68 Bridging research and practice: Investigating barriers and facilitators in the translational journey of transcranial magnetic stimulation
Bibliographic record
Abstract
Objectives/Goals: This systematic review aims to identify and synthesize evidence on the barriers and facilitators impacting the implementation of transcranial magnetic stimulation (TMS) in clinical practice, enhancing understanding for improved adoption and efficacy. Methods/Study Population: This systematic review follows PRISMA guidelines to identify relevant literature on barriers and facilitators to TMS in North America. We conducted a comprehensive search of databases including PubMed, Scopus, and PsycINFO, targeting studies published from 2000 onward. Eligible studies include qualitative and quantitative research focusing on adults aged 18 years and older in the USA and Canada. Two independent reviewers screened titles, abstracts, and full texts, extracting data on barriers and facilitators related to TMS implementation. Results/Anticipated Results: We anticipate identifying a diverse range of barriers and facilitators related to TMS implementation in North America. Expected barriers may include limited clinician knowledge, patient resistance, and logistical challenges in clinical settings. Facilitators could encompass supportive institutional policies, clinician training, and positive patient outcomes. The synthesis of findings will highlight key themes, guiding future research and practice. We aim to produce actionable recommendations for stakeholders, ultimately enhancing the effective integration of TMS in clinical care for adult populations. Discussion/Significance of Impact: This review will provide crucial insights into the barriers and facilitators of TMS implementation, informing clinicians, policymakers, and researchers. By highlighting actionable strategies, it aims to enhance TMS accessibility and efficacy, ultimately improving patient outcomes and advancing neurotherapeutic practices in North America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.144 | 0.362 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".