A Qualitative Study to Explore Patient Perspectives of Prophylactic Treatment with OnabotulinumtoxinA for Chronic Migraine
Bibliographic record
Abstract
INTRODUCTION: OnabotulinumtoxinA (OBT-A) is one of the most studied prophylactic treatments for chronic migraine. Large clinical trials, and now real-world studies, continue to provide evidence to support the use of OBT-A as an effective treatment to manage chronic migraine. The objective of this study was to explore patient experience and perception of prophylactic treatment with OBT-A for chronic migraine. METHODS: Data were collected using semi-structured interviews using open-ended questions to uncover rich descriptive data on patient experiences. Interviews were transcribed and analysed using NVivo data analysis software to code and identify themes across the dataset. Three patient groups were included in the analysis: (1) patients who were receiving continued OBT-A treatment; (2) patients who discontinued OBT-A treatment; (3) patients who were recommended for OBT-A treatment but did not proceed. RESULTS: For patients who received at least one OBT-A treatment, four main themes emerged, which described patients' expectations, experiences, and feelings towards their treatment decisions. Two main themes emerged that were common to patients, who had discontinued their treatment and those, who were recommended for OBT-A treatment but did not proceed, which were identified as potential barriers to initiate or continue prophylactic treatment with OBT-A. CONCLUSION: Understanding patients' perspective is an important part of clinical practice and may impact on decision-making. Qualitative data can provide a more holistic view of patient care and treatment insights that may not be evaluated during a clinical trial. This study revealed potential barriers to treatment that can inform future policy and practice.
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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".