Safe by Design: An Exploration of Jail-Based Injury Across New York City
Publication: Journal of Correctional Health Care
Volume 28, Issue Number 3
Abstract
Research studies on injuries within the jail setting are few and far between. Perhaps the assumption that violent offending and violent victimization precede injury explains the limited attention. We suggest that there is a need for more empirical investigations that distinctly focus on jail-based injury. Using monthly correctional health metrics for New York City jail facilities between January 2017 and June 2019, we performed negative binomial regression modeling to explore the facility-level predictors of injury evaluation reports (IERs). Findings showed that youth-centric jails reduced the likelihood of IERs by 89% and health care-centric jails reduced the likelihood of IERs by 91%. Findings support the use of specialized facilities to mitigate injuries in jail. However, further examinations into the underlying mechanisms of specialized facilities that reduce injury are still required to meet the immediate needs of people who are incarcerated in jails.
Introduction
Approximately 2.2 million people are in jails and prisons across the United States, with jails accounting for a large proportion of people who are incarcerated. This remains relatively stable despite a yearly decline in the U.S. prison population since 2007 (Kaeble & Cowhig, 2018; Minton & Golinelli, 2014). Estimates reflect that the number of individuals held in jail has grown exponentially since the early 1980s, from approximately 200,000 to more than 740,000 people (Beck, 1991; Kaeble & Cowhig, 2018).
Furthermore, there are more than 10 million jail admissions per year, with an estimated 9 million being unique admittances—representing nearly 19 times more than the number of admissions to prison (Sawyer & Wagner, 2019). Today, stakeholders continue to discuss pathways to lower the overall jail population due to the harms associated with spending time in jail.
Harms of Confinement in Jail
In some instances, jails are gateways for deeper involvement in the criminal justice system, especially due to the collateral consequences attendant to even short lengths of stay (Heaton et al., 2017; St. John & Blount-Hill, 2019). Broadly, research also shows that life after incarceration is riddled with hardships for formerly incarcerated people in accessing employment (Travis & Visher, 2005), housing (Evans et al., 2019a, 2020; Leasure, 2019), education (Evans et al., 2019b), and relationship opportunities (Evans, 2019; Evans & Blount-Hill, 2020; Evans & Vega, 2021). Families also suffer from the experience (Blount-Hill et al., 2018; Geller et al., 2009; Miller, 2018; Wildeman & Western, 2010).
Moreover, research highlights that the experience of being jailed has an impact on physical well-being. For example, spending a few hours or days in jail contributes to poorer overall health (Subramanian et al., 2015). Researchers also describe the physical harms that take place in the jail setting, including (a) violence (Furst, 2017; Schwirtz & Minerip, 2015; Venters, 2019), (b) frequent victimization (Beck et al., 2010; Ellison, 2017; Ellison et al., 2018; Fox et al., 2013), and (c) injuries (Maruschak, 2006; New York City Board of Correction, 2019a; Ramdath, 2015; Sung, 2010).
That physical harm is associated particularly with jail stays is especially concerning considering that efforts to reduce incarceration sentences may shift the population of people held in prison to local jails (see Lofstrom et al., 2012). Increasing populations stretch the resources for local jails thin, increasing the odds of exposure to violent offending (intentionally committing physical harm), violent victimization (being a victim of intentional physical harm), and injury (being physically harmed) while in jail. Of these, injuries in jail have been the subject of relatively few empirical investigations outside the scope of studies on violence, and it is this physical harm we examine in this article.
Literature Review
Jail administrators are responsible for the provision of safety while people are held behind bars, a responsibility enshrined in both the Eighth Amendment to the U.S. Constitution (Gorlin, 2009; Struve, 2012) and international law (Lines, 2008; van Zyl Smit, 2010). This mandate places the prevention and mitigation of violent offending, violent victimization, and injuries of occupants under correctional officials' purview. Thus, the extent to which policies and practices geared toward the reduction of injuries are implemented requires as much focus as violent offending and violent victimization.
Although broader research on physical harm in jail reveals predictors of violent offending and violent victimization (Lahm, 2016, 2015; Steiner et al., 2017; Toman, 2019), research shows that injuries are not synonymous with violent offending or victimization, and that they have a distinct set of factors associated with their occurrence (Sung, 2010). Sung's (2010) investigation of injuries departs from correctional safety researchers' traditional focus on violent behavior and shifts the attention to injuries, whether related to violence or not.
This is important considering that research on violent offending and violent victimization within correctional institutions often omits whether cases of violence and victimization were injurious or not. Although studies of violent offending and violent victimization play a vital role in facilitating a safe correctional institution, a comprehensive understanding of correctional injuries is also crucial in creating safer correctional environments.
Correctional violence—or violence within correctional facilities—often morphs in definition, ranging from the act of physical or sexual assault to the threat or attempt to commit these actions.1 Violent offending and violent victimization have distinct risk factors, with researchers extensively teasing out the varying attributes that increase the odds of committing specific forms of violence (i.e., violent offending) and becoming a victim to specific types of violence (i.e., violent victimization) within the correctional setting (Cooley, 1993; Kerbs, 2007; Lee, 2016; Listwan et al., 2014; O'Donnell & Edgar, 1998; Toman, 2019; Wolff et al., 2009; Wooldredge & Steiner, 2013).
Akin to the empirical distinction between risk factors of violent offending and those of violent victimization, correctional injuries—distinguished from violence—require attention. Given that injuries within the correctional setting are not always a result of violence, such as accident-related injury (Maruschak, 2006), the subject of correctional injuries is an area worthy of further research.
Research on Jail Injuries
The Bureau of Justice Statistics found that 13.4% of people recently admitted to jail report being injured; 7.4% attribute the injury to an accident and 7.0% to a fight (Maruschak, 2006). Overall, 30% of people who served more than 1 year in jail reported an injury compared with 4% of people who served a week or less in jail. Males had higher proportions of injuries compared with females (14% and 10%, respectively); younger (≤24 years of age) compared with older (≥45 years of age) people had greater proportions of injury (17% and 8%, respectively) in jail; and people incarcerated on violent charges had higher proportions of injuries due to a fight (11%) compared with people incarcerated on nonviolent charges (5%–6%). This held true for injuries due to an accident.
A 2019 serious injury study by New York City's Board of Correction found a 101% increase in injury evaluation reports (IERs) by people incarcerated between 2008 and 2017 in the city's jails (from 15,629 to 31,368; New York City Board of Correction, 2019a). The stated causes of injuries included “inmate on inmate” altercations, accidents, officer use of force, self-inflictions, and combinations of them. Although identifying and addressing the factors associated with violence and violent victimization behind bars is one way to promote institutional safety, it is not enough for a comprehensive response to injuries given that all are not related to violence.
There are few rigorous empirical investigations into jail-based injuries. Notable exceptions in the past decade include Ludwig et al. (2012) and Sung (2010). Sung's study explored several risk factors associated with injuries within jails in the United States, both as result of an accident and of violence. His study showed that sociodemographic characteristics, criminal history, history of violent victimization, mental health history, aggression and hostility, physical and psychological impairment, daily routine, and prior incidents were all individual-level predictors of accident- or violent-related injuries.
Specifically, his study asserted a 16-factor list of individual-level characteristics that increased the odds of an accident- or violence-related injury: employment status before incarceration, detention status, prior arrests, having a violent charge, being a prior shooting or stabbing victim, substance dependence, recent history of mental health treatment, symptoms of delusion or hallucination in the past year, temper, alienation from friends and/or family in the prior year, having a learning disability, use of physical aids in daily activities, time spent in recreation, number of visits per week, engagement in educational programs since admission, and having a work assignment on jail grounds.
In the past decade, apart from Sung (2010), rigorous investigation on injuries in jails is limited to Ludwig et al.'s (2012) study, which examine injuries in the same setting as this study—New York City (NYC) jails.2 Findings illustrate that the top three leading causes of injuries by people in custody were “inmate on inmate aggression” (40% of all injuries), “slip and falls” (26%), and “use of force” by correctional staff (12%). Although the link between violence and injuries is clear, the finding that 32% of injuries were unintentional and that 26% were slip and falls supports the argument that injuries and violence within the correctional setting are distinct phenomena. However, Ludwig et al.'s (2012) study left a need for further investigations into the predictors of injuries because it was limited by a sole reliance on descriptive statistical analyses.
Collectively, the two studies referenced focus on individual-level characteristics, excluding facility-level characteristics that may predict the prevalence of all injuries in jail. This study aims to address this gap by investigating facility-level IERs to provide insight into potential predictors of jail-based injuries.
Specialized Facilities
This study takes a facility-level approach to understanding injuries, an approach emphasizing that all facilities are not constructed with the same purpose (Gill, 1962; St. John, 2020) and at times are designed to support specific outcomes for particular incarcerated populations (Blount-Hill & Blount-Hill, 2018; Kendig et al., 2019; St. John et al., 2019; Valera & Kates-Benman, 2016). Variation at the facility level presents a significant challenge for studies solely focusing on individual-level characteristics, which may not capture the important influence of facility type. The specialized facility is not often explored in research as a potential risk factor for injuries within the jail setting. This study begins to fill this void in research by exploring differing prevalence in jail-based injuries across specialized facilities.
Youth-Centric Facilities
The developmental differences between youth and adults are well documented in research. Among other things, youth differ from adults in both neurological development and psychosocial maturity (Arredondo, 2003; Fareri et al., 2008; Tottenham & Galván, 2016). These differences create a significant chasm in the cognitive ability and emotional regulation between the two groups.
Most humans do not acquire full maturation of their prefrontal cortex until age of 25, an area key to cognitive control and goal-directed behavior (Cauffman et al., 2018; Miller & Cohen, 2001). This process may be further delayed among people who have experienced or are experiencing trauma. Outcomes associated with developmental delay include poor reasoning skills, instant gratification, impulsiveness (Steinberg, 2007; Steinberg et al., 2008), sensation-seeking behavior (Steinberg et al., 2008), disregard for long-term consequences (Steinberg et al., 2009), and risk-taking propensities (Albert et al., 2013; Fareri et al., 2008; Gardner & Steinberg, 2005; Steinberg, 2008).
In response to the developmental differences between adults and youth, several NYC jail facilities are tailored toward adolescents (under age 18) and young adults (ages 18–21), including the Robert N. Davoren Complex, Horizon Juvenile Center,3 and George Motchan Detention Center. These facilities are established, in part, to comply with regulations that disallow adolescents from having “… sight, sound, or physical contact with any inmate 18 years old or more…” (City of New York, 2017, section 5-05 a).
Regulations also require that young adults be housed separately from others (City of New York, 2017; New York City Board of Correction, 2015). These rules act, in part, to prevent sexual harassment or abuse and resulting injuries, and to better address the needs of younger people who have offended.4 By reducing contact between adults and younger age cohorts, youth-centric facilities mitigate known contributing factors to injuries and thereby should lower injuries in the overall correctional population.
Health Care-Centric Facilities
NYC also has jail facilities dedicated to the unique needs of certain penal populations. Chronic medical issues, such as asthma, hypertension, and cervical cancer, are prevalent within jail and prison at higher concentrations when compared with the general public (Binswanger et al., 2012). Correctional health care is further complicated by variation in the needs of age-related subpopulations: (a) youth populations require more medical attention related to physical injuries (Maruschak, 2006) and (b) geriatric populations need more attention to aging-related and chronic conditions as well as environmental accommodations such as high beds or poor lighting (Baidawi & Trotter, 2016; Bedard et al., 2016).
Moreover, variations in medical needs are often not based on a single factor, and, in turn, the specific medical needs of those in custody are complicated by combinations of characteristics such as age, race, or sex and gender (Bronson et al., 2017; Marquis, 2018; Reviere & Young, 2004; Young & Reviere, 2006). When one also accounts for estimations of 10 to 12 million individuals cycling in and out of jail annually across the United States (McDonnell et al., 2014; Sawyer & Wagner, 2019), U.S. jails as a hub for large populations of people with health care needs requires full attention from stakeholders.
Some NYC facilities are tailored to address specific health care needs of people with geriatric and complex care needs, including the North Infirmary Command (NIC) and West Facility (WF). This includes people who have acute and chronic medical needs, those living with disabilities requiring medical aids for ambulation or breathing, and people requiring isolation due to contagious diseases. Others may be housed in the NIC or WF for short periods while recovering from an illness. Owing to the protective and recovery-focused nature of these housing facilities and more immediate access to health care professionals, people housed in health care-centric facilities may report less serious injuries than those housed in other jail facilities, accounting for a significant proportion of reported injury across correctional systems.
Research Questions and Hypotheses
Building on the review of literature, we derived this research question: What impact do facility-level characteristics have on the likelihood of persons being physically harmed while in jail? We hypothesize (H) that jail injury events are less likely to be reported in (H1) youth-centric jails when compared with non-youth-centric jails and (H2) health care-centric jails when compared with non-health care-centric jails.
Research Design and Method
Data and Sample
This study uses administrative data from all NYC jails between January 2017 and June 2019. Monthly observations for 13 facilities were gathered from reports produced by Correctional Health Services (CHS), an arm of the public Health and Hospitals Corporation that serves as the primary local correctional health authority (Glowa-Kollisch et al., 2014). In NYC, jails are in the community (i.e., borough-based jails) and on Rikers Island.
Therefore, the sampling frame of facilities includes all jails on Rikers Island (George Motchan Detention Center, Otis Bantum Correctional Center, George R. Vierno Center, Eric M. Taylor Center, Anna M. Kross Center, Rose M. Singer Center, Robert N. Davoren Complex, WF, NIC) and borough-based jails (Vernon C. Bain Center, Manhattan Detention Complex, Brooklyn Detention Complex).
Horizon Juvenile Center, a juvenile facility, is also included because New York's Department of Correction and CHS were legally responsible for this population during the study period and continued to report metrics related to this younger population. In addition, due to the closure of George Motchan Detention Center in June 2018 and the use of Horizon Juvenile Center for 16- and 17-year-old youth as of October 2018, the sample totaled 306 observations from all jails. Subsequent removal of observations missing key variables reduced the final sample to 234 observations. Appendix A1 provides a further description of each NYC facility.
Variables
The dependent variable in this article is the monthly count of documented IERs. IERs are conducted for each unscheduled clinical examination for an injured person in custody. This number serves as a proxy for injuries. It is important to note that our dependent variable measures the number of distinct events that led to an injury that resulted in a clinical examination. It is an event-level measurement and does not indicate distinct injuries that may be numerous in a single event (e.g., a fall down the stairs may involve separate injuries to the head, arms, and legs).
Facility-level independent variables explored in this article include factors that have been found predictive of injuries at the individual level such as age (see Sung, 2010). Age is a binary measure indicating whether a jail predominately houses adolescents (under 18 years of age) and young adults (people between the ages of 18 and 21) or adults (over age 21 years). Health care measures include a continuous number of scheduled medical services and a binary code for whether a facility is specifically designed for the extremely sick, that is, health care-centric (e.g., NIC and WF/Contagious Disease Unit [CDU]).
In addition, variables for seasonality (coded 0 to 3 for the four seasons), month (coded 0 to 11 for the 12 calendar months), and the calendar year are included to control for time and seasonality in the data set. Finally, facilities' average daily population (ADP) and a data “flag” representing each unique facility were included as control variables that may explain variation in injuries across facilities.
Analyses and Results
Sample Statistics
Sample statistics illustrate that monthly IER counts ranged from a minimum of 8 to a maximum of 743, with a DOC-wide rate of 32 IERs for every 100 people in custody. Figure 1 shows that three facilities had a rate of IERs above the DOC-wide rate (numbers are per 100 people in custody: George Motchan Detention Center (GMDC, 50 IERs), Robert N. Davoren Complex (RNDC, 43 IERs), and WF/CDU (54 IERs). Notably, when examining our facility types of interest, youth-centric facilities had higher rates of injuries compared with non-youth-centric facilities (rates of 43 and 27 per 100 people in custody, respectively). Health care-centric and non-health care-centric facilities held a similar relationship (41 and 30, respectively). Table 1 presents sample statistics for the variables of interest.
| Variables | Obs. | Mean | SD | Min | Max |
|---|---|---|---|---|---|
| Unique jail | 357 | 5.6 | 3.6 | 0 | 12 |
| Average daily population | 241 | 543 | 264 | 32 | 2,037 |
| Month | 357 | 5.9 | 3.4 | 1 | 12 |
| Season | 357 | 1.49 | 1.12 | 0 | 3 |
| Medical appointments | 349 | 581 | 629 | 6 | 4,728 |
| Health care-centric | 357 | 0.17 | 0.37 | 0 | 1 |
| Youth-centric | 357 | 0.17 | 0.4 | 0 | 1 |
| Injury evaluation reports | 301 | 204 | 138 | 8 | 743 |
N = 357 observations (obs.).
SD = standard deviation.
Analytical Models
All inferential statistical analyses were conducted using Stata statistical software. Analytical diagnostics of the variables showed that the outcome of IER was not normally distributed and significantly positively skewed toward zero, removing the option for parametric analytical tests (Fletcher et al., 2005). Overdispersion in the dependent variable also led to the decision to use negative binomial models, as well as the negative binomial model statistics ruling out the use of Poisson regression analyses and substantiating the fitness of the negative binomial model (Piza, 2012).
Variance inflation factor tests were used to shed light on issues around multicollinearity in the analytical models (Stine, 1995). Ultimately, statistical bootstrapping of standard errors was employed to safeguard against spatial correlation and the assumptions of independence among observations (Efron, 1981; Efron & Tibshirani, 1986; Guan, 2003). Table 2 displays the results of the negative binomial model with and without bootstrapping. The bootstrapped model—Model II—contains the end results of the study. Model I (the model without bootstraps) is presented in this article for analytical transparency.
| Model I | ||||
|---|---|---|---|---|
| Variable | IRR | SE | p | 95% CI |
| Unique jail | 1.086 | 0.037 | .017** | 1.015–1.162 |
| Average daily population | 1.000 | 0.000 | .001*** | 1.000–1.001 |
| Month | 1.001 | 0.004 | .828 | 0.991–1.010 |
| Season | 1.012 | 0.014 | .406 | 0.983–1.041 |
| Medical appointments | 1.000 | 0.000 | .395 | 0.999–1.000 |
| Health care-centric | 0.171 | 0.059 | .000*** | 0.086–0.339 |
| Youth-centric | 0.140 | 0.040 | .000*** | 0.079–0.247 |
| Model II (Bootstrapped Model) | ||||
|---|---|---|---|---|
| Variable | IRR | Bootstrap SE | p | 95% CI |
| Unique jail | 1.086 | 0.064 | .165 | 0.966–1.221 |
| Average daily population | 1.000 | 0.000 | .095 | 0.999–1.001 |
| Month | 1.001 | 0.004 | .822 | 0.991–1.010 |
| Season | 1.012 | 0.022 | .588 | 0.969–1.057 |
| Medical appointments | 1.000 | 0.000 | .644 | 0.999–1.000 |
| Health care-centric | 0.171 | 0.117 | .010** | 0.044–0.655 |
| Youth-centric | 0.140 | 0.044 | .000*** | 0.075–0.260 |
Model uses 1,000 bootstraps.
*
p < .05, **p < .01, ***p < .001. N = 234 observations. Prob ≥ chibar2 = 0.00.
CI = confidence interval; IRR, incidence rate ratio; SE = standard error.
Results
Model II statistics confirm the use of negative binomial analysis as opposed to Poisson modeling (Prob ≥ chibar2 = 0.00). Two independent variables yield a significant relationship with injury evaluation outcomes. Youth-centric jails compared with non-youth-centric jails decreased the odds of IERs by 86% (Incidence Rate Ratio [IRR] = 0.14, p = .000). Similarly, health care-centric jails compared with non-health care-centric jails decreased the odds of IERs by 83% (IRR = 0.17, p = .010). Table 2 illustrates the results of Model II. Both findings are aligned with the originally proposed hypotheses.
Post Hoc Analyses and Results
Several post hoc sensitivity analyses were conducted to determine whether any differences arise in our outcomes of interest when controlling for additional facility-level factors. These factors are whether a facility was designed to house women or care for those with mental health issues, or were smaller or larger in size. Women-centric jails encompassed one correctional facility dedicated to women in custody. Mental health-centric jails included jails tailored for people in custody with serious mental illnesses. Finally, we used the ADP to categorize a jail as small (ADP ≤500), medium (ADP 501–1,000), or large (ADP >1,000) relative to the local jail population. The minimum ADP within a given month was 32 and maximum 2,037.
Our initial results are further substantiated, with youth-centric jails having a decrease in the odds of IERs by 89% (IRR = 0.11, p = 0.00) compared with non-youth-centric jails, and health care-centric jails having a decrease in odds of IERs by 91% (IRR = 0.09, p = 0.00) compared with non-health care-centric jails. In Table 3, Model III comprises the analyses conducted without statistical bootstrapping, included for transparency, and the results of Model IV represent a bootstrapped model.
| Model III | ||||
|---|---|---|---|---|
| Variable | IRR | SE | p | 95% CI |
| Unique jail | 1.125 | 0.048 | .006** | 1.034–1.223 |
| Average daily population | 1.000 | 0.000 | .083 | 0.999–1.001 |
| Month | 1.002 | 0.004 | .599 | 0.993–1.012 |
| Season | 1.015 | 0.015 | .307 | 0.985–1.046 |
| Medical appointments | 1.000 | 0.000 | .291 | 0.999–1.000 |
| Health care-centric | 0.095 | 0.041 | .000*** | 0.040–0.223 |
| Youth-centric | 0.111 | 0.037 | .000*** | 0.057–0.215 |
| Women-centric | 0.956 | 0.537 | .937 | 0.318–2.875 |
| Mental health-centric | 0.637 | 0.254 | .260 | 0.291–1.394 |
| Size ≤500 | 0.494 | 0.326 | .286 | 0.135–1.803 |
| Size 501:1,000 | 0.380 | 0.221 | .097 | 0.121–1.189 |
| Size ≥1,001 | Omitted | Omitted | Omitted | Omitted |
| Model IV (Bootstrapped Model) | ||||
|---|---|---|---|---|
| Variable | IRR | Bootstrap SE | p | 95% CI |
| Unique jail | 1.125 | 0.107 | .217 | 0.932–1.357 |
| Average daily population | 1.000 | 0.001 | .556 | 0.998–1.002 |
| Month | 1.002 | 0.005 | .617 | 0.992–1.012 |
| Season | 1.015 | 0.019 | .407 | 0.979–1.053 |
| Medical appointments | 1.000 | 0.000 | .360 | 0.999–1.000 |
| Health care-centric | 0.095 | 0.084 | .008** | 0.016–0.544 |
| Youth-centric | 0.111 | 0.058 | .000*** | 0.039–0.311 |
| Women-centric | 0.956 | 0.559 | .940 | 0.304–3.009 |
| Mental health-centric | 0.637 | 0.237 | .228 | 0.306–1.324 |
| Size ≤500 | 0.494 | 0.894 | .697 | 0.014–17.127 |
| Size 501:1,000 | 0.380 | 0.585 | .530 | 0.018–7.758 |
| Size ≥1,001 | Omitted | Omitted | Omitted | Omitted |
Omissions due to high multicollinearity; model uses 1,000 bootstraps.
*
p < .05, **p < .01, ***p < .001. N = 234 observations. Prob ≥ chibar2 = 0.00.
Discussion
Two variables were found to be significant predictors of injury evaluations: whether a facility was health care-centric or youth-centric. Health care-centric facilities decreased the odds of injury evaluations by 91% and youth-centric facilities decreased the odds of injury evaluations by 89%, when controlling for facility population size, unique characteristics, and time of year (month, year, and season). The relationship held true when examining other specialized facilities. The findings in this article present initial support for the use of specialized facilities that focus on the health needs and/or developmental needs (as in the case of youth and young adults) to reduce injury event prevalence.
The significant findings in this article may also be a proxy for other elements. That is, health care-centric and youth-centric facilities may reduce injury evaluations not only because all incarcerated people with serious health problems are housed in a specific jail or because the majority of youth are concentrated in a given facility, but as a result of these facilities having more responsive correctional staff, less movement or routines that can lead to injury, more check-ins from clinicians, higher concentration of resources, or more people who are bedridden, less mobile, or already injured. Arguably, such factors could negate any spikes in unscheduled clinical attention (e.g., injury evaluations), meaning that the reductions in injuries observed in our analyses are products of these underlying factors.
Injuries in Jail
Findings from this study support the need for further investigations into the risk factors associated with the prevalence of injuries in the jail setting. This study examined the phenomenon at the facility level, and we call for future studies to also include individual-level predictors of injuries. At both the facility and individual level, researchers should consider the exploration of various causes of injuries, such as violence-induced injuries, accidental injuries, or self-inflicted injuries.
Moreover, future research should consider the prevalence of correctional officers, civilian staff, and visitor injuries broken out by victim characteristics (e.g., race) in the jail setting, especially given the extensive “touch” jails have with people due to overcriminalization and mass incarceration. In return, policies on institutional safety can be tailored to address the specific causes of injury for all occupants, and discussions on jail safety can be evidence based, parsing out the distinct relationships that exist with jail-based injuries.
Designing Out Injuries?
The relationships found between the youth-centric and health care-centric facilities share a common theme. These facilities were redesigned to attend to the needs of specific populations and, through the findings of this study, show promise for rethinking how facilities are designed to deal with vulnerable populations such as youth or the medically unwell. Although this study sought to explore the facility-level factors that influence injuries, such findings are well situated in research related to the relationship between correctional architecture and design on the experience of occupants (Jewkes, 2015; Moran & Jewkes, 2015; Morris & Worrall, 2014; St. John et al., 2019; Wener, 2012).
Further empirical investigations of jails in NYC through an architectural and design lens are still required to substantiate any claim that housing vulnerable populations outside of jail systems should remain a preferred option for reducing physical harm. However, as long as large jail populations and systems exist, the use of specially designated facilities may be best suited for the temporary well-being of youth and the medically unwell. Also, the attention placed on specially designed facilities should not replace or cause burden to the resources provided to other clinical strategies for improving health care, such as clinical staff trainings on dual loyalty (Glowa-Kollisch et al., 2014, 2015).
This study was limited by the range of variables within the data set for us to examine. A more robust analysis would attempt to incorporate other metrics that may account for fluctuations in injuries, such as risk scores or ratios of incarcerated people to staff. In addition, capturing only the facility-level variables does not allow us to investigate the nuances at the individual level that may factor into an individual being injured, such as daily routines, age, sex, gang involvement, or history of arrest.
Moreover, there were limitations with the dependent variable of injury evaluations. We could not examine types of injuries given our access to data and resources, which would better inform whether different types of injuries are predicted by differing factors. In fact, research shows that self-infliction was the fourth leading reason for injuries within NYC jails (Ludwig et al., 2012) and, more broadly, the predictors of self-harm encompassed exposure to solitary confinement, serious mental illness, being age 18 or younger, and being Latino or White (Kaba et al., 2014). This is an additional testament to the need for similar studies to parse out the specific types of injuries. Finally, injury evaluations are not distinguished by the number of unique injuries, allowing for multiple evaluations for the same injury.
The data used in this article may also contain some degree of reporting error given that under, over, and inaccurate reporting or recall error are possibly present in self-reports (Hindelang et al., 1979; Kubiak et al., 2018; Walsh et al., 2012). This has implications for administrative data sets that are constructed, in part, on the forthcoming behaviors of others (e.g., the person in custody disclosing their injury).
Injuries within jail are not exempt from this limitation. For example, research highlights that upon a closer examination of injuries reported as an accident or unintentional in jail, these events are at times incorrectly reported because people in custody may feel intimidated to disclose the true cause of the injury (MacDonald et al., 2015). Although this study does not tease out the specific types of injuries reported, the misclassification of the causes of injuries support that some degree of reporting error may be present in the CHS data.
Future Studies
Although several variables one might think predict injuries were either statistically insignificant in this study or nonexistent due to limitations in the data, researchers should still consider these variables in future studies until the empirical investigations into injuries in jails replicate similar findings. In addition, given the limited prior literature and reliance on facility-level variables in this study, future research should explore the nature of these specific types of facilities—namely the youth- and health care-centric facilities. This includes incorporating more measures such as staffing, facility culture, individual-level factors, and other possible explanatory elements of these facilities.
The use of qualitative data holds the potential to unpack the elements behind the specialized facilities that are influencing the observed outcomes. Qualitative data may also help address the concerns on the false reporting that may lead to the improper classification of injuries in the jail setting. MacDonald et al. (2015) highlight the need to review the underlying clinical notes and documentation to ensure that the reported injury aligns with the other medical facts.
Data collection efforts of future studies can also be tailored to include the specific reasons for an injury, going beyond this study's definition of injury and broadening the scope of definitions in previous literature from accident-related injury or fight-related injury to specifications on what constitutes an accident. All in all, future research on the physical harms that occur in jail will explore the factors that allow for the perpetuation or prevention of violent offending, violent victimization, and injuries at the facility- and individual-levels, while accounting for the jails assigned and designed for specific populations.
Acknowledgments
We extend our gratitude to the New York City Board of Correction and Correctional Health Services' staff members for their monitoring, public reporting, and data transparency that allowed this study to be possible. We also thank the peer reviewers and editors of the Journal of Correctional Health Care for their thoughtful and meticulous feedback.
Footnotes
1
2
To be clear, this gap in jail-based injury research does not apply to investigations that focus on factors that influence specific types of injuries, such as self-inflicted injuries (see Kaba et al., 2014, on self-harm in NYC jails) or traumatic brain injuries (see Ramdath, 2015, on traumatic brain injuries in NYC jails), but instead emphasizes the absence of a comprehensive investigation into all injuries within the correctional setting.
3
Although Horizon Juvenile Center is technically a juvenile detention facility, during the study period youth under the custody of NYC Department of Correction and care of Correctional Health Services were transferred there in accordance with Raise the Age legislation.
4
New York City's Department of Correction was not consistently in full compliance with the regulation that prohibits young adults from being housed with adults, and thus there have been cases where young adults are housed outside of youth-centric facilities and with adults in other jails (New York City Board of Correction, 2019b).
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Appendix
| Facility | Description |
|---|---|
| AMKC | Completed in 1978, and named for DOC's second female commissioner, AMKC houses male detainees in a facility spread over 40 acres. It includes a methadone detoxification unit. |
| BKDC | Built on Atlantic Avenue in 1957, the facility housed male detainees, most of whom were undergoing the intake process or awaiting trial in Kings County (Brooklyn) and Richmond County (Staten Island) courts. BKDC was closed in 2020. |
| EMTC | Built in 1964 and expanded in 1973, EMTC houses males sentenced to terms of 1 year or less. Most of its housing is dormitory style. Previously designated the Correctional Institution for Men, the facility was renamed on July 14, 2000, in honor of a retired chief of department. |
| GMDC | Opened in 1971 as the Correctional Institution for Women, the jail became a male detention center with the 1988 opening of the Rose M. Singer Center for women and was renamed in memory of a 17-year veteran corrections officer fatally shot in the line of duty. GMDC was closed in 2018. |
| GRVC | Opened in 1991 and expanded in 1993, GRVC was named after a deceased retired chief of department and acting commissioner. |
| HOJC | ACS, in conjunction with DOC, administers a specialized juvenile detention facility at Horizon Juvenile Center, in the Mott Haven section of the Bronx. The facility is designed for housing pre-Raise the Age youth. These are youth who are housed in the juvenile system but fall under the old law and are prosecuted in the adult criminal system. |
| MDC | This lower Manhattan command consists of two buildings designated the North and South Towers, connected by a bridge. The North Tower was opened in 1990. The South Tower, formerly the Manhattan House of Detention, or the “Tombs,” was opened in 1983, after a complete remodeling. The complex houses male detainees, most of them undergoing the intake process or facing trial in New York County (Manhattan). |
| NIC | Consists of two separate buildings, one of them the original Rikers Island Hospital built in 1932. It houses people in custody who have acute medical conditions and require infirmary care and those who have a disability that requires housing compliant with the Americans with Disabilities Act. NIC also houses some general population detainees. |
| OBCC | Opened in June 1985, it was completed in less than 15 months using modern design and construction methods. OBCC has dormitory and cell housing. The jail was named for its second warden. |
| RMSC | Opened in June 1988 as a facility for female detainees and women sentenced to a year or less. Subsequently, modular housing was added. In 1985, the DOC opened the nation's first jail-based baby nursery at the old Correctional Institution for Women featuring an expanded 25-bed nursery. It was named for an original member of the New York City Board of Correction. |
| RNDC | Opened in 1972, the jail was renamed in May 2006 in honor of a former chief of department. |
| VCBC | A five-story jail barge built in New Orleans to DOC specifications, the facility houses medium to maximum security detainees. Opened in the fall of 1992, it is named for a former warden who died in a car accident. It serves as the Bronx facility for intake processing. |
| WF/CDU | Opened in the fall of 1991, WF was constructed of “Sprungs”—rigid aluminum framed structures covered by a heavy-duty plastic fabric. The facility includes single-cell units, some of which make up the DOC's CDU. Other cells house detainees separate and apart from the CDU. |
This table is based on information gleaned from the following websites: New York City Department of Correction. Facilities Overview—https://www1.nyc.gov/site/doc/about/facilities.page; Administration for Children's Services. Secure Detention—https://www1.nyc.gov/site/acs/justice/secure-detention.page.
HOJC is not listed on the DOC website, but during the study period, the population of youth held in HOJC were under the authority of DOC and CHS.
AMKC, Anna M. Kross Center; BKDC, Brooklyn Detention Complex; EMTC, Eric M. Taylor Center; GMDC, George Motchan Detention Center; GRVC, George R. Vierno Center; HOJC, Horizon Juvenile Center; MDC, Manhattan Detention Complex; NIC, North Infirmary Command; OBCC, Otis Bantum Correctional Center; RMSC, Rose M. Singer Center; RNDC, Robert N. Davoren Center; VCBC, Vernon C. Bain Center; WF/CDU, West Facility /Contagious Disease Unit.
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Journal of Correctional Health Care
Volume 28 • Issue Number 3 • June 2022
Pages: 179 - 189
PubMed: 35352990
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Published online: 2 June 2022
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