Web-Based Tailored Intervention for Preparation of Parents and Children for Outpatient Surgery (WebTIPS)
Bibliographic record
Abstract
BACKGROUND: As a result of cost-containment efforts, preparation programs for outpatient surgery are currently not available to the majority of children and parents. The recent dramatic growth in the Internet presents a unique opportunity to transform how children and their parents are prepared for surgery. In this article, we describe the development of a Web-based Tailored Intervention for Preparation of parents and children undergoing Surgery (WebTIPS). DEVELOPMENT OF PROGRAM: A multidisciplinary taskforce agreed that a Web-based tailored intervention consisting of intake, matrix, and output modules was the preferred approach. Next, the content of the various intake variables, the matrix logic, and the output content was developed. The output product has a parent component and a child component and is described in http://surgerywebtips.com/about.php. The child component makes use of preparation strategies such as information provision, modeling, play, and coping skills training. The parent component of WebTIPS includes strategies such as information provision, coping skills training, and relaxation and distraction techniques. A reputable animation and Web design company developed a secured Web-based product based on the above description. CONCLUSIONS: In this article, we describe the development of a Web-based tailored preoperative preparation program that can be accessed by children and parents multiple times before and after surgery. A follow-up article in this issue of Anesthesia & Analgesia describes formative evaluation and preliminary efficacy testing of this Web-based tailored preoperative preparation program.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".