Feasibility of paediatric postoperative telemedicine in Nunavik: A qualitative study
Bibliographic record
Abstract
Objectives: Children from Nunavik, a Northern Quebec region with a predominantly Inuit population, must travel by air for surgical care at urban paediatric centres. Telemedicine offers an opportunity for virtual postoperative visits for low-risk patients, though its feasibility remains unclear. This study aimed to assess the feasibility of paediatric postoperative telemedicine in Nunavik. Methods: This qualitative study (August 2022-June 2023) included a rapid literature review on telemedicine use in rural and postoperative care, which informed the interview process. Eleven healthcare providers with experience caring for Inuit children from Nunavik were interviewed on telemedicine viability. Data was thematically analyzed. Technical and operational feasibility was evaluated using data on Nunavik's resources from the regional health board. The primary outcome was healthcare providers' perspectives on feasibility, and the secondary outcome assessed technical and operational viability through community resources. Results: The literature review yielded few sources. All participants agreed on the feasibility of paediatric postoperative telemedicine but identified key conditions for its success. The thematic analysis highlighted seven themes, including benefits, challenges, patient suitability, and resource requirements. While two regional hospitals and three health centres were equipped to support postoperative telemedicine, nine health centres had only partial capability, primarily due to limited high-speed internet access. Imaging and laboratory services were available solely at regional hospitals. Conclusions: Postoperative telemedicine was deemed feasible from both provider and resource perspectives, with optimal utilization dependent on appropriate support to centres. Family and community involvement is crucial to expanding its use in Nunavik and respecting patient autonomy.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".