Evidence about tele-oncology applications and associated benefits for patients and their families
Bibliographic record
Abstract
We conducted a systematic review of evidence on the ability of tele-oncology applications to improve access to care closer to home for adult rural patients affected by cancer. From 269 publications identified in the literature search, 54 studies met our inclusion criteria. Forty two were clinical studies (32 quantitative, eight qualitative and two that included both quantitative and qualitative methodology). Strength of evidence from quantitative clinical studies was assessed using an approach that takes account of both study design and study quality. Qualitative studies were appraised by giving scores for six areas of interest. In terms of the continuum of cancer care, the most common study area was psychosocial and supportive care. While there were a number of high quality studies, overall the evidence of benefit from tele-oncology was limited and few investigations had proceeded beyond the stage of establishing feasibility. The literature suggests some useful possibilities for new services to cancer patients in rural areas but it seems likely that these would need validation with suitable local studies.
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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 | 0.028 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".