Psychosocial needs of post-radiotherapy cancer survivors and their direct caregivers – a systematic review
Bibliographic record
Abstract
Radiotherapy is an important modality for cancer treatment. About 50% of cancer patients receive radiotherapy, and one-third of radiotherapy recipients were identified as having unmet psychosocial needs. The unmet psychosocial needs worsen the patient's quality of life and treatment effectiveness. This review aims to identify the psychosocial needs of post-radiotherapy cancer survivors and their direct caregivers. Systematic research of Embase, Scopus and PubMed was done and 17 studies were selected for analysis. The results show that patients encounter distress and fear due to treatment immobilization and unfamiliarity with procedures respectively. Information provision is a common need raised by patients and caregivers. Patients and caregivers report relationship problems due to affected sexual functions. To facilitate future studies, solutions to each identified psychosocial need are proposed in the discussion based on the 17 selected papers and other supporting literature. This review proposes art therapy to alleviate psychological distress, and pre-treatment information sessions to reinforce information delivery. Creative interventions such as a sexual rehabilitation program are recommended. Future studies are warranted to examine the interventions and thus improve the patients' and caregivers' well-being.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".