Evidence map›Paper›PMID 36421627›Full record

ArticleHealthcare (Basel, Switzerland)2022

Handheld-Load-Specific Jump Training over 8 Weeks Improves Standing Broad Jump Performance in Adolescent Athletes.

Wei-Hsun Tai, Hai-Bin Yu, Ray-Hsien Tang, Chen-Fu Huang, Yan Wei, Hsien-Te Peng

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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.

  1. Article
  2. Article
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.

Wei-Hsun TaiSchool of Physical Education, Quanzhou Normal University, Quanzhou 362000, China.ORCID 0000-0002-5891-6279
Hai-Bin YuSchool of Physical Education, Quanzhou Normal University, Quanzhou 362000, China.ORCID 0000-0003-3018-8158
Ray-Hsien TangDepartment of Physical Education, National Taiwan Normal University, Taipei 106209, Taiwan.
Chen-Fu HuangDepartment of Physical Education, National Taiwan Normal University, Taipei 106209, Taiwan.ORCID 0000-0002-5563-6722
Yan WeiDepartment of Physical Education, Chinese Culture University, Taipei 11114, Taiwan.
Hsien-Te PengGraduate Institute of Sport Coaching Science, Chinese Culture University, Taipei 11114, Taiwan.ORCID 0000-0002-4738-4561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the effects of handheld-load-specific jump training on standing broad jump (SBJ) performance in youth athletes and the biomechanics changes involved.

methodsFifteen male athletes (mean age, body weight, height, and body mass index were 14.7 ± 0.9 years, 59.3 ± 8.0 kg, 1.73 ± 0.07 m, 19.8 ± 2, respectively) underwent 15 SBJ training sessions over 8 weeks. The data were collected over three phases: before training, after training, and after training with 4 kg loading. Ten infrared high-speed motion-capture cameras and two force platforms, whose sampling rates were 250 and 1000 Hz, respectively, were used to record the kinematic and kinetic data. Visual three-dimensional software was used for the data analyses.

resultsJump performance and all biomechanics variables, including joint and takeoff velocities, ground reaction force, takeoff impulse, and mechanical outputs, improved after training.

conclusionsSBJ training under handheld loading resulted in considerable acute improvements as well as training transfer after 8 weeks. Moreover, explosive ability was effectively enhanced. The present findings serve as a reference for SBJ assessment and jump-related training.

Indexed as

8-week traininghandheld loadimpulsesport biomechanicsstanding broad jump

Identifiers

PMID36421627
PMCPMC9690281

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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.