Evidence map›Paper›PMID 38890690›Full record

ArticleBMC sports science, medicine & rehabilitation2024

Efficacy of multicomponent interventions on injury risk among ice and snow sports participants-a systematic review and meta-analysis.

Zhanjiang Fan, Lanbin Min, Wenbin He, Yaorong Yang, Wen Ma, Jiayi Yao

Abstract read
In one paragraph

Article in BMC sports science, medicine & rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhanjiang FanCollege of Educational Sciences, Xinjiang Normal University, Urumqi, 830017, China. fanzhanjiang45@gmail.com.ORCID http://orcid.org/0009-0005-8084-4282
Lanbin MinCollege of Educational Sciences, Xinjiang Normal University, Urumqi, 830017, China.
Wenbin HeCollege of Educational Sciences, Xinjiang Normal University, Urumqi, 830017, China.
Yaorong YangDepartment of Physical Education, Xinjiang Agricultural University, Urumqi, 830052, China.
Wen MaCollege of Physical Education, Xinjiang Normal University, Urumqi, 830017, China.
Jiayi YaoNo. 126 Middle School of Urumqi, Xinjiang, Urumqi, 830057, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIce and snow sports, which are inherently high risk due to their physically demanding nature, pose significant challenges in terms of participant safety. These activities increase the likelihood of injuries, largely due to reduced bodily agility and responsiveness in cold, often unpredictable winter environments. The critical need for effective injury prevention in these sports is emphasized by the considerable impact injuries have on the health of participants, alongside the economic and social costs associated with medical and rehabilitative care. In the context of ice and snow sports environments, applying the E principles of injury prevention to evaluate intervention measures can guide the implementation of future sports safety and other health promotion intervention measures in this field. When well executed, this approach can substantially reduce both the frequency and severity of injuries, thereby significantly enhancing the safety and long-term viability of these challenging sports.

objectiveThe objective of this study was to rigorously assess and statistically substantiate the efficacy of diverse injury prevention strategies in ice and snow sports, aiming to bolster future safety measures with solid empirical evidence.

designSystematic review and meta-analysis.

methodsThe overarching aim of this research was to meticulously aggregate and scrutinize a broad spectrum of scholarly literature, focusing on the quantifiable efficacy of diverse, multicomponent intervention strategies in mitigating the incidence of injuries within the realm of ice and snow sports. This endeavour entailed an exhaustive extraction of data from esteemed academic databases, encompassing publications up to September 30, 2023. In pursuit of methodological excellence and analytical rigor, the study employed advanced bias assessment methodologies, notably the AMSTAR 2 and GRADE approaches, alongside sophisticated random-effects statistical modelling. This comprehensive approach was designed to ensure the utmost validity, reliability, and scholarly integrity of the study's findings.

resultsFifteen papers, including 9 randomized controlled trials, 3 case‒control studies, and 3 cohort studies with 26,123 participants and 4,382 injuries, were analysed. The findings showed a significant reduction in injury rates through various interventions: overall injury prevention (RR = 0.50, 95% CI 0.42-0.63), educational training (RR = 0.50, 95% CI 0.34-0.73), educational videos (RR = 0.53, 95% CI 0.34-0.81), protective equipment (RR = 0.64, 95% CI 0.46-0.87), and policy changes (RR = 0.28, 95% CI 0.16-0.49). Subgroup analysis revealed potential heterogeneity in compliance (p = 0.347). Compared to controls, multicomponent interventions effectively reduced injury rates.

conclusionThis systematic review and meta-analysis demonstrated that multicomponent interventions significantly prevent injuries in ice and snow sports. By applying the E principles of injury prevention and constructing a framework for practical injury prevention research in ice and snow sports, we can gradually shift towards a systemic paradigm for a better understanding of the development and prevention of sports injuries. Moreover, sports injury prevention is a complex and dynamic process. Therefore, high-quality experiments in different scenarios are needed in future research to provide more reliable evidence, offer valuable and relevant prevention information for practitioners and participants, and help formulate more effective preventive measures in practice.

Indexed as

Component-based interventionsIce and snow sportsInjury preventionMeta-analysis

Identifiers

PMID38890690
PMCPMC11186188

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.