A descriptive and analytical cross-sectional study was conducted between March and July 2024 in nine Instituts Supérieurs des Techniques Médicales (ISTM) in Kinshasa, Democratic Republic of the Congo (DRC). These institutions provide initial training for mid-level healthcare professionals who are expected to deliver primary healthcare services, including the implementation of vaccination activities under the Expanded Programme on Immunization (EPI).

The nine ISTMs included in this study were selected based on their operational status during the 2023-2024 academic year and their involvement in training mid-level health professionals in Kinshasa. These institutions represent a subsample of the eligible ISTMs in Kinshasa, selected to ensure diversity in institutional characteristics (public vs. private) and student population size. However, they may not fully represent all paramedical training institutions in the city, which should be considered when interpreting the generalizability of the findings.

The study aimed to analyze the pedagogical approaches used in the vaccination module and to examine their association with students’ level of knowledge, while accounting for variability across institutions.

The target population consisted of students enrolled during the 2023–2024 academic year in the selected ISTMs who had either completed or were currently undertaking the vaccination module.

Students were eligible if they were officially enrolled in the institution and had provided written informed consent. Those absent during data collection or who submitted incomplete questionnaires (less than 80% of items completed) were excluded from the final analysis.

The minimum sample size was calculated using Schwartz’s formula, commonly applied in cross-sectional studies:

Assuming a 95% confidence level (Z = 1.96), an expected proportion of 50% (a conservative estimate maximizing sample size), and a precision of 5%, the minimum required sample size was 384 students. To account for potential non-response and ensure adequate statistical power, a 30% increase was applied, resulting in a final target sample size of 555 students.

A proportionate stratified random sampling method was used. Each of the nine institutions constituted a stratum. Participants were allocated proportionally based on the estimated student population in each institution, out of an overall population of approximately 5,800 students. Within each institution, students were selected through simple random sampling using official academic lists.

2.4.1. Dependent Variable

The primary outcome variable was the level of knowledge on vaccination, categorized into three levels (low, moderate, high) based on a composite score derived from multiple-choice questions.

For regression analyses, this variable was dichotomized (high vs. moderate/low) to identify factors associated with a high level of knowledge.

2.4.2. Independent Variables

The explanatory variables included:

Pedagogical approaches (existence of a structured module, availability of teaching materials, organization of practical sessions, clinical placements, teaching methods);Institutional characteristics (public vs. private management);Sociodemographic characteristics (age, sex, academic level);Institutional constraints and perceived needs.

Data were collected using a structured self-administered questionnaire developed based on:

World Health Organization recommendations on immunization training [4];existing literature on vaccine confidence and healthcare provider-related determinants [5][6].

The questionnaire comprised four main sections:

1) sociodemographic characteristics;

2) pedagogical organization of the vaccination module;

3) assessment of vaccination knowledge;

4) institutional constraints and perceived needs.

Data collection was conducted face-to-face under the supervision of trained research assistants to ensure standardized administration and minimize information bias.

Vaccination knowledge was assessed using a composite score based on multiple-choice questions covering:

general principles of immunization;the national vaccination schedule;cold chain management;adverse events following immunization.

Each correct answer was awarded one point, and the total score was converted into a percentage.

Knowledge levels were classified as follows:

High: ≥ 75%Moderate: 50% - 74%Low: < 50%

The 75% threshold was selected in line with commonly accepted academic standards in health sciences education.

Non-responses and “don’t know” answers were coded as incorrect responses (score = 0) to avoid overestimation of knowledge levels.

Although internal consistency of the knowledge scale was acceptable (Cronbach’s alpha = 0.82), a full psychometric validation was not conducted. Specifically, the study did not assess: item difficulty indices, discrimination indices, criterion validity against standardized national examinations, such as those of the Expanded Programme on Immunization (EPI).

In addition, the threshold of 75% used to define a “high level of knowledge” was based on commonly used academic standards but lacks empirical validation in the specific context of vaccination training in the DRC. Future research should aim to develop and validate standardized assessment tools adapted to local training and evaluation frameworks.

Data were entered and analyzed using SPSS version 26.

Descriptive statistics included means and standard deviations for quantitative variables, and frequencies and percentages for qualitative variables.

Bivariate associations between explanatory variables and knowledge level were assessed using Pearson’s chi-square test. Variables with p < 0.20 in bivariate analysis were included in a multivariable logistic regression model to identify factors independently associated with a high level of knowledge.

Model goodness-of-fit was assessed using the Hosmer-Lemeshow test. Multicollinearity was evaluated using the variance inflation factor (VIF), with an acceptable threshold of VIF < 2.

Given the hierarchical structure of the data (students nested within institutions), a two-level multilevel logistic regression model was applied to account for clustering and estimate institutional-level random effects. The intraclass correlation coefficient (ICC) was calculated to estimate the proportion of variance attributable to differences between institutions. Statistical significance was set at p < 0.05.

For regression analysis, knowledge levels were dichotomized into high versus moderate/low. This approach was adopted to facilitate interpretation of results and to identify factors associated with achieving a competency threshold relevant for clinical practice. After excluding missing data (n = 29), the regression analysis was conducted on a final sample of n = 526 participants.

3.1.1. Participant Characteristics

A total of 555 students were included in the analysis. Their distribution across the nine participating institutions is presented in Table 1.

Table 1.Distribution of participants by institution (n = 555).

More than 60% of participants were drawn from ISTM Croix-Rouge and ISTM Kinshasa, reflecting the larger enrollment capacity of these institutions. The proportionate stratified sampling strategy ensured institutional representation consistent with student population size.

3.1.2. Sociodemographic Characteristics

Sociodemographic characteristics are presented in Table 2.

Table 2.Sociodemographic characteristics of participants (n = 555).

Most participants were under 35 years of age (91.2%), and the sex distribution was nearly balanced. The majority were enrolled at the undergraduate level.

3.1.3. Knowledge Levels and Perceptions

The distribution of vaccination knowledge levels is shown in Table 3.

Table 3.Level of vaccination knowledge (n = 555).

Overall, 44.3% of students demonstrated a high level of knowledge, 41.3% a moderate level, and 9.2% a low level. In addition, 73.0% of participants considered that the benefits of vaccination outweigh potential risks, indicating an overall favorable perception of immunization.

3.1.4. Reported Pedagogical Constraints and Institutional Needs

Institutional constraints reported by participants are presented in Table 4.

Table 4.Reported pedagogical constraints.

The most frequently reported constraint was insufficient teaching resources (80.7%), followed by inadequate teacher training (67.2%). Limited or absent practical sessions were also commonly reported.

Specific challenges related to the vaccination module are summarized in Table 5.

Table 5. Pedagogical challenges related to the vaccination module.

More than three-quarters of students reported the absence of a formally structured vaccination module and insufficient practical sessions, suggesting organizational weaknesses in curriculum implementation.

Priority needs expressed by students are presented in Table 6.

Table 6.Priority needs expressed by students.

Students emphasized the need to strengthen collaboration with the EPI (89.0%) and to provide standardized teaching materials (86.0%).

3.2.1. Bivariate Analysis

The results of the bivariate analysis are presented in Table 7.

Table 7.Bivariate analysis of factors associated with a high level of knowledge.

The availability of practical training, adequate teaching materials, and sufficient teacher preparation was significantly associated with a high level of knowledge in the bivariate analysis. Sex and type of institution were not significantly associated.

3.2.2. Multivariable Logistic Regression

The results of the multivariable analysis are presented in Table 8.

Table 8.Multivariable logistic regression of factors associated with a high level of knowledge.

After adjustment, the availability of practical training and adequate teaching materials remained significantly associated with a high level of knowledge. Teacher preparation was no longer statistically significant in the adjusted model.

Model diagnostics indicated good fit (Hosmer-Lemeshow χ² = 6.84; p = 0.553). The Nagelkerke pseudo R² was 0.18, indicating that 18% of the variance in high knowledge level was explained by the model. No significant multicollinearity was detected (VIF < 2).

3.2.3. Multilevel Analysis

Given the hierarchical structure of the data (students nested within institutions), a two-level multilevel logistic regression model was applied (Table 9).

Table 9.Null multilevel model (random intercept by institution).

The ICC value of 11.3% indicates that a notable proportion of the variance in knowledge level is attributable to differences between institutions. Adjusted multilevel model is presented in Table 10).

Table 10.Adjusted multilevel model.

After introducing pedagogical variables into the model, between-institution variance decreased from 0.42 to 0.27, and the ICC dropped to 7.6%, indicating that differences in pedagogical organization partially explain institutional variability in knowledge levels.

Although nearly half of the students (44.3%) demonstrated a high level of know- ledge, a comparable proportion (41.3%) remained at a moderate level, suggesting incomplete acquisition of vaccination-related competencies. The generally favorable perception of vaccination observed in this study—where 73% of participants considered the benefits to outweigh the risks—is consistent with findings reported among health professional students globally [3][4]. However, positive attitudes alone do not guarantee adequate technical competence.

Previous studies in health professions education have highlighted gaps between theoretical knowledge and practical performance, particularly in areas such as cold chain management and the handling of adverse events following immunization [1][5]. In this context, the moderate proportion of students achieving high knowledge levels in our study underscores the need to strengthen pedagogical approaches beyond theoretical instruction [6][7].

The availability of practical training emerged as the strongest factor associated with a high level of knowledge, both in multivariable analysis (adjusted OR = 2.03) and in multilevel modeling (adjusted OR = 2.18). This finding is consistent with competency-based education frameworks, particularly Miller’s model, which describes the progression from knowledge acquisition (“knows”) to application in real-life settings (“does”) [8][9].

Practical exposure promotes experiential learning, reinforces theoretical know- ledge, and supports long-term retention of skills. The high proportion of students reporting insufficient practical sessions (78.4%) suggests that experiential learning components are not adequately integrated into current curricula. This gap may partly explain why a substantial proportion of students remain at an intermediate level of knowledge.

The persistence of this association in the multilevel model further indicates that the effect of practical training is robust and not merely explained by institutional clustering.

Access to adequate pedagogical resources was also independently associated with higher knowledge levels. Educational tools such as updated guidelines, standardized manuals, and structured teaching materials are essential for ensuring consistency in training and alignment with national immunization policies [10].

Limited access to such resources may lead to fragmented learning and variability in educational quality across institutions. The strong demand expressed by students for standardized materials (86%) further highlights the need for harmonized and well-structured teaching supports.

The multilevel analysis showed that 11.3% of the variance in knowledge levels was attributable to differences between institutions in the null model. Although this proportion decreased to 7.6% after adjustment for pedagogical factors, a residual institutional effect remained.

This finding suggests that differences between institutions are not fully explained by measured pedagogical variables alone and may reflect broader structural factors, including academic governance, supervision quality, infrastructure, and institutional culture. The observed reduction in variance after adjustment indicates that strengthening pedagogical components—particularly practical training and access to resources—could help reduce disparities between institutions.

However, the persistence of residual variability highlights the importance of systemic approaches, including regulatory frameworks and curriculum standardization, to ensure more uniform training quality.

The multivariable model explained 18% of the variance in high knowledge levels. Although modest, this level of explained variance is consistent with findings in educational and behavioral research, where outcomes are influenced by multiple interacting factors. The absence of multicollinearity and the satisfactory model fit support the internal validity of the analysis.

Nevertheless, the cross-sectional design limits causal inference. While the observed associations are consistent and theoretically plausible, causal relationships cannot be definitively established.

In a setting characterized by recurrent outbreaks of vaccine-preventable diseases, strengthening pre-service immunization training represents a strategic investment in health system resilience. The findings suggest that structured vaccination modules integrating practical training and standardized pedagogical materials could significantly improve knowledge acquisition among paramedical students.

Given the identified institutional effect, harmonizing vaccination curricula across ISTMs and strengthening collaboration with the Expanded Programme on Immunization (EPI) may help reduce inter-institutional disparities and enhance workforce preparedness.