A proof-of-concept study of iCope: A nurse-led psycho-educational telephone intervention for women attending a rapid diagnostic centre for breast abnormality
Bibliographic record
Abstract
The period between the initial discovery of a suspicious breast lesion and a confirmed diagnosis is a time of significant psychological distress, heightened anxiety, and uncertainty for many women. This proof of concept (PoC) study explored the clinical outcomes and acceptability of iCope, a nurse-led psycho-educational telephone intervention aimed to assist with uncertainty, anxiety and coping in women going through a Rapid Diagnostic Centre (RDC) offering quick diagnosis of breast cancer (same day to three-day post-investigation). Guided by the Uncertainty Theory, and using a one-arm pretest-posttest design, two brief 15-minute telephone sessions were delivered by a nurse prior to the women's day of testing at the RDC and three days after the receipt of their results. Six women completed measures of anxiety, uncertainty, and coping before the clinic visit, three days and three weeks after receiving their test results. Results show that the implementation of the telephone intervention was challenging, yet may offer potential for positive impact. That is, trends of decreased uncertainty and anxiety in participants over time were noted. Considering the difficulty observed in the recruitment and delivering the two interventions in the timeline planned, feasibility testing is recommended before the conduct of a large-scale study.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".