SSRI effects on pyschomotor performance: assessment of citalopram and escitalopram on normal subjects.
Bibliographic record
Abstract
INTRODUCTION: Standard aeromedical doctrine dictates that aircrew receiving treatment for depression are grounded during treatment and follow-up observation, generally amounting to at least 1 yr. The Canadian Forces has initiated a program to return selected aircrew being treated for depression to restricted flying duties once stabilized on an approved antidepressant with resolution of depression. The currently approved medications are sertraline (a selective serotonin reuptake inhibitor) and bupropion (noradrenaline and dopamine reuptake inhibitor). This study was undertaken to determine whether or not citalopram or escitalopram affect psychomotor performance. METHOD: In a double-blind crossover protocol with counter-balanced treatment order, 24 normal volunteer subjects (14 men and 10 women) were assessed for psychomotor performance during placebo, citalopram (40 mg), and escitalopram (20 mg) treatment. Each treatment arm lasted 2 wk, involving a daily morning ingestion of one capsule. There was a 1-wk washout period between medication courses. Subjects completed a drug side-effect questionnaire and were tested on three psychomotor test batteries once per week. RESULTS: Neither citalopram nor escitalopram affected serial reaction time, logical reasoning, serial subtraction, multitask, or MacWorth clock task performance. CONCLUSIONS: While we found some of the expected side effects due to citalopram and escitalopram, there was no impact on psychomotor performance. These findings support the possibility of using citalopram and escitalopram for returning aircrew to restricted flight duties (non-tactical flying) under close observation as a maintenance treatment after full resolution of depression.
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 | 0.000 |
| 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 | 0.000 |
| 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".