The widespread use of Web 2.0 applications and the increasing number of social media applications are producing radical changes in tourism destination promotion. Destination Management Organizations (DMO) must be able to adapt and meet the challenges placed by new interaction and communication paradigms in the tourism sector. This paper describes a study done in which we analysed a set of national DMO and outlined and compared the use of social media applications in their communication activities. Shared practices and trends were identified and deconstructed according to a set of indicators and results enabled us to believe that, despite the differences in size and structure, there are some trends and shared practices worth adopting and exploring when designing social media communication strategies.

Background: Coronavirus 2019 (COVID-19) has become a public-health emergency of international concern. Most efforts to contain the spread and transmission of the virus rely on campaigns and interventions targeted to reduce Vaccine Hesitancy and Refusal (VHR). Objective: this study aims to assess the major factors associated with VHR in the older population in Portugal. Methods: a nation-wide cross-sectional study was conducted in the older Portuguese population (≥65 years old) through computer-assisted telephone interviewing. Logistic regression was used to determine the adjusted odds ratio (OR) of the independent variables (perceptions, knowledge and attitudes) and of the outcome (VHR). Results: the response rate was 60.1% (602/1,001). Perceptions, knowledge and attitudes were strongly associated with VHR probability. A 1-point Likert scale increase in concerns about the vaccines’ efficacy and safety increased the risk of VHR by 1.96 (95% confidence interval [CI]: 1.40–6.28) and 3.13 (95%CI: 2.08–8.22), respectively. A reduction of VHR probability for ‘reliability of the information released by social media’ (OR = 0.34, 95%CI: 0.16–0.70) and for ‘trust in national and international competent authorities’ (OR = 0.34, 95%CI: 0.17–0.69) is also observed per 1-point increase. Conclusions: as VHR seems to be strongly associated with perceptions, knowledge and attitudes, the design and promotion of vaccination campaigns/educational interventions specifically targeted at changing these potentially modifiable determinants may help to tackle COVID-19 VHR and achieve a wider vaccine coverage.

Background/Objectives: Artificial intelligence (AI) plays an important role in real-world health research. It can address the complexities of chronic diseases and their associated negative outcomes. This systematic review aims to identify the applications of AI that utilize real-world health data for populations with multiple chronic conditions. Methods: A systematic search was performed in MEDLINE and EMBASE following PRISMA guidelines. Studies were included if they applied AI methods using data from electronic health records for patients with multimorbidity. Results: Forty-four studies met the inclusion criteria. The review revealed AI applications identifying disease clusters, predicting comorbidities, and estimating health outcomes such as mortality, adverse drug reactions, and hospital readmissions. Commonly used AI techniques included clustering methods, XGBoost, random forest, and neural networks. These methods helped identify risk factors, predict disease progression, and optimize treatment plans. Conclusions: This study emphasizes the increasing role of AI in understanding and managing multimorbidity. Integrating AI into healthcare systems can enhance resource allocation, improve care delivery efficiency, and support personalized treatment strategies. However, further research is needed to overcome existing limitations, particularly the lack of standardized performance metrics, which affects model comparability. Future research should adhere to commonly recommended evaluation practices to improve reproducibility and meta-analysis.

This study aims to assess the determinants of the coronavirus disease 2019 (COVID-19) vaccination hesitancy and refusal (VHR) among teachers, from pre-school to higher education, through an online survey. A logistic regression analysis was used to determine the adjusted odds ratio (OR) of the independent variables (perceptions, knowledge, and attitudes) per 1-point increase in the Likert scale, and VHR.

Background: During the COVID-19 pandemic, social media became an important and easily accessible source of information to keep the population informed. In this study, we explored how Portuguese health entities used social media during the public health emergency caused by COVID-19 disease. Methods: A retrospective study on Portuguese public health entities’ communication with the public using social media platforms was performed. Data were retrieved from Facebook, Instagram, and Twitter. All retrieved posts were analyzed, and the engagement of the public was calculated. A thematic analysis of all COVID-19-related posts was conducted. Results: The analysis of each social media platform revealed that during the COVID-19 pandemic, health entities reinforced their presence on social media platforms. The most published posts were related to “epidemiological context” and “encouragement to take actions” to avoid the spread of COVID-19. High engagement frames were not associated with the most frequently published posts. Conclusions: Although health entities have reinforced their presence on social media platforms, they do not take full advantage of these platforms to improve health literacy.