Drug and alcohol review最新文献_第5页

Is Addiction Research Addicted to Artificial Intelligence? Mapping the Intersection of Artificial Intelligence, Substance Use and Mental Health Through a Bibliometric Analysis 成瘾研究是否对人工智能上瘾？通过文献计量学分析绘制人工智能、物质使用和心理健康的交集。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-08 DOI: 10.1111/dar.70057

Loïs Vanhée, Simone Scarpa

Issues

From extracting insights from large-scale, multimodal data to prevention and support, there is growing interest in the applications and implications of recent advances in Artificial Intelligence (AI) within the fields of addiction, substance use and mental health, which we refer to as ASUM. However, due to the absence of a structured mapping of AI for ASUM, it remains unclear how this interest is translated into concrete research results.

Approach

This paper addresses this gap by conducting a bibliometric analysis of AI for ASUM, exploring: (i) the scale of ASUM-related research (number of publications, authors, institutions and countries); (ii) the evolution of ASUM‘s research productivity over time, both in absolute terms and relative to its parent disciplines; (iii) the key topics within ASUM and their interrelations.

Key Findings

Results, supplemented by a comparison of similar fields, show that, while ASUM is an emerging and rapidly expanding domain (with a 25-fold increase in research output since 2012, attracting growing attention relative to parent disciplines as well as appearing to rely on applying more advanced AI methods than related fields), it remains largely fragmented through a dispersed group of infrequent contributors.

Implications

An integration of the findings suggests two dominant trajectories through which AI for ASUM is currently being realised: as AI-driven analytic support and as innovative research and therapeutic methods (e.g., virtual reality, chatbots).

Conclusions

The paper concludes by situating AI for ASUM as an emerging scientific field, outlining the scientific and practical challenges and opportunities that are likely to arise, and high-potential research areas open for exploration.

问题：从从大规模、多模式数据中提取见解到预防和支持，人们对人工智能（AI）在成瘾、物质使用和心理健康领域（我们称之为ASUM）的最新进展的应用和影响越来越感兴趣。然而，由于缺乏ASUM人工智能的结构化映射，目前尚不清楚这种兴趣如何转化为具体的研究成果。方法：本文通过对ASUM的人工智能进行文献计量分析来解决这一差距，探索：(i) ASUM相关研究的规模（出版物、作者、机构和国家的数量）；（ii） ASUM的研究生产力随时间的演变，无论是绝对的还是相对于其母学科的；（三）亚欧会议的主要议题及其相互关系。主要发现：通过对类似领域的比较，结果表明，尽管ASUM是一个新兴且迅速扩张的领域（自2012年以来，研究产出增长了25倍，相对于母学科吸引了越来越多的关注，并且似乎依赖于应用比相关领域更先进的人工智能方法），但它在很大程度上仍然是分散的，由一群不常见的贡献者组成。研究结果的整合表明，目前ASUM的人工智能正在实现两种主要轨迹：作为人工智能驱动的分析支持，以及作为创新的研究和治疗方法（例如，虚拟现实、聊天机器人）。结论：本文最后将ASUM人工智能定位为一个新兴的科学领域，概述了可能出现的科学和实践挑战和机遇，以及开放探索的高潜力研究领域。

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引用次数: 0

A Qualitative Study of How Teens in Washington State Make Sense of Cannabis Edibles Warning Labels and Packaging 华盛顿州青少年如何理解大麻食用警告标签和包装的定性研究。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-08 DOI: 10.1111/dar.70071

Jessica Fitts Willoughby, Stacey J. T. Hust, Soojung Kang, Leticia Couto, Ron Price, Christina Griselda Nickerson, Opeyemi Johnson, Sarah Ross-Viles

Introduction

Washington state's adult use cannabis market operates under regulations by the Washington State Liquor and Cannabis Board to restrict access and promotion among young people. Cannabis edibles sold in the state are required to contain specific labels that inform consumers that the product contains cannabis and provide contact information for Poison Control. However, it is unclear how teens perceive such labels.

Methods

Ten focus groups were conducted with a diverse sample of 28 teens (M = 15.93, SD = 1.25) in Washington state, United States. After viewing images of cannabis edible products available in Washington state, participants shared their thoughts and opinions about the packaging, warning labels and nutrition information.

Results

Through a thematic analysis, we noted that teens may be misinterpreting warning labels, and they think warning labels are hidden or unnoticeable. Most teens paid little attention to nutrition labels and often found serving size information confusing. Teens said if an edible product looked similar to snack products they know, they might perceive them as less risky and more enticing. Knowledge of cannabis products also impacted teens' understanding of edible product packaging.

Discussion and Conclusions

Labels alert teens to the fact that products contain cannabis. However, teens often feel such labels apply to younger children and would not keep teens from using a product. Youth might benefit from additional guidance around interpreting cannabis packaging and labels.

简介：华盛顿州的成人使用大麻市场在华盛顿州酒类和大麻委员会的规定下运作，以限制年轻人获得和推广。在该州销售的大麻食品必须包含特定的标签，告知消费者该产品含有大麻，并提供毒物控制的联系信息。然而，目前尚不清楚青少年如何看待这些标签。方法：选取美国华盛顿州10个不同样本的青少年28人（M = 15.93, SD = 1.25）进行焦点小组调查。在观看了华盛顿州可食用大麻产品的图片后，参与者分享了他们对包装、警告标签和营养信息的想法和意见。结果：通过专题分析，我们注意到青少年可能会误解警告标签，他们认为警告标签是隐藏的或不明显的。大多数青少年很少注意营养标签，经常发现每份的份量信息令人困惑。青少年表示，如果一种可食用产品看起来与他们所知道的零食相似，他们可能会认为这种产品风险更小，更诱人。对大麻产品的了解也影响了青少年对食用产品包装的理解。讨论和结论：标签提醒青少年产品中含有大麻。然而，青少年往往觉得这样的标签适用于更年幼的孩子，并不能阻止青少年使用产品。青少年可能会从解读大麻包装和标签的额外指导中受益。

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引用次数: 0

A Scoping Review of Large Language Model Chatbot Use for Alcohol and Other Drug Health Information 大型语言模型聊天机器人用于酒精和其他药物健康信息的范围审查。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-06 DOI: 10.1111/dar.70068

Natasha Harding, Nataly Bovopoulos, Dotahn Caspi, Craig Martin, Skye McPhie, Mohamed Reda Bouadjenek, Sunil Aryal, Michael Hobbs

Issues

While people prefer to seek alcohol and drug information (AOD) online, there can be quality and accessibility issues with these sources. Large Language Model (LLM) based chatbots are an emerging technology that may present an opportunity to overcome these barriers. We aimed to review the literature on the use of chatbots for seeking AOD health information, particularly the benefits, challenges and recommendations for future use.

Approach

Scoping review methodology was used to conduct a systematic search of four databases for English language studies relating to the use of chatbots to seek AOD health information in the last 5 years. This resulted in the screening of 243 articles, with five included studies.

Key Findings

There has been growing interest in the topic, though evidence is still limited. Despite identified benefits of chatbot use such as accuracy, appropriateness, overall experience and the provision of supporting documentation, important challenges in user safety concerns, lack of referral, quality, readability issues, and lack of adherence to current guidelines were noted, with mixed results regarding evidence-based responses. Only three of the five studies recommended chatbots for AOD-information seeking.

Implications/Conclusion

The current review suggests gaps in knowledge remain in the areas of accuracy, user safety, readability, evidence base and quality of LLM chatbot responses to AOD questions. More research is needed to investigate the applicability of LLMs in obtaining safe, non-stigmatising AOD information.

问题：虽然人们更喜欢在网上寻找酒精和药物信息（AOD），但这些来源可能存在质量和可及性问题。基于大型语言模型（LLM）的聊天机器人是一种新兴技术，它可能为克服这些障碍提供机会。我们的目的是回顾关于使用聊天机器人寻求AOD健康信息的文献，特别是其益处、挑战和对未来使用的建议。方法：采用范围审查方法对四个数据库进行系统搜索，以获取与过去5年使用聊天机器人寻求AOD健康信息有关的英语研究。结果筛选了243篇文章，其中5篇纳入研究。主要发现：尽管证据仍然有限，但人们对这个话题的兴趣越来越大。尽管确定了使用聊天机器人的好处，如准确性、适当性、整体体验和提供支持性文档，但注意到用户安全问题、缺乏转诊、质量、可读性问题以及缺乏对当前指南的遵守等方面的重要挑战，在循证回应方面的结果好坏参半。五项研究中只有三项建议使用聊天机器人来寻找aod信息。影响/结论：目前的综述表明，LLM聊天机器人对AOD问题的回答在准确性、用户安全性、可读性、证据基础和质量方面仍存在知识差距。需要更多的研究来调查llm在获取安全，非污名化的AOD信息方面的适用性。

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引用次数: 0

Effectiveness of Psychosocial Interventions for Adults With Substance Use Disorder That Have a Co-Occurring Common Mental Health Disorder: An Umbrella Review 心理社会干预对成人物质使用障碍并发常见心理健康障碍的有效性：综述

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-05 DOI: 10.1111/dar.70066

Emma L. Simpson, Munira Essat, Ruth Wong, Sarah Stacey, Edward Day

Issues

People with substance use disorders can have co-occurring mental disorders.

Approach

An umbrella review was conducted to identify evidence of the effectiveness of psychosocial interventions for adults (aged 18+) with substance use disorders and co-occurring common mental health disorders. Systematic reviews were sought of randomised controlled trials of psychosocial interventions compared to each other, treatment as usual or wait-list. Five databases were systematically searched in February 2024. Data, including critical appraisal (Joanna Briggs Institute Checklist), were extracted by one reviewer and checked by another. Data were discussed in a narrative review.

Key Findings

Of 5420 unique records, 28 systematic reviews were included. The methodological quality of the reviews was good. Most reviews focused on depression, anxiety or post-traumatic stress disorder. There was much heterogeneity between reviews, and randomised controlled trials within reviews. Most of the interventions and many of the treatment-as-usual comparators resulted in significant improvement in substance use and mental health disorders. Results suggested integrated (co-ordinated) treatment for co-occurring diagnosis patients was better than treating one condition alone, and usually better than parallel uncoordinated services. There was limited evidence assessing sequential treatment, but this suggested similar effectiveness to integrated treatment.

Implications

Implications for current practise could not be recommended due to heterogeneity. Improvement shown by all types of psychosocial intervention including active comparators precluded recommending one type of intervention over another.

Conclusion

Further research is needed comparing integrated with parallel or sequential treatment, with follow-up of 6 months or longer, and sample size large enough to encompass dropout.

问题：有物质使用障碍的人可能同时患有精神障碍。方法：进行了一项综合审查，以确定对患有物质使用障碍和共同发生的常见精神健康障碍的成年人（18岁以上）进行社会心理干预的有效性的证据。对随机对照试验进行了系统评价，将心理社会干预、常规治疗或等待治疗进行了比较。2024年2月系统检索了5个数据库。数据，包括关键的评估（乔安娜布里格斯研究所清单），由一个审稿人提取，并由另一个审稿人检查。在一篇叙述性综述中讨论了数据。主要发现：在5420个独特记录中，包括28个系统评价。综述的方法学质量很好。大多数评论集中在抑郁、焦虑或创伤后应激障碍上。综述之间存在很大的异质性，综述中的随机对照试验也存在很大的异质性。大多数干预措施和许多照旧治疗比较办法在药物使用和精神健康障碍方面取得了显著改善。结果表明，对合并诊断患者进行综合（协调）治疗优于单独治疗一种疾病，通常优于并行的不协调服务。评估顺序治疗的证据有限，但这表明与综合治疗的效果相似。含义：由于异质性，不能推荐对当前实践的含义。包括主动比较者在内的所有类型的社会心理干预所显示的改善排除了推荐一种干预而不是另一种干预的可能性。结论：与平行或序贯治疗相比较，随访6个月或更长时间，样本量大到足以包括退出，需要进一步的研究。

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引用次数: 0

Addressing Hepatitis A and Hepatitis B Risks: Screening and Preventative Care for People Who Inject Drugs 应对甲型肝炎和乙型肝炎风险：注射吸毒者的筛查和预防性保健。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-04 DOI: 10.1111/dar.70064

Wendy Yao, Natali Jokanovic, Hashini Herath, Susan Poole, Kate Mackie, Joseph S. Doyle, Alison Duncan

Introduction

People who inject drugs (PWID) often present to hospital with complicated infections, providing an opportunity to screen and vaccinate for hepatitis A virus (HAV) and hepatitis B virus (HBV). This study evaluated HAV and HBV screening and vaccination among PWID over 3 years.

Methods

A single-centre retrospective study of all infectious diseases inpatient admissions for current PWID with a length of stay ≥ 48 h, Drug and Alcohol team referral and/or opioid substitution therapy was performed (January 2020–December 2022). Serological screening for HAV (immunoglobulin G [IgG]) and HBV (complete screening: surface antigen, core and surface antibodies), and vaccinations were collected per encounter. The prevalence of serological screening and vaccinations against HAV and HBV and differences in characteristics by screening status were explored with descriptive statistics.

Results

Overall, 115 patients from 159 encounters were included (mean age: 41.8 ± 8.4 years; male: n = 73, 64%; median length of stay: 7 (IQR 4–16) days). Anti-HAV screening was performed for 47 patients across 57 (35.8%) encounters, with 12 patients who screened negative vaccinated (n = 12/21, 57.1%). Complete HBV screening was performed for 75 patients across 85 (53.5%) encounters, with 7 patients who screened negative vaccinated (n = 7/12, 58.3%). Males were more likely to receive HAV screening than females (77% vs. 23%, p = 0.015). HBV screening was less likely in encounters requiring intensive care unit admission (12% vs. 88%, p = 0.038).

Discussion and Conclusions

While more than half of eligible patients received vaccination, complete screening for both HAV and HBV was low. Initiatives including electronic serology order sets should be considered to improve screening.

注射吸毒者（PWID）经常因并发感染而住院，这为筛查和接种甲型肝炎病毒（HAV）和乙型肝炎病毒（HBV）提供了机会。本研究评估了3年来PWID患者HAV和HBV筛查和疫苗接种情况。方法：在2020年1月至2022年12月期间，对所有住院时间≥48小时、接受药物和酒精团队转诊和/或阿片类药物替代治疗的感染性疾病住院患者进行单中心回顾性研究。每次相遇收集HAV（免疫球蛋白G [IgG]）和HBV（完整筛查：表面抗原、核心抗体和表面抗体）的血清学筛查和疫苗接种。采用描述性统计方法探讨乙型肝炎病毒和乙型肝炎病毒的血清学筛查和疫苗接种的流行情况以及筛查状况在特征上的差异。结果：总共纳入159例就诊的115例患者（平均年龄：41.8±8.4岁；男性：n = 73,64%；中位住院时间：7 （IQR 4-16）天）。在57例（35.8%）病例中，对47例患者进行了抗甲肝病毒筛查，其中12例患者的筛查结果为阴性（n = 12/21, 57.1%）。在85例（53.5%）病例中，对75例患者进行了完全的HBV筛查，其中7例患者接种疫苗后筛查为阴性（n = 7/12, 58.3%）。男性比女性更有可能接受甲肝病毒筛查（77%对23%，p = 0.015）。需要进入重症监护病房的患者较少接受HBV筛查（12% vs. 88%, p = 0.038）。讨论和结论：虽然超过一半的符合条件的患者接受了疫苗接种，但HAV和HBV的完全筛查率很低。应考虑采取措施，包括电子血清学单集，以改善筛查。

{"title":"Addressing Hepatitis A and Hepatitis B Risks: Screening and Preventative Care for People Who Inject Drugs","authors":"Wendy Yao, Natali Jokanovic, Hashini Herath, Susan Poole, Kate Mackie, Joseph S. Doyle, Alison Duncan","doi":"10.1111/dar.70064","DOIUrl":"10.1111/dar.70064","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>People who inject drugs (PWID) often present to hospital with complicated infections, providing an opportunity to screen and vaccinate for hepatitis A virus (HAV) and hepatitis B virus (HBV). This study evaluated HAV and HBV screening and vaccination among PWID over 3 years.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A single-centre retrospective study of all infectious diseases inpatient admissions for current PWID with a length of stay ≥ 48 h, Drug and Alcohol team referral and/or opioid substitution therapy was performed (January 2020–December 2022). Serological screening for HAV (immunoglobulin G [IgG]) and HBV (complete screening: surface antigen, core and surface antibodies), and vaccinations were collected per encounter. The prevalence of serological screening and vaccinations against HAV and HBV and differences in characteristics by screening status were explored with descriptive statistics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Overall, 115 patients from 159 encounters were included (mean age: 41.8 ± 8.4 years; male: <i>n</i> = 73, 64%; median length of stay: 7 (IQR 4–16) days). Anti-HAV screening was performed for 47 patients across 57 (35.8%) encounters, with 12 patients who screened negative vaccinated (<i>n</i> = 12/21, 57.1%). Complete HBV screening was performed for 75 patients across 85 (53.5%) encounters, with 7 patients who screened negative vaccinated (<i>n</i> = 7/12, 58.3%). Males were more likely to receive HAV screening than females (77% vs. 23%, <i>p</i> = 0.015). HBV screening was less likely in encounters requiring intensive care unit admission (12% vs. 88%, <i>p</i> = 0.038).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion and Conclusions</h3>\u0000 \u0000 <p>While more than half of eligible patients received vaccination, complete screening for both HAV and HBV was low. Initiatives including electronic serology order sets should be considered to improve screening.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11318,"journal":{"name":"Drug and alcohol review","volume":"45 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145437799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Community Pharmacy-Based Injectable Opioid Agonist Treatment: Findings From a Canadian Pilot Program 以社区药房为基础的注射阿片类激动剂治疗：来自加拿大试点项目的发现。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-04 DOI: 10.1111/dar.70062

Tamara Mihic, Maria Eugenia Socias, Karen McCrae, Cheyenne Johnson, Seonaid Nolan, Cameron Grant, Christy Sutherland, Nadia Fairbairn

Introduction

Access to evidence-based treatment for opioid use disorder remains limited, particularly for individuals who have not responded to oral opioid agonist treatment (OAT). A community pharmacy-based model of injectable OAT (iOAT) was piloted in Vancouver, Canada from March 2017 to December 2018. This brief report describes the program structure, participant sociodemographics, reported outcomes, and strengths and areas for improvement of the program.

Methods

A retrospective review of cross-sectional, interviewer-led questionnaire data from participants who accessed iOAT at the pharmacy site (n = 176) and provided informed consent was conducted. Outcomes include participant-reported changes in symptomatology, function and satisfaction, analysed through descriptive statistics. Open-ended responses were analysed using content analysis to identify strengths and areas for improvement of the program.

Results

Fifty-one participants (29%) completed the questionnaire, and most had multiple previous overdoses and trials of oral OAT. The most commonly reported outcomes were reduction in illicit opioid use (76%), opioid cravings (45%) and illicit substance use (45%). Participants identified key strengths of the program as positive experiences with staff and efficiency of the pharmacy model including flexible dosing time and the ability to pick up other medications at the same time. Suggested improvements focused on medication options (e.g., access to diacetylmorphine, alternate routes of administration), expanded hours and flexibility, additional support services, and increased capacity and space.

Discussion and Conclusions

Community pharmacy-based iOAT represents a novel strategy to expand access to evidence-based opioid use disorder treatment among individuals who inject opioids and have not responded to or do not prefer oral OAT.

阿片类药物使用障碍的循证治疗仍然有限，特别是对口服阿片类药物激动剂治疗（OAT）无反应的个体。2017年3月至2018年12月，以社区药房为基础的可注射OAT （iOAT）模式在加拿大温哥华进行了试点。这份简短的报告描述了项目结构、参与者的社会人口统计、报告的结果以及项目的优势和需要改进的领域。方法：对在药房现场访问iOAT并提供知情同意的参与者（n = 176）的横断面访谈问卷数据进行回顾性分析。结果包括参与者报告的症状、功能和满意度的变化，并通过描述性统计进行分析。使用内容分析来分析开放式回答，以确定该计划的优势和改进领域。结果：51名参与者（29%）完成了问卷调查，其中大多数有多次口服OAT的过量用药和试验。最常见的报告结果是减少非法阿片类药物使用（76%）、阿片类药物渴望（45%）和非法药物使用（45%）。参与者确定了该计划的主要优势，包括员工的积极体验和药房模式的效率，包括灵活的给药时间和同时取药的能力。建议的改进侧重于药物选择（例如获得二乙酰吗啡、替代给药途径）、延长工作时间和灵活性、增加支助服务以及增加能力和空间。讨论和结论：基于社区药房的iOAT代表了一种新的策略，可以在注射阿片类药物且对口服OAT没有反应或不喜欢口服OAT的个体中扩大获得基于证据的阿片类药物使用障碍治疗的机会。

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引用次数: 0

Single-Dose, Long-Acting Injectable Buprenorphine for Opioid Withdrawal Treatment 单剂量长效注射丁丙诺啡用于阿片类药物戒断治疗。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-04 DOI: 10.1111/dar.70070

Jeffrey S. Kruk, Judith L. Fraser, Prasun Datta, Karen A. Fisher

Introduction

Long-acting, injectable buprenorphine (LAIB) is a recently introduced opioid agonist treatment (OAT) for opioid dependence in Australia. Little research has been performed for its role in opioid withdrawal management.

Methods

A retrospective analysis of hospital patient records was conducted for five patients who received a single dose of LAIB as part of an inpatient or outpatient opioid withdrawal management program. Patients analysed had tried and failed conventional opioid withdrawal management and were unwilling to commence or continue an OAT program.

Results

Patient demographics including types of opioid use and inpatient lengths of stay are reported. Patient withdrawal symptoms before treatment and during follow-up periods are also described. Overall, most patients were satisfied with a single dose of LAIB to adequately control withdrawal symptoms in the community.

Discussion and Conclusions

Given the stability of OAT patients on LAIB, it was inferred that some patients may do well in opioid withdrawal management using LAIB, should other conventional treatments not succeed. This was based on previous pharmacokinetic data and modelling by others which would allow for a slow, in vivo wean of the drug rather than discrete, daily dose reductions. For patients, this could reduce potential withdrawal symptoms and shorten admission lengths in hospital withdrawal management wards. Further research is needed to verify these results, but these preliminary data are encouraging.

简介：长效，可注射丁丙诺啡（LAIB）是最近在澳大利亚推出的阿片类药物激动剂治疗（OAT）阿片类药物依赖。很少研究其在阿片类药物戒断管理中的作用。方法：回顾性分析5例接受单剂量LAIB作为住院或门诊阿片类药物戒断管理计划一部分的患者的住院病历。分析的患者曾尝试过传统的阿片类药物戒断管理，但失败，不愿开始或继续OAT计划。结果：报告了患者人口统计数据，包括阿片类药物使用类型和住院时间。患者在治疗前和随访期间的戒断症状也被描述。总体而言，大多数患者对单剂量LAIB能充分控制社区戒断症状感到满意。讨论与结论：考虑到OAT患者对LAIB的稳定性，我们推断，在其他常规治疗不成功的情况下，一些患者使用LAIB可能在阿片类药物戒断管理中表现良好。这是基于先前的药代动力学数据和其他人的建模，这将允许缓慢的体内断药，而不是离散的每日剂量减少。对于患者来说，这可以减少潜在的戒断症状，缩短医院戒断管理病房的住院时间。需要进一步的研究来验证这些结果，但这些初步数据令人鼓舞。

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引用次数: 0

Machine Learning Algorithms to Predict Heavy Episodic Drinking in the United States Using Survey Data 使用调查数据预测美国重度间歇性饮酒的机器学习算法。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-04 DOI: 10.1111/dar.70065

Laura Llamosas-Falcón, Charlotte Probst, Kevin Shield, Erik Spence, Jürgen Rehm

Introduction

Heavy episodic drinking (HED) is a major public health concern but is often missing from surveys or measured unreliably. Predictive models offer a method to estimate HED's likelihood at the individual level in such cases. While logistic regression is commonly used, other machine learning algorithms (MLA) may offer greater accuracy and robustness. This study compares various MLAs to identify the best predictive model of HED.

Methods

Data from the 1997–2018 National Health Interview Survey were used. Six MLAs were trained and cross-validated: logistic regression, naïve bayes, k-nearest neighbour, support vector machine, random forest and XGBoost. Model performance was compared, and the SHapley Additive exPlanations (SHAP) method assessed interpretability by ranking features based on their contribution to the model's prediction.

Results

The probability of correctly ranking a randomly selected HED instance higher than a non-HED instance ranged from 0.85 to 0.97 (with values closer to 1 indicating better performance). XGBoost outperformed the other MLAs (sensitivity 0.80, precision 0.83, accuracy 0.92). Amongst the 11 features included in the models, average daily alcohol use and age were the most influential, as determined by SHAP values.

Discussion and Conclusions

The strong discriminative ability of our models shows that even a limited number of well-chosen features can yield robust predictions, highlighting the potential of MLAs for modelling health behaviours. Integrating our models into simulation frameworks can help model HED and test scenarios, leading to effective policies. Future studies should incorporate objective sources for external validation and investigate systematic biases to improve predictive accuracy.

重度间歇性饮酒（HED）是一个主要的公共卫生问题，但经常在调查中遗漏或测量不可靠。在这种情况下，预测模型提供了一种方法来估计HED在个体水平上的可能性。虽然逻辑回归是常用的，但其他机器学习算法（MLA）可能提供更高的准确性和鲁棒性。本研究比较了各种mla，以确定HED的最佳预测模型。方法：采用1997-2018年全国健康访谈调查数据。6个MLAs被训练并交叉验证：逻辑回归、naïve贝叶斯、k近邻、支持向量机、随机森林和XGBoost。通过比较模型性能，SHapley加性解释（SHAP）方法根据特征对模型预测的贡献对特征进行排序，从而评估可解释性。结果：随机选择的HED实例正确排名高于非HED实例的概率范围为0.85至0.97（值接近1表示性能更好）。XGBoost优于其他MLAs（灵敏度0.80，精密度0.83，准确度0.92）。在模型中包含的11个特征中，平均每日饮酒量和年龄是最具影响力的，由SHAP值确定。讨论和结论：我们模型的强判别能力表明，即使是有限数量的精心选择的特征也可以产生稳健的预测，突出了mla在健康行为建模方面的潜力。将我们的模型集成到仿真框架中可以帮助建模HED和测试场景，从而产生有效的策略。未来的研究应纳入客观来源进行外部验证，并调查系统偏差以提高预测准确性。

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引用次数: 0

Alcohol Purchase Modality: Differences in Demographics, Purchase Patterns and Alcohol-Related Harms Among Australians Who Drink at High-Risk Levels 酒精购买方式：澳大利亚高危饮酒人群在人口统计学、购买模式和酒精相关危害方面的差异

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-11-04 DOI: 10.1111/dar.70069

Kerri Coomber, Kira Button, Ryan Baldwin, Florentine Martino, Adyya Gupta, Kathryn Backholer, Peter G. Miller, Danica Keric, Julia Stafford

Introduction

Alcohol home delivery increases alcohol availability and is associated with high-risk drinking and increased harms. However, little is known about the specific impacts home delivery has among people who consume alcohol at high-risk levels. The current study examined demographics, purchase patterns and alcohol-related harms among Australian adults classified as drinking at high-risk levels, by purchase modality (in-store vs. online for delivery).

Methods

An online panel survey of 700 Australian adults who drink alcohol at high-risk levels measured demographics, usual purchasing behaviour, most recent alcohol purchase and alcohol-related harms. Participants were classified according to how they purchase alcohol: (i) only in-store (n = 202); (ii) occasionally online (n = 299); and (iii) frequently online (n = 199). Regression models controlling for demographics and clustering by location examined the association between purchase modality and purchasing behaviours and harms.

Results

Participants who purchased alcohol frequently online had significantly higher AUDIT-10 scores, were younger, less likely to be female, had higher levels of education, and were more likely to live in high socio-economic areas compared to those purchasing in-store or occasionally online. Participants purchasing frequently online were also significantly more likely to use buy-now-pay-later options than the occasionally online participant group. There were no clear differences in alcohol-related harms experienced by participant groups.

Discussion and Conclusions

The current study reaffirms the need for effective regulations targeting home delivery of alcohol, such as mandated delivery timeframes between sale and delivery and removal of buy-now-pay-later payment options from online alcohol stores.

导言：酒精送货上门增加了酒精的可得性，与高危饮酒和危害增加有关。然而，人们对送货上门对高危饮酒人群的具体影响知之甚少。目前的研究调查了澳大利亚成年人的人口统计数据、购买模式和与酒精相关的危害，这些成年人按购买方式（店内与在线送货）被归类为高危饮酒人群。方法：对700名饮酒高危水平的澳大利亚成年人进行在线小组调查，测量人口统计学、通常购买行为、最近购买酒精和酒精相关危害。参与者根据他们购买酒的方式进行分类：(i)仅在店内购买（n = 202）；（ii）偶尔上网（n = 299）；（iii）经常上网（n = 199）。控制人口统计学和地理位置聚类的回归模型检验了购买方式、购买行为和危害之间的关系。结果：与在实体店或偶尔在网上购买酒的人相比，经常在网上购买酒的参与者有更高的AUDIT-10分数，他们更年轻，女性的可能性更小，受教育程度更高，更有可能生活在高社会经济地区。经常在网上购物的参与者也明显比偶尔上网的参与者更有可能选择先买后付。在酒精相关的危害方面，各参与小组没有明显的差异。讨论和结论：目前的研究重申，需要针对酒精送货上门制定有效的法规，例如规定销售和送货之间的送货时间框架，并取消在线酒精商店的“先买后付”付款选项。

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引用次数: 0

Language Models for Standardising Clinical Notes and Information Extraction in Addiction Psychiatry—An Empirical Study 成瘾精神病学临床记录规范化与信息提取的语言模型研究。

IF 2.6 3区医学 Q2 SUBSTANCE ABUSE

Drug and alcohol review

Pub Date : 2025-10-29 DOI: 10.1111/dar.70059

Haritha Gireesh, Lekhansh Shukla, Prakrithi Shivaprakash, Animesh Mukherjee, Prabhat Chand, Pratima Murthy

<div> <section> <h3> Introduction</h3> <p>Electronic health records contain both structured and unstructured data, with unstructured clinical notes widely used in addiction psychiatry. Clinical notes have numerous errors and require proofreading to ensure accuracy and readability. This study evaluates natural language processing methods and adapts a Large Language Model (LLM) for proofreading clinical notes and extracting substance-related information.</p> </section> <section> <h3> Methods</h3> <p>We analysed clinical notes from a 5-year addiction medicine electronic health record dataset (2018–2023), selecting 6500 notes. The proofreading task involved correcting spelling and expanding abbreviations, while information extraction identified the presence of substance use and quantified the time since last use. Annotations by a team of doctors and nurses provided the gold standard. Against this, we compared the performance of existing solutions, including LLMs, and adapted an LLM for these tasks. The final model (fine-tuned LLAMA-3.2-3b) is also compared against a state-of-the-art commercial model (Generative Pretrained Transformer-4-o), and a human-preference experiment is done with masked raters choosing between model-generated and human-generated proofread versions.</p> </section> <section> <h3> Results</h3> <p>Proofreading improved readability and decreased out-of-vocabulary words. LLM-based solutions outperformed simpler approaches. The fine-tuned model outperformed the Generative Pretrained Transformer-4-o on both tasks. Masked human evaluators chose model-corrected clinical notes over the human-corrected version in 62% of trials (<i>p</i> < 0.001). On the information extraction task, while the overall performance is satisfactory (Mean F1 0.99), it is poor on rarer substance classes like hallucinogens.</p> </section> <section> <h3> Discussion and Conclusions</h3> <p>Fine-tuned LLMs effectively standardised clinical notes and extracted structured information from addiction psychiatry records. Both these functionalities have important applications. Standardising improves the readability of clinical documentation and facilitates communication within and between interdisciplinary teams. Automated information extraction can decrease the burden on clinical staff, allow the creation of research cohorts from existing records and improve treatment outcomes by extracting critical information, such as ‘time since last drink’, which can be used to raise alerts. Even with limited computational resources, it is possible to adapt open-source LLMs for bespoke tasks in the field of addiction psychiatry. Our proposed solution is a model that

电子健康记录包含结构化和非结构化数据，非结构化临床记录广泛应用于成瘾精神病学。临床记录有许多错误，需要校对以确保准确性和可读性。本研究评估了自然语言处理方法，并采用大语言模型（LLM）来校对临床记录和提取物质相关信息。方法：我们分析了5年成瘾药物电子健康记录数据集中（2018-2023）的临床记录，选择了6500个记录。校对任务包括纠正拼写和扩展缩写，而信息提取识别物质使用的存在并量化自上次使用以来的时间。一组医生和护士的注释提供了黄金标准。与此相反，我们比较了现有解决方案的性能，包括LLM，并为这些任务调整了LLM。最后的模型（微调LLAMA-3.2-3b）也与最先进的商业模型（生成预训练变压器-4- 0）进行了比较，并在模型生成和人工生成的校对版本之间进行了屏蔽评分者的人类偏好实验。结果：校对提高了可读性，减少了词汇外的单词。基于llm的解决方案优于更简单的方法。在这两项任务上，微调模型都优于生成预训练的transformer -4- 0。在62%的试验中，蒙面的人类评估者选择了模型修正的临床记录，而不是人类修正的版本(p)。讨论和结论：微调的llm有效地标准化了临床记录，并从成瘾精神病学记录中提取了结构化信息。这两个功能都有重要的应用。标准化提高了临床文献的可读性，促进了跨学科团队内部和之间的沟通。自动信息提取可以减轻临床工作人员的负担，允许从现有记录中创建研究队列，并通过提取关键信息来改善治疗结果，例如“自上次饮酒以来的时间”，这些信息可用于发出警报。即使计算资源有限，也有可能将开源法学硕士用于成瘾精神病学领域的定制任务。我们提出的解决方案是一个可以部署在消费者级服务器上的模型，从而确保数据隐私和安全性。

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引用次数: 0