What happens when flow ends? How and why your creativity is limited after a flow experience
Bibliographic record
Abstract
Flow is touted for the enjoyment it provides and for its relationship with concurrent task performance. But what happens when flow ends, and you move on to your next task? Our research demonstrates that there is a cost to being in flow in this regard. Specifically, the findings of three studies with 746 participants demonstrate that a person who just experienced flow carries forward a figurative tunnel vision which limits their creativity. This is important because flow can happen throughout daily life and can thus impair many creative tasks. In fact, our findings demonstrate that common activities can elicit a flow state that produces the effect on multiple subsequent tasks. Specifically, participants who experienced flow while playing video games in Study 1 were less creative in their subsequent two tasks compared to those who did not experience flow. This finding was replicated in Study 2 with a new flow inducing task. Study 2 also confirmed cognitive flexibility as an underlying mechanism wherein flow leads to a reduction in cognitive flexibility. Lastly, Study 3 shows that people can experience flow while shopping online, and if they do, their creativity is impaired in their next task. The negative carry-over effect was not equal for all forms of creativity, however; it consistently limited verbal creativity, but had limited influence on figural creativity. These findings make several theoretical contributions regarding the nature of flow and its consequences, while also providing practical insights for people structuring their day to increase creativity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".