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Record W4406426055 · doi:10.2196/66979

Assessing the Impact of a Virtual Reality Cognitive Intervention on Tennis Performance in Junior Tennis Players: Pilot Study

2025· article· en· W4406426055 on OpenAlexvenueno aff
Joaquin A. Anguera, Michael Seaman, Dominick Fedele

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychological interventionPsychologyIntervention (counseling)Cognitive trainingRandomized controlled trialExecutive functionsPhysical therapyMedicine

Abstract

fetched live from OpenAlex

Background There is evidence that cognitive training interventions can positively impact executive functions, and that some studies have demonstrated that athletes typically exhibit greater accuracy and faster response times on select cognitive tasks. While the engagement of executive functions is suggested to be part of high-level sporting activities, it is unclear whether such training approaches could directly benefit athletic performance. Objective The objective of this study was to evaluate the impact of a combined virtual reality (VR)– and tablet-based cognitive training intervention on adolescent tennis players’ performance. Here, we examined differences in Universal Tennis Rating (UTR) between players who supplemented their regular tennis training with a cognitive training intervention and a group that continued regular tennis training alone. This custom cognitive training program targeted specific cognitive control abilities including attention, working memory, and goal management. Methods Data were collected from a cohort of tennis players in a randomized controlled trial design led by the dedicated research team. Participants (N=23, age: mean 14.8, SD 2.4 years) from the Czech Lawn Tenis Klub (Prague, Czech Republic) were invited to participate in this study. These individuals were randomized into an intervention + training-as-usual group (n=13) or training-as-usual group (control group; n=10), with the change in UTR score being the primary metric of interest. Results There was no difference in UTR between the 2 groups at baseline (intervention: mean 8.32, SD 2.7; control: mean 7.60, SD 2.3). Following the treatment period, individuals in the intervention group showed a significant improvement in their UTR (an increase of 0.5; t12=4.88, P<.001) unlike the control group (an increase of 0.02; t9=1.77, P=.12). On comparing the change in UTR (posttraining UTR minus pretraining UTR) attained by each group, we found that the intervention group had a 38% greater improvement in UTR than the control group. An analysis of covariance revealed a significantly greater improvement in UTR for the intervention group than for the control group (F1,20=8.82, P=.008). Conclusions The present findings suggest that training cognitive abilities through an immersive visual platform may benefit athletic performance, including tennis. Such a result warrants careful consideration, given the known difficulties in evidencing far transfer not only in cognitive studies but also in athletic activities. These preliminary pilot findings suggest that the Mastermind Cognitive Training program may be a viable tool for supplementing athletic training practices, although this result warrants further investigation and replication. However, many questions remain unanswered, and further work is needed to better understand the potential utility and mechanisms underlying potential effects of such a platform.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.182
GPT teacher head0.566
Teacher spread0.384 · 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 designNon-randomized trial
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

Citations3
Published2025
Admission routes1
Has abstractyes

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