Reporting bias, not external focus
Bibliographic record
Abstract
Evidence has ostensibly been accumulating over the past two decades suggesting that an external focus on the intended movement effect (e.g., on the golf club during a swing) is superior to an internal focus on body movements (e.g., on your arms during a swing) for skill acquisition. Seven previous meta-studies have all reported evidence of external focus superiority. The most comprehensive of these concluded an external focus enhances motor skill retention, transfer, and performance, leads to reduced eletromyographic activity during performance, and that more distal external foci are superior to proximal external foci for performance. Here, we re-analyzed these data using robust Bayesian meta-analyses that included several plausible models of publication bias. We found moderate to strong evidence of publication bias for all analyses. After correcting for publication bias, estimated mean effects were negligible: g = 0.01 (performance), g = 0.15 (retention), g = 0.09 (transfer), g = 0.06 (electromyography), and g = -0.01 (distance effect). Bayes factors indicated data favored the null for each analysis, ranging from BF01 = 1.3 (retention) to 5.75 (performance). We found clear evidence of heterogeneity in each analysis, suggesting the impact of attentional focus depends on yet unknown contextual factors. Our results contradict the existing consensus that an external focus is always more effective than an internal focus. Instead, focus of attention appears to have a variety of effects that we cannot account for, and on average those effects are small to nil. These results parallel previous metascience suggesting publication bias has obfuscated the motor learning literature.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".