The effect of physician‐based cognitive behavioural therapy among pregnant women with depressive symptomatology: a pilot quasi‐experimental trial
Bibliographic record
Abstract
OBJECTIVE: The purpose of this pilot study is to evaluate the feasibility of a physician-based cognitive behavioural (CBT) intervention for the treatment of depressive symptomatology among pregnant women. METHODS: A pilot quasi-experimental trial was conducted in a family practice health centre in Toronto, Canada. Pregnant women (n = 42) were identified as having depressive symptomatology according to the Edinburgh Postnatal Depression Scale (EPDS) and allocated to either a control group (standard prenatal) or an intervention group. The intervention group received standard prenatal plus brief CBT, initiated between the 20th and 28th gestation week prenatal visit, from their obstetrical physician. Follow-up assessments were conducted at 38 weeks gestation and 6 weeks post-partum to examine depressive symptomatology, anxiety symptomatology, health-care utilization, medication utilization and overall treatment satisfaction. RESULTS: The delivery of the CBT intervention was feasible, acceptable and produced relatively high rates of treatment adherence. Of the 21 women in the intervention group who evaluated their CBT experience, 90% were satisfied. Although not sufficiently powered to detect differences between the study groups, trends in the clinical outcome data favoured the intervention group where mean depression and anxiety scores were lower for those who received the brief CBT intervention than those in the control group. CONCLUSION: Results suggest that brief physician-based CBT may be a feasible antenatal depression treatment option. The high satisfaction with, and acceptance of, the intervention by study participants and physicians suggests that a larger randomized trial is warranted.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".