Methods to reduce the incidence of false negative trial results in substance use treatment research

Identifying brief intervention factors to improve cannabis related outcomes in adolescents and young adults: A systematic review of sample characteristics and intervention components

INTRODUCTION

Prior systematic and meta-analytic reviews observed mixed evidence for the efficacy of cannabis brief interventions (BIs). Inconsistent support for cannabis BIs may be the result of intersecting methodological factors, including intervention structure and content, participant eligibility criteria, and outcome assessment measures. The current systematic review of cannabis BI studies narratively synthesizes these data to guide intervention development decision-making in future cannabis BI studies (PROSPERO CRD42022285990).

METHODS

We searched PubMed/MEDLINE, PsycINFO, and CINAHL databases in January 2022 and again in June 2023 to capture newly published studies. Studies were included if they were a randomized trial, enrolled adolescents (13-17) and/or young adults (18-30), specified cannabis use and/or problems inclusion criteria, and evaluated a cannabis BI (defined as ≤4 sessions). We extracted and synthesized data on intervention characteristics (e.g., components, length/duration, modality), cannabis inclusion criteria and recruitment setting, baseline cannabis use descriptives and treatment-seeking status, and outcome assessment measures to discern if/how they may intersect to determine intervention efficacy. The Cochrane Risk of Bias Tool 2 assessed study quality.

RESULTS

Our search resulted in a final sample of 25 study records including 4094 participants. Recruitment setting seemed to provide an influential backdrop for how well inclusion criteria determined baseline cannabis use level, as well as for the type/length of the BI evaluated. Motivational interviewing (MI) and personalized feedback (PF) were the most frequently used BI components overall; however, some differences were observed in the proportion of BIs with reported intervention effects using MI vs. PF. Frequency of use days was the most commonly used outcome measure, although this may not be the most sensitive measure for assessing cannabis BI efficacy.

CONCLUSIONS

Our systematic review indicates that cannabis BI studies require greater precision in their design, giving special attention to matching the content and structure of the BI to the needs of the target population and selecting outcomes commensurate to the goals of the BI and the target population to more accurately reflect the efficacy of the BI. However, consistent with prior reviews, all included studies demonstrated at least some concerns for risk of bias, and most were at high risk.

Alcohol and Cannabis Use and the Developing Brain

PURPOSE

Alcohol and cannabis are the most commonly used substances during adolescence and are typically initiated during this sensitive neurodevelopmental period. The aim of this review is to provide a comprehensive overview of the most recent literature focused on understanding how these substances affect the developing brain.

SEARCH METHODS

Articles included in this review were identified by entering 30 search terms focused on substance use, adolescence, and neurodevelopment into MEDLINE, Embase, PsycINFO, ProQuest Central, and Web of Science. Studies were eligible for inclusion if they longitudinally examined the effect of adolescent alcohol and/or cannabis use on structural or functional outcomes in 50 or more participants.

SEARCH RESULTS

More than 700 articles were captured by the search, and 43 longitudinal studies met inclusion criteria, including 18 studies focused on alcohol use, 13 on cannabis use, and 12 on alcohol and cannabis co-use.

DISCUSSION AND CONCLUSIONS

Existing studies suggest heavy alcohol and cannabis use during adolescence are related to small to moderate disruptions in brain structure and function, as well as neurocognitive impairment. The effects of alcohol use include widespread decreases in gray matter volume and cortical thickness across time; slowed white matter growth and poorer integrity; disrupted network efficiency; and poorer impulse and attentional control, learning, memory, visuospatial processing, and psychomotor speed. The severity of some effects is dependent on dose. Heavy to very heavy cannabis use is associated with decreased subcortical volume and increased frontoparietal cortical thickness, disrupted functional development, and decreased executive functioning and IQ compared to non-using controls. Overall, co-use findings suggest more pronounced effects related to alcohol use than to cannabis use. Several limitations exist in the literature. Sample sizes are relatively small and demographically homogenous, with significant heterogeneity in substance use patterns and methodologies across studies. More research is needed to clarify how substance dosing and interactions between substances, as well as sociodemographic and environmental factors, affect outcomes. Larger longitudinal studies, already underway, will help clarify the relationship between brain development and substance use.

Digitally Enabled, Patient-Centric Clinical Trials: Shifting the Drug Development Paradigm

The rapidly advancing field of digital health technologies provides a great opportunity to radically transform the way clinical trials are conducted and to shift the clinical trial paradigm from a site-centric to a patient-centric model. Merck's (Kenilworth, NJ) digitally enabled clinical trial initiative is focused on introduction of digital technologies into the clinical trial paradigm to reduce patient burden, improve drug adherence, provide a means of more closely engaging with the patient, and enable higher quality, faster, and more frequent data collection. This paper will describe the following four key areas of focus from Merck's digitally enabled clinical trials initiative, along with corresponding enabling technologies: (i) use of technologies that can monitor and improve drug adherence (smart dosing), (ii) collection of pharmacokinetic (PK), pharmacodynamic (PD), and biomarker samples in an outpatient setting (patient-centric sampling), (iii) use of digital devices to collect and measure physiological and behavioral data (digital biomarkers), and (iv) use of data platforms that integrate digital data streams, visualize data in real-time, and provide a means of greater patient engagement during the trial (digital platform). Furthermore, this paper will discuss the synergistic power in implementation of these approaches jointly within a trial to enable better understanding of adherence, safety, efficacy, PK, PD, and corresponding exposure-response relationships of investigational therapies as well as reduced patient burden for clinical trial participation. Obstacle and challenges to adoption and full realization of the vision of patient-centric, digitally enabled trials will also be discussed.

Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology

Background

While there have been many technological advances in studying the neurobiological and clinical basis of tobacco use disorder and nicotine addiction, there have been relatively minor advances in technologies for monitoring, characterizing, and intervening to prevent smoking in real time. Better understanding of real-time smoking behavior can be helpful in numerous applications without the burden and recall bias associated with self-report.

Objective

The goal of this study was to test the validity of using a smartwatch to advance the study of temporal patterns and characteristics of smoking in a controlled laboratory setting prior to its implementation in situ. Specifically, the aim was to compare smoking characteristics recorded by Automated Smoking PerceptIon and REcording (ASPIRE) on a smartwatch with the pocket Clinical Research Support System (CReSS) topography device, using video observation as the gold standard.

Methods

Adult smokers (N=27) engaged in a video-recorded laboratory smoking task using the pocket CReSS while also wearing a Polar M600 smartwatch. In-house software, ASPIRE, was used to record accelerometer data to identify the duration of puffs and interpuff intervals (IPIs). The recorded sessions from CReSS and ASPIRE were manually annotated to assess smoking topography. Agreement between CReSS-recorded and ASPIRE-recorded smoking behavior was compared.

Results

ASPIRE produced more consistent number of puffs and IPI durations relative to CReSS, when comparing both methods to visual puff count. In addition, CReSS recordings reported many implausible measurements in the order of milliseconds. After filtering implausible data recorded from CReSS, ASPIRE and CReSS produced consistent results for puff duration (R²=.79) and IPIs (R²=.73).

Conclusions

Agreement between ASPIRE and other indicators of smoking characteristics was high, suggesting that the use of ASPIRE is a viable method of passively characterizing smoking behavior. Moreover, ASPIRE was more accurate than CReSS for measuring puffs and IPIs. Results from this study provide the foundation for future utilization of ASPIRE to passively and accurately monitor and quantify smoking behavior in situ.

Remote Methods for Conducting Tobacco-Focused Clinical Trials

Most tobacco-focused clinical trials are based on locally conducted studies that face significant challenges to implementation and successful execution. These challenges include the need for large, diverse, yet still representative study samples. This often means a protracted, costly, and inefficient recruitment process. Multisite clinical trials can overcome some of these hurdles but incur their own unique challenges. With recent advances in mobile health and digital technologies, there is now a promising alternative: Remote Trials. These trials are led and coordinated by a local investigative team, but are based remotely, within a given community, state, or even nation. The remote approach affords many of the benefits of multisite trials (more efficient recruitment of larger study samples) without the same barriers (cost, multisite management, and regulatory hurdles). The Coronavirus Disease 2019 (COVID-19) global health pandemic has resulted in rapid requirements to shift ongoing clinical trials to remote delivery and assessment platforms, making methods for the conduct of remote trials even more timely. The purpose of the present review is to provide an overview of available methods for the conduct of remote tobacco-focused clinical trials as well as illustrative examples of how these methods have been implemented across recently completed and ongoing tobacco studies. We focus on key aspects of the clinical trial pipeline including remote: (1) study recruitment and screening, (2) informed consent, (3) assessment, (4) biomarker collection, and (5) medication adherence monitoring. Implications With recent advances in mobile health and digital technologies, remote trials now offer a promising alternative to traditional in-person clinical trials. Remote trials afford expedient recruitment of large, demographically representative study samples, without undo burden to a research team. The present review provides an overview of available methods for the conduct of remote tobacco-focused clinical trials across key aspects of the clinical trial pipeline.

The development of patient-centric sampling as an enabling technology for clinical trials

Accessing patient samples using a whenever/wherever paradigm is needed to enable a better understanding of human biology and disease. The technology for convenient self-collection of blood samples by patients at home is quickly becoming available. The potential benefits of patient-centric sampling far outweigh the short-term challenges associated with implementation of this disruptive approach. This is especially true given we are amid a global pandemic and enabling patients to sample at home would help not only clinical trials, but healthcare in general. This perspective article aims to convince the reader that patient-centric sampling is a reality and that we are on the cusp of an information revolution in clinical trials that will be enabled by patient-centric (e.g., at home) sampling.