Skip to main content
Canadian Journal of Psychiatry. Revue Canadienne de Psychiatrie logoLink to Canadian Journal of Psychiatry. Revue Canadienne de Psychiatrie
. 2020 Nov 6;66(6):560–568. doi: 10.1177/0706743720970829

Patterns and Predictors of Reincarceration among Prisoners with Serious Mental Illness: A Cohort Study: Modèles et prédicteurs de réincarcération chez les prisonniers souffrant de maladie mentale grave : Une étude de cohorte

Roland M Jones 1,2,, Madleina Manetsch 1,3, Cory Gerritsen 1,2, Alexander I F Simpson 1,2
PMCID: PMC8138736  PMID: 33155829

Abstract

Background:

A small proportion of people who have serious mental illness and rapid and frequent incarcerations account for a disproportionate amount of overall service use and cost. It is important to describe such individuals, so that services can respond more effectively.

Methods:

We investigated a cohort of 4,704 incarcerated men and women who were discharged from a correctional mental health service and followed for a median of 535 days. We investigated social, clinical, demographic, and offense characteristics as predictors of return to the service using Cox survival analyses. Secondly, we characterized individuals as high-frequency service users as those who had 3 or more incarcerations during a 1-year period and investigated their characteristics.

Results:

We found that a higher rate of return to custody was associated with schizophrenia spectrum/bipolar affective disorder (BPAD), personality disorder traits, crack cocaine and methamphetamine use, and unstable housing. Charges of theft/robbery and breach of probation were also positively associated, and sex assault was negatively associated with return to custody. Within a 1-year time period, we found 7.2% of individuals were high-frequency service users, which accounted for 19.5% of all reincarcerations.

Conclusion:

Identification of the characteristics of those with mental illness in custody, especially those who have high-frequency returns to custody, may provide opportunity to target resources more effectively. The primary targets of intervention would be to treat those with schizophrenia/BPAD and substance use problems, particularly those using stimulants, and addressing homelessness. This could reduce the problem of repeated criminalization of the mentally ill and reduce the overall incarceration rate.

Keywords: prison, corrections, mental illness, recidivism, women, homelessness, substance use disorders, revolving door

Background

Healthcare need is unevenly distributed within populations. Approximately 1% of health service users account for 20% to 33% of overall healthcare costs,1,2 and in mental health services, a small number of patients account for a disproportionate number of all admissions.3 Psychiatric patients who have frequent admissions to hospital have been termed “high-frequency users,”4 “high-intensity users,”5 and “revolving door” patients.3,4,68 Such patients are characterized as having multiple medical and behavioral problems, substance abuse, more psychopathology, and are more likely to have problems managing finances and housing.6,9,10 Existing mental health services may be inadequate at meeting these needs, contributing to repeat hospitalizations, homelessness, and other adverse outcomes.11,12

High-frequency mental health users also have high levels of police and criminal justice involvement.1316 Persons with serious mental illness (SMI) are more likely than those without SMI to be charged with a criminal offense after being arrested by the police17 and are often incarcerated for relatively minor offenses including crimes of poverty, offenses related to substance use, or minor offenses against judicial orders.18 This may result in repeated brief incarceration, which can cause fracturing of community ties such as housing, income support, or access to psychiatric care.

Higher rates of reincarceration among people with SMI have been found in previous studies from the United States.1921 One issue likely driving rapid and frequent reincarceration among those with SMI is concurrent substance use disorder. High rates of substance misuse and SMI have been found among prisoners globally22,23 and is one of the strongest predictors of recidivism among those with psychiatric diagnoses20,21,2427 though specific substances of abuse as predictors of rapid or frequent return in this population have rarely been studied.

Given the disproportionately high impact that high-frequency service users have on health and criminal justice services, detection and characterization of individuals with mental health needs who frequently return to custody is important as it may inform the tailoring of services specifically for this group in order to lower the impact on criminal justice and mental health services as a whole.28 In our study, we aim to (1) investigate the proportion and frequency of those who have mental health needs who are reincarcerated; (2) investigate diagnostic, clinical, criminological, and social factors that predict frequency of and time to return to custody; and (3) define high-frequency service users and describe their clinical, sociodemographic, and offense characteristics. We hypothesized that persons with mental illness with higher rates of repeat incarceration would have relatively minor charges, more symptoms, higher rates of homelessness, and higher rates of substance misuse.

Methods

Participants and Setting

This study was carried out at the Toronto South Detention Centre (TSDC), a male facility that holds a maximum of 1,650 inmates, and the Vanier Centre for Women (VCW), a facility that holds a maximum of 333 women, which serve Greater Toronto and parts of Southern Ontario, Canada. Both centers have a high turnover of inmates and detain primarily those on remand.

The Forensic Early Intervention Service (FEIS) is a team of 6 psychiatrists and 12 clinicians (comprising 3 nurses, 6 social workers, and 3 occupational therapists) that provides mental health screening, assessment, and consultation to men and women on remand in these jails.

Study Design

As part of routine care, all inmates are screened at reception by correctional health staff using the Brief Jail Mental Health Screen,29 which is an 8-item mental health screening tool requiring “yes” or “no” responses that has been validated in a number of settings.2931 Those who screen positive are referred to FEIS for assessment following which a triage assessment using the Jail Screening Assessment Tool (JSAT)32 is completed. A decision is then made whether secondary mental health services are needed, comprising outpatient equivalent psychiatric consultation. The inmate is either referred for a psychiatrist assessment or discharged. There are no inpatient mental health services within the jails. At the point of discharge, a checklist is completed which includes the clinical diagnosis and services which the patient received or was referred to. Discharge may be due to the client not requiring the service, the client declining the service, or when released from the jail. A research database was established in 2016 to record data from the screening assessments and the discharge checklist for all clients referred to the service for the purpose of research and service evaluation. Participants comprised all clients who were assessed by the FEIS service between January 1, 2016, and December 31, 2018. Reincarceration in this study was defined as those being rereferred to the FEIS service.

Ethical Approval

Research Ethical approval was granted by the Centre for Addiction and Mental Health Research Ethics Board (#018/2018) for this research. Participant consent was not required as it would be impractical to obtain consent from all participants and the risk of any harm is low.

Measures

The JSAT is a structured professional judgment tool based on a clinical interview by a trained mental health clinician, which takes approximately 20 min to complete and has been shown to have good sensitivity and specificity.33,34 All clinicians received training in the use of the JSAT, however, interrater reliability was not measured.

Diagnosis was taken from the JSAT as recorded by the clinician which maps onto Diagnostic and Statistical Manual of Mental Disorders, fourth edition diagnoses. We categorized diagnosis as either schizophrenia spectrum disorder/bipolar affective disorder (BPAD), substance use disorder mood disorder, stress/anxiety disorder, or personality disorder traits.

Ethnicity was self-identified and categorized as Asian, Black, White, Aboriginal, or Other.

Gender categorized as male or female is defined by the institution. Those incarcerated at VCW and TSDC were categorized as female or male, respectively.

Current charge(s) were recorded as given by the inmate and were categorized as assault, murder/attempted murder, breach of probation, driving under the influence of substances, property damage, sexual offense, theft/robbery, or drug offenses.

Homelessness was defined as living homeless/on the street or living in shelters or hostels.

Age was taken as the age recorded at the index admission.

Total Brief Psychiatric Rating Scale (BPRS-E). A modified version of the BPRS is incorporated in the JSAT and was summed to give a measure of severity of mental illness.

Length of stay was recorded as the number of days from referral to the service to discharge. Those referred and discharged on the same day were given a length of stay of 0.5 days.

Statistical Analysis

First, we carried out survival analyses on all clients assessed by the FEIS service between January 1, 2016, and December 31, 2018, to investigate the characteristics associated with the rate of reincarceration. We carried out univariate analysis on all variables of interest, using the logrank test for categorical variables and Cox proportional hazard models for continuous variables. We analyzed data as multiple failure time in Stata version 14 using a variance-corrected model that adjusts for nonindependence of multiple failures,35 such that clients remained at risk after discharge and were included for all reincarcerations until censored at December 31, 2018. We then selected all variables in which there was a difference in the univariate analyses where logrank P < 0.2 for the preliminary multivariate model and included all interaction terms in which there were significant main effects. We tested the proportionality assumption by specifying all time-varying predictors and finally produced a parsimonious model of significant variables.

Second, we defined a cohort of inmates in whom there was a complete 1-year follow-up period (i.e., a cohort in which each client had a period of observation of exactly 1-year postrelease) in order to identify and quantify the number of frequently reincarcerated individuals. We investigated the total number of referrals to FEIS during the 1-year follow-up period and defined a group that had 3 or more referrals during the year as “high-frequency” service users. We then investigated predictors of high-frequency service users creating a model using similar methods.

Results

Complete Cohort

There were 4,704 referrals to the FEIS service from 3,034 unique patients, comprising 2,281 (75.7%) men and 734 (24.3%) women. At time of first entry, the mean age was 35.5 years (SD = 11.2). Notwithstanding missing data on this variable, most clients self-identified as White (1,008; 53.7%), the remaining 392 (20.7) as Black, 163 (10.6%) as aboriginal, and 116 (6.2%) as Asian (see Table 1). Just over one half had a diagnosis of schizophrenia, schizoaffective disorder, or BPAD (54.7%), and one-third had a diagnosis of major depression or anxiety (34.8%). The median BPRS-E score on admission was 4 (interquartile range [IQR] 2 to 8). The most common charges were breach of probation (29.4%), assault (22.2%), and theft or robbery (20.6%). Nearly one-third reported the use of alcohol (28.8%) or cannabis (27.8%). Methamphetamine and crack use were reported by 15.3% and 16.3%, respectively.

Table 1.

Descriptive Characteristics of the Participants (Frequencies and Percentages).

Variable N (%)
Male 2,281 75.6
Age 34 27 to 43(IQR)
Diagnosis
 Schizophrenia spectrum/bipolar affective disorder 1,057 34.8
 Mood/anxiety disorders 1,660 54.7
 Personality traits 286 9.4
 ID/brain injury 69 2.3
Brief Psychiatric Rating Scale total 4 2 to 8(IQR)
Ethnicity
 Asian 116 6.2
 Black 392 20.0
 White 1,008 53.6
 Aboriginal 163 8.7
 Other 200 10.6
Charges
 Arson 26 0.9
 Assault 675 22.2
 Breach probation 891 29.4
 Driving under influence 20 0.67
 Murder 38 1.25
 Property damage 11 0.36
 Sex assault 64 2.11
 Theft/robbery 626 20.6
 Drug offense 233 7.7
 Other offense 1,032 34.0
Homeless 1,941 52.6
Social support 1,585 40.1
Drugs
 Alcohol 1,380 28.8
 Crack 783 16.3
 Opioids 360 7.5
 Cannabis 1,335 27.8
 Methamphetamine 732 15.3
 Other drug 499 10.4
Length of stay 1.5 0.5 to 7.5(IQR)

Abbreviation: IQR = interquartile range; ID = Intellectual Disability.

Following the first incarceration, 28.7% of individuals were reincarcerated at least once during the follow-up period. The median time at risk was 534.5 days (range = 7.5 to 1,109.5 days). We observed that 483 (15.9%) were reincarcerated twice, 191 (6.3%) 3 times, and 83 (2.7%) 4 times. The maximum number of reincarcerations observed was 15 (2 cases).

We investigated variables associated with the rate of reincarceration. We first investigated the univariate association between each exposure and rate of reincarcerations (see Table 2). We found highly significant associations between rate of reincarceration and having a diagnosis of schizophrenia/BPAD or personality traits, ethnicity, homelessness, methamphetamine or crack cocaine use, and offense types of theft/robbery or breach of probation, higher BPRS scores, and shorter length of stay.

Table 2.

Univariate Analyses of Variables Associated with Rate of Reincarceration.

Variable N (%) Missing Observed Expected χ2 P
Female gender 1,111 (23.5) 35 (0.7) 373 330.7 6.69 0.01
Schizophrenia spectrum/bipolar affective disorder 1,007 (25.4) 0 (0) 498 307.75 147.89 <0.0001
Mood/anxiety disorders 877 (22.1) 0 (0) 310 340.29 3.48 0.06
Personality disorder traits 494 (12.5) 0 (0) 255 148.6 84.6 <0.001
Ethnicity 1,696 (35.6)
Asian 174 (5.6) n/a 52 76.6 23.8 <0.001
Black 677 (21.7) n/a 273 254.0
White 1,613 (51.7) n/a 589 630.9
Aboriginal 313 (10.0) n/a 143 109.6
Other 344 (11.0) 152 137.9
Arson 35 (0.72) 1,042 (22.2) 10 11.1 0.10 0.75
Assault 1,120 (23.1) 1,042 (22.2) 380 354.6 2.31 0.13
Breach probation 1,653 (34.0) 1,042 (22.2) 592 478.6 37.7 <0.001
Driving under influence 23 (0.47) 1,042 (22.2) 3 10.7 5.61 0.02
Murder 43 (0.89) 1,042 (22.2) 2 16.5 12.87 <0.001
Property damage 20 (0.41) 1,042 (22.2) 8 6.1 0.62 0.43
Sex assault 95 (1.96) 1,042 (22.2) 20 39.4 9.78 0.002
Theft/robbery 1,164 (24.0) 1,042 (22.2) 475 335.1 73.1 <0.001
Drug offense 331 (6.8) 1,042 (22.2) 95 116.1 4.13 0.04
Homeless 1,941 (52.6) 1,145 (24.0) 789 579 142.3 <0.001
Social support 1,585 (40.1) 885 (18.6) 543 568.1 1.9 0.167
Alcohol 1,380 (28.8) 54 (1.1) 474 512 4.1 0.04
Crack 783 (16.3) 54 (1.1) 303 233.9 23.8 <0.001
Heroin 360 (7.5) 54 (1.1) 125 126.6 0.02 0.88
Cannabis 1,335 (27.8) 54 (1.1) 467 474.7 0.17 0.68
Methamphetamine 732 (15.3) 54 (1.1) 299 222.0 30.9 <0.001
Other drug 499 (10.4) 54 (1.1) 163 192.8 5.22 0.02
Age 4,704 0 (0) −2.13 0.033
Brief Psychiatric Rating Scale total 4,373 331 (7.0) 2.80 0.005
Length of stay 4,704 0 (0) −2.3 0.021

We entered those variables from the univariate analyses where there was an association at the 0.2 level of significance into a Cox regression model and tested main effects and all interactions and created a final parsimonious model (see Table 3).

Table 3.

Parsimonious Model of Variables Associated with Rate of Reincarceration.

Variable Hazard Ratio Standard Error z 95% Confidence Interval P
Female gender 1.15 0.10 1.60 0.97 to 1.38 0.11
Schizophrenia spectrum/bipolar affective disorder 2.14 0.28 5.85 1.67 to 2.77 <0.001
Personality disorder traits 1.62 0.14 5.62 1.37 to 1.93 <0.001
Breach probation 1.33 0.09 4.35 1.17 to 1.51 <0.001
Driving under influence 0.20 0.20 −1.61 0.03 to 1.41 0.11
Sex assault 0.62 0.16 −1.88 0.37 to 1.02 0.06
Theft/robbery 1.52 0.10 6.17 1.33 to 1.73 <0.001
Drug offense 0.80 0.10 −1.83 0.63 to 1.02 0.07
Homeless 1.77 0.04 7.12 1.51 to 2.07 <0.001
Crack 1.21 0.09 2.45 1.03 to 1.40 0.01
Methamphetamine 1.24 0.10 2.61 1.06 to 1.46 0.01
Other drug 0.80 0.09 −1.97 0.64 to 1.00 0.05
Brief Psychiatric Rating Scale total 1.01 0.01 2.06 1.00 to 1.02 0.04
Length of stay 0.99 0.00 −4.68 0.99 to 1.00 <0.001
Schizophrenia × female gender 1.45 0.24 2.25 1.05 to 2.00 0.02
Schizophrenia × homeless 1.23 0.12 1.43 0.92 to 1.63 0.15

We found strong evidence that schizophrenia spectrum/BPAD and personality traits were associated with higher rates of return to custody, as was crack and methamphetamine use, and homelessness. Higher severity of mental illness measured using the BPRS-E was also associated with higher rate of return to custody, and charges of theft/robbery and breach of probation were positively associated with rate of return to custody. Gender was not directly associated with rate of return to custody; however, females who had schizophrenia/BPAD had a higher rate of return to custody as indicated by the significant interaction effect of these variables.

One-Year Cohort

There were 2,935 individuals in this cohort: 468 (15.6%) had 1 reincarceration, 141 (4.8%) had 2, and 36 (1.3%) had 3 or more (maximum was eight). We defined high-frequency users as having 3 or more incarcerations within a year (2 or more reincarcerations after release from jail within the same year). Two hundred and eleven (7.2%) were defined as high-frequency users, and they accounted for 783 (19.5%) of all reincarcerations.

In the multivariate model, we found that schizophrenia spectrum/BPAD was strongly associated with high-frequency incarceration (odds ratio [OR] = 2.88, 95% confidence interval [CI], 2.07 to 4.00), as was homelessness (OR = 1.81, 95% CI, 1.31 to 2.48). Having an index offense of assault was inversely associated high-frequency incarceration (OR = 0.60, 95% CI, 0.41 to 0.86, respectively, see Table 4).

Table 4.

Variables Predicting High-Frequency Reincarceration.

Variable Odds Ratio Standard Error z 95% CI P
Female gender 0.96 0.18 −0.21 0.67 to 1.38 0.833
Schizophrenia spectrum/bipolar affective disorder 2.88 0.48 6.32 2.07 to 4.00 <0.001
Personality disorder traits 1.12 0.27 0.49 0.70 to 1.80 0.63
Depression/anxiety 0.86 0.14 −0.91 0.62 to 1.19 0.37
Methamphetamine use 1.5 0.24 0.70 0.77 to 1.73 0.48
Homeless 1.81 0.09 3.66 1.31 to 2.48 <0.001
Assault 0.60 0.11 −2.76 0.41 to 0.86 0.01
Theft/robbery 1.26 0.22 1.32 0.89 to 1.76 0.19

Discussion

We found that within 1 year of incarceration, 23.1% were reincarcerated at least once and 7.2% had 3 or more incarcerations. A diagnosis of schizophrenia spectrum/BPAD was strongly and consistently associated with reincarceration. Those with schizophrenia/BPAD were around twice as likely to have subsequent reincarcerations as those without in our sample, after adjusting for other variables. These findings are in keeping with a large observational study of inmates released from prisons in Florida, which found that inmates with schizophrenia were twice as likely, and people with bipolar disorder were more than 3 times more likely to have 4 or more previous incarcerations.19 The reasons for the overrepresentation are likely multifactorial. First, there is likely to be a direct association between psychotic symptoms and offending.36 Second, persons with a psychotic illness may exhibit disorganized behavior, which may lead to breaches of conditions of release. Third, reduced access to services and housing may precipitate offending to secure resources. Fourth, substance abuse can both destabilize mental state and lead to related drug offenses or acquisitive offenses.

One important factor therefore is likely to be the inadequate treatment of symptoms of mental disorder among these groups. Treatment with antipsychotic medication has been shown to reduce offending3739 and reincarceration and cost,40 however, continuity of community care is severely fractured by incarceration often leaving those released from custody without access to treatment or support.41,42 We found evidence that severity of symptoms was associated with rate of reincarceration. However, we did not have data on the rate of provision of, or compliance with, treatment after release from custody, and therefore, future studies should measure access to treatment on release and its impact on reincarceration.

Substance misuse was also found to be significantly associated with reincarceration. This is consistent with prior studies that have linked substance use to offending and incarceration,13,43 however, not all diagnostic categories of mental disorder are necessarily equally associated with recidivism in combination with substance use.26 It is possible that the type of substances used may also have differential effects on rates of return to custody. Our study indicates that stimulant use—crack cocaine and methamphetamine—was particularly associated with reincarceration, while other drugs, notably cannabis and alcohol, were not. A previous study has shown that stimulant use is associated with a greater risk of violent recidivism as compared with other classes of substances.44 This finding needs further exploration and replication. However, it is possible that the effects of crack cocaine and methamphetamine have a particularly destabilizing effect in precipitating symptoms of mental illness leading to offending behavior and reincarceration.

We did not find an association between gender and rate of reincarceration although we found a significant interaction effect of female gender and schizophrenia. It is often observed that even higher rates of SMI exist among female inmate populations than among male populations.22 One study found that SMI status had a stronger impact on time to reoffense for women than for men. They found that in general, women with SMI had longer times to reoffend than men. Future studies should investigate the reasons for a gender difference and the specific needs of women prisoners with SMI.

We found that homelessness was associated with significantly higher rates of reincarceration and was significant in defining the high-frequency service user group while adjusting for other variables. The 2-way cycle of homelessness and jail has been well-documented.45,46 Incarceration has the effect of reducing employability and fragmenting relationships with family and social ties, while homelessness can lead to “crimes of desperation” and exposure to aggressive policing of trespass or vagrancy offenses. High rates of mental illness have also been found among homeless people,47,48 and thus, a 3-way “trans-institutionalization” is at play, exacerbated by a lack of affordable housing and drug addiction. Provision of supportive housing has been shown to reduce overall costs to mental health services12 and could well lead to a reduction in incarceration, particularly among high-frequency offenders who have SMI.

We found that offenses of breach of probation, theft, and robbery were associated with a higher rate of reincarceration. It appears that a pattern of relatively low-severity offenses characterizes those who frequently or rapidly return to custody. Although the individual circumstances and details of the behaviors that have led to the charges are not known, it is possible that theft may be at least in part be motivated by poverty, substance use, and marginalization among those with SMI. Breach of the terms of probation, such as failing to appear in court or to adhere to the terms of supervision, is also more likely among those who have unstable housing and who have symptoms of major mental disorder and who have inadequate community support, leading to reincarceration and a perpetuation of the revolving door phenomenon.

Limitations

There are a number of limitations to our study. First, we were only able to measure reincarceration among those who returned to either of two jails in which the FEIS service operates. Although all individuals who are reincarcerated go to a provincial jail in the first instance, it is possible that individuals may recidivate and be reincarcerated in other provincial jails of which we would have no knowledge. VCW is by far the largest provincial jail in Ontario for women, accounting for approximately 43% female inmates in Ontario, and is the only jail that covers the Greater Toronto Area and Southern Ontario. Thus, there is a very high likelihood that females released from VCW would be reincarcerated at this institution rather than a different one unless they moved to and reoffended at a geographically distant location. TSDC is also the largest provincial jail for men and accounts for approximately 75% of the remand space available in the Greater Toronto Area, making it highly likely that males released from TSDC would be reincarcerated there as well.

In addition, it is possible that inmates who are reincarcerated at either VCW or TSDC are not referred to the FEIS service, and therefore, their reincarceration would not be recorded in our data. All individuals are screened for mental health needs on reception into custody, and those previously under the caseload of FEIS are highly likely to be identified and rereferred. It is possible however that some individuals are not identified on a subsequent reincarceration, and their reincarceration would not be recorded in our data. Furthermore, it is possible that some inmates after being identified on screening and referred to FEIS for assessment would be released from jail prior to being assessed. Currently, FEIS receives an average of 348 referrals per month, and although the standard is to assess those referred on the same or next business day, 43% are released prior to assessment; thus, there would be an underdetection of brief returns to custody. Thus, we are only likely to have included those with incarceration of longer than 2 to 3 days. Although we were able to test a fairly comprehensive set of variables and interactions in our models, there are variables that are relevant that have not been measured, such as access to and utilization of community health services, quality of relationships and personal support, and caregiver responsibilities in the community, which may have greater relevance for women. In addition, many of the variables were taken from self-report and we were not able to confirm those details using collateral sources. Also, we have used the BPRS-E Scale which may not have been able to be completed among those who are most severely ill and less cooperative with intake assessment. Future studies should therefore investigate symptom severity more proximal to release and consider using alternative measures of illness severity such as Clinical Global Impression (CGI-C).49,50 Finally, the diagnostic categories we used in our study were taken from the Mental Health Issues section of the JSAT, and thus, we were unable to use DSM-5 diagnostic categories in our analyses. It is also likely that personality disorder traits were underdiagnosed in our sample due to diagnostic overshadowing of the other categories, and since a structured diagnostic tool was not used. Future studies should investigate more specific diagnostic groupings and symptoms in relation to reincarceration.

Summary and Future Direction

In summary, we have identified a group of high-frequency service users who account for a disproportionately high number of incarcerations and found that the most important predictors of return to custody among those with mental illness are a diagnosis of schizophrenia/BPAD disorder, homelessness, and crack cocaine or methamphetamine use, with offenses of theft or robbery. Identification of these frequent users could allow targeting resources which could reduce the frequency and rate of incarcerations in this group. Services designed to target resources at high-intensity users have been successful elsewhere,5,28,51 and there is promise for interventions that provide services to help bridge the transition from jail to the community.41,42,52 The primary targets of intervention appear to be effectively treating those with SMI, provision of stable housing, and treating those who have substance use problems, particularly those using stimulants.

Investment in specific transition and community services and careful evaluation of their efficacy is required to address the problems faced by people with SMI released from jail to reduce reoffending. Focusing on the high-frequency service users may have the biggest impact in reducing the total number of incarcerations. Studies should be designed to investigate the efficacy and economic impact of such an approach. In addition, persons with SMI are often incarcerated for relatively minor offenses including crimes of poverty, offenses related to use of illegal substances, or minor offenses against judicial orders, and therefore, alternatives to incarceration should be considered for these individuals where possible.

Footnotes

Authors’ Note: The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: RJ work was supported in part by an Academic Scholar Award from the University of Toronto.

ORCID iD: Roland M. Jones, MBChB, PhD, MSc, BSc, MRCPsych Inline graphic https://orcid.org/0000-0002-3335-4871

Alexander I. F. Simpson, MBChB, BMedSci, FRANZCP Inline graphic https://orcid.org/0000-0003-0478-2583

References

  • 1. Wodchis WP, Austin PC, Henry DA. A 3-year study of high-cost users of health care. CMAJ. 2016;188(3):182–188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Cohen SB, Yu W. The concentration and persistence in the level of health expenditures over time: estimates for the U.S. Population, 2008–2009. Statistical Brief #354; 2012. [Google Scholar]
  • 3. Lichtenberg P, Levinson D, Sharshevsky Y, Feldman D, Lachman M. Clinical case management of revolving door patients—a semi-randomized study. Acta Psychiatr Scand. 2008;117(6):449–454. [DOI] [PubMed] [Google Scholar]
  • 4. Botha UA, Koen L, Joska JA, et al. The revolving door phenomenon in psychiatry: comparing low-frequency and high-frequency users of psychiatric inpatient services in a developing country. Soc Psychiatry Psychiatr Epidemiol. 2010;45(4):461–468. [DOI] [PubMed] [Google Scholar]
  • 5. Johnston M, Monteith R. Commissioning for value: reducing the number of high intensity users of unscheduled services. 2015. [Accessed 23rd April 2020]. https://www.england.nhs.uk/rightcare/wp-content/uploads/sites/40/2016/11/casebook-blackpool-tackling-frequent-callers.pdf . [Google Scholar]
  • 6. Haywood TW, Kravitz HM, Grossman LS, Cavanaugh JL, Jr, Davis JM, Lewis DA. Predicting the “revolving door” phenomenon among patients with schizophrenic, schizoaffective, and affective disorders. Am J Psychiatry. 1995;152(6):856–861. [DOI] [PubMed] [Google Scholar]
  • 7. Martin MS, Dorken SK, Wamboldt AD, Wootten SE. Stopping the revolving door: a meta-analysis on the effectiveness of interventions for criminally involved individuals with major mental disorders. Law Hum Behav. 2012;36(1):1–12. [DOI] [PubMed] [Google Scholar]
  • 8. Oyffe I, Kurs R, Gelkopf M, Melamed Y, Bleich A. Revolving-door patients in a public psychiatric hospital in Israel: cross sectional study. Croat Med J. 2009;50(6):575–582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Surber RW, Winkler EL, Monteleone M, Havassy BE, Goldfinger SM, Hopkin JT. Characteristics of high users of acute psychiatric inpatient services. Hosp Community Psychiatry. 1987;38(10):1112–1114. [DOI] [PubMed] [Google Scholar]
  • 10. Goodpastor WA, Hare BK. Factors associated with multiple readmissions to an urban public psychiatric hospital. Hosp Community Psychiatry. 1991;42(1):85–87. [DOI] [PubMed] [Google Scholar]
  • 11. Mental Health Commission of Canada. Strengthening the case for investing in Canada’s mental health system: economic considerations. Ottawa, Canada: Mental Health Commission of Canada; 2017. [Google Scholar]
  • 12. Culhane DP, Metraux S, Hadley T. Public service reductions associated with placement of homeless persons with severe mental illness in supportive housing. Hous Policy Debate. 2002;13(1):107–163. [Google Scholar]
  • 13. Somers JM, Rezansoff SN, Moniruzzaman A, Zabarauckas C. High-frequency use of corrections, health, and social services, and association with mental illness and substance use. Emerg Themes Epidemiol. 2015;12:17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Teplin LA. The prevalence of severe mental disorder among male urban jail detainees: comparison with the epidemiologic catchment area program. Am J Public Health. 1990;80(6):663–669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Teplin LA, Abram KM, McClelland GM. Prevalence of psychiatric disorders among incarcerated women: I. Pretrial jail detainees. Arch Gen Psychiatry. 1996;53(6):505–512. [DOI] [PubMed] [Google Scholar]
  • 16. Simpson AI, McMaster JJ, Cohen SN. Challenges for Canada in meeting the needs of persons with serious mental illness in prison. J Am Acad Psychiatr Law. 2013;41(4):501–509. [PubMed] [Google Scholar]
  • 17. Kane E, Evans E, Mitsch J, et al. Police interactions and interventions with suspects flagged as experiencing mental health problems. Crim Behav Ment Health. 2018;28(5):424–432. [DOI] [PubMed] [Google Scholar]
  • 18. Fisher WH, Roy-Bujnowski KM, Grudzinskas AJ, Jr, Clayfield JC, Banks SM, Wolff N. Patterns and prevalence of arrest in a statewide cohort of mental health care consumers. Psychiatr Serv. 2006;57(11):1623–1628. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Baillargeon J, Binswanger IA, Penn JV, Williams BA, Murray OJ. Psychiatric disorders and repeat incarcerations: the revolving prison door. Am J Psychiatry. 2009;166(1):103–119. [DOI] [PubMed] [Google Scholar]
  • 20. Hall DL, Miraglia RP, Lee LW, Chard-Wierschem D, Sawyer D. Predictors of general and violent recidivism among SMI prisoners returning to communities in New York State. J Am Acad Psychiatry Law. 2012;40(2):221–231. [PubMed] [Google Scholar]
  • 21. Castillo ED, Fiftal Alarid L. Factors associated with recidivism among offenders with mental illness. Int J Offender Ther Comp Criminal. 2011;55(1):98–117. [DOI] [PubMed] [Google Scholar]
  • 22. Fazel S, Seewald K. Severe mental illness in 33,588 prisoners worldwide: systematic review and meta-regression analysis. Br J Psychiatry. 2012;200(5):364–373. [DOI] [PubMed] [Google Scholar]
  • 23. Baranyi G, Scholl C, Fazel S, Patel V, Priebe S, Mundt AP. Severe mental illness and substance use disorders in prisoners in low-income and middle-income countries: a systematic review and meta-analysis of prevalence studies. Lancet Global health. 2019;7(4):e461–e471. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Andrews DA, Bonta J, Wormith JS. The recent past and near future of risk and/or need assessment. Crime Delinq. 2006;52(1):7–27. [Google Scholar]
  • 25. Rezansoff SN, Moniruzzaman A, Gress C, Somers JM. Psychiatric diagnoses and multiyear criminal recidivism in a Canadian provincial offender population. Psychol Public Policy Law 2013;19(4):443–453. [Google Scholar]
  • 26. Wilson JA, Wood PB. Dissecting the relationship between mental illness and return to incarceration. J Crim Justice. 2014;42(6):527–537. [Google Scholar]
  • 27. Luciano A, Belstock J, Malmberg P, et al. Predictors of incarceration among urban adults with co-occurring severe mental illness and a substance use disorder. Psychiatr Serv. 2014;65(11):1325–1331. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Best D, Walker D, Aston E, Pegram C, O’Donnell G. Assessing the impact of a high-intensity partnership between the police and drug treatment service in addressing the offending of problematic drug users. Polic Soc. 2010;20(3):358–369. [Google Scholar]
  • 29. Steadman HJ, Scott JE, Osher F, Agnese TK, Robbins PC. Validation of the brief jail mental health screen. Psychiatr Serv. 2005;56(7):816–822. [DOI] [PubMed] [Google Scholar]
  • 30. Steadman HJ, Robbins PC, Islam T, Osher FC. Revalidating the brief jail mental health screen to increase accuracy for women. Psychiatric Services. 2007;58(12):1598–1601. [DOI] [PubMed] [Google Scholar]
  • 31. Graf M, Wermuth P, Hafeli D, et al. Prevalence of mental disorders among detained asylum seekers in deportation arrest in Switzerland and validation of the brief jail mental health screen BJMHS. Int J Law Psychiatry. 2013;36(3-4):201–206. [DOI] [PubMed] [Google Scholar]
  • 32. Nicholls TL. Jail Screening Assessment Tool (JSAT): guidelines for mental health screening in jails. Burnaby, BC: Mental Health, Law and Policy Institute, Simon Fraser University; 2005. [Google Scholar]
  • 33. Nicholls TL, Lee Z, Corrado RR, Ogloff JRP. Women inmates’ mental health needs: evidence of the validity of the jail screening assessment tool (JSAT). Int J Forensic Mental Health. 2004;3(2):167–184. [Google Scholar]
  • 34. Martin MS, Colman I, Simpson AI, McKenzie K. Mental health screening tools in correctional institutions: a systematic review. BMC Psychiatry. 2013;13:275. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Andersen PK, Gill RD. Cox’s regression model for counting processes: a large sample study. Ann Stat. 1982;10(4):1100–1120. [Google Scholar]
  • 36. Penney SR, Morgan A, Simpson AIF. Motivational influences and trajectories to violence in the context of major mental illness. J Interpers Violence. 2019. doi:10.1177/0886260519876719. [DOI] [PubMed] [Google Scholar]
  • 37. Igoumenou A, Kallis C, Coid J. Treatment of psychosis in prisons and violent recidivism. BJPsych Open. 2015;1(2):149–157. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Rezansoff SN, Moniruzzaman A, Fazel S, McCandless L, Somers JM. Adherence to antipsychotic medication and criminal recidivism in a Canadian provincial offender population. Schizophr Bull. 2017;43(5):1002–1010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Chang Z, Lichtenstein P, Langstrom N, Larsson H, Fazel S. Association between prescription of major psychotropic medications and violent reoffending after prison release. JAMA. 2016;316(17):1798–1807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Lin I, Muser E, Munsell M, Benson C, Menzin J. Economic impact of psychiatric relapse and recidivism among adults with schizophrenia recently released from incarceration: a Markov model analysis. J Med Econ. 2015;18(3):219–229. [DOI] [PubMed] [Google Scholar]
  • 41. Jarrett M, Thornicroft G, Forrester A, et al. Continuity of care for recently released prisoners with mental illness: a pilot randomised controlled trial testing the feasibility of a critical time intervention. Epidemiol Psychiatr Sci. 2012;21(2):187–193. [DOI] [PubMed] [Google Scholar]
  • 42. Lennox C, Senior J, King C, et al. The management of released prisoners with severe and enduring mental illness. J Forensic Psychiatry Psychol. 2012;23(1):67–75. [Google Scholar]
  • 43. Cloyes KG, Wong B, Latimer S, Abarca J. Time to prison return for offenders with serious mental illness released from prison: a survival analysis. Crim Justice Behav. 2010;37(2):175–187. [Google Scholar]
  • 44. Lamsma J, Cahn W, Fazel S. Use of illicit substances and violent behaviour in psychotic disorders: two nationwide case-control studies and meta-analyses. Psychol Med. 2019:1–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Gowan T. The nexus. homelessness and incarceration in two American cities. Ethnography. 2002;3(4):500–534. [Google Scholar]
  • 46. Metraux S, Culhane DP. Homeless shelter use and reincarceration following prison release. Criminol Public Policy. 2004;3(2):139–160. [Google Scholar]
  • 47. Folsom D, Jeste DV. Schizophrenia in homeless persons: a systematic review of the literature. Acta Psychiatr Scand. 2002;105(6):404–413. [DOI] [PubMed] [Google Scholar]
  • 48. Kuno E, Rothbard AB, Averyt J, Culhane D. Homelessness among persons with serious mental illness in an enhanced community-based mental health system. Psychiatr Serv. 2000;51(8):1012–1016. [DOI] [PubMed] [Google Scholar]
  • 49. Jones RM, Moscovici M, Patel K, McMaster R, Glancy G, Simpson AIF. The Clinical Global Impression-Corrections (CGI-C); 2019. [Accessed 23rd April 2020]. https://www.researchgate.net/publication/330482937_The_Clinical_Global_Impression-Corrections_CGI-C. [DOI] [PMC free article] [PubMed]
  • 50. Jones RM, Patel K, Moscovici M, McMaster R, Glancy G, Simpson AIF. Adaptation of the clinical global impression for use in correctional settings: The CGI-C. Front Psychiatry. 2019;10:687. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. NHS RightCare. Setting up a high intensity user service: an NHS right care resource pack; 2017. [Accessed 23rd April 2020]. https://www.england.nhs.uk/publication/high-intensity-user-service-resource-pack/
  • 52. Hopkin G, Evans-Lacko S, Forrester A, Shaw J, Thornicroft G. Interventions at the transition from prison to the community for prisoners with mental illness: a systematic review. Adm Policy Ment Health. 2018;45(4):623–634. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Canadian Journal of Psychiatry. Revue Canadienne de Psychiatrie are provided here courtesy of SAGE Publications

RESOURCES