Percorrer por autor "Paulino, Paula"

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    Informing future seasonal influenza and COVID-19 vaccination campaigns based on past experience : a mixed-method approach with eligible populations and healthcare professionals
    (Frontiers Media SA, 2025-08) Oliveira, Jorge; Gonzalez, Bárbara; Mendes, Teresa; Paulino, Paula; António, Bruna; Gaspar, Rui; Costa, Diana; Pinto, Leonor Q; Costa, Andreia; De Arriaga, Miguel Telo; HEI-LAB - Human Environment Interaction Lab
    BACKGROUND: Seasonal vaccination campaigns against influenza and COVID-19 are critical for protecting vulnerable populations. Scientific evidence on past campaigns is essential for the effectiveness of future campaigns. This study aims to: (1) assess predictors of influenza and COVID-19 vaccination intentions (2) explore perceived barriers and facilitators of 2023-2024 seasonal vaccination campaign.METHODS: A cross-sectional study employing both quantitative and qualitative methods was conducted. The quantitative study involved a sample of 231 respondents from Portugal, including healthcare professionals and vaccination eligible population: individuals over 60 years of age, and individuals with chronic diseases. Quantitative data were collected via an online survey to assess vaccination literacy, attitudes, and future vaccination intention. The qualitative study consisted of four focus groups with a total of 17.PARTICIPANTS: Vaccinated/unvaccinated individuals and healthcare professionals. Thematic analysis was used to explore perceptions of eligible populations about this vaccination campaign.RESULTS: Quantitative analysis revealed that attitudes toward vaccination and factors related to personal/family health predicted future vaccination intentions for influenza and COVID-19. Thematic analysis identified key facilitators, such as positive perceptions of pharmacies as vaccination sites and an early start of the campaign specifically for vaccinated groups. Barriers were related to campaign communication, fear of side effects, vaccination fatigue, and the co-occurrence of high temperatures during the campaign start. Unvaccinated individuals expressed lower perceived susceptibility and severity.CONCLUSION: The study highlights the importance of clear communication, addressing vaccination fatigue, and considering environmental factors. Improving proximity between health professionals as trusted information sources and the population, alongside customized communication, may also enhance vaccination uptake among the eligible population. The potential influence of weather conditions on the acceptance of vaccination campaigns is a topic that deserves further consideration in the future, within the scope of climate changes.
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    Towards cyberbullying detection : building, benchmarking and longitudinal analysis of aggressiveness and conflicts/attacks datasets from Twitter
    (Institute of Electrical and Electronics Engineers Inc., 2024-12-16) Ferreira, Paula; Pereira, Nadia; Rosa, Hugo; Oliveira, Sofia; Coheur, Luisa; Francisco, Sofia; Souza, Sidclay; Ribeiro, Ricardo; Carvalho, Joao P.; Paulino, Paula; Trancoso, Isabel; Veiga-Simao, Ana Margarida; HEI-LAB - Human Environment Interaction Lab
    Offense and hate speech are a source of online conflicts which have become common in social media and, as such, their study is a growing topic of research in machine learning and natural language processing. This article presents two Portuguese language offense-related datasets that deepen the study of the subject: an Aggressiveness dataset and a Conflicts/Attacks dataset. While the former is similar to other offense detection related datasets, the latter constitutes a novelty due to the use of the history of the interaction between users. Several studies were carried out to construct and analyze the data in the datasets. The first study included gathering expressions of verbal aggression witnessed by adolescents to guide data extraction for the datasets. The second study included extracting data from Twitter (in Portuguese) that matched the most frequent expressions/words/sentences that were identified in the previous study. The third study consisted in the development of the Aggressiveness dataset, the Conflicts/Attacks dataset, and classification models. In our fourth study, we proposed to examine whether online aggression and conflicts/attacks revealed any trend changes over time with a sample of 86 adolescents. With this study, we also proposed to investigate whether the amount of tweets sent over a period of 273 days was related to online aggression and conflicts/attacks. Lastly, we analyzed the percentage of participants who participated in the aggressions and/or attacks/conflicts.