Improving Information Provision for Neurosurgical Patients: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Patients confronted with the daunting prospect of a potentially life-altering procedure with uncertain outcome demonstrate high levels of anxiety and need for information. Regardless, many patients are left unsatisfied by the amount of information received from physicians. This study sought to examine the information-seeking patterns of patients and suggest ways to optimize the communication of medical information, specifically within the context of neurosurgery. METHODS: Semi-structured interviews were conducted with 31 neurosurgical patients operated on for benign or malignant brain tumors. Interviews were transcribed and subjected to thematic analysis in NVivo10. RESULTS: Three major themes relating to information-seeking by neurosurgical patients were identified: 1) almost all patients searched for information on the Internet; 2) in addition to characterizing the tumor as benign or malignant, patients sought additional information such as the location of the tumor in the brain; and 3) patients with malignant tumors were less likely to seek information online and more likely to consider alternative therapies. To improve the provision of information to neurosurgical patients, physicians can 1) offer to review imaging results with patients; 2) promote an environment open to questions; 3) provide information in a forthright manner, avoiding the use of medical jargon; and 4) consider guiding patients to reliable Internet sites and facilitating written records of consultations. CONCLUSIONS: There are many ways that physicians can improve the provision of information to patients, including providing written information and physician recommended online resources, and being mindful of patient perceived time constraints and barriers to effective communication. Amélioration de l'information transmise aux patients traités en neurochirurgie : une étude qualitative.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".