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Assessment and Intervention of Addictive Behavior

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Mental Health".

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 4374

Special Issue Editors


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Guest Editor
Department of Pedagogy, Psychology, Philosophy, University of Cagliari, 09123 Cagliari, Italy
Interests: addiction; dependence; substance use; new technology; cognitive training; serious games; cognitive functions

E-Mail Website
Guest Editor
Department of Pedagogy, Psychology, Philosophy, University of Cagliari, 09123 Cagliari, Italy
Interests: addictive behaviours; new technologies; serious games; intelligence; learning processes; adolescence; risk-behaviours; self-regulation

E-Mail Website
Guest Editor
Department of Pedagogy, Psychology, Philosophy, University of Cagliari, 09123 Cagliari, Italy
Interests: cognitive processes; metacognition; emotional intelligence; self-regulation; learning processes; e-learning; new technologies; cyberbullying; smartphone addiction
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Special Issue Information

Dear Colleagues,

Addiction is a "complex and progressive pattern of behavior that has biological, psychological, sociological and behavioral components". What differentiates addiction from other behaviors is the pathological component and/or the inability to exert control over it, which results in its continuation despite the negative consequences. It is a chronic disorder that is very costly to the patients who suffer from it and to society. Behavioral addictions are also pervasive and disabling and have a negative impact, such as disruption of family and marital relationships, financial difficulties, mental and physical health problems, and decreased life fulfillment.

Unfortunately, only a portion of patients with addiction problems access treatment services. To date, available treatment options for addictive behaviors remain limited and success rates are poor. Although many receive adequate treatment, they still experience several relapses after interventions, and their quality of life (and that of their caregivers) is greatly reduced due to the chronic nature of these disorders.

Currently there are several diagnostic measurement and assessment tools, ranging from the use of standardized questionnaires and self- and other-report scales to neurophysiological measures (e.g., brain imaging) to nonverbal and/or objective measures (e.g., attentional bias). Although many instruments are reliable (e.g., good internal consistency), the difficulty in assessment is often due to the different characteristics of addiction (e.g., signs, symptoms, severity, type of addiction and so on) and to the limit of the psychometric instruments.

Scientific studies suggest that combined treatment (e.g., behavioral and pharmacological intervention) can increase clinical success and improve clinical attendance, reducing the risk of relapse. However, not all addictive disorders have empirically validated treatments. Thus, there is a need to explore new approaches for the diagnosis and treatment of addiction disorders, such as the use of new technologies (e.g., Brain–Computer Interface, Virtual Reality, neurostimulation, EEG, device and wearable device and so on) combined with conventional treatments and new instruments that overcome the limits of conventional psychometrics analysis, exploring new ways to “interpret” data (e.g., use of neural network and machine learning algorithms, latent analysis, etc.).

In line with this point of view, it is important to develop and validate addiction assessment measures and treatments that could be used in professional practice with clinical populations and as a screening tool or prevention programs for nonclinical populations. In this context, there is a need for more treatments and assessments for addiction behaviors in a complex and multidimensional manner in both clinical and nonclinical populations.

Dr. Natale Salvatore Bonfiglio
Dr. Renati Roberta
Dr. Maria Lidia Mascia
Guest Editors

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Keywords

  • addiction
  • treatments
  • instruments
  • measurements
  • assessments
  • intervention
  • clinical practice
  • prevention

Published Papers (2 papers)

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Research

17 pages, 1265 KiB  
Article
Risk Factors and Protective Factors of Internet Addiction in University Students during the Pandemic: Implications for Prevention and Treatment
by Daniel T. L. Shek, Wenyu Chai and Kaiji Zhou
Int. J. Environ. Res. Public Health 2023, 20(11), 5952; https://doi.org/10.3390/ijerph20115952 - 25 May 2023
Cited by 2 | Viewed by 2176
Abstract
While the prevalence rates of Internet addiction (IA) amongst young people during the pandemic are disturbing, few studies have investigated the risk and protective factors of IA in Hong Kong university students under COVID-19. In this study, we examined the relationship between COVID-19-related [...] Read more.
While the prevalence rates of Internet addiction (IA) amongst young people during the pandemic are disturbing, few studies have investigated the risk and protective factors of IA in Hong Kong university students under COVID-19. In this study, we examined the relationship between COVID-19-related stress and IA and the role of psychological morbidity and positive psychological attributes in the relationship. In summer 2022, 978 university students completed a survey assessing pandemic-related stress, psychological morbidity, and positive psychological attributes. While psychological morbidity was indexed by depression, post-traumatic stress disorder, and suicidal behavior, positive psychological attributes included life satisfaction, flourishing, adversity beliefs, emotional competence, resilience, and family functioning measures. Results showed that stress and psychological morbidity positively predicted IA, and psychological morbidity mediated the association between stress and IA. Positive psychological attributes negatively predicted stress and IA, and mediated the connection between stress and IA. Positive psychological attributes moderated the mediating effect of psychological morbidity on the relationship between stress and IA. In addition to theoretical contributions, this study contributes to IA prevention and treatment: reducing psychological morbidity and promoting positive psychological attributes are promising strategies to address IA issues in young people. Full article
(This article belongs to the Special Issue Assessment and Intervention of Addictive Behavior)
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12 pages, 1521 KiB  
Article
Polysubstance Use Patterns among Outpatients Undergoing Substance Use Disorder Treatment: A Latent Class Analysis
by Natale Salvatore Bonfiglio, Igor Portoghese, Roberta Renati, Maria Lidia Mascia and Maria Pietronilla Penna
Int. J. Environ. Res. Public Health 2022, 19(24), 16759; https://doi.org/10.3390/ijerph192416759 - 14 Dec 2022
Cited by 7 | Viewed by 1752
Abstract
Substance Use Disorders (SUDs) pose significant challenges to both individuals and society at large. The primary focus of existing research with clinical SUD populations has been on individual substances, but research is required to better understand the profiles of individuals who use different [...] Read more.
Substance Use Disorders (SUDs) pose significant challenges to both individuals and society at large. The primary focus of existing research with clinical SUD populations has been on individual substances, but research is required to better understand the profiles of individuals who use different substances simultaneously. The purpose of the current study was, therefore, to identify patterns of use among subjects (n = 1025) who reported using multiple substances by adopting a Latent Class Analysis (LCA) methodology. The Addiction Severity Index (ASI-lite) was included as a measure of substance misuse, we performed LCA to identify patterns of substance use through the administration of the ASI-Lite. Responses were collected from the following substances: alcohol, cannabis/cannabinoids, opioids and heroin, and cocaine. Results identified two latent classes: (1) alcohol use dominant, and (2) poly-abuser use dominants. Class 1 represented 60.0% of the sample and refers to individuals with the dominant use of alcohol, of those a higher proportion (47%) reported low-frequency use (1 to 7 days per month) and 26% reported a frequency of use of 24 to 30 days per month. Furthermore, 18% used alcohol in combination with cocaine. Class 2 represents 40.0% of the sample. This class is characterized by low-frequency and high-frequency users of several substances. The results obtained highlight the importance of deepening the study of the concomitant use of substances in individuals with SUDs to better understand the health risk of the combined use of two or more substances. Full article
(This article belongs to the Special Issue Assessment and Intervention of Addictive Behavior)
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