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Confidence And Performance Asymmetries Are Related To Psychological Readiness Following Acl Reconstruction

2022· article· en· W4294798595 on OpenAlexaff
Brittany Bruinooge, Pete MacDonald, Sheila McRae, Dan Ogborn

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2022
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsPan Am Clinic
Fundersnot available
KeywordsConfidence intervalACL injuryAnterior cruciate ligamentAnterior cruciate ligament reconstructionMedicineReturn to sportInternal medicinePhysical therapyPhysical medicine and rehabilitationSurgeryRehabilitation

Abstract

fetched live from OpenAlex

PURPOSE: Emerging evidence indicates that injury-specific confidence and performance may be predictive for return to sport (RTS) in patients following anterior cruciate ligament reconstruction (ACLr), however how patient confidence varies across differing tasks remains to be determined. The purpose of this study was to examine self-reported task-specific confidence for three functional tasks and injury-specific psychological readiness (ACL-RSI: ACL-Return to Sport after Injury) in patients at 6-months post-ACLr. It was hypothesized that confidence would vary between limbs and tasks and that confidence would correlate with ACL-RSI and performance on the affected (Aff) limb. METHODS: 32 participants (20F:12M, 25.6 ± 8.5 yrs, 82.4 ± 22.2 kg, 176.2 ± 8.8 cm, ACL-RSI 50 ± 22%) completed the single leg hop (SLH), drop vertical jump (DVJ), 5-0-5 change of direction (COD) task, and the ACL-RSI questionnaire at 6-months following ACLr. Confidence was rated for both limbs (Aff, unaffected (UA)) after each task on an 11-point scale from “0” (no confidence) to “10” (full confidence). RESULTS: Confidence was lower on Aff limb for the SLH (Aff: median 6 (range 2-9), UA: 9 (6-10), p < 0.001), DVJ (Aff: 6 (3-9), UA: 10 (6-10), p < 0.001) and COD (Aff: 7 (2-10), UA: 9 (7-10), p < 0.001). Aff performance was reduced for the SLH (Aff: 88.3 ± 41.4 cm, UA: 117.7 ± 42.2 cm, p < 0.001), and DVJ (Aff: 1.6 ± 0.6 N/kg, UA: 2.30 ± 0.59 N/kg, p < 0.001), but COD times were marginally faster (Aff: 3.3 ± 0.5 s, UA: 3.4 ± 0.5 s, p = 0.047). Aff limb confidence for the SLH (ρ = 0.544, p = 0.001) and COD (ρ = 0.486, p = 0.005) were correlated with the ACL-RSI while the DVJ was not (ρ = 0.346, p = 0.052). Raw performance on both limbs for the SLH (Aff: ρ = 0.558, p = 0.001, UA: ρ = 0.565, p < 0.001) and COD (Aff: ρ = -0.643, p < 0.001, UA: ρ = -0.627, p < 0.001) correlated with the ACL-RSI but not for the DVJ or when any measure was expressed as a symmetry index (LSI; SLH rs = 0.167, p = 0.360; DVJ rs = -0.029, p = 0.877; COD rs = 0.127, p = 0.49). CONCLUSIONS: Asymmetries in confidence exist between limbs even when performance differences are minimal (COD). Aff task-specific confidence and unilateral performance (SLH and COD) correlate with the ACL-RSI to a higher degree than DVJ or performance LSIs. Task-specific confidence may be more reflective of readiness to RTS than traditional performance measures alone.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 science0.0000.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.313
Teacher spread0.296 · 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.

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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