Psychosocial Aspects of Living Long Term with Advanced Cancer and Ongoing Systemic Treatment: A Scoping Review
Bibliographic record
Abstract
(1) Background: Studies examining the psychosocial impact of living long term on systemic treatment in advanced cancer patients are scarce. This scoping review aimed to answer the research question "What has been reported about psychosocial factors among patients living with advanced cancer receiving life-long systemic treatment?", by synthesizing psychosocial data, and evaluating the terminology used to address these patients; (2) Methods: This scoping review was conducted following the five stages of the framework of Arksey and O'Malley (2005); (3) Results: 141 articles published between 2000 and 2021 (69% after 2015) were included. A large variety of terms referring to the patient group was observed. Synthesizing qualitative studies identified ongoing uncertainty, anxiety and fear of disease progression or death, hope in treatment results and new treatment options, loss in several aspects of life, and worries about the impact of disease on loved ones and changes in social life to be prominent psychosocial themes. Of 82 quantitative studies included in the review, 76% examined quality of life, 46% fear of disease progression or death, 26% distress or depression, and 4% hope, while few studies reported on adaptation or cognitive aspects. No quantitative studies focused on uncertainty, loss, or social impact; (4) Conclusion and clinical implications: Prominent psychosocial themes reported in qualitative studies were not included in quantitative research using specific validated questionnaires. More robust studies using quantitative research designs should be conducted to further understand these psychological constructs. Furthermore, the diversity of terminology found in the literature calls for a uniform definition to better address this specific patient group in research and in practice.
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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 | 0.011 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".