Savicevic, Anamarija Jurcev
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Is Adolescent Physical Literacy Linked to Their Mental Health? Nurjanah, Nurjanah; Mubarokah, Kismi; Haikal, Haikal; Setiono, Oki; Belladiena, Alfiena Nisa; Muthoharoh, Nor Amalia; Rahma, Nis Syifa’ur; Iqbal, Muhammad; Nurmandani, Ririn; Ratna Wulan, Widya; Geets-Kesić, Marijana; Savicevic, Anamarija Jurcev
Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Vol. 13 No. SI1 (2025): Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Educat
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jpk.V13.ISI1.2025.85-93

Abstract

Background: More than 10% of adults in Indonesia experience mental and emotional disorders. Previous research has concluded that mental health is related to a person's physical literacy. Objectives: This study explores the relationship between physical literacy and mental health among adults in Semarang City, Indonesia, emphasizing the mediating role of various physical literacy domains. Methods: This observational study used a cross-sectional design with 610 participants chosen by stratified selection. Physical literacy and mental health were evaluated using the Perceived Physical Literacy Questionnaire (PPLQ) and the Self-Reporting Questionnaire (SRQ-20), respectively. All data acquired during interviews with trained enumerators were then processed using Stata. The data was then evaluated with the Spearman Rank test. Results: The study included more women than men. They were largely high school and college students who weren't yet married. The respondents' physical literacy remained moderate, while their mental health remained good/free of unhealthy mental issues. Bivariate analysis revealed that higher levels of physical literacy were linked to better mental health outcomes, particularly in the categories of physical ability, knowledge, and motivation. Age and education levels also have a substantial impact on mental health. Conclusions: Physical literacy has a substantial impact on mental health among adults in Semarang City.
Integrating ELECTRA and BERT models in transformer-based mental healthcare chatbot Zeniarja, Junta; Paramita, Cinantya; Subhiyakto, Egia Rosi; Rakasiwi, Sindhu; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Savicevic, Anamarija Jurcev
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp315-324

Abstract

Over the last decade, the surge in mental health disorders has necessitated innovative support methods, notably artificial intelligent (AI) chatbots. These chatbots provide prompt, tailored conversations, becoming crucial in mental health support. This article delves into the use of sophisticated models like convolutional neural network (CNN), long-short term memory (LSTM), efficiently learning an encoder that classifies token replacements accurately (ELECTRA), and bidirectional encoder representation of transformers (BERT) in developing effective mental health chatbots. Despite their importance for emotional assistance, these chatbots struggle with precise and relevant responses to complex mental health issues. BERT, while strong in contextual understanding, lacks in response generation. Conversely, ELECTRA shows promise in text creation but is not fully exploited in mental health contexts. The article investigates merging ELECTRA and BERT to improve chatbot efficiency in mental health situations. By leveraging an extensive mental health dialogue dataset, this integration substantially enhanced chatbot precision, surpassing 99% accuracy in mental health responses. This development is a significant stride in advancing AI chatbot interactions and their contribution to mental health support.