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Record W1516404509 · doi:10.1111/sms.12214

Training distress and performance readiness: Laboratory and field validation of a brief self‐report measure

2014· article· en· W1516404509 on OpenAlexaff
Bob Grove, Luana C. Main, Kate Alexandra Partridge, David J. Bishop, Simon Russell, A. Shepherdson, Leah Ferguson

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDistressPhysical therapyRandomized controlled trialMedicineInterval trainingPsychologyClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

Three studies were conducted to validate the Training Distress Scale (TDS), a 19-item measure of training-related distress and performance readiness. Study 1 was a randomized, controlled laboratory experiment in which a treatment group undertook daily interval training until a 25% decrement occurred in time-to-fatigue performance. Comparisons with a control group showed that TDS scores increased over time within the treatment group but not in the control group. Study 2 was a randomized, controlled field investigation in which performance capabilities and TDS responses were compared across a high-intensity interval training group and a control group that continued normal training. Running performance decreased significantly in the training group but not in the control group, and scores on the TDS mirrored those changes in performance capabilities. Study 3 examined the relationship between TDS scores obtained over a 2-week period before major swimming competitions and subsequent performance in those competitions. Significantly, better performance was observed for swimmers with low TDS scores compared with those with moderate or high TDS scores. These findings provide both laboratory and field evidence for the validity of the TDS as a measure of short-term training distress and performance readiness.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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

Citations41
Published2014
Admission routes1
Has abstractyes

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