Prediction of individual optimal drop height in drop jump from anthropometric and strength variables.

Yongmin Xie, Fan Peng, Xinyu Pan, Qinchang Sun

Abstract read

In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Yongmin XieSchool of Strength and Conditioning Training, Beijing Sport University, Haidian, 100084, China. xieyongminbsu@163.com.

Fan PengSchool of Strength and Conditioning Training, Beijing Sport University, Haidian, 100084, China.

Xinyu PanSchool of Strength and Conditioning Training, Beijing Sport University, Haidian, 100084, China.

Qinchang SunSchool of Strength and Conditioning Training, Beijing Sport University, Haidian, 100084, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to investigate the associations between individual optimal drop height (ODH), as determined by the reactive strength index (RSI) method, and selected anthropometric and strength parameters, and to develop a prediction model for ODH based on these variables. A total of 49 participants were recruited, and measurements included body height, body mass, maximal muscle strength (MSmax), lower limb stiffness, reactive strength ratio (RSR), countermovement jump (CMJ) height, and ODH. Pearson correlation analysis was conducted to examine the relationships between ODH and the assessed variables. A multiple linear regression model was constructed in a stepwise manner to predict individual ODH. Significant correlations were observed between ODH and relative MSmax (r = 0.827, P < 0.001), RSR (r = 0.703, P < 0.001), body mass (r = -0.481, P < 0.01), body height (r = -0.430, P < 0.01), and CMJ height (r = 0.487, P < 0.01). Relative MSmax, CMJ height and RSR collectively explained 78.4% of the variance in ODH (R

Indexed as

AnthropometryBody HeightBody Mass IndexExercise TestMuscle StrengthAdolescentAthletesAthletic PerformanceCross-Sectional StudiesHumansMalePlyometric ExercisePredictive Value of TestsRegression AnalysisReproducibility of ResultsYoung AdultOptimal drop heightPlyometric trainingReactive strengthTraining intensity

Identifiers

PMID41917087

DOI10.1038/s41598-026-45266-x

PMCPMC13181053

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LicenceCC BY-NC-ND

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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.