The patient needs assessment in cancer care: identifying barriers and facilitators to implementation in the UK and Canada
Bibliographic record
Abstract
PURPOSE: Personalised information and support can be provided to cancer survivors using a structured approach. Needs assessment tools such as the Holistic Needs Assessment (HNA) in the UK and the Comprehensive Problem and Symptom Screening (COMPASS) questionnaire in Canada are recommended for use in practice; however, they are not widely embedded into practice. The study aimed to determine the extent to which nurses working in cancer care in the UK and Manitoba value NA and identify any barriers and facilitators they experience. METHOD: Oncology nurses involved in the care of cancer patients in the UK (n = 110) and Manitoba (n = 221) were emailed a link to an online survey by lead cancer nurses in the participating institutions. A snowball technique was used to increase participation across the UK resulting in 306 oncology nurses completing the survey in the UK and 116 in Canada. RESULTS: Participants expressed concerns that these assessments were becoming bureaucratic "tick-box exercises" which did not meet patients' needs. Barriers to completion were time, staff shortages, lack of confidence, privacy, and resources. Facilitators were privacy for confidential discussions, training, confidence in knowledge and skills, and referral to resources. CONCLUSION: Many busy oncology nurses completed this survey demonstrating the importance they attach to HNAs and COMPASS. The challenges faced with implementing these assessments into everyday practice require training, time, support services, and an appropriate environment. It is vital that the HNA and COMPASS are conducted at optimum times for patients to fully utilise time and resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".