Applied Ergonomics最新文献

Work-related musculoskeletal disorder of upper extremity multi-task assessment methods (Revised Strain Index [RSI], Distal Upper Extremity Tool [DUET]) and manual handling multi-task assessment methods (Revised NIOSH Lifting Equation [RNLE], Lifting Fatigue Failure Tool [LiFFT]) were compared. RSI and DUET showed a strong correlation (r_s = 0.933, p < 0.001) where increasing risk factor exposure resulted in increasing outputs for both methods. RSI and DUET demonstrated fair agreement (κ = 0.299) in how the two methods classified outputs into risk categories (high, moderate or low) when assessing the same tasks. The RNLE and LiFFT showed a strong correlation (r_s = 0.903, p = 0.001) where increasing risk factor exposure resulted in increasing outputs, and moderate agreement (κ = 0.574) in classifying the outputs into risk categories (high, moderate or low) when assessing the same tasks. The multi-task assessment methods provide consistent output magnitude rankings in terms of increasing exposure, however some differences exist between how different methods classify the outputs into risk categories.

Sterile Processing Departments (SPDs) must clean, maintain, store, and organize surgical instruments which are then delivered to Operating Rooms (ORs) using a Courier Network, with regular coordination occurring across departmental boundaries. To represent these relationships, we utilized the Systems Engineering Initiative for Patient Safety (SEIPS) 101 Toolkit, which helps model how health-related outcomes are affected by healthcare work systems. Through observations and interviews which built on prior work system analyses, we developed a SEIPS 101 journey map, PETT scan, and tasks matrices to represent the instrument reprocessing work system, revealing complex interdependencies between the people, tools, and tasks occurring within it. The SPD, OR and Courier teams are found to have overlapping responsibilities and a clear co-dependence, with critical implications for the successful functioning of the whole hospital system.

The increased adoption of digital systems in the maritime domain has led to concerns about cyber resilience, especially in the wake of increasingly disruptive cyber-attacks. This has seen vessel operators increasingly adopt Maritime Security Operation Centers (M-SOCs), an action in line with one of the cyber resilience engineering techniques known as adaptive response, whose purpose is to optimize the ability to respond promptly to attacks. This research sought to investigate the domain-specific human factors that influence the adaptive response capabilities of M-SOC analysts to vessel cyber threats. Through collecting interview data and subsequent thematic analysis informed by grounded theory, cyber awareness of both crew onboard and vessel operators emerged as a pressing domain-specific challenge impacting M-SOC analysts' adaptive response. The key takeaway from this study is that vessel operators remain pivotal in supporting the M-SOC analysts’ adaptive response processes through resource allocation towards operational technology (OT) monitoring and cyber personnel staffing onboard the vessels.

Motor vehicle crashes (MVCs) are a leading cause of death for law enforcement officers (LEOs) in the U.S. LEOs and more specifically novice LEOs (nLEOs) are susceptible to high cognitive workload while driving which can lead to fatal MVCs. The objective of this study was to develop a machine learning algorithm (MLA) that can estimate cognitive workload of LEOs while performing secondary tasks in a patrol vehicle. A ride-along study was conducted with 24 nLEOs. Participants performed their normal patrol operations while their physiological responses such as heartrate, eye movement, and galvanic skin response were recorded using unobtrusive devices. Findings suggested that the random forest algorithm could predict cognitive workload with relatively high accuracy (>70%) given that it was entirely reliant on physiological signals. The developed MLA can be used to develop adaptive in-vehicle technology based on real-time estimation of cognitive workload, which can reduce the risk of MVCs in police operations.

This study investigated the roles of phishing knowledge, cue utilization, and decision styles in contributing to phishing email detection. Participants (N = 145) completed an online email sorting task, and measures of phishing knowledge, email decision styles, cue utilization, and email security awareness. Cue utilization was the only factor that uniquely predicted the capacity to discriminate phishing from genuine emails. Phishing knowledge was associated with greater phishing detection and a bias towards classifying all emails as phishing. A preference for intuitive decision making predicted lower detection of phishing emails, driven by a greater tendency to classify emails as genuine. These findings support the proposition that cue utilization is a distinct cognitive process that enables expert performance. The outcomes indicate that, in addition to increasing phishing knowledge and developing safe behavioral patterns, anti-phishing training needs to provide opportunities for trainees to develop meaningful cue associations.

Artificial lighting, which profits from the non-visual effects of light, is a potentially promising solution to support residents’ psychophysiological health and performance at specific times of the day in enclosed environments. However, few studies have investigated the non-visual effects of daytime correlated colour temperature (CCT) and its exposure timing on human alertness, cognition, and mood. However, the neural mechanisms underlying these effects are largely unknown. The current study evaluated the effects of daytime CCT and its exposure timing on markers of subjective experience, cognitive performance, and cerebral activity in a simulated enclosed environment. Forty-two participants participated a single-blind laboratory study with a 4 within (CCT: 4000 K vs. 6500 K vs. 8500 K vs. 12,000 K) × 2 between (exposure timing: morning vs. afternoon) mixed design. The results showed time of the day dependent benefits of the daytime CCT on subjective experience, vigilant attention, response inhibition, working memory, emotional perception, and risk decisions. The results of the electroencephalogram (EEG) revealed that lower-frequency EEG bands, including theta, alpha, and alpha-theta, were quite sensitive to daytime CCT intervention, which provides a valuable reference for trying to establish the underlying mechanisms that support the performance-enhancement effects of exposure to CCT in the daytime. However, the results revealed no consistent intervention pattern across these measurements. Therefore, future studies should consider personalised optimisation of daytime CCT for different cognitive demands.

Objective

To describe implementation strategies for preventive health measures in SMEs and the effectiveness of the strategies on implementation outcomes.

Methods

A literature search was performed in multiple electronic databases. Studies published between 2000 and 2021 that evaluated the implementation of preventive health measures in SMEs were included. Classification of implementation strategies was based on two complementary classification systems.

Results

Nineteen studies, of which 5 RCTs were included. Eighteen distinct implementation strategies were reported. All studies applied a combination of implementation strategies, and nearly all reported a positive effect on one or more implementation outcomes: sustainability, acceptability, feasibility, penetration, fidelity, adoption, and appropriateness.

Conclusions

Overall, a positive effect of combined implementation strategies on the implementation outcome(s) was found. The ‘distribution of educational materials’ and ‘provide ongoing consultation’ combined show positive effects on sustainability.

The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup. 120 participants realized a simple and a complex assembly task. 50% collaborated with another human (H/H) and 50% with a cobot (H/C). The workload and the acceptability of the cobotic collaboration were measured. Working with a cobot decreases the effect of the task complexity on the human workload and on the output quality. However, it increases the time completion and the number of gestures (while decreasing their frequency). The H/C couples have a higher chance of success but they take more time and more gestures to realize the task. The results of this research could help developers and stakeholders to understand the impacts of implementing a cobot in production chains.

Background

Load carriage imposes high physical stresses on the human body, increasing the risk of injuries. This study assessed the effectiveness of a passive military exoskeleton in off-loading the weight placed on the body during heavy load carriage under static standing and dynamic walking conditions.

Methods

Eight full-time regular personnel of the Singapore Armed Forces enrolled in the study. Static loading tests included nine trials of 10-s quiet standing while carrying different loads (0–55 kg) with and without the exoskeleton. For dynamic loading, participants walked on a treadmill on flat, inclined, and declined surfaces while carrying two different loads (25 kg, 35 kg) with and without the exoskeleton. In-shoe normal ground reaction forces (GRF) were recorded during quiet standing and treadmill walking. Differences in total force with and without the exoskeleton during static loading were compared using Wilcoxon one-sample signed ranked tests against zero (no weight off-load) as a reference. Statistical parametric mapping test was used to compare the walking in-shoe GRF-time series with and without exoskeleton use for each load and surface condition.

Results

Exoskeleton use was effective in off-loading loads of 2.3–13.5 kg during static quiet standing but the response varied substantially across loads and among the participants. Statistical analysis revealed no meaningful differences in the walking in-shoe GRF with and without exoskeleton use. The results were largely consistent across flat, inclined, and declined surfaces, and both 25-kg and 35-kg loads.

Conclusions

The passive military exoskeleton was effective in off-loading some load from the human body during static quiet standing but not dynamic walking on flat and sloped surfaces. The varied response across loads and participants calls for better design and fitting of the military exoskeleton to individual users.

Background

Digital health (DH) brings considerable benefits, but it comes with potential risks. Human Factors (HF) play a critical role in providing high-quality and acceptable DH solutions. Consultation with designers is crucial for reflecting on and improving current DH design practices.

Objectives

We investigated the general DH design processes, challenges, and corresponding strategies that can improve the digital patient experience (PEx).

Methods

A semi-structured interview study with 24 design professionals. All audio recordings were transcribed, deidentified, grammatically corrected, and imported into ATLAS.ti for data analysis. Three coders participated in data coding following the thematic analysis approach.

Results

We identified eight DH design stages and grouped them into four phases: preparation, problem-thinking, problem-solving, and implementation. The analysis presented twelve design challenges associated with contextual, practical, managerial, and commercial aspects that can hinder the design process. We identified eight common strategies used by respondents to tackle these challenges.

Conclusions

We propose a Digital Health Design (DHD) framework to improve the digital PEx. It provides an overview of design deliverables, activities, stakeholders, challenges, and corresponding strategies for each design stage.