Uriclarity Program Reduces Perceived Insufficient Milk Supply in Early Postpartum: Randomized Controlled Trial

Uriclarity Program Reduces Perceived Insufficient Milk Supply in Early Postpartum: Randomized Controlled Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Uriclarity Program Reduces Perceived Insufficient Milk Supply in Early Postpartum: Randomized Controlled Trial Jackeline Ashiyama Vega, Mario Yrigoyen Rojas, Javier Ravichagua Ashiyama This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8634552/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Perceived insufficient milk supply (PIMS) is a common early postpartum concern; this study tested whether a brief predischarge program (Uriclarity) reduces PIMS in the early postpartum period. Methods: Parallel-group, superiority, single-blind randomized trial (1:1; computer-generated simple randomization; allocation concealment with sequentially numbered opaque sealed envelopes). Outcome assessors and the data analyst were blinded. Conducted in three public hospitals in Piura, Peru. Participants were postpartum women ≥18 years, 24–48 h after term birth, exclusively breastfeeding. Interventions: Uriclarity—2-hour in-person educational workshop during discharge plus standardized WhatsApp messages/videos through the first two days after the workshop—versus routine pre-discharge breastfeeding counseling. Primary outcome was PIMS (MILQ, 0–8; higher = better perceived sufficiency) on days 1, 3, 7, and 14. Between-group comparisons used the Wilcoxon rank-sum test; the prespecified primary analysis was a cumulative-link proportional-odds mixed model (random intercept), adjusted for maternal age, parity, and education; intention-to-treat. Results: Of 114 screened, 100 were randomized (54 intervention; 46 control) and all were analyzed. At each follow-up, medians favored the intervention (all p < 0.001); typical Hodges–Lehmann difference +2.00 points (95% CI 1.00–2.00 to 1.00–3.00). By day 14, 83.3% (40/48) vs 30.2% (13/43) achieved MILQ ≥ 7 (RD +53.1 pp; NNT = 2). The adjusted mixed model showed markedly higher odds of being in a better MILQ category with Uriclarity (OR 10.64, 95% CI 4.26–26.58; p < 0.001). No intervention-related harms occurred. As a secondary finding, the AUS showed modest ROC discrimination (AUC 0.60–0.69) with high sensitivity at AUS ≤ 2. Conclusions: A brief, low-cost program embedded in the discharge workflow produced large, consistent reductions in PIMS over two postpartum weeks. Larger multicenter trials with longer follow-up and hard breastfeeding outcomes are warranted. Trial registration: ClinicalTrials.gov NCT06857461 (prospective; registered February 26, 2025). Breastfeeding Breastfeeding Exclusive Self Efficacy Postpartum Period Text Messaging Mobile Applications Randomized Controlled Trial Figures Figure 1 Key Message Uriclarity, a brief predischarge breastfeeding program combining a 2-hour interactive workshop with four days of WhatsApp messages, substantially reduced perceived insufficient milk supply during the first two postpartum weeks. Compared with routine counseling, mothers in public hospitals who received Uriclarity had about tenfold higher odds of being in a better MILQ category, with a typical 2-point improvement on the 0–8 scale and an NNT of about 2 to achieve MILQ ≥7 by day 14. No intervention-related harms were reported, representing a large, clinically meaningful benefit. The Uriclarity Program trains mothers to interpret neonatal urine color using the AUS as a simple, home-based indicator of milk transfer. Across follow-up, higher AUS scores were associated with poorer perceived milk sufficiency, and an AUS threshold ≤2 showed high sensitivity for identifying mothers with low PIMS (MILQ ≥7), though specificity remained modest. In practice, AUS can function as a sensitive triage and self-monitoring tool that reinforces maternal confidence, prompts early counseling when values are high, and supports timely correction of breastfeeding problems. Uriclarity was designed for routine use in resource-constrained public hospitals and integrated seamlessly into the discharge workflow, delivered by existing midwives or nurses using low-cost materials and standard smartphones. Because its effect did not depend on maternal age, parity or education, the program appears broadly applicable to diverse postpartum populations. Health systems seeking to improve early exclusive breastfeeding could adopt Uriclarity as a scalable quality-improvement strategy, strengthening discharge education and remote follow-up without creating new services, infrastructure, or substantial additional staffing costs. This trial provides experimental evidence that directly targets perceived insufficient milk supply as a primary outcome in a middle-income setting. Future research should test Uriclarity in larger, multicenter studies with longer follow-up, measuring exclusive breastfeeding duration, infant growth, and maternal mental health. Adaptations using other digital platforms, community health workers, or group tele-sessions could be evaluated. Policymakers and researchers should also explore how integrating AUS-based triage into postnatal care pathways might optimize early identification and management of breastfeeding difficulties. Background Optimal breastfeeding could save more than US$300 billion annually (Rollins et al., 2016; Walters et al., 2019) and avert 823,000 child deaths and >20,000 maternal deaths from breast cancer each year (Victora et al., 2016). Yet as of 2024, only 46% of newborns are breastfed within the first hour of life, 48% of infants under six months receive exclusive breastfeeding, and 46% of two-year-olds continue breastfeeding (UNICEF & World Health Organization, 2024). In the Americas and the Caribbean, 52% of neonates initiate breastfeeding in the first hour and 43% of infants under six months are exclusively breastfed (UNICEF Data, 2025). In Peru (2024), 47.6% of newborns initiated breastfeeding within the first hour, and 67.4% of infants under six months received breastfeeding—without disaggregation for exclusive breastfeeding (Instituto Nacional de Estadística e Informática, 2024). The WHO’s 2030 targets are 70% early initiation and 70% exclusive breastfeeding under six months (UNICEF & World Health Organization, 2024). The early postpartum period is critical for sustaining exclusive breastfeeding, and perceived insufficient milk supply (PIMS) is a leading reason for formula supplementation and early weaning (Olalere & Harley, 2024; Odom et al., 2013). PIMS consistently ranks among the top three causes of breastfeeding cessation during the first year, commonly affecting 43–65% of mothers depending on age at weaning (Li et al., 2008; Whipps & Demirci, 2021), and in some settings up to 80% report PIMS at some point (Huang et al., 2022). True primary hypogalactia is rare, yet the belief of low milk supply strongly undermines exclusive breastfeeding (Galipeau et al., 2017; Huang et al., 2022). Although PIMS has been widely described, there remains a gap in rigorous, scalable interventions to prevent or correct it (Galipeau et al., 2018; Demirci et al., 2020). Many prior studies have limited inferential capacity due to small samples, lack of comparators, or short follow-up (Galipeau et al., 2018). Several approaches are impractical in resource-constrained environments and rely on objective milk intake measures that are difficult to implement outside controlled settings (International Atomic Energy Agency, 2010; Kent et al., 2015). Moreover, interventions often minimize mothers’ active participation despite recommendations emphasizing maternal self-efficacy in preventing or reversing PIMS (World Health Organization, 2018; Dennis, 2003; McGovern et al., 2024). To address these gaps, we conducted a randomized, controlled, single-blind clinical trial that evaluated the effect of Uriclarity, a low-cost program that empowered mothers to pre-empt uncertainty about milk production by recognizing early warning signs and receiving standardized anticipatory virtual guidance to manage breastfeeding challenges at home. The study also introduced the Uriscale (AUS, see Supplementary Materials), a simple, novel tool enabling mothers to estimate milk transfer from neonatal urine color. Objectives The trial evaluated whether Uriclarity—a brief predischarge workshop plus standardized follow-up messages—was superior to usual counseling in reducing PIMS among postpartum women receiving care in public hospitals in Piura, Peru, during the early postpartum period (days 2–14). The primary outcome was PIMS severity measured with the MILQ (Maternal Insufficient Lactation Questionnaire, see Supplementary Materials) and analysed using a prespecified ordinal mixed-effects model over days 2–14. Secondary objectives The trial estimated the effect of Uriclarity on MILQ ≥ 7 (low PIMS) using a mixed logistic model as a sensitivity analysis; described the time trajectory of MILQ scores by group; assessed safety as maternal and neonatal adverse events related to the intervention during the 14-day follow-up; and estimated the diagnostic performance of the AUS to identify MILQ ≥ 7 (AUC, sensitivity, specificity, and Youden’s index). Methods Trial design and setting Patients and the public were not involved in the design, conduct, or reporting of the trial. This was a two-arm, parallel-group randomized superiority trial with 1:1 allocation to the Uriclarity Program or standard care. No protocol changes were made after commencement. The study was conducted in three public hospitals in Piura, Peru: Hospital Reátegui, Hospital Santa Rosa, and Hospital Cayetano Heredia. The study was approved by the Ethics Committee of Hospital Daniel Alcides Carrión and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to enrollment. Participants, sites, and providers Eligible participants were women ≥18 years, recruited 24–48 hours postpartum (vaginal or cesarean) with term newborns (37–41 weeks), exclusively breastfeeding, having at least completed primary education, and able to use a smartphone with WhatsApp. Exclusion criteria included maternal factors affecting lactation (e.g., flat/inverted nipples, diabetes, hypertension, morbid obesity, endocrine disorders), interfering medications, and active smoking, as well as newborn conditions such as congenital heart disease, cleft lip/palate, ankyloglossia, neonatal hypoglycaemia, or ≥7% in-hospital weight loss. Sites were public facilities providing routine postpartum care and able to accommodate a 2-hour discharge workshop. The intervention was delivered by Crianzamor health professionals trained in the Uriclarity Program and AUS prior to trial start, with no additional provider eligibility criteria specified. Intervention and measures Women in the intervention arm received the Uriclarity Program (see Supplementary Materials) on postpartum day 1–2, consisting of a two-hour discharge workshop using practical tools (breast/infant simulators, cloth diapers, AUS urine-color chart, and infographics), followed by standardized WhatsApp messages and short tutorial videos until day 2 after the workshop. Withdrawal criteria included non-response to WhatsApp, failure to submit Uriscale reports, or introduction of formula, bottles, or pacifiers. Controls received standard care with routine breastfeeding counselling before discharge. Outcomes were measured with the MILQ (4-item dichotomous scale, total 0–8; higher scores indicate greater perceived milk sufficiency/lower PIMS) and the AUS (urine-color ordinal scale 1–5; lower scores reflect lighter urine and higher milk transfer). Both the AUS and the MILQ have, to date, undergone content-validation and clinical-use studies, providing initial evidence of adequate content validity indices, acceptable operational performance, and favourable maternal perceptions of their ease of use and clinical utility. Outcomes Primary outcome . Comparison between study groups in PIMS, measured with MILQ on postpartum days 1 (baseline), 3, 7, and 14. PIMS was measured with the 4-item MILQ, administered by an interviewer in person on day 1 and by telephone on the remaining days. Responses were provided directly by participants; higher scores indicate better perception. Secondary outcome . Association between the AUS score and the PIMS. Harms No specific harms were anticipated due to the educational nature of the intervention. However, mothers and infants were monitored for any clinical adverse event that could interfere with breastfeeding (e.g., neonatal hypoglycaemia, hospitalization, or maternal complications). No systematic adverse-event collection was performed, and no harms related to the intervention were reported. Sample size The sample size was determined for detecting a clinically meaningful absolute difference in the proportion of mothers with MILQ ≥ 7 at day 14 (binary threshold chosen for feasibility and interpretability), with α=0.05 and β=0.10, plus 30% anticipated loss. Substituting values (Zα = 1.96, Zβ = 1.28, P1 = 0.1, P2 = 0.5, P = 0.3) and accounting for a 30% anticipated loss, the adjusted sample size was 38 participants per group. To strengthen statistical power, the sample size was rounded to 50 participants per group. Interim analyses No interim analyses or stopping guidelines were planned, given the small sample size, the short follow-up period, and the low-risk nature of the educational intervention. Sequence generation The random allocation sequence was computer-generated using R (version 4.4.0). A script produced a new random sequence of 100 numbers each time it was run, ensuring the assignment order could not be anticipated even if the code were obtained. Simple, unrestricted randomization with a 1:1 allocation ratio was used. Allocation Allocation concealment was ensured with sequentially numbered, opaque, sealed, light-proof envelopes. The envelopes were prepared by a staff member not associated with the trial, who remained anonymous throughout the study. Envelopes were released only after the recruiter had confirmed the number of eligible participants, preventing any advance access to the allocation sequence. The random sequence was generated by an independent individual who did not take part in recruitment. Participant enrollment was performed by members of the Crianzamor team at the hospitals, and assignment to the intervention or control group was carried out by opening the sealed envelopes in sequential order. Blinding Participants and care providers were not blinded due to the nature of the intervention. Telephone outcome assessors were blinded to group allocation and used a standardized script. The data analyst was blinded by coding the groups as A and B prior to statistical analysis; group identities were revealed only after analyses were completed. Statistical analysis All analyses were conducted in R (v4.4.0) using two-sided tests with α = 0.05. Between-group differences in MILQ were assessed with the Mann–Whitney U test. The primary longitudinal analysis used a cumulative-link proportional-odds mixed model (logit) for ordinal MILQ, including a participant-level random intercept, adjustment for maternal age, parity, and education, and time modeled as a linear trend. For secondary analyses, AUS (measured on days 3, 7, and 14) was entered as an ordinal predictor in proportional-odds logistic regression to evaluate dose–response associations with MILQ, and ROC curves were used to explore AUS thresholds distinguishing low vs. high MILQ. For clinical interpretability, ordinal effects were translated into absolute probabilities of achieving MILQ ≥ 7 at day 14, reporting risk differences and NNT (1/RD). All randomized participants were analyzed according to intention-to-treat. Missing data were assumed missing at random; the mixed model accommodated incomplete repeated measures without additional imputation. For day-specific Mann–Whitney comparisons, participants missing that time point were excluded only from that comparison. Participants with missing AUS values on a given day were excluded from dose–response and ROC analyses for that day but remained in the trial population for other analyses. No subgroup analyses were performed. As prespecified, a mixed-effects binary logistic model for MILQ ≥ 7 was also fitted as a robustness check. Results Participant flow and recruitment Of 114 mothers assessed for eligibility, 14 declined and 100 were randomized (54 to intervention, 46 to control). All received their allocated care and were included in the intention-to-treat primary analysis (Figure 1). In the intervention group, six mothers were lost to follow-up: one due to no response to telephone calls or WhatsApp messages; two for failing to submit requested information; one due to maternal hospitalization; one due to neonatal complications (readmission for hyperbilirubinaemia with initiation of formula feeding); and one due to a medically indicated weaning (suspected cow’s milk protein allergy with initiation of formula feeding). In the control group, three mothers were lost to follow-up because they did not respond to telephone calls or WhatsApp messages. Recruitment occurred from May 28 to August 10, 2025, and follow-up was completed by August 24, 2025, with the trial ending as planned and without early termination. Intervention delivered and concomitant care The intervention group attended a structured educational workshop (Uriclarity Program) of approximately two hours, delivered in person by trained health professionals. Implementation fidelity was ensured through a standardized teaching guide and a facilitator-completed checklist. All participants in the intervention group received the full workshop session, with no deviations from the planned content. During the trial, both groups continued to receive standard postpartum care provided by local health services. No restrictions were imposed on concomitant care, and no between-group differences were observed in additional health services accessed outside the study protocol. Routine pre-discharge breastfeeding counseling was provided by on-duty maternity staff (midwives or nurses) in accordance with the institutional protocol. Receipt of counseling was confirmed in the discharge records for 100% of control-group participants. Baseline data Table 1 summarizes baseline demographic and clinical characteristics of participants by study group. Maternal age, education, parity, gestational age at birth, neonatal sex, birth weight, and the MILQ score were comparable between groups, with no clinically relevant imbalances observed. Data analyses We analyzed 100 participants across four visits, yielding 380 observations (see Table 2). At all follow-up visits, between-group comparisons consistently favored the intervention (all Wilcoxon tests p < 0.001). The Hodges–Lehmann median difference (Intervention − Control) was 2.00, with 95% CIs ranging from 1.00–2.00 to 1.00–3.00. In an adjusted ordinal mixed model, the intervention increased the odds of being in a higher MILQ category (see Table 3). Between-group comparisons of MILQ scores At baseline (day 1), MILQ scores distributions were similar in both arms (median 8 [IQR 7–8] in each group). At all follow-up visits, between-group comparisons favored the intervention (Wilcoxon p < 0.001 at every visit). The Hodges–Lehmann median difference (Intervention − Control) was 2.00, with 95% CIs ranging from 1.00–2.00 to 1.00–3.00 across visits. Sample sizes by visit are shown in Table 2. 40/48 (83.3%) in the intervention versus 13/43 (30.2%) in control achieved MILQ ≥ 7. The absolute RD was +53.1 percentage points (95% CI +33.4 to +67.2), corresponding to an NNT of 1.88 (95% CI 1.49 to 2.99). In the longitudinal ordinal mixed model (random intercept per participant), with time modeled as a linear trend and adjusting for maternal age, parity, and education, the intervention was associated with higher MILQ scores (OR 10.64; 95% CI 4.26–26.58; p < 0.001). Time showed a negative trend across visits (per 1-day increase OR 0.63; 95% CI 0.52–0.77; p < 0.001). Maternal age, parity, and education were not significantly associated with PIMS (all p ≥ 0.55) (Table 3). Association between AUS and MILQ To quantify the day-specific relationship between the AUS and MILQ, separate proportional-odds logistic models were fitted for days 3, 7, and 14, adjusting for group, maternal age, parity, and education. Higher AUS scores were associated with lower odds of being in a higher MILQ category: day 3, adjusted OR 0.54 (95% CI 0.30–0.98; p = 0.044); day 7, OR 0.23 (95% CI 0.10–0.51; p < 0.001); day 14, OR 0.12 (95% CI 0.01–1.12; p = 0.062). Diagnostic performance of the AUS ROC analyses showed modest discrimination, with AUCs between 0.60 and 0.69 on all days. Using the Youden-selected cut-off of AUS ≤ 2, sensitivity was high (0.84–0.95), whereas specificity was low (0.33–0.50). Positive predictive values were high (0.70–0.95), while negative predictive values were low to moderate (0.33–0.55). Consequently, a low AUS (1–2) is most useful as a sensitive screen to identify mothers at high probability of MILQ ≥ 7, particularly on day 7, whereas AUS > 2 does not safely exclude MILQ ≥ 7. Detailed operating characteristics are provided in Table 4. No participant recorded an AUS score of 5 at any assessment. Adverse events No harms or unintended events related to the intervention were observed in either group during follow-up (0/54 vs 0/46). Clinical events contributing to loss to follow-up (e.g., maternal hospitalization, neonatal readmission) were not considered study related. Ancillary analyses A mixed-effects binary logistic model using MILQ ≥ 7 as the outcome showed an intervention effect in the same direction (OR 10.49; 95% CI 3.81–28.89; p < 0.001), supporting the robustness of the primary ordinal analysis. Discussion Main findings We demonstrated that the Uriclarity Program—a single 2-hour predischarge workshop plus 4 days of standardized messages that trains mothers to prevent the main breastfeeding difficulties and teaches them to interpret neonatal urine color to estimate milk transfer—reduced PIMS by an order of magnitude (OR 10.6) within the first two postpartum weeks; and, given the limited literature using PIMS as an outcome, the observed effect lies at the upper end of magnitudes reported for educational/psychobehavioral interventions related to PIMS/self-efficacy (Galipeau et al., 2018). In this single-blind randomized clinical trial, Uriclarity produced a large and consistent improvement in reducing PIMS during the first two postpartum weeks: at all assessments, the typical between-group difference was +2 points, and the ordinal mixed model showed that mothers assigned to Uriclarity had 10 times higher odds of being in a better MILQ category, adjusted for age, parity, and education. Clinically, this 2-point shift on the 0–8 MILQ scale translates into one additional mother out of 2 reaching MILQ ≥ 7 by day 14 (RD +53 pp; NNT = 2). For a brief, low-cost discharge-time intervention, this magnitude represents a large, patient-relevant benefit. As expected, MILQ scores tended to decrease over time in both groups (per-day OR 0.63), while the intervention benefit persisted. The sensitivity analysis (MILQ ≥ 7) yielded identical conclusions in the same direction (OR 10.49). Mechanisms and biological plausibility Mothers with PIMS often turn to infant formula and to weaning (Gatti, 2008; Doulougeri et al., 2013; Flaherman et al., 2016). Although in most cases PIMS is not supported by true milk-production insufficiency—that is, it is usually a misperception (Whipps & Demirci, 2021; Kellams et al., 2017)—failure to prevent or treat it in time can turn it into a genuine insufficiency. Maternal psychological distress due to PIMS can reduce oxytocin release (Ueda et al., 1994; Uvnäs-Moberg et al., 2020), impair the milk ejection (let-down) reflex, and lead to incomplete breast emptying at each feed, resulting in a clear reduction in milk supply. Likewise, elevated serum cortisol may reduce insulin sensitivity and trigger a true decrease in milk production (Nagel et al., 2022). To prevent PIMS, it is recommended to provide mothers with reliable parameters that allow them to objectify milk transfer during feeds (Huang et al., 2022; Nagel et al., 2022), given their value for modulating anxiety and strengthening maternal self-confidence (Kent et al., 2015). In Uriclarity, the AUS operated as an immediate, comprehensible biometric signal to monitor transfer—a pragmatic alternative to test-weighing when the latter is not feasible. Interpretation in context with the evidence Our findings are consistent with reviews linking self-efficacy–focused and early-support interventions to better breastfeeding outcomes in the first month. The systematic review and meta-analysis by Galipeau et al. (2018) estimated a moderate effect (SMD = 0.40; 95% CI 0.11–0.69; p = 0.006) on self-efficacy—an indirect indicator of reduced PIMS—whereas the Uriclarity Program showed a large effect (OR = 10.64), demonstrating a direct and clinically relevant impact on perceived milk sufficiency. Thus, this trial’s results empirically confirm Galipeau’s hypothesis: interventions that strengthen maternal confidence and competence reduce the perception of insufficient milk. Translated into practice, a 2-point increase in MILQ reflects fewer doubts about milk production and therefore a lower risk of introducing supplements. The structured educational component plus active monitoring of milk transfer with the AUS appear to act by strengthening self-efficacy and enabling early problem resolution, consistent with literature that links self-efficacy–based interventions to improved breastfeeding outcomes in the first postpartum month (Galipeau et al., 2018). What this study adds to the existing evidence PIMS is a leading reason for breastfeeding cessation, yet viable preventive interventions are scarce, especially in low- and middle-income countries. This randomized trial provides solid experimental evidence in a middle-income setting, using a replicable, public-health–feasible strategy to prevent/reduce PIMS. The systematic review by Galipeau et al. (2018) identified maternal self-efficacy as a key mediator but found very little direct evidence on PIMS (only 1/17 studies reported this outcome), precluding a PIMS-specific meta-analysis and noting methodological heterogeneity; our results address that gap, showing a large, clinically relevant effect. We also introduce the AUS as a practical home tool to monitor milk transfer, which reinforces positive self-perception and early response, offers a pragmatic alternative to costly transfer measurements, and preserves maternal agency—aligned with international recommendations to promote self-efficacy (Galipeau et al., 2018). The effects of Uriclarity were consistent across primary and sensitivity analyses, suggesting a clinically meaningful, potentially durable impact that warrants multicenter evaluation with longer follow-up. Taken together, the findings support Uriclarity as a low-cost public health strategy to reduce PIMS and strengthen maternal confidence, contributing to WHO targets for exclusive breastfeeding. Finally, the AUS showed ROC performance with AUC 0.60–0.69 and high sensitivity at the AUS ≤ 2 threshold (0.84–0.95), with high PPV in this sample; given its low–moderate specificity, it should not be used to rule out high PIMS without clinical evaluation, consistent with Youden index–based threshold selection. Investment and feasibility Implementing Uriclarity requires substantially less investment than other strategies to counter PIMS that depend on technological platforms, automated content, and monitoring (Demirci et al., 2020); trained visiting nurses with associated training, transport, and supplies (Kronborg et al., 2007); intensive self-efficacy programs with higher personnel and material costs (Chainakin et al., 2023); postpartum home-visit programs (Wood et al., 2017); or galactagogues requiring medication costs, safety monitoring, and specialized staff (Saxena et al., 2025). Because it is integrated into the hospital discharge workflow, Uriclarity does not require a new service, infrastructure, or additional equipment; its brief, simple, and practical workshop can be delivered by existing staff, and the 4-day WhatsApp follow-up entails no special monitors or travel. Its effect also appears independent of maternal age, parity, and education (covariates not associated with PIMS after adjustment), suggesting broad applicability. Assessed with RE-AIM (Glasgow et al., 1999) and NPT, the program emerges as model, innovative, accessible, sustainable, and replicable, with high potential for institutional integration in resource-limited settings; its brief, culturally adapted, mother-empowering approach—including the teté dance (Ashiyama Vega et al., 2025)—reinforces learning without operational burden, supporting institutionalization as a Latin American public-health strategy. We propose incorporating the AUS as a sensitive triage signal: a AUS > 2 (clinical threshold) would trigger brief, focused proactive contact with health personnel (without replacing full evaluation), while maintaining comprehensive clinical assessment for all mothers who express concerns. Limitations Follow-up was limited to two postpartum weeks, so longer-term outcomes (e.g., exclusive breastfeeding duration and other objective endpoints) were not assessed. Eligibility required primary education and the ability to use WhatsApp, and participants were recruited from three public hospitals in one region, which may limit generalizability. Because participants and providers were not blinded and MILQ is self-reported, reporting effects are possible despite blinded telephone outcome assessors and a blinded analyst. Finally, adverse events were not collected through systematic active surveillance; no intervention-related harms were reported, but rare events could have been missed. Conclusions A brief, low-cost predischarge program embedded in the hospital discharge workflow (Uriclarity) produced large and consistent improvements in perceived milk sufficiency over the first two postpartum weeks. These findings support the feasibility and potential effectiveness of scalable discharge-based education combined with short-term digital reinforcement. Larger multicenter trials with longer follow-up and objective breastfeeding outcomes are warranted. Abbreviations AUC: Area under the receiver operating characteristic curve AUS: Ashiyama Uriscale CI: Confidence interval EBF: Exclusive breastfeeding ITT: Intention-to-treat MILQ: Maternal Insufficient Lactation Questionnaire NNT: Number needed to treat OR: Odds ratio PIMS: Perceived insufficient milk supply RD: Risk difference ROC: Receiver operating characteristic Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of Hospital Daniel Alcides Carrión (990-2024). All participants provided written informed consent in accordance with the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials It was planned to make de-identified individual participant data (IPD) and the study protocol available, upon reasonable request, for research purposes only, beginning 6 months after publication of the primary results and for at least 1 year. Access will be restricted to qualified researchers affiliated with academic or health institutions, subject to ethics approval and institutional agreements. Data will be shared via a secure repository or an institutional data-sharing agreement and may not be used for commercial purposes or to re-identify participants. The full trial record is publicly available at ClinicalTrials.gov (NCT06857461). The study protocol and statistical analysis plan are available on the Open Science Framework (OSF) (DOI: 10.17605/OSF.IO/C4MFY). Competing interests The authors declare that they have no competing interests. Funding No external funding. Authors’ contributions JAV conceptualized the study and contributed to the methodology alongside JRA. JAV and MYR coordinated participant recruitment and data collection. JAV and JRA prepared the introduction and background sections. All three authors (JRA, MYR, and JAV) collaboratively wrote the discussion and conclusions. All authors reviewed and approved the final manuscript. Acknowledgements Not applicable. References Ashiyama Vega, J., Yrigoyen Rojas, M., & Ravichagua Ashiyama, J. (2025). Effect of teté dance on lactation session duration in irritable infants in Peru assessed in a randomized controlled trial. Scientific Reports, 15 (1), 9808. https://doi.org/10.1038/s41598-025-95236-y Chainakin, P., Sansiriphun, N., Chaloumsuk, N., & Deeluea, J. (2023). Effectiveness of the breastfeeding self-efficacy and family support enhancement program among first-time postpartum mothers: A randomized controlled trial. Pacific Rim International Journal of Nursing Research, 27 (4), 694–710. https://he02.tci-thaijo.org/index.php/PRIJNR/article/view/262625 Demirci, J. R., Suffoletto, B., Doman, J., Glasser, M., Chang, J. C., Sereika, S. M., & Bogen, D. L. (2020). The development and evaluation of a text message program to prevent perceived insufficient milk among first-time mothers: Retrospective analysis of a randomized controlled trial. JMIR mHealth and uHealth, 8 (4), e17328. https://doi.org/10.2196/17328 Doulougeri, K., Panagopoulou, E., & Montgomery, A. (2013). The impact of maternal stress on initiation and establishment of breastfeeding. Journal of Neonatal Nursing, 19 (4), 162–167. https://doi.org/10.1016/j.jnn.2013.02.003 Flaherman, V. J., Beiler, J. S., Cabana, M. D., & Paul, I. M. (2016). Relationship of newborn weight loss to milk supply concern and anxiety: The impact on breastfeeding duration. Maternal & Child Nutrition, 12 (3), 463–472. https://doi.org/10.1111/mcn.12171 Galipeau, R., Baillot, A., Trottier, A., & Lemire, L. (2018). Effectiveness of interventions on breastfeeding self-efficacy and perceived insufficient milk supply: A systematic review and meta-analysis. Maternal & Child Nutrition, 14 (3), e12607. https://doi.org/10.1111/mcn.12607 Galipeau, R., Dumas, L., & Lepage, M. (2017). Perception of not having enough milk and actual milk production of first-time breastfeeding mothers: Is there a difference? Breastfeeding Medicine, 12 (4), 210–217. https://doi.org/10.1089/bfm.2016.0183 Gatti, L. (2008). Maternal perceptions of insufficient milk supply in breastfeeding. Journal of Nursing Scholarship, 40 (4), 355–363. https://doi.org/10.1111/j.1547-5069.2008.00234.x Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. American Journal of Public Health, 89 (9), 1322–1327. https://doi.org/10.2105/AJPH.89.9.1322 Huang, Y., Liu, Y., Yu, X. Y., & Zeng, T. Y. (2022). The rates and factors of perceived insufficient milk supply: A systematic review. Maternal & Child Nutrition, 18 (1), e13255. https://doi.org/10.1111/mcn.13255 Instituto Nacional de Estadística e Informática. (2024). Encuesta demográfica y de salud familiar 2024: Nacional y departamental . INEI. https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib2016/libro.pdf International Atomic Energy Agency. (2010). Stable isotope technique to assess intake of human milk in breastfed infants (IAEA Human Health Series No. 7). IAEA. https://www.osti.gov/etdeweb/biblio/21535382 Kellams, A., Harrel, C., Omage, S., Gregory, C., Rosen-Carole, C., & Academy of Breastfeeding Medicine. (2017). ABM clinical protocol #3: Supplementary feedings in the healthy term breastfed neonate, revised 2017. Breastfeeding Medicine, 12 (4), 188–198. https://doi.org/10.1089/bfm.2017.29038.ajk Kent, J. C., Hepworth, A. R., Langton, D. B., & Hartmann, P. E. (2015). Impact of measuring milk production by test weighing on breastfeeding confidence in mothers of term infants. Breastfeeding Medicine, 10 (6), 318–325. https://doi.org/10.1089/bfm.2015.0025 Kronborg, H., Væth, M., Olsen, J., Iversen, L., & Harder, I. (2007). Effect of early postnatal breastfeeding support: A cluster-randomized community based trial. Acta Paediatrica, 96 (7), 1064–1070. https://doi.org/10.1111/j.1651-2227.2007.00341.x Li, R., Fein, S. B., Chen, J., & Grummer-Strawn, L. M. (2008). Why mothers stop breastfeeding: Mothers’ self-reported reasons for stopping during the first year. Pediatrics, 122 (Suppl. 2), S69–S76. https://doi.org/10.1542/peds.2008-1315i Nagel, E. M., Howland, M. A., Pando, C., Stang, J., Mason, S. M., Fields, D. A., & colleagues. (2022). Maternal psychological distress and lactation and breastfeeding outcomes: A narrative review. Clinical Therapeutics, 44 (2), 215–227. https://doi.org/10.1016/j.clinthera.2021.12.005 Odom, E. C., Li, R., Scanlon, K. S., Perrine, C. G., & Grummer-Strawn, L. (2013). Reasons for earlier than desired cessation of breastfeeding. Pediatrics, 131 (3), e726–e732. https://doi.org/10.1542/peds.2012-1295 Olalere, O., & Harley, C. (2024). Why women discontinue exclusive breastfeeding: A scoping review. British Journal of Midwifery, 32 (12), 673–682. https://doi.org/10.12968/bjom.2024.0044 Rollins, N. C., Bhandari, N., Hajeebhoy, N., Horton, S., Lutter, C. K., Martines, J. C., Piwoz, E. G., Richter, L. M., & Victora, C. G. (2016). Why invest, and what it will take to improve breastfeeding practices? The Lancet, 387 (10017), 491–504. Saxena, U., Ota, S., Rajput, S., Anand, B., Tripathi, A., Singhal, R., & colleagues. (2025). Clinical evaluation of ayush-SS granules in exclusively breastfeeding mothers with insufficient lactation: A randomized, double-blind, placebo-controlled trial. International Breastfeeding Journal, 20 (1), 26. https://doi.org/10.1186/s13006-025-00721-9 UNICEF. (2025). Breastfeeding . UNICEF Data. https://data.unicef.org/topic/nutrition/breastfeeding/ UNICEF, & World Health Organization. (2024). Global breastfeeding scorecard 2024 (Child Nutrition and Development). UNICEF/WHO. https://knowledge.unicef.org/child-nutrition-and-development/resource/global-breastfeeding-scorecard-2024 Ueda, T., Yokoyama, Y., Irahara, M., & Aono, T. (1994). Influence of psychological stress on suckling-induced pulsatile oxytocin release. Obstetrics & Gynecology, 84 (2), 259–262. https://journals.lww.com/greenjournal/Abstract/1994/08000/Influence_of_Psychological_Stress_on.21.aspx Uvnäs-Moberg, K., Ekström-Bergström, A., Buckley, S., Massarotti, C., Pajalic, Z., Luegmair, K., Kotlowska, A., Lengler, L., Olza, I., Grylka-Baeschlin, S., & Leahy-Warren, P. (2020). Maternal plasma levels of oxytocin during breastfeeding—A systematic review. PLOS ONE, 15 (8), e0235806. https://doi.org/10.1371/journal.pone.0235806 Victora, C. G., Bahl, R., Barros, A. J. D., França, G. V. A., Horton, S., Krasevec, J., Murch, S., Sankar, M. J., Walker, N., & Rollins, N. C. (2016). Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. The Lancet, 387 (10017), 475–490. Walters, D. D., Phan, L. T. H., & Mathisen, R. (2019). The cost of not breastfeeding: Global results from a new tool. Health Policy and Planning, 34 (6), 407–417. https://doi.org/10.1093/heapol/czz050 Whipps, M. D., & Demirci, J. R. (2021). The sleeper effect of perceived insufficient milk supply in US mothers. Public Health Nutrition, 24 (5), 935–941. https://doi.org/10.1017/S1368980020001482 World Health Organization. (2018). Guideline: Counselling of women to improve breastfeeding practices . WHO. https://www.ncbi.nlm.nih.gov/books/NBK539309/ Wood, N. K., Sanders, E. A., Lewis, F. M., Woods, N. F., & Blackburn, S. T. (2017). Pilot test of a home-based program to prevent perceived insufficient milk. Women and Birth, 30 (6), 472–480. https://doi.org/10.1016/j.wombi.2017.04.006 Tables Tab 1. Baseline characteristics of the intervention and control groups Characteristic Intervention (n=54) Control (n=46) Maternal age, mean (SD) 29.6 (7.2) 26.7 (6.8) Maternal education, n (%) – Primary 20 (37.0) 19 (41.3) – Secondary 23 (42.6) 22 (47.8) – Higher 11 (20.4) 5 (10.9) Parity, median (IQR) 2 (2–3) 2 (1–3) Gestational age at birth, mean (SD), weeks 38.6 (1.1) 38.8 (1.7) Neonatal sex, male, n (%) 27 (50) 22 (47.8) Birth weight, mean (SD), grams 3242.9 (511.4) 3293.2 (379.3) MILQ score, median (IQR) 8 (7–8) 8 (7–8) Tab 2. Between-group comparisons of PIMS (MILQ) by visit. Day Control (n) Intervention (n) Control median (IQR) Intervention median (IQR) p Effect (HL, 95% CI) PIMS1 46 54 8 (7–8) 8 (7–8) — — PIMS3 46 51 5.5 (4–6.75) 8 (6–8) < 0.001 2.00 (1.00–2.00) PIMS7 44 48 6 (4.75–7) 8 (7–8) < 0.001 2.00 (1.00–2.00) PIMS14 43 48 5 (4–7) 8 (7–8) < 0.001 2.00 (1.00–3.00) Tab 3. Ordinal mixed-effects model for the MILQ score Predictor OR (95% CI) p Intervention vs Control 10.64 (4.26–26.58) < 0.001 Time (per 1-day increase) 0.63 (0.52–0.77) < 0.001 Maternal age (per year) 1.02 (0.95–1.10) 0.556 Parity (per unit) 1.05 (0.66–1.67) 0.827 Secondary vs Primary 1.16 (0.46–2.93) 0.752 Higher vs Primary 0.94 (0.26–3.37) 0.929 Tab 4. ROC performance of AUS for identifying a high MILQ score Metric Day 3 Day 7 Day 14 n 51 48 43 AUC (95% CI) 0.60 (0.45–0.76) 0.69 (0.51–0.87) 0.64 (0.31–0.97) Optimal cut-off AUS ≤ 2 AUS ≤ 2 AUS ≤ 2 Sensitivity 0.85 0.84 0.95 Specificity 0.33 0.50 0.33 PPV 0.70 0.87 0.95 NPV 0.55 0.46 0.33 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8634552","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580676969,"identity":"342f7d83-cb6b-4abc-8626-9366553aa20a","order_by":0,"name":"Jackeline Ashiyama Vega","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABKUlEQVRIiWNgGAWjYBACxgYGZgaGAgkQm40hAUSxNwAJAwsCWgyQtfAcYICJ4AIgLQwQLWAgAdaIWwtz++HHBh8MLPL42Y8/e/CwzS6af+bzqxt+AJ3K396dgNVhPWnGiTMMJIole3LMDRLbknNn3M4pu9kDdJjEmbMbsPslh/kwj4FE4oYDOWwSiW3MuQ23c9JuAEWA3snFrqX/DfPhP0At+88/fwbUUp87/+aZtJt/8GmZkcOczACyRSLBDKjlcO6GG+zHbuO1ZcYzY0OgyxNn3HhjJpFw7njuxjM5bLdlDCR4cPnFsD/5scSPirrE/v70Z5I/yqpz5x0//uzmmz82cvztvdi1NKDYCY4aHnA08WBTDgLyqNw/IIL9AS7Vo2AUjIJRMDIBAAA1Zx0qTT7eAAAAAElFTkSuQmCC","orcid":"","institution":"Universidad San Ignacio de Loyola","correspondingAuthor":true,"prefix":"","firstName":"Jackeline","middleName":"Ashiyama","lastName":"Vega","suffix":""},{"id":580676970,"identity":"b58bb74a-2313-4ca1-a016-945bb43de09c","order_by":1,"name":"Mario Yrigoyen Rojas","email":"","orcid":"","institution":"Crianzamor","correspondingAuthor":false,"prefix":"","firstName":"Mario","middleName":"Yrigoyen","lastName":"Rojas","suffix":""},{"id":580676971,"identity":"9d192e78-ac05-47c4-8494-878dc0d67049","order_by":2,"name":"Javier Ravichagua Ashiyama","email":"","orcid":"","institution":"Crianzamor","correspondingAuthor":false,"prefix":"","firstName":"Javier","middleName":"Ravichagua","lastName":"Ashiyama","suffix":""}],"badges":[],"createdAt":"2026-01-19 03:08:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8634552/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8634552/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101436049,"identity":"07e73f57-175b-4fbf-ae81-eaa320f77dbe","added_by":"auto","created_at":"2026-01-29 16:21:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":272670,"visible":true,"origin":"","legend":"\u003cp\u003e\u0026nbsp;Legend not included with this version.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8634552/v1/953fcb47fb6a58bbfbca15e5.png"},{"id":101751211,"identity":"920c5bf3-b5d7-44ba-a44c-48f974598628","added_by":"auto","created_at":"2026-02-03 10:18:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":996983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8634552/v1/129d668c-9204-4b27-a54d-9124fc4b8cdf.pdf"},{"id":101436048,"identity":"802805c9-0912-4cda-92bf-1f98fab48f1a","added_by":"auto","created_at":"2026-01-29 16:21:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":203182,"visible":true,"origin":"","legend":"","description":"","filename":"MATERNALINSUFFICIENTLACTATIONQUESTIONNAIRE.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8634552/v1/b2820c2d3b76854da0c5fb8c.pdf"},{"id":101436046,"identity":"f2e0de88-e21e-404c-8cc4-88a02a159a69","added_by":"auto","created_at":"2026-01-29 16:21:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2130195,"visible":true,"origin":"","legend":"","description":"","filename":"AshiyamaUriscale.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8634552/v1/a7550bdb40113a2b5bdb6551.pdf"},{"id":101436045,"identity":"73dec965-ff8c-49d9-acf5-7fd5e584c111","added_by":"auto","created_at":"2026-01-29 16:21:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":85728,"visible":true,"origin":"","legend":"","description":"","filename":"APPLICATIONPROTOCOLOFTHEURICLARITYPROGRAM.docx","url":"https://assets-eu.researchsquare.com/files/rs-8634552/v1/38b8ea4b07a8142f5e09a7ed.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Uriclarity Program Reduces Perceived Insufficient Milk Supply in Early Postpartum: Randomized Controlled Trial","fulltext":[{"header":"Key Message","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eUriclarity, a brief predischarge breastfeeding program combining a 2-hour interactive workshop with four days of WhatsApp messages, substantially reduced perceived insufficient milk supply during the first two postpartum weeks. Compared with routine counseling, mothers in public hospitals who received Uriclarity had about tenfold higher odds of being in a better MILQ category, with a typical 2-point improvement on the 0\u0026ndash;8 scale and an NNT of about 2 to achieve MILQ \u0026ge;7 by day 14. No intervention-related harms were reported, representing a large, clinically meaningful benefit.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"2\" type=\"1\"\u003e\n \u003cli\u003eThe Uriclarity Program trains mothers to interpret neonatal urine color using the AUS as a simple, home-based indicator of milk transfer. Across follow-up, higher AUS scores were associated with poorer perceived milk sufficiency, and an AUS threshold \u0026le;2 showed high sensitivity for identifying mothers with low PIMS (MILQ \u0026ge;7), though specificity remained modest. In practice, AUS can function as a sensitive triage and self-monitoring tool that reinforces maternal confidence, prompts early counseling when values are high, and supports timely correction of breastfeeding problems.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"3\" type=\"1\"\u003e\n \u003cli\u003eUriclarity was designed for routine use in resource-constrained public hospitals and integrated seamlessly into the discharge workflow, delivered by existing midwives or nurses using low-cost materials and standard smartphones. Because its effect did not depend on maternal age, parity or education, the program appears broadly applicable to diverse postpartum populations. Health systems seeking to improve early exclusive breastfeeding could adopt Uriclarity as a scalable quality-improvement strategy, strengthening discharge education and remote follow-up without creating new services, infrastructure, or substantial additional staffing costs.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"4\" type=\"1\"\u003e\n \u003cli\u003eThis trial provides experimental evidence that directly targets perceived insufficient milk supply as a primary outcome in a middle-income setting. Future research should test Uriclarity in larger, multicenter studies with longer follow-up, measuring exclusive breastfeeding duration, infant growth, and maternal mental health. Adaptations using other digital platforms, community health workers, or group tele-sessions could be evaluated. Policymakers and researchers should also explore how integrating AUS-based triage into postnatal care pathways might optimize early identification and management of breastfeeding difficulties.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Background","content":"\u003cp\u003eOptimal breastfeeding could save more than US$300 billion annually (Rollins et al., 2016; Walters et al., 2019) and avert 823,000 child deaths and \u0026gt;20,000 maternal deaths from breast cancer each year (Victora et al., 2016). Yet as of 2024, only 46% of newborns are breastfed within the first hour of life, 48% of infants under six months receive exclusive breastfeeding, and 46% of two-year-olds continue breastfeeding (UNICEF \u0026amp; World Health Organization, 2024). In the Americas and the Caribbean, 52% of neonates initiate breastfeeding in the first hour and 43% of infants under six months are exclusively breastfed (UNICEF Data, 2025). In Peru (2024), 47.6% of newborns initiated breastfeeding within the first hour, and 67.4% of infants under six months received breastfeeding\u0026mdash;without disaggregation for exclusive breastfeeding (Instituto Nacional de Estad\u0026iacute;stica e Inform\u0026aacute;tica, 2024). The WHO\u0026rsquo;s 2030 targets are 70% early initiation and 70% exclusive breastfeeding under six months (UNICEF \u0026amp; World Health Organization, 2024).\u003c/p\u003e\n\u003cp\u003eThe early postpartum period is critical for sustaining exclusive breastfeeding, and perceived insufficient milk supply (PIMS) is a leading reason for formula supplementation and early weaning (Olalere \u0026amp; Harley, 2024; Odom et al., 2013). PIMS consistently ranks among the top three causes of breastfeeding cessation during the first year, commonly affecting 43\u0026ndash;65% of mothers depending on age at weaning (Li et al., 2008; Whipps \u0026amp; Demirci, 2021), and in some settings up to 80% report PIMS at some point (Huang et al., 2022). True primary hypogalactia is rare, yet the belief of low milk supply strongly undermines exclusive breastfeeding (Galipeau et al., 2017; Huang et al., 2022).\u003c/p\u003e\n\u003cp\u003eAlthough PIMS has been widely described, there remains a gap in rigorous, scalable interventions to prevent or correct it (Galipeau et al., 2018; Demirci et al., 2020). Many prior studies have limited inferential capacity due to small samples, lack of comparators, or short follow-up (Galipeau et al., 2018). Several approaches are impractical in resource-constrained environments and rely on objective milk intake measures that are difficult to implement outside controlled settings (International Atomic Energy Agency, 2010; Kent et al., 2015). Moreover, interventions often minimize mothers\u0026rsquo; active participation despite recommendations emphasizing maternal self-efficacy in preventing or reversing PIMS (World Health Organization, 2018; Dennis, 2003; McGovern et al., 2024).\u003c/p\u003e\n\u003cp\u003eTo address these gaps, we conducted a randomized, controlled, single-blind clinical trial that evaluated the effect of Uriclarity, a low-cost program that empowered mothers to pre-empt uncertainty about milk production by recognizing early warning signs and receiving standardized anticipatory virtual guidance to manage breastfeeding challenges at home. The study also introduced the Uriscale (AUS, see Supplementary Materials), a simple, novel tool enabling mothers to estimate milk transfer from neonatal urine color.\u003c/p\u003e\n\u003ch2\u003eObjectives\u003c/h2\u003e\n\u003cp\u003eThe trial evaluated whether Uriclarity\u0026mdash;a brief predischarge workshop plus standardized follow-up messages\u0026mdash;was superior to usual counseling in reducing PIMS among postpartum women receiving care in public hospitals in Piura, Peru, during the early postpartum period (days 2\u0026ndash;14). The primary outcome was PIMS severity measured with the MILQ (Maternal Insufficient Lactation Questionnaire, see Supplementary Materials) and analysed using a prespecified ordinal mixed-effects model over days 2\u0026ndash;14.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary objectives\u003cbr\u003e\u003c/strong\u003eThe trial estimated the effect of Uriclarity on MILQ \u0026ge; 7 (low PIMS) using a mixed logistic model as a sensitivity analysis; described the time trajectory of MILQ scores by group; assessed safety as maternal and neonatal adverse events related to the intervention during the 14-day follow-up; and estimated the diagnostic performance of the AUS to identify MILQ \u0026ge; 7 (AUC, sensitivity, specificity, and Youden\u0026rsquo;s index).\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eTrial design and setting\u003c/h2\u003e\n\u003cp\u003ePatients and the public were not involved in the design, conduct, or reporting of the trial. This was a two-arm, parallel-group randomized superiority trial with 1:1 allocation to the Uriclarity Program or standard care. No protocol changes were made after commencement. The study was conducted in three public hospitals in Piura, Peru: Hospital Re\u0026aacute;tegui, Hospital Santa Rosa, and Hospital Cayetano Heredia. The study was approved by the Ethics Committee of Hospital Daniel Alcides Carri\u0026oacute;n and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to enrollment.\u003c/p\u003e\n\u003ch2\u003eParticipants, sites, and providers\u003c/h2\u003e\n\u003cp\u003eEligible participants were women \u0026ge;18 years, recruited 24\u0026ndash;48 hours postpartum (vaginal or cesarean) with term newborns (37\u0026ndash;41 weeks), exclusively breastfeeding, having at least completed primary education, and able to use a smartphone with WhatsApp. Exclusion criteria included maternal factors affecting lactation (e.g., flat/inverted nipples, diabetes, hypertension, morbid obesity, endocrine disorders), interfering medications, and active smoking, as well as newborn conditions such as congenital heart disease, cleft lip/palate, ankyloglossia, neonatal hypoglycaemia, or \u0026ge;7% in-hospital weight loss. Sites were public facilities providing routine postpartum care and able to accommodate a 2-hour discharge workshop. The intervention was delivered by Crianzamor health professionals trained in the Uriclarity Program and AUS prior to trial start, with no additional provider eligibility criteria specified.\u003c/p\u003e\n\u003ch2\u003eIntervention and measures\u003c/h2\u003e\n\u003cp\u003eWomen in the intervention arm received the Uriclarity Program (see Supplementary Materials) on postpartum day 1\u0026ndash;2, consisting of a two-hour discharge workshop using practical tools (breast/infant simulators, cloth diapers, AUS urine-color chart, and infographics), followed by standardized WhatsApp messages and short tutorial videos until day 2 after the workshop. Withdrawal criteria included non-response to WhatsApp, failure to submit Uriscale reports, or introduction of formula, bottles, or pacifiers. Controls received standard care with routine breastfeeding counselling before discharge. Outcomes were measured with the MILQ (4-item dichotomous scale, total 0\u0026ndash;8; higher scores indicate greater perceived milk sufficiency/lower PIMS) and the AUS (urine-color ordinal scale 1\u0026ndash;5; lower scores reflect lighter urine and higher milk transfer). Both the AUS and the MILQ have, to date, undergone content-validation and clinical-use studies, providing initial evidence of adequate content validity indices, acceptable operational performance, and favourable maternal perceptions of their ease of use and clinical utility.\u003c/p\u003e\n\u003ch2\u003eOutcomes\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary outcome\u003c/strong\u003e. Comparison between study groups in PIMS, measured with MILQ on postpartum days 1 (baseline), 3, 7, and 14. PIMS was measured with the 4-item MILQ, administered by an interviewer in person on day 1 and by telephone on the remaining days. Responses were provided directly by participants; higher scores indicate better perception.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary outcome\u003c/strong\u003e. Association between the AUS score and the PIMS.\u003c/p\u003e\n\u003ch2\u003eHarms\u003c/h2\u003e\n\u003cp\u003eNo specific harms were anticipated due to the educational nature of the intervention. However, mothers and infants were monitored for any clinical adverse event that could interfere with breastfeeding (e.g., neonatal hypoglycaemia, hospitalization, or maternal complications). No systematic adverse-event collection was performed, and no harms related to the intervention were reported.\u003c/p\u003e\n\u003ch2\u003eSample size\u003c/h2\u003e\n\u003cp\u003eThe sample size was determined for detecting a clinically meaningful absolute difference in the proportion of mothers with MILQ \u0026ge; 7 at day 14 (binary threshold chosen for feasibility and interpretability), with \u0026alpha;=0.05 and \u0026beta;=0.10, plus 30% anticipated loss.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1769693469.png\" width=\"747\" height=\"130\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eSubstituting values (Z\u0026alpha; = 1.96, Z\u0026beta; = 1.28, P1 = 0.1, P2 = 0.5, P = 0.3) and accounting for a 30% anticipated loss, the adjusted sample size was 38 participants per group. To strengthen statistical power, the sample size was rounded to 50 participants per group.\u003c/p\u003e\n\u003ch2\u003eInterim analyses\u003c/h2\u003e\n\u003cp\u003eNo interim analyses or stopping guidelines were planned, given the small sample size, the short follow-up period, and the low-risk nature of the educational intervention.\u003c/p\u003e\n\u003ch2\u003eSequence generation\u003c/h2\u003e\n\u003cp\u003eThe random allocation sequence was computer-generated using R (version 4.4.0). A script produced a new random sequence of 100 numbers each time it was run, ensuring the assignment order could not be anticipated even if the code were obtained. Simple, unrestricted randomization with a 1:1 allocation ratio was used.\u003c/p\u003e\n\u003ch2\u003eAllocation\u003c/h2\u003e\n\u003cp\u003eAllocation concealment was ensured with sequentially numbered, opaque, sealed, light-proof envelopes. The envelopes were prepared by a staff member not associated with the trial, who remained anonymous throughout the study. Envelopes were released only after the recruiter had confirmed the number of eligible participants, preventing any advance access to the allocation sequence. The random sequence was generated by an independent individual who did not take part in recruitment. Participant enrollment was performed by members of the Crianzamor team at the hospitals, and assignment to the intervention or control group was carried out by opening the sealed envelopes in sequential order.\u003c/p\u003e\n\u003ch2\u003eBlinding\u003c/h2\u003e\n\u003cp\u003eParticipants and care providers were not blinded due to the nature of the intervention. Telephone outcome assessors were blinded to group allocation and used a standardized script. The data analyst was blinded by coding the groups as A and B prior to statistical analysis; group identities were revealed only after analyses were completed.\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eAll analyses were conducted in R (v4.4.0) using two-sided tests with \u0026alpha; = 0.05. Between-group differences in MILQ were assessed with the Mann\u0026ndash;Whitney U test. The primary longitudinal analysis used a cumulative-link proportional-odds mixed model (logit) for ordinal MILQ, including a participant-level random intercept, adjustment for maternal age, parity, and education, and time modeled as a linear trend. For secondary analyses, AUS (measured on days 3, 7, and 14) was entered as an ordinal predictor in proportional-odds logistic regression to evaluate dose\u0026ndash;response associations with MILQ, and ROC curves were used to explore AUS thresholds distinguishing low vs. high MILQ. For clinical interpretability, ordinal effects were translated into absolute probabilities of achieving MILQ \u0026ge; 7 at day 14, reporting risk differences and NNT (1/RD).\u003c/p\u003e\n\u003cp\u003eAll randomized participants were analyzed according to intention-to-treat. Missing data were assumed missing at random; the mixed model accommodated incomplete repeated measures without additional imputation. For day-specific Mann\u0026ndash;Whitney comparisons, participants missing that time point were excluded only from that comparison. Participants with missing AUS values on a given day were excluded from dose\u0026ndash;response and ROC analyses for that day but remained in the trial population for other analyses. No subgroup analyses were performed. As prespecified, a mixed-effects binary logistic model for MILQ \u0026ge; 7 was also fitted as a robustness check.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eParticipant flow and recruitment\u003c/h2\u003e\n\u003cp\u003eOf 114 mothers assessed for eligibility, 14 declined and 100 were randomized (54 to intervention, 46 to control). All received their allocated care and were included in the intention-to-treat primary analysis (Figure 1). In the intervention group, six mothers were lost to follow-up: one due to no response to telephone calls or WhatsApp messages; two for failing to submit requested information; one due to maternal hospitalization; one due to neonatal complications (readmission for hyperbilirubinaemia with initiation of formula feeding); and one due to a medically indicated weaning (suspected cow\u0026rsquo;s milk protein allergy with initiation of formula feeding). In the control group, three mothers were lost to follow-up because they did not respond to telephone calls or WhatsApp messages. Recruitment occurred from May 28 to August 10, 2025, and follow-up was completed by August 24, 2025, with the trial ending as planned and without early termination.\u003c/p\u003e\n\u003ch2\u003eIntervention delivered and concomitant care\u003c/h2\u003e\n\u003cp\u003eThe intervention group attended a structured educational workshop (Uriclarity Program) of approximately two hours, delivered in person by trained health professionals. Implementation fidelity was ensured through a standardized teaching guide and a facilitator-completed checklist. All participants in the intervention group received the full workshop session, with no deviations from the planned content.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring the trial, both groups continued to receive standard postpartum care provided by local health services. No restrictions were imposed on concomitant care, and no between-group differences were observed in additional health services accessed outside the study protocol. Routine pre-discharge breastfeeding counseling was provided by on-duty maternity staff (midwives or nurses) in accordance with the institutional protocol. Receipt of counseling was confirmed in the discharge records for 100% of control-group participants.\u003c/p\u003e\n\u003ch2\u003eBaseline data\u003c/h2\u003e\n\u003cp\u003eTable 1 summarizes baseline demographic and clinical characteristics of participants by study group. Maternal age, education, parity, gestational age at birth, neonatal sex, birth weight, and the MILQ score were comparable between groups, with no clinically relevant imbalances observed.\u003c/p\u003e\n\u003ch2\u003eData analyses\u003c/h2\u003e\n\u003cp\u003eWe analyzed 100 participants across four visits, yielding 380 observations (see Table 2). At all follow-up visits, between-group comparisons consistently favored the intervention (all Wilcoxon tests p \u0026lt; 0.001). The Hodges\u0026ndash;Lehmann median difference (Intervention \u0026minus; Control) was 2.00, with 95% CIs ranging from 1.00\u0026ndash;2.00 to 1.00\u0026ndash;3.00. In an adjusted ordinal mixed model, the intervention increased the odds of being in a higher MILQ category (see Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBetween-group comparisons of MILQ scores\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;At baseline (day 1), MILQ scores distributions were similar in both arms (median 8 [IQR 7\u0026ndash;8] in each group). At all follow-up visits, between-group comparisons favored the intervention (Wilcoxon p \u0026lt; 0.001 at every visit). The Hodges\u0026ndash;Lehmann median difference (Intervention \u0026minus; Control) was 2.00, with 95% CIs ranging from 1.00\u0026ndash;2.00 to 1.00\u0026ndash;3.00 across visits. Sample sizes by visit are shown in Table 2. 40/48 (83.3%) in the intervention versus 13/43 (30.2%) in control achieved MILQ \u0026ge; 7. The absolute RD was +53.1 percentage points (95% CI +33.4 to +67.2), corresponding to an NNT of 1.88 (95% CI 1.49 to 2.99).\u003c/p\u003e\n\u003cp\u003eIn the longitudinal ordinal mixed model (random intercept per participant), with time modeled as a linear trend and adjusting for maternal age, parity, and education, the intervention was associated with higher MILQ scores (OR 10.64; 95% CI 4.26\u0026ndash;26.58; p \u0026lt; 0.001). Time showed a negative trend across visits (per 1-day increase OR 0.63; 95% CI 0.52\u0026ndash;0.77; p \u0026lt; 0.001). Maternal age, parity, and education were not significantly associated with PIMS (all p \u0026ge; 0.55) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between AUS and MILQ\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;To quantify the day-specific relationship between the AUS and MILQ, separate proportional-odds logistic models were fitted for days 3, 7, and 14, adjusting for group, maternal age, parity, and education. Higher AUS scores were associated with lower odds of being in a higher MILQ category: day 3, adjusted OR 0.54 (95% CI 0.30\u0026ndash;0.98; p = 0.044); day 7, OR 0.23 (95% CI 0.10\u0026ndash;0.51; p \u0026lt; 0.001); day 14, OR 0.12 (95% CI 0.01\u0026ndash;1.12; p = 0.062).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic performance of the AUS\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;ROC analyses showed modest discrimination, with AUCs between 0.60 and 0.69 on all days. Using the Youden-selected cut-off of AUS \u0026le; 2, sensitivity was high (0.84\u0026ndash;0.95), whereas specificity was low (0.33\u0026ndash;0.50). Positive predictive values were high (0.70\u0026ndash;0.95), while negative predictive values were low to moderate (0.33\u0026ndash;0.55). Consequently, a low AUS (1\u0026ndash;2) is most useful as a sensitive screen to identify mothers at high probability of MILQ \u0026ge; 7, particularly on day 7, whereas AUS \u0026gt; 2 does not safely exclude MILQ \u0026ge; 7. Detailed operating characteristics are provided in Table 4. No participant recorded an AUS score of 5 at any assessment.\u003c/p\u003e\n\u003ch2\u003eAdverse events\u003c/h2\u003e\n\u003cp\u003eNo harms or unintended events related to the intervention were observed in either group during follow-up (0/54 vs 0/46). Clinical events contributing to loss to follow-up (e.g., maternal hospitalization, neonatal readmission) were not considered study related.\u003c/p\u003e\n\u003ch2\u003eAncillary analyses\u003c/h2\u003e\n\u003cp\u003eA mixed-effects binary logistic model using MILQ \u0026ge; 7 as the outcome showed an intervention effect in the same direction (OR 10.49; 95% CI 3.81\u0026ndash;28.89; p \u0026lt; 0.001), supporting the robustness of the primary ordinal analysis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eMain findings\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;We demonstrated that the Uriclarity Program\u0026mdash;a single 2-hour predischarge workshop plus 4 days of standardized messages that trains mothers to prevent the main breastfeeding difficulties and teaches them to interpret neonatal urine color to estimate milk transfer\u0026mdash;reduced PIMS by an order of magnitude (OR 10.6) within the first two postpartum weeks; and, given the limited literature using PIMS as an outcome, the observed effect lies at the upper end of magnitudes reported for educational/psychobehavioral interventions related to PIMS/self-efficacy (Galipeau et al., 2018).\u003c/p\u003e\n\u003cp\u003eIn this single-blind randomized clinical trial, Uriclarity produced a large and consistent improvement in reducing PIMS during the first two postpartum weeks: at all assessments, the typical between-group difference was +2 points, and the ordinal mixed model showed that mothers assigned to Uriclarity had 10 times higher odds of being in a better MILQ category, adjusted for age, parity, and education. Clinically, this 2-point shift on the 0\u0026ndash;8 MILQ scale translates into one additional mother out of 2 reaching MILQ \u0026ge; 7 by day 14 (RD +53 pp; NNT = 2). For a brief, low-cost discharge-time intervention, this magnitude represents a large, patient-relevant benefit. As expected, MILQ scores tended to decrease over time in both groups (per-day OR 0.63), while the intervention benefit persisted. The sensitivity analysis (MILQ \u0026ge; 7) yielded identical conclusions in the same direction (OR 10.49).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMechanisms and biological plausibility\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Mothers with PIMS often turn to infant formula and to weaning (Gatti, 2008; Doulougeri et al., 2013; Flaherman et al., 2016). Although in most cases PIMS is not supported by true milk-production insufficiency\u0026mdash;that is, it is usually a misperception (Whipps \u0026amp; Demirci, 2021; Kellams et al., 2017)\u0026mdash;failure to prevent or treat it in time can turn it into a genuine insufficiency. Maternal psychological distress due to PIMS can reduce oxytocin release (Ueda et al., 1994; Uvn\u0026auml;s-Moberg et al., 2020), impair the milk ejection (let-down) reflex, and lead to incomplete breast emptying at each feed, resulting in a clear reduction in milk supply. Likewise, elevated serum cortisol may reduce insulin sensitivity and trigger a true decrease in milk production (Nagel et al., 2022). To prevent PIMS, it is recommended to provide mothers with reliable parameters that allow them to objectify milk transfer during feeds (Huang et al., 2022; Nagel et al., 2022), given their value for modulating anxiety and strengthening maternal self-confidence (Kent et al., 2015). In Uriclarity, the AUS operated as an immediate, comprehensible biometric signal to monitor transfer\u0026mdash;a pragmatic alternative to test-weighing when the latter is not feasible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation in context with the evidence\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Our findings are consistent with reviews linking self-efficacy\u0026ndash;focused and early-support interventions to better breastfeeding outcomes in the first month. The systematic review and meta-analysis by Galipeau et al. (2018) estimated a moderate effect (SMD = 0.40; 95% CI 0.11\u0026ndash;0.69; p = 0.006) on self-efficacy\u0026mdash;an indirect indicator of reduced PIMS\u0026mdash;whereas the Uriclarity Program showed a large effect (OR = 10.64), demonstrating a direct and clinically relevant impact on perceived milk sufficiency. Thus, this trial\u0026rsquo;s results empirically confirm Galipeau\u0026rsquo;s hypothesis: interventions that strengthen maternal confidence and competence reduce the perception of insufficient milk.\u003c/p\u003e\n\u003cp\u003eTranslated into practice, a 2-point increase in MILQ reflects fewer doubts about milk production and therefore a lower risk of introducing supplements. The structured educational component plus active monitoring of milk transfer with the AUS appear to act by strengthening self-efficacy and enabling early problem resolution, consistent with literature that links self-efficacy\u0026ndash;based interventions to improved breastfeeding outcomes in the first postpartum month (Galipeau et al., 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds to the existing evidence\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;PIMS is a leading reason for breastfeeding cessation, yet viable preventive interventions are scarce, especially in low- and middle-income countries. This randomized trial provides solid experimental evidence in a middle-income setting, using a replicable, public-health\u0026ndash;feasible strategy to prevent/reduce PIMS. The systematic review by Galipeau et al. (2018) identified maternal self-efficacy as a key mediator but found very little direct evidence on PIMS (only 1/17 studies reported this outcome), precluding a PIMS-specific meta-analysis and noting methodological heterogeneity; our results address that gap, showing a large, clinically relevant effect.\u003c/p\u003e\n\u003cp\u003eWe also introduce the AUS as a practical home tool to monitor milk transfer, which reinforces positive self-perception and early response, offers a pragmatic alternative to costly transfer measurements, and preserves maternal agency\u0026mdash;aligned with international recommendations to promote self-efficacy (Galipeau et al., 2018). The effects of Uriclarity were consistent across primary and sensitivity analyses, suggesting a clinically meaningful, potentially durable impact that warrants multicenter evaluation with longer follow-up. Taken together, the findings support Uriclarity as a low-cost public health strategy to reduce PIMS and strengthen maternal confidence, contributing to WHO targets for exclusive breastfeeding.\u003c/p\u003e\n\u003cp\u003eFinally, the AUS showed ROC performance with AUC 0.60\u0026ndash;0.69 and high sensitivity at the AUS \u0026le; 2 threshold (0.84\u0026ndash;0.95), with high PPV in this sample; given its low\u0026ndash;moderate specificity, it should not be used to rule out high PIMS without clinical evaluation, consistent with Youden index\u0026ndash;based threshold selection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInvestment and feasibility\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Implementing Uriclarity requires substantially less investment than other strategies to counter PIMS that depend on technological platforms, automated content, and monitoring (Demirci et al., 2020); trained visiting nurses with associated training, transport, and supplies (Kronborg et al., 2007); intensive self-efficacy programs with higher personnel and material costs (Chainakin et al., 2023); postpartum home-visit programs (Wood et al., 2017); or galactagogues requiring medication costs, safety monitoring, and specialized staff (Saxena et al., 2025). Because it is integrated into the hospital discharge workflow, Uriclarity does not require a new service, infrastructure, or additional equipment; its brief, simple, and practical workshop can be delivered by existing staff, and the 4-day WhatsApp follow-up entails no special monitors or travel. Its effect also appears independent of maternal age, parity, and education (covariates not associated with PIMS after adjustment), suggesting broad applicability.\u003c/p\u003e\n\u003cp\u003eAssessed with RE-AIM (Glasgow et al., 1999) and NPT, the program emerges as model, innovative, accessible, sustainable, and replicable, with high potential for institutional integration in resource-limited settings; its brief, culturally adapted, mother-empowering approach\u0026mdash;including the tet\u0026eacute; dance (Ashiyama Vega et al., 2025)\u0026mdash;reinforces learning without operational burden, supporting institutionalization as a Latin American public-health strategy. We propose incorporating the AUS as a sensitive triage signal: a AUS \u0026gt; 2 (clinical threshold) would trigger brief, focused proactive contact with health personnel (without replacing full evaluation), while maintaining comprehensive clinical assessment for all mothers who express concerns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Follow-up was limited to two postpartum weeks, so longer-term outcomes (e.g., exclusive breastfeeding duration and other objective endpoints) were not assessed. Eligibility required primary education and the ability to use WhatsApp, and participants were recruited from three public hospitals in one region, which may limit generalizability. Because participants and providers were not blinded and MILQ is self-reported, reporting effects are possible despite blinded telephone outcome assessors and a blinded analyst. Finally, adverse events were not collected through systematic active surveillance; no intervention-related harms were reported, but rare events could have been missed.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA brief, low-cost predischarge program embedded in the hospital discharge workflow (Uriclarity) produced large and consistent improvements in perceived milk sufficiency over the first two postpartum weeks. These findings support the feasibility and potential effectiveness of scalable discharge-based education combined with short-term digital reinforcement. Larger multicenter trials with longer follow-up and objective breastfeeding outcomes are warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAUC:\u003c/strong\u003e Area under the receiver operating characteristic curve\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAUS:\u003c/strong\u003e Ashiyama Uriscale\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCI:\u003c/strong\u003e Confidence interval\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEBF:\u003c/strong\u003e Exclusive breastfeeding\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eITT:\u003c/strong\u003e Intention-to-treat\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMILQ:\u003c/strong\u003e Maternal Insufficient Lactation Questionnaire\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNNT:\u003c/strong\u003e Number needed to treat\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOR:\u003c/strong\u003e Odds ratio\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePIMS:\u003c/strong\u003e Perceived insufficient milk supply\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRD:\u003c/strong\u003e Risk difference\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eROC:\u003c/strong\u003e Receiver operating characteristic\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Hospital Daniel Alcides Carri\u0026oacute;n (990-2024). All participants provided written informed consent in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eIt was planned to make de-identified individual participant data (IPD) and the study protocol available, upon reasonable request, for research purposes only, beginning 6 months after publication of the primary results and for at least 1 year. Access will be restricted to qualified researchers affiliated with academic or health institutions, subject to ethics approval and institutional agreements. Data will be shared via a secure repository or an institutional data-sharing agreement and may not be used for commercial purposes or to re-identify participants. The full trial record is publicly available at ClinicalTrials.gov (NCT06857461). The study protocol and statistical analysis plan are available on the Open Science Framework (OSF) (DOI: 10.17605/OSF.IO/C4MFY).\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNo external funding.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eJAV conceptualized the study and contributed to the methodology alongside JRA. JAV and MYR coordinated participant recruitment and data collection. JAV and JRA prepared the introduction and background sections. All three authors (JRA, MYR, and JAV) collaboratively wrote the discussion and conclusions. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAshiyama Vega, J., Yrigoyen Rojas, M., \u0026amp; Ravichagua Ashiyama, J. (2025). Effect of tet\u0026eacute; dance on lactation session duration in irritable infants in Peru assessed in a randomized controlled trial. \u003cem\u003eScientific Reports, 15\u003c/em\u003e(1), 9808. https://doi.org/10.1038/s41598-025-95236-y\u003c/li\u003e\n\u003cli\u003eChainakin, P., Sansiriphun, N., Chaloumsuk, N., \u0026amp; Deeluea, J. (2023). Effectiveness of the breastfeeding self-efficacy and family support enhancement program among first-time postpartum mothers: A randomized controlled trial. \u003cem\u003ePacific Rim International Journal of Nursing Research, 27\u003c/em\u003e(4), 694\u0026ndash;710. https://he02.tci-thaijo.org/index.php/PRIJNR/article/view/262625\u003c/li\u003e\n\u003cli\u003eDemirci, J. R., Suffoletto, B., Doman, J., Glasser, M., Chang, J. C., Sereika, S. M., \u0026amp; Bogen, D. L. (2020). The development and evaluation of a text message program to prevent perceived insufficient milk among first-time mothers: Retrospective analysis of a randomized controlled trial. \u003cem\u003eJMIR mHealth and uHealth, 8\u003c/em\u003e(4), e17328. https://doi.org/10.2196/17328\u003c/li\u003e\n\u003cli\u003eDoulougeri, K., Panagopoulou, E., \u0026amp; Montgomery, A. (2013). The impact of maternal stress on initiation and establishment of breastfeeding. \u003cem\u003eJournal of Neonatal Nursing, 19\u003c/em\u003e(4), 162\u0026ndash;167. https://doi.org/10.1016/j.jnn.2013.02.003\u003c/li\u003e\n\u003cli\u003eFlaherman, V. J., Beiler, J. S., Cabana, M. D., \u0026amp; Paul, I. M. (2016). Relationship of newborn weight loss to milk supply concern and anxiety: The impact on breastfeeding duration. \u003cem\u003eMaternal \u0026amp; Child Nutrition, 12\u003c/em\u003e(3), 463\u0026ndash;472. https://doi.org/10.1111/mcn.12171\u003c/li\u003e\n\u003cli\u003eGalipeau, R., Baillot, A., Trottier, A., \u0026amp; Lemire, L. (2018). Effectiveness of interventions on breastfeeding self-efficacy and perceived insufficient milk supply: A systematic review and meta-analysis. \u003cem\u003eMaternal \u0026amp; Child Nutrition, 14\u003c/em\u003e(3), e12607. https://doi.org/10.1111/mcn.12607\u003c/li\u003e\n\u003cli\u003eGalipeau, R., Dumas, L., \u0026amp; Lepage, M. (2017). Perception of not having enough milk and actual milk production of first-time breastfeeding mothers: Is there a difference? \u003cem\u003eBreastfeeding Medicine, 12\u003c/em\u003e(4), 210\u0026ndash;217. https://doi.org/10.1089/bfm.2016.0183\u003c/li\u003e\n\u003cli\u003eGatti, L. (2008). Maternal perceptions of insufficient milk supply in breastfeeding. \u003cem\u003eJournal of Nursing Scholarship, 40\u003c/em\u003e(4), 355\u0026ndash;363. https://doi.org/10.1111/j.1547-5069.2008.00234.x\u003c/li\u003e\n\u003cli\u003eGlasgow, R. E., Vogt, T. M., \u0026amp; Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. \u003cem\u003eAmerican Journal of Public Health, 89\u003c/em\u003e(9), 1322\u0026ndash;1327. https://doi.org/10.2105/AJPH.89.9.1322\u003c/li\u003e\n\u003cli\u003eHuang, Y., Liu, Y., Yu, X. Y., \u0026amp; Zeng, T. Y. (2022). The rates and factors of perceived insufficient milk supply: A systematic review. \u003cem\u003eMaternal \u0026amp; Child Nutrition, 18\u003c/em\u003e(1), e13255. https://doi.org/10.1111/mcn.13255\u003c/li\u003e\n\u003cli\u003eInstituto Nacional de Estad\u0026iacute;stica e Inform\u0026aacute;tica. (2024). \u003cem\u003eEncuesta demogr\u0026aacute;fica y de salud familiar 2024: Nacional y departamental\u003c/em\u003e. INEI. https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib2016/libro.pdf\u003c/li\u003e\n\u003cli\u003eInternational Atomic Energy Agency. (2010). \u003cem\u003eStable isotope technique to assess intake of human milk in breastfed infants\u003c/em\u003e (IAEA Human Health Series No. 7). IAEA. https://www.osti.gov/etdeweb/biblio/21535382\u003c/li\u003e\n\u003cli\u003eKellams, A., Harrel, C., Omage, S., Gregory, C., Rosen-Carole, C., \u0026amp; Academy of Breastfeeding Medicine. (2017). ABM clinical protocol #3: Supplementary feedings in the healthy term breastfed neonate, revised 2017. \u003cem\u003eBreastfeeding Medicine, 12\u003c/em\u003e(4), 188\u0026ndash;198. https://doi.org/10.1089/bfm.2017.29038.ajk\u003c/li\u003e\n\u003cli\u003eKent, J. C., Hepworth, A. R., Langton, D. B., \u0026amp; Hartmann, P. E. (2015). Impact of measuring milk production by test weighing on breastfeeding confidence in mothers of term infants. \u003cem\u003eBreastfeeding Medicine, 10\u003c/em\u003e(6), 318\u0026ndash;325. https://doi.org/10.1089/bfm.2015.0025\u003c/li\u003e\n\u003cli\u003eKronborg, H., V\u0026aelig;th, M., Olsen, J., Iversen, L., \u0026amp; Harder, I. (2007). Effect of early postnatal breastfeeding support: A cluster-randomized community based trial. \u003cem\u003eActa Paediatrica, 96\u003c/em\u003e(7), 1064\u0026ndash;1070. https://doi.org/10.1111/j.1651-2227.2007.00341.x\u003c/li\u003e\n\u003cli\u003eLi, R., Fein, S. B., Chen, J., \u0026amp; Grummer-Strawn, L. M. (2008). Why mothers stop breastfeeding: Mothers\u0026rsquo; self-reported reasons for stopping during the first year. \u003cem\u003ePediatrics, 122\u003c/em\u003e(Suppl. 2), S69\u0026ndash;S76. https://doi.org/10.1542/peds.2008-1315i\u003c/li\u003e\n\u003cli\u003eNagel, E. M., Howland, M. A., Pando, C., Stang, J., Mason, S. M., Fields, D. A., \u0026amp; colleagues. (2022). Maternal psychological distress and lactation and breastfeeding outcomes: A narrative review. \u003cem\u003eClinical Therapeutics, 44\u003c/em\u003e(2), 215\u0026ndash;227. https://doi.org/10.1016/j.clinthera.2021.12.005\u003c/li\u003e\n\u003cli\u003eOdom, E. C., Li, R., Scanlon, K. S., Perrine, C. G., \u0026amp; Grummer-Strawn, L. (2013). Reasons for earlier than desired cessation of breastfeeding. \u003cem\u003ePediatrics, 131\u003c/em\u003e(3), e726\u0026ndash;e732. https://doi.org/10.1542/peds.2012-1295\u003c/li\u003e\n\u003cli\u003eOlalere, O., \u0026amp; Harley, C. (2024). Why women discontinue exclusive breastfeeding: A scoping review. \u003cem\u003eBritish Journal of Midwifery, 32\u003c/em\u003e(12), 673\u0026ndash;682. https://doi.org/10.12968/bjom.2024.0044\u003c/li\u003e\n\u003cli\u003eRollins, N. C., Bhandari, N., Hajeebhoy, N., Horton, S., Lutter, C. K., Martines, J. C., Piwoz, E. G., Richter, L. M., \u0026amp; Victora, C. G. (2016). Why invest, and what it will take to improve breastfeeding practices? \u003cem\u003eThe Lancet, 387\u003c/em\u003e(10017), 491\u0026ndash;504.\u003c/li\u003e\n\u003cli\u003eSaxena, U., Ota, S., Rajput, S., Anand, B., Tripathi, A., Singhal, R., \u0026amp; colleagues. (2025). Clinical evaluation of ayush-SS granules in exclusively breastfeeding mothers with insufficient lactation: A randomized, double-blind, placebo-controlled trial. \u003cem\u003eInternational Breastfeeding Journal, 20\u003c/em\u003e(1), 26. https://doi.org/10.1186/s13006-025-00721-9\u003c/li\u003e\n\u003cli\u003eUNICEF. (2025). \u003cem\u003eBreastfeeding\u003c/em\u003e. UNICEF Data. https://data.unicef.org/topic/nutrition/breastfeeding/\u003c/li\u003e\n\u003cli\u003eUNICEF, \u0026amp; World Health Organization. (2024). \u003cem\u003eGlobal breastfeeding scorecard 2024\u003c/em\u003e (Child Nutrition and Development). UNICEF/WHO. https://knowledge.unicef.org/child-nutrition-and-development/resource/global-breastfeeding-scorecard-2024\u003c/li\u003e\n\u003cli\u003eUeda, T., Yokoyama, Y., Irahara, M., \u0026amp; Aono, T. (1994). Influence of psychological stress on suckling-induced pulsatile oxytocin release. \u003cem\u003eObstetrics \u0026amp; Gynecology, 84\u003c/em\u003e(2), 259\u0026ndash;262. https://journals.lww.com/greenjournal/Abstract/1994/08000/Influence_of_Psychological_Stress_on.21.aspx\u003c/li\u003e\n\u003cli\u003eUvn\u0026auml;s-Moberg, K., Ekstr\u0026ouml;m-Bergstr\u0026ouml;m, A., Buckley, S., Massarotti, C., Pajalic, Z., Luegmair, K., Kotlowska, A., Lengler, L., Olza, I., Grylka-Baeschlin, S., \u0026amp; Leahy-Warren, P. (2020). Maternal plasma levels of oxytocin during breastfeeding\u0026mdash;A systematic review. \u003cem\u003ePLOS ONE, 15\u003c/em\u003e(8), e0235806. https://doi.org/10.1371/journal.pone.0235806\u003c/li\u003e\n\u003cli\u003eVictora, C. G., Bahl, R., Barros, A. J. D., Fran\u0026ccedil;a, G. V. A., Horton, S., Krasevec, J., Murch, S., Sankar, M. J., Walker, N., \u0026amp; Rollins, N. C. (2016). Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. \u003cem\u003eThe Lancet, 387\u003c/em\u003e(10017), 475\u0026ndash;490.\u003c/li\u003e\n\u003cli\u003eWalters, D. D., Phan, L. T. H., \u0026amp; Mathisen, R. (2019). The cost of not breastfeeding: Global results from a new tool. \u003cem\u003eHealth Policy and Planning, 34\u003c/em\u003e(6), 407\u0026ndash;417. https://doi.org/10.1093/heapol/czz050\u003c/li\u003e\n\u003cli\u003eWhipps, M. D., \u0026amp; Demirci, J. R. (2021). The sleeper effect of perceived insufficient milk supply in US mothers. \u003cem\u003ePublic Health Nutrition, 24\u003c/em\u003e(5), 935\u0026ndash;941. https://doi.org/10.1017/S1368980020001482\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2018). \u003cem\u003eGuideline: Counselling of women to improve breastfeeding practices\u003c/em\u003e. WHO. https://www.ncbi.nlm.nih.gov/books/NBK539309/\u003c/li\u003e\n\u003cli\u003eWood, N. K., Sanders, E. A., Lewis, F. M., Woods, N. F., \u0026amp; Blackburn, S. T. (2017). Pilot test of a home-based program to prevent perceived insufficient milk. \u003cem\u003eWomen and Birth, 30\u003c/em\u003e(6), 472\u0026ndash;480. https://doi.org/10.1016/j.wombi.2017.04.006\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTab 1.\u003c/strong\u003e Baseline characteristics of the intervention and control groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003eIntervention (n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003eControl (n=46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eMaternal age, mean (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e29.6 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e26.7 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eMaternal education, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ndash; Primary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e20 (37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e19 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ndash; Secondary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e23 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e22 (47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ndash; Higher\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e11 (20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e5 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eParity, median (IQR)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e2 (2\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eGestational age at birth, mean (SD), weeks\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e38.6 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e38.8 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonatal sex, male, n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e27 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e22 (47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eBirth weight, mean (SD), grams\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e3242.9 (511.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e3293.2 (379.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 37.1025%;\"\u003e\n \u003cp\u003e\u003cem\u003eMILQ score, median (IQR)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4488%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTab 2.\u003c/strong\u003e Between-group comparisons of PIMS (MILQ) by visit.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.73913%;\"\u003e\n \u003cp\u003eDay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003eControl (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8261%;\"\u003e\n \u003cp\u003eIntervention (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003eControl median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1739%;\"\u003e\n \u003cp\u003eIntervention median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2174%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.8696%;\"\u003e\n \u003cp\u003eEffect (HL, 95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.73913%;\"\u003e\n \u003cp\u003e\u003cem\u003ePIMS1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8261%;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1739%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2174%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.8696%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.73913%;\"\u003e\n \u003cp\u003e\u003cem\u003ePIMS3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8261%;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e5.5 (4\u0026ndash;6.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1739%;\"\u003e\n \u003cp\u003e8 (6\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2174%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.8696%;\"\u003e\n \u003cp\u003e2.00 (1.00\u0026ndash;2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.73913%;\"\u003e\n \u003cp\u003e\u003cem\u003ePIMS7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8261%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e6 (4.75\u0026ndash;7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1739%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2174%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.8696%;\"\u003e\n \u003cp\u003e2.00 (1.00\u0026ndash;2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.73913%;\"\u003e\n \u003cp\u003e\u003cem\u003ePIMS14\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8261%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.087%;\"\u003e\n \u003cp\u003e5 (4\u0026ndash;7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1739%;\"\u003e\n \u003cp\u003e8 (7\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2174%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.8696%;\"\u003e\n \u003cp\u003e2.00 (1.00\u0026ndash;3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTab 3.\u003c/strong\u003e Ordinal mixed-effects model for the MILQ score\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eIntervention vs Control\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.64 (4.26\u0026ndash;26.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eTime (per 1-day increase)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.63 (0.52\u0026ndash;0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eMaternal age (per year)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.02 (0.95\u0026ndash;1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eParity (per unit)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.05 (0.66\u0026ndash;1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eSecondary vs Primary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.16 (0.46\u0026ndash;2.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cem\u003eHigher vs Primary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.94 (0.26\u0026ndash;3.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTab 4.\u003c/strong\u003e ROC performance of AUS for identifying a high MILQ score\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eMetric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDay 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDay 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDay 14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eAUC (95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.60 (0.45\u0026ndash;0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.69 (0.51\u0026ndash;0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.64 (0.31\u0026ndash;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eOptimal cut-off\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAUS \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAUS \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAUS \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eSensitivity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eSpecificity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003ePPV\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eNPV\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breastfeeding, Breastfeeding, Exclusive, Self Efficacy, Postpartum Period, Text Messaging, Mobile Applications, Randomized Controlled Trial","lastPublishedDoi":"10.21203/rs.3.rs-8634552/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8634552/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePerceived insufficient milk supply (PIMS) is a common early postpartum concern; this study tested whether a brief predischarge program (Uriclarity) reduces PIMS in the early postpartum period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eParallel-group, superiority, single-blind randomized trial (1:1; computer-generated simple randomization; allocation concealment with sequentially numbered opaque sealed envelopes). Outcome assessors and the data analyst were blinded. Conducted in three public hospitals in Piura, Peru. Participants were postpartum women ≥18 years, 24–48 h after term birth, exclusively breastfeeding. Interventions: Uriclarity—2-hour in-person educational workshop during discharge plus standardized WhatsApp messages/videos through the first two days after the workshop—versus routine pre-discharge breastfeeding counseling. Primary outcome was PIMS (MILQ, 0–8; higher = better perceived sufficiency) on days 1, 3, 7, and 14. Between-group comparisons used the Wilcoxon rank-sum test; the prespecified primary analysis was a cumulative-link proportional-odds mixed model (random intercept), adjusted for maternal age, parity, and education; intention-to-treat.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf 114 screened, 100 were randomized (54 intervention; 46 control) and all were analyzed. At each follow-up, medians favored the intervention (all p \u0026lt; 0.001); typical Hodges–Lehmann difference +2.00 points (95% CI 1.00–2.00 to 1.00–3.00). By day 14, 83.3% (40/48) vs 30.2% (13/43) achieved MILQ ≥ 7 (RD +53.1 pp; NNT = 2). The adjusted mixed model showed markedly higher odds of being in a better MILQ category with Uriclarity (OR 10.64, 95% CI 4.26–26.58; p \u0026lt; 0.001). No intervention-related harms occurred. As a secondary finding, the AUS showed modest ROC discrimination (AUC 0.60–0.69) with high sensitivity at AUS ≤ 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eA brief, low-cost program embedded in the discharge workflow produced large, consistent reductions in PIMS over two postpartum weeks. Larger multicenter trials with longer follow-up and hard breastfeeding outcomes are warranted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e ClinicalTrials.gov NCT06857461 (prospective; registered February 26, 2025).\u003c/p\u003e","manuscriptTitle":"Uriclarity Program Reduces Perceived Insufficient Milk Supply in Early Postpartum: Randomized Controlled Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:21:08","doi":"10.21203/rs.3.rs-8634552/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"277714787941990393285583502816601873759","date":"2026-05-04T13:52:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T22:16:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49242938988365649405863676669878709831","date":"2026-02-18T19:38:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-26T16:48:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-21T18:28:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-21T18:26:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Breastfeeding Journal","date":"2026-01-19T02:58:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d2a4917-fd67-4d9f-9203-6d58ed7873f5","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"277714787941990393285583502816601873759","date":"2026-05-04T13:52:18+00:00","index":62,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T16:21:08+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 16:21:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8634552","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8634552","identity":"rs-8634552","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}