The effect of load on biomechanics of the back and upper limb in a bench to shoulder lift during the WorkHab Functional Capacity Evaluation

Technological interventions in functional capacity evaluations: An insight into current applications

BACKGROUND

Functional Capacity Evaluation (FCE) is a crucial component within return-to-work decision making. However, clinician-based physical FCE interpretation may introduce variability and biases. The rise of technological applications such as machine learning and artificial intelligence, could ensure consistent and precise results.

OBJECTIVE

This review investigates the application of information and communication technologies (ICT) in physical FCEs specific for return-to-work assessments.

METHODS

Adhering to the PRISMA guidelines, a search was conducted across five databases, extracting study specifics, populations, and technological tools employed, through dual independent reviews.

RESULTS

Nine studies were identified that used ICT in FCEs. These technologies included electromyography, heart rate monitors, cameras, motion detectors, and specific software. Notably, although some devices are commercially available, these technologies were at a technology readiness level of 5-6 within the field of FCE. A prevailing trend was the combined use of diverse technologies rather than a single, unified solution. Moreover, the primary emphasis was on the application of technology within study protocols, rather than a direct evaluation of the technology usability and feasibility.

CONCLUSION

The literature underscores limited ICT integration in FCEs. The current landscape of FCEs, marked by a high dependence on clinician observations, presents challenges regarding consistency and cost-effectiveness. There is an evident need for a standardized technological approach that introduces objective metrics to streamline the FCE process and potentially enhance its outcomes.

The highs and lows of lifting loads: SPM analysis of multi-segmental spine angles in healthy adults during manual handling with increased load

Introduction: Manual handling personnel and those performing manual handling tasks in non-traditional manual handling industries continue to suffer debilitating and costly workplace injuries. Smart assistive devices are one solution to reducing musculoskeletal back injuries. Devices that provide targeted assistance need to be able to predict when and where to provide augmentation via predictive algorithms trained on functional datasets. The aim of this study was to describe how an increase in load impacts spine kinematics during a ground-to-platform manual handling task. Methods: Twenty-nine participants performed ground-to-platform lifts for six standardised loading conditions (50%, 60%, 70%, 80%, 90%, and 100% of maximum lift capacity). Six thoracic and lumbar spine segments were measured using inertial measurement units that were processed using an attitude-heading-reference filter and normalised to the duration of the lift. The lift was divided into four phases weight-acceptance, standing, lift-to-height and place-on-platform. Statistical significance of sagittal angles from the six spine segments were identified through statistical parametric mapping one-way analysis of variance with repeated measures and post hoc paired t-tests. Results: Two regions of interest were identified during a period of peak flexion and a period of peak extension. There was a significant increase in spine range of motion and peak extension angle for all spine segments when the load conditions were increased (p < 0.001). There was a decrease in spine angles (more flexion) during the weight acceptance to standing phase at the upper thoracic to upper lumbar spine segments for some condition comparisons. A significant increase in spine angles (more extension) during the place-on-platform phase was seen in all spine segments when comparing heavy loads (>80% maximum lift capacity, inclusive) to light loads (<80% maximum lift capacity) (p < 0.001). Discussion: The 50%-70% maximum lift capacity conditions being significantly different from heavier load conditions is representative that the kinematics of a lift do change consistently when a participant's load is increased. The understanding of how changes in loading are reflected in spine angles could inform the design of targeted assistance devices that can predict where and when in a task assistance may be needed, possibly reducing instances of back injuries in manual handling personnel.

Characterization of upper limb use in health care workers during regular shifts: A quantitative approach based on wrist-worn accelerometers

Despite the high prevalence of upper limb (UL) work-related musculoskeletal disorders (WRMSD) among health care workers (HCWs), little is known about their relationship with exposure to biomechanical risk factors. This study aimed to assess UL activity features under actual working conditions using two wrist-worn accelerometers. Accelerometric data were processed to obtain duration, intensity, and asymmetry of UL use in 32 HCWs during the execution of commonly performed tasks (e.g., patient hygiene, transfer, and meal distribution) within a regular shift. The results show that such tasks are characterized by significantly different patterns of UL use, in particular, higher intensities and larger asymmetries were observed respectively for patient hygiene and meal distribution. The proposed approach appears, thus, suitable to discriminate tasks characterized by different UL motion patterns. Future studies could benefit from the integration of such measures with self-reported workers' perception to elucidate the relationship between dynamic UL movements and WRMSD.

Adjustments in Shoulder and Back Kinematics during Repetitive Palletizing Tasks

Repetitive task performance is a leading cause of musculoskeletal injuries among order-picking workers in warehouses. The repetition of lifting tasks increases the risk of back and shoulder injuries among these workers. While lifting in this industry is composed of loaded and unloaded picking and placing, the existing literature does not address the separate analysis of the biomechanics of the back and shoulder for these events. To that end, we investigated the kinematics of the back and shoulder movements of nine healthy male participants who performed three sessions of a simulated de/palletization task. Their back and shoulder kinematics were sensed using an optical motion capture system to determine the back inclination and shoulder flexion. Comparison of the kinematics between the first and last sessions indicated statistically significant changes in the timings, angles, coordination between the back and shoulder, and moments around the shoulder (p<0.05). The majority of the significant changes were observed during the loaded events, which confirms the importance of the separation of these events for biomechanical analysis. This finding suggests that focusing worker evaluation on the loaded periods can provide important information to detect kinematic changes that may affect musculoskeletal injury risk.

The assessment of heavy work investment: Psychometric properties of the WI-10 on a sample of Israeli workers

BACKGROUND: Heavy Work Investment (HWI) is a construct that covers both positive and negative behaviors characterized by a high investment of time and energy in working (work engagement and workaholism, respectively). In the literature, it has been introduced, recently, the Work-related Inventory (WI-10) that allows evaluating four types of worker, three of which are HWIs: disengaged workaholics, engaged workaholics, engaged workers, and detached workers. OBJECTIVE: This study aims to validate the Hebrew WI-10 on Israeli workers. METHODS: We recruited a convenient sample of 459 workers (about half females and half males) with a mean age of 37.12±10.33. We performed Confirmatory Factor Analysis, convergent and divergent validity analyses. Finally, we calculated the cut-off scores corresponding to high and low workaholism and work engagement. RESULTS: We found support for the 10-item (2 filler) and 2-factor structure (Workaholism and Work Engagement) of the WI-10, as well as for its good psychometric properties. CONCLUSIONS: The WI-10 may be used in future research aimed at disentangling the question about the positive and adverse effects that might be associated with different types of HWI.

Feature Detection and Biomechanical Analysis to Objectively Identify High Exposure Movement Strategies When Performing the EPIC Lift Capacity test

Purpose The Epic Lift Capacity (ELC) test is used to determine a worker's maximum lifting capacity. In the ELC test, maximum lifting capacity is often determined as the maximum weight lifted without exhibiting a visually appraised "high-risk workstyle." However, the criteria for evaluating lifting mechanics have limited justification. This study applies feature detection and biomechanical analysis to motion capture data obtained while participants performed the ELC test to objectively identify aspects of movement that may help define "high-risk workstyle". Method In this cross-sectional study, 24 participants completed the ELC test. We applied Principal Component Analysis, as a feature detection approach, and biomechanical analysis to motion capture data to objectively identify movement features related to biomechanical exposure on the low back and shoulders. Principal component scores were compared between high and low exposure trials (relative to median exposure) to determine if features of movement differed. Features were interpreted using single component reconstructions of principal components. Results Statistical testing showed that low exposure lifts and lowers maintained the body closer to the load, exhibited squat-like movement (greater knee flexion, wider base of support), and remained closer to neutral posture at the low back (less forward flexion and axial twist) and shoulder (less flexion and abduction). Conclusions Use of feature detection and biomechanical analyses revealed movement features related to biomechanical exposure at the low back and shoulders. The objectively identified criteria could augment the existing scoring criteria for ELC test technique assessment. In the future, such features can inform the design of classifiers to objectively identify "high-risk workstyle" in real-time.

Functional Capacity Evaluation Research: Report from the Fourth International Functional Capacity Evaluation Research Meeting

Purpose To summarize progress of functional capacity evaluation (FCE) research based on the proceedings of the Fourth International FCE Research Conference held in Switzerland on September 21 and 22, 2018. Methods A scientific committee identified key issues in FCE research and developed the program including key note presentations, a call for abstracts, and round table discussions over 2 days. Highlights of the presentations and discussions are summarized in this article. Results Seventy-nine participants from 11 countries attended the conference where 10 keynote lectures and 21 abstracts were presented. There was also an open discussion regarding the need for an International FCE clinical practice guideline (CPG), methods for developing such a guideline, and practical next steps. Full program details and abstracts from this Fourth International FCE Research Conference are available from https://www.sar-reha.ch/interessengemeinschaften/ig-ergonomie.html . Conclusions Researchers and clinicians continue to increase the body of knowledge in the FCE field. A major finding of this conference is the diversity across the different FCE protocols and research groups as well as of the different uses of FCE across cultural and social economic systems. Next steps will include exploring the development of an international, interdisciplinary, evidence-based FCE clinical practice guideline by a committee formed at the conference.

What type of worker are you? Work-related Inventory (WI-10): A comprehensive instrument for the measurement of workaholism

BACKGROUND

In literature, there are many instruments for evaluating workaholism; however, they do not have convergent validity, because of the lack of a shared definition of workaholism.

OBJECTIVE

We propose a new instrument for evaluating workaholism and work engagement, namely the Work-related Inventory (WI-10), which is based on Loscalzo and Giannini's (2017) comprehensive definition of workaholism.

METHODS

We developed a pool of 36 items, covering: 1) addiction symptoms; 2) obsessive-compulsive symptoms, and 3) work engagement. Then, we conducted Exploratory and Confirmatory Factor analyses on a sample of 503 Italian workers (165 males, 337 females, one missing; Mean age = 38.26±10.84) aiming to reduce the number of items.

RESULTS

The results showed a 10-items (2 filler) and 2-factor solution: 1) Workaholism and 2) Work Engagement; moreover, the WI-10 has good internal reliability, convergent and divergent validity.

CONCLUSIONS

We found good psychometric properties for the WI-10. We also proposed the cut-off scores for the screening of the four kinds of workers proposed by Loscalzo and Giannini (2017): disengaged workaholics, engaged workaholics, engaged workers, and detached workers. The WI-10 will be useful for both research and preventive and clinical purposes.