A Probiotic Intervention With Bifidobacterium longum NCC3001 on Perinatal Mood Outcomes (PROMOTE Study): Protocol for a Decentralized Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Perinatal mood disorders such as depression and anxiety are common, with subclinical symptomology manifesting as perinatal mood disturbances being even more prevalent. These could potentially affect breastfeeding practices and infant development. Pregnant and lactating women usually limit their exposure to medications, including those for psychological symptoms. Interestingly, the naturally occurring probiotic Bifidobacterium longum (BL) NCC3001 has been shown to reduce anxious behavior in preclinical models and feelings of low mood in nonpregnant human adults. During the COVID-19 pandemic, mental health issues increased, and conventionally conducted clinical trials were restricted by social distancing regulations. OBJECTIVE: This study, Probiotics on Mothers' Mood and Stress (PROMOTE), aimed to use a decentralized clinical trial design to test whether BL NCC3001 can reduce symptoms of depression, anxiety, and stress over the perinatal period. METHODS: This double-blind, placebo-controlled, randomized, and 3-parallel-arm study aimed to recruit 180 women to evaluate the efficacy of the probiotic taken either during pregnancy and post partum (from 28-32 weeks' gestation until 12 weeks after delivery; n=60, 33.3%) or post partum only (from birth until 12 weeks after delivery; n=60, 33.3%) in comparison with a placebo control group (n=60, 33.3%). Participants consumed the probiotic or matched placebo in a drink once daily. Mood outcomes were measured using the State-Trait Anxiety Inventory and Edinburgh Postnatal Depression Scale questionnaires, captured electronically at baseline (28-32 weeks' gestation) and during e-study sessions over 5 further time points (36 weeks' gestation; 9 days post partum; and 4, 8, and 12 weeks post partum). Saliva and stool samples were collected longitudinally at home to provide mechanistic insights. RESULTS: In total, 520 women registered their interest on our website, of whom 184 (35.4%) were eligible and randomized. Of these 184 participants, 5 (2.7%) withdrew after randomization, leaving 179 (97.3%) who completed the study. Recruitment occurred between November 7, 2020, and August 20, 2021. Advertising on social media brought in 46.9% (244/520) of the prospective participants, followed by parenting-specific websites (116/520, 22.3%). Nationwide recruitment was achieved. Data processing is ongoing, and there are no outcomes to report yet. CONCLUSIONS: Multiple converging factors contributed to speedy recruitment and retention of participants despite COVID-19-related restrictions. This decentralized trial design sets a precedent for similar studies, in addition to potentially providing novel evidence on the impact of BL NCC3001 on symptoms of perinatal mood disturbances. This study was ideal for remote conduct: because of the high digital literacy and public trust in digital security in Singapore, the intervention could be self-administered without regular clinical monitoring, and the eligibility criteria and outcomes were measured using electronic questionnaires and self-collected biological samples. This design was particularly suited for a group considered vulnerable-pregnant women-during the challenging times of COVID-19-related social restrictions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04685252; https://clinicaltrials.gov/ct2/show/NCT04685252. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41751.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.012 |
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".