Stunting remains a public health problem in Indonesia. The 2024 Indonesian Nutritional Status Survey recorded a stunting prevalence of 19.8 percent among children under five, still above the global target. At the individual level, length or height-for-age below -2 SD is a statistical indicator. Not every short child has a nutrition problem, because short stature can also come from normal variation or another medical condition.
National clinical guidance recommends a complete growth evaluation, including a comparison of weight age, height age, and chronological age. That comparison is hard to do by hand at a village health post because of limited time and the complexity of the calculation. This study turns that clinical logic into a digital decision aid for health volunteers and health workers.
Objectives
- Translate the national clinical guidance on child growth pattern analysis into a digital decision algorithm.
- Assess the agreement between the calculator triage result and the assessment of a paediatrician.
- Assess the sensitivity, specificity, positive predictive value, and negative predictive value of the calculator.
- Assess the usability of the calculator in community-level growth monitoring.
Design
The study runs in two phases. The first phase develops the calculator following a software development cycle, including content validation of the algorithm by an expert panel and functional testing. The second phase is a field validation study with a cross-sectional approach. Trained health volunteers and health workers measure children and use the calculator, while a paediatrician assesses the same children independently and blinded to the calculator result.
Participants and setting
Participants are children aged 0 to 59 months attending growth monitoring in the catchment areas of the Tanjungsari, Pamulihan, and Sukasari community health centres in Sumedang District. Consecutive sampling runs to about 270 children, calculated with the Buderer formula for a sensitivity of 85 percent, a precision of 10 percent, and a prevalence of 20 percent, plus a reserve for incomplete data.
Analysis
Agreement is measured with the Cohen kappa coefficient and the percentage of agreement. Accuracy is assessed with sensitivity, specificity, positive predictive value, and negative predictive value from a 2x2 table, with 95 percent confidence intervals. Usability is assessed with a Likert scale questionnaire, triage time, use errors, and focus group discussion.
Team
- Aly Diana, dr., M.Kes., MPH(Nutr), PhD, principal investigator
- Viramitha Kusnandi Rusmil, dr., M.Kes., Sp.A(K), co-investigator
- Mulya Nurmansyah Ardisasmita, dr., M.T., co-investigator
- Claudia Leong, Ara Institute of Canterbury, international research partner
The study is proposed under the 2026 Universitas Padjadjaran Lecturer Competence Research scheme, hosted by the Centre for Health System Studies and Health Workforce Education Innovation, Faculty of Medicine, Universitas Padjadjaran.