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versão impressa ISSN 0012-7353


LAVALLIERE, Martin; BURSTEIN, Arielle A.; AREZES, Pedro  e  COUGHLIN, Joseph F.. Tackling the challenges of an aging workforce with the use of wearable technologies and the quantified-self. Dyna rev.fac.nac.minas [online]. 2016, vol.83, n.197, pp.38-43. ISSN 0012-7353.

The world's population is aging at an unprecedented rate, this demographic shift will change all aspects of life, including work. The aging of the worforce and a higher percentage of workers who will work past traditional retirement years presents significant challenges and opportunities for employers. Older workers are a valuable resource, but in order to ensure they stay in good health, prevention will be key. Wearable technologies are quickly becoming ubiquitous, individuals are turning to them to monitor health, activities and hundreds of other quantifiable occurences. Wearable technologies could provide a new means for employers to tackle the challenges associated with an aging workforce by creating a wide spectrum of opportunities to intervene in terms of aging employees and extend their working lives by keeping them safe and healthy through prevention. Employers are already making standing desks available, and encouraging lunch time exercise, is it feasible for Wearables to make the jump from a tool for individuals to a method for employers to ensure better health, well-being and safety for their employees? The aim of this work is to lay out the implications for such interventions with Wearable technologies (monitoring health and well-being, oversight and safety, and mentoring and training) and challenges (privacy, acceptability, and scalability). While an ageing population presents significant challenges, including an aging work force, this demographic change should be seen, instead, as an opportunity rethink and innovate workplace health and take advantage of the experience of older workers. The Quantified-Self and Wearables can leverage interventions to improve employees' health, safety and well-being.

Palavras-chave : Aging; Health and Safety; Monitoring; Personalized intervention; Big Data.

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