Does decision fatigue mainly make people use less effortful strategies rather than make more mistakes, and how do studies tell these apart?

Why fatigue shows up as a change in strategy, not a spike in errors

Decision fatigue is defined as a gradual shift toward decisions that are less cognitively effortful as a person makes many decisions without a break [1][2]. The key word is 'shift': the person does not necessarily start making more mistakes; instead, they gravitate toward options that demand less mental work. For example, in a study of Australian general practitioners, as the workday progressed, doctors became more likely to prescribe antibiotics—a quick, low-effort choice—and less likely to prescribe statins or osteoporosis medications, which require more effort to assess and discuss [1].

This pattern is consistent with a strategy change rather than a simple error increase. If fatigue merely caused more mistakes, you would expect random increases in all kinds of prescribing errors. Instead, the direction of change depended on how effortful each decision was: easy options became more likely, effortful ones less likely [1].

How studies tell a strategy shift from a mistake increase

Researchers distinguish the two by first classifying each decision option as more or less effortful, then testing whether the likelihood of choosing the less effortful option rises over the workday. In the GP prescribing study, antibiotics were classified as less effortful to prescribe (frequently overprescribed), while statins and osteoporosis medications were classified as more effortful (frequently underprescribed). The hypothesis was that fatigue would increase the former and decrease the latter—and that is what the data showed for antibiotics, statins, and osteoporosis medications [1].

A second study applied the same logic to referrals and test ordering, but had to justify the effort level for each decision context. For instance, ordering imaging for back complaints was considered less effortful than providing lengthy self-management advice, so the prediction was that imaging orders would increase with fatigue. Conversely, ordering lipid screening tests—which have future benefit but no immediate need—was considered more effortful, so the prediction was that such orders would decrease [2]. By making these directional predictions in advance, the studies can test whether fatigue shifts choices toward easier options, rather than just looking for any change in error rates.

What the evidence shows—and what it doesn't

The prescribing study found that the odds of prescribing antibiotics increased by 8.7% with every 15 additional patient encounters, while the odds of prescribing statins decreased by 21.9% and osteoporosis medications by 25.0% [1]. These changes are consistent with a shift toward less effortful decisions. However, the study did not measure whether these prescribing choices were correct or incorrect—so it cannot say whether mistakes increased. The same limitation applies to the referral and test-ordering study, which defines decision fatigue as a shift toward less effortful choices but does not explore whether errors also rise [2].

A qualitative study of doctors and nurse practitioners working long shifts found that healthcare workers are aware of decision fatigue effects and deliberately use strategies to keep their decision quality stable [4]. This suggests that people may consciously compensate for fatigue, which could further blur the line between strategy shifts and actual errors. The study did not directly compare error rates, but it highlights that decision-making quality is influenced by many factors beyond fatigue alone.

Why the distinction matters for real-world decisions

If decision fatigue mainly changes strategy rather than causing outright mistakes, then interventions should focus on making effortful choices easier or reducing the number of decisions, rather than simply telling people to 'try harder' or 'make fewer errors.' The GP prescribing study concludes that decision fatigue is a promising target for optimizing prescribing behavior [1]. Similarly, the referral study argues that understanding how fatigue shifts decisions can help design better workflows [2].

However, because the evidence so far comes from observing shifts in decision patterns rather than measuring error rates directly, it remains possible that some of these shifts do lead to worse outcomes. The studies are consistent with a strategy-shift explanation, but they do not rule out that mistakes also increase. Future research that directly measures both the effortfulness of chosen options and the correctness of those choices would help settle the question.

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