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Record W7117772279 · doi:10.3126/mrj.v6i1.88182

Competitive Sports Anxiety among Nepalese National Athletes: Differences by Gender, Sport Type, and Sporting Disciplines

2025· article· W7117772279 on OpenAlexaff
Diwakar Amatya, Rocky Maharjan, Kumari Hira Pant, Shreeram Bhandari, Chandan Koju

Bibliographic record

VenueMangal Research Journal · 2025
Typearticle
Language
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsInternational Health Economics Association
Fundersnot available
KeywordsAthletesAnxietyCompetitive athletesTest (biology)Competitive sport

Abstract

fetched live from OpenAlex

Sport psychology focuses on the influence of competitive anxiety on performance, despite a paucity of work with athletes in Nepal. The prevalent patterns of sports competition anxiety based on gender, sports type and sporting disciplines are examined in this study. The sample consisted of 496 athletes (281 males and 215 females) who participated in 21 events from the 9th National Games in Pokhara.Competitive anxiety was measured using the Sports Competition Anxiety Test (SCAT). Nonparametric statistical techniques were used as the anxiety scores violated normality assumptions. A Mann–Whitney U test indicated male and female athletes did not show statistically significant differences in anxiety (U = 29701.50, p = .749, r = 0.014). However, athletes competing in individual sportsreported significantly higher anxiety than compared to team events (U = 25813, p = .002, r = 0.14). A Kruskal–Wallis test revealed significant differences in anxiety across the 21 sports examined (H = 134.87, p < .001, η² = .27). Kabaddi, Kho- Kho and Archery athletes had the highest anxiety levels, while Football, Rugby and Volleyball athletes had the lowest ones. This implies that competitive anxiety in the athletes of Nepal is more affected not by gender but by sport type and sport-specific demands. The findings emphasize the requirement for targeted psychological assistance, especially for individual and precision-based sportsmen.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.081
GPT teacher head0.438
Teacher spread0.357 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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