The psychosocial needs of students conducting research with patients and their families in advanced cancer and palliative care: A scoping review
Bibliographic record
Abstract
OBJECTIVE: The objective of this article was to explore the extent of the scientific literature and evidence base about the psychosocial needs of students conducting research in the fields of advanced cancer and palliative care. METHOD: A scoping review was conducted in major scientific databases. English-language articles on the topic of interest were retained if they were published in peer-reviewed journals between 1995 and 2013. RESULTS: A total of 3,161 references were screened, and 7 were retained for analysis. Only two articles were empirical studies involving the collection of primary empirical data. The remaining ones were commentaries and personal reflections. While there is a near absence of empirical research about the psychosocial needs of students, several commentaries suggest that students in this field have a high need for support. Three themes were identified in the limited literature retrieved: (1) the importance of proper training and supervision; (2) the availability of emotional support structures; and (3) the use of effective and deliberate self-care strategies. SIGNIFICANCE OF RESULTS: This scoping review demonstrates that little is known about the psychosocial needs of students conducting research in advanced cancer and palliative care. However, what is clear is that there is a large emotional impact on student researchers engaged in this type of work. Adequate training and support is needed to promote students' health and well-being, encourage retention of students, and foster high-quality studies. More empirical data are needed to better understand the experiences of students conducting this type of research and to ensure the sustainability of training and 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 | 0.066 | 0.239 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".