Effect of Harm Anchors in Visual Displays of Test Results on Patient Perceptions of Urgency About Near-Normal Values: Experimental Study
Bibliographic record
Abstract
BACKGROUND: Patient-facing displays of laboratory test results typically provide patients with one reference point (the "standard range"). OBJECTIVE: To test the effect of including an additional harm anchor reference point in visual displays of laboratory test results, which indicates how far outside of the standard range values would need to be in order to suggest substantial patient risk. METHODS: Using a demographically diverse, online sample, we compared the reactions of 1618 adults in the United States who viewed visual line displays that included both standard range and harm anchor reference points ("Many doctors are not concerned until here") to displays that included either (1) only a standard range, (2) standard range plus evaluative categories (eg, "borderline high"), or (3) a color gradient showing degree of deviation from the standard range. RESULTS: Providing the harm anchor reference point significantly reduced perceived urgency of close-to-normal alanine aminotransferase and creatinine results (P values <.001) but not generally for platelet count results. Notably, display type did not significantly alter perceptions of more extreme results in potentially harmful ranges. Harm anchors also substantially reduced the number of participants who wanted to contact their doctor urgently or go to the hospital about these test results. CONCLUSIONS: Presenting patients with evaluative cues regarding when test results become clinically concerning can reduce the perceived urgency of out-of-range results that do not require immediate clinical action.
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".