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Record W4391126423 · doi:10.16926/par.2024.12.07

The effect of length of sport experience on the prevalence of non-specific back pain and injury in soccer and ice hockey

2024· article· en· W4391126423 on OpenAlexaboutno aff
Alena Buková, Magdaléna Hagovská, Zuzana Kovačíková, Klaudia Zusková, Tomasz Pączkowski, Ladislav Kručanica

Bibliographic record

VenuePhysical Activity Review · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsIce hockeyPhysical therapyPsychologySports injuryPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Background: Back pain is one of the most common health problems not only in the general population but also in athletes. However, there is a lack of evidence-based findings on the dose-response effect of athletic training on back pain and injuries. The aim of this study was to determine whether training experience affects the intensity of back pain and the number of injuries in moderate-to-high performance team sport athletes. Methods: A total of 147 male soccer players (age 27.8 ± 5.9 y; training experience 17.2 ± 5.6 y) and 179 male ice hockey players (age 29.2 ± 5.9 y; training experience 20.5 ± 6.1 y) were asked to complete questionnaires focusing on back pain and injuries: Oswestry Disability Index (ODI) and McGill Pain Questionnaire (MPQ). Results: Spearman correlation analysis revealed significant positive associations between length of training experience and the occurrence of thoracic pain (p=0.005), low back pain (p=0.016), thoracic injuries (p=0.006), and ODI (p=0.007) in soccer players. In hockey players, training duration was significantly correlated with low back pain (p<0.001) and injuries (=0.006), ODI (p<0.001), affective dimension (p<0.001), evaluative dimension (p=0.002), miscellaneous dimension (p=0.027), and total MPQ (p=0.029). Conclusions: The results of this study suggest that the length of training experience is another important factor influencing low back pain. Therefore, it is necessary to focus more attention on more experienced players and to include significantly more compensatory exercises and recovery time in their training process.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.160

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.324
Teacher spread0.310 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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