Reigniting the Flame: An Exploration of Flow in Surgery
Bibliographic record
Abstract
PURPOSE: Although distress and burnout in medical practice are widely acknowledged, less attention has been paid to the positive experiences that help keep physicians engaged. Cognitive flow (being "in the zone") is an intrinsically rewarding state in which individuals feel challenged and focused. To date, academic investigations of flow have largely been limited to the cognitive aspects of the phenomenon, limiting understanding of other elements, such as practice culture and environment. This study examines flow in surgical practice through a multifaceted lens. METHOD: Guided by a constructivist grounded theory approach, semistructured interviews were conducted from June 2018 to May 2021 with staff surgeons at the University of Toronto. Purposive sampling was used to include a range of surgical disciplines and experience levels to produce a conceptual framework that captures the multifaceted experience of flow. RESULTS: Twenty staff surgeons from diverse specialties participated. A conceptual framework was developed for illustrating the different facets of flow, including the traditional view (cognitive) and an expanded view (physiologic, physical, affective, social, cultural, and environmental facets). Through the cognitive lens, participants appreciated how they could achieve the necessary mindset to experience flow and enjoy their work. The ability to feel in control, use creative approaches to solve problems, and possess the agency to continue to learn and improve invoked positive feelings about their work and practice. In the expanded view, it became evident that experiences of flow were much more multifaceted and complex. Beyond the individual, aspects such as the sociocultural environment shaped and comprised key aspects of the flow experience that surgeons found truly meaningful in their practice. CONCLUSIONS: Appreciating flow as a multifaceted phenomenon may assist in the identification and optimization of experiences that are central to encouraging lifelong career advancement and innovation while also helping protect against burnout and distress.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".