Bibliographic record
Abstract
BACKGROUND: "Unnecessary use of health services" refers to care that does not add value for patients and can lead to physical, emotional, and economical harm. High rates of overuse have been reported within oncology, and patients experience its consequences. OBJECTIVE: The aim of this study was to explore perceptions and experiences of oncology nurses regarding unnecessary use of oncology services. METHODS: In-depth, semistructured interviews were conducted with a convenience sample of 20 oncology nurses currently practicing in Israel. Interviews were recorded, transcribed, and analyzed thematically. RESULTS: Themes included perceptions of unnecessary use of health services in cancer (causes and effects of unnecessary use, current and proposed solutions) and negative effects of unnecessary cancer care on patients, families, providers, and the system, including decreased quality of life, increased suffering, and emotional effects on patients and families. Causes were seen on provider, family, and patient levels, such as difficulty for providers to "give up," lack of registered nurses' authority, and family and patient demands. Multidisciplinary care provision, nurses' role, and the patient-provider relationship were seen as existing facilitators minimizing unnecessary use. Future improvement can be achieved by strengthening relationships, providing support to healthcare providers, and improving communication. CONCLUSIONS: Nurses perceive unnecessary use of health services as a result of multiple, interlinked and complex causes, but few targeted interventions exist. Future research should explore quantifying unnecessary use to determine an accurate representation of the issue. IMPLICATIONS FOR PRACTICE: Solutions should include engaging patients and families, involving nurses, and fostering multidisciplinary collaborative teamwork to positively affect care and treatment decision-making processes.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".