Ecological momentary assessment: what it is and why it is a method of the future in clinical psychopharmacology
Bibliographic record
Abstract
Current methods of assessment in clinical psychopharmacology have several serious disadvantages, particularly for the study of social functioning. We aimed to review the strengths and weaknesses of current methods used in clinical psychopharmacology and to compare them with a group of methods, developed by personality/social psychologists, termed ecological momentary assessment (EMA), which permit the research participant to report on symptoms, affect and behaviour close in time to experience and which sample many events or time periods. EMA has a number of advantages over more traditional methods for the assessment of patients in clinical psychopharmacological studies. It can both complement and, in part, replace existing methods. EMA methods will permit more sensitive assessments and will enable more wide-ranging and detailed measurements of mood and behaviour. These types of methods should be adopted more widely by clinical psychopharmacology researchers.
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 | 0.202 | 0.223 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".