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Record W4391744040 · doi:10.3390/healthcare12040463

Adaptive Shooting Disciplines: A Scoping Review of the Literature with Bibliometric Analysis

2024· review· en· W4391744040 on OpenAlexaff
Luca Puce, Carlo Biz, Halil İ̇brahim Ceylan, Nicola Luigi Bragazzi, Matteo Formica, Khaled Trabelsi, Łukasz Szarpak, Carlo Trompetto, Alessandro Rossin, Nicola Antonio Lanciano, Pietro Ruggieri

Bibliographic record

VenueHealthcare · 2024
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsYork University
Fundersnot available
KeywordsScopusExcellenceComputer scienceWeb of scienceApplied psychologyData sciencePsychologyMEDLINEEngineering ethicsManagement sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

Para-archery and para-shooting, two very popular adaptive shooting disciplines that have earned their place as major official events in the Paralympic Games, share some similarities, as well as distinctive features in terms of rules, physiological requirements, and equipment used. The International Paralympic Committee has a clear responsibility to ensure that all sports within its jurisdiction, including adaptive shooting, can achieve excellence in their respective fields. To achieve this, the conduct of well-designed studies and rigorous research is essential. Although some research has been conducted in this area, a comprehensive and systematic evaluation is still needed. Therefore, the present study aims to provide a thorough review and synthesis of existing research on adaptive shooting disciplines, identify strengths and gaps, and suggest future directions. Arksey and O'Malley's methodology is leveraged and enhanced with bibliometric and policy analyses to review literature on adaptive shooting. Databases like PubMed/MEDLINE, Scopus, Web of Science, OvidSP, and EMBASE were searched, focusing on studies in adaptive shooting disciplines and analysing these findings through a blend of thematic and statistical methods. Twenty-four studies totalling 483 para-athletes (299 para-shooters and 184 para-archers) are included in this scoping review, focusing on a range of aspects, including physiological responses (n = 9), research design and measurement methods for evidence-based classification (n = 6), biopsychosocial aspects (n = 3), development of new methods and technologies (n = 4), kinematic and biomechanical assessment (n = 1), and epidemiology of injuries (n = 1). Seven articles focused exclusively on para-archery, thirteen exclusively on para-shooting, and four on both para-archery and para-shooting. In conclusion, the available literature on adaptive shooting disciplines is still very limited, especially regarding para-archery compared to para-shooting. This highlights the need for further research in many key areas to ensure a better understanding of the different disciplines and to provide appropriate support for para-athletes. Future research in para-archery and para-shooting should focus on technological innovations, biomechanical studies, and psychological support to enhance athlete performance and accessibility. Addressing the imbalance between the two disciplines, along with injury prevention and global participation, can drive the sports towards greater inclusivity and equity for para-athletes worldwide.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.375
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0200.231
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.462
Teacher spread0.380 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review · Other design
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

Citations4
Published2024
Admission routes1
Has abstractyes

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