Decisional Conflict in Patients and Their Physicians: A Dyadic Approach to Shared Decision Making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Decisional conflict is defined as personal uncertainty about which course of action to take when choice among competing options involves risk, regret, or challenge to personal life values. It is influenced by inadequate knowledge, unclear values, inadequate support, and the perception that an ineffective decision has been made. Until recently, it has been studied at the individual level, which ignores the interpersonal system between patients and physicians. OBJECTIVE: To explore the effect of feeling uninformed, unclear values, inadequate support, and the perception that an ineffective decision has been made on one own's outcome (actor effect) and on the other person's outcome (partner effect). METHODS: After a clinical encounter, modifiable deficits and personal uncertainty were measured in physicians and patients using the Decisional Conflict Scale. Structural equation modeling was used to measure the parameters of the Actor-Partner Interdependence Model. RESULTS: A total of 112 dyads of physicians and patients were included in the analysis. For both patients and physicians, 2 actor effects, unclear values (P < 0:0001) and the perception that an ineffective decision has been made (P < 0:0001), were found to be positively correlated with personal uncertainty. One partner effect, feeling uninformed (P=0:03), was found to be negatively correlated with personal uncertainty. CONCLUSIONS: Personal uncertainty of patients and physicians is influenced not only by their respective deficits but also by the deficits of the other member of the dyad. Our results indicate that the more unclear the expression of their own values and the more they perceive that an ineffective choice had been made, the more both physicians and patients experience personal uncertainty. They also indicate that the less uninformed they feel, the more both physicians and patients experience personal uncertainty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it