31 research outputs found
Cocaine Use Prediction with Tensor-based Machine Learning on Multimodal MRI Connectome Data
This paper considers the use of machine learning algorithms for predicting
cocaine use based on magnetic resonance imaging (MRI) connectomic data. The
study utilized functional MRI (fMRI) and diffusion MRI (dMRI) data collected
from 275 individuals, which was then parcellated into 246 regions of interest
(ROIs) using the Brainnetome atlas. After data preprocessing, the datasets were
transformed into tensor form. We developed a tensor-based unsupervised machine
learning algorithm to reduce the size of the data tensor from
(individuals) (fMRI and dMRI) (ROIs)
(ROIs) to (individuals) (fMRI and dMRI) (clusters)
(clusters). This was achieved by applying the high-order Lloyd
algorithm to group the ROI data into 6 clusters. Features were extracted from
the reduced tensor and combined with demographic features (age, gender, race,
and HIV status). The resulting dataset was used to train a Catboost model using
subsampling and nested cross-validation techniques, which achieved a prediction
accuracy of 0.857 for identifying cocaine users. The model was also compared
with other models, and the feature importance of the model was presented.
Overall, this study highlights the potential for using tensor-based machine
learning algorithms to predict cocaine use based on MRI connectomic data and
presents a promising approach for identifying individuals at risk of substance
abuse
A CBT-based mobile intervention as an adjunct treatment for adolescents with symptoms of depression: a virtual randomized controlled feasibility trial
BackgroundHigh rates of adolescent depression demand for more effective, accessible treatment options. A virtual randomized controlled trial was used to assess the feasibility and acceptability of a 5-week, self-guided, cognitive behavioral therapy (CBT)-based mobile application, Spark, compared to a psychoeducational mobile application (Active Control) as an adjunct treatment for adolescents with depression during the COVID-19 pandemic.MethodsA community sample aged 13–21, with self-reported symptoms of depression, was recruited nationwide. Participants were randomly assigned to use either Spark or Active Control (NSpark = 35; NActive Control = 25). Questionnaires, including the PHQ-8 measuring depression symptoms, completed before, during, and immediately following completion of the intervention, evaluated depressive symptoms, usability, engagement, and participant safety. App engagement data were also analyzed.Results60 eligible adolescents (female = 47) were enrolled in 2 months. 35.6% of those expressing interest were consented and all enrolled. Study retention was high (85%). Spark users rated the app as usable (System Usability Scalemean = 80.67) and engaging (User Engagement Scale-Short Formmean = 3.62). Median daily use was 29%, and 23% completed all levels. There was a significant negative relationship between behavioral activations completed and change in PHQ-8. Efficacy analyses revealed a significant main effect of time, F = 40.60, p < .001, associated with decreased PHQ-8 scores over time. There was no significant Group × Time interaction (F = 0.13, p = .72) though the numeric decrease in PHQ-8 was greater for Spark (4.69 vs. 3.56). No serious adverse events or adverse device effects were reported for Spark users. Two serious adverse events reported in the Active Control group were addressed per our safety protocol.ConclusionRecruitment, enrollment, and retention rates demonstrated study feasibility by being comparable or better than other mental health apps. Spark was highly acceptable relative to published norms. The study's novel safety protocol efficiently detected and managed adverse events. The lack of significant difference in depression symptom reduction between Spark and Active Control may be explained by study design and study design factors. Procedures established during this feasibility study will be leveraged for subsequent powered clinical trials evaluating app efficacy and safety.Clinical Trial Registrationhttps://clinicaltrials.gov/ct2/show/NCT0452459
Assessing the Efficacy and Safety of a Digital Therapeutic for Symptoms of Depression in Adolescents: Protocol for a Randomized Controlled Trial
BackgroundDepression is a serious, prevalent, recurrent, and undertreated disorder in adolescents. Low levels of treatment seeking and treatment adherence in this age group, combined with a growing national crisis in access to mental health care, have increased efforts to identify effective treatment alternatives for this demographic. Digital health interventions for mental illness can provide cost-effective, engaging, and accessible means of delivering psychotherapy to adolescents.
ObjectiveThis protocol describes a virtual randomized controlled trial designed to evaluate the efficacy and safety of a self-guided, mobile app–based implementation of behavioral activation therapy, SparkRx, for the adjunct treatment of symptoms of depression in adolescents.
MethodsParticipants are recruited directly through web-based and print advertisements. Following eligibility screening and consenting, participants are randomly assigned to a treatment arm (SparkRx) or a control arm (assessment-enhanced usual care) for 5 weeks. The primary efficacy outcome, total score on the 8-item Patient Health Questionnaire (PHQ-8), is assessed at the end of the 5-week intervention period. Additional participant-reported outcomes are assessed at baseline, the postintervention time point, and 1-month follow-up. The safety of the intervention is assessed by participant report (and legal guardian report, if the participant is younger than 18 years) and by patterns of symptom deterioration on the PHQ-8, as part of a larger clinical safety monitoring protocol. The primary efficacy outcome, total PHQ-8 score at the postintervention time point, will be compared between SparkRx and enhanced usual care arms using mixed effect modeling, with baseline PHQ-8 and current antidepressant medication status included as covariates. Secondary efficacy outcomes, including the proportion of participants exhibiting treatment response, remission, and minimal clinically significant improvement (all derived from total PHQ-8 scores), will be compared between groups using chi-square tests. Symptom severity at 1-month follow-up will also be compared between arms. Planned subgroup analyses will examine the robustness of treatment effects to differences in baseline symptom severity (PHQ-8 score <15 or ≥ 15) and age (younger than 18 years and older than 18 years). The primary safety outcome, the number of psychiatric serious adverse events, will be compared between trial arms using the Fisher exact test. All other adverse events will be presented descriptively.
ResultsAs of May 2023, enrollment into the study has concluded; 223 participants were randomized. The analysis of the efficacy and safety data is expected to be completed by Fall 2023.
ConclusionsWe hypothesize that the results of this trial will support the efficacy and safety of SparkRx in attenuating symptoms of depression in adolescents. Positive results would more broadly support the prospect of using accessible, scientifically validated, digital therapeutics in the adjunct treatment of mental health disorders in this age range.
Trial RegistrationClinicalTrials.gov NCT05462652; https://clinicaltrials.gov/study/NCT05462652
International Registered Report Identifier (IRRID)DERR1-10.2196/4874
Healthcare workers’ attitudes on mandates, incentives, and strategies to improve COVID-19 vaccine uptake: A mixed methods study
Healthcare workers are a trusted health information source and are uniquely positioned to reduce the burden of the COVID-19 pandemic. The purpose of this sequential exploratory mixed methods study was to understand attitudes of healthcare workers working in Massachusetts during the COVID-19 pandemic regarding strategies to improve COVID-19 vaccine utilization, including vaccine mandates and incentives. Fifty-two individuals completed one-on-one interviews between April 22nd and September 7th, 2021. The survey was developed based on findings from the interviews; 209 individuals completed the online survey between February 17th and March 23rd, 2022. Both the interview and survey asked about attitudes toward COVID-19 vaccine and booster mandates, incentives, and strategies to improve vaccination rates. Most participants were female (79%-interview, 81%-survey), Caucasian (56%, 73%), and worked as physicians (37%, 34%) or nurses (10%, 18%). Overall, nuanced attitudes regarding vaccine and booster mandates were expressed; many supported mandates to protect their patients’ health, others emphasized personal autonomy, while some were against mandates if job termination was the consequence of declining vaccines. Similarly, views regarding vaccine incentives differed; some considered incentives helpful, yet many viewed them as coercive. Strategies believed to be most effective to encourage vaccination included improving accessibility to vaccination sites, addressing misinformation, discussing vaccine safety, tailored community outreach via trusted messengers, and one-on-one conversations between patients and healthcare workers. Healthcare workers’ experiences with strategies to improve utilization of COVID-19 vaccines and boosters have implications for public health policies. Generally, efforts to improve access and education were viewed more favorably than incentives and mandates
Traditional Femininity Versus Strong Black Women Ideologies and Stress Among Black Women
High Versus Low Level of Response to Alcohol: Evidence of Differential Reactivity to Emotional Stimuli
Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study
Sieve analysis of breakthrough HIV-1 sequences in HVTN 505 identifies vaccine pressure targeting the CD4 binding site of Env-gp120.
Although the HVTN 505 DNA/recombinant adenovirus type 5 vector HIV-1 vaccine trial showed no overall efficacy, analysis of breakthrough HIV-1 sequences in participants can help determine whether vaccine-induced immune responses impacted viruses that caused infection. We analyzed 480 HIV-1 genomes sampled from 27 vaccine and 20 placebo recipients and found that intra-host HIV-1 diversity was significantly lower in vaccine recipients (P ≤ 0.04, Q-values ≤ 0.09) in Gag, Pol, Vif and envelope glycoprotein gp120 (Env-gp120). Furthermore, Env-gp120 sequences from vaccine recipients were significantly more distant from the subtype B vaccine insert than sequences from placebo recipients (P = 0.01, Q-value = 0.12). These vaccine effects were associated with signatures mapping to CD4 binding site and CD4-induced monoclonal antibody footprints. These results suggest either (i) no vaccine efficacy to block acquisition of any viral genotype but vaccine-accelerated Env evolution post-acquisition; or (ii) vaccine efficacy against HIV-1s with Env sequences closest to the vaccine insert combined with increased acquisition due to other factors, potentially including the vaccine vector