2022
Autores
Amarti, K; Schulte, MHJ; Kleiboer, AM; van Genugten, CR; Oudega, M; Sonnenberg, C; Gonçalves, GC; Rocha, A; Riper, H;
Publicação
Abstract Internet-based interventions can be effective in the treatment of depression. However, internet-based interventions for older adults with depression are scarce and little is known about their feasibility and effectiveness. To present the design of two studies aiming to assess the feasibility of internet-based cognitive behavioural treatment (CBT) for older adults with depression (E-MODEL). We will assess the feasibility of an online, guided version of E-MODEL among depressed older adults from the general population as well as the feasibility of a blended format (combining integrated face-to-face sessions and internet-based modules) in specialised mental health care outpatient clinic. A single-group pretest-posttest design will be applied for both settings. The primary outcome of the studies will be feasibility in terms of (a) acceptance and satisfaction (measured with the Client Satisfaction Questionnaire-8, (b) usability (measured with the System Usability Scale) and (c) engagement (measured with the Twente Engagement with Ehealth Technologies Scale). Secondary outcomes include: (a) severity of depressive symptoms (PHQ-8), (b) participant and therapist experience with the digital technology (with the use of qualitative interviews), (c) working alliance between patient and practitioner (from both perspectives; WAI-SF), (d) technical alliance between patient and the platform (WAI-TECH-SF) and (e) uptake in terms of attemped and completed modules. N=30 older adults with mild to moderate depressive symptoms (score between 5 and 11 as measured with the Geriatric Depression Scale 15) will be recruited from the general population. N=15 older adults with moderate to severe depressive symptoms (GDS-15 score between 8 and 15) will be recruited from a specialised mental health care outpatient clinic. A mixed-method approach of quantitative and qualitative analyses will be adopted. Both the primary and secondary outcomes will be additionally explored with an individual semistructured interview and synthesized descriptively. Descriptive statistics (Mean and SDs) will be used to examine the primary and secondary outcome measures. Within-group depression severity will be analyzed using a two-tailed paired sample t-test to investigate differences between time points. The interviews will be recorded and analyzed using thematic analysis. The results of this pilot study will show whether this platform is feasible among the older adult population in a blended and guided format in the two settings as well as a first exploration of the size of the effect of E-MODEL in terms of decrease of depressive symptoms.
2022
Autores
Goncalves M.; Henriques A.; Costa A.R.; Correia D.; Severo M.; Severo M.; Lucas R.; Lucas R.; Barros H.; Santos A.C.; Ribeiro A.I.; Rocha A.; Lopes C.; Correia D.; Ramos E.; Gonçalves G.; Barros H.; Araújo J.; Talih M.; Tavares M.; Lunet N.; Meireles P.; Duarte R.; Camacho R.; Fraga S.; Correia S.; Silva S.; Leão T.;
Publicação
SLEEP MEDICINE
Abstract
Objective/background: To describe and characterize insomnia symptoms and nightmare profiles in Portugal during the first six weeks of a national lockdown due to COVID-19. Patients/methods: An open cohort study was conducted to collect information of the general population during the first wave of SARS-CoV-2/COVID-19 pandemic in Portugal. We analyzed data from 5011 participants (>= 16 years) who answered a weekly questionnaire about their well-being. Two questions about the frequency of insomnia and nightmares about COVID-19 were consecutively applied during six weeks (March-May 2020). Latent class analysis was conducted and different insomnia and nightmare profiles were identified. Associations between individual characteristics and both profiles were estimated using odds ratios (ORs) and 95% confidence intervals (CI). Results: Five insomnia (No insomnia, Stable-mild, Decreasing-moderate, Stable-severe, Increasing-severe) and three nightmares profiles (Stable-mild, Stable-moderate, Stable-severe) were identified. Being female, younger, perceiving their income as insufficient and feelings of fear towards COVID-19 were associated with higher odds of insomnia (Women: OR = 6.98 95%CI: 4.18-11.64; >= 60 years: OR = 0.30 95%CI: 0.18-0.53; Insufficient income: adjusted OR (aOR) = 8.413 95% CI: 3.93-16.84; Often presenting fear of being infected with SARS-CoV-2 infection: aOR = 9.13 95%CI: 6.36-13.11), and nightmares (Women: OR = 2.60 95%CI: 1.74-3.86; >= 60 years: OR = 0.45 95%CI: 0.28-0.74; Insufficient income: aOR = 2.60 95%CI: 1.20e5.20; Often/almost always presenting fear of being infected with SARS-CoV-2 infection: aOR = 6.62 95%CI: 5.01-8.74). Having a diagnosis of SARS-CoV-2 virus infection was associated with worse patterns of nightmares about the pandemic. Conclusions: Social and psychological individual factors are important characteristics to consider in the developmentof therapeutic strategies to supportpeoplewithsleep problems during the COVID-19 pandemic.
2022
Autores
Amarti, K; Schulte, MHJ; Kleiboer, A; Van Genugten, CR; Oudega, M; Sonnenberg, C; Gonçalves, Gc; Rocha, A; Riper, H;
Publicação
JMIR Research Protocols
Abstract
Background: Internet-based interventions can be effective in the treatment of depression. However, internet-based interventions for older adults with depression are scarce, and little is known about their feasibility and effectiveness. Objective: To present the design of 2 studies aiming to assess the feasibility of internet-based cognitive behavioral treatment for older adults with depression. We will assess the feasibility of an online, guided version of the Moodbuster platform among depressed older adults from the general population as well as the feasibility of a blended format (combining integrated face-to-face sessions and internet-based modules) in a specialized mental health care outpatient clinic. Methods: A single-group, pretest-posttest design will be applied in both settings. The primary outcome of the studies will be feasibility in terms of (1) acceptance and satisfaction (measured with the Client Satisfaction Questionnaire-8), (2) usability (measured with the System Usability Scale), and (3) engagement (measured with the Twente Engagement with eHealth Technologies Scale). Secondary outcomes include (1) the severity of depressive symptoms (measured with the 8-item Patient Health Questionnaire depression scale), (2) participant and therapist experience with the digital technology (measured with qualitative interviews), (3) the working alliance between patients and practitioners (from both perspectives; measured with the Working Alliance Inventory-Short Revised questionnaire), (4) the technical alliance between patients and the platform (measured with the Working Alliance Inventory for Online Interventions-Short Form questionnaire), and (5) uptake, in terms of attempted and completed modules. A total of 30 older adults with mild to moderate depressive symptoms (Geriatric Depression Scale 15 score between 5 and 11) will be recruited from the general population. A total of 15 older adults with moderate to severe depressive symptoms (Geriatric Depression Scale 15 score between 8 and 15) will be recruited from a specialized mental health care outpatient clinic. A mixed methods approach combining quantitative and qualitative analyses will be adopted. Both the primary and secondary outcomes will be further explored with individual semistructured interviews and synthesized descriptively. Descriptive statistics (reported as means and SDs) will be used to examine the primary and secondary outcome measures. Within-group depression severity will be analyzed using a 2-tailed, paired-sample t test to investigate differences between time points. The interviews will be recorded and analyzed using thematic analysis. Results: The studies were funded in October 2019. Recruitment started in September 2022. Conclusions: The results of these pilot studies will show whether this platform is feasible for use by the older adult population in a blended, guided format in the 2 settings and will represent the first exploration of the size of the effect of Moodbuster in terms of decreased depressive symptoms. © 2022 Khadicha Amarti, Mieke H J Schulte, Annet Kleiboer.
2022
Autores
Fortier, I; Wey, TW; Bergeron, J; de Moira, AP; Nybo Andersen, AM; Bishop, T; Murtagh, MJ; Miocevic, M; Swertz, MA; van Enckevort, E; Marcon, Y; Mayrhofer, MT; Ornelas, JP; Sebert, S; Santos, AC; Rocha, A; Wilson, RC; Griffith, LE; Burton, P;
Publicação
JOURNAL OF DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE
Abstract
Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.
2022
Autores
Pequeno, JT; Fonseca, B; Lopes, JBO;
Publicação
EUROPEAN JOURNAL OF ENGINEERING EDUCATION
Abstract
This study contributes to learning improvement in practical classes in Computer Network technology courses, using the Physical Technological Laboratory (PTL) as a tool. Multimodal narration content analysis was used, which aggregates and organises the data collected in the PTL environment. Based on the results, we infer that both the student and the teacher use the physical laboratory as a tool since the detected physical interactions prove its use and reuse. Evidence of causality between teacher epistemic movements and learning in terms of physical interactions, epistemic practices, and student autonomy was also noted. Contributions were: (1) In the context of work in networks PTL, the variety and quality of epistemic practices of students are enhanced if there is autonomous work concomitant with the physical interaction of students with the respective artifacts. (2) Teacher action can better promote epistemic practices, stretching beyond direct action if there is an 'orchestration' of teacher mediation patterns.
2022
Autores
Oliveira, L; Castro, M; Ramos, R; Santos, J; Silva, J; Dias, L;
Publicação
2022 17TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)
Abstract
The complexity of the number of stakeholders, information systems used, and port operations evoke new challenges to port security when it comes to the total knowledge and control of the overall operations of transport and parking of containerized freight, namely hazmat ones. The rising interest and the port authorities' awareness of the relevance of security concerns involved in this complex ecosystem has led to the search for new technological solutions that allow, in an integrated manner, the smart and automatic control of operations of transport and hazardous freight parking in all the areas of its jurisdiction, without third-party dependencies. Despite its importance and criticality, port authorities tend to have limited real-time knowledge of the location of hazmat containers, whether moving within the port (entering and leaving), or in its parking, having a direct impact on the port security. This article presents a Digital Twin platform for 3D and real-time georeferenced visualization of container parks and the location of hazardous containerized freight. This tool combines different modules that further allow to visualize information associated to a container, its movement, as well as its surrounding area, including a realistic and dynamic 3D representation of what is the area encircling the port.
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