Bibliographic record
Abstract
Abstract This Critical Synthesis Package contains: (1) a Critical Analysis of the psychometric properties and application to health sciences education for the Decisional Conflict Scale (DCS), and (2) a copy of the DCS instrument, scoring key; and manual developed by Annette O'Connor, PhD, RN. The DCS is meant to identify patients' decisional conflicts regarding a treatment or screening option. The original version has 16 items with five subscales labeled: Informed, Values, Support, Uncertainty, and Effective Decision. Together these items assess decisional uncertainty, as well as social and cognitive variables believed to be important in decision making. The items are scored by participants on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Currently, there are a number of different versions of the DCS: the original 16-item statement-based questionnaire; a modified 16-item statement-based questionnaire; a 16-item question-based version that contains the five subscales that uses a 5-point scale ranging from yes to no; and a low literacy version (DCS-LL) where the questionnaire is reduced to 10 items with a 3-point scale meant to assess four of the original five scales. The fifth and most recent version is a 4-item questionnaire titled SURE and it measures decision making capabilities across four domains of: Sure of myself, Understand information, Risk-benefit ratio, and Encouragement, utilizing a yes/no question format. Total scores from the modified 16-item measure, the 16-item yes/no measure, and the SURE questionnaire versions are used to assess decisional conflicts, while high scores on the original DCS and DCS-LL, as well as scores below four on the SURE indicate decisional conflicts. The SURE version has been recommended for clinical practice and the other four are recommend for research purposes with the statement formatted versions being used in the most studies to date. All versions are easy to implement and score. While there is ample evidence for the reliability of the scores from these instruments, there is still no clear evidence regarding the underlying factor structure. However, this instrument has been used in hundreds of studies with various patient populations and has been validated in a number of languages. While factor structure is an issue, scores do provide foundational evidence for patient decisional conflicts.
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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 | 0.053 | 0.370 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.290 | 0.016 |
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".