Early stimulation is increasingly recognised as essential for optimising neurodevelopmental outcomes in preterm infants admitted to Neonatal Intensive Care Units (NICUs). However, most existing stimulation protocols are derived from controlled research settings and lack guidance in gestational age (GA) -specific timing, caregiver role allocation, and cultural applicability, limiting their translation into routine practice in resource-constrained settings like India. To develop a GA-specific early stimulation protocol for preterm infants using structured triangulation of trial evidence, therapist-informed practice patterns and maternal experience in Indian NICU settings. A sequential exploratory mixed-method design was employed. First, a systematic review of randomised controlled trials (2010–2023) mapped stimulation modalities and GA characteristics. Second, a semi-structured interview was conducted with 16 NICU physiotherapists across eight Indian states to capture feasibility-driven clinical expertise. Third, in-depth interviews with 12 mothers of preterm infants explored maternal readiness, emotional acceptance and culturally embedded caregiving practices. Data were integrated using joint display analysis and a fixed decision algorithm. Triangulation classified modalities into four categories: five with strong convergence, five requiring conditional implementation, two restricted to specialist delivery and two excluded from the protocol. These findings were synthesised into a novel, colour-coded week x modality matrix, operationalising developmental sequencing, modality layering and transitions from therapist-led to parent-led delivery across GA. This study presents the foundational development of a contextually grounded GA-specific early stimulation protocol that maps twelve modalities across 26–40 weeks with colour-coded transitions from therapist-led to parent-led care. By integrating evidence, expertise and lived experience, the framework offers a transparent and culturally informed basis for subsequent feasibility testing, validation and implementation.
Abishek et al. (Sun,) studied this question.