Author: Efosa Obariase, MS
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: John F Reichard, PhD
Abstract:
Inorganic lead (Pb) is a critical occupational and environmental toxicant with dermal exposure representing an underexplored pathway of exposure. The dissolution of lead salts in sweat plays a key role in its dermal absorption; however, the rate of dissolution is influenced by the chemical constituents of sweat. This study investigates the effect of pH on the dissolution kinetics of Pb nitrate in synthetic sweat to improve understanding of the dermal exposure pathway and inform occupational health risk assessment.
A factorial study design was employed with three pH levels (4.5, 5.5, 6.5) and seven time points (0–180 min). Dissolution assays were conducted using Varian VK 7000 dissolution apparatus, and Pb concentrations were quantified using ICP-MS. Statistical analysis was conducted on study data using two-way ANOVA and Tukey’s Post-Hoc comparison tests.
Maximum dissolution of lead nitrate was achieved in synthetic sweat at pH 4.5 with approx. 66% of the starting mass going into solution. At pH 5.5, dissolution peaked around 45% before declining to approx. 28%. The lowest amount of dissolved Pb was at pH 6.5, with maximum dissolution at approx. 31% and decreasing to approx. 20%. ANOVA confirmed pH has a significant effect on dissolution outcomes (F (2,42) = 1580.57, p < 0.001), indicating substantial differences in dissolution rates across pH levels. Pairwise comparisons confirmed significantly lower dissolution with increasing pH (4.5 > 5.5 > 6.5, all pairwise p < 0.0001).
The pH of sweat was identified as a primary determinant of inorganic Pb dissolution, with more acidic conditions sustaining markedly greater dissolved Pb concentrations than near-neutral pH levels. This emphasizes the pivotal role of sweat acidity in controlling dermal Pb bioaccessibility and indicates that individuals with lower sweat pH could face heightened dermal exposure risks. These findings reinforce the importance of integrating sweat chemistry variability into occupational exposure and risk-assessment frameworks.
Author: Hannah L. Frame
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Dr. Yevgen Nazarenko
Abstract:
Safety is critical in the aviation industry, and the creation of an unsafe working environment jeopardizes both passenger and worker health and safety. Human factors and errors are the main contributing factors in up to 75% of accidents in the aviation industry. Health and safety training offers the opportunity to impact aviation workers’ health and safety motivation as well as their attitudes, beliefs, and behavior surrounding safety. However, due to the ongoing prevalence of accidents, it is clear that current training practices are not sufficient. This study will investigate the impact of focus and cognitive load experienced by workers during health and safety training on occupational health and safety motivation, perceived safety culture, and job satisfaction among workers in the aviation industry. By characterizing these factors and describing their connection with engagement in a training environment, this study aims to probe the connection between occupational health and safety motivation and focus during training.
Author: Tigist Zewde
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Dr. Paul Norrod, Dr. Afton Erbe, and Tara Haskins.
Abstract:
Significance: Loggers experience persistently high suicide mortality compared to other occupations, which is driven by hazardous work, social isolation, stigma, and uncontrollable stress. However, there is a lack of epidemiologic evidence on the factors contributing to logger suicide despite their alarming suicide rates (161/100,000). This study addresses the knowledge gap by identifying contextual characteristics and circumstantial factors contributing to logger suicide.
Theoretical framework: Bronfenbrenner’s ecological theory frames how individual factors (e.g., injuries, mental health) and systems-level conditions (e.g., lethal means access, timber prices) are associated with a logger’s risk of suicide.
Methods: We conducted a case-series study of U.S. logger suicides using the National Violent Death Reporting System, 2003-2022. Loggers were identified using occupational codes. Investigators described logger demographics and thematically classified suicide death narratives using six predefined themes. Interrater reliability was moderate–high across all coders with disagreement debated until thematic reconciliation.
Results: There were 665 loggers who died by suicide during the study period. Aligning with occupational suicide research, firearms were used in 71% of the deaths followed by hanging/strangulation/suffocation. Thematic classification found that 58% of loggers experienced a mental health problem preceding death.
Conclusions: Study findings highlight the need for occupational health nurses to implement and advocate for multilevel prevention tailored to logging. Interventions should include awareness of mental health problems in loggers, lethal means safety aligned with rural contexts, and logging crew-based peer support with confidential access to evidence-based care. Partnerships across employers, clinicians, and state forestry agencies should guide targeted, evaluable interventions and ongoing surveillance.
Author: Abour Dondi
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Mercy Omoifo, Dickson Rungere, Kermit G. Davis
Abstract:
MSDs are mostly reported in healthcare industry. Long-term care Nurses and Nurse aides complete physically demanding jobs on routine basis. Prevalence of MSDs for nurses and nurse aides in Long-term care facilities is high for LBP (63%). Few studies that have utilized wearable sensors to objectively quantify postural demand
Author: Michael Yermakov
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Jun Wang, Sergey Grinshpun, Xinyi Niu
Abstract:
Background: Firefighters are routinely exposed to hazardous airborne contaminants, including particulate matter (PM), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs), generated during structural fires. Despite the use of NFPA-certified personal protective equipment (PPE), recent studies have demonstrated that toxicants penetrate turnout gear due to design limitations, thermal degradation, and operational stress. To date, field-deployable technology to quantify real-time protective performance has been largely unavailable.
Methods: This study addressed this gap by developing and testing a wearable, real-time monitoring system designed to calculate the Workplace Protection Factor (WPF) by continuously measuring PM and VOC concentrations both inside and outside the PPE ensemble. The system utilized two magnetically coupled sensor pockets: an external unit for ambient monitoring and an internal unit for in-gear exposure assessment. Each unit featured a miniaturized low-cost PM sensor and a photoionization detector (PID)-based VOC sensor.
Results: The research was conducted in two phases: we identified and calibrated sensors under laboratory conditions that mimicked the extreme heat, humidity, and smoke environments of a fireground. Sensors were benchmarked against reference-grade optical particle counters and calibrated PIDs. We developed specific calibration algorithms to mitigate environmental interferences. In the second phase, system performance was evaluated using a full-body manikin equipped with turnout gear and a Breathing Recording and Simulation System (BRSS). The manikin was exposed to controlled combustion byproducts (wood, plastics, paper) while simulating workloads at mean inspiratory flows of 30, 85, and 135 L/min to represent moderate to strenuous breathing.
Conclusions: The system successfully generated dynamic WPF values across varying environmental and physiological conditions. This pilot study provided the foundational data and a validated prototype necessary for future field deployment. These findings contribute to evidence-based strategies to improve firefighter health and safety, particularly for high-risk responders.
Author: Dickson J. Rungere
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Amour C. Dondi, Ryan Bellacov, Mercy Omoifo-Irefo, Alana Pringle, Peirre Abbey, Kyle Pickney, Kermit G. Davis, Ph.D.
Abstract:
Falls when egressing and ingressing a hospital bed are common occurrences. The height of the bed may be one of the critical factors related to these falls, as it may result in non-optimal postures of the body, especially the lower extremities. The study evaluated individuals egressing and ingressing a bed using a motion capture system. Low bed height (25 to 39 cm) and high hospital bed height (63 to 87 cm) were shown to have greater flexion and abduction angles of the upper/lower arm, ankle, pelvis, knee, and head with more difficulty, less stability, and more slippery participant perception. Further, the results suggest that setting a hospital bed at mid-range height (39 -63 cm) could significantly reduce the risk of patient falls.
Author: Ron Neimark
Affiliated University: University of Illinois at Chicago
Collaborators/Faculty Mentors: Preethi Pratap, Kirsten Almberg, Lee Friedman
Abstract:
Introduction/Background
Hospital workers experience musculoskeletal disorders (WMSDs) at rates substantially higher than workers in most other industries, yet regulatory approaches have largely focused on patient-handling hazards and Registered Nurses, with limited attention to other occupational groups or staffing as a structural determinant of risk. This study examines the incidence and severity of WMSDs among Illinois hospital workers and evaluates whether nurse staffing levels are associated with injury rates.
Methods
This retrospective observational study analyzed Illinois Workers’ Compensation First Report of Injury (FROI) data for hospital workers from 2018–2023. Musculoskeletal injuries were identified using standardized nature and cause codes aligned with Bureau of Labor Statistics definitions. Injury incidence rates were estimated using negative binomial regression with employment denominators derived from the American Community Survey. Injury severity was examined using logistic regression. For general hospitals with medical-surgical units, hospital-wide nursing WMSD rates were compared by staffing levels using Nursing Hours per Patient Day (NHPPD) and Registered Nurse Hours per Patient Day (RNHPPD).
Results
A total of 5,656 hospital worker WMSDs were identified. Nursing assistants and service workers experienced the highest injury incidence across all regions. Injury rates were significantly higher in Chicago and Suburban Cook County than in other parts of Illinois. Among injured workers, Registered Nurses and service workers had the highest odds of severe injury. Hospitals in the Chicago metropolitan area showed significantly greater odds of severe injuries. In years with available staffing data, hospitals with higher musculoskeletal injury rates had significantly lower medical-surgical staffing levels, particularly nursing support hours per patient day.
Conclusion/Discussion
Findings suggest that patient-handling programs alone are insufficient without addressing workload and staffing adequacy, particularly for nursing assistants and service workers. Strengthening staffing standards and expanding ergonomic regulation beyond patient lifting may reduce injury risk and improve workforce sustainability in Illinois hospitals.
Author: Abas Shkembi
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Richard L. Neitzel
Abstract:
Background: Occupation is a neglected social determinant of health. Injuries and deaths directly occurring in workplaces are well characterized, but delayed downstream outcomes often exacerbated by other social stressors are difficult to attribute to occupational risks. A traditionally narrow focus on safety risks has limited our understanding of the full public health burden of occupational risks.
Methods: We conducted a subnational estimation of 14 chemical, physical, biological, safety, and psychosocial occupational risk factors in the United States (US) between 2010 to 2019. We leveraged this spatiotemporal exposure characterization to empirically estimate the effect of each occupational risk factor on mortality using data on all deaths among the working age population in the US (15-64 years old). We then counterfactually quantified the potential, excess deaths due to each occupational risk.
Findings: On average, the most prevalent risk factors were musculoskeletal strain (27%; 95% uncertainty interval (UI): 11-39%), infectious disease transmission (25%; 95% UI: 9-49%), and noise (20%; 95% UI: 17-23%) during 2010-2019. We estimated that the 14 occupational risk factors together impose an average of 147,000 (95% UI: 80,000-200,000) annual excess deaths in the working age population, over one-fifth of working age deaths.
Interpretation: The large uncertainty in our estimates highlight the need for a robust occupational exposure surveillance system in the US. Regardless, our research suggests that occupational risks are likely a meaningful driver of mortality among the working age population. Their burden could be substantially larger than what current health surveillance of occupational fatalities indicates. Occupational health should remain a focus of public health prevention and policy efforts.
Author: Mercy Omoifo-Irefo
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Kermit Davis PhD
Abstract:
Respirable crystalline silica (RCS) is generated during cutting, grinding, drilling, and demolition of silica-containing materials and can deposit in the distal lung which poses significant health risks, including diseases like silicosis and lung cancer, classified as carcinogenic by the International Agency for Research on Cancer (International Agency for Research on Cancer, 2012; National Institute for Occupational Safety and Health [NIOSH], 2002). Despite existing regulatory frameworks under OSHA to limit RCS exposure, construction tasks still reveal frequent overexposures, necessitating more refined strategies for monitoring and prevention (Flanagan et al., 2003; Occupational Safety and Health Administration [OSHA], 2016).
The primary aim of this research is to empirically quantify personal breathing-zone exposure to RCS among construction workers engaged in silica-generating tasks and to identify the factors contributing to increased exposure levels. To accomplish this, field exposure assessments will be performed at multiple construction sites that are currently disturbing concrete, masonry, and stone materials. Workers aged 18 and above will be monitored through personal breathing zone sampling utilising calibrated pumps and size-selective sampling media to collect data, which will subsequently be analysed using X-ray diffraction (XRD) techniques consistent with occupational exposure standards (NIOSH, 2002; OSHA, 2016). Additionally, the study aims to log task durations, tool usage, site conditions, and other relevant variables through questionnaires, facilitating a comprehensive characterisation of exposure risks.
Expected outcomes of this research include the development of a detailed exposure profile that correlates specific work activities with heightened RCS exposure. This research will consider differences between workers and look for specific task and condition combinations that lead to the highest exposure levels (Carey et al., 2018; Flanagan et al., 2003). The information collected will help create specific plans to reduce RCS exposure for construction workers, leading to a better understanding of how to prevent health risks related to silica in real-life situations.
The significance of this study lies in its focus on practical task determinants of RCS exposure, thereby enhancing the accuracy of exposure characterization, which in turn underpins actionable health protection initiatives for construction workers in environments where silica-related illnesses remain both preventable and persistent (NIOSH, 2002; OSHA, 2016).
Author: Jisang Um; Jun Hu; Oshin Tyagi
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Dr. Oshin Tyagi
Abstract:
Emergency Medical Technicians (EMTs) experience musculoskeletal disorders (MSDs) at rates six times higher than the national average. Their routine duties, such as carrying heavy equipment and patient handling, place substantial strain on the lower back, highlighting the need for interventions to reduce MSDs. Passive low-back exoskeletons, which have been shown to reduce low back strain during repetitive and static tasks, may reduce MSD risk for EMTs. However, since EMTs work in highly dynamic environments, their potential for EMS remains unclear.
To evaluate this potential, we examined the effects of exoskeleton use on low back and thigh muscle activity and posture during five tasks simulating EMT duties. Twelve male and eight female EMTs performed all tasks with and without an exoskeleton, while muscle activity was recorded from the erector spinae and vastus lateralis using surface electromyography (sEMG), and joint angles were captured across the full body using inertial measurement units (IMU). A Sex (male, female) × Condition (Exoskeleton, Control) Repeated Measures Analysis of Variance was performed on the sEMG and IMU data. Perceived workload (NASA TLX) and exertion (RPE) scores were also collected after each task with and without the exoskeleton, and paired t-tests were conducted to compare scores between conditions.
Perceived workload and exertion did not change with exoskeleton use. Analysis revealed a significant condition x sex effect for a patient lifting task (p = 0.008), where post hoc analysis revealed that the exoskeleton made male EMTs use more of their low back muscles while lifting. In contrast, during a patient dragging task, the exoskeleton reduced trunk variability (p = 0.021). These findings suggest that an exoskeleton’s effect on low back activity and posture may depend on the specific task, providing support in some contexts while hindering in others. Importantly, they also highlight the need for proper and effective training protocols, as targeted instruction may enhance the ergonomic effectiveness of exoskeletons in dynamic work environments.
Author: Nathan Chen & Austin Dymont
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Richard Neitzel
Abstract:
Background: Occupational exposure to whole-body vibration (WBV) has been associated with adverse musculoskeletal health effects, especially for lower back pain, which is one of the occupational diseases increasing disability-adjusted life years. Occupational drivers who drive cargo vans in delivery industries are exposed to WBV during their regular work. Recently, a WBV mobile application utilizing accelerometers built into off-the-shelf smartphones to has been validated to measure vibration in mining vehicles and light vehicles. However, the validation of using the WBV mobile app to measure WBV exposure on the cargo van for exposure assessment purpose remains limited.
Study Aim: The present study aimed to evaluate the performance of using a mobile app to estimate whole-body vibration (WBV) in a cargo van through a simulated experiment.
Methods: The simulated experiment measured the vibration from the seat using the standard whole-body vibration dosimeter (Larson Davis HVM200 logger, PCB Piezotronics, Depew, NY, USA) and estimated the vibration level using the mobile app (WBV mobile app, Byte Works, Inc, Duluth, GA), which utilizing the accelerometers built-in the phone (iPhone 15, Apple Incorporation, Cupertino, California) on a 2018 Ford Transit cargo van for 6 hours and 42 minutes. The measured and estimated vibration levels were then calculated into frequency-weighted root-mean-square acceleration (awx, awy, and awz) and the vibration dose value for each axis (VDVx, VDVy and VDVz). The performance of the estimated vibration values was evaluated with the R2 through fitting data into simple linear regression models.
Results: The results showed the average awx, awy and awz was measured at the level of 0.12, 0.14 and 0.29 m/s2, respectively with the standard dosimeter, while was estimated at the level of 0.13, 0.13 and 0.30 m/s2 with the mobile app, respectively. The R2 between the measured and the estimated awx, awy, awz ranged from 0.72 to 0.93. Average VDVx, y and z were measured at 3.46, 3.60 and 8.41 m/s1.75, respectively, while estimated at 3.30, 3.34 and 6.80 m/s1.75, respectively. The R2 between the measured and the estimated VDVx, y and z ranged from 0.72 to 0.92.
Conclusions: The present study supported that using a mobile app to estimate whole-body vibration (WBV) in a cargo van was with good correlation with the measurements derived from standard dosimeters.
Author: Lisa McQueen French, MSN, RN, CPHQ, RHDS, Shawn Howe, Benjamin Goulart, Deyze Badarane, MD, MPH, CPH, Thomas R. Huston, PhD, Victoria W. Wulsin, PhD, MD, Beverly Hittle, PhD, RN, FAAOHN, Gordon L. Gillespie, PhD, DNP, RN, FAAN, Kermit G. Davis, PhD
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Thomas R. Huston, PhD, Victoria W. Wulsin, PhD, MD, Beverly Hittle, PhD, RN, FAAOHN, Gordon L. Gillespie, PhD, DNP, RN, FAAN, Kermit G. Davis, PhD
Abstract:
Background- Workers in health care settings face a substantial risk of workplace violence (WPV) compared to other private industries. Multiple factors, such as aggressive patients, workplace conditions, patient and visitor attitudes, and night shift work, can increase WPV risk. While regulatory agencies in the U.S. offer guidance, no national standard exists to address WPV. Many healthcare systems have their own WPV policies, and the state of Ohio recently enacted legislation to further reduce WPV in healthcare settings.
Methods- We conducted a retrospective, descriptive review of de-identified incident-reporting data from 2020 to 2024 to understand WPV occurrences. The data were obtained from two sources: an employee health treatment database (N=536) and an incident-reporting database (N=2073) within a healthcare system in Ohio.
Results- Nurses, Security/Police Personnel, and Nursing Assistants were seen in the employee health clinic more than other job titles, and WPV occurrences were higher in the Psych/Mental Health and Hospital Inpatient departments. Within the incident reporting database, most responses were classified as Code Violet (an aggressive situation requiring a security response).
Conclusions- WPV Increasing trends suggest ongoing challenges in addressing WPV. Future studies with access to staffing, volume, and integrated reporting data would provide a more robust assessment of WPV trends and risks.
Author: Onyinye A. Ezeifeka; Yevgen Nazarenko
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Yevgen Nazarenko
Abstract:
Aircraft ground operations generate particle emissions that contribute to occupational exposure of aviation workers, particularly during idle, taxiing, and takeoff phases. These operating conditions of aircraft differ substantially in combustion efficiency and fuel–air mixture used in the engines, which influence particle formation and aerosol size distribution in the emissions. Limited experimental work has compared particle emission characteristics across these operating modes under controlled laboratory conditions. This study investigates size-resolved particle emissions from Jet A fuel combustion under simulated aircraft operating conditions using a laboratory-scale combustor. Three representative operating states corresponding to idle, taxi, and takeoff were achieved by adjusting the equivalence ratio (ϕ) while maintaining constant temperature (150 °C), chamber pressure (2 atm) and air flow rate (3.915 g/s). Four equivalence ratios were tested: ϕ = 0.7, 1.0, 1.3, and 1.6. Particle sampling was done using a customized sampling train that dilutes the exhaust emissions with an airflow rate of 30 L/min using a mass flow controller (MFC). Particle number concentration and size distribution were measured using a Fast Mobility Particle Sizer (FMPS), a Scanning Mobility Particle Sizer (SMPS), and an Optical Particle Sizer (OPS), enabling high-resolution characterization of particles in the nanometer/ultrafine and coarse size ranges. Results were compared across the three operating modes to examine differences in total particle number emissions and size distribution patterns. Particular attention was given to ultrafine particles (<100 nm), which are of interest in occupational health due to their ability to penetrate deep into the respiratory system. Statistical analysis was conducted to compare particle emissions across the 4 operating conditions. Analysis of variance (ANOVA) was used to test for overall differences among conditions, followed by post hoc multiple-comparison testing to identify specific pairwise differences. Comparative analysis provides insight into how engine operational regimes influence the magnitude and characteristics of particle emissions to which aviation ground personnel and flight crews could be exposed. These findings contribute to understanding emission variability across aircraft engine operating conditions and provide evidence that can inform future occupational exposure assessments and mitigation strategies in aviation environments.
Author: Onyinye A. Ezeifeka; Yevgen Nazarenko
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Yevgen Nazarenko
Abstract:
Severe workplace injuries, defined under 29 CFR 1904.39 as amputations, in-patient hospitalizations, or loss of an eye, represent some of the most serious non-fatal outcomes of occupational exposure. Since reporting became mandatory in 2015, the OSHA Severe Injury Report (SIR) database has provided a national record of these incidents under federal jurisdiction. This study analyzed 102,922 reported cases from January 2015 through July 2025. The dataset was cleaned and analyzed using JMP statistical software. Injuries were categorized based on industry (NAICS), event type, nature of injury, and affected body part using the Occupational Injury and Illness Classification System. The results show that severe injuries peaked between 2018 and 2019, exceeding 11,000 cases per year, followed by a sharp decline during the COVID-19 period. Since then, annual cases have stabilized around 8,900 to 9,100, suggesting that improvements have slowed. Manufacturing accounted for nearly one-third of all reported injuries and had the highest proportion of amputations. Incidents involving machinery and falls made up the majority of cases, while fingers and fingertips were the most frequently injured body parts. Overall, the findings point to recurring and largely preventable injury patterns, particularly in high-risk sectors. Despite reporting requirements, similar hazards continue to drive severe outcomes, indicating ongoing gaps in machine safety practices and fall prevention efforts. These results support the need for more focused interventions and stronger implementation of engineering controls to improve worker safety.
Author: Shawn Howe, Justin Morrow, Ph.D., Michael Yermakov, M.D., Jun Wang, Ph.D., PE, CIH
Affiliated University: University of Cincinnati
Collaborators/Faculty Mentors: Justin Morrow, Ph.D., Jun Wang, Ph.D., PE, CIH
Abstract:
Respirable crystalline silica (RCS) affects 600,000 workplaces in the USA. For stone-cutting operations, RCS exposure can be exacerbated due to dust generation during uncontrolled processes. OSHA regulates RCS levels using time-consuming sampling methods and established Permissible Exposure Limits (PELs) and Action Levels (ALs) to ensure workers mitigate health risks. Emerging research from the National Institute for Occupational Safety and Health (NIOSH) using Raman spectroscopy to address these challenges is promising, showing alternative ways to both quantify and characterize RCS. This was done by creating Raman spectra from specialized dust collection methods using known-mass α-quartz both in lab and field scenarios. Field studies have been limited and are in need of developed hardware accessories for sample collection and spectra production. This thesis aims to complement NIOSH's research by evaluating the ease, speed, alignment capability, and repeatability of specialized adapted dust-collection cassettes against a field representative experimental setup that generates crystalline silica mass under stone-cutting conditions in order to evaluate the feasibility of applying NIOSH's research to the stone-cutting process and generate a Raman based calibration curve for in field use.
Author: Jingkun Wang
Affiliated University: Purdue University
Collaborators/Faculty Mentors: Denny Yu
Abstract:
Burnout, depression, and suicide among healthcare professionals are urgent occupational health challenges that align closely with the Total Worker Health (TWH) framework, which promotes integrated strategies to protect and advance worker well-being. Surgical teams are particularly vulnerable due to the intense cognitive, emotional, and interpersonal demands of their clinical environment. For example, 40% to 60% of orthopedic surgeons, 31% of nurses, and 59% of anesthesiologists report experiencing or being at high risk of burnout. These psychological stressors can compromise both healthcare worker well-being and patient safety. Yet early detection remains difficult, as current tools for assessing mental health rely on retrospective self-report questionnaires that are limited in capturing moment-to-moment psychological strain. This proposed research addresses two critical gaps: (1) the lack of communication-based indicators of burnout and psychological distress in clinical teams, and (2) the absence of predictive models that can detect emerging mental health risk from naturalistic, in-situ team interactions. We propose a novel system that continuously analyzes team dialogue in real time to assess and predict burnout risk.
Author: Johana Todd
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Julianne Armijo and Marie-Anne Rosemberg
Abstract:
Background: Disengagement-- a core component of burnout--relates to detachment from work expressed through negative attitudes and behaviors. Burnout among healthcare workers remains a significant and persistent concern, affecting provider well-being and the quality of patient care. Occupational health nurses (OHN) play a critical role at the forefront of worker health and safety, yet little is known about how their unique job demands shape burnout risk.
Objective/Purpose: We examined how organization size, measured by the number of employees, influenced disengagement among OHN.
Methods: Flyers were distributed to the Education Research Centers funded by the National Institute for Occupational Safety and Health (NIOSH) that had an OHN program. Participants were also recruited via word of mouth, social media (e.g. Facebook) and professional platforms (e.g. LinkedIn). Eligible individuals completed a survey via Qualtrics. Descriptive and regression analyses were performed controlling for time-pressure and age.
Results: The relationship between the number of employees and disengagement was statistically significant. Using an ordinary least squares regression with robust standard errors, company size was associated with disengagement. Compared to nurses in organizations with 0–50 employees, those in organizations with 51–500 employees reported higher disengagement (b = 1.59, SE = 0.61, p = .011, 95% CI [0.37, 2.80]) and those in organizations with 501–1000 employees also reported higher disengagement (b = 1.70, SE = 0.63, p = .008, 95% CI [0.46, 2.94]).
Conclusion: Organization size represents an important structural determinant when considering how OHNs experience burnout overall. More studies are needed to explore the impact of other aspects of large organizations (e.g. high workload/worker-OHN ratio; work hours; social support) on OHNs’ health and wellbeing.
Author: Xin Zhang
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Rick Neitzel
Abstract:
Wearable sensor technologies are increasingly deployed across occupational health and safety (OHS). The application started as early as the 1960s and the 1970s with the chemical and noise exposure monitoring with a shift in the 2010s toward human-centered smart health surveillance using biometrics such as heart rate, body temperature, and movement. High-risk industries including construction, mining, oil and gas, and agriculture seem to benefit the most. With long-term and personalized insights, wearables are best positioned to prevent not just acute events, but also cumulative and systemic health issues.
However, implementation barriers remain. Privacy concerns, data quality concerns, sensor inaccuracy across skin tones, and regulatory fragmentation are frequently raised among OHS professionals. This narrative review examines existing cases to show potential harms and proposes solutions in future OHS education. Wearables hold genuine promise, and their impact will depend both on the technology and the regulatory, organizational and ethical frameworks surrounding it.
Author: Kenedi Clinton
Affiliated University: University of Michigan
Collaborators/Faculty Mentors: Rick Neitzel
Abstract:
Background: Occupational noise exposure is a pervasive hazard for millions of U.S. workers, yet its cognitive impacts are poorly characterized. While environmental noise has been linked to cognitive decline and dementia, few studies have focused on occupational noise, and none have used a nationally representative older adult sample with standardized job–exposure linkages. We examined cross-sectional associations between occupational and industry noise exposure and cognitive status among older U.S. adults.
Methods: We used 2016 Health and Retirement Study data for adults aged ≥50 years. Cognitive status (normal, cognitive impairment no dementia [CIND], dementia) was classified with Langa–Weir algorithms. Occupation- and industry-specific noise metrics (mean 8‑hour A‑weighted time‑weighted average [TWA] and exceedance fractions [EFs] above 90, 85, and 80 dBA) were derived from the NoiseJEM v4 and linked via standardized occupation and industry crosswalks. Modified Poisson regression with robust variance estimated relative risks (RRs) for CIND and dementia versus normal, adjusting for demographics, with additional adjustment for lifestyle factors and occupational physical activity in sensitivity analyses; race/ethnicity-stratified models were fit for key occupational metrics.
Results: Each 1 dBA increase in occupational mean TWA was associated with higher prevalence of CIND and dementia; EF-based metrics showed stronger and more consistent associations, while industry-level noise metrics were null after adjustment. Dementia associations remained significant across EF thresholds in sensitivity models, and were strongest among non-Hispanic Black workers.
Conclusions: Occupational noise exposure is associated with higher prevalence of CIND and dementia at levels below current regulatory limits, with particularly strong effects among non-Hispanic Black workers. Findings suggest existing noise standards focused on hearing loss may not adequately protect cognitive health.