Promoting mental wellbeing in pregnant women living in Pakistan with the Safe Motherhood—Accessible Resilience Training (SM-ART) intervention: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The negative impact of adverse perinatal mental health extends beyond the mother and child; therefore, it is essential to make an early intervention for the management of mental illness during pregnancy. Resilience-building interventions are demonstrated to reduce depression and anxiety among expectant mothers, yet research in this field is limited. This study aims to examine the effect of the 'Safe Motherhood-Accessible Resilience Training (SM-ART)' on resilience, marital adjustment, depression, and pregnancy-related anxiety in a sample of pregnant women in Karachi, Pakistan. METHOD: In this single-blinded block randomized controlled study, 200 pregnant women were recruited and randomly assigned to either an intervention or a control group using computer-generated randomization and opaque sealed envelopes. The intervention group received the SM-ART intervention consisting of six, weekly sessions ranging from 60 to 90 min. Outcomes (Resilience, depression, pregnancy-related anxiety and marital harmony) were assessed through validated instruments at baseline and after six weeks of both intervention and control groups. RESULTS: The results revealed a significant increase in mean resilience scores (Difference:6.91, Effect size: 0.48, p-value < 0.05) and a decrease in depressive symptoms (Difference: -2.12, Effect size: 0.21, p-value < 0.05) in the intervention group compared to the control group. However, no significant change was observed in anxiety and marital adjustment scores. CONCLUSION: The SM-ART intervention has the potential to boost resilience scores and decrease depressive symptoms in pregnant women and offers a promising intervention to improve maternal psychological health. TRIAL REGISTRATION: NCT04694261, Date of first trial registration: 05/01/2021.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".