Tracing the threads: a system dynamics and network diffusion model of kangaroo care implementation in neonatal care
Emanuela Nyantakyi1, Per Block2, Lauren Clack3,4
1Institute for Implementation Science in Health Care, Medical Faculty, University of Zurich, Zurich, 8006, Switzerland. emanuela.nyantakyi@uzh.ch.
Implementation Science Communications
|March 28, 2026
Summary
System dynamics and network science effectively mapped kangaroo care (KC) implementation factors. Nurse staffing and education availability most influenced KC duration in neonatal intensive care units.
Area of Science:
- Neonatal care research
- Implementation science
- Systems thinking in healthcare
Background:
- Implementing evidence-based practices like kangaroo care (KC) in neonatal intensive care units (NICUs) is complex.
- Traditional methods struggle to capture the dynamic interplay of factors influencing KC implementation.
- This study utilized advanced modeling to understand KC implementation determinants.
Purpose of the Study:
- To map determinants of kangaroo care implementation in NICUs.
- To examine mechanisms influencing KC duration using system dynamics and network diffusion.
- To understand the complex adaptive system of KC implementation.
Main Methods:
- Developed a causal loop diagram (CLD) with 32 KC experts.
- Validated the CLD through interviews with individuals with KC experience.
- Converted the CLD into a network diffusion model to assess variable influence on KC duration.
Main Results:
- The CLD identified 73 variables across parental engagement, workforce capacity, and service delivery.
- Network diffusion modeling showed 'Nurses per Shift' and 'Availability of KC Education & Counseling' had the strongest impact.
- These factors initiated the most influential cascades affecting average KC hours provided.
Conclusions:
- Integrating system dynamics and network science is valuable for studying implementation mechanisms.
- These methods offer insights into complex factors influencing healthcare practice adoption.
- Further research is needed to validate and refine these modeling approaches for implementation science.
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