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Recruiting a geographically, ethnically and socioeconomically diverse population of postpartum women into a behavioural weight management intervention trial: an evaluation of strategies used in the Supporting MumS (SMS) randomised controlled trial.

2025· article· en· W4413909511 on OpenAlexaff
Dunla Gallagher, Eleni Spyreli, Norelle Calder-MacPhee, Kirsty Crossley, C Feuillatre, Alexandra Ivory, Ben Karatas, Kelly CB, Marcus Lind, Emmanuela Osei-Asemani, R Potrick, Heather Stanton, Sally Bridges, Elinor Coulman, Caroline Free, Pat Hoddinott, Annie S. Anderson, Chris R. Cardwell, Dejun Su, Seamus Heaney, Kee F, Clíona McDowell, Emma McIntosh, Lynn Murphy, Jayne V. Woodside, Michelle C. McKinley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsEthnically diverseIntervention (counseling)MedicineRandomized controlled trialWeight managementPopulationPhysical therapyFamily medicineGerontologyEnvironmental healthWeight lossObesityNursingInternal medicine

Abstract

fetched live from OpenAlex

Objective To evaluate strategies used to recruit a geographically, ethnically and socioeconomically diverse sample of postpartum women (including those who gave birth but who do not identify as women) to the Supporting MumS randomised controlled trial (RCT). Design Two-arm, parallel, multi-centre RCT. Setting Five sites across the United Kingdom, selected with consideration of geographic, ethnic and socioeconomic diversity. Population or Sample Women, within 6 weeks to two years postpartum, with BMI ≥25 kg/m 2 . Methods Strategies used to recruit over a 12-month period were recorded, and outcomes were assessed by site, ethnicity and Index of Multiple Deprivation (IMD) data. Main Outcome Measures Numbers expressing interest, screened and randomised. Results Over 12 months, 2,457 women expressed an interest, 1,227 (49.9%) were screened for eligibility and 892 (36.3%) were randomised. The sample had 33.6% non-white ethnicity and 53.5% lived in the two most deprived quintiles (according to IMD). Most participants learnt about the study through social media (45.5%), followed by community groups and settings aimed at parents (26.0%), the Born in Bradford’s Better Start ( BiBBS ) cohort (12.5%), friends/family (7.2%), general community settings (5.3%) and health professionals (5.4%). Success of recruitment strategies varied across sites and participant characteristics. Conclusions An ethnically and socioeconomically diverse sample of postpartum women across the four UK countries was recruited within the planned 12-month timeframe. This was achieved by selection of recruitment sites (considering geographical spread and population characteristics), using a range of strategies and tailoring these to local populations, and iteratively adapting strategies employed based on success.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.080
GPT teacher head0.468
Teacher spread0.388 · 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.

Study designObservational
DomainMethods
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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