The goal of this clinical trial is to build capacity and assess the teaching effectiveness of a new simulator for manual neonatal ventilation in third-year nursing and clinical officer students, as well as healthcare professionals from the neonatology, gynecology, and pediatric departments.

The main questions it aims to answer are:

• Does the high-fidelity active setup of the simulator improve the percentage of target pressure achieved and the mean ventilation frequency compared to other configurations?
• How do different simulator configurations affect the training outcomes of unexperienced and experienced personnel, based on objective evaluations by expert clinicians and knowledge surveys?
• What is the self-reported usability and perceived usefulness of the different simulator configurations among the trainees? Researchers will compare a medium-fidelity passive setup, a high-fidelity passive setup with mechanical feedback, and a high-fidelity active setup with both mechanical and sensor feedback to see if the high-fidelity active configuration results in significantly higher clinical performance scores and better achievement of ventilation targets.

Participants will:

• Attend theoretical frontal lectures covering manual emergency ventilation procedures and medical simulation.
• Complete pre-training and post-training surveys to assess baseline knowledge, evaluate acquired skills, and report on the simulator's usability.
• Participate in hands-on simulator training, practicing the clinical procedure (positioning the newborn, positioning the mask, and ventilating) three times.
• Undergo a final simulation session for evaluation, where performance is objectively scored by a tutor and automatically recorded by the simulator's sensors.

Background and Rationale

Neonatal mortality in sub-Saharan Africa remains disproportionately high-26 deaths per 1,000 live births in 2023, which is 8.7 times higher than rates in Europe and North America. A significant portion of these deaths are attributable to preventable and treatable conditions occurring during birth. While skilled birth attendance can prevent up to 40% of neonatal deaths, assistance rates in sub-Saharan Africa are drastically low (40%) compared to high-income countries (90%). Consequently, strengthening the capacity of the health workforce to deliver essential newborn care is a critical priority.

Neonatal resuscitation is a complex, time-sensitive procedure. Due to severe limitations in access to advanced respiratory technologies in these regions, manual ventilation using a self-inflating bag and face mask constitutes the primary method of respiratory support. Because manual ventilation is highly operator-dependent and can cause substantial harm if performed incorrectly, technical proficiency is paramount. Simulation-based training is internationally recommended to improve provider competence, yet data on the real-world implementation, acceptability, and educational effectiveness of low-cost, high-fidelity simulators tailored to low-resource settings remains limited. This study evaluates a newly designed simulator developed specifically for the Tanzanian environment to ensure healthcare workers can acquire and maintain resuscitation skills.

Study Objectives

The specific objectives of this study are:

1. to evaluate the educational effectiveness of different simulator configurations across participants with varying levels of clinical experience, using objective performance metrics collected by the simulator.

2. to assess the acquisition of core manual ventilation competencies among inexperienced medical students through objective tutor evaluation and knowledge assessment.

3. to assess skill reinforcement among experienced clinicians through objective tutor evaluation and knowledge assessment.

4. to examine user-reported usability and perceived usefulness of the simulator configurations.

   Investigational Device Details

   The novel, low-cost, high-fidelity neonatal simulator is designed to replicate neonatal airway anatomy and ventilation mechanics while providing objective performance feedback.

   Anatomical Construction: The simulator integrates a physical manikin with internal anatomy designed to mimic the upper airways, lungs, and stomach.

   Physiological Mechanics: The device mimics physiological movements, specifically the visible rise of the chest and abdomen during successful ventilation. It also features a mechanical obstruction of the esophagus if the head is not correctly placed in the required "sniffing" position.

   Sensory and Digital Interface: The system incorporates pressure sensors and connects to a mobile user interface (app) that enables real-time data acquisition. The app provides the operator with real-time visual and auditory feedback regarding ventilation rate and pressure.

   Study Design and Allocation

   This is a prospective, randomized, and controlled study conducted at the Tosamaganga Regional Referral Hospital (TRRH) and the Tosamaganga Institute of Health and Allied Sciences (TIHAS) in the Iringa region of Tanzania.

   The study population consists of two cohorts: second-year undergraduate clinical officer students at TIHAS (with no prior manual ventilation experience) and local health professionals (nursing, midwifery, and neonatal care) working at TRRH. A total of 42 students and 37 health professionals were enrolled.

   Participants within each cohort were randomly assigned to one of three groups to evaluate the teaching effectiveness of different simulator configurations:

   • Group A (Medium-fidelity passive setup): (14 students, 12 professionals). The simulator provides no mechanical feedback (chest rise) and no mobile user interface guidance.
   • Group B (High-fidelity passive setup): (14 students, 13 professionals). The simulator provides mechanical feedback via chest and/or abdominal rise, but no mobile user interface guidance.
   • Group C (High-fidelity active setup): (14 students, 12 professionals). The simulator provides full mechanical feedback alongside real-time sensor-based guidance via the mobile user interface (visual and auditory feedback).

   Study Protocol and Workflow

   The training course was delivered over four consecutive days (June 17-20, 2025).

   • Day 1 (Theoretical Phase): Participants completed a pre-training survey to assess baseline knowledge and sociodemographic characteristics. This was followed by half-day standardized frontal lectures on manual emergency ventilation and the principles of medical simulation.
   • Days 2 and 3 (Hands-on Training): Participants engaged in two hands-on sessions (one per day with a minimum 24-hour washout period). After a clinical demonstration and a 1-minute familiarization period, participants performed three 1-minute ventilation trials per session (six trials total per participant) according to their randomized group configuration. Each trial involved newborn positioning, mask placement, and target ventilation delivery.
   • Day 4 (Evaluation Phase): All participants completed a standardized evaluation session using Configuration B (mimicking real clinical conditions with only chest rise feedback). Participants performed a single 1-minute ventilation trial. Performance was objectively assessed by a tutor and via simulator-derived data. Participants subsequently completed two post-training surveys assessing acquired knowledge and simulator acceptability.

   Data Collection and Statistical Analysis Plan

   All data were anonymized using unique numeric identifiers to link datasets across sessions. Data triangulation was achieved through three primary streams: automated simulator data, expert tutor evaluations, and self-reported surveys.

   - Primary Outcome Analysis (Educational Effectiveness): The primary outcome was ventilatory performance measured by the simulator during the six training trials, specifically the mean and standard deviation (Coefficient of Variation) of the ventilation rate (target: 40 BPM) and peak inspiratory pressure (target: 25 cmH2O). Longitudinal evolution across the trials was analyzed using linear mixed-effects models, evaluating trial number, group assignment, and their interaction.

   - Secondary Outcome Analysis (Knowledge and Skill acquisition/Reinforcement): Assessed via data from the final Day 4 evaluation session. Outcomes included simulator data, structured tutor performance scores (0 = poor, 0.5 = average, 1 = good), and theoretical knowledge scores (pre/post-training questionnaire). Continuous variables were analyzed using ANOVA (ANalysis Of VAriance) a (following Shapiro-Wilk testing for normality), and paired theoretical knowledge was analyzed using the Wilcoxon test.

   - Tertiary Outcome Analysis (Simulator Acceptability): User-reported acceptability was measured across four Technology Acceptance Model (TAM) dimensions: Perceived Usefulness (PU), Perceived Ease-of-Use (PEU), Behavioral Intention (BI), and Fidelity of the Simulator (FS), rated on a 7-point Likert scale. Associations between these latent variables and proposed cause-effect hypotheses were tested using a partial least squares structural equation model.

Inclusion Criteria:

• Third-year nursing students enrolled at the Tosamaganga Institute of Health and Allied Sciences (TIHAS).
• Third-year clinical officer students enrolled at TIHAS.
• Healthcare professionals working at Tosamaganga Hospital within the neonatology, gynecology, midwifery, and pediatrics departments.
• Individuals who voluntarily choose to attend the course.

Exclusion Criteria:

• Healthcare professionals working in fields outside of nursing, gynecology, midwifery, neonatology, and pediatrics.
• Participants who fail to complete the full training program, either by not attending all sessions or by prematurely withdrawing from the course.

Anonimized and aggregated data corresponding to the primary outcomes (mean and standard deviations of PIP and Ventilation Rate per trial per group).

Starting date: Janualy 1st 2026 End date: November 30st 2026

Data can be accessed by reseachers upon request only for reseach purpose and with a signed data access agreement after approval of a proposal. Any request can be sent to arianna.menciassi@santannapisa.it