1. Engagement and Treatment Completion in a Correctional Sample
Stephanie A. Van Horn, M.A.
&
Robert Morgan, Ph.D.
Texas Tech University
June 22, 2016
Engagement and Treatment Completion in a Correctional Sample

2. What’s Working in CLCO? Psychoeducation Treatment Engagement
Increased management of symptoms (Lukens & McFarlane, 2006)
Reduced symptom severity and institutional misconduct (Liau, Shively, Horn, Landau, Barriga, & Gibbs, 2004; Pomeroy, Kian, & Abel, 1999)
Treatment Engagement
Varying Definitions
Attendance, homework, participation
Significant predictor of non-completion (Drieschner and Verschuur, 2010)
To get closer look at what’s working, we wanted to focus on two key components: psychoeducation and treatment engagement
Large focus on psychoeducation throughout the program. Research shows psychoeducation important piece of symptom management and behavioral change, in both clinical and correctional populations
Treatment engagement is defined in various ways across the literature. Attendance, homework compliance, homework quality, participation in sessions, etc. Dry-shner and Vur-shurr found that attendance and active participation was predicitve of treatment completion in an outpatient sample of justice involved individuals

3. Research Questions
Are participants gaining knowledge in each of the modules?
Is knowledge acquisition predictive of treatment completion?
To what extent are attendance and homework completion related to program completion?
Is engagement early in the program predictive of completion?

4. Sample Three correctional facilities (N = 177)
Two separate residential facilities for dually- diagnosed offenders (n = 39; n = 130)
One psychiatric correctional facility (n = 8)
Sample size for analyses differed based on research question
Sample size differed based on research question due to differences in implementation of the program. One residential facility used open group format so order effects could not be tested. In addition, only individuals who completed both pre and post module quizzes were included in analysis of knowledge acquisition.

5. Demographics M age = 34.38 years (SD = 10.36) 68.9% Male 31.1% Female
Race/Ethnicity
63.8% White
34.5% African-American
1.7% Other
12.4% Hispanic
36.2% Unreported
Education
62.3% Less than HS
35.3% High school
20.8% Post- secondary
Marital Status
64.4% Single
15.8% Married
19.2% Divorced
0.6% Widowed

6. Measures Knowledge Acquisition Attendance and Homework
Content quizzes administered before and after completion of Modules 2-9
Raw pre/post change scores
Attendance and Homework
Binary variables (0 = no; 1 = yes)
Percent total for program completion
Raw count for early prediction

7. Knowledge Acquisition
Pre
Post n
M (SD) t
dav
Awareness
117
11.12 (4.94)
14.76 (2.38)
9.49*
.94
Thinking
142
4.50 (3.09)
9.08 (4.19)
11.81*
1.24
Medication
129
7.29 (1.83)
8.19 (1.84)
4.93*
.49
Coping
179
6.98 (1.80)
8.83 (2.60)
10.34*
.83
Emotion
122
7.12 (1.90)
9.89 (3.91)
7.06*
.90
Associates
119
4.87 (1.61)
6.29 (1.63)
7.61*
.84
Skills 66
4.58 (3.36)
6.55 (3.13)
3.96*
.62
Substance 27
5.04 (3.04)
9.48 (4.41)
4.65*
1.17
Dependent t tests were conducted using pre and post test scores. Post scores significantly higher than pre scores in all modules with large effect sizes in most of the modules

8. Knowledge Acquisition & Program Completion
Knowledge acquisition across program (N = 169)
M = 9.09 SD = 8.97
Statistically significant but minimal effect
β = .04, p = .04
OR = 1.04, 95% CI [1.00, 1.08]
53% likelihood for +1 SD
51% likelihood for -1 SD
Mean and SD somewhat difficult to interpret as each module had differing numbers of questions. Logistic regression conducted with total KA as predictor and program completion as outcome variable. Used estimates to calculate probability of program completion at mean, 1 sd above and 1 sd below. Effect of KA on program completion was negligible, as you can see by small difference in likelihood of completion.

9. Engagement and Program Completion
Percent of Total Attendance
M = 71.2% SD =26.2%
β = 1.29, p = .03
OR = 3.65; 95% CI [1.15, 12.11]
79.3% likelihood for +1 SD
51.3% likelihood at mean
22.4% likelihood for -1 SD
To control for fact that individuals who completed the program had the opportunity to attend more sessions and complete more homework than those who didn’t, attendance was measured by calculating the percentage of sessions attended and homework completed of each person’s total possible attendance/homework. Using same method, calculated likelihood of completion at mean, and +/- 1 SD.
Attendance was significantly related to program completion. Those who attended only 50% of sessions available to them were only 22% likely to complete the program. Those with average attendance, 71% in this sample, were just as likely to complete as not complete.

10. Engagement and Program Completion
Percent of Total Homework
M = 64.1% SD = 26.8%
β = 1.06, p = .07
OR = 2.89; 95% CI [.94, 9.19]
75.2% likelihood for +1 SD
51.3% likelihood at mean
26.7% likelihood for -1 SD
Again, using same methods of data analysis, we found that homework completion was not significantly related to program completion. However, the effect sizes suggest there may be some clinical meaning here. Individuals who completed less than half the homework assigned to them were almost three times less likely to complete the program as those who completed almost all their homework assignments.

11. Identifying At-Risk Participants
Attendance in Module 3 related to program completion
n = 47
M = 4.49 SD = 1.18
β = .84, p = .05
OR = 2.32; 95% CI [1.01, 5.36]
84% likelihood for 5 sessions
66% likelihood at 4 sessions
41% likelihood for 3 sessions
Wanted to examine if it was possible to predict non-completion within the first few weeks of the program, using attendance and homework in each of the first 3 Modules as individual predictors. Only significant predictor was attendance in Module 3 (Medication at that time). Module was six sessions in length, those who attended only half those sessions only had 41% likelihood of completing the whole program, compared to those who attended all the sessions, who were over 80% likely to complete the program.

12. Summary Participants learning program content
Knowledge has negligible effect on completion
Attendance and homework completion increase likelihood of program completion
More investigation needed to identify those at-risk for non-completion in the early phases of program

13. Limitations & Future Directions
Quiz reliability
Small sample size for early prediction
Primarily inpatient
Update and standardize quizzes
Test quiz reliability
Randomized Clinical Trial

14. Thank You