Related Experiment Video
Updated: Jun 10, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
Unpacking the black box of training effectiveness: a structural equation modelling analysis
Ayako Masu1, Tomoka Takano2, Hirotsugu Aiga3
1Bureau of Global Health Cooperation, Japan Institute for Health Security, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan. masu.a@jihs.go.jp.
Background:
The health workforce shortage in low- and middle-income countries (LMICs) remains a critical challenge. The quality of health personnel impacts population health, particularly in LMICs. While development partners invest in training programmes to improve quality, evaluation of these programmes remains rare, with limited evidence on the structural and contextual factors influencing outcomes. This study aims to evaluate Japan's Official Development Assistance (ODA) capacity-building training programmes conducted in Japan for LMIC health workforces and to identify key structural factors to guide future workforce development strategies.
Methods:
A cross-sectional questionnaire-based study was conducted from January to June 2023 in the Lao People's Democratic Republic and Mongolia. A total of 148 health professionals who had participated in ODA training programmes between 2013 and 2020 were included. Exploratory factor analysis (EFA) was applied to 97 questionnaire items developed based on the training transfer literature, followed by Wilcoxon rank-sum tests and structural equation modelling (SEM) with robust estimation.
Results:
EFA identified six latent factors related to training effectiveness. Wilcoxon rank-sum tests showed that five factors-Feasible Action Plan, Collaborative Work Environment, Encouraging Learning Environment, Job-aligned Training and Readiness, and Altruistic Desire-were significantly associated with training effectiveness. During SEM refinement, two factors (Limited Authority and Altruistic Desire) were excluded due to non-significant effects or construct instability. The final model retained four factors, with Feasible Action Plan showing the strongest direct effect on training effectiveness (β = 0.72, p < 0.001). Collaborative Work Environment influenced training effectiveness indirectly through Job-aligned Training and Readiness and Feasible Action Plan. The model explained 45% of the variance in training effectiveness.
Conclusions:
Training effectiveness, defined as self-reported application of acquired knowledge, skills, and attitudes in the workplace, is shaped by interrelated factors operating before, during, and after training. The Feasible Action Plan emerged as the strongest direct predictor, highlighting the importance of translating learning into concrete and implementable actions. Collaborative and supportive workplace environments further facilitate this process. These findings underscore the importance of a holistic, process-oriented approach to ODA capacity-building training to enhance training transfer and sustain impact in LMIC settings.
Related Concept Videos
Theory of Attribution II: Kelley's Covariation Theory
Self-Evaluation Maintenance Model
Factorial Design
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the means for...
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Typical Model Studies
