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Record W7115576472 · doi:10.47197/retos.v76.117507

Group cohesion in football: a scoping review and bibliometric analysis (1996-2024)

2025· article· en· W7115576472 on OpenAlexaboutno aff

Bibliographic record

VenueRetos · 2025
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)ScopusGroup cohesivenessEliteSample (material)BibliometricsFootball

Abstract

fetched live from OpenAlex

Introduction: Group cohesion, understood as the dynamic process that reflects a team’s tendency to remain united in the pursuit of common goals and achieving the socio-affective needs of its members, is a decisive factor for performance in team sports. In football, however, while technical and tactical advances are extensively documented, human and social dimensions remain less explored, resulting in a fragmented body of literature. Objective: To map and analyse the scientific production on group cohesion in football published between 1996 and 2024. Methodology: A scoping review supported by bibliometric techniques was conducted using data collected from Scopus and Web of Science. Sixty-four articles were identified and examined with regard to temporal evolution, authorship networks, journals, instruments employed, geographical distribution, and sample characteristics. Results: Studies predominantly involved male youth samples, with limited participation of coaches and elite clubs. The scientific output also revealed temporal trends and networks of collaboration among authors, with greater concentration in Spain and Canada. Discussion: The findings confirm the fragmented nature of the field and the under-representation of women’s and elite-level football, contrasting with the recognised importance of cohesion for sporting success. Conclusions: Significant gaps were identified in the literature, reinforcing the need to broaden methodological and sample diversity. This study provides a comprehensive overview to guide future research and support team management strategies, such as the systematic application of validated instruments.

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)0.037
metaresearch head score (Gemma)0.134
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.773
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.134
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.2270.192
Science and technology studies0.0030.002
Scholarly communication0.0080.006
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.401
Teacher spread0.368 · 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.

Study designSystematic review
Domainnot available
GenreReview

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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