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TBI and Substance Abuse Correlates Within a Prison Therapeutic Community

2014 APA ConventionWashington, D.C.

Paper Session

Scott R. La Point, MA, Doctoral CandidateJoseph Francis, Psy.D. and Linda Baum, Ph.D.

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Acknowledgments:Lakeview NeuroRehabilitation CenterAmerican Psychological Association

Regent UniversityJoseph Francis, Psy.D.

Linda Baum, Ph.D.John Corrigan, Ph.D.

George Parkerson, Ph.D.James Brockington, Ph.D.

My family - wife Amy and our three sons(Luke, Joshua & Samuel)

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Introduction

• Between 1.5 million to 2 million individuals are presently incarcerated in U.S. prisons and jails.

(Bureau of Justice Statistics, 2012; Torrey et al., 2010)

• TBI is an unrecognized problem in prisons and jails nationwide, with 25% to 87% of offenders reporting a history of TBI as compared to 8.5% of the general population. (Slaughter, Fann, & Ehde, 2003)

• An estimated 155.9 million individuals identify as illicit drug users or drinkers of alcohol.

(National Survey on Drug Use and Health, 2011)

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New Mexico2 Million

New Hampshire

1.3 Million

Wyoming 0.5 Million

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1.7 Million

9 Million

Nebraska

Georgia

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Background on TBI, SA

• Alcohol and accidents– 50% of all TBI-related accidents involve alcohol use

(Allen et al., 2010; Sparadeo, Strauss, and Barth, 1990)

• TBI and Substance Abuse– Cognitive decline; TBI or SA? (Iverson, Lange, and Franzen, 2005)

• Comorbidity– Major Depressive Disorder, anxiety, substance use disorders,

impulsivity, and problems with executive functions (attention, memory, initiation) (CDC, 2010; Rimel et al.,1981)

• Screening for TBI < SA or psychiatric disorders• Affect of TBI on functioning in a TC population

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Background on TBI

• Controversies about TBI– Level of impairment not always representative of injury severity

• mTBI and PCS– Small percentage of individuals with mTBI experience

long-term deficits (McCrea, 2008)

• Technology not the answer– Advancements have not led to better identification

(Zhou et al., 2013)

• Study rationale– Group parings: mTBI and no TBI

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Purpose of the Study

• The lack of research among offenders within a prison therapeutic community means that an exploratory study could yield important findings with implications on the importance of screening for TBI.

• Improved identification of offenders with a history of TBI could enhance understanding of TBI-related problems within a prison TC.

• This study sought to explore if having a TBI has an effect on offenders’ health, cognition, and prison performance.

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Hypotheses

• Hypothesis 1: Among offenders with a history of substance-related problems, measures of program compliance will be higher for those without a history of moderate/severe TBI.

• Hypothesis 2: Among offenders with a history of substance-related problems, offenders with moderate/severe TBI will show evidence of greater problems with physical health and mental health as measured by the Duke Health Profile (DUKE) than will offenders without a history of moderate/severe TBI.

• Hypothesis 3: Among offenders with a history of substance-related problems, offenders with moderate/severe TBI will perform less well on the Trail Making Test (TMT) than will offenders without a history of moderate/severe TBI.

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Hypotheses (cont.)

• Hypothesis 4: Offenders who lack both a diagnosis of substance abuse/dependence and moderate/severe TBI will show better health indices on the DUKE, better program compliance, and perform better on the TMT than offenders with history of moderate/severe TBI and/or substance abuse/dependence.

• Hypothesis 5: A higher percentage of offenders with a history of TBI will be identified through the use of a structured interview (Ohio State University TBI Identification Method) than indicated by self-report methods upon admission to the prison TC.

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Methodology

• Participants– 213 offenders aged 18 to 65

• Procedures• Measures– Demographic Form– Prison TC Compliance Rating– Duke Health Profile (DUKE)– Trail Making Test (TMT)– Ohio State University TBI

Identification Method (OSU TBI-ID)

– Addiction Severity Index (ASI) 8

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Demographics

• Age– Mean: 37 years

• Date of birth• Ethnicity• Educational level• Marital status

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Data Analysis

• Between-group design

• SPSS Statistics 20 for Windows

• Prior to Analysis– Preliminary examination included assessment of normality,

outlier analysis, and descriptive statistics.

– All assumptions met

• Eager participants– Unexpected number

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Results

• Hypothesis 1– Level of TBI not predictive of TC compliance

• Virtually the same TC performance rating

• Hypothesis 2– Level of TBI predictive of physical and mental health

• Moderate/severe TBI reported more problems

• Hypothesis 3– Level of TBI significantly affected less cognitively

demanding task but not more difficult one• Moderate/severe TBI accounted for 3.4% of variance on TMT-A

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Results (cont.)

• Hypothesis 4a– Cognitive Processing Speed (TMT)

• Level of TBI significantly affected TMT-A but not TMT-B• Level of SA significantly affected TMT-B but not TMT-A

• Hypothesis 4b– Physical and Mental Health (DUKE)

• Level of TBI predictive of health problems– Moderate/severe TBI reported more problems

• Level of SA not predictive of health problems

• Hypothesis 4c– TC Compliance

• TBI and SA not predictive of program participation12

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Results (cont.)

TC, DUKE and TMT Performance by Substance Use and TBI Status

TBI: Traumatic Brain Injury; TC: Therapeutic Community; DUKE: Duke Health Profile; TMT: Trail Making Test; 1Results for TMT-A and TMT-B only include participants whose ethnicity is African American and Caucasian; Note: * p < .05

Substance Use History of TBI

SU

Problem

(n = 165)

(n = 151)1

No

SU Problem

(n = 48)

(n = 43)1

Moderate/

Severe

(n = 54)

(n = 50)1

No Moderate/

Severe

(n = 159)

(n = 144)1

Domain M SD M SD F p η² M SD M SD F p η²

TC Compliance 2.78 .433 2.75 .438 .25 .62 .001 2.76 .432 2.77 .435 .15 .69 .001

DUKE Physical 70.42 21.31 70.83 21.31 .097 .76 .00 65.00 22.38 72.52 21.77 4.21 .04* .020

DUKE Mental 68.24 23.50 71.04 22.99 .005 .95 .00 63.15 25.24 70.82 22.45 5.14 .02* .024

TMT-A 49.56 10.21 49.79 10.47 .020 .89 .00 46.40 10.13 50.72 10.08 4.75 .03* 0.24

TMT-B 47.62 9.48 44.42 11.78 3.94 .048* .02 44.82 9.82 47.64 10.12 3.38 .07 .017

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Results (cont.)

• Hypothesis 5– TBI identification

• Higher percentage of offenders reported history of TBI on structured interview than indicated in prison records– 69.5% on OSU TBI-ID

– 84.5% indicated “possible TBI,” “mild TBI,” and “moderate/severe TBI”

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Discussion

• Prison TC Compliance– Regardless of TBI history or substance abuse, rating

virtually the same

• Physical and Mental Health– TBI severity predictive of lower estimates of physical and

mental health• Individuals with more severe TBI may experience long-term

comorbid disorders or lifelong physical, cognitive, behavioral, and emotional disturbances.

(Cohen, et al., 1999; Lucas & Addeo, 2006)

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Discussion (cont.)

• Cognitive Processing Speed– Group differences; unexpected directions

– Substance Abuse• No ready explanation for why offenders with SA performed

better on the more demanding task• Practice effect? Concept formation practice (Corrigan, 2012)

• TBI identification– Findings congruent with previous research

– Prison records revealed only 11.3% of offenders indicated a history of TBI

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Limitations

• Volunteer participants– Results cannot be generalized as broadly

– “I’ve had a concussion, but…”

– Participants in better health

• Reliability of Duke Health Profile– Evidence of actual health problems?

• Accuracy of offenders’ self-reporting– Health, TBI history (Schofield et al., 2010), and addiction severity

• Validity and reliability of ASI– Systemic bias of ISRs

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Future Research

• mTBI as its own category– Results possibly distorted by study’s grouping

– A “no” TBI group?

• PCS among offenders with moderate/severe TBI– Cognitive rehabilitation as an alternative treatment

• Studying female offenders– Insights into prevalence, health of incarcerated women

• More specific measure to rate offender compliance– Organic factors vs. personality characteristics

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Questions?

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References

Allen, D., Frantom, L., Forrest, T., & Strauss, G. (2006). Neuropsychology of Substance Use Disorders. In P. Snyder (Ed.), Clinical neuropsychology: A pocket handbook for assessment (p. 649-673). Washington, DC: American Psychiatric Publishing.

Bigler, E., & Maxwell, W. (2012). Neuropathology of mild traumatic brain injury: Relationship to neuroimaging findings. Brain imaging and behavior, 6(2), 108- 136.

Bureau of Justice Statistics (2012, December). Prisoners in 2011. U.S. Department of Justice, Office of Justice Programs.

Centers for Disease Control and Prevention (2010). Traumatic brain injuries in prisons and jails: An unrecognized problem. Retrieved November 13, 2010, from Centers for

Disease Control and Prevention Web site: http://wwww.cdc.gov/traumaticbraininjury/pdf/Prisoner_TBI_Prof-a.pdf

Cohen, R., Rosenbaum, A., Kane, R., Warnken, W., & Benjamin, S. (1999). Neuropsychological correlates of domestic violence. Violence and Victims, 14(4), 397-

411.

Corrigan, J., & Bogner, J. (2007). Initial reliability and validity of the Ohio State University TBI Identification Method. Journal of Head Trauma Rehabilitation, 22(6), 318-329.

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References (cont.)

Heaton, R., Miller, S., Taylor, M., & Grant, I. (2004). Revised Comprehensive Norms for an Expanded Halstead-Reitan Battery: Demographically Adjusted Neuropsychological

Norms for African American and Caucasian Adults Scoring Program. Lutz, FL: Psychological Assessment Resources.

Iverson, G., Lange, R., & Franzen, M. (2005). Effects of mild traumatic brain injury cannot be differentiated from substance abuse. Brain Injury, 19(1), 15-25.

Lucas, J., & Addeo, R. (2006). Traumatic brain injury and postconcussion syndrome. In P. Snyder (Ed.), Clinical neuropsychology: A pocket handbook for assessment (p. 351-

380). Washington, DC: American Psychiatric Publishing.

McCrea, M. (2008). Mild traumatic brain injury and postconcussion syndrome. New York: Oxford University Press.

McLellan, A., Luborsky, L, Woody, G., & O’Brien, C. (1980). An improved diagnostic evaluation instrument for substance abuse patients: The addition severity index. The Journal of Nervous and Mental Illness, 168(1), 26-33

Parkerson, G., Broadhead, W., & Tse, C. (1990). The Duke Health Profile: A 17-itemmeasure of health and dysfunction. Medical Care, 28(11), 1056-1072. 21

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References (cont.)

Rimel, R., Giordani, B., Barth, J., Boll, T., & Jane, J. (1981). Disability caused by minor head injury. Neurosurgery, 9(3), 221-228.

Schofield, P., Butler, T., Hollis, S., Smith, N., Lee, S., & D’Este, C. (2010). Are prisoners reliable survey respondents? A validation of self-reported traumatic brain injury (TBI) against medical records. Brain Injury, 20(5), 1-9.

Slobounov, S., Gay, M., Zhang, K., Johnson, B., Pennell, D., Sebastianelli, W. … & Hallett, M. (2011). Alteration of brain functional network at rest and in response to YMCA

physical stress test in concussed athletes: rsFMRI study. NeuroImage, 55(4), 1716- 1727.

Sparadeo, F., Strauss, D., & Barth, J. (1990). The incidence, impact, and treatment of substance abuse in head trauma rehabilitation. Journal of Head Trauma Rehabilitation, 5(3), 1-8.

Zhou, Y., Kierans, A., Kenul, D., Ge, Y., Rath, J., Reaume, J. … & Lui, Y. (2013) Mild traumatic brain injury: Longitudinal regional brain volume changes. Radiology.

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