The information needs of relatives of childhood cancer patients and survivors: A systematic review of quantitative evidence
Bibliographic record
Abstract
OBJECTIVE: We aimed to: (1) summarize the quantitative evidence on the information needs of relatives of childhood cancer patients, survivors, and children deceased from cancer; and (2) identify factors associated with these needs. METHODS: PubMed, PsycINFO, Scopus, and CINAHL were systematically searched. The methodological quality of all included publications was assessed, and the extracted data were analyzed using narrative synthesis. RESULTS: Of 5810 identified articles, 45 were included. Information needs were classified as unmet, met (satisfied), and unspecified and categorized into five domains: medical information, cancer-related consequences, lifestyle, family, and support. Most unmet information needs concerned cancer-related consequences (e.g., late effects), while information needs on support were generally met. Migrant background and higher education were associated with higher information needs among parents. Siblings had lower information needs than parents. CONCLUSION: This systematic review provides a comprehensive overview of the information needs of relatives in the context of childhood cancer, showing that information on cancer-related consequences is needed most often. The socioeconomic background of the relatives needs continued consideration throughout the cancer trajectory. PRACTICE IMPLICATIONS: Our findings suggest the need for personalized information. Healthcare professionals should adapt their communication strategies to respond to the different and evolving needs of all affected relatives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".