Post-surgical telehealth support for children and family care-givers
Bibliographic record
Abstract
Early discharge of children following surgery shifts the burden of care from professionals in hospital to family care-givers at home. We evaluated the relative effectiveness of telephone and videophone follow-up for children and families after a child's scoliosis surgery. Fourty-three patients and their families were enrolled in the study with 21 dyads receiving videophone and 22 dyads telephone support. At discharge, those in the intervention arm were provided with a videophone operating on the ordinary telephone network (PSTN). Data were gathered during telehealth contact on post-discharge day 3 and during extra calls with the clinic nurse, and during sessions with a research assistant comprising a follow-up call and an interview at the six-week post-surgical visit. Calls and interviews were recorded and transcribed. Data were analysed using constant comparative analysis. The results showed that videophone and telephone use provided care continuity for patients and their families following a child's back surgery. The relative effect of the videophone and telephone technology depended on the fit between the characteristics of the patients and families and the capacities of the technology. When implementing telehealth for follow-up care, a participatory process is recommended to ensure a fit between user characteristics and technology.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".