Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05368571 |
Other study ID # |
R01DA050670 |
Secondary ID |
|
Status |
Recruiting |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
April 8, 2022 |
Est. completion date |
March 2026 |
Study information
Verified date |
February 2024 |
Source |
Baylor University |
Contact |
Danielle E Parrish, Ph.D. |
Phone |
346-701-8047 |
Email |
danielle_parrish[@]baylor.edu |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
This randomized controlled trial will: 1) Test the efficacy of the CHOICES-TEEN (CT)
intervention compared with an Attentional Control (AC) condition on reducing the risk of
substance-exposed pregnancy (SEP) and HIV/STI among high-risk female youth involved with the
juvenile justice system by reducing alcohol use, increasing marijuana cessation, reducing
risk of pregnancy, and increasing condom use; 2) Test the efficacy of CT, compared to AC, on
increasing cognitive self-regulation abilities; 3) Test proposed intervention
mediators/mechanisms of action for CT overall and by race/ethnicity; and 4) Test the
moderating effect of initial readiness to change on risk of SEP and risk of HIV/STI.
Description:
This CHOICES-TEEN intervention study will use a Phase II Behavioral Treatment Trial to employ
a single blind randomized design with an attention control (AC) group to assess the efficacy
of the CHOICES-TEEN intervention. Young women, 14-19 years of age, entering the Harris County
Juvenile Probation (HCJP) system's probation and field diversion and community probation
program will be eligible for screening into the study. The investigators anticipate
recruiting N=435 with 92% retention based on prior experience, yielding a total sample size
of N=400, stratified by program, with 200 randomized to the CHOICES-TEEN intervention (plus
Standard Care; CT) or the Attention only group (AC) using urn randomization. Both groups will
be assessed at 3-, 6- and 9-month follow up. Eligibility will be determined based on the
following inclusion/exclusion information. This efficacy trial will: (1) Test the efficacy of
CHOICES-TEEN (CT) compared with attentional control (AC) on reducing the risk of
substance-exposed pregnancy (SEP) and HIV/STI among high-risk female youth involved with the
juvenile justice system by reducing alcohol use, increasing marijuana cessation, reducing
pregnancy risk, and increasing condom use; (2) Test the efficacy of CT, compared to an
attentional control condition, in increasing cognitive self-regulation abilities; (3) Test
proposed intervention mediators/mechanisms of action for CT overall and by race/ethnicity;
and (4) Test the moderating effect of initial readiness to change on risk of SEP and risk of
HIV/STI.
Female adolescents between the ages of 14-19 will be recruited for eligibility screening from
the aforementioned community probation program. Voluntarily referred youth will be screened
for eligibility in the study after obtaining parental permission and youth assent. All youth
enrolled in the study must be identified as being at risk for substance-exposed pregnancy and
HIV/STI. Eligible youth who provide written informed consent (and parents who provide written
permission) will then be randomized to the CHOICES-TEEN intervention or the Attentional
Control Condition.
The investigators anticipate recruiting N=435 with 92% retention based on prior experience
with similar studies, yielding a final sample size for analyses of N=400. Randomization,
stratified by program, will result in n=200 participants per condition with participants
clustered within k=4 forensic programs. Investigators assume a conservative ICC =0.20 due to
clustering. Absolute risk reductions in risk of SEP range from 14.8% to 25.1% based on
Project CHOICES, Project CHOICES Plus and our pilot CHOICES-TEEN. For the purposes of sample
size justification, investigators will assume N=435 randomized in 1:1 fashion (minimum 400
completers), stratified by program, and ICC = 0.20 and a conservative estimate of an ARR=15%
for reduced risk of SEP and HIV/STI. Finally, investigators stipulate that if the posterior
probability that there is an effect of treatment (Odd Ratio>1.0) is greater than 0.75 and
that the median treatment effect estimate exceeds an Odds Ratio=1.5, this constitutes
sufficient evidence to warrant subsequent investigation. M=1000 Monte Carlo simulations,
using a normal approximation to the posterior indicates that under the preceding assumptions
the proposed design will identify an effect of treatment 81.9% of the time.
Data analyses. The data analytic strategy will use generalized linear mixed and structural
equation modeling (SAS 9.4, R v. 3.4, Stan,v. 2.17 and MPlus v. 8.3) for both continuous and
discrete outcomes. All analyses will be conducted on an intention-to-treat basis. To address
missingness, Bayesian approaches will implement joint modeling of observed outcomes and the
missing data which is robust to ignorable missingness (i.e., MCAR and MAR). Sensitivity
analyses will evaluate robustness of analytic conclusions to missing data. Non-ignorable
missing data patterns (i.e., MNAR) will be addressed through pattern-mixture modeling
methods.Specification of diffuse, neutral priors will reflect the initial uncertainty
regarding effect sizes. For all generalized linear mixed models, priors for regression
coefficients will be specified as ~Normal (µ=0, σ2=1 x 106) (for non-normal outcomes this
refers to the prior for the coefficient within the link function), level one error variances
will be specified as ~Inverse Gamma (shape=0.001, scale=0.001). Choice of prior distribution
for level two variances will follow Gelman's recommendations. Bayesian Structural Equation
Modeling (BSEM) prior specification will adapt recommendations from Muthén and Asparouhov
230. Priors for the comparison of proportions will be specified as ~Beta (α=0.5, β=0.5).
Similar procedures will be used in secondary analyses to investigate subgroups of youth using
specific substances (i.e. alcohol and marijuana), as well as intervention effects as a
function of baseline readiness to change as a potential moderator. Mediational modeling will
examine the degree to which putative mechanisms of behavioral change transmit the effects of
the intervention on the specified outcomes. BSEM will investigate mediation of treatment
effects due to CT on SEP and HIV/STI risk at 9 months by hypothesized mechanisms (processes
of change, cognitive self-regulation, and confidence and temptation) measured at 3 months
utilizing MPlus v. 8.3. Examination of the posterior distribution of the indirect effects
will evaluate the probability that mediational effects exist.
Specific Data Analyses - Hypothesis 1: CT, compared to Attentional Control (AC) AC will be
associated with reduced risk of SEP and HIV/STI at 9-months post intake. The primary outcome
is reduced risk of SEP and HIV/STI at 9 months, however at each time point (3-, 6-, and
9-month) multilevel logistic models will evaluate the risk of SEP and HIV/STI as a function
of treatment condition while addressing clustering due to forensic program assignment. At
each time point generalized linear multilevel models will evaluate the presence/absence of
risk drinking, presence/absence of marijuana use, presence/absence of vaginal intercourse
without effective contraception, and presence/absence of vaginal or anal intercourse without
condom use as a function of treatment condition while addressing clustering due to forensic
program assignment.
Hypothesis 2: Compared to AC, CT will improve cognitive self-regulation abilities at 3-, 6-,
and 9-month post intake as measured by self-report self-regulation measures. At each time
point (3- and 9-month) generalized multilevel linear models will evaluate self-regulation as
a function of treatment condition while addressing clustering due to forensic program
assignment.
Hypothesis 3: The processes of change, confidence and temptation, and cognitive self-
regulation, for each risk behavior at 3-months will mediate the effect of treatment on SEP
risk and HIV/STI risk at 9-months post intake for CT. Multilevel Bayesian structural equation
modeling (M-BSEM) will evaluate the degree to which processes of change, cognitive
self-regulation, confidence and temptation measured at 3 months follow-up mediate the effect
of treatment on SEP and HIV/STI risk at 9 month follow-up. Multilevel elements will address
clustering as a function of forensic program assignment. Multigroup analyses testing the
mediation models will find invariance between Non-Hispanic Black, Hispanic, and Non-Hispanic
White.
Hypothesis 4: Female youth with low baseline readiness to change risk behavior will have less
risk of SEP and HIV/STI at 3-, 6- and 9-months post intake in the CT intervention condition,
designed to increase motivation and goal striving, than female youth with low baseline
readiness to change risk behavior in the AC condition. At each time point (3-, 6-, and
9-month) multilevel logistic models will evaluate the risk of SEP and HIV/STI as a function
of treatment condition, baseline readiness and the interaction of treatment and baseline
readiness. These models will use the approach advocated by Simon and Dixon.
Sample Size. The investigators anticipate recruiting N=435 with 92% retention based on our
experience with Project CHOICES, CHOICES Plus, and CP-T yielding a final sample size for
analyses of N=400. Randomization, stratified by program, will result in n=200 participants
per condition with participants clustered within k=4 forensic program assignments.
Investigators assume a conservative ICC = 0.20 due to clustering. Absolute risk reductions in
risk of SEP range from 14.8% to 25.1% based on Project CHOICES, Project CHOICES Plus and our
pilot CHOICES-TEEN. For the purposes of sample size justification, investigators will assume
N=435 randomized in 1:1 fashion (minimum 400 completers), stratified by program, and ICC =
0.20 and a conservative estimate of an ARR=15% for reduced risk of SEP and HIV/STI. Finally,
investigators stipulate that if the posterior probability that there is an effect of
treatment (Odd Ratio>1.0) is greater than 0.75 and that the median treatment effect estimate
exceeds an Odds Ratio=1.5, this constitutes sufficient evidence to warrant subsequent
investigation. M=1000 Monte Carlo simulations, using a normal approximation to the posterior
indicates that under the preceding assumptions the proposed design will identify an effect of
treatment 81.9% of the time.