An adaptive data-driven architecture for mental health care applications.

Background: In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven architectures are pivotal for organizing, manipulating, and presenting data to facilitate positive computing through ensemble machine learning models. Moreover, the COVID-19 pandemic underscored a substantial need for a flexible mental health care architecture. This architecture, inclusive of machine learning predictive models, has the potential to benefit a larger population by identifying individuals at a heightened risk of developing various mental disorders. Objective: Therefore, this research aims to create a flexible mental health care architecture that leverages data-driven methodologies and ensemble machine learning models. The objective is to proficiently structure, process, and present data for positive computing. The adaptive data-driven architecture facilitates customized interventions for diverse mental disorders, fostering positive computing. Consequently, improved mental health care outcomes and enhanced accessibility for individuals with varied mental health conditions are anticipated. Method: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the researchers conducted a systematic literature review in databases indexed in Web of Science to identify the existing strengths and limitations of software architecture relevant to our adaptive design. The systematic review was registered in PROSPERO (CRD42023444661). Additionally, a mapping process was employed to derive essential paradigms serving as the foundation for the research architectural design. To validate the architecture based on its features, professional experts utilized a Likert scale. Results: Through the review, the authors identified six fundamental paradigms crucial for designing architecture. Leveraging these paradigms, the authors crafted an adaptive data-driven architecture, subsequently validated by professional experts. The validation resulted in a mean score exceeding four for each evaluated feature, confirming the architecture's effectiveness. To further assess the architecture's practical application, a prototype architecture for predicting pandemic anxiety was developed.

The Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S): Measurement Invariant Evidence for Its Nine-Item Version in Taiwan, Indonesia, and Malaysia.

Background: As the number of COVID-19 cases grows worldwide, one solution to the global pandemic is vaccination. Unfortunately, the hesitancy of receiving vaccines is still high, particularly among younger age groups (eg, students). Because the hesitancy of receiving vaccines is an important issue, instruments have been developed to assess vaccine hesitancy. Moreover, the use of these instruments among specific groups such as students is of critical importance. Aim: The present study examined the psychometric properties of the nine-item MoVac-COVID19S (also known as the DrVac-COVID19S) including its measurement invariance among university students in three different countries (ie, Taiwan, Indonesia, and Malaysia). Methods: A multi-country, web-based cross-sectional survey study was conducted among 1809 university students, recruited from the three countries from May to September 2021. The nine-item scale was translated into Traditional Chinese, Bahasa Indonesian, and Malay. Results: The results of the confirmatory factor analysis indicated that the one-factor structure of the MoVac-COVID19S was fully supported among Indonesian and Malay participants (comparative fit index [CFI] = 0.991 and 0.998; Tucker-Lewis index [TLI] = 0.997 and 0.987; root mean sqaure error of approximation [RMSEA] = 0.040 and 0.071; and standardized root mean square residual [SRMR] = 0.014 and 0.039). Moreover, the four-factor structure was supported among Indonesian, Malay, and Taiwanese participants (CFI = 0.998, 0.998, and 0.985; TLI = 0.997, 0.996, and 0.973; RMSEA = 0.044, 0.038, and 0.091; and SRMR = 0.013, 0.018, and 0.049). Conclusion: The MoVac-COVID19S has good construct validity among university students from three different countries (ie, Taiwan, Indonesia, and Malaysia). The four-factor structure of the MoVac-COVID19S was supported. Therefore, health-care providers may want to assess the four underlying constructs to better understand why a university student accepts or declines COVID-19 vaccine uptake in the three countries. Using the findings, government policymakers and health-care authorities can design appropriate programs to help decrease vaccine hesitancy.

Prospective comparison of cytological specimen adequacy assessment by different rapid staining techniques for rapid on-site evaluation in fine needle aspiration cytology and their cost-effectiveness.

OBJECTIVE: Rapid on-site evaluation (ROSE) is a technique beneficial in determining the adequacy of the samples, thereby increasing the diagnostic yield, useful in triage of specimens for ancillary studies and can also help determine a preliminary diagnosis in emergency cases. The different rapid stains for on-site evaluation described in the literature are diff quik, toluidine blue (TB), brilliant cresyl blue (BCB), ultra-fast Pap stains, and rapid hematoxylin and eosin (H&E). This study was undertaken as there is sparse literature regarding the best and the most cost-effective rapid stain. METHOD: Fine needle aspiration samples from 200 patients with palpable swellings in easily accessible regions were taken. Smears stained by rapid and routine stains were assessed based on four parameters, with provisional diagnosis on the rapid stained smears. A comparative analysis of the advantages and disadvantages of the rapid stains was carried out with appropriate statistical tests with the routinely stained smears as gold standard. RESULTS: There was adequate material in 100% of ROSE smears. rapid pap stained smears showed well preserved cytoplasmic details, nuclear details, and background details. The time taken was least with TB and BCB being 5 s each. The most cost-effective was found to be TB. CONCLUSIONS: We conclude that TB is the most cost-effective, quick, least labor-intensive, and reliable rapid stain for ROSE especially in resource-poor settings.