Auricular Acupuncture for Exam Anxiety in Medical Students—A Randomized Crossover Investigation
Bibliographic record
Abstract
Auricular acupuncture (AA) is effective in the treatment of preoperative anxiety. The aim was to investigate whether AA can reduce exam anxiety as compared to placebo and no intervention. Forty-four medical students were randomized to receive AA, placebo, or no intervention in a crossover manner and subsequently completed three comparable oral anatomy exams with an interval of 1 month between the exams/interventions. AA was applied using indwelling fixed needles bilaterally at points MA-IC1, MA-TF1, MA-SC, MA-AT1 and MA-TG one day prior to each exam. Placebo needles were used as control. Levels of anxiety were measured using a visual analogue scale before and after each intervention as well as before each exam. Additional measures included the State-Trait-Anxiety Inventory, duration of sleep at night, blood pressure, heart rate and the extent of participant blinding. All included participants finished the study. Anxiety levels were reduced after AA and placebo intervention compared to baseline and the no intervention condition (p < 0.003). AA was better at reducing anxiety than placebo in the evening before the exam (p = 0.018). Participants were able to distinguish between AA and placebo intervention. Both AA and placebo interventions reduced exam anxiety in medical students. The superiority of AA over placebo may be due to insufficient blinding of participants.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".