When algorithms manage care: Nurses’ autonomy and job happiness across contexts
Keywords:
Algorithmic management; digital rostering; nurses; job happiness; autonomy; well-being; comparative study; healthcare managementAbstract
The growing integration of algorithmic management in healthcare has changed the organisational setting of nursing duties, particularly shift scheduling and performance monitoring. Although algorithmic rostering and task allocation are frequently implemented to enhance efficiency and equity, their impact on nurses' autonomy, well-being, and job happiness is still debated. This research conducts a thorough literature analysis of studies published from 2020 to 2025, analysing the impact of algorithmic management on nurses' job experiences in various national contexts. In accordance with PRISMA principles, seventy peer-reviewed publications were obtained from prominent databases, including Scopus, Web of Science, and PubMed. The research delineates distinct disparities in outcomes across early adopters, including the United Kingdom, the Netherlands, Singapore, South Korea, and Australia. Evidence indicates that the influence of algorithmic management is significantly contingent upon contextual elements, including legislative frameworks, organisational support, and cultural attitudes towards digital technologies. In many instances, algorithms enhanced transparency and diminished perceived bias in scheduling, thereby fostering job happiness; conversely, in other circumstances, they curtailed professional autonomy, escalated workload pressure, and eroded trust. This comparative synthesis offers theoretical and practical insights into the circumstances in which algorithmic management might improve, rather than diminish, nurses' job happiness. The analysis finishes by delineating implications for healthcare executives, international policymakers, and prospective research on technology-enhanced nursing practices.
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