75 research outputs found

    Unfolding the real-time neural mechanisms in addiction: functional near-infrared spectroscopy (fNIRS) as a resourceful tool for research and clinical practice

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    © 2022 The Author(s). Published by Elsevier B.V. This is an open access article distributed under the Creative Commons Attribution License, to view a copy of the license, see: https://creativecommons.org/licenses/by/4.0/Neural underpinnings of addiction have been widely investigated using traditional neuroimaging techniques and paradigms. However, certain mechanisms are still underexplored, and existing studies often do not adopt an ecological assessment. Functional near-infrared spectroscopy (fNIRS) emerges as a potential elective tool to assess real-time neural activity with high ecological validity, as well as a good spatial and temporal resolution. So far, fNIRS has been rarely used as an instrument to study the neural underpinnings of substance and behavioral dependence. Starting from the available scientific literature, we aim to present the various applications of fNIRS in the research field of addiction, leading to unprecedented advancements in research and clinical practice.Peer reviewe

    Understanding the Evolving Nature of Novel Psychoactive Substances: Mapping 10 Years of Research

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    © 2023 Published by Elsevier Ltd on behalf of International Society for the Study of Emerging Drugs. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Novel psychoactive substances (NPS) is an umbrella term used to describe a heterogeneous group of compounds that mimic the effects of existing drugs and whose demand and use rapidly emerge, change, or even vanish in the drug market. The novelty of this global phenomenon and its dynamic nature represent major challenges for the scientific community that constantly requires timely evidence-based inputs. Our aim is to review the literature on NPS and compare its temporal evolution according to the topics presented at the International Conference series on NPS over the past decade. Our analysis shows that some new clusters of research recently emerged in comparison to a previous review and that the material presented at the NPS Conferences anticipates the scientific literature by approximately 2.5 years. Such findings not only provide new original insights on the latest NPS trends but also address existing knowledge gaps in the NPS field, while emphasizing the importance of face-to-face thematic events supported by faster publication processes to inform prompt interventions and policy making.Peer reviewe

    An Exploratory Analysis of the Effect of Demographic Features on Sleeping Patterns and Academic Stress in Adolescents in China

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    Adolescents typically engage in unhealthy lifestyle habits including short sleep and high academic stress. These in turn may have serious impacts on their development. The present study examines the effect of demographic characteristics on sleep patterns and academic stress in adolescents. A sample of 244 (119 females) junior high school adolescents aged between 11 and 16 were recruited from China. The Student Life Stress Questionnaire and the School Sleep Habits Survey were used to assess participants’ sleep habits and academic stress. Multipair and corrected pairwise Kruskal–Wallis tests were conducted to assess the effect of school grade, gender, academic performance level, living situation, single child status, and parental education on adolescents’ sleeping patterns and academic stress. Significant changes in facets of sleeping patterns emerged when examining groups of students in terms of school grade, living situation, and single-child status. Furthermore, caffeine consumption was found to be significantly higher in males, in students with poorer academic performances, and in single-child adolescents. Ultimately, academic stress was modulated by adolescents’ school grade, academic performances, living situation, and single-child status. Developmental trajectories in sleep patterns together with differential exposure to stressors and adopted coping mechanisms are discussed in the manuscript

    I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece.

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    OBJECTIVES: In the past months, many countries have adopted varying degrees of lockdown restrictions to control the spread of the COVID-19 virus. According to the existing literature, some consequences of lockdown restrictions on people's lives are beginning to emerge yet the evolution of such consequences in relation to the time spent in lockdown is understudied. To inform policies involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term time-related effects of lockdown on people's physical and mental health. STUDY DESIGN: An online questionnaire was launched on 17 April 2020, distributed through convenience sampling and was self-completed by 2,276 people from 66 different countries. METHODS: Focusing on the UK sample (N = 325), 12 aggregated variables representing the participant's living environment, physical and mental health were used to train a RandomForest model to estimate the week of survey completion. RESULTS: Using an index of importance, Self-Perceived Loneliness was identified as the most influential variable for estimating the time spent in lockdown. A significant U-shaped curve emerged for loneliness levels, with lower scores reported by participants who took part in the study during the 6th lockdown week (p = 0.009). The same pattern was replicated in the Greek sample (N = 137) for week 4 (p = 0.012) and 6 (p = 0.009) of lockdown. CONCLUSIONS: From the trained Machine Learning model and the subsequent statistical analysis, Self-Perceived Loneliness varied across time in lockdown in the UK and Greek populations, with lower symptoms reported during the 4th and 6th lockdown weeks. This supports the dissociation between social support and loneliness, and suggests that social support strategies could be effective even in times of social isolation

    Self-perceived loneliness and depression during the Covid-19 pandemic: a two-wave replication study

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    The global Covid-19 pandemic has forced countries to impose strict lockdown restrictions and mandatory stay-at-home orders with varying impacts on individual's health. Combining a data-driven machine learning paradigm and a statistical approach, our previous paper documented a U-shaped pattern in levels of self-perceived loneliness in both the UK and Greek populations during the first lockdown (17 April to 17 July 2020). The current paper aimed to test the robustness of these results by focusing on data from the first and second lockdown waves in the UK. We tested a) the impact of the chosen model on the identification of the most time-sensitive variable in the period spent in lockdown. Two new machine learning models - namely, support vector regressor (SVR) and multiple linear regressor (MLR) were adopted to identify the most time-sensitive variable in the UK dataset from Wave 1 (n = 435). In the second part of the study, we tested b) whether the pattern of self-perceived loneliness found in the first UK national lockdown was generalisable to the second wave of the UK lockdown (17 October 2020 to 31 January 2021). To do so, data from Wave 2 of the UK lockdown (n = 263) was used to conduct a graphical inspection of the week-by-week distribution of self-perceived loneliness scores. In both SVR and MLR models, depressive symptoms resulted to be the most time-sensitive variable during the lockdown period. Statistical analysis of depressive symptoms by week of lockdown resulted in a U-shaped pattern between weeks 3 and 7 of Wave 1 of the UK national lockdown. Furthermore, although the sample size by week in Wave 2 was too small to have a meaningful statistical insight, a graphical U-shaped distribution between weeks 3 and 9 of lockdown was observed. Consistent with past studies, these preliminary results suggest that self-perceived loneliness and depressive symptoms may be two of the most relevant symptoms to address when imposing lockdown restrictions

    Understanding Sleep Disturbances in Prostate Cancer—A Scientometric Analysis of Sleep Assessment, Aetiology, and Its Impact on Quality of Life

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    Prostate cancer is the most commonly diagnosed cancer in the United Kingdom. While androgen-deprivation therapy is the most common treatment for prostate cancer, patients undergoing this treatment typically experience side effects in terms of sleep disturbances. However, the relation between prostate cancer and sleep and the way in which sleep interventions may benefit oncological patients is underinvestigated in the literature. The current study aims to review in a data-driven approach the existing literature on the field of prostate cancer and sleep to identify impactful documents and major thematic domains. To do so, a sample of 1547 documents was downloaded from Scopus, and a document co-citation analysis was conducted on CiteSpace software. In the literature, 12 main research domains were identified as well as 26 impactful documents. Research domains were examined regarding the link between prostate cancer and sleep, by taking into account variations in hormonal levels. A major gap in the literature was identified in the lack of use of objective assessment of sleep quality in patients with prostate cancer

    Sleep Profiles in Eating Disorders: A Scientometric Study on 50 Years of Clinical Research

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    Sleep and diet are essential for maintaining physical and mental health. These two factors are closely intertwined and affect each other in both timing and quality. Eating disorders, including anorexia nervosa and bulimia nervosa, are often accompanied by different sleep problems. In modern society, an increasing number of studies are being conducted on the relationship between eating disorders and sleep. To gain a more comprehensive understanding of this field and highlight influential papers as well as the main research domains in this area, a scientometric approach was used to review 727 publications from 1971 to 2023. All documents were retrieved from Scopus through the following string “TITLE-ABS ((“sleep” OR “insomnia”) AND (“anorexia nervosa” OR “bulimia nervosa” OR “binge eating” OR “eating disorder*”) AND NOT “obes*”) AND (LIMIT-TO (LANGUAGE, “English”))”. A document co-citation analysis was applied to map the relationship between relevant articles and their cited references as well as the gaps in the literature. Nine publications on sleep and eating disorders were frequently cited, with an article by Vetrugno and colleagues on nocturnal eating being the most impactful in the network. The results also indicated a total of seven major thematic research clusters. The qualitative inspection of clusters strongly highlights the reciprocal influence of disordered eating and sleeping patterns. Researchers have modelled this reciprocal influence by taking into account the role played by pharmacological (e.g., zolpidem, topiramate), hormonal (e.g., ghrelin), and psychological (e.g., anxiety, depression) factors, pharmacological triggers, and treatments for eating disorders and sleep problems. The use of scientometric perspectives provides valuable insights into the field related to sleep and eating disorders, which can guide future research directions and foster a more comprehensive understanding of this important area

    The novel psychoactive substances epidemic: A scientometric perspective

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    /© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)The unprecedented proliferation of novel psychoactive substances (NPS) in the illicit drug market has been a public health concern since their emergence in the 2000s. Their consumption can pose severe health risks as their mechanism of action is poorly understood and their level of toxicity is high mainly due to the diffusion of very potent synthetic cannabinoid receptor agonists and synthetic opioids. This study systemically analyses the evolution of the scientific literature on NPS to gain a better understanding of the areas of major research interests and how they interlink. Findings indicate that the published evidence covers clusters focused on classes of NPS that have received widespread media attention, such as mephedrone and fentanyl, and have largely been concerned with the pharmacological and the toxicological profiles of these substances. This scientometric perspective also provides greater insight into the knowledge gaps within this new and rapidly growing field of study and highlights the need for an interdisciplinary approach in tackling the NPS epidemic.Peer reviewe

    Children’s online collaborative storytelling during 2020 covid-19 home confinement

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    Digital collaborative storytelling can be supported by an online learning-management system like Moodle, encouraging prosocial behaviors and shared representations. This study investigated children’s storytelling and collaborative behaviors during an online storytelling activity throughout the 2020 SARS-CoV-2 home confinement in Spain. From 1st to 5th grade of primary school, one-hundred-sixteen students conducted weekly activities of online storytelling as an extracurricular project of a school in Madrid. Facilitators registered participants’ platform use and collaboration. Stories were audio-recorded, transcribed verbatim, and analyzed using the Bears Family Story Analysis System. Three categories related to the SARS-CoV-2 pandemic were added to the story content analysis. The results indicate that primary students worked collaboratively in an online environment, with some methodology adaptations to 1st and 2nd grade. Story lengths tended to be reduced with age, while cohesion and story structure showed stable values in all grades. All stories were balanced in positive and negative contents, especially in characters’ behavior and relationships, while story problems remained at positive solution levels. In addition, the pandemic theme emerged directly or indirectly in only 15% of the stories. The findings indicate the potential of the online collaborative storytelling activities as a distance-education tool in promoting collaboration and social interaction
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