Evidence map›Paper›PMID 41024127›Full record

ArticleBMC sports science, medicine & rehabilitation2025

Evaluating athletic mental energy analysis: a novel approach using fuzzy-based Bayesian networks.

Yasin Yildiz, Doğukan Batur Alp Gülşen, Umut Sevilmiş, Orkun Burak Öztürk

Abstract read
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Article in BMC sports science, medicine & rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yasin YildizFaculty of Sport Science, Department of Recreation, Aydın Adnan Menderes University, Aydın, Türkiye.
Doğukan Batur Alp GülşenFaculty of Sport Science, Department of Recreation, Aydın Adnan Menderes University, Aydın, Türkiye. dogukangulsen@adu.edu.tr.ORCID http://orcid.org/0000-0001-9434-619X
Umut SevilmişSchool of Physcial Education and Sports, 7 Aralık Kilis University, Kilis, Turkey.
Orkun Burak ÖztürkThe Faculty of Turgut Kıran Maritime, Recep Tayyip Erdogan University, Rize, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis paper focuses on the impact of physical and psychological conditions on athletes' mental energy, which is a serious concern in terms of performance and overall health and seeks to evaluate this problem by identifying its causes.

methodA Fuzzy Bayesian Network (FBN) model is therefore created to provide an approach for determining the factors and weights to be considered by coaches and sports scientists when assessing the causes of mental fatigue in athletes.

resultAs a result of the research process, a model for evaluating the factors affecting athletic mental energy was developed, and probabilistic relationships between physical and psychological causes were established. The analysis of the model indicates that physical fitness (10.9%), fatigue (10.4%), and nutrient intake (10.2%) are the three most significant root causes affecting athletic mental energy. In addition, the most obvious finding to emerge from this study is that the factors affecting athletic mental energy are closely related to both physical state and psychological state processes. Taken together, the results indicate that physical condition variables are too important to be overlooked in effectively enhancing athletes' mental energy.

conclusionConsequently, In conclusion, the FBN model developed for this study is considered to provide a comprehensive probabilistic analysis of the interactions between physical and psychological factors, and to serve as an important guide in identifying new ways to enhance athletes' mental energy.

Indexed as

AthletesAthletic mental energyFuzzy Bayesian network

Identifiers

PMID41024127
PMCPMC12482422

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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.