GIULIO dE FELICE

Associate Professor

Mercatorum University
Country flagItaly

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About

Giulio de Felice is an Associate Professor at Mercatorum University in Italy. His research focuses on neurophysiological states, clinical interventions based on dynamical systems, and the complexities of treatment-resistant depression. He has published extensively on topics including the application of data-driven approaches in psychotherapy and the geopolitical aspects of COVID-19 vaccine distribution.

Articles (10)

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

In December 2019, the Wuhan Municipal Health Commission (China) reported to the World Health Organization (WHO) a cluster of pneumonia cases with unknown aetiology in Wuhan City, Province of Hubei, China. In March 2020, WHO declared a pandemic. So began the spread of Sars-Cov-2 and the race to possible countermeasures. This article analyses the commercial relationships of the sale and purchase of vaccines as a measure of influence between different regions of the world. Taking all vaccines with a degree of global diffusion into account (Sputnik V, Russia; Sinovac, China; Sinopharm, China; Covishield, Oxford/AstraZeneca formulation, India; Johnson &amp; Johnson, USA; Oxford/AstraZeneca, UK; Pfizer/BioNTech, USA; and Moderna, USA), the article examines the specific regions of distribution. The paper has two aims: Firstly, to understand if the vaccines’ distribution mirrors the geopolitical <i>status quo</i>. Secondly, to identify the territories potentially more capable of causing important, regional or global, geopolitical frictions. In order to do that, the article highlights regions with unipolar and multipolar geopolitical influences. Limitations and further possible developments of the work will be commented on in the conclusions.

Year:

2023

Year:

2023

The evaluation and assessment of outcome is an important issue in psychotherapy research and practice. Since the beginning of empirical research, the effectiveness of treatments has been in the focus of interest to optimise mental health care. Despite this importance, the assessment of outcome by pre‐to‐post comparisons of point measures is hampered by some limitations. These include, amongst others, the predominant use of standard questionnaires neglecting personalised outcome criteria, the focus on point measures that ignore dynamic patterns representing the volatility of mental functioning, memory biases that become important if a recall of longer time periods is urged, and the non‐ergodicity of trajectories of change. Based on new methods of digitalised data collection in the real‐life setting of patients, some conclusions for process and outcome monitoring can be drawn: first, most mental diseases are characterised by specific dynamic patterns (dynamic diseases) whose changes can be assessed by high‐frequency time sampling, for example daily assessments of patients. Second, personal criteria for self‐assessments can be identified by multiperspective case formulations. Third, electronic devices such as smartphones allow for data collection in the real‐world settings of patients, which gives access to experiences in their ecosystems.

Year:

2022

Year:

2022

Year:

2022

Collaborators (6)

Jessica Burrai

Sapienza University of Rome

ITALY
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Luca Faes

Professore Associato

Università degli Studi di Palermo

ITALY
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Wolfgang Aichhorn

Professor

Paracelsus Medical University

AUSTRIA
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Isa Sammet

-

AUSTRIA
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Riccardo Pernice

University of Palermo

ITALY
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Nicolina Sciaraffa

-

UNITED KINGDOM
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