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    Exterior Biophilic Design Attributes Supporting Urban Mental Well-Being: A Case Study of Singapore’s Architecture
    (2026-02-01)
    Bunyarittikit, Suphat
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    Wongvorachan, Tarid
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    Petlai, Taksaporn
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    Somngam, Panyaphat
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    Ratanapong, Naipai
    The biophilic city concept has been proposed as an approach to mitigate the negative impacts of urban growth under global warming, which increasingly affects people’s mental health. As architecture occupies a substantial proportion of urban areas, biophilic architecture plays a crucial role in supporting urban well-being, contributing to sustainable development in line with Sustainable Development Goal 3 (SDG 3) (Good Health and Well-being). Previous studies have identified a research gap regarding the integration of exterior biophilic architectural attributes within urban contexts. Therefore, this study aims to identify exterior biophilic architectural attributes that can enhance urban mental well-being, using buildings in Singapore as case studies. A questionnaire survey was conducted to evaluate architectural attributes and people’s emotional responses, with the aim of analyzing their relationships. The results indicate that exterior biophilic architectural attributes contribute unequally to urban mental well-being. Natural features emerged as the most influential attribute, exerting comprehensive positive effects on attentiveness, inspiration, and self-assurance. Natural forms and natural colors also demonstrated significant contributions by promoting relaxation, cognitive engagement, and inspiration. In addition, natural spaces supported attentiveness and confidence, while natural materials, despite being less prevalent, exhibited strong qualitative effects on inspiration and psychological security. Accordingly, this study provides biophilic architectural design guidelines that support the mental sustainability of urban populations affected by global warming.
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    Integrating generative AI with the flipped classroom teaching model: enhancing emotional well-being and student achievement
    (2026-01-01)
    Liu, Hanchu
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    Sriwisathiyakun, Kanyarat
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    Petsangsri, Sirirat
    Education in the modern society is undergoing rapid transformation as helping students perform better academically and feel emotionally better has become increasingly important. One way to support this is by using Generative AI (GenAI) in combination with the flipped classroom approach. This study focused on creating and testing a new teaching model called the Generative AI-Integrated Flipped Classroom (GenAI-FC) designed for mental health courses. The research was done in two main parts. In the first part, the GenAI-FC model was developed and its structure was adjusted based on feedback from experts. In the second part, the model was used with students to see how it affected their learning and emotional well-being. The results were promising as five experts reviewed the model and gave it a high-quality score of 4.68 out of 5, showing that it was strong and useful for teaching. Then, the model was tested with 95 first-year university students. After using the model, students showed clear improvement in their exam scores and emotional well-being, based on a standard questionnaire. Both scores were significantly higher after the course compared to before as the results show that the GenAI-FC model can make a real difference by helping students to learn better and also feel more supported. This suggests that using Generative AI in a flipped classroom could be a helpful way to improve education and support students’ mental health at the same time.
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    A Systematic Review of Architectural Atmosphere That Fosters Mindfulness Constructs
    (2025-07-01)
    Thampanichwat, Chaniporn
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    Sirisakdi, Limpasilp
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    Petsirasan, Sippakorn
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    Wutisun, Duangkamon
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    Singkham, Sathirat
    This study explores how architectural atmosphere can foster mindfulness constructs in response to the growing mental health crisis. Mindfulness, known for improving mental health, reducing stress, and enhancing overall well-being, is increasingly recognized as a potential solution to mental health challenges. However, research on how architectural atmosphere supports mindfulness is limited. This study systematically reviews architectural atmosphere features that promote mindfulness constructs, which includes awareness, openness, attention, focus, connection, and calmness. A literature review was conducted using the Scopus database, following PRISMA guidelines for transparency. Fifty-three articles were selected, focusing on mindfulness features in architectural atmosphere: awareness (4), openness (1), attention (28), focus (5), and connection (15). No studies were found on architectural atmosphere fostering calmness. The findings suggest that architectural atmosphere plays a significant role in supporting mindfulness, but further empirical studies are needed to validate these results in real-world contexts.
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    A Systematic Review of Architecture Stimulating Attention through the Six Senses of Humans
    (2024-08-01)
    Thampanichwat, Chaniporn
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    Meksrisawat, Pratsanee
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    Jinjantarawong, Narongrit
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    Sinnugool, Somchok
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    Phaibulputhipong, Prima
    The climate change crisis is negatively impacting the mental health of people worldwide. Attention is a pivotal pathway to healing ourselves and the world, as it is a sensory process that enhances mental health and promotes sustainable behavior. Despite architecture’s potential to captivate all six human senses immediately, there is still a significant gap in research. Thus, this study aimed to identify architectural features that stimulate attention through the six human senses: visual, touch, auditory, olfaction, taste, and emotion. This review article was conducted by searching data from Scopus in February 2024, identifying 4844 related publications. After data screening following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 32 relevant and accessible research works were identified. Finally, data were extracted from the selected articles and analyzed using thematic analysis to explore their relevance to all six senses. The results reveal that the architectural features predominantly eliciting attention are mainly related to visual sensory stimuli. Closely following are the architectural features perceived through the emotional sense. The architecture that promotes attention is minimally associated with touch, auditory, and olfaction senses. Lastly, no architectural features were found to influence attention perceived through the sense of taste. Nevertheless, this study merely synthesizes data from previous research studies. Future research endeavors should validate this study’s findings for broader implications empirically.
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    The Architectural Design Strategies That Promote Attention to Foster Mindfulness: A Systematic Review, Content Analysis and Meta-Analysis
    (2024-08-01)
    Thampanichwat, Chaniporn
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    Wongvorachan, Tarid
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    Bunyarittikit, Suphat
    ;
    Chunhajinda, Pornteera
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    Phaibulputhipong, Prima
    Attention is a pivotal component and a central vehicle of mindfulness, a psychological factor improving mental health. Despite architecture’s potential to encourage attention and mindfulness, there is still a research gap. This study aimed to investigate architectural design strategies that promotes attention in order to foster mindfulness. The research was carried out in three primary stages. The first step entailed conducting a systematic review by searching publications related to architecture that promotes attention from Scopus in February 2024. After considering the suitability and accessibility, 32 articles were included. No studies were found to have investigated the field of enhancing mindfulness. The second step utilized content analysis to decode the selected articles using a framework developed from literature reviews. All three coders decoded the data independently, allowing the main researcher to compile it into the final dataset. Finally, the data underwent Python meta-analysis for word frequency and association. The result revealed certain qualities that help achieve attention through architecture. The architectural atmosphere is most effective when it features natural forms and spaces that evoke a sense of enclosure. The lighting should emphasize natural light and uniformity, whereas the sound designs primarily concern acoustics, ambient, and noises, with controlled weather emphasizing air aspects. The building should utilize natural materials and incorporate object elements; the facade and entrance are particularly crucial components. Moreover, the colors of brick and green and views encompassing gardens and vegetation are among the qualities mentioned. Based on the analysis, the material, view, and color features were most congruent with the biophilic design concept. All these factors are expected to foster mindfulness, thereby improving mental health.
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    Learning Extended Term Frequency-Inverse Document Frequency (TF-IDF++) for Depression Screening From Sentences in Thai Blog Post
    (2023-01-01)
    Khunruksa, Sahussawud
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    Wangsiripitak, Somkiat
    This paper proposed the method of depression screening from a sentence in Thai blog posts. Three classifiers based on a decision tree, linear SVC, and logistic regression were used to create classification models; each learned from extended term frequency-inverse document frequency (TF-IDF++) which is a feature vector created from a term frequency-inverse document frequency (TF-IDF), part-of-speech, and statistics of sentences such as word counts of selected terms. Our experiments showed that the model based on logistic regression achieves the top average score with a precision of 78.32%, a recall of 78.26%, and an f1-score of 78.27%. The proposed method outperforms the Thai BERT model by 0.75%, 0.77%, and 0.76%, respectively. Our investigation also showed that excessive confidence in the Thai BERT model tends to classify a sample with high probability. This also happens in case of an incorrect prediction; the error in such a case becomes noticeably higher than that of the wrong prediction in our proposed logistic regression-based model.