Design and Conduct of an <scp>I</scp>nternet‐Based Preconception Cohort Study in <scp>N</scp>orth <scp>A</scp>merica: <scp>P</scp>regnancy <scp>S</scp>tudy <scp>O</scp>nline
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: We launched the Boston University Pregnancy Study Online (PRESTO) to assess the feasibility of carrying out an Internet-based preconception cohort study in the US and Canada. METHODS: We recruited female participants age 21-45 and their male partners through Internet advertisements, word of mouth, and flyers. Female participants were randomised with 50% probability to receive a subscription to FertilityFriend.com (FF), a web-based programme that collects real-time data on menstrual characteristics. We compared recruitment methods within PRESTO, assessed the cost-efficiency of PRESTO relative to its Danish counterpart (Snart-Gravid), and validated retrospectively reported date of last menstrual period (LMP) against the FF data. RESULTS: After 99 weeks of recruitment (2013-15), 2421 women enrolled; 1384 (57%) invited their male partners to participate, of whom 693 (50%) enrolled. Baseline characteristics were balanced across randomisation groups. Cohort retention was similar among those randomised vs. not randomised to FF (84% vs. 81%). At study enrollment, 56%, 22%, and 22% couples had been trying to conceive for < 3, 3-5, and ≥ 6 months, respectively. The cost per subject enrolled was $146 (2013 US$), which was similar to our companion Danish study and half that of a traditional cohort study. Among FF users who conceived, > 97% reported their LMP on the PRESTO questionnaire within 1 day of the LMP recorded via FF. CONCLUSIONS: Use of the Internet as a method of recruitment and follow-up in a North American preconception cohort study was feasible and cost-effective.
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.
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 | 0.016 | 0.077 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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 it