Computerized ambulatory monitoring in psychiatry: a multi‐site collaborative study of acceptability, compliance, and reactivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Computerized ambulatory monitoring overcomes a number of methodological and conceptual challenges to studying mental disorders, however concerns persist regarding the feasibility of this approach with severe psychiatric samples and the potential of intensive monitoring to influence data quality. This multi-site investigation evaluates these issues in four independent samples. Patients with schizophrenia (n = 56), substance dependence (n = 85), anxiety disorders (n = 45), and a non-clinical sample (n = 280) were contacted to participate in investigations using computerized ambulatory monitoring. Micro-computers were used to administer electronic interviews several times per day for a one-week period. Ninety-five percent of contacted individuals agreed to participate in the study, and minimum compliance was achieved by 96% of these participants. Seventy-eight percent of all programmed assessments were completed overall, and only 1% of micro-computers were not returned to investigators. There was no evidence that missing data or response time increased over the duration of the study, suggesting that fatigue effects were negligible. The majority of variables investigated did not change in frequency as a function of study duration, however some evidence was found that socially sensitive behaviors changed in a manner consistent with reactivity.
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.
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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it