Impact of a cancer diagnosis on the income of adult cancer survivors: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: While the socioeconomic impact of a cancer diagnosis on cancer survivors has gained some attention in the literature, to our knowledge, a review of the evidence on changes in income due to cancer has yet to be undertaken. In this paper, we describe a scoping review protocol to review the evidence on the effect of a cancer diagnosis on the income of individuals diagnosed with cancer during adulthood (≥18 years). The purpose is to summarise existing evidence, identify gaps in current research and highlight priority areas for future research. METHODS AND ANALYSIS: This study will follow the methodological framework for conducting scoping reviews by the Joanna Briggs Institute In collaboration with a health science librarian, we developed a search strategy to be performed in Ovid MEDLINE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, EMBASE, Econ-Literature and Evidence-Based Medicine Reviews. This scoping review will search the scientific literature published in English from 1 January 2000 to 31 December 2020. Studies that measured the impact of cancer on income of adults will be eligible for inclusion. Studies exclusively focused on employment outcomes (eg, return to work, unemployment, productivity loss), financial expenditures, childhood cancer survivors and/or the caregivers of cancer survivors will be excluded. Three independent reviewers will conduct screening and extract data. Descriptive information will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews. ETHICS AND DISSEMINATION: This scoping review will analyse data from publicly available materials and thus does not require ethics approval. Results from this review will be disseminated through a peer-reviewed publication and/or conference presentation with the potential to identify gaps in the literature, suggest strategies for standardised terminology and provide directions for future research.
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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 | 0.124 | 0.111 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.080 | 0.017 |
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".