ReviewJMIR human factors2022
Strategic Guidance and Technological Solutions for Human Resources Management to Sustain an Aging Workforce: Review of International Standards, Research, and Use Cases.
Review in JMIR human factors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 34 citations in OpenAlex.
- Shared Failures: Uniting Four Career Pathways to Overcome Decentralized Wastewater Workforce Challenges in Limited-Resource Rural Communities.ACS ES&T water · 2025Article
- Remote Work, Well-Being, and Healthy Labor Force Participation Among Older Adults: A Scoping Review.International journal of environmental research and public health · 2025Article
- Work performance of middle-aged and elderly employees in hotel industry: the moderating effects of organizational support and age discrimination.Frontiers in psychology · 2025Article
- Exploring the Landscape of Standards and Guidelines in AgeTech Design and Development: Scoping Review and Thematic Analysis.JMIR aging · 2024Article
- Public management approaches to an aging workforce: organizational strategies for strategies for adaptability and efficiency.Frontiers in psychology · 2024Article
- Optimizing Nursing Productivity: Exploring the Role of Artificial Intelligence, Technology Integration, Competencies, and Leadership.Journal of nursing management · 2024Article
- Research agenda for using artificial intelligence in health governance: interpretive scoping review and framework.BioData mining · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNew technologies offer opportunities to create a healthy, productive, and capable aging workforce. There is little research from an organizational perspective about how technology can help create a sustainable aging workforce.
objectiveThis study aims to (1) explore how technological solutions in organizations can help create and maintain a healthy, productive, and capable aging workforce; and (2) provide recommendations and strategic guidance that benefit both the aging worker and the organization.
methodsInternational standardization practices, ethical frameworks, collaborative research, and use cases are used to demonstrate how technological solutions can be translated into practice and formed the basis for the development of a set of recommendations to create and maintain a sustainable aging workforce.
resultsOrganizations need to look at aging through different lenses to optimize an age-inclusive workforce rather than viewing it by chronological age alone. International standards in technology, human resources management, and aging societies can form part of the solution to improve aging workforces. Digitalization of workplaces, digital literacy, innovation, intergenerational collaboration, and knowledge management form important elements of the international standard on age-inclusive workforce. Using internationally agreed ethical frameworks that consider age bias when designing artificial intelligence-related products and services can help organizations in their approach. Age bias in artificial intelligence development in the workplace can be avoided through inclusive practices. No blockchain application was found yet to improve the aging workforce. Barriers to blockchain adoption include fear of layoffs, worker resistance and lack of blockchain competence, worldwide adoption, support, and funding. Integrating blockchain into the internet of things may allow for improved efficiencies, reduce cost, and resolve workforce capacity problems. Organizations could benefit from implementing or funding wearable technologies for their workers. Recent tools such as the Ageing@Work toolkit consisting of virtual user models and virtual workplace models allow for the adaptation of the work processes and the ergonomics of workplaces to the evolving needs of aging workers. Lastly, selected use cases that may contribute to sustaining an aging workforce are explored (eg, the Exposure-Documentation-System, wireless biomedical sensors, and digital voice notes).
conclusionsThe synergy of international standardization and ethical framework tools with research can advance information and communication technology solutions in improving aging workforces. There appears to be a momentum that technological solutions to achieve an age-inclusive workforce will undoubtedly find a stronger place within the global context and is most likely to have increased acceptance of technological applications among aging workers as well as organizations and governments. International standardization, cross-country research, and learning from use cases play an important role to ensure practical, efficient, and ethical implementation of technological solutions to contribute to a sustainable aging workforce.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.