IntroductionAdherence to weekly iron/folic acid (IFA) supplementation, a vital intervention to combat anaemia among adolescent girls, remains a global challenge, including in Maluku Province, Indonesia. This study assessed the effect of “Jaga Diri” application, in enhancing knowledge and adherence to IFA supplementation among adolescent girls from Salahutu Sub-District of Maluku Province, Indonesia.MethodsIn mid-2024, a quasi-experimental study was conducted among 82 adolescent girls from two senior high schools in Salahutu Sub-District, Maluku Province, Indonesia. The intervention group used the “Jaga Diri” Android-based application for four weeks, which delivered weekly reminders and brief educational messages on anaemia and iron–folic acid (IFA) supplementation, while the control group received routine school-based services. Knowledge was measured using a validated 15-item questionnaire. Adherence was defined as consumption of ≥75% of the provided weekly IFA tablets over the previous four weeks, assessed by self-report, and supported by haemoglobin measurement. Group differences were analyzed using non-parametric and chi-square tests, and multivariable binary logistic regression was used to assess factors associated with high knowledge and adherence.ResultsAfter four weeks of using the “Jaga Diri” application, adolescent girls from the intervention school showed a significantly higher level of knowledge about anaemia (p = 0.011) and adherence to weekly IFA supplementation (p < 0.001) than those from the control school. The improved adherence was shown by the reduction of anaemia prevalence in the intervention school, from 35% to 17.5%. In the control school, the prevalence increased from 19% to 28.6%.ConclusionsThe “Jaga Diri” application effectively improves knowledge about anaemia and adherence to IFA supplementation among adolescent girls. Further investigation with larger and more varied groups are required to confirm its effectiveness before it can be widely implemented in larger areas of Maluku and Indonesia.
Epistemic and ethical limits of large language models in evidence-based medicine: from knowledge to judgment
BackgroundThe rapid evolution of general large language models (LLMs) provides a promising framework for integrating artificial intelligence into medical practice. While these models are capable