Knowledge and attitudes toward repetitive transcranial magnetic stimulation (rTMS) as a treatment for postpartum and peripartum depression
Bibliographic record
Abstract
Introduction Postpartum and peripartum depression are debilitating disorders that impact the mother and their ability to care for their children’s emotional, social, and physical needs. Current treatments include psychotherapy, pharmacotherapy, and electroconvulsive therapy. These treatments are moderately effective or come with side effects that can negatively impact mother and child. As a result, many mothers view some treatments as unacceptable while pregnant or breastfeeding. Over the last decade, repetitive transcranial magnetic stimulation (rTMS) has shown promise as an effective and safe treatment option for postpartum and peripartum depression. However, little is known regarding people’s knowledge and attitudes towards this emerging technology, with no research assessing this in Canada. Objectives We aim to identify gaps in knowledge and to assess attitudes toward rTMS as a treatment for postpartum and peripartum depression in mental health professionals, patients, and the general public living in Canada. Methods A mixed methods study design will be employed. The qualitative portion will consist of individual semi-structured interviews. An inductive thematic analysis will be completed. The quantitative portion will consist of an anonymous, self-administered survey shared through REDCap. Focus groups with rTMS experts will be conducted to inform survey creation. Results No resulst at this time. Conclusions Understanding gaps in knowledge and attitudes toward rTMS is the first step toward ensuring that everyone is well informed and able to access safe and effective treatments. With limited treatment options available to a postpartum and/or peripartum depression patients being well informed on all treatments is crucial towards accessing treatments that best suit their needs. Disclosure No significant relationships.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".