One‐Day Online CBT Intervention for Postpartum Depression: Subjective Experiences and Pre‐Post Symptom Severity
Bibliographic record
Abstract
ABSTRACT Purpose Postpartum depression (PPD) affects about 17% of parents after childbirth and can have adverse effects on individuals, families and offspring. Parents with PPD frequently encounter significant barriers to tailored health care that make timely access to treatment difficult. Methods Twenty‐nine help‐seeking German parents of at least one child (< 1 year old) and with symptoms of depression participated in a synchronous 1‐day online cognitive behavioural therapy (CBT) group intervention. Following a mixed‐methods approach, intervention acceptance and preferences were evaluated using semi‐structured interviews conducted 2 weeks post‐intervention. Analyses were performed via qualitative content analysis. Severity of depressive symptoms were assessed via the Edinburgh Postnatal Depression Scale (EPDS) 1 week before and 4 weeks after the intervention. Results Twenty‐one interviews were conducted. Most participants rated the workshop as overall helpful (n = 164, 72.57%), with workshop characteristics, such as the online format (n = 112; 68.29%) and structure (n = 15; 20.55%) being most helpful. Expectations were mostly content‐related (n = 25; 52.08%), and 80% (n = 20) of expectations were met (e.g. regarding self‐help strategies being taught or deepening of existing knowledge). Two weeks after participation, the majority of parents were still applying intervention techniques in their daily lives (n = 42; 77.78%). Depressive symptoms were also significantly reduced at post‐measurement (t = 3159; p = 0.004; d = 0.608). Conclusions The 1‐day online CBT group intervention is easily accessible and could support parents after birth by teaching cognitive behavioural strategies to cope with symptoms of PPD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".