Wearable Exoskeletons on the Workplaces: Knowledge, Attitudes and Perspectives of Health and Safety Managers on the implementation of exoskeleton technology in Northern Italy.
Bibliographic record
Abstract
BACKGROUND: Exoskeleton technology (ExT) has potential to significantly improve occupational health and safety. However, studies on stakeholders' perspectives are lacking. To facilitate the implementation of ExT on the workplaces, a study was undertaken exploring specific knowledge, attitudes and perspectives (KAP) of Health and Safety Consultants (HSC). METHODS: An online survey with quantitative and qualitative components was conducted with HSC participating to a series of qualification courses focusing on new technologies in occupational settings. Respondents rated whether they would use or recommend an exoskeleton, being assessed regarding their knowledge on ExT through a specifically designed knowledge test. Design features (n = 16) and expected benefits (n = 12) were rated and compared in terms of their importance. Regression analysis was used to identify factors significantly affecting the propensity towards the implementation of ExT. RESULTS: A total of 59 HSC participated to the survey (participation rate, 90.8%): of them, 20 (33.9%) were somehow favorable towards the use of ExT on the workplaces. The most highly rated reason for potential use/recommendation of ExT was reducing the stress on joints and tendons (74.6%), followed by reducing muscle fatigue (71.2%). Among design features, higher ratings were identified for: comfort (4.53 ± 0.68), ease of setup (4.37 ± 0.72), portability (4.32 ± 0.97), minimization of falls risk (4.31 ± 0.93), ease of putting on/taking off the device (4.12 ± 1.16), and amount of physical energy needed for use (4.14 ± 0.92). Overall knowledge of ExT was quite low (knowledge score 43.2% ± 18.2), with high rate of false beliefs on the protective role of ExT on musculoskeletal disorders and physical efforts, positive effects on productivity. In multivariate analysis, age < 50 years and being an internal HSC were identified as significant effectors for a positive attitude towards ExT. CONCLUSIONS: This study emphasizes the opportunity to spread better knowledge of actual ExT features among potential stakeholders. Moreover, design of future exoskeleton should focus on devices comfortable, highly portable, ease to setup, with a reduced risk of falls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".