15 Sep In 1600 words, do the following: Describe some of the theoretical best practices for restorative justice, crime
In 1600 words, do the following:
- Describe some of the theoretical best practices for restorative justice, crime prevention, and corrections.
- Explain how the theoretical best practices are, and are not, manifested in current correctional settings in the United States.
- Explain different ways to improve rehabilitative services to make them more readily utilized within the criminal justice system, and better aligned to the theoretical best practices you identified.
Provide five to seven peer reviewed resources to support your explanations.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Reading for the week
1. Correctional Mental Health: From Theory to Best Practice Read Chapter 16 in Correctional Mental Health: From Theory to Best Practice.
https://bibliu.com/app/#/view/books/9781452236315/epub/OEBPS/s9781544302805.i1940.html#page_604
2. GCU Statement on the Integration of Faith and Work Access and read the "GCU Statement on the Integration of Faith and Work" to assist you in completing assignments and discus
https://www.gcu.edu/Documents/Statement-IFLW.pdf
3. Inside the Nation's Largest Mental Health Institution: A Prevalence Study in a State Prison System
Read “Inside the Nation's Largest Mental Health Institution: A Prevalence Study in a State Prison System” by Al-Rousan,
4. The Treatment of Persons With Mental Illness in Prisons and Jails: An Untimely Report Please the attachment in PDF for #1, 3, and 4
RESEARCH ARTICLE Open Access
Inside the nation’s largest mental health institution: a prevalence study in a state prison system Tala Al-Rousan1*, Linda Rubenstein2, Bruce Sieleni3, Harbans Deol3,4 and Robert B. Wallace2
Abstract
Background: The United States has the highest incarceration rate in the world which has created a public health crisis. Correctional facilities have become a front line for mental health care. Public health research in this setting could inform criminal justice reform. We determined prevalence rates for mental illnesses and related comorbidities among all inmates in a state prison system.
Methods: Cross-sectional study using the Iowa Corrections Offender Network which contains health records of all inmates in Iowa. The point prevalence of both ICD-9 and DSM-IV codes for mental illnesses, timing of diagnosis and interval between incarceration and mental illness diagnosis were determined.
Results: The average inmate (N = 8574) age was 36.7 ± 12.4 years; 17% were ≥50 years. The majority of inmates were men (91%) and white (65%).Obesity was prevalent in 38% of inmates, and 51% had a history of smoking. Almost half of inmates were diagnosed with a mental illness (48%), of whom, 29% had a serious mental illness (41% of all females and 27% of all males), and 26% had a history of a substance use disorder. Females had higher odds of having both a mental illness and substance use disorder. Almost all mental illness diagnoses were first made during incarceration (99%). The mean interval to diagnosis of depression, anxiety, PTSD and personality disorders were 26, 24, 21 and 29 months respectively. Almost 90% of mental illnesses were recognized by the 6th year of incarceration. The mean interval from incarceration to first diagnosis (recognition) of a substance abuse history was 11 months.
Conclusions: There is a substantial burden of mental illness among inmates. Racial, age and gender disparities in mental health care are coupled with a general delay in diagnosis and treatment. A large part of understanding the mental health problem in this country starts at prisons.
Keywords: Aging, Prisoners, Inmates, Correctional, Mental health
Background Over twenty million Americans are currently or have been incarcerated, the highest rate in the world. In the US in 2013, there were almost 2.3 million people incarcerated in prisons and jails, one in every 110 adults [1]. The mentally ill are overrepresented in correctional settings at estimated rates ranging from two to four times the general popula- tion [2]. As result, there are now ten times more individ- uals with Serious Mental Illnesses (SMI) in prisons and
jails than there are in state mental hospitals [3]. Incarcer- ation of people with mental illness is a major public health issue, with social, clinical and economic implications. The balance between public safety and human rights has left corrections services with challenges in providing appropri- ate care for these patients. Previous research in this field, such as examining the
relationship between the numbers of psychiatric hospital beds in relation to number of inmates [4] and describing recidivism of the mentally ill after release, [5–8] has im- proved our understanding of the mental health burden in prisons, but a more detailed look is needed. For ex- ample, little is known about actual prevalence rates
* Correspondence: [email protected] 1Department of Global Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Building 1, Room 1107, Boston, MA 02115, USA Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Al-Rousan et al. BMC Public Health (2017) 17:342 DOI 10.1186/s12889-017-4257-0
during incarceration across different age, gender and ethnic groups, or the association between substance abuse and other mental illnesses, and general medical co-morbidity. This study is one a few that used statewide electronic
correctional health records to better understand the occurrence of mental illness among prisoners. We also explored the interval between dates of incarceration and psychiatric diagnosis and suggested reasons behind dis- parities in care and ways to improve it. To our know- ledge, only a few studies have investigated this issue [9]. We explored the differences in age distribution in regards to mental illnesses since older prisoners are the fastest growing subgroup with the largest health expen- ditures within correctional systems [10, 11]. The associ- ation with substance use history and the distribution of these illnesses among different demographic subgroups was also described [12–14]. The aims of this study were to illustrate the burden of mental illness in a state prison using the prison’s own data system, profile mental illness and related comorbidities across different subgroups, and determine the vulnerability of these subgroups suggesting ways to help deal with this public health encumbrance.
Methods Study population The Iowa Department of Corrections (IDOC) collects health and other data on all inmates upon admission to the state prison system during processing at a single site, the Iowa Medical and Classification Center. Using data retrieved from the Iowa Corrections Offender Network, which is the electronic offender management system for staff across the entire statewide corrections system, we obtained and analyzed cross-sectional prevalence data on all IDOC inmates. The data file contained health in- formation as of February 17, 2015, and that date was used as the point prevalence for analysis. The extracted, anonymized data files contained demographic and other characteristics as well as the International Classification of Diseases, 9th Revision (ICD-9) codes for all diagnoses. A separate file contained the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) codes. The final sample size for all subjects in this study was 8574. The University of Iowa Institutional Review Board approved this study.
Study variables Demographic variables included race/ethnicity, gender, birth year, marital status and educational attainment. In this analysis, older inmates were those ≥50 years. Body Mass Index (BMI) was calculated with the formula weight in kilograms divided by the square of height in meters. History of tobacco use (Yes/No), pack-years of cigarette exposure (calculated by multiplying the number
of packs of cigarettes smoked per day by the number of years the inmate smoked) and mean of number of years using any smokeless tobacco products reflect data from the initial screening upon admission to the IDOC. The number of general medical conditions was classified into: none, one, two-three and four or more. History of any substance use disorder was diagnosed by the Iowa Medical and Classification Center staff. General medical conditions were determined using ICD-9-CM codes [15]. For this study, medical conditions were classified using three-digit codes, subsuming all four and five digit codes. With regard to incarceration and crime classifications,
supervision status was classified into: prison or work re- lease. Work release is defined by the IDOC as “granting inmates sentenced to an institution under its jurisdiction the privilege of leaving actual confinement during neces- sary and reasonable hours for the purpose of working at gainful employment” within the prison facility. Crime classification reflected the maximum penalties and in- cluded: Life in prison (A Felony), 25–50 years in prison (B Felony), 10 years (C Felony), 5 years (D Felony), 2 years (aggravated misdemeanor) and other felonies (variable penalties that range between 1 and 2 years). Sentence in years reflected length of stay and was deter- mined by Most Serious Conviction Category. Type of crime was classified by the most common crimes, which included: drug, violent, public order, property or other. Commitment indicator included: first, second or more than two terms. Mental illnesses were presented based on DSM-IV codes [16] and ICD-9 codes for each inmate. Recently, the IDOC switched officially from using DSM- IV to using the ICD-9 coding system for psychiatric ill- nesses. The DSM-IV has a cross reference to ICD-9 codes [17]. Some subjects had an ICD-9 code for mental illness but not a DSM-IV code, so we also reported the prevalence of mental illnesses using information from both DSM-IV and ICD-9 codes, and all diagnoses were manually reviewed to avoid any duplicate counting. Mental illness status was classified into: current, remis- sion and resolved. Date of admission to prison and date of mental illness diagnosis were provided in individual records. The difference between the two dates yielded the interval between current incarceration and diagno- sis. The numbers and odds ratios for inmates with a history of substance use also having mental illness were reported.
Statistical analysis Descriptive statistics were generated using frequencies and percents for categorical variables and means and standard deviations (SD) for continuous variables. The p values in Table 1 were unadjusted, while p-values in Tables 2 and 4 were adjusted for age group and
Al-Rousan et al. BMC Public Health (2017) 17:342 Page 2 of 9
gender using Cochran-Mantel-Haenszel methods. Two-sided tests with a p value ≤0.05 were considered statistically significant. All analyses were performed using SAS version 9.3 (SAS Institute Inc., Cary, North Carolina).
Results Table 1 shows the characteristics of the study popula- tion, based on the point prevalence date, for both
younger and older inmates. The average inmate age was 36.7 (SD = 12.4) years and the majority were males (91.4%) and white (64.9%). Older inmates (≥ 50 years), comprised 17% of the total cohort. A large proportion of inmates were either overweight (40.1%) or obese (37.6%). More than half of the inmates reported a history of smoking (51.2%) averaging 15.1 pack-years. Younger smokers were more likely to have smoked compared to older inmates (54% vs 38.1%). Approximately 63% had at
Table 1 Demographic characteristics of the prison’s population (n = 8574)
Characteristics Younger n = 7107
Older n = 1467
All n = 8574
p valuea
Younger vs older
Age, mean (SD) in years 32.4 (8.4) 57.2 (6.8) 36.7 (12.4)
Age, range in years 16–49 50–88 16–88
Gender 0.003
Female 637 (9.0) 97 (6.6) 734 (8.6)
Male 6470 (91.0) 1370 (93.4) 7840 (91.4)
Race <0.0001
Black 1913 (26.9) 309 (21.1) 2222 (25.9)
Hispanic 507 (7.1) 45 (3.1) 552 (6.4)
White 4473 (62.9) 1089 (74.2) 5562 (64.9)
Other 214 (3.0) 24 (1.6) 238 (2.8)
Marital status <0.0001
Married 1199 (17.0) 408 (28.1) 1607 (18.9)
Single 953 (13.5) 619 (42.6) 1572 (18.5)
Divorced or widowed 4884 (69.4) 425 (29.3) 5309 (62.6)
Highest level of education <0.0001
College graduate 57 (0.8) 43 (3.0) 100 (1.2)
Some college 142 (2.1) 66 (4.6) 208 (2.5)
High school/ equivalent 5266 (76.0) 991 (69.5) 6257 (74.9)
Less than high school 1300 (18.8) 270 (18.9) 1570 (18.8)
Other 160 (2.3) 56 (3.9) 216 (2.6)
Body mass index, kg/m2 <0.0001
< 18.5 (underweight) 18 (0.2) 4 (0.3) 22 (0.3)
18.5- < 25.0 (normal) 1697 (23.9) 191 (13.0) 1888 (22.0)
25- < 30 (overweight) 2848 (40.1) 594 (40.5) 3442 (40.1)
≥ 30 (obese) 2544 (35.8) 678 (46.2) 3222 (37.6)
History of tobacco use 3864 (54.4) 562 (38.1) 4426 (51.6) <0.0001
Pack-years for smokers only, mean (SD) 13.3 (11.2) 34.9 (23.3) 16.0 (15.2) <0.0001
Smokeless years, mean (SD) 6.6 (6.9) 18.4 (16.1) 7.8 (9.0) <0.0001
Medical Conditions, mean (SD) 1.1 (1.3) 2.6 (2.1) 1.4 (1.6) <0.0001
Chronic Medical Conditions <0.0001
0 2924 (41.4) 268 (18.3) 3192 (37.2)
1 2286 (32.7) 297(20.3) 2583 (30.1)
2–3 1500 (21.1) 465 (31.7) 1965 (22.9)
≥ 4 397 (5.6) 437 (29.8) 834 (9.7) ap-values are from Fisher’s exact test or the Pearson chi-square statistic Values represent numbers and percentages unless indicated otherwise
Al-Rousan et al. BMC Public Health (2017) 17:342 Page 3 of 9
least one chronic medical condition, and among the older inmates, approximately 30% had four or more, compared to 6% for younger inmates. The distribution of medical conditions among the inmate population are shown in Additional file 1: Table S1. Coronary artery disease was the most prevalent chronic medical condi- tion (15%), particularly among the older inmates, followed by hypertension (13%), hyperlipidemia (9%) and hepatitis C (8.3%). Additional file 1: Table S2 shows the crime and incar-
ceration status of the inmate population. The mean and median sentences were 24.0 and 12.0 years respectively. Nearly half of inmates were convicted for violent crimes
(47.8%), with the next most common being drug-related offenses (22.6%). Older inmates had a higher proportion of violent crimes and a somewhat lower proportion of offenses related to drugs. Only a small minority had work release status (6.1%). Table 2 shows the distribution of mental illness diag-
noses according to age group. The odds ratios reflect the relative prevalence among the younger versus the older age groups, adjusted for sex and race/ethnicity. Overall, almost half of the inmates had a history or a diagnosis of one or more mental illnesses (48%). Of female inmates, 60% had a mental illness diagnosis, compared to 46.6% of males (data not shown). Almost a third of all inmates
Table 2 History of mental illness in younger and older prisoners (n = 8574)
Mental disorders from the ICD9 and DSM Younger n = 7107
Older n = 1467
All n = 8574
OR (95% CI)a
Reference = older
Mental illness (DSM and ICD9) 3448 (48.5) 645 (44.0) 4093 (47.7) 1.3 (1.2–1.5)
Mental illness (DSM) 3222 (45.3) 570 (38.9) 3792 (44.2) 1.4 (1.3–1.6)
Mental illness (ICD9 only) 226 (3.2) 75 (5.1) 301 (3.5) 0.7 (0.5–0.9)
Serious mental illnessb (DSM and ICD9) 2048 (28.8) 404 (27.5) 2452 (28.6) 1.1 (0.99–1.3)
Serious mental illness (DSM) 1976 (27.8) 386 (26.3) 2362 (27.5) 1.1 (1.0–1.3)
Serious mental illness (ICD9 only) 72 (1.0) 18 (1.2) 90 (1.0) ne
Substance usec (DSM and ICD9) 1928 (27.1) 312 (21.3) 2240 (26.1) 1.5 (1.3–1.7)
Substance use (DSM) 1791 (25.2) 286 (19.5) 2077 (24.2) 1.5 (1.3–1.7)
Substance use (ICD9 only) 137(1.9) 26 (1.8) 163 (1.9) 1.2 (0.8–1.8)
Depression, major depressive disorders 1267 (17.8) 294 (20.0) 1561 (18.2) 0.9 (0.8–1.1)
Anxiety, general anxiety, panic disorders 1222 (17.2) 193 (13.2) 1415 (16.5) 1.5 (1.3–1.8)
Personality disorders 824 (11.6) 135 (9.2) 959 (11.2) 1.3 (1.1–1.6)
Psychosis, psychotic disorders 664 (9.3) 97 (6.6) 761 (8.9) 1.5 (1.2–1.9)
Developmental disabilities 677 (9.5) 45 (3.1) 722 (8.4) 3.5 (2.6–4.8)
Bipolar 579 (8.2) 65 (4.4) 644 (7.5) 2.1 (1.6–2.7)
Post-Traumatic Stress Disorder 459 (6.5) 79 (5.4) 538 (6.3) 1.2 (0.9–1.5)
Schizophrenia 177 (2.5) 77 (5.3) 254 (3.0) 0.5 (0.4–0.6)
Impulse control disorders 160 (2.3) 10 (0.7) 170 (2.0) 3.6 (1.9–6.9)
Dysthymia, neurotic depression 132 (1.9) 45 (3.1) 177 (2.1) ne
Dementia 29 (0.4) 24 (1.6) 53 (0.6) ne
Sleep, movement and eating disorders 24 (0.3) 2 (0.1) 26 (0.3) ne
Sexual disorders, paraphelias 11 (0.2) 3 (0.2) 14 (0.2) ne
Pervasive developmental disorders 7 (0.1) 0 (0.0) 7 (0.1) ne
Somatization disorders 0 (0.0) 1 (0.1) 1 (0.0) ne
DSM The Diagnostic and Statistical Manual of Mental Disorders, ICD9 The International Classification of Diseases, 9th Revision, ne not estimable, sample size too small. CI confidence interval aOdds Ratios and 95% CI are from logistic regression models adjusting for sex and race/ethnicity. If the (95% CI) includes 1.0, the odds ratio is not statistically significant bSerious mental illness includes bipolar disorders, dementia/organic disorders, depression and major depressive disorders, dysthymia/neurotic depression, psychosis/psychotic disorders, schizophrenia, and substance use disorders cSubstance use includes alcohol-induced persisting amnestic disorder, cannabis-induced psychotic disorder, with hallucinations, other (or unknown) substance- induced psychotic disorder with hallucinations, phencyclidine-induced psychotic disorder, with hallucinations, psychotic disorder NOS, substance-induced, alcohol dependence, opioid dependence, sedative/hypnotic/anxiolytic dependence, cocaine dependence, cannabis dependence, amphetamine dependence, other polysubstance abuse, methamphetamine dependence, hallucinogen dependence, inhalant dependence, polysubstance dependence, other (or unknown) dependence, phencyclidine dependence
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had a Serious Mental Illness (SMI) (29%) (Table 2) and a similar proportion had history of substance abuse (26%). SMIs were relatively more prevalent in females (41%) than males (27%). For specific mental illnesses, depression and major de-
pressive disorders were the most prevalent conditions, present in 18% of all inmates and accounting for 38% of all the mentally ill inmates (Table 2). The next most common were anxiety and panic disorders, present in 17% of inmates. With regard to sex-specific illnesses (data not shown) females were more likely to be diag- nosed with substance abuse, depression and major de- pressive disorders, developmental disabilities, bipolar disorder, PTSD and sleep, movement and eating disorders. Males were more likely to be diagnosed with impulse control disorders and dysthymia or neurotic depression. Younger inmates were more likely to be diagnosed with substance abuse, anxiety and panic disorders, personality disorders, psychotic disorders, developmental disabilities, bipolar disorder, dysthymia and neurotic depression and impulse control disorders. Figure 1 shows the distribution of mental illnesses
counts across race/ethnicity and gender groups. Among the three major race/ethnicity groups, females were more likely to have one or more mental illnesses, but among females, Hispanics had a lower proportion with such illnesses. Among males, whites were more likely to have one or more mental conditions than African- Americans or Hispanics.
Table 3 displays the prevalence of a substance abuse history and odds ratios for those rates, both crude and adjusted for inmate demographic characteristics. Overall, nearly half of those with a mental illness also had a history of substance abuse (48.5%). Having any of the mental con- ditions was associated with an eight-fold increased odds of also having a substance abuse history. Higher odds ratios were also seen associated with SMIs, anxiety and panic disorders and major depressive illnesses. For all mental conditions where the odds ratios of associated substance abuse were calculable, odds of substance abuse were at least 2.5. Additional file 1: Table S3 shows the numbers and
rates of mental disorders among younger and older in- mates, according to whether the disorders were con- sidered currently active or resolved/in remission. Overall, in both younger and older age groups, the ma- jority of all conditions ever diagnosed were “current,” that is, active. This was true for both males and females (data not shown). Particularly, older inmates were more likely to be diagnosed during incarceration (74%). Table 4 and Additional file 1: Figure S1 show the diag-
noses of all mental illnesses for the inmates’ life duration in prison since incarceration. The mean interval to first diagnosis of substance abuse and bipolar disorders was 11 months since admission. The mean interval to diag- nosis of depression, anxiety, PTSD and personality disor- ders were 26, 24, 21 and 29 months respectively. For psychosis, the mean duration was 14 months and for
Fig. 1 All prevalence rates are cross-sectional. There were 2090 African American men, 64.1% of which has no mental illness. Women in general exhibited the highest burden of mental illness compared to other racial groups. Quarter of the female African American inmates had three or more mental illness diagnoses. These prevalence rates were similar to white women (n = 554) of which 24.7% had three or more mental illnesses. More than half of the white men (n = 5008) had a mental illness diagnosis which is the highest number compared to rates in other racial groups. Percentage of inmates diagnosed with mental illness in Iowa by race and gender
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developmental disabilities it was 16 months. The longest mean durations to diagnosis were for schizophrenia and dysthymia, 52 and 45 months respectively. The shortest duration was to the diagnosis of dementia (7 months). As shown in Additional file 1: Figure S1, almost 90% of mental illnesses were diagnosed (i.e., appeared in the clinical record) by the 6th year of incarceration.
Discussion Mental health conditions constitute a substantial burden among inmates in correctional institutions, and this issue has gained increasing attention in recent years. Within the state penitentiaries in Iowa, we found the prevalence rate for mental illnesses to be nearly 50%, similar to prevalence rates reported by other states [18]. However, US national estimates mental illness rates are somewhat dated, as the most recent survey by the Bureau of Justice Statistics (BJS) was performed in 2004 for federal inmates and in 2002 for jail inmates [18]. While only representing the experience of one state, this
study provides recent and representative estimates for the prevalence of mental health problems among individuals involved in the criminal justice system. In previous studies
within federal prisons and jails, inmates have been asked to complete a modified clinical interview based on the DSM-IV [19–21]. Inmates in mental hospitals or other- wise physically or mentally unable to complete the surveys were excluded from such studies. Despite this, it has been estimated in the BJS study that 56% of state inmates had a mental health problem, similar to our own findings des- pite differing methods. Also, we found that illness rates were higher among female than males, consistent with BJS reports. In this study, the presence of mental illness was associated with an eight-fold increased odds of a sub- stance use and abuse history. In this cross-sectional prevalence study, those with di-
agnosed mental disorders were much more likely to be under active treatment than designated as resolved or in remission. There is evidence that inmates with a mental condition are more likely to have been charged with breaking correctional facility rules [18]. Also, they are more likely to be injured in a fight and be charged with a physical or verbal assault on correctional staff or another inmate. These behaviors may promote more concurrent mental illness diagnoses in the clinical re- cords, in part, because these inmates receive more clinical attention. Thus, it is not surprising that these
Table 3 Odds ratios (95% CI) for the association of history of substance use disordera with mental illness
Mental disorders Substance users with disorder, n (%)
Odds Ratio (95% CI)b
Unadjusted Adjusted
Any mental disorder (excluding substance abuse) 1747 (48.5) 8.5 (7.6–9.6) 8.1 (7.2–9.1)
Serious mental disorderc 1198 (53.5) 4.7 (4.2–5.2) 4.4 (4.0–4.9)
Anxiety, general anxiety, panic disorders 766 (34.2) 4.6 (4.0–5.1) 4.2 (3.7–5-4.8)
Depression, major depressive disorders 711 (31.7) 3.0 (2.7–3.4) 2.8 (2.5–3.2)
Personality disorders 520 (23.2) 4.1 (3.5–4.7) 4.0 (3.5–4.6)
Psychosis, psychotic disorders 406 (18.1) 3.7 (3.2–4.3) 3.8 (3.2–4.4)
Developmental disabilities 360 (16.1) 3.2 (2.7–3.7) 2.9 (2.5–3.4)
Bipolar 358 (16.0) 4.0 (3.4–4.7) 3.6 (3.1–4.3)
Post-Traumatic Stress Disorder 254 (11.3) 2.7 (2.3–3.3) 2.6 (2.2–3.1)
Schizophrenia 117 (5.2) 2.5 (1.9–3.2) 2.8 (2.1–3.6)
Impulse control disorders 87 (3.9) 3.0 (2.2–4.1) 2.9 (2.1–4.0)
Dysthymia, neurotic depression 83 (3.7) 2.6 (1.9–3.4) 2.5 (1.8–3.4)
Sleep, movement and eating disorders 12 (0.5) ne ne
Sexual disorders, paraphilia 2 (0.1) ne ne
Pervasive developmental disorders 2 (0.1) ne ne
Values represent numbers and percentages ne not estimable aSubstance use disorder as derived from the ICD9/DSM codes and includes alcohol-induced persisting amnestic disorder, cannabis-induced psychotic disorder, with hallucinations, other (or unknown) substance-induced psychotic disorder with hallucinations, phencyclidine-induced psychotic disorder, with hallucinations, psychotic disorder NOS, substance-induced, alcohol dependence, opioid dependence, sedative/hypnotic/anxiolytic dependence, cocaine dependence, cannabis dependence, amphetamine dependence, other polysubstance abuse, methamphetamine dependence, hallucinogen dependence, inhalant dependence, polysubstance dependence, other (or unknown) dependence, phencyclidine dependence; bOdds ratios were generated in logistic regression models adjusted for age, gender, and race/ethnicity; Odds ratios are statistically significant if the 95% CI does not include 1.0 cSerious mental illness includes bipolar disorders, dementia/organic disorders, depression and major depressive disorders, dysthymia/neurotic depression, psychosis/psychotic disorders, schizophrenia, and substance use disorders
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illnesses are generally very costly to treat, and patients are at great risk for recidivism, hospitalization, and suicide upon release [22]. These experiences have been previously described, as well as the wave of mass incarceration and increasing deinstitutionalization of the mentally ill in the community, resulting in an increased prevalence of mental illness in prisons. It is not surprising that mental illness is the leading cause of clinical expenditures in corrections facilities [23]. High rates of mental illnesses among inmates in this
study, as well as in other national studies, are likely to be in part because of the reservoir of mental conditions and the inadequate treatment access in the community prior to incarceration [24]. Another possibility is the higher incarceration rates for substance abuse, part of the “War on Drugs” [25]. Substance use and abuse are associated with other psychiatric co-morbidity [26]. De- layed psychiatric diagnosis in many inmates is analogous to findings from other studies [24]. This may be attributed to the following explanations: high rates of undiagnosed conditions at entry, the incomplete transmission of relevant clinical records upon incarceration and highly stressed diagnostic and management resources within the corrections system. It is also possible that some inmates choose to withhold their psychiatric histories because of
stigma and other reasons. Another hypothesis is that the prison environment itself may be stressful enough to ignite subclinical mental illnesses during the course of in- carceration related to social isolation, violence, lack of support and others [27, 28]. There is an important need for longitudinal research to evaluate and better under- stand our findings and those of others. Despite potential clinical policy and resource problems within prisons and jails, contrasts with community care dynamics would seem to also be of value. Black and Hispanic inmates were overrepresented rela-
tive to Iowa’s general population which is comparable to other demographic data on incarcerated populations [29]. According to the US Census Bureau, 3.3% of Iowa’s population is African-American [30], in contrast to 26% in the state prison system. Mental health challenges, substance use disorders, and HIV/AIDS disproportion- ately affect African-Americans in correctional settings [31], consistent with our findings. Minority inmates had mental illness rates generally similar to Whites, but Whites were more likely to have more than one mental illness diagnosis. Of interest, female Hispanic inmates were more likely to have three or more mental condi- tions in contrast to their White and Black counterparts. Women inmates, especially younger ones, were more
Table 4 Duration in months to the first documentation of mental illness made after prison entrya
Mental disorders First diagnosisb
n = 4044 Months Percent diagnosed in months
Frequency (%) Mean (SD) Median [range] ≤1 >1–6 > 6–24 > 24
Substance abusec 1130 (27.9) 10.3 (36.6) 0.5 [0.25–402] 72.2 13.5 6.0 8.3
Depression 729 (18.0) 26.2 (65.0) 0.75 [0.25–483] 57.2 14.9 8.0 19.9
Anxiety 616 (15.2) 24.4 (57.6) 1.0 [0.25–385] 52.1 18.3 12.0 17.5
Personality disorders 366 (9.1) 29.5 (59.0) 3.0 [0.25–354] 39.1 21.3 13.9 25.7
Psychosis and psychotic disorders 280 (6.9) 13.7 (36.3) 0.75 [0.25–290] 60.7 16.4 10.0 12.9
Developmental …
,
The Treatment of Persons With Mental Illness in Prisons and Jails: An Untimely Report Published on Psychiatric Times (http://www.psychiatrictimes.com)
The Treatment of Persons With Mental Illness in Prisons and Jails: An Untimely Report August 13, 2014 | Forensic Psychiatry [1], Cultural Psychiatry [2] By Alan R. Felthous, MD [3]
The recent 2014 Joint Report of the Treatment Advocacy Center and the National Sheriffs’ Association could have been a most useful and timely report on the woefully inadequate access to appropriate levels of mental health services for incarcerated seriously mentally ill persons. This author believes the report will only make the problem worse. Source:
The recent 2014 Joint Report of the Treatment Advocacy Center and the National Sheriffs’ Association1 could have been a most useful and timely report
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