The Enhancing Life Research Laboratory: Tools for Addressing Orientational Distress in the Medical Profession
Bibliographic record
Abstract
PURPOSE: To explore distress in the medical profession and how it was highlighted by the ongoing COVID-19 pandemic. The term "orientational distress" was developed to name the experience of a breakdown in the patterns of moral self-understanding and one's capacity to navigate professional responsibilities. METHOD: The Enhancing Life Research Laboratory at the University of Chicago convened a 5-session online workshop (total 10 hours, May-June 2021) to explore orientational distress and to promote collaboration between academics and physicians. Sixteen participants from Canada, Germany, Israel, and the United States engaged in discussions of the conceptual framework and toolkit to address orientational distress within institutional settings. The tools included 5 dimensions of life, 12 dynamics of life, and the role of counterworlds. Follow-up narrative interviews were transcribed and coded using a consensus-based iterative process. RESULTS: Participants reported that the concept of orientational distress helped explain their professional experiences better than burnout or moral distress. Moreover, participants strongly endorsed the project's supporting thesis that collaborative work on orientational distress and the tools provided in the research laboratory had a specific intrinsic value and provided benefits not found in other support instruments. CONCLUSIONS: Orientational distress compromises medical professionals and threatens the medical system. Next steps include the dissemination of materials from the Enhancing Life Research Laboratory to more medical professionals and medical schools. In contrast to burnout and moral injury, the concept of orientational distress may better enable clinicians to understand and more fruitfully navigate the challenges of their professional situations.
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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 | 0.030 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".