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Record W3092092890 · doi:10.1186/s12874-020-01136-2

Recruiting men from across the socioeconomic spectrum via GP registers and community outreach to a weight management feasibility randomised controlled trial

2020· article· en· W3092092890 on OpenAlexaff
Matthew McDonald, Stephan U Dombrowski, Rebecca Skinner, Eileen Calveley, Paula Carroll, Andrew Elders, Cindy M. Gray, Mark Grindle, Fiona Harris, Claire Jones, Pat Hoddinott, Alison Avenell, Frank Kee, Michelle C. McKinley, Martin Tod, Marjon van der Pol

Bibliographic record

VenueBMC Medical Research Methodology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsUniversity of New Brunswick
FundersMedical Research CouncilUniversity of StirlingNational Institute for Health and Care ResearchUniversity of DundeeUniversity of AberdeenScottish GovernmentPublic Health Research ProgrammeScottish Government Health and Social Care Directorate
KeywordsOutreachDisadvantagedMedicineWeight managementPsychological interventionWaistFamily medicineSocioeconomic statusGerontologyRandomized controlled trialObesityWeight lossPhysical therapyDemographyPopulationNursingEnvironmental healthSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Men, particularly those living in disadvantaged areas, are less likely to participate in weight management programmes than women despite similar levels of excess weight. Little is known about how best to recruit men to weight management interventions. This paper describes patient and public involvement in pre-trial decisions relevant to recruitment and aims to report on recruitment to the subsequent men-only weight management feasibility trial, including the: i) acceptability and feasibility of recruitment; and ii) baseline sample characteristics by recruitment strategy. METHODS: and/or waist circumference ≥ 40 in. were recruited to the feasibility trial via two strategies; community outreach (venue information stands and word of mouth) and GP letters, targeting disadvantaged areas. Recruitment activities (e.g. letters sent, researcher venue hours) were recorded systematically, and baseline characteristics questionnaire data collated. Qualitative interviews (n = 50) were conducted three months post-recruitment. Analyses and reporting followed a complementary mixed methods approach. RESULTS: 105 men were recruited within four months (community n = 60, GP letter n = 45). Community outreach took 2.3 recruiter hours per participant and GP letters had an opt-in rate of 10.2% (n = 90/879). More men were interested than could be accommodated. Most participants (60%) lived in more disadvantaged areas. Compared to community outreach, men recruited via GP letters were older (mean = 57 vs 48 years); more likely to report an obesity-related co-morbidity (87% vs 44%); and less educated (no formal qualifications, 32% vs 10%, degree educated 11% vs 41%). Recruitment strategies were acceptable, a sensitive approach and trusting relationships with recruiters valued, and the 'catchy' study name drew attention. CONCLUSIONS: Targeted community outreach and GP letters were acceptable strategies that successfully recruited participants to a men-only weight management feasibility trial. Both strategies engaged men from disadvantaged areas, a typically underserved population. Using two recruitment strategies produced samples with different health risk profiles, which could add value to research where either primary or secondary prevention is of interest. Further work is required to examine how these strategies could be implemented and sustained in practice. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03040518 , 2nd February 2017.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.145
metaresearch head score (Gemma)0.361
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1450.361
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.692
GPT teacher head0.603
Teacher spread0.089 · 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; both teacher heads agree on what is shown here.

Study designRandomized trial
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

Citations17
Published2020
Admission routes1
Has abstractyes

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