Emerging trends in drugs, addictions, and health最新文献

Objectives

Methods

Results

Conclusions

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.

Background

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.

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.

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.

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 ($n=149$), we review and analyze research with measurable Online-to-Offline impacts ($n=88$). 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.

Background

The use of online psychological services has shown potential in alleviating mental health concerns during the coronavirus epidemic. This study aimed to investigate the effects of online psychological services on COVID-19 fear and academic achievement among students with addicted parents.

Methods

The current study is a quasi-experimental study with pretest, posttest, and control group. The statistical population of this study included all male and female students in Tehran province in 2022. In order to select the sample, the call to participate in the study was made by the social media (Telegram, WhatsApp, Instagram, LinkedIn) for two months. Then, corona fear questionnaire link was sent to the email addresses of the respondents and 120 students who met the inclusion criteria were selected as the sample of the study. In the next stage, 120 students were randomly assigned in the experimental and control groups. After 8 online sessions, 4 students from the experimental group and 5 students from the control group ended their cooperation due to personal reasons and as a result, 56 and 55 students constituted the experimental and control groups, respectively.

Results

The results indicated a significant increase in academic achievement for students in the experimental group post-intervention compared to the control group. Additionally, online psychological services appeared to mitigate COVID-19 related fears.

Conclusion

This study suggests that online psychological services play a pivotal role in enhancing student's mental well-being during the COVID-19 epidemic.

Gambling disorder can be treated with cognitive behavioral therapy (CBT), but treatment is under-dimensioned in many settings. For example, in Sweden, a setting with mixed responsibility for addiction treatment between health care and social services, treatment for gambling disorder has only recently been introduced in the responsibilities of public institutions. After the introduction of gambling in treatment legislation in 2018, few studies have assessed the real-world feasibility of such treatment. In addition, treatment in social services specifically has not been documented or evaluated, and therefore, in a pioneer gambling treatment facility in such a setting, this study aimed to investigate treatment outcome in patients with gambling disorder six months after completed CBT treatment within a social service setting. Twenty patients receiving CBT treatment during 2018–2020 were followed with respect to gambling habits at end of treatment and at follow-up six months after treatment. The National Opinion Research Center DSM Screen for Gambling Problems (NODS) was used as screening tool. Rates of gambling abstinence, as well as subjective experience of the treatment, are reported. Ninety percent of the patients were abstinent from gambling at six-month follow-up, and 95 percent of the patients no longer fulfilled criteria of a gambling disorder. In conclusion, these pilot results suggest that CBT treatment is a feasible method for treatment of gambling disorder also in a social service setting. However, due to the limited sample size of this pilot study, and the limited background information of clients who could not be reached, future studies with larger sample sizes are needed.

Background

In the current digital age, individuals often look to the widely used social media application “TikTok” to obtain information about autism spectrum disorder (ASD). Despite this, no studies have evaluated the quality of information available about ASD on the app. Our aim was to investigate the understandability, actionability, and usefulness of TikTok videos about ASD.

Methods

To evaluate video quality, 100 videos tagged with “autism spectrum disorder” were obtained from TikTok between June 19th-21st, 2023. Videos were included if they pertained to ASD and excluded if they were not in English, unrelated to ASD, or duplicates. Two systems were used to assess the videos. The Patient Education Materials Assessment Tool for Audio- Visual Materials (PEMAT-A/V) was used to obtain percentage scores for video understandability and actionability. The videos were also sorted into one of three categories: useful, personal experience, or misleading (UPM). The assignment was based on if they contained factual information, anecdotal personal experiences, or incorrect information, respectively.

Results

Of the 100 videos analyzed, 24 % were classified as useful; 36 % as personal experience; and 40 % as misleading. They had a mean PEMAT-A/V understandability score of 60.1 % (SD=14.5, range=31.0–91.7 %) and a median PEMAT-A/V actionability score of 0 % (IQR=0–0, range=0–100 %). The breakdown of topics discussed in the videos were as follows: 62 % of videos discussed the diagnosis/symptoms of ASD, 17 % pertained to disorder management, 7 % gave an overview of the disorder as a whole, 2 % discussed the cause of ASD, and 7 % contained information classified as “other”. The majority of the videos were made by non-HCPs (86 %), while the remaining videos were made by HCPs (14 %). HCPs uploaded a significantly higher percentage of useful content (50 %) than non-HCPs (20 %, p = 0.034). HCPs also uploaded a significantly higher percentage of Diagnosis/Symptoms content (85.7 %) than non-HCPs (62 %, p = 0.015).

Conclusion

TikTok content about ASD is of unsatisfactory quality. Overall, videos are of moderate understandability, very low actionability, and are often misleading. Individuals should exercise caution when browsing the app for information about ASD, and HCPs should be aware that patients are likely to have been exposed to confusing or misleading information.