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Record W4402060589 · doi:10.1016/j.jshs.2024.100969

Promoting men's health through sports clubs: A systematic rapid realist review

2024· review· en· W4402060589 on OpenAlexaff
Anne Timm, Aurélie Van Hoye, Paul Sharp, Tue Helms Andersen, Louise Hansen, Jane Nautrup Østergaard, Peter Krustrup, Kenneth Holm Cortsen, Peter Bindslev Iversen, Morten Hulvej Rod, Charlotte Demant Klinker

Bibliographic record

VenueJournal of sport and health science/Journal of Sport and Health Science · 2024
Typereview
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia
FundersNovo Nordisk FondenNovo Nordisk
KeywordsPolitical scienceMedicineSociology

Abstract

fetched live from OpenAlex

• Leveraging professional sports clubs as venues for health promotion (HP) interventions targeting men demonstrates positive HP effects. • By utilizing men's appeal of sports clubs, this arena serves as familiar and masculine reducing barriers of recruitment including seeing health as feminine, limited accessibility, and lack of trust. • Men's engagement in HP interventions in sports club contexts was strengthened when they experienced supportive group environments and inclusive competition. • Investigations of men's HP maintenance after interventions were lacking, yet establishment of communal partnerships seemed crucial. • Incorporating men's perspectives in intervention development is recommended to foster sustainable HP interventions. Health promotion (HP) interventions delivered through sports clubs have demonstrated promising outcomes among men, but less is known about which aspects of the interventions work, for whom, and under what circumstances. This rapid realist review aims to understand the contexts, mechanisms, and outcomes of HP interventions for men delivered through sports clubs. A systematic literature search was conducted in February 2023 for studies published after 2013 in MEDLINE, Embase, and SPORTDiscus databases. Included studies: (a) were delivered by or in collaboration with sports clubs, (b) targeted men aged 18+ years, and (c) reported 1 or more HP outcome. A grey literature search was also performed. Studies were included in a realist synthesis based on richness and rigor. Hereafter, context-mechanisms-outcome (CMO) configurations were developed. We identified and screened 3356 studies, finally including 60 studies describing 22 interventions. Most HP interventions were delivered in high income countries, included Caucasian men aged 35–65 years with overweight/obesity, and used professional sports clubs (mostly football) for recruitment and facilities. Quantitative HP outcomes were reported across 19 interventions. Of these 19 interventions, the majority reported on weight ( n = 18), physical activity ( n = 12), mental health ( n = 10), and diet ( n = 9). We identified 12 CMOs related to how HP interventions affected men's recruitment, engagement, and health behavior maintenance. Our findings show that using sports clubs for HP interventions is effective for engaging men. Recruitment was facilitated by leveraging sports clubs’ identity, addressing masculinity-related barriers, improving accessibility, and building trust. Engagement was enhanced through shared identity experiences, safe spaces, inclusive competition, and self-efficacy. However, there's limited evidence on behavior maintenance post-intervention, though involving community stakeholders seemed vital. In general, considerations should be made to avoid perpetuating traditional masculine norms, which may exclude some men and reinforce unhealthy behaviors. These findings can guide intervention development, emphasizing the need to harness men's perspectives in the process.

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)0.025
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.079
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0190.016
Science and technology studies0.0010.001
Scholarly communication0.0060.006
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.155
GPT teacher head0.459
Teacher spread0.304 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations23
Published2024
Admission routes1
Has abstractyes

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