Recruitment Challenges in Mother–Infant Research: Factors Associated With Low Enrollment and Inclusion in the Synbio‐Breast Study.
Background: An optimal early‐life environment is crucial for child health, with human milk and the infant microbiome playing central roles. The Synbio‐Breast study investigates how maternal diet contributes to the synbiotic composition of human milk in atopic women. Despite increasing societal inter...
| Publicado en: | BioMed Research International Vol. 2026; pp. 1 - 8 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
7/24/2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195624597&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195624597 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 7/24/2026 vid: 2026 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 195624597 195624597 195624597 10.1155/bmri/2358274 195624597 ppf: 1 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Recruitment Challenges in Mother–Infant Research: Factors Associated With Low Enrollment and Inclusion in the Synbio‐Breast Study. aug: au: Simons, Sandra van Goudoever, Hans Vlieg-Boerstra, Berber Banerjee, Baisakhi affil: Department of Pediatrics,, OLVG Hospital,, Amsterdam, the Netherlands sug: subj: Research Subject Recruitment Evaluation Research, Medical Mother-Infant Relations Synbiotics Maternal Nutritional Physiology Milk, Human Expectant Mothers Human Funding Source Female Nonexperimental Studies Prospective Studies Logistic Regression Odds Ratio Confidence Intervals Descriptive Statistics Health Screening Female ab: Background: An optimal early‐life environment is crucial for child health, with human milk and the infant microbiome playing central roles. The Synbio‐Breast study investigates how maternal diet contributes to the synbiotic composition of human milk in atopic women. Despite increasing societal interest in this topic, recruitment proved challenging. Objective: The aim of this study is to quantify and analyze factors associated with low enrollment and inclusion rates and to explore strategies for improving recruitment in future mother–infant studies. Methods: Enrollment and inclusion rates and temporal trends were assessed using linear regression models, whereas associations between facilitating factors—including involvement of the PhD student, recruitment strategy, lactation meetings, and attendance at the Nine Months Fair—and enrollment were assessed using logistic regression models. Results: Of the 681 women screened, 215 expressed willingness to participate. Despite multiple efforts and adaptations to enhance engagement, enrollment remained low. After adjusting for the COVID‐19 period, only recruitment conducted by the PhD student via email—without personal contact through a healthcare professional—was significantly associated with lower odds of enrollment. Of the 215 enrolled participants, 75 were ultimately included (11% of all screened women). Key reasons for exclusion were partial breastfeeding (30.0%), antibiotic use (22.1%), and loss of interest (19.3%). Conclusion: Strict inclusion and exclusion criteria contributed to substantial low enrollment and inclusion rates in the Synbio‐Breast study. Successful recruitment in mother–infant research requires more than logistical organization; it depends on personalized engagement built on existing relationships of trust. Moreover, studies that offer no direct health benefit to participants—such as the Synbio‐Breast study—tend to have inherently lower uptake, underscoring the need for tailored and relationship‐based recruitment strategies. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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