Impact of Telemedicine Use by Oncology Physicians on the Patient and Informal Caregiver Experience of Receiving Care: Protocol for a Scoping Review in the Context of COVID-19 (Preprint)
Bibliographic record
Abstract
BACKGROUND During the COVID-19 pandemic, the use of telemedicine by oncology physicians in Manitoba, Canada, has increased to limit the risk of exposure to the virus for both patients and health care providers. It is not clear how telemedicine impacts the information needs of patients or the experience of receiving cancer care. OBJECTIVE The objective of this study is to describe how the use of telemedicine impacts the information needs and experience of patients with cancer and their informal caregivers (ie, family and friends) and identify directions for future research. METHODS This review will include all studies addressing telemedicine in the cancer context including those using quantitative, qualitative, and mixed methods approaches. This scoping review will be conducted using the methodology described by the Joanna Briggs Institute. In collaboration with a librarian scientist specializing in health sciences, a comprehensive search will be undertaken to identify and retrieve relevant reports published in English from 1990 to the present. Databases searched will include MEDLINE, CINAHL, EMBASE, Scopus, Cochrane Library, and PsycINFO. Data will be extracted by two independent reviewers, synthesized, and reported in a summary table and in a narrative format describing what has been reported regarding the impact of telemedicine by physicians in oncology on the experience of patients and their informal caregivers and their receipt of information. RESULTS The results from this scoping review are expected to be available by late spring 2021. CONCLUSIONS The results from this scoping review will be useful for informing practice as well as directing future research, both in the context of COVID-19 and beyond. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/25501
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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 | 0.085 | 0.083 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.020 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.009 |
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".