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Record W4241139931 · doi:10.2196/preprints.25208

Comparative Success of Recruitment Strategies for an Exercise Intervention Trial Among Women With Polycystic Ovary Syndrome: Observational Study (Preprint)

2020· preprint· en· W4241139931 on OpenAlexaff
Jamie L. Benham, Jane E. Booth, Christine M. Friedenreich, Doreen M. Rabi, Ronald J. Sigal

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsPolycystic ovaryMedicineReferralFamily medicineObservational studyRandomized controlled trialNewspaperPhysical therapyPsychologyAdvertisingInternal medicineObesity

Abstract

fetched live from OpenAlex

BACKGROUND Effective and efficient participant recruitment is a key determinant of the success of a research program. Previously reported recruitment strategies have displayed variable success rates in studies on women with polycystic ovary syndrome (PCOS). OBJECTIVE This study aimed to evaluate the effectiveness and cost per participant of the recruitment strategies that we used in a prospective randomized controlled trial to examine the effects of exercise training among inactive women with PCOS, who are aged 18-40 years. METHODS The 4 recruitment methods we used were as follows: (1) referral by health care providers or by word of mouth, (2) media (eg, local newspaper stories and radio interviews), (3) Facebook advertisements, and (4) unpaid advertisements including posters and websites. The proportions of potential, eligible, and enrolled participants recruited with each method were determined and compared using tests of proportion. The time investment and cost per participant enrolled were calculated for each recruitment strategy. RESULTS Of 200 potential participants screened, 98 (49%) were recruited from unpaid advertisements (posters and websites), 70 (35%) from Facebook advertisements, 16 (8%) by referral, and 16 (8%) from traditional media (newspaper and radio). Every potential participant was recruited from separate means (ie, no participant was approached through more than one recruitment method). A total of 109 (54.5%) women were deemed eligible for participation in the trial, and 60 (30.0%) were enrolled. The proportion of potential participants who completed the trial was higher for those recruited from traditional media than from Facebook advertisements (n=7/16, 44% vs n=13/70, 19%, respectively; P=.03) or unpaid advertisements (n=7/16, 44% vs n=13/98, 13%, respectively; P=.002). The cost per participant was Can $18.21 for Facebook advertisements and Can $43.88 for unpaid advertisements. There were no direct trial costs for referrals or traditional media. CONCLUSIONS For this trial, each method was important for recruiting inactive women with PCOS because no participant reported learning about the trial through more than one method. Unpaid advertisements and Facebook advertisements helped recruit the largest number of participants in the trial, the former resulting in a higher cost per participant than the latter. CLINICALTRIAL ClinicalTrials.gov NCT03362918; https://clinicaltrials.gov/ct2/show/NCT03362918

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 imitation

Not 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.

metaresearch head score (Codex)0.049
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.118
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.236
GPT teacher head0.394
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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