Zhang, Z., & Lin, K.-Y. (2023). Applying implementation science to evaluate participatory ergonomics program for continuous improvement: A case study in the construction industry. Applied Ergonomics, 115, 104181–104181. https://doi.org/10.1016/j.apergo.2023.104181
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Abstract
While participatory ergonomics (PE) presents numerous benefits, its empirical effectiveness remains elusive due to the lack of transparency in implementation contexts and processes. This hinders our ability to discern the reasons behind a program's success or failure and to determine optimization and adaptation strategies. To unravel this "black box," we present a case study using implementation science to evaluate a PE program and illuminate the mechanisms linking process to outcome. The study examines a 4.5-year PE program at a construction company, targeting musculoskeletal disorders (MSDs) from material-cart handling. Using the RE-AIM framework and Implementation Causal Pathway Model, we evaluated implementation process and catalogued contextual factors through worker surveys (n = 106), safety document review (27 training sessions and 7 construction projects), and key informant observations. We assessed the program's impact using a 42-worker survey and an analysis of 8-year injury data, and determined the return-on-investment (ROI) by monetizing the collected data. The program achieved significant impact: Workers' ergonomic knowledge improved from 73% in baseline to 86% in follow-up; 97% of workers reported at least one positive change in their crews; and no cart handling injuries occurred after the first program change, resulting in a ROI rate of 1.99. Implementation process evaluation revealed that seamless integration, tailored intervention, and ongoing adjustments contributed to the success. Five organizational factors necessary for the effective functioning of these three strategies were identified, along with three moderators that amplified their influence. Finally, this case study demonstrates that implementation science offers a coherent structure for evaluating PE programs, uncovering mechanisms of change, and informing future improvements and adaptations. Our research facilitates knowledge transfer from implementation science to ergonomics, eventually leading to more cost-effective PE programs that are faithfully implemented across various industrial settings to prevent MSDs.
• This case study employs implementation science to assess a participatory ergonomics program within the construction industry.
• The evaluation encompasses the implementation process and context, program outcomes, and the return on investment.
• We delve into the mechanisms of change, establishing a link between the process and its intervention outcomes.
• We identify critical implementation strategies, including their preconditions and moderating factors.
• Through the lens of implementation science, we provide a structured framework for evaluating the execution of ergonomic intervention, thereby guiding improvements and future adaptations
Keywords
Case study; Implementation science; Participatory ergonomics
Lee, Wonil; Lin, Ken-Yu; Johnson, Peter W.; Seto, Edmund Y.W. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-Level Construction Worker Fatigue: a Logistic Regression Approach. Engineering, Construction, and Architectural Management, 29(8), 2905–23.
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Abstract
The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors.
Keywords
Technology, management, construction safety, information and communication technology (ICT) applications
Lee, Wonil; Lin, Ken-yu; Johnson, Peter W.; Seto, Edmund Y.w. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach. Engineering Construction & Architectural Management (09699988), 29(8), 2905-2923.
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Abstract
Purpose: The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors. Design/methodology/approach: Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods. Findings: The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management. Research limitations/implications: This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group. Originality/value: This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities. [ABSTRACT FROM AUTHOR]; Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Construction Workers; Wearable Technology; Logistic Regression Analysis; Fatigue (physiology); Frequency-domain Analysis; Heart Beat; Lifting & Carrying (human Mechanics); Construction Safety; Information And Communication Technology (ict) Applications; Management; Technology
Chi, Nai-wen; Lin, Ken-yu; El-Gohary, Nora; Hsieh, Shang-hsien. (2016). Evaluating the Strength of Text Classification Categories for Supporting Construction Field Inspection. Automation In Construction, 64, 78 – 88.
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Abstract
Field inspection is a common approach to the prevention of on-site accidents in the construction industry, which aims to identify and correct violations before they result in accidents. While conducting a field inspection, quite often safety professionals need to consult applicable construction safety standards. By doing so, they can make informed judgments on the violations and reference applicable standards. Text classification (TC) can be used to classify safety standards based on the types and causes of violations. Safety professionals can therefore use violation types and causes as indices to quickly locate applicable standards. Defining TC categories (or labels) is the first important step in performing TC, because satisfactory results cannot be achieved without appropriate TC categories. Researchers often determine applicable TC categories based on the important topics within a knowledge domain. However, not all TC categories can yield satisfactory TC results because some of them are not associated with strong and specific keywords that can be identified by text classifiers. This paper proposes a methodology with two strength measures for evaluating the appropriateness of candidate TC categories. The measures were tested on two alternative sets of candidate categories that were drafted for supporting construction field inspections. The results showed that the measures could accurately predict the relative TC performance and the satisfaction levels (satisfactory or unsatisfactory) of TC categories. Beyond the construction domain, this research provides a generalized procedure for evaluating the strength of candidate TC categories. (C) 2016 Elsevier B.V. All rights reserved.
Keywords
Accident Prevention; Classification; Construction Industry; Inspection; Occupational Safety; Standards; Text Classification Categories; Construction Field Inspection; On-site Accident Prevention; Violations; Safety Professionals; Construction Safety Standards; Candidate Tc Categories; Reference Applicable Standards; Information; Model; Construction Safety; Field Inspection; Text Classification
Lee, Wonil; Lin, Ken-yu; Seto, Edmund; Migliaccio, Giovanni C. (2017). Wearable Sensors For Monitoring On-duty And Off-duty Worker Physiological Status And Activities In Construction. Automation In Construction, 83, 341 – 353.
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Abstract
Total Worker Health (R) (TWH) integrates occupational health and safety with the promotion of workers' off-duty wellbeing. Wearable sensors (e.g., activity trackers and physiological monitors) have facilitated personalized objective measurement of workers' health and wellbeing. Furthermore, the TWH concept is relevant to construction workers, especially roofing workers, as they encounter high on-duty health and safety risks and have poor off-duty lifestyles. This study examined the reliability and usability of wearable sensors for monitoring roofing workers' on-duty and off-duty activities. The results demonstrated the usability of these sensors and recommended a data collection period of three consecutive days for obtaining an intraclass correlation coefficient of 0.75 for heart rate, energy expenditure, metabolic equivalents, and sleep efficiency. The participants exhibited significant variations in their physical responses, health statuses, and safety behaviors. Moreover, several issues were identified in the application of wearable sensors to TWH evaluations for construction workers including roofers.
Keywords
Construction Workers; Wearable Technology; Employee Health Promotion; Roofing Industry; Body Sensor Networks; Health; Construction Safety And Health; Usability Study; Wearable Sensors; Worker Monitoring; Worker Physiology; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Patient Monitoring; Personnel; Roofs; Sleep; Off-duty Worker Physiological Status; Total Worker Health®; Off-duty Wellbeing; Activity Trackers; Physiological Monitors; Twh Concept; On-duty Health; Safety Risks; Off-duty Lifestyles; Monitoring Roofing Workers; Off-duty Activities; Health Statuses; Heart-rate-variability; Energy-expenditure; Health Protection; Physical-activity; Validity; Reliability; Validation; Promotion; Productivity; Actigraph
Lee, Wonil; Seto, Edmund; Lin, Ken-yu; Migliaccio, Giovanni C. (2017). An Evaluation Of Wearable Sensors And Their Placements For Analyzing Construction Worker’s Trunk Posture In Laboratory Conditions. Applied Ergonomics, 65, 424 – 436.
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Abstract
This study investigates the effect of sensor placement on the analysis of trunk posture for construction activities using two off-the-shelf systems. Experiments were performed using a single-parameter monitoring wearable sensor (SPMWS), the ActiGraph GT9X Link, which was worn at six locations on the body, and a multi-parameter monitoring wearable sensor (MPMWS), the Zephyr BioHarnessTM3, which was worn at two body positions. One healthy male was recruited and conducted 10 experiment sessions to repeat measurements of trunk posture within our study. Measurements of upper-body thoracic bending posture during the lifting and lowering of raised deck materials in a laboratory setting were compared against video-captured observations of posture. The measurements from the two sensors were found to be in agreement during slow-motion symmetric bending activities with a target bending of <= 45. However, for asymmetric bending tasks, when the SPMWS was placed on the chest, its readings were substantially different from those of the MPMWS worn on the chest or under the armpit. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords
Detectors; Construction Workers; Posture; Wearable Technology; Accelerometers; Work-related Injuries; Health; Accelerometer For Inclinometry; Construction Worker; Work-related Musculoskeletal Disorder; Motion Measurement; Position Measurement; Sensor Placement; Upper-body Thoracic Bending Posture Measurements; Trunk Posture Measurements; Zephyr Bioharness 3; Sensor Placement Effect; Construction Worker Trunk Posture Analysis; Wearable Sensor Evaluation; Asymmetric Bending Tasks; Slow-motion Symmetric Bending Activities; Mpmws; Multiparameter Monitoring Wearable Sensor; Actigraph Gt9x Link; Spmws; Single-parameter Monitoring Wearable Sensor; Low-back-pain; Physical-activity Assessment; Risk-factors; Musculoskeletal Disorders; Reliability; Movements; Validity; System; Gt3x+accelerometer
Liang, Huakang; Lin, Ken-yu; Zhang, Shoujian. (2018). Understanding The Social Contagion Effect Of Safety Violations Within A Construction Crew: A Hybrid Approach Using System Dynamics And Agent-based Modeling. International Journal Of Environmental Research And Public Health, 15(12).
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Abstract
Previous research has recognized the importance of eliminating safety violations in the context of a social group. However, the social contagion effect of safety violations within a construction crew has not been sufficiently understood. To address this deficiency, this research aims to develop a hybrid simulation approach to look into the cognitive, social, and organizational aspects that can determine the social contagion effect of safety violations within a construction crew. The hybrid approach integrates System Dynamics (SD) and Agent-based Modeling (ABM) to better represent the real world. Our findings show that different interventions should be employed for different work environments. Specifically, social interactions play a critical role at the modest hazard levels because workers in this situation may encounter more ambiguity or uncertainty. Interventions related to decreasing the contagion probability and the safety-productivity tradeoff should be given priority. For the low hazard situation, highly intensive management strategies are required before the occurrence of injuries or accidents. In contrast, for the high hazard situation, highly intensive proactive safety strategies should be supplemented by other interventions (e.g., a high safety goal) to further control safety violations. Therefore, this research provides a practical framework to examine how specific accident prevention measures, which interact with workers or environmental characteristics (i.e., the hazard level), can influence the social contagion effect of safety violations.
Keywords
Risk-taking; Coworker Support; Employee Safety; Job Demands; Work Groups; Behavior; Climate; Impact; Performance; Simulation; Social Contagion Effect; Routine Safety Violations; Situational Safety Violations; System Dynamics; Agent-based Simulation; Research; Violations; Modelling; Accident Prevention; Social Factors; Safety; Organizational Aspects; Occupational Safety; Construction; Influence; Construction Accidents & Safety; Workers; Safety Management; Information Processing; Construction Industry; Hybrid Systems; Social Interactions; Cognitive Ability; Human Error; Accident Investigations
Liang, Huakang; Lin, Ken-yu; Zhang, Shoujian; Su, Yikun. (2018). The Impact Of Coworkers’ Safety Violations On An Individual Worker: A Social Contagion Effect Within The Construction Crew. International Journal Of Environmental Research And Public Health, 15(4).
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Abstract
This research developed and tested a model of the social contagion effect of coworkers' safety violations on individual workers within construction crews. Both situational and routine safety violations were considered in this model. Empirical data were collected from 345 construction workers in China using a detailed questionnaire. The results showed that both types of safety violations made by coworkers were significantly related to individuals' perceived social support and production pressure. Individuals' attitudinal ambivalence toward safety compliance mediated the relationships between perceived social support and production pressure and both types of individuals' safety violations. However, safety motivation only mediated the effects of perceived social support and production pressure on individuals' situational safety violations. Further, this research supported the differences between situational and routine safety violations. Specifically, we found that individuals were more likely to imitate coworkers' routine safety violations than their situational safety violations. Coworkers' situational safety violations had an indirect effect on individuals' situational safety violations mainly through perceived social support and safety motivation. By contrast, coworkers' routine safety violations had an indirect effect on individuals' routine safety violations mainly through perceived production pressure and attitudinal ambivalence. Finally, the theoretical and practical implications, research limitations, and future directions were discussed.
Keywords
Health-care Settings; Job Demands; Attitudinal Ambivalence; Industry Development; Workplace Safety; Behavior; Climate; Model; Risk; Employee; Social Contagion; Situational Safety Violations; Routine Safety Violations; Social Learning; Social Information Processing
Lin, Ken-yu; Lee, Wonil; Azari, Rahman; Migliaccio, Giovanni C. (2018). Training Of Low-literacy And Low-english-proficiency Hispanic Workers On Construction Fall Fatality. Journal Of Management In Engineering, 34(2).
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Abstract
The construction industry has made extensive efforts to improve the safety of its labor force through various approaches, including training. However, many construction workers in the United States are recent immigrants who lack English proficiency and do not possess sufficient literacy levels in their own language for training comprehension. This reduces the effectiveness of traditional text-dominated translated training materials, which depend on both literacy and proficiency in a language. Thus, in this study, the authors used three-dimensional (3D) visualization to overcome the communication barriers that hinder effective safety training for low-literacy (LL) and low-English-proficiency (LEP) construction workers. This article summarizes the contributions of a study sponsored by the Occupational Safety and Health Administration (OSHA) Susan Harwood Training Grant Program; it describes the methodology to develop scenario-based 3D training materials on fall safety for LL and LEP workers and to validate the effectiveness of the materials. The results show that 3D training materials improve interaction between trainer and trainee during safety training, facilitate learning processes, and can overcome some of the communication barriers that hinder effective safety training. (c) 2017 American Society of Civil Engineers.
Keywords
Chemical Hazards; Computer Based Training; Construction Industry; Hazardous Materials; Industrial Training; Occupational Health; Occupational Safety; Personnel; Safety; Low-literacy; Low-english-proficiency Hispanic Workers; Construction Fall Fatality; Extensive Efforts; Labor Force; Construction Workers; English Proficiency; Sufficient Literacy Levels; Training Comprehension; Training Materials; Three-dimensional Visualization; Communication Barriers; Effective Safety Training; Health Administration Susan Harwood Training Grant Program; Fall Safety; Occupational Injuries; United-states; Industry; Health; Education; Issues; Occupational Health And Safety; Training; Visualization; Fall Protection; Case Study
Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.
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Abstract
This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.
Keywords
Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis