Research News Roundup: March 6, 2025

Journal: Journal of Medical Internet Research, 2025, doi: 10.2196/66896

Authors: Lorien C. Abroms, Artin Yousefi, Christina N. Wysota, Tien-Chin Wu, & David A. Broniatowski

Abstract:

Background: Large language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. However, little is known about the reliability of the information provided to users.

Objective: This study aims to examine whether 3 ChatGPT chatbots-the World Health Organization’s Sarah, BeFreeGPT, and BasicGPT-provide reliable information on how to quit smoking.

Methods: A list of quit smoking queries was generated from frequent quit smoking searches on Google related to “how to quit smoking” (n=12). Each query was given to each chatbot, and responses were analyzed for their adherence to an index developed from the US Preventive Services Task Force public health guidelines for quitting smoking and counseling principles. Responses were independently coded by 2 reviewers, and differences were resolved by a third coder.

Results: Across chatbots and queries, on average, chatbot responses were rated as being adherent to 57.1% of the items on the adherence index. Sarah’s adherence (72.2%) was significantly higher than BeFreeGPT (50%) and BasicGPT (47.8%; P<.001). The majority of chatbot responses had clear language (97.3%) and included a recommendation to seek out professional counseling (80.3%). About half of the responses included the recommendation to consider using nicotine replacement therapy (52.7%), the recommendation to seek out social support from friends and family (55.6%), and information on how to deal with cravings when quitting smoking (44.4%). The least common was information about considering the use of non-nicotine replacement therapy prescription drugs (14.1%). Finally, some types of misinformation were present in 22% of responses. Specific queries that were most challenging for the chatbots included queries on “how to quit smoking cold turkey,” “…with vapes,” “…with gummies,” “…with a necklace,” and “…with hypnosis.” All chatbots showed resilience to adversarial attacks that were intended to derail the conversation.

Conclusions: LLM chatbots varied in their adherence to quit-smoking guidelines and counseling principles. While chatbots reliably provided some types of information, they omitted other types, as well as occasionally provided misinformation, especially for queries about less evidence-based methods of quitting. LLM chatbot instructions can be revised to compensate for these weaknesses.

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Journal: Implementation Science Communications, 2025, doi: 10.1186/s43058-025-00697-x

Authors: Kelli Scott, Michael J. Mello, Geraldine Almonte, Emely Arenas Lemus, Julie R. Bromberg, Janette Baird, … Sara J. Becker

Abstract:

Background: Screening, Brief Intervention, and Referral to Treatment (SBIRT) is an evidence-based practice that can identify adolescents who use alcohol and other drugs and support proper referral to treatment. Despite an American College of Surgeons mandate to deliver SBIRT in pediatric trauma care, trauma centers throughout the United States have faced numerous patient, provider, and organizational level barriers to SBIRT implementation. The Implementing Alcohol Misuse Screening, Brief Intervention, and Referral to Treatment Study (IAMSBIRT) aimed to implement SBIRT across 10 pediatric trauma centers using the Science-to-Service Laboratory (SSL), an empirically supported implementation strategy. This manuscript aimed to assess trauma center staff preferences and experience with the didactic training, performance feedback, and ongoing coaching elements of the SSL via a retrospective qualitative process evaluation.

Methods: Nurses, social workers, and site leaders that participated in IAMSBIRT were recruited to complete qualitative exit interviews guided by the Consolidated Framework for Implementation Research. Qualitative interviews were recorded, transcribed, and analyzed by two coders using a directed content analysis approach in NVivo software. Codes were then translated into frequently endorsed themes by the IAMSBIRT study research team.

Results: Thirty-six exit interviews were conducted with site leaders, social workers, and nurses across the 10 IAMSBIRT pediatric trauma centers. Findings revealed key strengths as well as areas for improvement across the IAMSBIRT preparation phase and the three elements of the SSL: didactic training, performance feedback, and ongoing coaching. Trauma center staff generally reported that all three elements of the SSL were high quality and helpful for supporting SBIRT implementation. However, staff also noted that performance feedback and ongoing coaching were generally only available to center leadership or to individuals selected by leadership, making it challenging for non-leaders to troubleshoot SBIRT delivery.

Conclusions: Findings from the qualitative process evaluation revealed discrepancies in the experience of the SSL strategy between those in leadership roles and those involved in direct care delivery. These results suggest the need for several modifications to the SSL strategy, including increasing engagement of direct care staff in all elements of the SSL throughout the implementation process.

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Journal: Journal of Substance Use & Addiction Treatment, 2025, doi: 10.1016/j.josat. 2025.209630

Authors: Neil Dunne, Maire-Brid Casey, & Jo-Hanna Ivers

Abstract:

Introduction: Non-fatal opioid overdose (NFOD) is a concerning public health issue that is a risk factor for subsequent fatal overdose.

Methods: This systematic review aimed to evaluate all the previous literature using a self-report method to investigate the risk factors of NFOD. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRSIMA) and its 27-item checklist guided the conduct and reporting of this systematic review. The review used the population, risk factor, and outcome (PRO) framework. The population was studies with a majority of participants that regularly used opioids. Risk factors were demographic, medical, and behavioral characteristics. The outcomes were self-reported recent (<12 months) or lifetime presence of NFOD. The study explored seven databases: PubMed, Embase, Cochrane Library, PsycINFO, CINAHL, ProQuest, and Web of Science and used Google Scholar to search for grey literature. A risk of bias assessment was carried out using ROBANS-E and meta-analysis was performed using STATA.

Results: The review discovered 53 studies using the self-report experience of persons who use opioids assessing different factors associated with NFOD. Involvement in the sex trade, having a lower than typical education, previous incarceration, experiencing homelessness, unemployment, psychiatric co-morbidity, suicidal ideation or behavior, polysubstance use, especially benzodiazepine use and problematic alcohol use, needing help injecting, former opioid agonist therapy (OAT) engagement, previous treatment experiences, and a hepatitis-C diagnosis were associated with an increased likelihood of NFOD. Current engagement in OAT was protective against NFOD. Gender, relationship status, needle exchange use, symptoms of anxiety, and being HIV positive were not strongly associated with a difference in NFOD likelihood.

Conclusion: Using the findings from above to identify the individuals who are at high risk for NFOD, particularly those using opioids, will enable a targeted approach to outreach and education programs based on the identified risk factors- such as polysubstance use, socioeconomic associations, and psychiatric co-morbidities, which can help reduce the occurrence of NFOD.

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Journal: Biological Psychiatry, 2025, doi: 10.1016/j.biopsych.2024.10.018

Authors: Tsen Vei Lim, Rudolf N. Cardinal, Hisham Ziauddeen, Ralf Regenthal, Barbara J. Sahakian, Trevor W. Robbins, & Karen D. Ersche

Abstract:

Background: Impulsivity is a well-known determinant of maladaptive behavior in cocaine use disorder (CUD), but there are currently no effective strategies for managing excessive impulsivity. Growing evidence from preclinical and clinical studies suggests that atomoxetine, a selective noradrenaline reuptake inhibitor, is effective in improving impulse control in both healthy individuals and individuals with neuropsychiatric conditions.

Methods: We investigated the effects of atomoxetine on decisional impulsivity in patients with CUD. In a randomized, double-blind, placebo-controlled, crossover study, 28 patients diagnosed with moderate-to-severe CUD and 28 matched healthy control participants completed the Cambridge Gambling Task in 2 separate sessions, where they received either placebo or a single dose of 40 mg atomoxetine at each session. Computational modeling was used to break down decision making into 3 separable components: value, probability, and decisional impulsivity.

Results: Our analyses revealed that patients with CUD were impaired in all components of decision making. Atomoxetine selectively reduced decisional impulsivity in patients with CUD by reducing their risk-seeking tendencies while enhancing their ability to tolerate delays. By contrast, atomoxetine did not affect impulsivity in control participants, but increased their sensitivity to prospective losses.

Conclusions: Taken together, our findings support the hypothesis of noradrenergic dysfunction in patients with CUD and provide novel translational evidence for the efficacy of atomoxetine in remediating decisional impulsivity in CUD

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