ArticleTranslational sports medicine2024
Longitudinal Monitoring of Biomechanical and Psychological State in Collegiate Female Basketball Athletes Using Principal Component Analysis.
Article in Translational sports medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Tracking Recovery in Motion: Longitudinal, Multi-Contextual Monitoring of Return-to-Play in Collegiate Basketball.Sensors (Basel, Switzerland) · 2026Article
- Multivariate Neuromuscular Profile and Principal Component Analysis: A Pilot Study in Professional Female Soccer Players.Life (Basel, Switzerland) · 2026Article
- Participant-Aware Model Validation for Repeated-Measures Data: Comparative Cross-Validation Study.JMIR AI · 2026Article
- Monitoring of internal load, sleep, and well-being in relation to injury and illness in professional basketball.BMC sports science, medicine & rehabilitation · 2026Article
- Enhancing psychological resilience and decision-making in basketball players through emerging technologies.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The growth in participation in collegiate athletics has been accompanied by increased sport-related injuries. The complex and multifactorial nature of sports injuries highlights the importance of monitoring athletes prospectively using a novel and integrated biopsychosocial approach, as opposed to contemporary practices that silo these facets of health. Methods: Data collected over two competitive basketball seasons were used in a principal component analysis (PCA) model with the following objectives: (i) investigate whether biomechanical PCs (i.e., on-court and countermovement jump (CMJ) metrics) were correlated with psychological state across a season and (ii) explore whether subject-specific significant fluctuations could be detected using minimum detectable change statistics. Weekly CMJ (force plates) and on-court data (inertial measurement units), as well as psychological state (questionnaire) data, were collected on the female collegiate basketball team for two seasons. Results: While some relationships ( Conclusion: Overall, this work demonstrates the potential of advanced analytical modeling to characterize components of and detect statistically and clinically relevant fluctuations in student-athlete performance, health, and well-being and the need for more tailored and athlete-centered monitoring practices.
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Registered trials
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.