Abstract
Purpose
This article describes the protocol for a Hybrid Type I cost-effectiveness and implementation study of interpersonal psychotherapy (IPT) for men and women prisoners with major depressive disorder (MDD). The goal is to promote uptake of evidence-based treatments in criminal justice settings by conducting a randomized effectiveness study that collects implementation data, including a full cost-effectiveness analysis.
Background
More than 2.3 million people are incarcerated in the United States on any given day. MDD is the most common severe mental illness among incarcerated individuals. Despite the prevalence and consequences of MDD among incarcerated populations, this study will be the first fully-powered randomized trial of any treatment for MDD in an incarcerated population.
Design
Given the politically charged nature of the justice system, advantageous health outcomes are often not enough to get an intervention implemented in prisons. To increase the policy impact of this trial, we sought advice from prison providers and administrators about outcomes that would be persuasive to policy-makers and defensible to the public. In this trial, effectiveness questions will be answered using a randomized clinical trial design comparing IPT plus prison treatment as usual (TAU) to TAU alone, with outcomes including depressive symptoms (primary), suicidality, and in prison functioning (enrollment and completion of correctional programs; disciplinary and incident reports; aggression/victimization; social support). Implementation outcomes will include cost-effectiveness; feasibility and acceptability of IPT to clients, providers, and administrators; prison provider intervention fidelity, attitudes, and competencies; and barriers and facilitators of implementation assessed through surveys, interviews, and process notes.
Keywords: Prisoners, prisons, major depressive disorder, implementation science, cost-effectiveness
1. Introduction
More than 2.3 million people are incarcerated in the United States on any given day1,2. Incarcerated individuals have high rates of mental health problems3. In fact, the three largest mental health treatment facilities in the United States are correctional institutions4.
Major depressive disorder (MDD) is the most common severe mental illness among incarcerated individuals3,5,6. A Bureau of Justice Statistics national survey of state prisoners found that 23.5% met criteria for MDD within the past 12 months, three times the national 12-month prevalence3. In addition to being the 4th specific leading cause of death and disability burden in the world7, MDD has serious consequences for prisoners. In-prison effects of MDD include dramatically increased risk for suicide8–10, dropout from correctional treatment programs11–14, rejection by other inmates15, inability to assertively protect oneself16, physical victimization by other inmates17, and aggressive acting out16. The impairment in social, family, and occupational functioning seen with MDD18 also has repercussions for individuals leaving prison as they try to re-integrate into their communities. In fact, MDD increases risk of return to correctional custody19–21.
Despite the prevalence and consequences of MDD, there has never been a fully powered randomized controlled trial (RCT) of any treatment (psychosocial or pharmacological) for MDD in an incarcerated population. The largest RCT to date (n = 38) was published by the first author in 201222. This is in contrast to the thousands of RCTs of treatments for individuals with MDD in the community (150 published in 2007 alone)23, which may reflect a political and societal ambivalence about investments in mental health for this population. The proposed study is the first fully-powered RCT of treatment for MDD in an incarcerated population.
Interpersonal psychotherapy (IPT) has proven effectiveness for MDD in many mental health treatment settings24–27. IPT also has potential for good uptake within prison systems because it (1) is effective in a group format22,28, (2) can be effectively delivered by counselors without advanced degrees28,29, and (3) addresses the life stressors, relationship challenges, and social isolation that are salient among prisoners with MDD30–33,34. This NIMH-funded R01 hybrid cost-effectiveness/implementation study: (1) evaluates the effectiveness of adding IPT for MDD to prison treatment as usual (TAU) relative to TAU alone among male and female prisoners from prisons in two states, and (2) collects descriptive implementation data, including a full cost-effectiveness evaluation, to inform subsequent implementation trials. There are few previous methodologically rigorous RCTs of mental health treatments for justice-involved individuals, and none addressing MDD. The integration of effectiveness, cost-effectiveness, and implementation outcomes in this trial make it noteworthy, as do prison-related implementation issues (e.g., the politically charged nature of decisions about resources for prisoners).
2. Method
This RCT (1) evaluates the effectiveness of IPT for MDD + TAU relative to prison TAU alone among a target population of 90 male and 90 female prisoners from multiple prisons across two states, and (2) collects descriptive implementation data, including a full cost-effectiveness evaluation, to set up subsequent implementation studies. Effectiveness outcomes include depressive symptoms, suicidality, and in-prison functioning (i.e., enrollment and completion of correctional programs [e.g., GED classes, domestic violence programs, job training]; disciplinary and incident reports; aggression/victimization; social support). Implementation outcomes include cost and cost-effectiveness, feasibility and acceptability of IPT to all stakeholders, prison provider intervention fidelity, prison provider attitudes and competencies, and barriers and facilitators of implementation assessed through surveys, interviews, and process notes.
The trial is funded by the National Institute of Mental Health. It is approved by Brown University’s Institutional Review Board as well as regulatory bodies overseeing prison research in both participating states. A three-member external Data Safety and Monitoring Board has been assembled to evaluate data and safety of study participants. The trial is registered at clinicaltrials.gov (NCT01685294).
2.1. Rationale for Hybrid Type I effectiveness-implementation study design
Clinical effectiveness trials evaluate the outcomes of an intervention delivered in real-world settings using real-world providers. Implementation trials compare strategies for improving the uptake, fidelity, or sustainability of interventions already shown to be effective35. Curran et al.36 have described how trials combining elements of clinical effectiveness and of implementation trials can be used to provide “more rapid translational gains, more effective implementation strategies, and more useful information for decision makers,” improving the speed and enhancing the public health impact of research (p. 217). Hybrid effectiveness-implementation studies vary in the degree to which they emphasize the test of intervention effectiveness (Hybrid Type I), the test of implementation strategy effectiveness (Hybrid Type III), or both (Hybrid Type II)36. A Hybrid Type I study, such as this one, provides a randomized test of a clinical intervention (i.e., rigorous effectiveness trial) while gathering descriptive information to guide future implementation efforts36,37. Hybrid Type I trials are appropriate when the clinical intervention appears likely to be effective using the new setting, population, or delivery method (in our case, IPT is a front-line treatment for MDD in many other populations and evidence from our pilot RCT suggests that it is likely to be effective among prisoners22) and when the clinical intervention provides minimal risk to study participants.
In this Hybrid Type I trial, effectiveness and cost-effectiveness questions will be answered using an RCT design and data including longitudinal interview, self-report, and medical and correctional records. Implementation questions include: (1) what are the facilitators/barriers to delivering IPT for MDD in prisons using existing prison counselors, and (2) how likely is IPT to be implemented in prisons, and (3) what implementation strategies might maximize the facilitators and overcome barriers to implementation? Implementation data will consist of stakeholder (i.e., prison provider, administrator) surveys at the beginning and end of the effectiveness trial, client acceptability surveys, cost data from facilities and providers, audiotapes of intervention sessions, process notes from study clinical supervisors’ meetings with study clinicians, expert ratings of intervention fidelity, and qualitative interviews with participating providers and other prison decision-makers. This data will provide a mixed-method, multi-stakeholder process evaluation of intervention training and delivery. To put it another way, in this Hybrid Type I study, participants are randomized to interventions (IPT or TAU) and there is a single implementation strategy38 being tested: provider training and supervision. Therefore, this trial is simultaneous an effectiveness/cost-effectiveness RCT and an implementation strategy open trial. Assuming that IPT is found to be effective in this trial, the subsequent implementation trial will provide all participants with IPT and will compare two (or more) implementation strategies using a randomized design.
2.2. Rationale for choice of study outcomes
Societal issues strongly affect choice of outcomes in prison and jail health intervention RCTs that aspire to have real-world impact. Despite pressing public health needs and responsibilities for incarcerated individuals, unlike most healthcare systems, the justice system (including prisons and jails) has a primary goal of public safety rather than public health39. The system’s public safety mandate is to protect the public from harmful behavior (such as crime) and to bring individuals who violate the law to justice40. However, federal statutes and ethical obligations41 mandating adequate medical treatment for individuals in the justice system give it a secondary public health responsibility, posing a problem of multiple (and occasionally competing) system goals39,42. That public health is a secondary goal can be seen even in prison mental health and substance use treatment research, the vast majority of which examines the effects of interventions on public safety outcomes (recidivism, arrest) only, ignoring health outcomes (e.g.,43–46).
Taxman and Belenko explain that a “dilemma about providing treatment to offenders is that the customers are people who have wronged society and who are being punished”39 (p. 190). Offenders are often considered lesser citizens47 and they have diminished civil liberties and responsibilities (i.e., limitations on voting, employment, public housing)39. These factors may affect the empathy of general society toward offenders39. The external community may debate whether offenders deserve evidence-based mental health care, and whether treatment services for offenders are essential or the responsibility of tax-payers39. Those who make decisions about what mental health treatments will be provided in prisons need to be able to defend their decisions to politicians, legislators, prosecutors, judges, and defenders, who may have different agendas and strong opinions, and in turn, these stakeholders have to be able to explain the decisions to the public39. Therefore, for results of an RCT to influence intervention adoption and sustainment in prisons, unlike RCTs in most populations, it is not usually enough to show that the intervention has advantageous health outcomes. Even sympathetic administrators and policy-makers have to defend treatment decisions in the wider political arena, which is often less sympathetic.
Given this larger societal context, we sought advice from prison providers and administrators about additional outcomes that would be persuasive to policy-makers and defensible to the public. These included reduced suicidality, disciplinary and incident reports, and aggression/victimization (each of these create hassle, cost, and liability risk for prisons), and increased enrollment and completion of correctional programs, such as GED classes, domestic violence programs, or job training programs. Cost-effectiveness (and particularly cost-offsets that may come from reductions in discipline reports, hospitalization, etc.) may be the most important outcome for eventual implementation: cost-benefit and reinvestment frames for justice-related issues test strongly with voters48.
2.3 Preliminary studies
Preliminary studies included two open trials29,49 and a pilot randomized trial22 of adaptations of IPT for women prisoners with MDD, as well as mixed method studies with study participants50 and prison providers51 about the treatment needs of prisoners with MDD. This research indicated that MDD treatment in prisons is needed. Prisoners enrolled in the three treatment trials had severe recurrent MDD, despite the fact that a majority were taking antidepressant medications. The median number of past depressive episodes was “too many to count.” Participants were young, primarily single, and poor. Other typically negative treatment indicators, including physical (81%) and sexual abuse (78%) histories and borderline (35%) and antisocial (45%) personality disorders, were common.
Our pilot trials also showed that group IPT for MDD was feasible and acceptable, and likely efficacious among women prisoners, and that prison participants and providers viewed it as relevant and important. After the first open trial demonstrated feasibility and acceptability49, the pilot randomized trial (n = 38)22 found that IPT resulted in lower depressive symptoms and greater decreases in interpersonal problems than did an attention-matched psychoeducation control condition. Pilot RCT findings were also notable because study treatment doses were small relative to the other services participants were receiving at the prison, including residential substance use treatment (for all women), individual mental health counseling (for some women), and antidepressant medications (for many women). In fact, IPT produced better MDD outcomes despite patterns of medication use and other mental health treatment that should have biased the study in favor of the control condition22. Pilot RCT procedures resulted in good treatment and study retention rates. Follow-up qualitative interviews and surveys with study participants50 indicated that participants viewed the interpersonal issues addressed in IPT as vital to their well-being and that a mean of 13 months after release from prison, they viewed IPT depression treatment as the most important treatment they received in prison. A survey of prison providers, administrators, and stakeholders (n = 17) indicated that they viewed treatment focused on relationship issues (IPT addresses relationship issues) as the most important kind of treatment for women to receive in prison (9.3 out of 10), with treatment for MDD coming as a close second (9.2 out of 10).
The second open trial29 also demonstrated that bachelor’s level prison counselors who are not licensed or license-eligible mental health professionals can deliver IPT adherently and competently. In many prisons, specialized mental health professionals (e.g., MSWs and PhDs) are in short supply. Therefore, after initially piloting group IPT using co-therapist teams consisting of non-specialist bachelor’s-level prison counselors and psychology postdoctoral fellows22,49 we explored an alternative task-shifting approach. We trained additional prison counselors who were not mental health treatment specialists. These counselors were re-entry workers (i.e., bachelor’s level counselors who helped to coordinate services and logistics for individuals leaving prison) and a bachelor’s level prison substance use counselor from women’s prisons in two states. These individuals were selected to determine whether counselors with bachelor’s degrees could deliver group IPT adherently and competently without cotherapists. Although the non-specialist counselors responded enthusiastically to the treatment, they asked for more detailed information on some treatment elements than was described in published IPT manuals52,53. We created a training manual that explained the essential elements of IPT in more detail and with less jargon for these counselors, with extensive input from them to make sure all sections were clear and simple to understand. Our second open trial (n =22) found that these counselors were able to conduct IPT adherently, competently, and effectively using the expanded training manual29. Based on these pilot studies, we designed the current trial to examine the effectiveness, cost-effectiveness, and implementability of IPT for MDD, delivered by prison counselors with a range of previous mental health treatment training, for men and women in prisons across two states.
2.4. Interventions
2.4.1. Rationale for IPT + TAU vs. TAU alone design
The purpose of the trial is to inform prison practice and policy. According to NIMH’s Road Ahead report, “policy makers need to know if a new program works better or costs less with similar effectiveness than what is currently available, or if it is better than doing nothing at all” (p. 10). In some cases, the important question for implementation is: “how much better is the new program than care-as-usual and at what cost?” (p 11).54 Furthermore, because external validity is such a salient concern in criminal justice settings, many, if not most, NIH-funded criminal justice R01s use TAU controls (i.e., MH094090, MH086232, MH088716, DA025943, DA027209, DA021174, DA018977). Because our goal is to design a study that is most relevant to prison policy decisions, we decided to employ a treatment as usual (TAU) control condition. In order to determine the naturalistic effects and costs of adding IPT to the prison setting, participants in both conditions can receive any other treatment available to them and we will not exclude participants receiving other treatment, including antidepressant medications. We will carefully characterize prison TAU separately for each condition as part of our effectiveness and cost analyses because it is likely that IPT participants will use less TAU. Because this is an intent-to-treat trial in a real-world setting, participants will not be discontinued from the active treatment phase or from the study for study treatment non-participation.
2.4.2
IPT + TAU participants will receive standard group IPT, as specified in the training manual and published IPT manuals52,53, in addition to prison TAU. IPT focuses on addressing recent life stressors in the context of building or better utilizing one’s social support network. IPT identifies a current interpersonal crisis in one of four areas (interpersonal conflict, life change, grief, social isolation) as the proximal trigger for the current depressive episode and addresses it by helping the individual to improve communication, change relationship expectations, or adapt to changes within the context of building or better utilizing a social support network52,53. This approach is relevant to the treatment needs of prisoners with MDD, for whom life stressors, relationship challenges, and social isolation are common and salient30–33,34. The therapeutic stance of IPT is active, goal-oriented, semi-structured, supportive, positive, present-focused, and conducive to skills acquisition. IPT participants will receive 20 90-minute group therapy sessions over 10 weeks and 4 individual (pre-group, mid-group, post-group, and maintenance) sessions. The maintenance session occurs 4 weeks after the post-group session. The individual sessions were used successfully in our pilot work and in other group IPT protocols53 to prepare patients to use the group effectively and to keep group members focused on their interpersonal goals.
2.5.2. TAU alone
Participants in this condition will be screened and offered referrals to prison mental health staff for TAU. Nationally, TAU for MDD within prisons typically consists of antidepressant medications (either tricyclics or SSRIs)55, with about 80% of inmates being treated for MDD in one large state being given antidepressants56. Compliance with these medications is reasonable (75–80%)55. Limited psychosocial treatment (e.g., psychoeducation, once-monthly check-ins with a mental health clinician) is available for some. Criteria for being offered prison mental health services (medications and/or psychosocial treatment) vary by facility. In addition, some prisoners with MDD choose not to receive any treatment because they do not find medications or the psychosocial intervention offered acceptable. . No one other than individuals employed by our studies currently provides IPT within participating facilities.
2.6. Power
Our pilot RCT indicated an effect size for IPT relative to psychoeducation of d = .70 (95% CI = .03 1.33) for depressive symptoms (Hamilton Rating Scale for Depression [HRSD] scores57) at the end of prison group treatment. Both treatments occurred in addition to prison TAU. In previous randomized trials, intent-to-treat effect sizes (Cohen’s d) of IPT relative to placebo for HRSD depression scores have been .4427 and .4358. Intent-to-treat effect sizes of IPT + medications vs. medications alone have been .3759 for depressive symptoms and .3560 and .7361 for dichotomous outcomes. This study is powered to detect an effect size at the lower end of the range of effect sizes of successful similar studies, or a d = .37. Using standard deviations from our pilot data, an effect size of d = .37 corresponds to a difference between conditions of 4.5 scale points (out of 54) on our depression symptom measure (HRSD). Given that non-inferiority limits for the Hamilton have been set at about 2.5 points62 and the NICE guidelines consider a 3-point difference between conditions to be the cutoff for clinical significance63, the 4.5 point difference is near the minimum clinically significant difference between groups.
After examining a range of plausible effect sizes and attrition rates (see Table 1), we decided to base our power analyses on a 10% attrition rate over the 6 months from baseline to 3-month follow-up. A 10% attrition rate is low compared to some studies, but reasonable in this study because: 1) Follow-up interviews take place inside prison; and 2) our previous treatment studies with prisoners have had 90%–100% rates of completion for 3–6 month follow-ups that took place in the community after prison release due to careful, diligent tracking of participants22,64. It is highly likely we can do at least that well with in-prison follow-up.
Table 1.
Ranges of plausible effect sizes and attrition rates to guide power and sample size calculations
Sample size required for 80% power | |||
---|---|---|---|
d = .34 | d = .37 | d = .40 | |
15% attrition | 227 | 192 | 165 |
10% attrition | 213 | 180 | 155 |
5% attrition | 202 | 171 | 147 |
Power for n = 180 | |||
---|---|---|---|
d = .34 | d = .37 | d = .40 | |
15% attrition | .71 | .78 | .84 |
10% attrition | .74 | .80 | .86 |
5% attrition | .76 | .82 | .88 |
2.7. Research sites and randomization
Study participants will be recruited from the women’s facilities and from men’s medium security facilities in two northeastern U.S. states. These facilities house the entire female state prison populations for both states, all the medium security men in one state, and part of the medium security men in the other state. Prisoner demographics and sentencing practices are similar between the two states. Treatment as usual for MDD between the two states is also similar, consisting mainly of medications with occasional psychosocial treatment. Because these services are similar to other state prison facilities nationally55, findings from this study are likely to be generalizable. To increase balance between conditions, randomization will be stratified by state and by sex (male or female).
2.8. Participants
Participants will be sentenced prisoners between the ages of 18 and 65 who are incarcerated in one of the participating prisons. Participants must also: (1) Meet DSM-IV-TR criteria for current primary (non substance-induced) MDD after at least 4 weeks incarceration and abstinence from substances. (2) Be likely to stay at their current facilities for at least 6 months, giving us time to complete the treatment and follow-up phases. Individuals who meet lifetime criteria for bipolar disorder or a primary psychotic disorder or who cannot understand English well enough to understand the consent form or assessment instruments when they are read aloud will be excluded. Virtually all men and women at participating prisons speak English. Consent forms will always be read aloud. We will also offer to read each questionnaire aloud.
We will take several steps to avoid coercion in the consent process. Prior to enrolling each participant in the research, research staff will fully explain the study procedures, risks, benefits, and alternatives. Research staff will emphasize that choosing to participate has no effect on the other services individuals will receive at the prisons or the terms or length of their confinement, and neither does choosing not to participate or withdrawing from the study. All reimbursements for participating will be commensurate with participants’ time required for participating in the research. Participants also complete a short (5-item) questionnaire covering basic elements of study participation, which research staff review with them to clarify any potential misconceptions.
2.9. Counselors
IPT counselors in the current study will be counselors employed at participating prisons, with a bachelor’s degree and at least one year of experience working with incarcerated individuals. As in our previous studies22,29,49, some study counselors will have advanced degrees in mental health fields with previous mental health treatment training, and some will not. Implementation outcomes, including treatment integrity (rated by independent raters), cost and time involved in the training, and any retraining/extra supervision required, will be collected as part of the training process. We will explore how these vary by provider mental health training. One of the implementation barriers for evidence-based mental health treatments in prisons is not having enough trained mental health providers to serve all the need51. Therefore, to explore whether a task-shifting approach is feasible and effective, this trial will explore intervention fidelity and outcomes obtained when bachelor’s level providers who are not mental health treatment specialists are used as service extenders, and whether they are more or less expensive when the supervisory time and effort to train them is taken into account.
The principal investigator, who is a certified IPT supervisor, will train counselors in IPT using the training manual, which has been elaborated for bachelor’s level prison counselors from other IPT training materials53,65 and pilot tested in our second open trial29. The 2-day training consists of reviewing the treatment rationale, concepts, materials, and strategies; audio-taped demonstrations; and live practice sessions along with feedback. The PI will serve as primary clinical supervisor for study counselors, with help from other trained IPT supervisors. As in our previous IPT studies, supervision throughout the study will involve weekly review of therapists’ audiotaped sessions, weekly individual phone consultation, and 2-hour in-person group meetings every 2 months. Because this trial examines real-world effectiveness and implementation, because it uses a group intervention, and because the trial is complex and the timeline tight, it is not practical to have study counselors complete IPT practice cases before treating study participants. Because some data suggest that novice IPT counselors improve significantly after their first IPT case66, we will explore differences in intervention fidelity and outcomes between each counselor’s first IPT group (when s/he is using IPT for the first time), and his/her subsequent groups.
2.10. Assessments
Participants will be assessed three times: pre-treatment, at the end of group (10–12 weeks later), and then at 3-month follow-up (about 6 months after intake; see Table 2). Participants will receive $10 US deposited into their inmate accounts for completion of the post-group and follow-up assessments. Assessments will take place in prison, will include structured interviews and self-report measures, and will be conducted by research assistants (RAs) with a BA or MA and experience working with individuals who are justice-involved and/or who have mental health problems. RAs will be trained in interviewer administered instruments at Brown’s Clinical Assessment and Training Unit. The PI and a clinical interviewing trainer will supervise the RAs. Assessments will be audio recorded and checked for interview fidelity and quality. Twice a month, assessment trainers will choose a recently recorded interview for all interviewers to rate to check reliability, provide ongoing training, and prevent rater drift. RAs will be blind to treatment assignment.
Table 2.
Schedule of assessments for prisoner participants
Measure | Intake | End of group treatment | 3-month follow-up |
---|---|---|---|
SCID | X | ||
Psychopathic Personality Inventory: Short Form (PPI-SF) | X | ||
Longitudinal Interval Follow-up Evaluation (LIFE) | X | X | X |
Hamilton Rating Scale for Depression (HRSD) | X | X | X |
Beck Scale for Suicide Ideation (BSS) | X | X | X |
Beck Hopelessness Scale (BHS) | X | X | X |
Correctional discipline, incident, and medical records | X | X | X |
Conflict Tactics Scale 2 (CTS2) | X | X | X |
Multidimensional Scale of Perceived Social Support (MSPSS) | X | X | X |
UCLA Loneliness Scale | X | X | X |
PTSD Checklist (PCL-C) | X | X | X |
Client Satisfaction Questionnaire - Revised | X |
2.10.1. Diagnosis and Screening
Participants will be asked for demographic information, arrest and sentencing history, and current psychiatric medications. The mood disorder module and psychotic screener from the Structured Clinical Interview for DSM-IV (SCID)67 will be used to determine diagnostic eligibility. During the follow-up period, the Longitudinal Interval Follow-up Examination (LIFE)68, a brief standardized interview, will be used to assess MDD diagnosis. Unlike the SCID, which provides only a cross-sectional measure, the LIFE tracks MDD severity and course over time. The LIFE uses Psychiatric Status Ratings (PSRs) to measure MDD severity (by number of diagnostic symptoms experienced) each week on a scale of 1 (asymptomatic) to 6 (incapacitated). MDD recovery is defined as a PSR of 1 or 2 for 8 consecutive weeks69. The LIFE is a well-validated, widely used retrospective measure, developed for longitudinal studies, which uses a systematic calendar-based inquiry method to cue recall.68 For example, the PSR method was used in NIMH’s Collaborative Depression Study and others with good interrater reliability70,71.
2.10.2. Effectiveness Outcomes. 1
Depressive symptoms (primary) will be assessed with the Modified 17-item Hamilton Rating Scale for Depression (HRSD)57, a well-validated and reliable72 17-item measure used extensively in MDD treatment studies73 and in our prison pilot studies. 2. Suicidality will be assessed with the Beck Scale for Suicide Ideation (BSS), a 21-item self-report questionnaire with excellent internal and interrater reliability74. The BSS assesses current suicide ideation. However, our experience has been that many individuals in prison under-report current suicide ideation because suicide watch in prison is unpleasant. Therefore, we will also assess weeks of suicide ideation during each follow-up period using the LIFE (past suicide ideation does not require mandatory reporting to the prisons), and we will also assess hopelessness, which is strongly related to suicidality, using the Beck Hopelessness Scale (BHS)75.,. BHS scores have been found to predict subsequent death by suicide76. 3. Most in-prison functioning variables (e.g., number of correctional programs begun, number of correctional programs completed, number of disciplinary and incident reports) will be assessed through self-report and cross-checked against correctional records. Aggression and victimization will be measured using the reliable and valid 39-item Conflict Tactics Scale 277 with adaptations to ask about incidents in relationships with anyone over the past 3 months, rather than only with romantic partners. Social support will be assessed with the reliable and valid 12-item Multidimensional Scale of Perceived Social Support (MSPSS)78,79 and the 10-item UCLA Loneliness Scale80. 4. Exploratory. Given growing evidence that IPT may be effective for posttraumatic stress disorder (PTSD)81, we will explore the effects of IPT on PTSD symptoms, which are common among prisoners, using the reliable and valid PTSD Checklist Civilian Version82
2.10.3. Implementation outcomes
4. Cost-effectiveness of group IPT and of TAU for MDD. Our grant accounting will capture the costs of the IPT providers as well as costs incurred to train and supervise them. We will track treatment received as part of TAU for the IPT + TAU and TAU conditions separately. Tracking the cost of TAU (both usual mental health treatment and associated medications) is easy because all prison medications and providers are paid through a single entity in each state. We will use budget data from these agencies to add fringe benefit and overhead costs to payroll costs and administrative overhead costs to contract provider costs. All costs will be converted to same-year dollars. Costs (and savings) in future years will be discounted to present value in the year of treatment initiation using the 3% discount rate recommended by the Panel on Cost-Effectiveness in Health and Medicine83. If IPT is effective at improving prisoner behavior, it may lead to earlier release for some offenders and a reduction in in-prison incidents that result in new charges that extend stays. We will capture budget data on average total cost per prisoner-day that can be used to evaluate any savings of this nature. We will exclude research costs because these would not be incurred if IPT were standard care.
5. Feasibility and acceptability of IPT to all stakeholders. We will track participant feasibility and acceptability parameters including rates of treatment attendance, rates of treatment completion, reasons for termination, and treatment satisfaction. 6. Provider parameters will include prison provider intervention fidelity and time/training required to achieve fidelity, number of providers who leave the prison systems during the study or who drop out of the study for other reasons and have to be replaced. We will use provider fidelity (i.e., adherence and competence) scales adapted from standard IPT fidelity scales84 in our pilot RCT for use in groups and in prisons. Two trained expert raters will review audiotaped sessions and will provide session-level fidelity ratings. 7. Prison provider and administrator attitudes and competencies (see Table 3). Assessments will include the Stakeholder Acceptability Survey (SAS), based on the “Awareness and Concern” and “Rogers’s Adoption Questions” items from Steckler (1992)85. The SAS will assess ease of delivering IPT, the perceived helpfulness of IPT, and level of enthusiasm for IPT. The SAS will also assess issues related to sustainability including whether or not respondents would continue to use IPT outside of research, how easily IPT integrates into their other clinical care, and their perception of the time versus benefit trade-off for getting trained to deliver IPT. We will also assess prison provider attitudes toward evidence-based practice using: (a) the revised Evidence-Based Practice Attitude Scale (EBPAS-50), which has good reliability and factorial validity86; (b) prison provider attitudes toward rehabilitation and punishment using an established measure adapted by Taxman from Cullen87–89; and (c) provider competencies using the reliable and valid Competency Assessment Inventory (CAI)90. The CAI evaluates the attitudes, knowledge, and skills needed to provide high-quality mental health care (e.g., learns and respects clients’ preferences about treatment, creates opportunities for clients to practice skills). These measures will be given to a variety of stakeholders, including prison study counselors, other prison mental health providers, and prison administrators. 8. We will examine barriers and facilitators of implementation using surveys, interviews, and process notes. We will use the Dimensions of Organization Readiness Revised (DOOR-R) survey91 to assess the perceived importance of intervention characteristics for implementation in these settings and how well stakeholders perceive that IPT fits each of these characteristics. We will also have brief structured interviews with prison stakeholders and study counselors. Finally, we will qualitatively analyze process notes from study meetings (including supervision sessions with study counselors, and comments on barriers and facilitators provided by fidelity raters) for information on implementation barriers and facilitators. This information will be used to determine which implementation strategy or strategies might best capitalize on facilitators and overcome barriers to implementation, so that we can test these strategies in a subsequent implementation trial.
Table 3.
Schedule of assessments for prison providers and administrators
Beginning of study | End of study | |
---|---|---|
Evidence-Based Practice Attitude Scale-50 | X | X |
Attitudes toward rehabilitation/punishment | X | X |
Competency Assessment Inventory | X | X |
Stakeholder Acceptability Survey | X | X |
Dimensions of Organizational Readiness | X |
2.10.4. Characterization of TAU (both conditions)
We will track psychopharmacological and psychosocial treatment received by participants (e.g., type, number of visits, dose, etc.) using the LIFE. We will cross-check this self-report data against correctional medical record review and report concordance.
2.11. Data Analysis
Primary analyses will be intent-to-treat and we will examine dose-response effects in secondary analyses. All primary tests will be two-sided with p=0.05. Descriptive statistics will include effect sizes and measures of clinical significance (i.e., number needed to treat; NNT) for all major comparisons. We will separate our primary hypothesis from the remaining hypotheses.
2.11.1. Missing data
We will employ multiple imputation to deal with missing data; this method takes into account the associations between observed variables and patterns of missingness92,93. We will also compare treatment conditions on rates of missingness and time to missingness. We will test whether baseline characteristics are associated with missingness. Finally, we will perform a sensitivity analysis in which we impute a return to baseline levels for missing data to determine the sensitivity of analysis results to missing data.
2.11.2. Preliminary analyses
We will examine the distribution of our key variables for skewness, variability, missing data, and outliers. Preliminary analyses will also compare participants from various prison facilities on demographic and background information, parameters of study treatment and TAU received, adherence and competence rates, and treatment response. We will also check for site effects with each specific hypothesis by including site as main effect in analyses. If site differences are non-significant, they will be removed. Analyses will adjust for baseline levels of dependent variables but will not test for or adjust for any other baseline differences between conditions that result from randomization. We will evaluate the effects of non-IPT treatment on study outcomes as well as the effects of randomization to IPT on use of non-IPT treatment in secondary analyses. Reliability of adherence and competence ratings for the current study will be assessed by computing intraclass correlation coefficients between raters of the scales. Both individual item correlations and total intraclass correlations will be calculated.
2.11.3. Analysis of effectiveness outcomes
Primary
We will test the hypothesis that, relative to TAU alone, IPT + TAU will result in lower depressive symptoms (HRSD scores) at post-treatment and follow-up, using hierarchical linear modeling (HLM) with baseline HRSD score as a covariate.
Secondary
Correcting for multiple comparisons, we will test the hypotheses that, relative to TAU alone, IPT+TAU will result in lower levels of suicidality (BSS scores, Beck Hopelessness Scale scores, weeks of suicide ideation) and better in-prison functioning, including separate tests for enrollment in more correctional programs, completion of more correctional programs, fewer disciplinary and incident reports, lower levels of aggression (CTS2 aggression score), lower levels of victimization (CTS2 victimization score), and higher social support (MSPSS scores)/less loneliness (UCLA Loneliness Scale scores). For normally distributed variables, analyses will use HLM with baseline scores as covariates. For count data, analyses will use Poisson-class regression methods94,95 (e.g., zero-inflated negative binomial regression) and will include appropriate tests for zero-inflation and over-dispersion. Baseline scores will be predictors in both continuous and zero-inflated models.
Exploratory
We will explore whether conditions differed in time to recovery from a depressive episode (defined as 8 consecutive weeks of a PSR of 1–2 on the LIFE69) using Cox regression. Growing evidence indicates that IPT may be effective for posttraumatic stress disorder (PTSD).81 Therefore, we will also explore the effects of IPT on PTSD symptoms, which are common among prisoners, using the PTSD Checklist Civilian Version82.
2.11.4. Analysis of implementation outcomes
Cost and cost-effectiveness
Treatment costs tend to be skewed with long right tails. Therefore, we propose to rely on regression analysis to estimate the mean and standard deviation of the cost difference between IPT + TAU and TAU alone. Popular methods for dealing with skewed cost data include Ordinary Least Squares on log of costs, alternative weighting approaches based on Generalized Linear Models or exponential conditional models (ECM) with log link, and survival models. We will use the Generalized Gamma Model96 which implements a consistent evaluation strategy of these competing methods. We will analyze costs separately by gender (and possibly facility size) because treatment needs tend to differ by gender and the larger facilities typically used to house men may benefit from cost-reducing economies to scale. If it seems helpful, we also are prepared to use Glick et al.’s97 improved parametric representation of cost data, for example in valuing depression costs.
We will use a comparative cost effectiveness (CE) analysis of IPT + TAU relative to TAU. The primary analysis will include costs related to IPT delivery but not development. Thus it will compare cost and quality of an operational program. Secondary analyses will evaluate training and supervision costs and estimate the budget impact of newly implementing IPT for MDD in a prison system. The primary effectiveness measure is the HRSD depression score with disciplinary infractions, suicidality, and possibly early release/added time as a result of in-prison infractions or completed prison programs as secondary measures. Following recommendations from the Panel on Cost-Effectiveness in Health and Medicine83 and Neumann98, baseline analyses will adopt a societal perspective, considering all economic costs regardless of source. We will also calculate cost per disciplinary infraction avoided from the state government’s perspective, excluding benefits to the prisoners. We describe our statistical plan for determining mean change in and standard deviations of these measures above.
The CE ratio equals ΔC/ΔE, where ΔC is the difference in mental health treatment costs between IPT + TAU and TAU alone and ΔE is the difference in the outcome measure. We will compute 95% confidence intervals around the CER and test the hypothesis that the ratio is greater than 1.0. In sensitivity analyses, we will examine the CER at 0%, 1% and 5% discount rates.
Other implementation outcomes (feasibility and acceptability of IPT to all stakeholders, prison provider intervention fidelity, prison provider attitudes and competencies, stakeholder perspectives on barriers and facilitators of widespread implementation) will be examined descriptively. Qualitative data (qualitative interviews, process notes) will be analyzed using thematic analysis.
2.11.5. Predictors/Personalization
This is one of a few RCTS of correctional mental health treatments to aim to recruit equal numbers of men and women to explore gender effects, despite recognition that clinical pictures of incarcerated men and women99,100, as well as costs associated with providing services in men’s and women’s facilities101, often differ. Given the importance of gender-responsive programming for offenders102, this study will explore gender as a moderator of the effectiveness and costs of IPT relative to TAU.
We will also conduct exploratory tests self-reported number of lifetime arrests, length of current sentence, psychopathy (assessed with the Psychopathic Personality Inventory: Short Form103), MDD severity and number of past depressive episodes, and SCID-II104 assessed Borderline and Antisocial personality disorders (BPD and ASPD) as moderators, with p < .01 to control for Type I error. We will also examine whether minority status moderates treatment outcome.
3. Summary and Discussion
There is a great need for effective mental health care for justice-involved individuals and a relative lack of research in this area to date. The need is especially acute for research evaluating intervention effects on mental health, rather than solely criminal justice, outcomes. This protocol describes a Hybrid Type 1 cost-effectiveness and implementation study of IPT for MDD among prisoners. Effectiveness, cost-effectiveness, and implementation data from this registered randomized trial will be published following the CONSORT guidelines. We anticipate that this study, conducted by a team that is experienced with, committed to, and enthusiastic about criminal justice research, will test the effectiveness of IPT for MDD in a prison population, will provide information about cost-effectiveness of this treatment relative to TAU alone, and will elucidate potential barriers and facilitators of implementation. This information will be used to help shape choice of implementation strategies38 to test in future implementation trials (which will provide randomized comparisons of the effectiveness of strategies to foster adoption, fidelity, and sustainment of IPT and other evidence-based mental health treatments in prisons), and to use in practice to implement IPT for MDD in prisons. This line of research will help provide a foundation to speed implementation of evidence-based treatments for a severe and prevalent disorder among this vulnerable, understudied population.
Pilot work leading up to this study22,29,49–51 indicated that: (1) treatment for MDD is needed in prisons, (2) group IPT for MDD was likely effective among female prisoners and was feasible and acceptable to them and to their providers; (3) IPT’s interpersonal approach made sense to prisoners and prison stakeholders and seemed important to them; and (4) non-specialist bachelor’s level prison counselors can deliver IPT adherently and competently. These preliminary studies have prepared us to successfully conduct a large, multi-component treatment trial that takes place in many prisons across two states, and incorporate cost, medical and correctional record, stakeholder survey and interview, expert rater, and process note data.
Innovative aspects of the trial include the exploration of the use of prison counselors who do not have specialty mental health training as mental health service extenders in prisons, and the goal of enrolling roughly equal numbers of men and women prisoners to allow us to explore gender-related treatment effects. Other design strengths are that the study includes stakeholder input at all phases; accommodates prison setting and provider training, needs, and preferences; works to foster an intervention that will be financially feasible, effective, available, and acceptable; works to demonstrate a method for providing high quality services at low cost; and examines factors related to personalization (i.e., it will be one of only a few prison RCTs to have a roughly equal gender ratio). The trial was designed to maximize practice and policy impact by addressing effectiveness, cost-effectiveness, and implementation questions simultaneously and by intentionally choosing outcomes that satisfy the needs of the public health community (i.e., depressive symptoms, other clinical outcomes) and that address implementation challenges in the larger social and policy context (e.g., the politically charged nature of decisions about resources for prisoners). That this trial (in 2015) is the first fully-powered MDD treatment trial for incarcerated individuals demonstrates some of these societal challenges.
Public attitudes toward offenders translate into arrest and sentencing laws (which govern how many people enter the justice system) and into funding for offender care (given that justice system budgets are set by state and local governments). Over the past 4 decades, these forces have worked against each other: justice-involved populations (including prisons, jails, probation, and parole) have expanded exponentially (1 in 36 U.S. adults is currently justice-involved105,106) and justice healthcare budgets and the formal and informal processes that should work together to support the health and rehabilitation of offenders have not kept up107. As a result, justice systems care for more people with fewer resources. Lack of resources translate into crisis-oriented environments, ongoing threat of high staff turnover, high caseloads, lack of services, and lack of time to coordinate services39,51 with less than optimal system-wide outcomes39,88,108–111. The vast majority of incarcerated individuals will leave prisons and jails and rejoin communities that will take on the costs of their untreated behavioral health conditions. The aim of this trial is to contribute knowledge relevant to discussions about the business case for public health, especially mental health, services for prisoners.
Acknowledgments
Funding. All authors’ participation in this research was funded by a grant from the National nstitute of Mental Health (NIMH; R01 MH095230; PI Johnson). NIMH did not participate in the design, collection, analysis, or interpretation of the data, the writing of the manuscript, or the decision to submit the manuscript for publication.
Footnotes
Competing interests. The authors have no competing interests.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Contributor Information
Jennifer E. Johnson, Email: Jennifer.Johnson@hc.msu.edu, Division of Public Health, Michigan State University College of Human Medicine, 200 East 1st St Room 332, Flint, MI 48503
Ted R. Miller, Email: miller@pire.org, Pacific Institute of Research and Evaluation, 11720 Beltsville Drive, Suite 900, Calverton, MD 20705
Robert L. Stout, Email: Stout@pire.org, Decision Sciences Institute, 1005 Main Street Unit 8120, Pawtucket, RI 02860
Caron Zlotnick, Email: Caron_Zlotnick@brown.edu, Butler Hospital and Brown University, 345 Blackstone Blvd, Providence, RI 02906.
Louis A. Cerbo, Email: Louis.Cerbo@doc.ri.gov, Rhode Island Department of Corrections, 39 Howard Avenue, Cranston, RI 02920
Joel T. Andrade, Email: jandrade@mhm-services.com, MHM Services, Inc. 110 Turnpike Road, Suite 308, Westborough, MA 01581
Shannon Wiltsey-Stirman, Email: Shannon.Wiltsey-Stirman@va.gov, National Center for PTSD, Dissemination and Training Division, 795 Willow Road (NC-PTSD 334), Menlo Park, CA 94025.
References
- 1.Carson E. Prisoners in 2014. Bureau of Justice Statistics (NCJ 248955); 2015. [Google Scholar]
- 2.Minton T, Zeng Z. Jail inmates at midyear 2014. Bureau of Justice Statistics (NCJ 248629); 2015. [Google Scholar]
- 3.James D, Glaze LE. Mental health problems of prison and jail inmates. Bureau of Justice Statistics Special Report (NCJ 213600); 2006. [Google Scholar]
- 4.Fields G, Phillips EE. The new asylums: Jails swell with mentally ill. American's jails face growing need to provide mental-health treatment. The Wall Street Journal. 2013 Sep 25; [Google Scholar]
- 5.Fazel S, Danesh J. Serious mental disorder in 23,000 prisoners: A systematic review of 62 surveys. Lancet. 2002;359:545–550. doi: 10.1016/S0140-6736(02)07740-1. [DOI] [PubMed] [Google Scholar]
- 6.Brinded P, Simpson AI, Laidlaw TM, Fairley N, Malcom F. Prevalence of psychiatric disorders in New Zealand prisons: A national study. Aust NZ J Psychiat. 2001;35:166–173. doi: 10.1046/j.1440-1614.2001.00885.x. [DOI] [PubMed] [Google Scholar]
- 7.Murray C, Lopez AD. Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study. Lancet. 1997;349:1436–1442. doi: 10.1016/S0140-6736(96)07495-8. [DOI] [PubMed] [Google Scholar]
- 8.Aharonovich E, Liu X, Nunes E, Hasin DS. Suicide attempts in substance abusers: Effects of major depression in relation to substance use disorders. Am J Psychiat. 2002;159:1600–1602. doi: 10.1176/appi.ajp.159.9.1600. [DOI] [PubMed] [Google Scholar]
- 9.Charles DR, Abram KM, McClelland GM, Teplin LA. Suicidal ideation and behavior among women in jail. J Contemporary Crim Justice. 2003;19:65–81. [Google Scholar]
- 10.Baillargeon J, Penn JV, Thomas CR, Temple JR, Baillargeon G, Murray OJ. Psychiatric disorders and suicide in the nation’s largest state prison system. J Am Acad Psychiatry Law. 2009;37:188–193. [PubMed] [Google Scholar]
- 11.Brady TM, Krebs CP, Laird G. Psychiatric comorbidity and not completing jail-based substance abuse treatment. Am J on Addiction. 2004;13:83–101. doi: 10.1080/10550490490265398. [DOI] [PubMed] [Google Scholar]
- 12.Hiller M, Knight K, Simpson D. Risk factors that predict dropout from corrections-based treatment for drug abuse. The Prison Journal. 1999;79(4):411–430. [Google Scholar]
- 13.Hickert A, Boyle SW, Tollefson DR. Factors that predict drug court completion and drop out: Findings from an evaluation of Salt Lake County's adult felony drug court. J Soc Serv Res. 2009;35:149–162. [Google Scholar]
- 14.Gray A, Saum CA. Mental health, gender, and drug court completion. Am J Crim Just. 2005;30:55–69. [Google Scholar]
- 15.Marcus D, Hamlin RJ, Lyons PM. Negative affect and interpersonal rejection among prison inmates in a therapeutic community: A social relations analysis. J Abnorm Psychol. 2001;110(4):544–552. doi: 10.1037//0021-843x.110.4.544. [DOI] [PubMed] [Google Scholar]
- 16.Varese T, Pelowski S, Riedel H, Heiby EM. Assessment of cognitive-behavioral skills and depression among female prison inmates. Eur J Psychol Assess. 1998;14(2):141–145. [Google Scholar]
- 17.Blitz C, Wolff N, Shi J. Physical victimization in prison: The role of mental illness. Int J Law Psychiat. 2008;31:385–393. doi: 10.1016/j.ijlp.2008.08.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Langlieb A, Guico-Pabia CJ. Beyond symptomatic improvement:assessing real-world outcomes in patients with major depressive disorder. The Primary Care Companion to the J Clin Psychiat. 2010;12(1):e1–e14. doi: 10.4088/PCC.09r00826blu. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Baillargeon J, Binswanger IA, Penn JV, Murray OW, Williams BA. Psychiatric disorders and repeat incarcerations: The revolving prison door. Am J Psychiat. 2009;166(1):103–109. doi: 10.1176/appi.ajp.2008.08030416. [DOI] [PubMed] [Google Scholar]
- 20.Skeem J, Louden JE, Manchak S, Haddad E, Vidal S. Social networks and social control of probationers with co-occurring mental and substance abuse problems. Law Human Behav. 2009;33(2):122–135. doi: 10.1007/s10979-008-9140-1. [DOI] [PubMed] [Google Scholar]
- 21.Benda BB. Gender differences in life-course theory of recidivism: A survival analysis. Int J Offender Ther. 2005;49:325–342. doi: 10.1177/0306624X04271194. [DOI] [PubMed] [Google Scholar]
- 22.Johnson JE, Zlotnick C. Pilot study of treatment for major depression among women prisoners with substance use disorder. J Psychiat Res. 2012;46(9):1174–1183. doi: 10.1016/j.jpsychires.2012.05.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Weinberger A, McKee SA, Mazure CM. Inclusion of women and gender-specific analyses in randomized clinical trials of treatments for depression. J Women's Health. 2010;19(9):1727–1732. doi: 10.1089/jwh.2009.1784. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Chambless D, Ollendick TH. Empirically supported psychological interventions: Controversies and evidence. Annu Rev Psychol. 2001;52:685–716. doi: 10.1146/annurev.psych.52.1.685. [DOI] [PubMed] [Google Scholar]
- 25.National Collaborating Centre for Mental Heath. Depression: The NICE guideline on the treatment and management of depression in adults, updated edition. British Psychological Society and The Royal College of Psychiatrists; 2010. [Google Scholar]
- 26.Hollon SD, Shelton RC. Treatment guidelines for major depressive disorder. Behav Ther. 2001;32(2):235–258. [Google Scholar]
- 27.Elkin I, Shea MT, Watkins JT, Imber SD, Sotsky SM, Collins JF, Glass DR, Pilkonis PA, Leber WR, Docherty JP, et al. National Institute of Mental Health Treatment of Depression Collaborative Research Program: General effectiveness of treatments. Arch Gen Psychiat. 1989;46:971–982. doi: 10.1001/archpsyc.1989.01810110013002. [DOI] [PubMed] [Google Scholar]
- 28.Bolton P, Bass J, Neugebauer R, Verdeli H, Clougherty KF, Wickramaratne P, Speelman L, Ndogoni L, Weissman M. Group interpersonal psychotherapy for depression in rural Uganda: A randomized controlled trail. JAMA. 2003;289(23):3117–3124. doi: 10.1001/jama.289.23.3117. [DOI] [PubMed] [Google Scholar]
- 29.Johnson JE, Williams C, Zlotnick C. Development and feasibility of a cell phone-based transitional intervention for women prisoners with comorbid substance use and depression. The Prison Journal. 2015;95(3):330–352. doi: 10.1177/0032885515587466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Keaveny M, Zauszniewski JA. Life events and psychological well-being in women sentenced to prison. Issues Ment Health Nurs. 1999;20(1):73–89. doi: 10.1080/016128499248790. [DOI] [PubMed] [Google Scholar]
- 31.Bleiberg KL, Markowitz JC. A pilot study of interpersonal psychotherapy for posttraumatic stress disorder. A J Psychiat. 2005;162:181–183. doi: 10.1176/appi.ajp.162.1.181. [DOI] [PubMed] [Google Scholar]
- 32.Holtfreter K, Morash M. The needs of women offenders: Implications for correctional programming. Women Crim Justice. 2003;14:137–160. [Google Scholar]
- 33.Bonner R, Rich AR. Psychosocial vulnerability, life stress, and suicide ideation in a jail population: A cross-validation study. Suicide Life-Threat. 1990;20(3):213–224. [PubMed] [Google Scholar]
- 34.Brown S, Day A. The role of loneliness in prison suicide prevention and management. J Offender Rehabilitation. 2008;47(4):433–449. [Google Scholar]
- 35.Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M. Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Admin Policy Ment Health. 2011;38(2):65–76. doi: 10.1007/s10488-010-0319-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Curran G, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: Combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217–226. doi: 10.1097/MLR.0b013e3182408812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Spillane J, Pareja AS, Dorner L, Barnes C, May H, Huff J, Camburn E. Mixing methods in randomized controlled trials (RCTs): Validation, contextualization, triangulation, and control. Educ Assess Evaluation Account. 2010;22(1):5–28. [Google Scholar]
- 38.Powell BJ, McMillen JC, Proctor EK, Carpenter CR, Griffey RT, Bunger AC, Glass JE, York JL. A compilation of strategies for implementing clinical innovations in health and mental health. Med Care Res Rev. 2012;69:123. doi: 10.1177/1077558711430690. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Taxman FS, Belenko S. Implementing evidence-based practices in community corrections and addiction treatment. New York: Springer; 2011. [Google Scholar]
- 40.Taxman FS, Piquero A. On preventing drunk driving recidivism: An examination of rehabilitation and punishment approaches. J Crim Justice. 1998;26(2):129–143. [Google Scholar]
- 41.US Department of Health and Human Services. The Surgeon General's call to action on corrections and community health. Rockville, MD: US Department of Health and Human Services, Office of Surgeon General; 2007. [Google Scholar]
- 42.Taxman F, Young DW, Fletcher BW. The National Criminal Justice Treatment Practices survey: An overview of the special issue. J Subs Abuse Treat. 2007;32(3):221–223. doi: 10.1016/j.jsat.2006.12.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Center for Effective Public Policy. A framework for evidence-based decision making in local criminal justice settings. 3. Washington: National Institute of Corrections; 2010. [Google Scholar]
- 44.Ringhoff D, Rapp L, Robst J. The criminalization hypothesis: Practice and policy implications for persons with serious mental illness in the criminal justice system. Best Pract Ment Health: An Int J. 2012;8(2):1–19. [Google Scholar]
- 45.Sateschi CM, Vaughn MG, Kim K. Assessing the effectiveness of mental health courts: A quantitative review. J Crim Just. 2011;39(1):12–20. [Google Scholar]
- 46.MacKenzie DL, Mitchell L, Wilson DB. The impact of drug treatment provided in correctional facilities. In: Leukefeld C, Gullotta TP, Gregrich J, Ramos JM, editors. Handbook of evidence-based substance abuse treatment in criminal justice settings. New York: Springer Science + Business Media; 2011. [Google Scholar]
- 47.Duffee DE, Carlson BE. Competing value premises for the provision of drug treatment to probationers. Crime Delinquency. 1996;42(4):574–592. [Google Scholar]
- 48.Pew Center on the States. National Research of Public Attitudes on Crime and Punishment. 2010 http://www.saferfoundation.org/files/documents/Pew%20Center%20--%20Public%20Survey%20Prison%20Pop.pdf.
- 49.Johnson JE, Zlotnick C. A pilot study of group interpersonal psychotherapy for depression in substance-abusing female prisoners. J Subst Abuse Treat. 2008;34(4):371–377. doi: 10.1016/j.jsat.2007.05.010. [DOI] [PubMed] [Google Scholar]
- 50.Johnson JE, Schonbrun YC, Nargiso JE, Kuo CC, Shefner RT, Williams CA, Zlotnick C. “I know if I drink I won’t feel anything”: Substance use relapse among depressed women leaving prison. Int J Prisoner Health. 2013;9(4):1–18. doi: 10.1108/IJPH-02-2013-0009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Johnson JE, Schonbrun YC, Peabody ME, Shefner RT, Fernandes KM, Rosen RK, Zlotnick C. Provider experiences with prison care and aftercare for women with co-occurring mental health and substance use disorders: Treatment, resource and systems integration challenges. J Behav Health Ser R. 2014 Mar 25;:1–19. doi: 10.1007/s11414-014-9397-8. [DOI] [PMC free article] [PubMed]
- 52.Weissman M, Markowitz J, Klerman G. Comprehensive guide to interpersonal psychotherapy. New York: Basic Books; 2000. [Google Scholar]
- 53.Wilfley D, MacKenzie KR, Welch RR, Ayres VE, Weissman MM. Interpersonal psychotherapy for group. New York: Basic Books; 2000. [Google Scholar]
- 54.National Institute of Mental Health. The road ahead: Research partnerships to transform services: A report by the National Advisory Mental Health Council's Workgroup on Services and Clinical Epidemiology Research. NIMH; 2006. [Google Scholar]
- 55.Baillargeon J, Contreras S, Grady JJ, Black SA, Murray O. Compliance with antidepressant medication among prison inmates with depressive disorders. Psychiatr Serv. 2000;51(11):1444–1446. doi: 10.1176/appi.ps.51.11.1444. [DOI] [PubMed] [Google Scholar]
- 56.Baillargeon J, Black SA, Contreras S, Grady J, Pulvino J. Anti-depressant prescribing patterns for prison inmates with depressive disorders. J Affect Disorders. 2001;63(1–3):224–231. doi: 10.1016/s0165-0327(00)00188-9. [DOI] [PubMed] [Google Scholar]
- 57.Hamilton Rating depressive patients. J Clin Psychiat. 1980;41(12 sec2):21–24. [PubMed] [Google Scholar]
- 58.Markowitz J, Kocsis JH, Fishman B, Spielman LA, Jacobsberg LB, Frances AJ, Klerman GL, Perry SW. Treatment of depressive symptoms in human immunodeficiency virus-positive patients. Arch Gen Psychiat. 1998;55(5):452–457. doi: 10.1001/archpsyc.55.5.452. [DOI] [PubMed] [Google Scholar]
- 59.Blom M, Jonker K, Dusseldorp E, Spinhoven P, Hoencamp E, Haffmans J, van Dyck R. Combination treatment for acute depression is superior only when psychotherapy is added to medication. Psychother Psychosom. 2007;76(5):289–297. doi: 10.1159/000104705. [DOI] [PubMed] [Google Scholar]
- 60.Reynolds CF, Miller MD, Pasternak RE, Fran E, Perel JM, Cornes C, Houck PR, Mazumdar S, Dew MA, Kupfer DJ. Treatment of bereavement-related major depressive episodes in later life: A controlled study of acute and continuation treatment with nortriptyline and interpersonal psychotherapy. Am J Psychiat. 1999;156(2):202–208. doi: 10.1176/ajp.156.2.202. [DOI] [PubMed] [Google Scholar]
- 61.Weissman MM, Prusoff BA, DiMascio A, Neu C, Goklaney M, Klerman GL. The efficacy of drugs and psychotherapy in the treatment of acute depressive episodes. Am J Psychiat. 1979;136(4B):555–558. [PubMed] [Google Scholar]
- 62.Szegedi A, Kohnen R, Dienel A, Kieser M. Acute treatment of moderate to severe depression with hypericum extract WS 5570 (St John’s wort): randomised controlled double blind non-inferiority trial versus paroxetine. Brit Med J. 2005;330:503. doi: 10.1136/bmj.38356.655266.82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Depression: Management of depression in primary and secondary care. 2004. NICE Guidelines. [Google Scholar]
- 64.Zlotnick C, Johnson JE, Najavits LM. Randomized controlled pilot study of cognitive-behavioral therapy in a sample of incarcerated women with substance use disorder and PTSD. Behav Therapy. 2009;40:325–326. doi: 10.1016/j.beth.2008.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Verdeli H, Clougherty K, Bolton P, Speelman L, Ndogoni L, Bass J, Neugebauer R, Weissman MM. Adapting group interpersonal psychotherapy for a developing country: Experience in rural Uganda. World Psychiat. 2003;2(2):114–120. [PMC free article] [PubMed] [Google Scholar]
- 66.Stewart MO, Raffa SD, Steele JL, Miller SA, Clougherty KF, Hinrichsen GA, Karlin BE. National dissemination of interpersonal psychotherapy for depression in veterans: Therapist and patient-level outcomes. J Consult Clin Psych. 2014;82(6):1201–1206. doi: 10.1037/a0037410. [DOI] [PubMed] [Google Scholar]
- 67.First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders: Patient Edition. New York: Biometrics Research Department; 1996. [Google Scholar]
- 68.Keller MB, Lavori PW, Friedman B, Nielsen E, Endicott J, McDonald-Scott NC, Andreasen NC. The longitudinal interval follow-up evaluation: A comprehensive method for assessing outcome in prospective longitudinal studies. Arch Gen Psychiat. 1987;44(6):540–548. doi: 10.1001/archpsyc.1987.01800180050009. [DOI] [PubMed] [Google Scholar]
- 69.Keller M. Past, present, and future directions for defining optimal treatment outcome in depression: Remission and beyond. JAMA. 2003;289:3152–3160. doi: 10.1001/jama.289.23.3152. [DOI] [PubMed] [Google Scholar]
- 70.Solomon D, Keller MB, Leon AC, Mueller TI, Shea MT, Warshaw M, Maser JD, Coryell W, Endicott J. Recovery from major depression: A 10-year prospective follow-up across multiple episodes. Arch Gen Psychiat. 1997;54:1001–1006. doi: 10.1001/archpsyc.1997.01830230033005. [DOI] [PubMed] [Google Scholar]
- 71.Warshaw M, Keller MB, Stout R. Reliability and validity of the longitudinal interval follow-up evaluation for assessing outcome of anxiety disorders. J Psychiat Res. 1994;28:531–545. doi: 10.1016/0022-3956(94)90043-4. [DOI] [PubMed] [Google Scholar]
- 72.Bech P. Rating scales for affective disorders: Their validity and consistency. Acta Psychiatrica Scandinavica. 1981;64(Suppl 295):11–101. [PubMed] [Google Scholar]
- 73.Keller M. Past, present, and future directions for defining optimal treatment outcome in depression: Remission and beyond. JAMA. 2003;289:3152–3160. doi: 10.1001/jama.289.23.3152. [DOI] [PubMed] [Google Scholar]
- 74.Beck A, Kovacs M, Weissman A. Assessment of Suicidal Ideation: The Scale for Suicidal Ideation. J Consult Clin Psych. 1979;47(2) doi: 10.1037//0022-006x.47.2.343. [DOI] [PubMed] [Google Scholar]
- 75.Beck A. Beck Hopelessness Scale. The Psychological Corporation; 1988. [Google Scholar]
- 76.Brown GK, Beck AT, Steer RA, Grisham JR. Risk factors for suicide in psychiatric outpatients: A 20-year prospective study. J Consult Clin Psychol. 2000;68:371–377. [PubMed] [Google Scholar]
- 77.Straus MA, Hamby SL, McCoy SB, Sugarman DB. The revised conflict tactic scales (CTS2) J Fam Issues. 1996;17:283–316. [Google Scholar]
- 78.Zimet GD, Dahlem NW, Zimet SG, Farley GK. The Multidimensional Scale of Perceived Social Support. J Pers Assess. 1988;52:30–41. [Google Scholar]
- 79.Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess. 1990;55:610–617. doi: 10.1080/00223891.1990.9674095. [DOI] [PubMed] [Google Scholar]
- 80.Russell D. The UCLA Loneliness Scale (Version 3): Reliability, validity, and factor structure. J Pers Assess. 1996;66:20–40. doi: 10.1207/s15327752jpa6601_2. [DOI] [PubMed] [Google Scholar]
- 81.Markowitz JC, Petkova E, Neria Y, Van Meter PE, Zhao Y, Hembree E, Lovell K, Biyanova T, Marshall RD. Is exposure necessary? A randomized clinical trial of interpersonal psychotherapy for PTSD. Am J Psychiat. 2015;172(5):430–440. doi: 10.1176/appi.ajp.2014.14070908. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Ruggiero KJ, Del Ben K, Scotti JR, Rabalias AE. Psychometric Properties of the PTSD Checklist-Civilian Version. J Traum Stress. 2003;16(5):495–502. doi: 10.1023/A:1025714729117. [DOI] [PubMed] [Google Scholar]
- 83.Gold M, Siegel JE, Russell LB, Weinstein MC, editors. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996. [Google Scholar]
- 84.Rounsaville BJ, O'Malley SS, Foley S, Weissman MM. Role of manual-guided training in the conduct and efficacy of interpersonal psychotherapy for depression. J Consult Clin Psych. 1988;56:681–688. doi: 10.1037//0022-006x.56.5.681. [DOI] [PubMed] [Google Scholar]
- 85.Steckler A, Goodman RM, McLeroy KR, Davis S, Koch G. Measuring the diffusion of innovative health promotion programs. Am J Health Promot. 1992;6(3):214–224. doi: 10.4278/0890-1171-6.3.214. [DOI] [PubMed] [Google Scholar]
- 86.Aarons G, Cafri G, Lugo L, Sawitsky A. Expanding the domains of attitudes towards evidence-based practice: The Evidence Based Practice Attitude Scale-50. Adm Policy Ment Health. 2012;39(5):331–340. doi: 10.1007/s10488-010-0302-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Cullen F, Fisher BS, Applegate BK. Public opinion about punishment and corrections. Crime Justice. 2000;27:1–79. [Google Scholar]
- 88.Friedmann P, Taxman FS, Henderson CE. Evidence-based treatment practices for drug-involved adults in the criminal justice system. J Subst Abuse Treat. 2007;32:267–277. doi: 10.1016/j.jsat.2006.12.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Taxman F, Cropsey KL, Melnick G, Perdoni ML. COD services in community correctional settings: An examination of organizational factors that affect service delivery. Behav Sci Law. 2008;26:435–455. doi: 10.1002/bsl.830. [DOI] [PubMed] [Google Scholar]
- 90.Chinman M, Young AS, Rowe M, Forquer S, Knight E, Miller A. An instrument to assess competencies of providers treating severe mental illness. Ment Health Serv Res. 2003;5(2):97–108. doi: 10.1023/a:1023281527952. [DOI] [PubMed] [Google Scholar]
- 91.Schoenwald S, Chapman JE, Kelleher K, Hoagwood KE, Landsverk J, Stevens J, Glisson C, Rolls-Reutz J The Research Network on Youth Mental Health. A survey of the infrastructure for children’s mental health services: Implications for the implementation of empirically supported treatments (ESTs) Adm Policy Ment Health. 2008;35:84–97. doi: 10.1007/s10488-007-0147-6. [DOI] [PubMed] [Google Scholar]
- 92.Little R, Rubin D. Statistical analysis with missing data. New York: John Wiley and Sons; 1987. [Google Scholar]
- 93.Allison PD. Missing data. Thousand Oaks, CA: Sage Publications; 2002. [Google Scholar]
- 94.Simons J, Neal DJ, Gaher RM. Risk for marijuana-related problems among college students: An application of zero-inflated negative binomial regression. Am J Drug Alcohol Ab. 2006;32:41–53. doi: 10.1080/00952990500328539. [DOI] [PubMed] [Google Scholar]
- 95.Walters G. Using Poisson class regression to analyze count data in correctional and forensic psychology: A relatively old solution to a relatively new problem. Crim Justice Behav. 2007;34(12):1659–1674. [Google Scholar]
- 96.Manning W, Basu A, Mullahy J. Generalized modeling approaches to risk adjustment of skewed outcomes data. J Health Econ. 2005;24(3):465–488. doi: 10.1016/j.jhealeco.2004.09.011. [DOI] [PubMed] [Google Scholar]
- 97.Glick H, Doshi JA, Sonnad SS, Polsky D. Economic evaluation is clinical trials. New York: Oxford University Press; 2007. [Google Scholar]
- 98.Neumann P. Using cost-effectiveness analysis to improve health care. New York: Oxford University Press; 2005. [Google Scholar]
- 99.Johnson JE, Friedmann P, Green TC, Harrington M, Taxman F. Gender and treatment response in substance-use treatment mandated parolees. J Subst Abuse Treat. 2011;40:313–321. doi: 10.1016/j.jsat.2010.11.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Johnson JE, Esposito-Smythers C, Miranda R, Justus AN, Rizzo C, Clum G. Gender, social support, and distress in criminal justice involved adolescents. Int J Offender Ther. 2011;55(7):1096–1109. doi: 10.1177/0306624X10382637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Rhode Island Department of Corrections. Population Report FY2009. 2010. [Google Scholar]
- 102.Center for Substance Abuse Treatment. Practical approaches in the treatment of women who abuse alcohol and other drugs. Rockville, MD: Department of Health and Human Services, Public Health Service; 1994. [Google Scholar]
- 103.Lilienfeld S, Andrews BP. Development and preliminary validation of a self-report measure of psychopathic personality traits in noncriminal populations. J Pers Assess. 1996;66:488–524. doi: 10.1207/s15327752jpa6603_3. [DOI] [PubMed] [Google Scholar]
- 104.First MB, Gibbon M, Spitzer RL, Williams JBW, Benjamin LS. Structured Clinical Interview for DSM Axis II Personality Disorders. New York: Biometrics Research Department; 1996. [Google Scholar]
- 105.Pew Center on the States. One in 31: The long reach of American corrections. Washington, DC: The Pew Charitable Trusts; 2009. [Google Scholar]
- 106.Kaeble D, Glaze L, Tsoutis A, Minton T. Correctional populations in the United States, 2014. Bureau of Justice Statistics Bulletin (NCJ 249513); 2015. [Google Scholar]
- 107.Travis J, Petersilia J. Re-entry reconsidered: A new look at an old question. Crime Delinquency. 2001;47:291–313. [Google Scholar]
- 108.Wolff N. Community reintegration of prisoners with mental illness: A social investment perspective. Int J Law Psychiat. 2005;28:43–58. doi: 10.1016/j.ijlp.2004.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Human Rights Watch. Ill-equipped: US prisons and offenders with mental illness. Washington, DC: Human Rights Watch; 2003. [Google Scholar]
- 110.VanderWaal CJ, Taxman FS, Gurka-Ndanyi MA. Reforming drug treatment services to offenders: Cross-system collaboration, integrated policies, and a seamless continuum of care model. J Soc Work Pract Addictions. 2008;8(1):127–153. [Google Scholar]
- 111.Daniel A. Care of the Mentally Ill in Prisons: Challenges and Solutions. J Am Acad Psychiat Law. 2007;35:406–410. [PubMed] [Google Scholar]