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Record W4388720001 · doi:10.1370/afm.22.s1.4779

Recruitment and characteristics of men with overweight/obesity from a trial of a gender-sensitized healthy lifestyle program

2023· article· en· W4388720001 on OpenAlexaboutno aff
Robert J. Petrella, Melissa Majoni, Marisa Kfrerer, Narlon Boa Sorte Silva, Precious Adekoya, Brendan Riggin, Wendy Blunt, Dawn P. Gill, Brooke Bliss, Matthew Dinunzio, Paul Aspinall, Jennifer D. Irwin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsBody mass indexPhysical therapyOverweightMedicineGlycated hemoglobinWaistRandomized controlled trialPopulationContext (archaeology)GerontologyDemographyPsychologyType 2 diabetesDiabetes mellitusEnvironmental healthInternal medicineGeography

Abstract

fetched live from OpenAlex

Context: Engaging men in chronic disease prevention is critical as rates of obesity in men continue to increase, coupled with men being less likely to proactively seek preventative health care services. Objective: To report on the recruitment and baseline characteristics of a healthy lifestyle program using the power of sport (hockey) to engage men. Study Design and Analysis: Cluster randomized controlled trial where 42 sites were randomly assigned to either the intervention or wait-list control group. The intervention group received the Hockey Fans in Training (Hockey FIT) program (3-month active phase; 9-month minimally-supported phase) while the control group continued with usual activities for 12 months. Setting: Sites were located across 40 cities in Canada and the U.S., selected based on the availability/interest of both a local major junior/professional hockey team and an implementation partner. Population Studied: Men aged 35-65 years with a body mass index (BMI) ≥ 27 kg/m2 and who were fans of the local hockey team. Participants were recruited through the hockey team (i.e., social media, email blasts, website) and using other traditional recruitment methods. Intervention: Hockey FIT is a gender-sensitized, off-ice, healthy lifestyle program, designed to appeal to hockey fans through support from their local team and based on men’s preferences (e.g., group-based competition, humour, being with like-minded and -sized men). Outcome Measures: In-person assessments (weight, height, waist circumference, blood pressure, glycated hemoglobin, fitness) and online questionnaires (physical activity, sedentary time, healthy eating, health-related quality of life, and demographics) were completed at baseline, 3, and 12 months. Accelerometry-based step counters were also used to measure steps over 7 days at each time point. Results: 1,397 individuals were assessed for eligibility and 997 men were enrolled. Most participants heard about Hockey FIT through social media and team email blasts (41% and 29%, respectively). Participants averaged 48.6 years of age (± 8.3 SD), had mean BMI values of 35.3 kg/m2 (± 6.1), were predominately white, and had varying levels of education. Conclusions: By partnering with local hockey teams, we were able to engage men in a healthy lifestyle program. While participants were among the target audience intended for the study, targeted recruitment is needed to attract more diverse populations.

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)0.006
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.087
GPT teacher head0.351
Teacher spread0.264 · 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
Published2023
Admission routes1
Has abstractyes

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