Prescribing Gabapentin off Label: Perspectives from Psychiatry, Pain and Neurology Specialists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to explore the experiences of physicians prescribing gabapentin off label. METHODS: We used a case study approach to explore the experiences of physicians prescribing gabapentin for off-label indications. Semi-structured interviews were conducted with 10 physicians (psychiatry, pain and neurology specialists) in the Greater Toronto Area. Data were collected to the point of saturation of key themes and analyzed using interpretive content analysis. KEY FINDINGS: Key informants appeared to rely primarily on informal information from colleagues and meetings, putting into question the accuracy of their information about the potential off-label uses of gabapentin. Our findings suggest the need for more evidence-based information on off-label drug use. CONCLUSION: There is a need for greater understanding of off-label prescribing practices as an important step toward improving rational prescribing and ultimately toward improving patient safety and health outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it