Eliciting Personhood Within Clinical Practice: Effects on Patients, Families, and Health Care Providers
Bibliographic record
Abstract
CONTEXT: Failure to acknowledge personhood is often the cause of patient and family dissatisfaction. We developed the Patient Dignity Question (PDQ) as a simple means of inquiring about personhood: "What do I need to know about you as a person to give you the best care possible?" OBJECTIVES: This study aimed to evaluate the impact of the PDQ on patients and families, evaluate its influence on health care providers (HCPs), and determine if HCP characteristics mediate receptivity to PDQ-elicited information. METHODS: Palliative care patients or their family members were asked to respond to the PDQ. Responses were summarized, read to participants to ensure accuracy, and with permission, placed in their charts. Patient, family, and HCP responses to the PDQ were then elicited. RESULTS: A total of 126 participants (66 patients and 60 family members) responded to the PDQ; 99% indicated that the summaries were accurate, 97% permitted the summary to be placed in the chart, 93% felt that the information was important for HCPs to know, and 99% would recommend the PDQ for others. A total of 137 HCPs completed 293 evaluations of individual PDQs; 90% indicated that they learned something new from it, 64% that they were emotionally affected by it, 59% that it influenced their sense of empathy, and 44% that it influenced their care. HCP empathy, job satisfaction, having a meaningful life, and social support mediated responsiveness to PDQ-elicited information. CONCLUSION: The PDQ offers an effective way of eliciting personhood, enhancing patient, family, and HCP experience alike.
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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 | 0.081 | 0.201 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".