Challenges of evaluating a computer-based educational programme for women diagnosed with early-stage breast cancer: a randomised controlled trial
Bibliographic record
Abstract
In a two-group, multi-centre, randomised controlled 9 months trial, we (1) evaluated the impact of a computer-based educational programme compared to standard care and (2) examined whether different patterns of programme usage could be explained by demographic, medical and psychosocial factors. We involved 226 Swedish-speaking women diagnosed with early-stage breast cancer and scheduled for surgery. Primary outcomes were health self-efficacy and health care participation measured by the Comprehensive Health Enhancement Supportive System instrument. Secondary outcomes were anxiety and depression levels measured by the Hospital Anxiety and Depression scale. The Functional Assessment of Cancer Therapy-Breast and Sense of Coherence scales measured psychosocial factors for the study's secondary aim. Multi-level modelling revealed no statistically significant impact of the computer-based educational programme over time on the outcomes. Subsequent exploratory regression analysis revealed that older women with axillary dissection and increased physical well-being were more likely to use the programme. Furthermore, receiving post-operative chemotherapy and increased meaningfulness decreased the likelihood of use. Providing reliable and evidence-based medical and rehabilitation information via a computer-based programme might not be enough to influence multi-dimensional outcomes in women diagnosed with breast cancer. The use of these programmes should be further explored to promote adherence to e-Health supportive interventions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".