This study significantly contributes to both theory and practice by providing valuable insights into the role and value of healthcare in the context of online health communities. This study highlights the increasing dependence of patients and their families on online sources for health information and the potential of technology to support individuals with health information needs. This study develops a theoretical framework by analyzing data from a cross-sectional survey using partial least squares structural equation modeling and multi-group and importance–performance map analysis. The findings of this study identify the most beneficial technology-related issues, like ease of site navigation and interaction with other online members, which have important implications for the development and management of online health communities. Healthcare professionals can also use this information to disseminate relevant information to those with chronic illnesses effectively. This study recommends proactive engagement between forum admins and participants to improve technology use and interaction, highlighting the benefits of guidelines for effective technology use to enhance users’ information-seeking processes. Overall, this study’s significant contribution lies in its identification of factors that aid online health community participants in the information-seeking process, providing valuable information to professionals on using technology to disseminate information relevant to chronic illnesses like COPD.

Summary: This research establishes a theoretical framework for evaluating antecedents of the information seeking behaviors of online forum participants with chronic obstructive pulmonary disease (COPD). We evaluated the proposed framework using partial least squares structural equation modeling (PLS-SEM) after gathering data using a cross-sectional survey. We subsequently assessed the framework using importance−performance map analysis (IPMA). Findings suggest that perceived ease of use does not singularly influence COPD forum users’ information seeking behavior. IPMA analysis reveals that the opportunity to interact with other forum members creates the greatest impact on COPD forum users’ mindsets, among all the indicators. For healthcare professionals, the results of this study provide a blueprint in terms of utilizing COPD online forums to foster recurrent associations among forum administrators and users and by creating a strong social and informational resource for COPD information seekers.

Objective: Frequent travel between the Southern border states in the USA, Mexico, and Latin American countries increases the risk of the Zika virus (ZIKV) spread. Patient education on virus transmission is fundamental in decreasing the number of imported cases, particularly among pregnant women.Methods: The study used cross-sectional methodology to investigate information sources and knowledge concerning the ZIKV virus among 300 under-served pregnant Latinas recruited from prenatal care clinics in the North Texas region. Bivariate and multiple logistic regression models were used to investigate associations between the primary outcomes and patient characteristics.Results: Physicians, nurses, and families are the major sources for pregnancy information, while media/internet (65%) and physician/nurse (33%) are the main sources for ZIKV information. Less than one-half of the mothers reported that their physician/nurse did not discuss safe sexual practices or inquired about their sexual practices. A considerable proportion of women from the community clinic were neither warned nor queried about travel to ZIKV risk countries. There is an overall understanding of Zika virus transmission, symptoms, complications, and recommended guidelines. Younger age and single mother status are risk factors for lack of ZIKV knowledge. Foreign-born mothers are 2.5–3.0 times more likely to have knowledge on disease transmission, symptoms, and microcephaly condition. While, younger mothers (18–24) are less likely to have knowledge of ZIKV infection symptoms (fever, rash and pink eye) and transmission of infection via unprotected sexual (vaginal, anal, or oral) behavior, compared to older mothers.Conclusions: Interventions are needed to heighten the knowledge of ZIKV, particularly among women of reproductive age and their male partners in the community health care setting. Our study underscores the need for health care providers to be trained in delivering messages to enhance risk perception during health emergencies to vulnerable and underserved families (lower economic background, language ability, and culture). During health emergencies, clinics must disseminate crucial information via multi modalities to ensure messages reach the targeted patients.

Background: Exacerbations of chronic obstructive pulmonary disease (COPD) are a leading cause of morbidity, mortality, and healthcare burden worldwide. Early detection and timely intervention remain important challenges in COPD management, given the unpredictable nature of acute deterioration and limitations of traditional spirometry-based risk assessment. Methods: This narrative review synthesizes artificial intelligence (AI)-driven approaches for predicting and detecting chronic obstructive pulmonary disease (COPD) exacerbations across electronic health records, wearable sensors, imaging, environmental data, and patient-reported outcomes, emphasizing novel discoveries and emerging relationships rather than predictive performance. Results: Three major discoveries have been made. First, measurable physiological and behavioral deterioration may precede symptom recognition by approximately 7–14 days, thereby establishing a potential intervention window for anticipatory care. Second, machine learning (ML) models integrating pollutant exposure, medication adherence, and clinical characteristics have identified phenotypes with differential environmental sensitivity, including unexpected exposure–adherence interactions. Third, deep neural network analysis of full spirometry curves has revealed structural phenotypes beyond traditional Forced Expiratory Volume (FEV₁)-based measures and novel imaging biomarkers. The predictive performance ranges from the Area Under the Curve (AUC) 0.72–0.95, with a pooled meta-analytic AUC of approximately 0.77. Conclusions: AI has uncovered hidden patterns in the progression of COPD, supporting a shift from reactive to anticipatory management. Translation to routine care requires prospective validation, improved interpretability, workflow integration, and generalizability and equity.

Introduction: This study examines how online technologies can support patients and their families address specific medical needs by creating an integrated theoretical framework based on the Health Belief Model, Social Exchange Theory, and Technology Acceptance Model.Methods: We obtained a total of 264 responses from an online survey posted in several COPD Facebook groups. After data preprocessing, we were left with 155 responses that met our inclusion criteria. Using the Partial Least Squares-Structural Equation Model (PLS-SEM), we evaluate how individuals in Chronic Obstructive Pulmonary Disease (COPD) Facebook groups seek information.Results: This study examines the relationship between demographic variables, psychological attributes (including emotional support and self-worth), perceived disease severity, benefits and barriers, and the perceived utility and ease of internet use in the information-seeking behavior of COPD patients on Facebook.Discussion: The findings underscore the importance of ease of internet use and intuitive platform design as a critical determinant that positively affects user engagement and fosters active participation among online participants. These findings offer critical insights into how online communities help patients and families obtain broad support and enhance the adoption and acceptance of emerging healthcare technologies. This also shows the advantages that online platforms offer individuals managing chronic diseases. Given these insights, we urge healthcare providers to recognize the beneficial effects of online health communities on patient well-being and health outcomes. This understanding is essential for healthcare professionals seeking to enhance patient care, aiming to improve the quality of life for individuals with chronic diseases in an increasingly digital landscape.