An Examination of Quality of Life of Children and Parents During Their Tele-HomeCare Experience
Bibliographic record
Abstract
Video-conferencing and remote vital signs monitors were used to provide Tele-HomeCare (THC) to children with complex healthcare needs. This paper reports the effects of THC on the health-related quality of life (QoL) of children and their parents, and the Impact on Families (IoF). A total of 63 children and their parents were enrolled in a THC trial in which they received traditional home care services and up to 6 weeks of THC. A reference group of 16 children and their parents was also recruited and received only traditional home care services. All parents completed QoL questionnaires for both their child and themselves, and the IoF scale. Complete data were available for 50 THC participants: 34 of these had no readmissions and 16 experienced multiple admissions. The reference group contained 10 participants who received standard community care. All three groups experienced similar improvements in quality of life at the time of their discharge to home after which their QoL remained stable. There were no significant differences in the IoF scores. THC is an effective clinical service that supports the transition from hospital to home at a time when the children continued to have complex care needs. Furthermore, improvements in QoL were observed for these families that were similar to those of families whose children had less intensive care needs. Moreover, the improvements were sustained beyond the termination of the THC service and were not associated with additional burden on families.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".