Seeking psychological treatment for perinatal anxiety: Attitudes and preferences among pregnant, postpartum, and non-perinatal women
Bibliographic record
Abstract
Objective: Perinatal anxiety (PA) impacts 15 to 24.5% of women though treatment-seeking rates are low, despite various available and effective treatment options. The present study aimed to understand pregnant, postpartum, and non-perinatal women’s attitudes toward treatment-seeking and information needs regarding PA. Methods: Non-perinatal, pregnant, and postpartum women ages 18-40 in Central Canada completed an online survey (N = 200). Crosstabulation analyses illustrated differences in treatment preferences across groups. A one-way between-subjects ANOVA informed differences in attitudes toward psychological treatment-seeking across groups.Results: Across groups, women had positive attitudes toward psychological treatment seeking. Women endorsed a preference for PA support from peers and psychoeducation from their family doctor. Most women desired brief 1-page fact sheets on psychological and pharmacological treatment options during early pregnancy or pregnancy planning. Conclusion: Findings inform a need for evidence-based eHealth and in-person treatments for PA. Women have positive attitudes toward seeking such services and voiced a preference for information regarding treatment options to be delivered early in pregnancy. Practice Implications: Findings demonstrate a need for a unified national psychoeducation and treatment information resource to be developed and disseminated online. Such resources should be available early in pregnancy or pregnancy planning to prevent developing or worsening PA.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".