Bibliographic record
Abstract
This article is the report of the development and validation of a tailored Web-based intervention for postoperative pain self-management in adults who underwent cardiac surgery. The development of SOULAGE-TAVIE included four main phases: (1) identification of a clinical problem, (2) outline design, (3) clinical operationalization, and (4) production. The validation of the intervention's feasibility and acceptability was made through pilot testing with 30 patients expecting cardiac surgery over 4 months in 2010. SOULAGE-TAVIE consists of a 30-minute computer-tailored preoperative educational session about postoperative pain management. Activities and information were tailored according to a predetermined profile. Two short reinforcements were provided in person postoperatively. Ninety-six percent of participants agreed that the strategies proposed responded to their needs. An iterative process among various sources of knowledge gave place to an innovative approach to preoperative education. Pilot testing provided preliminary support for the acceptability and feasibility of a tailored Web-based intervention. Patient empowerment is complementary yet crucial in the current context of care and may contribute to improved pain relief. The use of information technologies can increase personalization and accessibility to health education in a complex environment of care.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".