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Development of Boccia Throw Test Instrument for Athletes with Cerebral Palsy

2022· article· en· W4224235023 on OpenAlexvenueno aff
Rumi Iqbal Doewes, Islahuzzaman Nuryadin, Singgih Hendarto, Sapta Kunta Purnama

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2022
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsThrowingCerebral palsyCronbach's alphaAthletesReliability (semiconductor)Test (biology)Physical medicine and rehabilitationPsychologyComputer sciencePhysical therapyMedicineDevelopmental psychologyPsychometricsEngineeringPhysics

Abstract

fetched live from OpenAlex

Background: Boccia is an accuracy game for athletes with cerebral palsy. In a Boccia game, the players throw a red- or blue-colored leather ball towards a white-colored target ball called the jack. Points are awarded to the colored balls with the closest distance to the jack.
 Aims: This development research aims to design a Boccia throw test instrument for novice athletes with cerebral palsy and test the instrument's validity and reliability.
 Methods: We use research and development with a 6-step instrument development method by Gall, Gall, and Borg. The subject of this research was 20 novice Boccia athletes who completed six trials to test the validity and reliability of the test instrument. Analysis was conducted through corrected item-total correlation and Cronbach’s Alpha using SPSS.
 Results: This research has produced a boccia throwing test instrument for cerebral palsy athletes with a throwing target in the form of a circle diameter of 25 cm, which is placed 5 meters from the ball throwing area. This instrument has proven its validity and reliability based on the validity value on the corrected item-total correlation > 0.05 and the reliability value on Cronbach's alpha > 0.80.
 Conclusion: The resulting test instrument is valid and reliable to assess the Boccia throwing accuracy skill in novice players.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.206
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.126
GPT teacher head0.419
Teacher spread0.292 · 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
Published2022
Admission routes1
Has abstractyes

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