Kinesiophobia, Knee Self-Efficacy, and Fear Avoidance Beliefs in People with ACL Injury: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: To improve the understanding of the psychological impacts of anterior cruciate ligament (ACL) injury, a systematic review synthesizing the evidence on knee self-efficacy, fear avoidance beliefs and kinesiophobia following ACL injury is needed. OBJECTIVE: The aim of this systematic review was to investigate knee self-efficacy, fear avoidance beliefs and kinesiophobia following ACL injury, and compare these outcomes following management with rehabilitation alone, early and delayed ACL reconstruction (ACLR). METHODS: Seven databases were searched from inception to April 14, 2022. Articles were included if they assessed Tampa Scale of Kinesiophobia (TSK), Knee Self-Efficacy Scale (KSES), or Fear Avoidance Beliefs Questionnaire (FABQ). Risk of bias (RoB) was assessed using domain-based RoB tools (ROBINS-1, RoB 2, RoBANS), and GRADE-assessed certainty of evidence. Random-effects meta-analyses pooled outcomes, stratified by time post-injury (pre-operative, 3-6 months, 7-12 months, > 1-2 years, > 2-5 years, > 5 years). RESULTS: Seventy-three studies (70% high RoB) were included (study outcomes: TSK: 55; KSES: 22; FABQ: 5). Meta-analysis demonstrated worse kinesiophobia and self-efficacy pre-operatively (pooled mean [95% CI], TSK-11: 23.8 [22.2-25.3]; KSES: 5.0 [4.4-5.5]) compared with 3-6 months following ACLR (TSK-11: 19.6 [18.7-20.6]; KSES: 19.6 [18.6-20.6]). Meta-analysis suggests similar kinesiophobia > 3-6 months following early ACLR (19.8 [4.9]) versus delayed ACLR (17.2 [5.0]). Only one study assessed outcomes comparing ACLR with rehabilitation only. CONCLUSIONS: Knee self-efficacy and kinesiophobia improved from pre-ACLR to 3-6 months following ACLR, with similar outcomes after 6 months. Since the overall evidence was weak, there is a need for high-quality observational and intervention studies focusing on psychological outcomes following ACL injury.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".