perception, - noise misperception - among miners, to examine whether different types of noisy environments (e.g., continuous, highly variable, etc.) alter workers' misperception of their noise exposures, and to evaluate whether noise misperception is associated with hearing protection device (HPD) use behavior. In this cross-sectional study across 10 surface mines in the USA, 135 normal-hearing participants were surveyed on their perceptions of exposure to noise at work and were monitored for three shifts, each with personal noise dosimetry, to examine which workers had a mismatch in perceived versus true noise exposure by 8-hr, time-weighted average, NIOSH exposure limits (TWANIOSH). Mixed effects logistic regression and probit Bayesian Kernel Machine Regression (BKMR) models examining on the odds of noise misperception associated with four different noise metrics (kurtosis, crest factor, variability, and number of peaks >135 dB) were used to determine which types of noisy environments may influence noise misperception. The relationship between noise misperception and odds of not wearing HPDs during a work shift was further examined. Our findings showed that nearly 1 in 3 workers underestimated their exposure to noise when their true exposure was in fact hazardous (TWANIOSH≥85 dBA) for at least one shift, and 6% misperceived hazardous exposures for all shifts. Work shifts with highly kurtotic noise distributions (>3) had 3.1 (95% CI: 1.1 to 8.4) times significantly higher odds of resulting in misperceived noise; no other noise metric was significantly associated with noise misperception. BKMR modeling provided further evidence that kurtosis dominates this relationship, with an IQR increase in kurtosis significantly associated with 1.68 (95% CI: 1.13 to 2.50) higher odds of noise misperception. Although not statistically significant, misperception of hazardous noise exposure was associated with 3.2 (95% CI: 0.8 to 12.5) times higher odds of not using earplugs during a work shift. Misperception of noise occurs in the workplace, and likely occurs for other physical, chemical, and biological exposures. This hazard misperception may influence risk perceptions and worker behavior and reduce the effectiveness of behavior-related training. Elimination, substitution, or engineering controls of exposures is the best way to prevent hazard misperceptions and exposure-related diseases.

Perceived Patient Workload and Its Impact on Outcomes During New Cancer Patient Visits: Analysis of a Convenience Sample

BACKGROUND

Studies exploring the workload in health care focus on the doctors' perspectives. The ecology of the health care environment is critical and different for doctors and patients.

OBJECTIVE

In this study, we explore the patient workload among newly diagnosed patients with cancer during their first visit and its impact on the patient's perceptions of the quality of care (their trust in their doctors, their satisfaction with the care visits, their perception of technology use).

METHODS

We collected data from the Hackensack Meridian Health, John Theurer Cancer Center between February 2021 and May 2022. The technology use considered during the visit is related to doctors' use of electronic health records. A total of 135 participants were included in the study. Most participants were 50-64 years old (n=91, 67.41%). A majority (n=81, 60%) of them were White, and only (n=16, 11.85%) went to graduate schools.

RESULTS

The findings captured the significant effect of overall workload on trust in doctors and perception of health IT use within the visits. On the other hand, the overall workload did not impact patients' satisfaction during the visit. A total of 80% (n=108) of patients experienced an overall high level of workload. Despite almost 55% (n=75) of them experiencing a high mental load, 71.1% (n=96) reported low levels of effort, 89% (n=120) experienced low time pressure, 85.2% (n=115) experienced low frustration levels, and 69.6% (n=94) experienced low physical activity. The more overall workload patients felt, the less they trusted their doctors (odds ratio [OR] 0.059, 95% CI 0.001-2.34; P=.007). Low trust was also associated with the demanding mental tasks in the visits (OR 0.055, 95% CI 0.002-2.64; P<.001), the physical load (OR 0.194, 95% CI 0.004-4.23; P<.001), the time load (OR 0.183, 95% CI 0.02-2.35; P=.046) the effort needed to cope with the environment (OR 0.163, 95% CI 0.05-1.69; P<.001), and the frustration levels (OR 0.323, 95% CI 0.04-2.55; P=.03). The patients' perceptions of electronic health record use during the visit were negatively impacted by the overall workload experienced by the patients (OR 0.315, 95% CI 0.08-6.35; P=.01) and the high frustration level experienced (OR 0.111, 95% CI 0.015-3.75; P<.001).

CONCLUSIONS

The study's findings established pathways for future research and have implications for cancer patients' workload. Better technology design and use can minimize perceived workload, which might contribute to the trust relationship between doctors and patients in this critical environment. Future human factors work needs to explore the workload and driving factors in longitudinal studies and assess whether these workloads might contribute to unintended patient outcomes and medical errors.

Associations between Poorer Mental Health with Work-Related Effort, Reward, and Overcommitment among a Sample of Formal US Solid Waste Workers during the COVID-19 Pandemic

Background

Effort-reward imbalance (ERI) and overcommitment at work have been associated poorer mental health. However, nonlinear and nonadditive effects have not been investigated previously.

Methods

The association between effort, reward, and overcommitment with odds of poorer mental health was examined among a sample of 68 formal United States waste workers (87% male). Traditional, logistic regression and Bayesian Kernel machine regression (BKMR) modeling was conducted. Models controlled for age, education level, race, gender, union status, and physical health status.

Results

The traditional, logistic regression found only overcommitment was significantly associated with poorer mental health (IQR increase: OR = 6.7; 95% CI: 1.7 to 25.5) when controlling for effort and reward (or ERI alone). Results from the BKMR showed that a simultaneous IQR increase in higher effort, lower reward, and higher overcommitment was associated with 6.6 (95% CI: 1.7 to 33.4) times significantly higher odds of poorer mental health. An IQR increase in overcommitment was associated with 5.6 (95% CI: 1.6 to 24.9) times significantly higher odds of poorer mental health when controlling for effort and reward. Higher effort and lower reward at work may not always be associated with poorer mental health but rather they may have an inverse, U-shaped relationship with mental health. No interaction between effort, reward, or overcommitment was observed.

Conclusion

When taking into the consideration the relationship between effort, reward, and overcommitment, overcommitment may be most indicative of poorer mental health. Organizations should assess their workers' perceptions of overcommitment to target potential areas of improvement to enhance mental health outcomes.

Evaluating Occupational Noise Exposure as a Contributor to Injury Risk among Miners

OBJECTIVES

This study: (i) assessed the relationship between noise exposure and injury risk, comprehensively adjusting for individual factors, psychosocial stressors, and organizational influences; (ii) determined the relative importance of noise on injuries; (iii) estimated the lowest observed adverse effect level (LOAEL) of noise on injury risk to determine the threshold of noise considered hazardous to injuries; and (iv) quantified the fraction of injuries that could be attributed to hazardous noise exposure.

METHODS

In this cross-sectional study at 10 US surface mine sites, traditional mixed effects, Poisson regression, and boosted regression tree (BRT) models were run on the number of reported work-related injuries in the last year. The LOAEL of noise on injuries was identified by estimating the percent increase in work-related injuries at different thresholds of noise exposure using a counterfactual estimator through the BRT model. A population attributable fraction (PAF) was quantified with this counterfactual estimator to predict reductions in injuries at the LOAEL.

RESULTS

Among 18 predictors of work-related injuries, mine site, perceived job safety, age, and sleepiness were the most important predictors. Occupational noise exposure was the seventh most important predictor. The LOAEL of noise for work-related injuries was a full-shift exposure of 88 dBA. Exposure ≥88 dBA was attributed to 20.3% (95% CI: 11.2%, 29.3%) of reported work-related injuries in the last year among the participants.

CONCLUSIONS

This study further supports hypotheses of a dose-response relationship between occupational noise exposure and work-related injuries, and suggests that exposures ≥88 dBA may increase injury risk in mining.