May the force be with you: understanding how patellofemoral joint reaction force compares across different activities and physical interventions—a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To systematically review and synthesise patellofemoral joint reaction force (PFJRF) in healthy individuals and those with patellofemoral pain and osteoarthritis (OA), during everyday activities, therapeutic exercises and with physical interventions (eg, foot orthotics, footwear, taping, bracing). DESIGN: A systematic review with meta-analysis. DATA SOURCES: Medline, Embase, Scopus, CINAHL, SportDiscus and Cochrane Library databases were searched. ELIGIBILITY CRITERIA: Observational and interventional studies reporting PFJRF during everyday activities, therapeutic exercises, and physical interventions. RESULTS: In healthy individuals, the weighted average of mean (±SD) peak PFJRF for everyday activities were: walking 0.9±0.4 body weight (BW), stair ascent 3.2±0.7 BW, stair descent 2.8±0.5 BW and running 5.2±1.2 BW. In those with patellofemoral pain, peak PFJRF were: walking 0.8±0.2 BW, stair ascent 2.5±0.5 BW, stair descent 2.6±0.5 BW, running 4.1±0.9 BW. Only single studies reported peak PFJRF during everyday activities in individuals with patellofemoral OA/articular cartilage defects (walking 1.3±0.5 BW, stair ascent 1.6±0.4 BW, stair descent 1.0±0.5 BW). The PFJRF was reported for many different exercises and physical interventions; however, considerable variability precluded any pooled estimates. SUMMARY: Everyday activities and exercises involving larger knee flexion (eg, squatting) expose the patellofemoral joint to higher PFJRF than those involving smaller knee flexion (eg, walking). There were no discernable differences in peak PFJRF during everyday activities between healthy individuals and those with patellofemoral pain/OA. The information on PFJRF may be used to select appropriate variations of exercises and physical interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.166 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.033 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".