Sustainable HIV Risk Reduction Strategies for Criminal Justice (CJ) Systems
Phase: NA
Conditions: Health Behavior
Sponsor: Texas Christian University

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Sustainable HIV Risk Reduction Strategies for Probationers (DRR2) 
NCT #02777086 
April 8, 2020 
 
 

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We developed a multi-session, brief tablet app, StaySafe, designed to improve decision 
making around health risk behaviors for people under community supervision who had 
substance use disorders. As part of a randomized clinical trial testing post-treatment outcomes 
hypothesized to be associated with StaySafe administration, this study examines improvements 
in decision-making skills associated with reductions in health risk behaviors, especially those 
involving HIV and Hepatitis B or C (for more detail on StaySafe development and the research 
protocol, refer to Lehman et al., 2018).  
1.1  Decision-making and Analytically-created Schemas 
StaySafe is based on cognitive processing models derived from Analytically-Created 
Schemas (ACS) and TCU Mapping Enhanced Counseling (MEC; Dansereau, 2005; Dansereau 
& Simpson, 2009) that include experiential and analytic systems (Kahneman, 2011; Klacynski, 
2005). Experiential systems reference previous experiences (Kahneman, 2011; Weber & 
Johnson, 2009) believed to be used in making decisions about risk behaviors because they are 
rapid and refer to familiar behaviors, even those with negative outcomes. Analytic systems are 
typically slower because they often require conscious referencing and reinforcement. Schemas 
using the analytic system are created through repetition and practice.  
The ACS approach can be a vehicle for organizing information through a series of steps and 
exercises that develop analytic thinking. Exhibiting options visually when developing plans and 
making decisions can contribute to an objective evaluation of available choices (Dansereau et 
al., 2013).  This can help individuals monitor and control decision making (metacognition), 
increase knowledge in specific areas (e.g., substance use, treatment initiation, etc.), and 
improve judgment and behavioral choices (self-regulation). Analytic repetition (similar to practice 
in athletic training) can develop procedural memory (i.e., skills and tasks that can be stored in 
long-term memory) that can be accessed rapidly. This process, developed by repetition, can 
then be used in real-life contexts rather than the more labor-intensive analytic processing. The 
goal of the StaySafe intervention is to replace or “override” inaccurate or maladaptive 

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information, expectations, and behavior patterns with accurate health-related information and 
appropriate attitudes and behavioral choices.  
1.2  WaySafe 
The ACS-based tablet app that is used in this study grew out of an NIH-funded disease risk 
reduction study of WaySafe, a group-based curriculum that used an ACS approach to help 
people in prison-based substance use treatment make better decisions around health risk 
behaviors when they return to the community. The highly interactive curriculum relies on MEC to 
prepare individuals for the transition back to the community by demonstrating interrelationships 
among constructs including problem recognition, commitment to change, and strategies for 
avoiding behavioral health risks; key information for developing plans to address risky 
situations. Research has shown that, when compared to standard practice (SP), participants 
randomly assigned to WaySafe groups had greater improvements on knowledge and 
confidence measures related to HIV information and testing, avoiding risky sex and substance 
use, and risk reduction skills (Joe et al., 2019, Lehman et al., 2015, Lehman et al., 2019). 
1.3  WORKIT 
WORKIT, a major component of StaySafe, is a specific ACS schema that teaches a 
simplified structure for analyzing problems, weighing and rating options to make a decision, and 
then planning how to carry out that decision -- What is the problem; Who is affected by the 
problem; Who can help with the problem; Options for dealing with the problem; Rating the 
options; Knowing what to do based on the ratings; Imagining steps to carry out the decision; 
and then Testing those steps. Several studies using WORKIT have shown improved decision 
making, self-awareness, and problem recognition (Becan et al., 2015; Knight et al., 2015, 2016).  
1.4  StaySafe 
StaySafe was developed as a self-administered Android app for people participating in 
treatment while under community supervision, targeting decision-making skills to reduce health 
risk behaviors. Based on WaySafe, StaySafe uses the WORKIT ACS with accompanying health 

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information facts to train users in making more systematic and informed decisions (Lehman et 
al., 2018). The intervention includes 12 weekly sessions for participants to learn the WORKIT 
ACS through systematic repetition. 
1.5  Research goals 
A randomized clinical trial was conducted to address three primary research goals around 
the StaySafe app: 1) examination of the participation rates of StaySafe sessions, 2) test of the 
effect of StaySafe on knowledge, confidence and motivation around health risk behaviors and 
better decision-making skills, and 3) assessment of the relationship between greater StaySafe 
participation and greater pre-post change from baseline to follow-up time points.  
2.  Methods 
2.1  StaySafe intervention  
StaySafe includes 12 brief (10 minutes) self-administered sessions on a tablet; one session 
per week. Nine of the sessions involve the WORKIT ACS and three Participant Choice sessions 
include several information-based activities around HIV and health risks.  
The first StaySafe session presents the participant with an overview of how to navigate 
through the StaySafe app, followed by a demonstration of a WORKIT exercise. Those sessions 
featuring WORKIT start with choosing from a list of 11 problem themes related to (1) people 
(e.g., “Asking a partner about his or her HIV testing”), (2) places (“Favorite high-risk places to 
hang out”) or (3) things (“Practicing safe sex”). Topics were designed to be relevant for people 
under community supervision with substance use disorders, incorporating feedback from 
probation officers, substance use treatment counselors, and recommendations from the Center 
for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) on 
reducing health risks.  
After choosing a topic (What is the problem?), the participant views a vignette showing 
actors working through a risky situation (vicarious learning), prior to proceeding through the rest 
of the WORKIT steps. Some of the WORKIT steps involve selecting from a list of possible 

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responses to questions such as “Who is affected by the decision?” or “Who can help with the 
problem?”  For the WORKIT step, “Options for dealing with the problem,” participants select 
from a series of four options that are related to the chosen topic. For example, two of the 
options for the problem theme, “It’s hard to ask a partner about his or her HIV testing,” are 
“Don’t ask, but always use condoms,” and “Have unprotected sex just this one time.” Supporting 
health facts for each option “pop up” on the screen, thus providing educational information 
embedded within the decision-making schema. Mental practice such as this is deemed to help 
prepare the participant for using the WORKIT schema in the “real world” and therefore an 
effective way to learn (Cooper et al., 2001). The goal is not to have the participant solve specific 
problems during sessions, but through repeated practice using relevant examples across 
multiple StaySafe sessions, to internalize the schema. A final activity in the WORKIT sessions is 
a “maze” game in which an animated character moves around a maze as participants 
responded to quiz questions designed to reinforce information from the session. 
Participant choice sessions are interspersed among the WORKIT sessions in order to 
provide more in-depth information about HIV and health risks and to vary the tablet 
presentations. Three different activities were offered including (1) a CDC video giving 
information about HIV/AIDS, (2) an information page about HIV/AIDS with a brief discussion 
about HIV medication therapy or someone affected by HIV/AIDS talking about their experience, 
and (3) the maze game with additional question content. Participants chose one or more of the 
activities. 
2.2  Procedures 
The study took place at five community supervision and corrections department (CSCD) 
facilities in three large counties in Texas; these included two CSCD community-based locations 
and three residential facilities. In the community-based facilities, recruiting materials included 
flyers, posters, and brief presentations at the beginning or end of orientation or group sessions; 
additionally, the research team spoke with individuals in CSCD waiting rooms about the study 

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opportunity. All recruiting was conducted by TCU researchers. At the CSCD residential facilities, 
researchers provided a brief overview of the study to groups of new client admissions within a 
week of their arrival into the substance use treatment program. Those interested in participating 
completed TCU IRB-approved informed consent and brief demographic forms. Participants 
completed baseline surveys the following week according to individual community supervision 
schedules. Community-based site participants also provided contact information for receiving 
meeting reminders about study data collection appointments. Participants were randomized into 
study conditions (i.e., StaySafe and SP arms) following completion of the baseline survey 
packet. The project utilized a permuted block randomization approach, with block size varying 
randomly between 2, 4 or 6.  
2.2.1  Data Collection. Sources of data used for the project included surveys and tablet data. 
Participants in both conditions completed surveys, and those in the StaySafe condition also 
contributed tablet data. In community facilities, researchers coordinated survey administration 
and tablet sessions with participants on the same day as their required community supervision 
activities (e.g., treatment groups and meetings with counselor or probation officer [PO)]. A 
subset of individuals in the StaySafe arm who had completed at least six tablet sessions were 
also invited to interview with a senior member of the research team about the StaySafe 
experience. Qualitative results are reported in Pankow et al. (2019). For those in the community 
locations, participants were handed a scheduling card with the date/time of the next study 
activity and a contact number for the researcher in case of scheduling conflicts. In residential 
facilities, scheduling was coordinated with program staff who provided the researcher with a list 
of available time slots when participants were free to complete study activities.  
2.2.2  StaySafe sessions. The 12-session StaySafe intervention was designed to be 
administered one session per week for 12-weeks post consent. In cases where a participant 
missed a week, two sessions were administered in a single week. Sessions were completed on 
a hand-held Android tablet, and participants were provided with headphones to listen as a 

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narrator relayed the content of each tablet screen. Researchers utilized a tracking system 
(developed for the study) to coordinate data collection and manage the history of completed 
activities. Participant survey and tablet session data were linked by a study identification 
number; no identifiable information was recorded on the data sources.   
2.3  Data collection and measures  
Paper and pencil surveys were administered at baseline prior to random assignment and 
again three months after baseline. Outcome measures included the TCU Confidence & 
Motivation scales, and three decision-making scales – Rational decision-making, Dependent 
decision-making, and the TCU Decision-making scale. The surveys also included demographic 
and background measures from the TCU A-RSK form (IBR, 2008). Variables included age, 
gender, race/ethnicity, education, marital status, and in the last six months before entering their 
current program – employment, public assistance, arrested, on parole or probation, in jail or 
prison, and treatment in an emergency room, for mental health, alcohol use, and illegal 
substance use.  
2.3.1  TCU Knowledge, Confidence, and Motivation scales (KCM). Four scales included HIV 
Knowledge Confidence, Avoiding Risky Sex, HIV Services & Testing, and Risk Reduction Skills. 
Each of the scales, except for HIV Services & Testing, included items that assessed how 
knowledgeable (K) the participant felt about the topic, how confident (C) they were about their 
knowledge, and how motivated (M) they were to act on the knowledge. HIV Services & Testing 
only included knowledge and motivation items (Lehman et al., 2015). The knowledge, 
confidence, and motivation components for each scale were included in an overall score as well 
as examined as separate subscales. 
The TCU HIV Knowledge Confidence scale has 13 items (alpha = .93) and sample items 
include “You know enough to teach others what they should do if they think they have been 
exposed to HIV” (K), “You feel very confident that you could be a role model for others in 
helping reduce HIV risks” (C), and “You are totally committed to helping your friends and/or 

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family avoid HIV/AIDS” (M). Coefficient alpha reliabilities for the three subscales ranged from 
.75 to .88. The TCU Avoiding Risky Sex scale has 13 items (alpha = .93 and ranged from .81 to 
.84 for the three subscales) and includes items such as “During the past month, you have 
learned about what situations might lead you to make a poor decision about risky sex” (K), 
“During the past month, your confidence in managing emotions in sexual situations in the real 
world has increased” (C), and “During the past month, you have become more motivated to 
protect your sexual partner from HIV risk in the real world” (M). The TCU HIV Services & 
Testing scale consists of 7 items (alpha = .81 for the full scale, .62 and to .79 for the knowledge 
and motivation subscales respectively). Sample items include “During the past month, you have 
become more knowledgeable about how to get HIV services in the real world” (K) and “You will 
get tested for HIV if you think that you might have been exposed” (M). The TCU Risk Reduction 
Skills scale is comprised of 14 items (alpha = .91 and ranged from .65 to .82 for the three 
subscales) and includes items such as “During the past month, you have a better understanding 
of how your shoulds and wants can conflict in the real world” (K), “During the past month, you 
have become more confident in balancing your shoulds and wants in the real world” (C), and 
“During the past month, your motivation to avoid personal HIV risks in the real world has 
increased” (M). 
All items for the TCU Confidence & Motivation scales use a 5-point Likert-type response 
scale ranging from 1=Disagree Strongly to 5=Agree Strongly. Items worded in the opposite 
direction from the scale construct were reflected by subtracting the score from 6. Scale scores 
were then computed by calculating the average score for items within the scale then multiplying 
the average score by 10 to obtain a range from 10 to 50. Scores above 30 indicated at least 
some agreement with the scale construct and scores below 30 indicated at least some 
disagreement. 

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2.4  Analytical approach 
Three primary sets of analyses were conducted. In the first set, characteristics of the 
research sample are reported and StaySafe participation in terms of number of sessions 
completed by the StaySafe group are calculated. A second set of analyses compared the 
StaySafe and SP groups on baseline and post-intervention measures using SAS Proc GLM. 
Analyses were conducted separately for the community and residential samples. The StaySafe 
and SP groups were first compared on demographic and background variables, and baseline 
measures of the outcome variables to check for group equivalence. The StaySafe and SP 
groups were then compared on outcome variables from the post-intervention surveys using the 
appropriate baseline measure as a covariate. Effect sizes (Cohen’s d) were computed for each 
outcome measure by taking the difference between least square means of the StaySafe and SP 
groups and dividing by the standard deviation of the SP group (Cohen, 1988).