Recruiting pregnant smokers for a placebo-randomised controlled trial of nicotine replacement therapy
Bibliographic record
Abstract
BACKGROUND: Smoking in pregnancy is a public health problem and effective methods for reducing this are required. Although nicotine replacement therapy (NRT) is effective for smoking cessation in non-pregnant people, there is no direct evidence concerning its effectiveness in pregnancy. Despite this, clinical guidelines recommend the cautious use of NRT during pregnancy. Randomised controlled trials are needed to determine the safety and efficacy of NRT when used by pregnant women for smoking cessation, but the feasibility of recruiting women to such trials is unknown. Consequently, in this study we aimed to determine i) the feasibility of recruiting women to a RCT of NRT in pregnancy as they attend hospital antenatal ultrasound examinations, ii) the proportion of such women who are eligible for and interested in trial enrollment and iii) research staff perceptions of how one method of trial recruitment could be improved. METHODS: During a one month period, all women attending for antenatal ultrasound examination in an English teaching hospital were asked to complete a questionnaire which determined their eligibility to enroll in a proposed placebo controlled randomised trial investigating the effectiveness of NRT in pregnancy. Women who were eligible to participate were asked whether they would do so and those who accepted enrollment were offered an appointment with a smoking cessation advisor. RESULTS: Over 99% (851/858) of women agreed to complete a questionnaire about smoking habits whilst waiting for ultrasound examinations. 10.3% (88/851) of women attending for antenatal ultrasound fitted eligibility criteria for a proposed RCT of NRT in pregnancy, but only 3.6% [(31/851), 95% CI, 2.4 to 4.9%] indicated on the questionnaire that they would like to take part in a study involving randomisation to placebo or active patches. Researchers offered trial enrollment to 26 of these 31 women and 96% (25) accepted. Staff recruiting women believed that trial recruitment would be maximised if women attending the ultrasound department knew about trial recruitment before attending and greater staff resources were made available for this. It was also perceived that women generally under-reported the amount they smoked on questionnaires completed whilst waiting in ultrasound department areas. CONCLUSIONS: It is feasible to recruit women for a trial of NRT in pregnancy as they wait for antenatal ultrasound examinations. Using similar recruitment methods, researchers can expect to recruit between 24 and 49 women per 1000 approached.
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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 | 0.029 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".