Group-based interventions for caregivers to patients diagnosed with a brain tumor: A systematic review
Bibliographic record
Abstract
Background: Individuals diagnosed with a primary brain tumor often depend on practical assistance and emotional support from family and social network. Supportive care interventions are therefore of importance to informal caregivers. The aim of this review was to identify and explore available evidence of outcomes of supportive group interventions for caregivers to patients diagnosed with a primary brain tumor. Methods: A systematic review was conducted following the PRISMA guidelines. Six databases: PubMed, Embase, Web of Science, Emcare, Cochrane Library, and PsycINFO were searched for peer-reviewed publications. Quality of included publications was assessed by the Mixed-Methods Appraisal Tool and data synthesis followed Guidance on the Conduct of Narrative Synthesis in Systematic Reviews. Results: Five eligible publications were identified, published between 2007 and 2021, originating from Australia, Austria, Canada, Denmark, and Germany. Supportive group interventions for caregivers to patients diagnosed with a primary brain tumor were considered feasible, with outcomes evaluated positively in 5 publications. The group interaction within a supportive intervention created a trusted environment for caregivers to share their experiences. Group interactions represented an essential source of support and information to manage the caregiver role. Shared acknowledgment of their new role boosted caregivers' confidence in their abilities to deliver care. Conclusion: Interventions seeking to facilitate interaction between caregivers may provide an extra supportive resource for the caregivers. Nevertheless, further research is necessary to ascertain the optimal setting, content, and timing for providing caregivers a supportive group intervention.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".