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Predicting polytomous career choices in healthcare using probabilistic expectations data

Authors: Schweri, Jürg;

Predicting polytomous career choices in healthcare using probabilistic expectations data

Abstract

Summary This paper compares the career expectations and outcomes of Swiss healthcare assistants, an occupation created to increase the supply of new nurses. We investigate whether healthcare assistants can predict their own professional careers two years ahead by eliciting their expectations for a range of career alternatives, including nursing and other studies. Polytomous choice situations have rarely been analyzed using numerical probabilities in the expectations literature. Our results show that almost all respondents gives informative answers. Individuals express considerable uncertainty about their future careers, with over 60 percent expressing varying degrees of uncertainty. The analyses reveal that individuals’ numerical expectations have considerable predictive value for their future careers, even after controlling for a host of variables, but that predicted shares for career alternatives are more accurate over four years than over two years. The information conveyed in numerical expectations and their deviations from actual outcomes enables us to derive policy recommendations to increase transitions to nursing.

Keywords

Discrete choice, Medical workforce, Healthcare, Nursing, FOS: Health sciences, Subjective expectations, Career choice

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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