Pub Date : 2024-12-01DOI: 10.1016/j.etdah.2024.100162
Dong Liu , Roy F Baumeister , Chia-Chen Yang
The effect of digital media use on psychological well-being has been debated among scholars and the public for a long time. This study investigates the relationship between various types of media use and psychological well-being. It was proposed that communication media such as phone calls, texting, and instant messaging positively correlate with well-being. In contrast, the usage of social network sites (SNSs) and online gaming would be negatively correlated. To test this hypothesis, we conducted a meta-analysis of 292 studies. The meta-analysis revealed a positive correlation between phone calls and psychological well-being and a negative correlation between online gaming and psychological well-being. However, the overall correlations between digital media use and well-being were weak. Furthermore, the impact of digital media on well-being was influenced by how technology was utilized. For example, using SNSs for entertainment was linked to better well-being, whereas self-presentation and content consumption on SNSs were correlated to poorer well-being.
{"title":"A meta-analysis on the relationship between the use of electronic media and psychological well-being","authors":"Dong Liu , Roy F Baumeister , Chia-Chen Yang","doi":"10.1016/j.etdah.2024.100162","DOIUrl":"10.1016/j.etdah.2024.100162","url":null,"abstract":"<div><div>The effect of digital media use on psychological well-being has been debated among scholars and the public for a long time. This study investigates the relationship between various types of media use and psychological well-being. It was proposed that communication media such as phone calls, texting, and instant messaging positively correlate with well-being. In contrast, the usage of social network sites (SNSs) and online gaming would be negatively correlated. To test this hypothesis, we conducted a meta-analysis of 292 studies. The meta-analysis revealed a positive correlation between phone calls and psychological well-being and a negative correlation between online gaming and psychological well-being. However, the overall correlations between digital media use and well-being were weak. Furthermore, the impact of digital media on well-being was influenced by how technology was utilized. For example, using SNSs for entertainment was linked to better well-being, whereas self-presentation and content consumption on SNSs were correlated to poorer well-being.</div></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100162"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.etdah.2024.100163
Eleonora Zorzi , Thomas Zandonai
Originating in 19th-century Japan, judo blends traditional martial arts with modern educational principles. As a martial art rooted in the Budo tradition, it embodies a philosophy focused on the harmony of mind and body. In the West, however, the discipline evolved with an emphasis on competition and athleticism, which has led to increased competitive pressures among athletes. We report here the case studies of two Italian judokas who retired due to the development of unhealthy eating habits, extreme exercise and other unwanted psychological distress. It will be argued that the prevalent practice of weight cutting in combat sports poses substantial physical and psychological risks, particularly for young athletes. Despite regulatory efforts to mitigate extreme weight loss methods, there remains a critical need for improved education on safe practices. It sheds light on the complex interplay between athletic success, physical and mental health, and cultural perceptions of Judo in contemporary society.
{"title":"Maladaptive eating habits in judo athletes and psychological side effects: Case studies","authors":"Eleonora Zorzi , Thomas Zandonai","doi":"10.1016/j.etdah.2024.100163","DOIUrl":"10.1016/j.etdah.2024.100163","url":null,"abstract":"<div><div>Originating in 19th-century Japan, judo blends traditional martial arts with modern educational principles. As a martial art rooted in the Budo tradition, it embodies a philosophy focused on the harmony of mind and body. In the West, however, the discipline evolved with an emphasis on competition and athleticism, which has led to increased competitive pressures among athletes. We report here the case studies of two Italian judokas who retired due to the development of unhealthy eating habits, extreme exercise and other unwanted psychological distress. It will be argued that the prevalent practice of weight cutting in combat sports poses substantial physical and psychological risks, particularly for young athletes. Despite regulatory efforts to mitigate extreme weight loss methods, there remains a critical need for improved education on safe practices. It sheds light on the complex interplay between athletic success, physical and mental health, and cultural perceptions of Judo in contemporary society.</div></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.etdah.2024.100161
Lovlish Gupta , Neha Tomar , Rajendra Kumar Sarin
Drug Abuse is a global menace. This problem becomes grave concern when pharmaceutical preparations are abused. Dextromethorphan (DXM) is one such drug which is an antitussive agent which is reported to be used for illicit purposes. DXM (C18H25NO) belongs to class of dissociative hallucinogens that are known to manifest detachment in sight and sound perceptions. Researchers in forensic lab in India have reported the presence of DXM in substantial amount in heroine samples as bulking agent/ additives. The drug not only adds to the bulk but also intensify the effects of heroin by synergism. Hence, it becomes mandatory that extensive studies should be carried out on every additive/ Bulking agent that is present in the seized samples so as to identify and address the abuse and trade of such compounds. The present paper aims to comprehensively study and present the Chemical Properties of the DXM and its metabolites, their pharmacological and pharmacokinetics action on Human body and other related aspects. The Compound annual growth rate, market trends, abuse trends, side effects and Forensic analysis of the Samples have been methodically presented.
{"title":"Dextromethorphan: A double-edged drug – Unveiling the pernicious repercussions of Abuse and forensic implications","authors":"Lovlish Gupta , Neha Tomar , Rajendra Kumar Sarin","doi":"10.1016/j.etdah.2024.100161","DOIUrl":"10.1016/j.etdah.2024.100161","url":null,"abstract":"<div><div>Drug Abuse is a global menace. This problem becomes grave concern when pharmaceutical preparations are abused. Dextromethorphan (DXM) is one such drug which is an antitussive agent which is reported to be used for illicit purposes. DXM (C18H25NO) belongs to class of dissociative hallucinogens that are known to manifest detachment in sight and sound perceptions. Researchers in forensic lab in India have reported the presence of DXM in substantial amount in heroine samples as bulking agent/ additives. The drug not only adds to the bulk but also intensify the effects of heroin by synergism. Hence, it becomes mandatory that extensive studies should be carried out on every additive/ Bulking agent that is present in the seized samples so as to identify and address the abuse and trade of such compounds. The present paper aims to comprehensively study and present the Chemical Properties of the DXM and its metabolites, their pharmacological and pharmacokinetics action on Human body and other related aspects. The Compound annual growth rate, market trends, abuse trends, side effects and Forensic analysis of the Samples have been methodically presented.</div></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100161"},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-05DOI: 10.1016/j.etdah.2024.100160
D. Murthy , S. Keshari , S. Arora , Q. Yang , A. Loukas , S.J. Schwartz , M.B. Harrell , E.T. Hébert , A.V. Wilkinson
<div><h3>Background</h3><div>Social media platforms are critical channels for promoting e-cigarettes, particularly among youth, making analysis of their vast and diverse content essential for public health interventions. Prevalence rates of e-cigarette use are high and evidence suggests that social media are popular forums that promote e-cigarette use through direct and indirect marketing techniques. The volume and diverse nature of e-cigarette-related information on social media is challenging and may obfuscate public health prevention messaging. Traditional hand-coding methods are labor-intensive and limit scalability. In contrast, unsupervised machine learning approaches, such as topic modeling, allow for efficient analysis of large datasets, uncovering patterns and trends that manual methods cannot achieve at scale. The present study focused on ascertaining the extent to which themes and topics in tweets related to e-cigarettes can be successfully rendered into useful homogenous units using machine learning. A better understanding of current depictions and discussions around e-cigarette products and use on social media can inform public health counter messaging and policy interventions.</div></div><div><h3>Methods</h3><div>We used topic modeling (BERTopic) to iteratively derive vape-related tweet clusters and calculate the importance of particular words to these groupings. We conducted a qualitative content analysis to study clustered tweets. We also sought to determine the geographic locations of e-cigarette conversations using automated geoparsing methods, which translate toponyms in textual data into geographic identifiers, to attempt to infer the location of tweets.</div></div><div><h3>Results</h3><div>We were able to successfully identify >100,000 tweets in broad thematic categories in English and Spanish. Our correlation and inter-topic map analysis of the machine-derived topics, which examines the relationships between topics, indicated that most of the topics were unique (correlation value < 0.5) and did not overlap with each other. We identified six topics: Flavors and Disposable Vapes, Cannabis, Vape Shops and Refillable Vapes, Vape Culture, Anti-vaping and Quitting, and Spanish Tweets and Vaping Nicotine. Further analysis of these topics using qualitative methods identified themes within each topic. For example, Category 6 (Spanish Tweets and Vaping Nicotine) included four topics focused on the health risks of vaping, personal motivations for vaping, and the regulation of vaping products. Using geoparsing, which automatically detects location information, we found that the United States had the highest number of tweets related to vaping.</div></div><div><h3>Discussion/conclusion</h3><div>Results underscore the possibility of leveraging BERTopic modeling to reduce large quantities of data to comprehensively describe and categorize myriad e-cigarette related messages to which social media users are exposed. This data reduction
{"title":"Categorizing E-cigarette-related tweets using BERT topic modeling","authors":"D. Murthy , S. Keshari , S. Arora , Q. Yang , A. Loukas , S.J. Schwartz , M.B. Harrell , E.T. Hébert , A.V. Wilkinson","doi":"10.1016/j.etdah.2024.100160","DOIUrl":"10.1016/j.etdah.2024.100160","url":null,"abstract":"<div><h3>Background</h3><div>Social media platforms are critical channels for promoting e-cigarettes, particularly among youth, making analysis of their vast and diverse content essential for public health interventions. Prevalence rates of e-cigarette use are high and evidence suggests that social media are popular forums that promote e-cigarette use through direct and indirect marketing techniques. The volume and diverse nature of e-cigarette-related information on social media is challenging and may obfuscate public health prevention messaging. Traditional hand-coding methods are labor-intensive and limit scalability. In contrast, unsupervised machine learning approaches, such as topic modeling, allow for efficient analysis of large datasets, uncovering patterns and trends that manual methods cannot achieve at scale. The present study focused on ascertaining the extent to which themes and topics in tweets related to e-cigarettes can be successfully rendered into useful homogenous units using machine learning. A better understanding of current depictions and discussions around e-cigarette products and use on social media can inform public health counter messaging and policy interventions.</div></div><div><h3>Methods</h3><div>We used topic modeling (BERTopic) to iteratively derive vape-related tweet clusters and calculate the importance of particular words to these groupings. We conducted a qualitative content analysis to study clustered tweets. We also sought to determine the geographic locations of e-cigarette conversations using automated geoparsing methods, which translate toponyms in textual data into geographic identifiers, to attempt to infer the location of tweets.</div></div><div><h3>Results</h3><div>We were able to successfully identify >100,000 tweets in broad thematic categories in English and Spanish. Our correlation and inter-topic map analysis of the machine-derived topics, which examines the relationships between topics, indicated that most of the topics were unique (correlation value < 0.5) and did not overlap with each other. We identified six topics: Flavors and Disposable Vapes, Cannabis, Vape Shops and Refillable Vapes, Vape Culture, Anti-vaping and Quitting, and Spanish Tweets and Vaping Nicotine. Further analysis of these topics using qualitative methods identified themes within each topic. For example, Category 6 (Spanish Tweets and Vaping Nicotine) included four topics focused on the health risks of vaping, personal motivations for vaping, and the regulation of vaping products. Using geoparsing, which automatically detects location information, we found that the United States had the highest number of tweets related to vaping.</div></div><div><h3>Discussion/conclusion</h3><div>Results underscore the possibility of leveraging BERTopic modeling to reduce large quantities of data to comprehensively describe and categorize myriad e-cigarette related messages to which social media users are exposed. This data reduction ","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100160"},"PeriodicalIF":0.0,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142416913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.etdah.2024.100159
Cerina Dubois , Ming Ye , Olivia Weaver , Salim Samanani , Ed Jess , Fizza Gilani , Dean T. Eurich
Objectives
Stimulants are a class of drugs approved for the treatment of attention-deficit hyperactivity disorder (ADHD) and narcolepsy. However, they are also often used “off-label” as adjunct therapies for the treatment of obesity and depression. The objective of this study is to summarize how stimulant use is globally measured in the literature and to explore rates of stimulant use in Alberta, Canada.
Methods
A traditional narrative literature review was conducted to summarize global methods of stimulant assessment. Then using definitions guided by the literature and current regulatory bodies in Alberta, we conducted a series of descriptive analyses to assess how frequent stimulant use was in Alberta patients from 2019 to 2021: 1) number of dispenses by year; 2) average days of drug supply; 3) proportion of days covered (PDC); and 4) defined daily dose (DDDs).
Results
In the literature review, the most frequently used measures of stimulant drug use were trends over time (prevalence), types of drug use, and dispensations of prescriptions. In all, there is a global trend of increased use of stimulants among both adults and children. In Alberta, 173,789 patients were prescribed stimulant medication in 2019–2021, representing approximately 4 % of the entire Alberta population. Overall, 61.1 % were between the ages of 10–34 and 46.8 % were female. The number of dispensations rose from 713,896 in 2019 to 973,930 in 2021 – with up to 43 % being lisdexamfetamine stimulant dispenses.
Conclusions
Although stimulant use in AB was measured using similar trend estimates as the literature, there is a lack of research to support whether these measures are accurate and effective at the population-level. Future steps to standardize both medical and nonmedical use of prescription stimulants are warranted in efforts to fully quantify both benefits and risks associated with stimulant use.
{"title":"Measures of stimulant medications: A population-based study in Alberta, Canada","authors":"Cerina Dubois , Ming Ye , Olivia Weaver , Salim Samanani , Ed Jess , Fizza Gilani , Dean T. Eurich","doi":"10.1016/j.etdah.2024.100159","DOIUrl":"10.1016/j.etdah.2024.100159","url":null,"abstract":"<div><h3>Objectives</h3><div>Stimulants are a class of drugs approved for the treatment of attention-deficit hyperactivity disorder (ADHD) and narcolepsy. However, they are also often used “off-label” as adjunct therapies for the treatment of obesity and depression. The objective of this study is to summarize how stimulant use is globally measured in the literature and to explore rates of stimulant use in Alberta, Canada.</div></div><div><h3>Methods</h3><div>A traditional narrative literature review was conducted to summarize global methods of stimulant assessment. Then using definitions guided by the literature and current regulatory bodies in Alberta, we conducted a series of descriptive analyses to assess how frequent stimulant use was in Alberta patients from 2019 to 2021: 1) number of dispenses by year; 2) average days of drug supply; 3) proportion of days covered (PDC); and 4) defined daily dose (DDDs).</div></div><div><h3>Results</h3><div>In the literature review, the most frequently used measures of stimulant drug use were trends over time (prevalence), types of drug use, and dispensations of prescriptions. In all, there is a global trend of increased use of stimulants among both adults and children. In Alberta, 173,789 patients were prescribed stimulant medication in 2019–2021, representing approximately 4 % of the entire Alberta population. Overall, 61.1 % were between the ages of 10–34 and 46.8 % were female. The number of dispensations rose from 713,896 in 2019 to 973,930 in 2021 – with up to 43 % being lisdexamfetamine stimulant dispenses.</div></div><div><h3>Conclusions</h3><div>Although stimulant use in AB was measured using similar trend estimates as the literature, there is a lack of research to support whether these measures are accurate and effective at the population-level. Future steps to standardize both medical and nonmedical use of prescription stimulants are warranted in efforts to fully quantify both benefits and risks associated with stimulant use.</div></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667118224000187/pdfft?md5=ad646dc034bb75e07cf7d8d15e1e2ad6&pid=1-s2.0-S2667118224000187-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142310737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Semaglutide, a Glucagon-like peptide 1 (GLP-1) receptor agonist marketed under the brand name Ozempic, is originally prescribed for diabetes treatment and obesity management. However, healthy individuals without a medical cause use Ozempic without medical supervision to improve their physical appearance - a trend that has proliferated through social media, news coverage, and relevant celebrity endorsements. Thus, exploring social media posts can provide insight into understanding individuals’ experiences, beliefs, motivation, as well as misconceptions about Ozempic. To do so, this study utilizes BERTopic, a natural language processing approach for topic modeling, to analyze 46,491 Reddit posts from three subreddits (r/ozempic, r/ozempicforweightloss, r/semaglutide) dated between April 2019 and December 2023. The analysis revealed various discussion topics, including using Ozempic for weight loss, dosaging, insurance denial due to lack of a diabetes diagnosis, weight loss tracking, and side effect management. Overall, the overarching theme centered on the off-label use of Ozempic and its GLP-1 agonist counterparts for weight loss purposes. Moreover, awareness on the health hazards associated with the off-label and unsupervised use of Ozempic as an image enhancer do not frequently appear in the social media discussions. These findings, supported by a dynamic topic modeling analysis, offer ecological insights into the experiences and opinions of community members in Ozempic-related subreddits, reinforcing the growing evidence of the drug's increasing popularity for weight management as well as the role played by social media. The study also shows how information campaigns about the health risks associated with the off-label use of Ozempic by healthy individuals without a medical cause may help counterbalance the lack of risk awareness detected in social media discussions.
{"title":"Ozempic (Glucagon-like peptide 1 receptor agonist) in social media posts: Unveiling user perspectives through Reddit topic modeling","authors":"Seraphina Fong , Alessandro Carollo , Lambros Lazuras , Ornella Corazza , Gianluca Esposito","doi":"10.1016/j.etdah.2024.100157","DOIUrl":"10.1016/j.etdah.2024.100157","url":null,"abstract":"<div><p>Semaglutide, a Glucagon-like peptide 1 (GLP-1) receptor agonist marketed under the brand name Ozempic, is originally prescribed for diabetes treatment and obesity management. However, healthy individuals without a medical cause use Ozempic without medical supervision to improve their physical appearance - a trend that has proliferated through social media, news coverage, and relevant celebrity endorsements. Thus, exploring social media posts can provide insight into understanding individuals’ experiences, beliefs, motivation, as well as misconceptions about Ozempic. To do so, this study utilizes BERTopic, a natural language processing approach for topic modeling, to analyze 46,491 Reddit posts from three subreddits (r/ozempic, r/ozempicforweightloss, r/semaglutide) dated between April 2019 and December 2023. The analysis revealed various discussion topics, including using Ozempic for weight loss, dosaging, insurance denial due to lack of a diabetes diagnosis, weight loss tracking, and side effect management. Overall, the overarching theme centered on the off-label use of Ozempic and its GLP-1 agonist counterparts for weight loss purposes. Moreover, awareness on the health hazards associated with the off-label and unsupervised use of Ozempic as an image enhancer do not frequently appear in the social media discussions. These findings, supported by a dynamic topic modeling analysis, offer ecological insights into the experiences and opinions of community members in Ozempic-related subreddits, reinforcing the growing evidence of the drug's increasing popularity for weight management as well as the role played by social media. The study also shows how information campaigns about the health risks associated with the off-label use of Ozempic by healthy individuals without a medical cause may help counterbalance the lack of risk awareness detected in social media discussions.</p></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667118224000163/pdfft?md5=e6446bfde3023bfcb79435aa5d444878&pid=1-s2.0-S2667118224000163-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Considering the adverse effect of drug abuse on Parenting, this study was conducted to determine the parenting style of parents undergoing substance abuse treatment who were referred to addiction treatment clinics in Bojnurd in 2021.
Methods
The type of cross-sectional study was descriptive-analytical. The sample size was 360 parents with adolescent children (12–20 years old) undergoing substance abuse treatment who were included in the study by simple random sampling. A two-part questionnaire, including personal characteristics questions and Bamrind's parenting style questionnaire, was used to collect information. Data analysis was done using SPSS 23 software with parametric T-test, ANOVA, and non-parametric equivalent tests of Spearman's correlation at a significance level of 0.05.
Results
The average score of permissive, authoritarian, and authoritative parenting styles was (16.15±5.92), (18±6.34) and (24.89±7.09) respectively. Men used permissive and authoritarian parenting styles significantly more than women. The people living in the village, compared to the city residents, and the people in the Turkish and Kurdish ethnicities, compared to Fars, significantly used authoritarian parenting style more. People using opioids significantly less preferred the permissive method and the authoritarian method compared to stimulant drug users and simultaneous users of stimulant and opioid drugs.
Conclusion
Children of parents with substance abuse disorders are at risk of various adverse consequences, and it seems that inconsistent behavior of parents is an essential cause of this risk; therefore, the need for public education regarding Parenting, especially in addicted parents, is raised.
{"title":"Parenting style of parents undergoing substance abuse treatment having adolescent children (12–20 years old) referring to addiction treatment clinics in Bojnurd","authors":"Yasaman Jafari , Rezvan Rajabzadeh , Seyed Hamid Hosseini , Mohammad Khorrami , Nazanin Gholizadeh , Malihe Namvar","doi":"10.1016/j.etdah.2024.100158","DOIUrl":"10.1016/j.etdah.2024.100158","url":null,"abstract":"<div><h3>Background</h3><p>Considering the adverse effect of drug abuse on Parenting, this study was conducted to determine the parenting style of parents undergoing substance abuse treatment who were referred to addiction treatment clinics in Bojnurd in 2021.</p></div><div><h3>Methods</h3><p>The type of cross-sectional study was descriptive-analytical. The sample size was 360 parents with adolescent children (12–20 years old) undergoing substance abuse treatment who were included in the study by simple random sampling. A two-part questionnaire, including personal characteristics questions and Bamrind's parenting style questionnaire, was used to collect information. Data analysis was done using SPSS 23 software with parametric T-test, ANOVA, and non-parametric equivalent tests of Spearman's correlation at a significance level of 0.05.</p></div><div><h3>Results</h3><p>The average score of permissive, authoritarian, and authoritative parenting styles was (16.15±5.92), (18±6.34) and (24.89±7.09) respectively. Men used permissive and authoritarian parenting styles significantly more than women. The people living in the village, compared to the city residents, and the people in the Turkish and Kurdish ethnicities, compared to Fars, significantly used authoritarian parenting style more. People using opioids significantly less preferred the permissive method and the authoritarian method compared to stimulant drug users and simultaneous users of stimulant and opioid drugs.</p></div><div><h3>Conclusion</h3><p>Children of parents with substance abuse disorders are at risk of various adverse consequences, and it seems that inconsistent behavior of parents is an essential cause of this risk; therefore, the need for public education regarding Parenting, especially in addicted parents, is raised.</p></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100158"},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667118224000175/pdfft?md5=7f16a6df257e78bc70849d8666a8113e&pid=1-s2.0-S2667118224000175-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142164651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1016/j.etdah.2024.100156
Tarcisio Correa , Jéssica Sales Barbosa , Thiara Vanessa Barbosa da Silva , Thiala Soares Josino da Silva Parente , Danielle de Paula Magalhães , Wanderley Pinheiro Holanda Júnior
The rapid development and introduction of new psychoactive substances (NPS) into illegal markets present an enormous challenge for forensic toxicologists, as there is limited knowledge about their toxicity in humans. To strengthen forensic interpretation of NPS intoxication cases, we have developed a predictive model for estimating human lethal blood concentrations (LBC) of various NPS. This quantitative structure-activity relationship (QSAR) model focuses on opioids, designer benzodiazepines, synthetic cathinones, synthetic cannabinoids, and phenethylamines. Utilising linear regression and multilayer perceptron algorithms, the models was trained using data from the existing literature. A toxicological significance-based approach have been applied to refine the selection of training data. The model demonstrated satisfactory performance metrics through cross-validation (R ≈ 0.8, MAE ≈ 0.6) and comparison with experimental data (R ≈ 0.9). A Python-based web application have been developed to facilite the use of the created model in predicting LBC of NPS. Despite the model's reliability, limitations due to data availability, quality and the complexities of post-mortem toxicology mean that its predictions should be interpreted with caution.
{"title":"A QSAR-based application for the prediction of lethal blood concentration of new psychoactive substances","authors":"Tarcisio Correa , Jéssica Sales Barbosa , Thiara Vanessa Barbosa da Silva , Thiala Soares Josino da Silva Parente , Danielle de Paula Magalhães , Wanderley Pinheiro Holanda Júnior","doi":"10.1016/j.etdah.2024.100156","DOIUrl":"10.1016/j.etdah.2024.100156","url":null,"abstract":"<div><p>The rapid development and introduction of new psychoactive substances (NPS) into illegal markets present an enormous challenge for forensic toxicologists, as there is limited knowledge about their toxicity in humans. To strengthen forensic interpretation of NPS intoxication cases, we have developed a predictive model for estimating human lethal blood concentrations (LBC) of various NPS. This quantitative structure-activity relationship (QSAR) model focuses on opioids, designer benzodiazepines, synthetic cathinones, synthetic cannabinoids, and phenethylamines. Utilising linear regression and multilayer perceptron algorithms, the models was trained using data from the existing literature. A toxicological significance-based approach have been applied to refine the selection of training data. The model demonstrated satisfactory performance metrics through cross-validation (<em>R</em> ≈ 0.8, MAE ≈ 0.6) and comparison with experimental data (<em>R</em> ≈ 0.9). A Python-based web application have been developed to facilite the use of the created model in predicting LBC of NPS. Despite the model's reliability, limitations due to data availability, quality and the complexities of <em>post-mortem</em> toxicology mean that its predictions should be interpreted with caution.</p></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100156"},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667118224000151/pdfft?md5=2719b77e6514717fbfe2a068903f6205&pid=1-s2.0-S2667118224000151-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141848388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-22DOI: 10.1016/j.etdah.2024.100155
Achiya Khanom , Most. Zannatul Ferdous , Md. Saiful Islam , Ummay Soumayia Islam , Hailay Abrha Gesesew , Paul R Ward
University students may be particularly vulnerable to develop mental disorders, including depression, due to sudden and unexpected changes in their daily life during the COVID-19 pandemic. The present study aimed to assess depression among male smokers and non-smokers university students during the first wave of COVID-19 in Bangladesh. A web-based cross-sectional survey was conducted among 444 university male students using convenient and snowball sampling with a 1:1 ratio of male smokers and non-smokers from July to October, 2020. The prevalence estimates of moderate to severe depression were 53.6 % and 22.1 %, respectively among male smokers and non-smokers with an overall prevalence rate of 37.9 %. The participants who smoked cigarette were 4.05 times more likely to have depression compared to those who did not smoke (AOR = 4.05; 95 % CI = 2.60–6.30, p < 0.001). The following factors were found to be associated with depression: being smokers, having family members who lost jobs due to the impact of COVID-19, and having food scarcity due to COVID-19. The findings suggest mental health awareness and psychosocial support programs with a special focus on quitting smoking behavior among university students.
{"title":"Depressive symptoms among cigarette smokers and non-smokers during the first wave of COVID-19 pandemic: Preliminary findings from Bangladeshi male university students","authors":"Achiya Khanom , Most. Zannatul Ferdous , Md. Saiful Islam , Ummay Soumayia Islam , Hailay Abrha Gesesew , Paul R Ward","doi":"10.1016/j.etdah.2024.100155","DOIUrl":"https://doi.org/10.1016/j.etdah.2024.100155","url":null,"abstract":"<div><p>University students may be particularly vulnerable to develop mental disorders, including depression, due to sudden and unexpected changes in their daily life during the COVID-19 pandemic. The present study aimed to assess depression among male smokers and non-smokers university students during the first wave of COVID-19 in Bangladesh. A web-based cross-sectional survey was conducted among 444 university male students using convenient and snowball sampling with a 1:1 ratio of male smokers and non-smokers from July to October, 2020. The prevalence estimates of moderate to severe depression were 53.6 % and 22.1 %, respectively among male smokers and non-smokers with an overall prevalence rate of 37.9 %. The participants who smoked cigarette were 4.05 times more likely to have depression compared to those who did not smoke (AOR = 4.05; 95 % CI = 2.60–6.30, <em>p</em> < 0.001). The following factors were found to be associated with depression: being smokers, having family members who lost jobs due to the impact of COVID-19, and having food scarcity due to COVID-19. The findings suggest mental health awareness and psychosocial support programs with a special focus on quitting smoking behavior among university students.</p></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266711822400014X/pdfft?md5=9271e9142d5190b74b8de8b5fdf5003d&pid=1-s2.0-S266711822400014X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-31DOI: 10.1016/j.etdah.2024.100154
Scott Leo Renshaw , Kathleen M. Carley
As society grapples with the emerging significance and implications of Large Language Models (LLMs), such as OpenAI’s ChatGPT, or Google’s Gemini, as well as other advancements in modern generative Artificial Intelligence (AI), it is crucial to recognize the existing role that data, algorithms, and online social networks have already played in shaping our contemporary society. This review article provides the first comprehensive examination of the current state of knowledge, across disciplinary divides, on how online influences impact offline behaviors, laying the necessary groundwork for investigating and researching the potential impact that these new technologies will have on our “offline” lives. Through a deep-dive collection of articles (), we review and analyze research with measurable Online-to-Offline impacts (). Within this Online-to-Offline criteria, we identify five emergent cross-cutting themes, namely: Social Diffusion, Social Reinforcement, Social Boundary & Identity Maintenance, Cognitive and Attitudinal Research, and Research on Vulnerable & Marginalized Impacts. Through a second wave snowball collection process, we construct a citation network from the broader Online and Offline research literature, allowing us to locate the Online-to-Offline subset as part of a larger intellectual discussion. Finally, we conduct a Term Frequency-Inverse Document Frequency (TF-IDF) analysis of terms used in the titles of these online/offline research papers, from 1990 to 2023, to identify the evolution of researchers’ conceptualization and framing of Online and Offline research across the past 30 years. The meta-review, presentation of high-level cross-cutting interdisciplinary themes, co-citation network analysis, and TF-IDF analysis collectively provide a cohesive and deeper understanding of the research space of online/offline influences. By taking stock of the ways in which online factors have already shaped individual, group, or organizational behaviors and social dynamics broadly in “offline” contexts, this work aims to provide a cohesive theoretical and empirical foundation for future researchers to better anticipate, address, and frame the future consequences of the rapidly evolving digitally influenced landscape we find ourselves in today.
{"title":"Linking online activity to offline behavior: A meta-review of three decades of online-to-offline scholarship with future implications for AI","authors":"Scott Leo Renshaw , Kathleen M. Carley","doi":"10.1016/j.etdah.2024.100154","DOIUrl":"10.1016/j.etdah.2024.100154","url":null,"abstract":"<div><p>As society grapples with the emerging significance and implications of Large Language Models (LLMs), such as OpenAI’s ChatGPT, or Google’s Gemini, as well as other advancements in modern generative Artificial Intelligence (AI), it is crucial to recognize the existing role that data, algorithms, and online social networks have already played in shaping our contemporary society. This review article provides the first comprehensive examination of the current state of knowledge, across disciplinary divides, on how online influences impact offline behaviors, laying the necessary groundwork for investigating and researching the potential impact that these new technologies will have on our “offline” lives. Through a deep-dive collection of articles (<span><math><mrow><mi>n</mi><mo>=</mo><mn>149</mn></mrow></math></span>), we review and analyze research with measurable Online-to-Offline impacts (<span><math><mrow><mi>n</mi><mo>=</mo><mn>88</mn></mrow></math></span>). Within this Online-to-Offline criteria, we identify five emergent cross-cutting themes, namely: Social Diffusion, Social Reinforcement, Social Boundary & Identity Maintenance, Cognitive and Attitudinal Research, and Research on Vulnerable & Marginalized Impacts. Through a second wave snowball collection process, we construct a citation network from the broader Online and Offline research literature, allowing us to locate the Online-to-Offline subset as part of a larger intellectual discussion. Finally, we conduct a Term Frequency-Inverse Document Frequency (TF-IDF) analysis of terms used in the titles of these online/offline research papers, from 1990 to 2023, to identify the evolution of researchers’ conceptualization and framing of Online and Offline research across the past 30 years. The meta-review, presentation of high-level cross-cutting interdisciplinary themes, co-citation network analysis, and TF-IDF analysis collectively provide a cohesive and deeper understanding of the research space of online/offline influences. By taking stock of the ways in which online factors have already shaped individual, group, or organizational behaviors and social dynamics broadly in “offline” contexts, this work aims to provide a cohesive theoretical and empirical foundation for future researchers to better anticipate, address, and frame the future consequences of the rapidly evolving digitally influenced landscape we find ourselves in today.</p></div>","PeriodicalId":72899,"journal":{"name":"Emerging trends in drugs, addictions, and health","volume":"4 ","pages":"Article 100154"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667118224000138/pdfft?md5=9ba395fcc98bd7c7899f763a5189485f&pid=1-s2.0-S2667118224000138-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142048425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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