The Enactment Effect: A Systematic Review and Meta-Analysis of Behavioral, Neuroimaging, and Patient Studies
Bibliographic record
Abstract
The enactment effect is the phenomenon that physically performing an action represented by a word or phrase (e.g., clap; clap your hands) results in better memory than does simply reading it. We examined data from three different methodological approaches to provide a comprehensive review of the enactment effect across 145 behavioral, 7 neuroimaging, and 31 neurological patient studies. Boosts in memory performance following execution of a physical action were compared to those produced by reading words or phrases, by watching an experimenter perform actions, or by engaging in self-generated imagery. Across the behavioral studies, we employed random-effects meta-regression with robust variance estimation to reveal an average enactment effect size of g = 1.23. Further meta-analyses revealed that variations in study design and comparison task reliably influence the size of the enactment effect, whereas four other experiment factors—test format, learning instruction type, retention interval, and the presence of objects during encoding—likely do not influence the effect. Neuroimaging studies demonstrated enactment-related activation to be prevalent in the motor cortex and inferior parietal lobule. Patient studies indicated that, regardless of whether impairments of memory (e.g., Alzheimer’s) or of motor capability (e.g., Parkinson’s) were present, patients were able to benefit from enactment. The findings of this systematic review and meta-analysis highlight two components accounting for the memory benefit from enactment: a primary mental contribution relating to planning of actions and a secondary physical contribution of the action itself.
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 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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".