Abstract
The Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, assessing its characteristics is worthwhile. The WAI was distributed online among the employees of a healthcare company; the results were compared with data contained in the employees’ personal health records and with absence registers. A total of 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in their day shift counterparts due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to over-report illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.
Lingua originale | English |
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pagine (da-a) | N/A-N/A |
Rivista | INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES & NATURAL RESOURCES |
Volume | 21 |
DOI | |
Stato di pubblicazione | Pubblicato - 2024 |
Keywords
- ageing
- disability management
- gender differences
- health promotion
- total worker health
- musculoskeletal disorders
- night work
- psychiatric disorders
- psychometrics
- medical surveillance