New perspectives for understanding depression during pregnancy. Prevalence and women's experiences of this disorder
Bibliographic record
Abstract
Depression during pregnancy is a potentially devastating mood disorder. Estimates of the number of women affected, however, have varied widely. Furthermore, how pregnant women manage depression and how they make decisions regarding the gestational use of antidepressant medication is a topic that has received little attention. The aim of the present research was two-fold: (1) to use a random effects meta-analytic model to estimate the prevalence of depression, as detected by validated screening instruments and structured interviews, for each trimester of pregnancy, and (2) to use grounded theory to develop a theoretical model that explained managing depression during pregnancy from the perspective of women who had experienced this disorder. Rates of depression during pregnancy are substantial. Structured interviews found lower rates than the Beck Depression Inventory but not the Edinburgh Postnatal Depression Scale. To facilitate women's decisions regarding antenatal depression treatment health systems should provide information about depression, antidepressants, and the prevalence and signs of postpartum depression. 1. A search for observational studies was conducted in MEDLINERTM from 1966, CINAHLRTM from 1982, EMBASERTM from 1980, and HealthSTARRTM from 1975. Of 714 articles identified, 21 (19,284 patients) met predefined acceptability criteria for inclusion in the meta-analysis. Prevalence rates and 95% confidence intervals (CI95%) were: 7.4% (2.2-12.6), 12.8% (10.7 to 14.8), and 12.0% (7.4-16.7) for the 1st, 2nd, and 3rd trimesters, respectively. 2. Nineteen women were recruited through a reproductive mental health program in Ontario. Data were collected during semi-structured interviews and analysed using constant comparative analysis. The theoretical model that explained the process of managing depression was becoming the best mom that I can. The model describes women's journeys from the depths of despair, where depression was perceived to threaten their pregnancy and ability to care for the coming baby, to their arrival at knowing the self and being in a better place. Six interrelated themes, perceived consequences of untreated depression, perceived neonatal adverse effects of antidepressant use, personal influences, interpersonal influences, societal influences, and availability of information, emerged as influencing women's decisions regarding the use of antidepressants. The dominance of each theme was determined by each woman's previous experience with depression.
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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 | 0.027 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".