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About

About

He is a senior researcher at INESC TEC since 1998. He is coordinator of HumanISE - Human-centered computing and Information Science

Current research interests include platforms and methods for collaborative research, privacy-preserving distributed computation, the semantic sensor Web (IoT) and Big Data processing.

From October 1996 to December 1997, he was an associate member of CERN - European Laboratory for High Energy Physics, IT Division/Web Office.

His research is applied in two major areas: Personalized Health Research (PHR) and Earth and Ocean Observation Science (EOOS).

The PHR area currently subdivides in: a) personalized Internet-based treatments; and b) human data storage, privacy-preserving processing and controlled FAIR data sharing. In this area, he participates in several European projects, such as ICT4Depression (FP7), E-COMPARED (FP7), STOP Depression (EEA Grant), iCare4Depression (FCT), RECAP Preterm (H2020), EUCAN-Connect (H2020) and iReceptor Plus (H2020). In these projects, he often undertakes the role of responsible for the system's architecture, platform implementation, or technical coordinator.

In the EOOS area he participates in the implementation of the RAIA Observatory (Interreg projects RAIA, RAIA.co, RAIA TEC, MarRisk and RADAR ON RAIA), SeaBioData(EEA Grant), MELOA (H2020) and C4G which is the Portuguese node of EPOS (H2020 EPOS-SP).

Details

Details

  • Name

    Artur Rocha
  • Role

    Centre Coordinator
  • Since

    02nd February 1998
026
Publications

2023

Using Digital Tools to Study the Health of Adults Born Preterm at a Large Scale: e-Cohort Pilot Study

Authors
Lorthe, E; Santos, C; Ornelas, JP; Doetsch, JN; Marques, SCS; Teixeira, R; Santos, AC; Rodrigues, C; Goncalves, G; Sousa, PF; Lopes, JC; Rocha, A; Barros, H;

Publication
JOURNAL OF MEDICAL INTERNET RESEARCH

Abstract
Background: Preterm birth is a global health concern. Its adverse consequences may persist throughout the life course, exerting a potentially heavy burden on families, health systems, and societies. In high-income countries, the first children who benefited from improved care are now adults entering middle age. However, there is a clear gap in the knowledge regarding the long-term outcomes of individuals born preterm. Objective: This study aimed to assess the feasibility of recruiting and following up an e-cohort of adults born preterm worldwide and provide estimations of participation, characteristics of participants, the acceptability of questions, and the quality of data collected. Methods: We implemented a prospective, open, observational, and international e-cohort pilot study (Health of Adult People Born Preterm-an e-Cohort Pilot Study [HAPP-e]). Inclusion criteria were being an adult (aged =18 years), born preterm (<37 weeks of gestation), having internet access and an email address, and understanding at least 1 of the available languages. A large, multifaceted, and multilingual communication strategy was established. Between December 2019 and June 2021, inclusion and repeated data collection were performed using a secured web platform. We provided descriptive statistics regarding participation in the e-cohort, namely, the number of persons who registered on the platform, signed the consent form, initiated and completed the baseline questionnaire, and initiated and completed the follow-up questionnaire. We also described the main characteristics of the HAPP-e participants and provided an assessment of the quality of the data and the acceptability of sensitive questions. Results: As of December 31, 2020, a total of 1004 persons had registered on the platform, leading to 527 accounts with a confirmed email and 333 signed consent forms. A total of 333 participants initiated the baseline questionnaire. All participants were invited to follow-up, and 35.7% (119/333) consented to participate, of whom 97.5% (116/119) initiated the follow-up questionnaire. Completion rates were very high both at baseline (296/333, 88.9%) and at follow-up (112/116, 96.6%). This sample of adults born preterm in 34 countries covered a wide range of sociodemographic and health characteristics. The gestational age at birth ranged from 23+6 to 36+6 weeks (median 32, IQR 29-35 weeks). Only 2.1% (7/333) of the participants had previously participated in a cohort of individuals born preterm. Women (252/333, 75.7%) and highly educated participants (235/327, 71.9%) were also overrepresented. Good quality data were collected thanks to validation controls implemented on the web platform. The acceptability of potentially sensitive questions was excellent, as very few participants chose the I prefer not to say option when available. Conclusions: Although we identified room for improvement in specific procedures, this pilot study confirmed the great potential for recruiting a large and diverse sample of adults born preterm worldwide, thereby advancing research on adults born preterm.

2022

Development of a data classification system for preterm birth cohort studies: the RECAP Preterm project

Authors
Bamber, D; Collins, HE; Powell, C; Goncalves, GC; Johnson, S; Manktelow, B; Ornelas, JP; Lopes, JC; Rocha, A; Draper, ES;

Publication
BMC MEDICAL RESEARCH METHODOLOGY

Abstract
Background The small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT. Methods The multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round. Results Expert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system's topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created. Conclusions This bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project's web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies.

2022

Moodbuster (E-MODEL): The feasibility of digital cognitive behavioural therapy (CBT) for depressed older adults: Study protocol of two pilot feasibility studies (Preprint)

Authors
Amarti, K; Schulte, MHJ; Kleiboer, AM; van Genugten, CR; Oudega, M; Sonnenberg, C; Gonçalves, GC; Rocha, A; Riper, H;

Publication

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 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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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

Insomnia and nightmare profiles during the COVID-19 pandemic in Portugal: characterization and associated factors

Authors
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.;

Publication
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

Feasibility of Digital Cognitive Behavioral Therapy for Depressed Older Adults With the Moodbuster Platform: Protocol for 2 Pilot Feasibility Studies

Authors
Amarti, K; Schulte, MHJ; Kleiboer, A; Van Genugten, CR; Oudega, M; Sonnenberg, C; Gonçalves, Gc; Rocha, A; Riper, H;

Publication
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.

Supervised
thesis

2016

Platform for monitoring and treat depression

Author
José Pedro Alves Ornelas

Institution
UP-FCUP