Perinatal transmission of Lyme disease: A qualitative study investigating the research priorities of patients with Lyme disease in pregnancy
Bibliographic record
Abstract
INTRODUCTION: Lyme disease is one of the most prevalent vector-borne disease in North America, yet its implications during pregnancy are poorly understood. Our knowledge of perinatal transmission of Lyme disease is limited due to the lack of robust epidemiological studies and longitudinal follow-up. OBJECTIVES: This study aimed to understand the research priorities of people who have experienced Lyme disease in pregnancy and the feasibility of recruiting this population for future studies on perinatal transmission of Lyme disease. We also sought to understand the barriers and enablers to participating in research on perinatal transmission of Lyme disease. METHODS: We conducted a qualitative study using focus groups and interviews with people who had experienced Lyme disease during pregnancy. English speaking participants were recruited through an online survey. There was no geographic restriction on participation. The focus groups and the interview were recorded and transcribed. Data were analyzed using interpretive content analysis. RESULTS: Twenty people participated in four semi-structured focus groups and one semi-structured individual interview. The majority of participants were from North America. Participants' research priorities fell into five categories: transmission, testing, treatment, disease presentation, and education. All study participants expressed interest in future participation in research on Lyme disease in pregnancy and highlighted barriers and enablers to participation that could be addressed to facilitate future study recruitment. CONCLUSION: The research priorities identified in this research would be well addressed through prospective research. People who experience Lyme disease in pregnancy are invested in continued research into perinatal transmission of Lyme disease.
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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 | 0.022 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".