Use and impact of virtual resources for peer support by young adults living with cancer: A systematic review
Bibliographic record
Abstract
Background: Young adults (YA) with cancer often have unmet psychosocial needs. The impact of peer support delivered in an online format to fulfil these needs in the populations of YA with cancer has not been thoroughly examined. Methods: We searched Cochrane Central Register of Controlled Trials, CINAHL, Embase, and Medline databases. We included articles about online peer support interventions for YA cancer survivors between the ages of 18 to 40 years old. Results: Our literature search yielded n = 2,773 articles and we obtained consensus on 12 articles for inclusion. We qualitatively synthesized these articles using data abstraction based on the Template for Intervention and Replication (TIDierR) checklist. Overall, six studies demonstrated correlation between online peer support and improved wellbeing of participants. Thus, online peer support may be useful for young cancer patients. Conclusion: This systematic review summarizes the current state of knowledge regarding the availability and evaluation of online YA peer support programs and reveals the need for further research in this field.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 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) | 0.004 | 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".