Screening for Perinatal OCD: A Comparison of the DOCS and the EPDS
Bibliographic record
Abstract
Screening for perinatal-occurring obsessive-compulsive disorder (OCD) is rare. We sought to evaluate the Dimensional Obsessive-Compulsive Scale (DOCS) as a screening tool for perinatal OCD and compare the screening accuracy of the DOCS with the commonly recommended Edinburgh Postnatal Depression Scale (EPDS). English-speaking, pregnant individuals aged 19+ ( N = 574) completed online questionnaires and diagnostic interviews to assess for OCD prenatally and twice postpartum. The DOCS total score demonstrated the highest level of accuracy. Neither the EPDS-Full nor the three-item Anxiety subscale of the EPDS (EPDS-3A) met the criteria of a sufficiently accurate screening tool for OCD at any of the assessment points. Findings provide support for the DOCS as a screening tool for perinatal OCD and indicate a need for disorder-specific screening for perinatal anxiety and their related disorders (AD). Generalizability of findings is limited to Canada only. Future research would benefit from comparisons with measures of perinatal OCD (e.g., the Perinatal Obsessive-Compulsive Scale).
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".