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  • Name

    Gonçalo Campos Gonçalves
  • Cluster

    Computer Science
  • Role

    Assistant Researcher
  • Since

    01st February 2017


Preparedness in a public health emergency: determinants of willingness and readiness to respond in the onset of the COVID-19 pandemic

Leao, T; Duarte, G; Goncalves, G;




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

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


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.


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

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



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.