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Factors contributing to inaccurate migraine diagnosis: a prospective study at a tertiary hospital in Southern Thailand
(2026-12-01)
Suwanlaong, Kanokrat
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Sittisomwong, Sirianong
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Dutsadeethammo, Duangkamon
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Anukoolwittaya, Prakit
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Rattanawong, Wanakorn
Background: Migraine is a common and disabling neurological disorder, yet diagnostic accuracy remains suboptimal, especially in non-specialist settings. Misdiagnosis may lead to delayed treatment, medication overuse, and reduced quality of life. The objective of this study was to estimate the proportion of patients with migraine attending the headache clinic who were misdiagnosed or not diagnosed as having migraine before attending the headache clinic, and to identify factors associated with inaccurate migraine diagnosis among patients before attending a tertiary hospital in Southern Thailand. Methods: A prospective, cross-sectional study was conducted at Songkhla Hospital between July 2024 and April 2025. Adult patients (≥ 18 years) with a final migraine diagnosis confirmed by two blinded independent neurologists were enrolled. Participants were divided into two groups: (1) an appropriate diagnosis group, defined as patients who received a correct diagnosis of migraine at their initial consultation with any physicians prior to attending the headache clinic; and (2) an inappropriate diagnosis group, defined as patients who were previously misdiagnosed with another headache disorder or had not been diagnosed with migraine before their headache clinic visit. Data on demographics, clinical features, and the specialty of the first attending physician were analyzed using univariable and multivariable logistic regression. Results: 90 patients were included (87.8% female, mean age 43.4 ± 14.8 years). 43.3% had been misdiagnosed at their initial visit. The most common incorrect diagnoses were tension-type headache and sinusitis. Multivariable analysis identified five independent factors significantly associated with inappropriate diagnosis: male sex (adjusted OR 7.77, 95% CI 1.07–56.50, p = 0.043), bilateral headache (aOR 3.90, 95% CI 1.25–12.13, p = 0.019), lack of worsening by physical activity (aOR 5.09, 95% CI 1.54–16.89, p = 0.008), presence of vertigo/dizziness (aOR 4.39, 95% CI 1.22–15.83, p = 0.024) and initial consultation with a non-neurologist (aOR 7.92, 95% CI 2.63–23.88, p < 0.001),. Conclusion: Misdiagnosis of migraine remains frequent in clinical practice, particularly among patients initially evaluated by non-neurologists. Atypical symptom profiles—such as bilateral pain, lack of activity-related exacerbation, or associated vertigo—contribute to diagnostic inaccuracy. Enhanced awareness and targeted education for primary physicians are essential to improve diagnostic precision and reduce treatment delay.
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Work-related generative artificial intelligence adoption and employee-perceived organisational performance in Thailand's manufacturing industry
(2026-10-01)
Yudhistyra, Wecka Imam
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Srinuan, Chalita
Generative Artificial Intelligence (GenAI) is increasingly integrated into organisational work processes, yet its implications for manufacturing firms cannot be inferred from adoption intention or usage frequency alone. In contrast to deterministic workplace technologies, GenAI produces probabilistic and context-responsive outputs whose organisational value depends on employees' ability to evaluate, interpret, and apply generated content effectively. This research examines how work-related GenAI use is associated with employee perceptions of GenAI-enabled organisational performance in Thailand's manufacturing sector. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the Human-Centred Design paradigm, and Knowledge Management theory, the research develops a framework in which perceived usability, knowledge acquisition, knowledge application, and performance expectancy influence behavioural intention, which subsequently affects use behaviour and employee-perceived GenAI-enabled organisational performance. Survey data from 381 manufacturing employees with prior GenAI experience were analysed using Partial Least Squares Structural Equation Modelling. Bayesian Network (BN) algorithms were subsequently employed to refine the theoretical structure by identifying conditional dependencies beyond the hypothesised model, while Artificial Neural Networks and Importance-Performance Map Analysis provided complementary predictive and managerial insights. The results support all hypothesised relationships. The BN-refined model further identifies direct links between knowledge application, performance expectancy, and organisational performance, suggesting that, in addition to adoption and use, GenAI-derived value also depends on employees' capacity to translate AI-generated knowledge into workplace outcomes. The findings advance technology adoption research by developing and validating a GenAI-specific extension of the UTAUT that integrates human-centred design and knowledge management perspectives. The research further demonstrates that organisational value is realised through a sequential pathway linking adoption antecedents, behavioural intention, and use behaviour, while providing policy-relevant evidence on workforce-driven AI adoption in an emerging economy undergoing digital transformation.
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Climate thresholds and yield elasticity of durian, mangosteen, and coffee under hydroclimatic variability in Thailand
(2026-08-01)
Ansari, Kutubuddin
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Tanır Kayıkçı, Emine
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Jamjareegulgarn, Punyawi
This study examines the empirical relationships between hydroclimatic variability and the yields of durian, mangosteen, and coffee across Thailand using meteorological observations from 56 stations and provincial level yield statistics for 2008 to 2024. An integrated statistical framework was applied, including exploratory correlation analysis, nonlinear quadratic additive modelling, lagged climate response analysis, elasticity estimation, model comparison, mangosteen regional sensitivity analysis, and a Climate Risk Index (CRI). The results show clear spatial gradients in temperature, humidity, and precipitation across the six agroclimatic regions of Thailand, broadly corresponding to regional crop productivity patterns. Annual anomaly analysis indicates that warm and humid years are generally associated with higher durian and mangosteen yields, whereas excessive rainfall and warming are associated with reduced coffee productivity. Pairwise linear correlations between annual climate variables and crop yields are generally weak, suggesting that simple linear models may not fully capture crop climate relationships. Nonlinear modelling indicates approximate empirical temperature turning points near 28.0°C for durian, 27.3°C for mangosteen, and 26.6°C for coffee, with humidity related turning points around 76–78%. Lagged climate response models suggest that multi-year hydroclimatic conditions may influence perennial crop productivity, particularly humidity for durian, precipitation for coffee, and temperature and precipitation for mangosteen. The mangosteen sensitivity analysis shows that humidity and precipitation thresholds are affected by regional composition, especially when marginal production regions are included. The CRI formulation under the equal weight, mangosteen shows the highest rainfall related climate risk signal, while coffee is more sensitive to temperature related risk and durian shows moderate vulnerability to prolonged humid and wet conditions.
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Thai Dairy Farmers' Adoption of Automated Disinfectant Production
(2026-07-01)
Akkhasingh, Akkhawit
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Vuthisopon, Sujira
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Saengnoree, Amnuay
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Sonsupap, Somchai
Adoption of sustainable on-farm technologies is essential to minimize environmental impacts and improve the sustainability and biosecurity of the livestock industry. Despite growing interest in precision livestock farming, no prior study has examined the psychological and behavioral determinants of dairy farmers' adoption of automated disinfectant production systems, particularly in developing economies. The current research uses structural equation modeling to investigate the determinants of adoption intention for a novel automated on-farm disinfectant production system that requires minimal external chemicals and generates no waste. The data were gathered from 320 members of the Dairy Farming Cooperative of Thailand. The hypothesized model includes the constructs of innovation characteristics, trust in innovation, perceived usefulness and perceived value to explain adoption intention. The model had a good fit (χ²/df = 1.22, RMSEA = 0.02, CFI = 0.99) and accounted for 73% of the variability in adoption intention. Among the variables studied, perceived value showed the strongest direct influence on adoption, followed by perceived usefulness. In addition, innovation characteristics exerted the greatest overall influence on adoption intention through the intermediary factors of trust, perceived usefulness and perceived value. It becomes evident that, to foster sustainable innovation in agriculture, it is essential to convey a value proposition that goes well beyond its functional aspects, with trust an indispensable factor in the process. The outlined model provides theoretical and practical views that can enhance the implementation of innovative livestock management techniques.
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Households’ Intention to Use Solar Rooftop Panels in Thailand: An Integrated TPB-TAM Approach
(2026-07-01)
Theppratuangthip, Pongsapat
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Rojniruttikul, Nuttawut
The rise in energy demand in Thailand due to constant economic growth coupled with reliance on limited natural gas and oil resources has led to an increased demand for alternative sources of energy. Therefore, this study aims at examining factors that influence the intention of adopting solar rooftop energy among households in Thailand through the integration of the theory of planned behavior (TPB) and the technology acceptance model (TAM). A quantitative research approach was adopted whereby data were obtained from 255 households in all parts of Thailand through questionnaires. The results reveal that attitude (β = 0.484, p < 0.001), perceived usefulness (β = 0.271, p < 0.05), and subjective norms (β = 0.257, p < 0.001) positively and significantly influence intention to use solar rooftop energy, collectively explaining 61% of the variance (R<sup>2</sup> = 0.61). Attitude proved to be the most significant predictor in this regard, underscoring the significance of the evaluative process of cognition and emotion for adopting certain behavior. This research makes a valuable contribution to the body of knowledge on renewable energy in that the TPB-TAM model has been empirically validated in a Thai household setting. In addition, the findings provide suggestive evidence of a mediating role of attitude in the link between perceived usefulness and intention, although this mediation finding should be interpreted with caution due to the conceptual overlap between these constructs and the absence of bootstrap confidence intervals. Future research is recommended to confirm this mediation pathway using formal bootstrap procedures.
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Epidemiology and Antimicrobial-Resistant Genes of Family Staphylococcaceae in Musca domestica: Case Studies from Chicken Farm, Pig Farms, and Residential Areas in Southern Thailand
(2026-05-01)
Sontigun, Narin
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Thanawan, Nattharee
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Fungwithaya, Punpichaya
The major Staphylococcaceae family is recognized as opportunistic pathogens colonizing human and animal skin, mucous membranes, and environments. Musca domestica, the house fly, plays a role in the transmission of AMR bacteria. This study focused on examining the epidemiology and antimicrobial-resistant genes of the family Staphylococcaceae in M. domestica through metagenomic analysis, using samples collected from three animal farms and two residential areas in southern Thailand. Fifty M. domestica were collected from five places surrounding Walailak University, including one chicken farm (CF1), two pig farms (PF2 and PF3), and two residential areas (H1 and H2). All samples were dispatched for analysis using shotgun metagenomic sequencing and analyzed using FastQC, MultiQC, FASTQ, MEGAHIT, QUAST, ABRicate, AMRFinderPlus, ResFinder, ARG-ANNOT, MEGARES, PlasmidFinder, VFDB, Kraken2, Krona and Python. Our findings describe the taxonomic composition of Staphylococcaceae taxa in M. domestica from different environments; the representation of the family Staphylococcaceae in CF1, PF2, PF3, H1, and H2 was recorded at 2%, 0.7%, 0.2%, 0.2%, and 2% of this phylum, respectively. The average populations discovered were Staphylococcus (37.4%), Mammaliicoccus (17.4%), and Macrococcus (10.3%), respectively. Trimethoprim-resistant genes (dfrG and dfrE) were found only in CF1, PF2, and H1. Interestingly, fosfomycin-resistant genes were found only in M. domestica within residential areas. Our findings pertain to the Staphylococcaceae population in M. domestica within residential areas, which exhibited varying multidrug-resistance genes, particularly those resistant to fosfomycin.
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Community-based water management competencies of agriculture and technology college teachers: A needs assessment
(2026-04-01)
Sarimanond, Ratchita
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Viriyavejakul, Chantana
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Pimdee, Paitoon
This research aims to study, assess, and prioritize the needs regarding learning competencies in community-based water management programs in Thai agriculture and technology college (CAT) instructors. The sample group was CAT teachers who participated in a training project to promote knowledge and learning competency in community-based water management. This Activity was part of the 2023 Royal Initiative Community-based Water Management Project. The sample group of 36 CAT water management instructors was obtained by purposive sampling. The research tool used was a needs assessment questionnaire. It is a 5-rating scale consisting of three aspects including knowledge (K), attitude (A), and practice (P). The index of item objective congruence (IOC) was 0.88, and the reliability of the questionnaire was 0.97. Data analysis used descriptive statistics, including the mean and standard deviation (SD), and analysis needs assessment with the modified PNI index value (PNI<inf>modified</inf>). The research results found that teachers have high expectations regarding learning competencies in water management, both individually and overall. In contrast, the Actual condition of both individual aspects and the overall picture is moderate to high. Moreover, for the needs assessment regarding teachers’ competencies in learning about water management, the aspect with the highest PNI value was cognitive competence (0.21), followed by practical competence (0.16) and affective competence (0.10).
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Experimenting With a Digital Application to Codesign Ikat Textile Patterns With Weaving Community
(2026-01-01)
Boonyaputthipong, Warin
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Chudasri, Disaya
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Palee, Patison
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Gilsdorf, Thomas
This article presents a multidisciplinary research project that involves a digital application developed for ikat weaving communities from Chonnabot District in Khon Kaen Province in Thailand. The app is aimed at generating new pattern designs based on traditional textile patterns and that correlate to weaving cultures. The structure of this article is as follows. First, it explains digitization and cultural heritage, followed by ikat weaving, a cultural heritage of the Chonnabot district, and the traditional skirt and changes to reed′s width. Second, research methodology is discussed, comprising two main tasks: designing patterns and making mudmee fabrics. We also explain a reason for applying a mathematical theory, specifically frieze group, as a set of rules to generate patterns, and outline the main steps for using the app. Third, we present results, including virtual pattern designs and real woven fabrics, and assessment of the app′s usability. Next, we discuss feedback from the participants as well as the weavers′ behavior in relation to the app′s usability and weaving, along with suggestions for improving the app. We conclude that the app is useful and has potential for teaching and learning for textile design courses. However, the app needs further development to correspond with the weavers′ view on the ikat weaving process. Overall, this collaborative project, including design and weaving tasks, enables knowledge exchange and is beneficial for design students and weavers as well as supports their livelihood.
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AHP approach for employee recruitment with COVID-19 situation in Thailand
(2026-01-01)
Narabin, Akan
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Boonjing, Veera
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Wuttanachamsri, Kanognudge
With the COVID-19 situation being unlike the usual, selecting an appropriate person for a job position requires the criteria and weight of each criterion be determined and adjusted to suit the crisis. The criteria chosen in this work are emphasised on selecting applicants who, while studying, have been in the midst of the COVID-19 situation. In this research, we employ analytic hierarchy process to assist the committee to have an agreement. In this study, each person in the committee can have his/her own pairwise comparison matrix of the criteria with a three-level hierarchical model. Some ambiguity may occur when initiating a hierarchical model; therefore, in this work, the criteria used in the three-level model are properly adjusted to create a four-level hierarchical model. The comparison inspected, provide some guidance in both theoretical manner and applications.
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Competency Components for Trainers in Workplaces Collaborating with Higher Education Institutions in Thailand
(2025-12-25)
Suranat, Chimparos
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Boonchan, Sisan
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Pariyaporn, Tungkunanan
This research aims to identify and establish the fundamental competency components necessary for trainers in workplace settings that collaborate with higher education institutions in Thailand. These trainers play the key role in connecting academic knowledge with practical application, significantly improving the effectiveness of Work-Integrated Learning (WIL) programs. A quantitative research design was utilized, involving 800 participants from five stakeholder groups: university administrators, curriculum instructors, career support staff, enterprise managers, and in-company trainers. Stratified random sampling guaranteed representation among numerous institutional varieties. Strong content validity and high reliability were obtained by the research instrument, which was developed through an extensive literature review and expert consultation. Confirmatory Factor Analysis (CFA) was utilized to determine the construct validity of the suggested competency model. As a result, the model indices showed exceptional outcomes. The findings confirmed three key competency domains: (1) knowledge competencies, such as curriculum quality development, training material design, and understanding of industrial laws; (2) skill competencies, such as digital media use, problem-solving, and communication skills; and (3) attitude competencies, such as work ethics, responsibility, and social interaction. These findings emphasize the necessity of building trainer competencies that are aligned with the changing needs of the industry, as well as the usefulness of educational-industry partnerships in preparing learners for the real world.

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