Quasi‐experimental evaluation of a telephone‐based peer support intervention for maternal depression
Bibliographic record
Abstract
AIMS: To evaluate the effect of telephone-based peer support on maternal depression and social support BACKGROUND: Postpartum depression is a global health concern and lack of treatment options mean many mothers are depressed beyond the first year after birth. Strong evidence has shown telephone-based peer support, provided by a mother recovered from depression, effectively improves depression outcomes. This model has not been tested with mothers with depression any time up to two years postpartum. DESIGN: Quasi-experimental, one group pre-test, posttest. METHOD: The study population was mothers in New Brunswick, Canada with depression up to 24 months after delivery. The sample (N = 64) was recruited between May 2011-October 2013. Peer volunteers recovered from postpartum depression were trained and delivered an average of 8·84 (Range 1-13) support telephone calls. Depression and social support outcomes were assessed at intervention mid-point (average 7·43 weeks, n = 37) and end (average 13·9 weeks, n = 34). RESULTS: Mean depression significantly declined from baseline, 15·4 (N = 49), to mid-point, 8·30 and end of the study, 6·26. At mid-point 8·1% (n = 3/37) of mothers were depressed and at endpoint 11·8% (4/34) were depressed suggesting some relapse. Perceptions of social support significantly improved and higher support was significantly related with lower depression symptoms. CONCLUSION: Findings offer promise that telephone-based peer support is effective for both early postpartum depression and maternal depression up to two years after delivery.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".