Studying the incidence of depression: an ‘interval’ effect
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
Abstract A review of studies about the incidence of depression suggested that the length of the ‘interval’ of follow up may influence the findings. Exploration of these issues is carried out using data from the Stirling County Study, an investigation of psychiatric epidemiology in a general population. The study's customary method of diagnosis, DePression and AnXiety (DPAX), and the Diagnostic Interview Schedule (DIS) were used in an incidence investigation whose ‘interval’ was less than three years. Average annual incidence rates of depression for both DPAX and DIS were about 15 per 1000. Where longer intervals were used in the Stirling Study, rates were close to four per 1000. Projected lifetime risk based on the lower rates was more congruent with reported lifetime prevalence than that based on the higher rates. Irrespective of method, 90% or more of the incident cases gave an onset that predated the initial interview, suggesting poor reliability. This was often due to the fact that information given in the first interview met some but not all of the criteria for diagnosis. Being in the ‘borderline’ category at the beginning of the study significantly increased incidence. Thus, evidence from the Stirling County Study replicated findings that suggest an ‘interval effect’ and pointed to the need in incidence studies for distinguishing between the onset of the prodrome and the onset of diagnosable depression. Copyright © 2000 Whurr Publishers Ltd.
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 | 0.040 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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