PARENTAL SUPPORT TECHNOLOGIES IN NICU: DIGITAL INTERVENTION TO REDUCE STRESS AND IMPROVE BONDING
DOI:
https://doi.org/10.31435/ijitss.1(49).2026.5345Keywords:
NICU, Digital Health, AI in Medicine, BondingAbstract
Parents of infants admitted to Neonatal Intensive Care Units (NICUs) frequently experience elevated levels of stress, anxiety, and depressive symptoms, which may negatively affect early bonding and caregiving confidence. Digital interventions have emerged as accessible and scalable tools to address these challenges.
This narrative review synthesizes current evidence on five categories of digital parental support: mHealth applications, telehealth and video communication systems, digital psychological interventions, virtual peer support platforms and IA based solutions.
The findings suggest that mHealth interventions can improve parental self-efficacy and reduce stress, while telehealth solutions enhance communication with healthcare providers and increase perceived involvement. Digital psychological interventions, including CBT, ACT, and mindfulness-based approaches, support emotional regulation and reduce depressive symptoms. Peer support platforms contribute to social connectedness, empowerment, and shared experiential learning. AI based solutions, including chatbots and predictive monitoring tools may enhance communication, education and engagement in neonatal care.
Despite these promising outcomes, the evidence remains heterogeneous in terms of study design, intervention characteristics, and outcome measures. Future research should focus on long-term effectiveness, standardized evaluation, and equitable access, as well as the integration of multiple digital modalities. A combination of quantitative and qualitative approaches may support the development of user-centered, evidence-based systems that enhance parental well-being and strengthen parent–infant bonding in NICU settings.
References
Choudhury, A., & Urena, E. (2022). Artificial intelligence in NICU and PICU: A need for ecological validity, accountability, and human factors. Healthcare, 10(5), 952. https://pubmed.ncbi.nlm.nih.gov/35628089/
Chua, J. Y. X., & Shorey, S. (2022). Effectiveness of mobile application-based perinatal interventions in improving parenting outcomes: A systematic review. https://pubmed.ncbi.nlm.nih.gov/35985142
Coşkun, A. B., Kenner, C., & Elmaoğlu, E. (2024). Neonatal intensive care nurses’ perceptions of artificial intelligence: A qualitative study on discharge education and family counseling. Journal of Perinatal & Neonatal Nursing. https://pubmed.ncbi.nlm.nih.gov/39740134
Ginsberg, K. H., Alsweiler, J., Rogers, J., et al. (2024). A digital Acceptance and Commitment Therapy and education intervention targeting stress of parents and caregivers with preterm babies in the NICU: A randomized controlled cluster trial protocol. Contemporary Clinical Trials. https://pubmed.ncbi.nlm.nih.gov/38547962
Ginsberg, K. H., Alsweiler, J., Ross, P., et al. (2025). Exploring stress and stress-reduction with caregivers and clinicians in the NICU to inform intervention development: Qualitative interview study. JMIR Pediatrics and Parenting. https://pubmed.ncbi.nlm.nih.gov/40173370
Hall, S. L., et al. (2015). Recommendations for peer-to-peer support for NICU parents. Journal of Perinatology. https://pubmed.ncbi.nlm.nih.gov/26597805
He, K., et al. (2024). mHealth service effects for negative emotions among parents of preterm infants: A systematic review and meta-analysis. https://pubmed.ncbi.nlm.nih.gov/39325981
Holm, K. G., et al. (2019). Parent perspectives of neonatal tele-homecare: A qualitative study. https://pubmed.ncbi.nlm.nih.gov/29792079
Joshi, A., … (2025). Enhancing neonatal intensive care unit (NICU) paternal experience with generative AI-enhanced counseling. Journal of Neonatal Nursing. https://pubmed.ncbi.nlm.nih.gov/41235020
Lee, H. N., et al. (2025). A mobile health app (mHealth)-based post-NICU discharge intervention for parents of preterm infants: A pilot study. https://pubmed.ncbi.nlm.nih.gov/41450162
Molu, B., … (2023). The effectiveness of AI-assisted information provision in guiding parents in premature infant care. Pediatric Research. https://pubmed.ncbi.nlm.nih.gov/40679926
Pascual, A., et al. (2024). The fundamentals of a parental peer-to-peer support program in the NICU: A scoping review. https://pubmed.ncbi.nlm.nih.gov/39354584
Ranu, J., et al. (2021). Engaging and supporting families in the NICU with telehealth platforms. https://pubmed.ncbi.nlm.nih.gov/33994011
Racine, N., et al. (2024). Health care professionals’ and parents’ perspectives on the use of AI for pain monitoring in the neonatal intensive care unit: A multisite qualitative study. JMIR AI, 3, e51535. https://pubmed.ncbi.nlm.nih.gov/38875686
Saito, T., et al. (2024). The effects of telepresence with real-time video and audio communication on parent-infant interaction and staff experience in NICU. https://pubmed.ncbi.nlm.nih.gov/39101054
Sunshine, I. L., et al. (2023). Mobile applications to support parents in the transition from neonatal intensive care unit to home: A narrative review. https://pubmed.ncbi.nlm.nih.gov/37492120
Wagenaar, J., et al. (2024). Opportunities for telemedicine to improve parents’ well-being during the neonatal care journey: Scoping review. https://pubmed.ncbi.nlm.nih.gov/39622079
Weber, J. C., et al. (2021). Impact of a parent video viewing program in the neonatal intensive care unit. https://pubmed.ncbi.nlm.nih.gov/32985954
Wegman, S., et al. (2024). Efficacy of peer support on caregiver well-being and patient outcomes in the NICU: A systematic review. https://pubmed.ncbi.nlm.nih.gov/40456134
Sullivan, B. A., Beam, K., Vesoulis, Z. A., et al. (2024). Transforming neonatal care with artificial intelligence: Challenges, ethical consideration, and opportunities. Journal of Perinatology, 44(1), 1–11. https://pubmed.ncbi.nlm.nih.gov/38097685
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Gabriela Daniel, Karolina Halat, Antoni Hajdas, Natalia Kaczmarczyk, Justyna Chudy, Łukasz Ćmok, Julia Dobrowolska, Jakub Robert Skalski, Iga Kałka, Julia Szmuc

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles are published in open-access and licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Hence, authors retain copyright to the content of the articles.
CC BY 4.0 License allows content to be copied, adapted, displayed, distributed, re-published or otherwise re-used for any purpose including for adaptation and commercial use provided the content is attributed.

