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Psychotic-like experiences (PLEs) are common throughout childhood, and the presence of these experiences is a significant risk factor for poor mental health later in development. Given the association of PLEs with a broad number of mental health diagnoses, these experiences serve as an important malleable target for early preventive interventions. However, little is known about these experiences across childhood. While these experiences may be common, longitudinal measurement in non-clinical settings is not. Therefore, in order to explore longitudinal trajectories of PLEs in childhood, we harmonized three school-based randomized control trials with longitudinal follow-up to identify heterogeneity in trajectories of these experiences. In an integrative data analysis (IDA) using growth mixture modeling, we identified three latent trajectory classes. One trajectory class was characterized by persistent PLEs, one was characterized by high initial probabilities but improving across the analytic period, and one was characterized by no reports of PLEs. Compared to the class without PLEs, those in the improving class were more likely to be male and have higher levels of aggressive and disruptive behavior at baseline. In addition to the substantive impact this work has on PLE research, we also discuss the methodological innovation as it relates to IDA. This IDA demonstrates the complexity of pooling data across multiple studies to estimate longitudinal mixture models.

BACKGROUND: Adverse childhood experiences (ACEs) are associated with a number of medical comorbidities. However, there is a paucity of data on the role ACEs play in transitions in stages of alcohol involvement. OBJECTIVE: To examine the association between ACEs and transitions in alcohol problems progression and regression between No Problems, Moderate Problems and Severe Problems stages. PARTICIPANTS AND SETTING: Data from 14,363 male and 19,774 female participants in Waves 1 and 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). METHODS: We used latent transition analysis (LTA) with propensity score adjustment to estimate the odds of transitioning across stages of alcohol involvement, between waves, based on the number of types of ACEs experienced. We hypothesized that ACEs would be associated with increased risk of progression and decreased risk of regression. RESULTS: ACEs were associated with progression to higher alcohol involvement stages, with greatest likelihood of progression from No Problems to Severe Problems for those reporting ≥3 ACEs (males: aOR = 4.78 [CI (1.84-12.44)]; females: aOR = 3.81 [CI (1.69-8.57)]). ACEs were also associated with decreased odds of regression to less problematic alcohol involvement stages, with some distinctive patterns of associations in males and in females. CONCLUSIONS: This study suggests that ACEs impact transitions in alcohol involvement in both males and females, affecting both progression and regression. The association is magnified for those with multiple types of ACE exposures. These results highlight the need for prevention, early identification and intervention to mitigate the risks associated with childhood maltreatment.

Aims: The aim of this study was to measure trajectories of craving for methamphetamine during the course of pharmacotherapy trials for methamphetamine use disorder. Design, setting and participants: Craving trajectories were identified using Group‐Based Trajectory Modeling. The association of craving trajectories with drug use trajectories was examined using a dual trajectory model. Association of craving trajectories with other health and social outcomes was also examined. The study used pooled data from five randomized controlled pharmacotherapy trials for methamphetamine use disorder. A total of 866 adults with methamphetamine use disorder participated in randomized controlled pharmacotherapy trials. Measurement: Craving was assessed weekly using the Brief Substance Craving Scale. Drug use was assessed using urine toxicology. Alcohol‐ and drug‐related problems, as well as psychiatric, medical, legal, employment and relationship problems, were measured using the Addiction Severity Index. Findings: A three‐trajectory model with high, medium and low craving trajectories was selected as the most parsimonious model. Craving trajectories were associated with methamphetamine use trajectories in the course of trial; 88.4% of those in the high craving trajectory group had a consistently high frequency of methamphetamine use compared with 18.7% of those in the low craving group. High craving was also associated with less improvement in most other outcomes and higher rate of dropout from treatment. In turn, low craving was associated with a rapidly decreasing frequency of methamphetamine use, greater improvement in most other outcomes and a lower rate of dropout. Participants on modafinil daily and ondansetron 1 mg twice daily were less likely to be in the high craving group compared with those on placebo. Conclusions: Trajectories of methamphetamine craving in the course of clinical trials for methamphetamine use disorder appear to be both highly variable and strongly associated with greater frequency of drug use, other drug‐related outcomes and dropout from trials. Two medications, modafinil daily and ondansetron at a dose of 1 mg two times daily, appear to be associated with greater reduction in craving in the course of treatment compared with placebo. A decrease in methamphetamine craving shows promise as an early indicator of recovery from methamphetamine use disorder. [ABSTRACT FROM AUTHOR]

Background: Alcohol use has profound public health impact on women; however, modifiable factors that may influence alcohol use progression/recovery, including health service utilization, are understudied in women. Objective: To investigate the association between mental health (MH) and substance use (SU) treatment with alcohol use progression and recovery among women who currently use alcohol or have in the past. Methods: This study is a secondary data analysis of prospective data from waves 1 (2001–2002) and 2 (2004–2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; a US-nationally representative sample of adults). The analytic sample was limited to women who reported past or current alcohol use at wave 1 (N = 15,515). Latent transition analysis (LTA) examined whether receiving SU/MH treatment in the year prior to wave 1 was associated with transitioning between three empirically-derived stages of alcohol involvement (no, moderate, and severe problems classes), between Waves 1 and 2 adjusting for possible confounders using propensity score weight. Results: Compared to White female drinkers, female drinkers who were from Black, Hispanic, or other races were less likely to receive SU/MH treatment (p-values ≤. 001). SU/MH treatment in the year prior to wave 1 was associated with transitioning from the moderate problems class to the no problems class between Waves 1 and 2 (p-value =.04). Conclusion: Receipt of SU or MH treatment among women, was associated with a higher likelihood of remission from moderate alcohol use problems to no problems over time. Future research, including investigation into treatment characteristics (e.g., frequency, duration, type) should further explore why women initially experiencing severe alcohol use problems did not experience similar remission. [ABSTRACT FROM AUTHOR]

Background and aims: Total abstinence has historically been the goal of treatment for substance use disorders; however, there is a growing recognition of the health benefits associated with reduced use as a harm reduction measure in stimulant use disorders treatment. We aimed to assess the validity of reduced stimulant use as an outcome measure in randomized controlled trials (RCTs) of pharmacological interventions for stimulant use disorder. Design: We conducted a secondary analysis of a pooled dataset of 13 RCTs. Setting and participants: Participants were individuals seeking treatment for cocaine or methamphetamine use disorders (N = 2062) in a wide range of treatment facilities in the United States. Measurements We validated reduced stimulant use against a set of clinical indicators drawn from harmonized measurements, including severity of problems caused by drug use, comorbid depression, global severity of substance use and improvement, severity of drug‐seeking behavior, craving and high‐risk behaviors, all assessed at the end of the trial, as well as follow‐up urine toxicology. A series of mixed effect regression models was conducted to validate reduction in frequency of use against no reduction in use and abstinence. Findings More participants reduced frequency of primary drug use than achieved abstinence (18.0% vs. 14.2%, respectively). Reduced use was significantly associated with decreases in craving for the primary drug [60.1%, 95% confidence interval (CI) = 54.3%–64.7%], drug seeking behaviors (41.0%, 95% CI = 36.6%–45.7%), depression severity (39.9%, 95% CI = 30.9%–48.3%), as well as multiple measures of global improvement in psychosocial functioning and severity of drug‐related problems, albeit less strongly so than abstinence. Moreover, reduced use was associated with sustained clinical benefit at follow‐up, as confirmed by negative urine tests (adjusted odds ratio compared with those with no reduction in use: 0.50, 95% CI = 0.35–0.71). Conclusion: Reduced frequency of stimulant use appears to be associated with meaningful improvement in various clinical indicators of recovery. Assessment of reduced use, in addition to abstinence, could broaden the scope of outcomes measured in randomized controlled trials of stimulant use disorders and facilitate the development of more diverse treatment approaches. [ABSTRACT FROM AUTHOR]

Involvement of opioids in suicides has doubled during the past two decades, worsening a major public health concern. This study examined the characteristics of opioid-involved suicides. The sample of decedents (N = 12,038) in Maryland between 2006 and 2020 was used to compare the characteristics of opioid-involved suicides (n = 947) with suicides not involving opioids (n = 6,896) and accidental opioid deaths (n = 4,125). Direct comparisons were then made between opioid-involved suicides with and without the additional presence of non-opioid substances. Opioid-involved suicides were significantly more likely than suicides not involving opioids to occur among those aged 18–64 years, non-Hispanic Whites, and unemployed or disabled individuals. Opioid-involved suicides were more likely than accidental opioid deaths to occur among females, those aged <18 years, non-Hispanic Whites, and employed individuals. Of all suicides involved opioids, 45% involved other non-opioid substances. Polysubstance opioid suicides were significantly more likely than suicides involving opioids only to occur among non-Hispanic Whites. Significant differences were observed in the demographic groups most at risk for opioid-involved suicide than other suicide or accidental opioid death. Among opioid-involved suicides, polysubstance involvement also represents a distinct group. These findings may enhance the targeting of prevention efforts. Opioid-involved suicides differ from other suicides or accidental opioid deaths. In opioid-involved suicides, polysubstance involvement represents a distinct group. These findings may enhance the targeting of prevention efforts. [ABSTRACT FROM AUTHOR]

Two commonly used methods for improving precision and power in clinical trials are stratified randomization and covariate adjustment. However, many trials do not fully capitalize on the combined precision gains from these two methods, which can lead to wasted resources in terms of sample size and trial duration. We derive consistency and asymptotic normality of model-robust estimators that combine these two methods, and show that these estimators can lead to substantial gains in precision and power. Our theorems cover a class of estimators that handle continuous, binary, and time-to-event outcomes; missing outcomes under the missing at random assumption are handled as well. For each estimator, we give a formula for a consistent variance estimator that is model-robust and that fully captures variance reductions from stratified randomization and covariate adjustment. Also, we give the first proof (to the best of our knowledge) of consistency and asymptotic normality of the Kaplan–Meier estimator under stratified randomization, and we derive its asymptotic variance. The above results also hold for the biased-coin covariate-adaptive design. We demonstrate our results using data from three trials of substance use disorder treatments, where the variance reduction due to stratified randomization and covariate adjustment ranges from 1% to 36%. for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. [ABSTRACT FROM AUTHOR]

Integrative data analysis (IDA) is an analytic tool that allows researchers to combine raw data across multiple, independent studies, providing an improved measurement of latent constructs as compared to single study analysis or meta-analyses. This is often achieved through the implementation of moderated non-linear factor analysis (MNLFA), an advanced modeling approach that allows for covariate moderation of item and factor parameters. The current paper provides an overview of this modeling technique, highlighting distinct advantages most apt for IDA. We further illustrate the complex model building process involved in MNLFA by providing a tutorial using empirical data from five separate prevention trials. The code and data used for analyses are also provided. [ABSTRACT FROM AUTHOR]

Background: Secondary analysis of data from completed randomized controlled trials is a critical and efficient way to maximize the potential benefits from past research. De-identified primary data from completed randomized controlled trials have been increasingly available in recent years; however, the lack of standardized data products is a major barrier to further use of these valuable data. Pre-statistical harmonization of data structure, variables, and codebooks across randomized controlled trials would facilitate secondary data analysis, including meta-analyses and comparative effectiveness studies. We describe a pre-statistical data harmonization initiative to standardize de-identified primary data from substance use disorder treatment randomized controlled trials funded by the National Institute on Drug Abuse available on the National Institute on Drug Abuse Data Share website. Methods: Standardized datasets and codebooks with consistent data structures, variable names, labels, and definitions were developed for 36 completed randomized controlled trials. Common data domains were identified to bundle data files from individual randomized controlled trials according to relevant concepts. Variables were harmonized if at least two randomized controlled trials used the same instruments. The structures of the harmonized data were determined based on the feedback from clinical trialists and substance use disorder research experts. Results: We have created a harmonized database of variables across 36 randomized controlled trials with a build-in label and a brief definition for each variable. Data files from the randomized controlled trials have been consistently categorized into eight domains (enrollment, demographics, adherence, adverse events, physical health measures, mental-behavioral-cognitive health measures, self-reported substance use measures, and biologic substance use measures). Standardized codebooks and concordance tables have also been developed to help identify instruments and variables of interest more easily. Conclusion: The harmonized data of randomized controlled trials of substance use disorder treatments can potentially promote future secondary data analysis of completed randomized controlled trials, allowing combining data from multiple randomized controlled trials and provide guidance for future randomized controlled trials in substance use disorder treatment research. [ABSTRACT FROM AUTHOR]