ABSTRACT

General strain theory posits that individuals commit crimes when they experience negative emotions following various sources of strain. One such source of strain is poverty. In this study, researchers use focus group data and apply a general strain framework to analyze criminal offending during the Missouri Community Action Network's Poverty Simulation^© (2022) at a regional comprehensive university in the Southeast region of the United States. A total of 99 undergraduate and graduate students participated in the focus groups at the end of the simulation. Findings support Agnew’s (1992) theory with examples of sources of strain stemming from poverty leading to adverse emotional reactions and, at times, resulting in criminal responses that were economic. Participants noted the poverty simulation was a credible exercise that contributed to participant empathy. Implications within criminal justice and criminology education and future research are discussed.

Keywords: Poverty; simulation; general strain theory; college students

According to the U.S. Census Bureau, the official poverty rate in 2020 was 11.4%, resulting in 37.2 million Americans living below the poverty line (Shrider et al., 2021). This demonstrates the first increase in the poverty rate following five consecutive annual declines (Shrider et al., 2021). Poverty rates fluctuate with the economy and tend to increase during periods of recession (Chaudry et al., 2016). As such, the economic impact of COVID-19 and the resulting recession (Fernandes, 2020; Shrider et al., 2021) will likely result in higher poverty rates.

Previous research suggests that there is a link between poverty and crime. Indeed, prominent criminological theories, such as social disorganization theory (Shaw & McKay, 1942) and strain theory (Merton, 1938), focus on economic disadvantage's impact on criminal offending. At the macro level, poverty is a consistent and strong predictor of crime rates (Pratt & Cullen, 2005) and appears to influence both violent and property offenses. Using data from 121 U.S. cities, Lee (2000) concluded that city-level poverty significantly predicted homicide rates. Furthermore, Pearlman and colleagues (2003) determined that poor neighborhoods had the highest rates of police-reported domestic violence, while Kelly (2000) found that higher poverty rates significantly increased property crimes, especially burglary and larceny.

Poverty also appears to affect criminal offending at the micro-level. As evidence, Hay et al. (2007) found that family poverty increased juvenile delinquency, and this was especially true for families residing in poor communities. Furthermore, children experiencing long-term poverty were 79% more likely to engage in persistent offending in early adolescence compared to children who did not live in poverty (Hay & Forrest, 2009). Additionally, experiencing poverty in childhood may be associated with a higher likelihood of arrest in adulthood (Nikulina et al., 2011). Still, most individuals living below the poverty line do not engage in crime (Delgado, 1985; Green, 2010); therefore, it may not be poverty that leads to criminal behavior. Utilizing general strain theory (Agnew, 1992), the current study uses qualitative data from focus groups composed of undergraduate and graduate students who participated in the Missouri Community Action Network’s Poverty Simulation^© (2022) to explore the relationship between poverty as a source of strain and justifications for criminal offending.

General Strain Theory

Merton’s (1938) concept of anomie is a purely economic phenomenon that involves a disjuncture between conventional goals and legitimate means. Agnew (1992), however, deviated from the conceptualization of strain as a structural condition and expanded upon Merton’s (1938) theory to include three sources of strain: (1) the failure to achieve positively valued goals, (2) the presence of noxious stimuli, and (3) the removal of positive stimuli. Yet, only some strained individuals turn to crime. According to Agnew (1992), everyday life stressors have the capacity to foster a criminal response when they elicit a negative emotional reaction (e.g., anger, disappointment, fear) in the absence of prosocial coping mechanisms. Criminal offending is one way an individual can respond to negative life situations to alleviate strain. Additionally, strains are more likely to result in crime when they are greater in magnitude, recent, long in duration (i.e., chronic), and clustered in time (Agnew, 1992).

Strains Associated with Poverty

Individuals living in poverty experience several sources of strain that can broadly be categorized as physical, family, social, financial, and health-related. Physical sources of strain associated with poverty include substandard housing, high-crime neighborhoods, disorganized and chaotic environments, inadequate schools, pest infestations, and higher levels of environmental pollutants such as lead (Clark et al., 2014; Desmond & Bell, 2015; Evans & Kim, 2013; Hipp, 2007; Khullar & Chokshi, 2018; Pais et al., 2014; Shaw & McKay, 1942). These conditions contribute to the strain felt by individuals and the family unit (Rodems & Shaefer, 2020) and may increase the likelihood of crime. For example, older housing structures in disadvantaged communities are likelier to have peeling, lead-based paint (Adamkiewicz et al., 2011). This is of particular concern, as previous research has established a link between lead exposure and violence, especially homicide (Boutwell et al., 2017; Nevin, 2007; Stretsky & Lynch, 2001). More generally, living in substandard conditions can result in individuals who may be more socially withdrawn, stressed, and aggressive (Evans, 2006).

According to the family stress model, poverty is a major contributor to family dysfunction and emotional distress (Conger et al., 2002). Family sources of strain that are related to poverty include punitive and detached parenting, parental conflict, exposure to violence, and single-parent households (Conger et al., 2002; Duncan et al., 2017; Evans & Kim, 2013; Finegood et al., 2017; Mistry et al., 2002; Yeung et al., 2002). These strains are often linked to less effective parenting (Masarik & Conger, 2017), which, in turn, may contribute to juvenile delinquency via insufficient surveillance, lack of warmth and support, as well as inconsistent discipline (Agnew et al., 2000; Chung & Steinberg, 2006). Furthermore, as established by Conger and colleagues (2002), family dysfunction can result in negative emotions, such as depression, which are a key component of general strain theory (Agnew, 1992).

Social sources of strain include stigma, social isolation and exclusion, feelings of inadequacy, and resentment for being dependent on government assistance, among others (Reutter et al., 2009; Stewart et al., 2009; Walker, 2014). According to Mickelson and Williams (2008), poverty stigma is associated with depression among low-income individuals. This may be because many impoverished individuals internalize the stereotype that they are less worthy than other members of society. Additionally, poverty restricts an individual’s ability to form and maintain social support networks (Hawthorne, 2006; Mood & Jonsson, 2016). This is of particular concern because the lack of a strong social support network is a risk factor for criminality (Ellis & Savage, 2009; Spohr et al., 2016). As an example, Ellis and Savage (2009) found that social support was negatively associated with violence. Indeed, improving social networks can reduce crime rates (Cullen et al., 1999). Moreover, the quality versus the quantity of social support matters (Spohr et al., 2016). As the quality of social support increases, the risk of criminality decreases.

Poverty is grounded in a person’s or family’s inability to meet financial needs. Poverty contributes to financial sources of strain such as the inability to pay bills, the possibility of eviction and subsequent homelessness, and a lack of health insurance (Desmond & Bell, 2015; Duncan et al., 2017; Frick & Bopp, 2005; Gennetian & Shafir, 2015). Financial instability is also related to material deprivation. Material deprivation refers to low living standards and a lack of consumer goods, such as the inability to purchase enrichment resources for children, including educational toys, books, and computers (Becker, 1991; Duncan et al., 2017; Kaushal et al., 2011; Yeung et al., 2002). Agnew (1992) posits that this inability to achieve the valued goal of financial success so ingrained in American culture (i.e., the American Dream) propels individuals to seek prosperity through illegitimate means. For example, Dunlap and colleagues (2010) found that poverty was a strain that reduced the legitimate opportunities individuals had to acquire money and social capital. As a result, inner-city residents turned to the illicit drug market as a means of obtaining much-needed resources.

A well-documented link between poverty and health has an inverse relationship (Palomar-Lever & Victorio-Estrada, 2012). According to Khullar and Choksi (2018), the United States has “among the largest income-based health disparities in the world” (p. 1). Living in poverty has been shown to lead to a variety of adverse health outcomes, such as asthma, depression, anxiety, heart disease, and diabetes (Duncan et al., 2017; Hackman et al., 2010; McEwen & Gianaros, 2010; Santiago et al., 2011). Substandard dwellings and housing affordability problems are associated with poor health in vulnerable populations (Novoa et al., 2015), such as impoverished individuals. Prior research conducted by Stogner and Gibson (2010) and Schroeder et al. (2011) has supported the notion that physical illness is a source of strain that has the potential to lead to non-violent criminal offending. In addition to the physiological ailments associated with poverty, psychological stress is also present. Psychological stress includes negative cognitive and emotional states that occur when demands on an individual exceed their ability to cope (Ng et al., 2009). Neurological changes can result from high levels of stress hormones that negatively affect mental health (Ng et al., 2009).

To summarize, experiencing various obstacles associated with poverty, as discussed above, can lead to psychological distress (Proctor et al., 2016), heightened negative emotions such as anger (Hackman et al., 2010; McEwen et al., 2010), as well as decreased emotion regulation (Kim et al., 2013), which may contribute to criminal offending.

Emotional Reactions Associated with Poverty

An important consideration in examining the impact of strain on individuals includes the emotional reactions experienced by those living in poverty. The emotional reaction is considered to be closely linked to the subjective strain or how the individual perceives an event or situation (Agnew, 2001). For this manuscript, emotion will be defined as an affective response to a situation. It is important to acknowledge that emotions are multifaceted and part of an overall holistic system response, including measurable psychological changes (Agnew, 2001). Concerning general strain theory, the emotional reaction to strain is a reaction to one or more of the following components of the strain: poverty.

A study conducted by Conger and colleagues (2002) utilized a sample of 897 African American families to explore the impact of economic pressure on the family stress model. Economic pressure was defined as the inability to meet material needs, the inability to make ends meet, and financial cutbacks (Conger et al., 2002). Relevant outcome measures included caregiver depression and child adjustment. Results indicated that economic hardship was predictive of caregiver depression. Furthermore, economic hardship was significantly related to negative developmental outcomes for children, including externalizing behaviors (Conger et al., 2002). Similarly, Raver et al. (2015) found that exposure to chronic poverty reduced children’s ability to regulate their negative emotions, such as sadness and anxiety.

A study by Piff and Moskowitz (2018) examined how social class (measured by household income) is associated with emotions. Their study included a sample of 1,519 participants. Generally, this study found that upper-class individuals reported higher levels of contentment than their lower-class counterparts. Lastly, a qualitative study by Ali et al. (2018) centered on the emotion of shame. An analysis of interviews with 60 participants revealed that shame was experienced in two areas: (1) as caregivers and (2) as recipients of social welfare. Participants noted that there were both material and symbolic aspects of shame related to poverty. For example, material aspects related to shame included the inability to pay rent, loss of shelter, or food insecurity. Participants reported a range of negative emotions, including anger, frustration, guilt, and embarrassment (Ali et al., 2018). This is important, as anger can directly increase the likelihood of violence (Baron et al., 2001; Caspi et al., 1994).

Poverty Simulations and Criminal Justice Education

Participating in a poverty simulation has many benefits for criminal justice students. First, poverty simulations offer an experiential learning opportunity (Steck et al., 2011). By role-playing the lives of diverse low-income families, students can experience first-hand the challenges that individuals in poverty face through a strain theory lens. In doing so, students can better understand how strains associated with poverty can propel an individual to commit crime as a means of survival. Poverty simulations also promote critical thinking, as students must make difficult decisions when balancing their family responsibilities (see below for examples). Another benefit of engaging in a poverty simulation is that criminal justice students can develop empathy towards low-income individuals, as well as marginalized communities, and demonstrate cultural competency, which is vital when working with people from diverse socioeconomic backgrounds. Since poverty is often associated with a lack of access to resources, as future criminal justice practitioners, students gain an appreciation for social welfare programs that aim to alleviate poverty and, in turn, have the potential to reduce crime.

Current Study

Students who participated in this study completed a poverty simulation using the Missouri Community Action Network Poverty Simulation©. The Missouri Community Action Network Poverty Simulation© model has proven effective for facilitating learning and engagement through participants’ role-playing the lives of diverse low-income families, such as that of a single parent, senior citizens on a fixed income raising grandchildren, and families with children who have disabilities (Keeney et al., 2019; Walker et al., 2021). The simulation is facilitated through a kit of materials, scripts, and instructions (Steck et al., 2011). Each “family” receives a packet that includes descriptions of each family member and their assets (e.g., transportation passes, electronic benefit cards) and bills. Families may also receive “luck of the draw” cards throughout the simulation. These cards indicate a positive situation, such as an event that provides additional income to the family, or a negative occurrence, such as a death in the family (Steck et al., 2011).

During the first part of the simulation, students go through four 15-minute “weeks” and must balance family responsibilities (e.g., caregiving, paying bills, going to work/school) while navigating a variety of community agencies such as a bank, mortgage/loan office, utility company, school, social services offices, and pawn store. Most relevant to the current study, one of the community agencies was a police department, and a designated police officer patrolled the area during the simulation, thus creating a potential deterrent effect against engaging in crime. Students were invited by faculty from a variety of university departments (i.e., Nursing, Education, Health Promotion, Criminology and Criminal Justice, and Social Work) to participate in the poverty simulation and subsequent debriefing. The entire process lasted approximately three hours. The first half of the process is the simulation itself, and the last half is a debriefing session consisting of small focus groups and a large group discussion about the experience of the simulation related to program improvement and addressing issues of social justice, equity, diversity, and inclusiveness throughout the university and larger community (Walker et al., 2021).

Method

Research Design and Measures

This study reports on findings specific to qualitative data from focus groups of students who volunteered to participate in the Missouri Community Action Network Poverty Simulation^© (2022) and how their experiences can be applied to general strain theory. The larger study employed a mixed-method quasi-experimental design where students were asked to participate in the poverty simulation (independent variable), complete a pre- and post-simulation survey (dependent variables), and participate in focus groups (Walker et al., 2021). The quantitative portion of the study engaged a pre- and post-simulation survey that included 11 demographic questions, 21 Likert-type questions from the Short Form of the Attitude Toward Poverty Scale (Yun & Weaver, 2010), three poverty experience questions, and one open-ended question. Demographic questions included name, gender, race, college major, and personal experiences with poverty. Participants provided their rating (ranging from strongly agree to strongly disagree) to statements regarding their beliefs about poor people (e.g., “Poor people are dishonest.”) and behaviors of poor people (e.g., “Unemployed poor people could find jobs if they tried harder.”) (Yun & Weaver, 2021). Three questions also inquired about their personal experiences with poverty (e.g., “Have you had a personal experience with poverty?”) and asked them to identify the individuals impacted (e.g., self, family, friend, client/patient), as well as the developmental stage of those impacted (e.g., child, adult, both). One open text field item asked participants to define poverty using their own words. Lastly, participants were asked to identify their role in the simulation. Additional methodology and findings on the quantitative portion of the study are available for review (Walker et al., 2021).

Qualitative data were also captured via focus groups. Open-ended questions were employed to ascertain participant’s perceptions of poverty pre- and post-simulation (e.g., “What was your perception of poverty before participating in the simulation?”), implications on personal and professional identity (e.g. “How do you anticipate the simulation impacting you as a professional?”), and knowledge about poverty/resources available on campus (e.g., “Tell me what you know about resources at [University Name].” Though moderators were encouraged to ask all six questions in the interview guide, they had the flexibility to ask probing questions to elicit more detail and/or dialogue from the groups.

Ethical Considerations and Recruitment

The university’s Institutional Review Board approved the study before recruitment and data collection (IRB 2020-184 approved February 11, 2020). Subsequently, participants were recruited during the Spring 2020 semester. The research team consisted of faculty from various university departments across multiple colleges who recruited students from their current classes as extra credit or engaged their entire class if the poverty simulation aligned with their course schedule. All participants completed informed consent before engaging in the research process.

Data Collection and Management

After the simulation concluded, participants were randomly assigned to one of 10 focus groups with approximately 10 participants. Focus groups were moderated by a research team member who used a standardized introduction script and interview guide. Focus groups were digitally recorded and transcribed using the Otter.ai application (https://otter.ai/) and stored in the research team’s institutional Google for Education software system. Specifically, transcripts were stored via Google Drive’s password-protected cloud-based system. Transcripts included only the researcher’s names. Though the engagement of cloud-based systems within the research process is growing, the literature regarding research ethics in the virtual landscape, such as cloud-based systems, remains limited (Hopper et al., 2021). However, there is support for the enhanced security offered by Google Drive’s two-factor authentication as an added protective factor against data breaches. Hopper et al. (2021) assert, “[F]rom a password point of view, it is harder to break into or hack a person’s YouTube and Google Account than it is to hack into a person’s email” (p. 863).

Data Analysis and Quality

Focus group transcripts were thoroughly reviewed and sanitized against the Otter.ai application transcripts to ensure accuracy before analysis. Specifically, transcripts were reviewed to ensure the Otter.ai application captured all data and recorded the correct spelling of words/phrases. Once transcripts were sanitized, researchers reviewed each focus group in its entirety. Three researchers employed their software (i.e., Atlas.ti v.9.1.1, Excel v.16, and NVivo v.12) for independent data analysis.

Researchers engaged in deductive, or a priori, analysis (Bingham & Witkowsky, 2021) guided by GST’s theoretical framework. Specifically, when researchers initially reviewed transcripts, the theory-based categories of strain, reaction, and response were used as predetermined codes. According to Grbich (2013), the concepts of coding and themes are often used interchangeably within research, though the act of coding can be defined as “grouping or labeling the data in the process of making it more manageable” (p. 259). Therefore, as researchers performed the early review of the transcripts within their software systems, they “coded” the data as either strain, reaction, and response.

Through the iterative nature of qualitative data analysis and routine research meetings, further elucidation of specific focus areas within the three a priori codes was discussed. For example, within the a priori code of strain, analytic patterns or themes (Gribich, 2013) were considered within the context of the theory’s three sources of strain. The code reaction was further categorized inductively into the themes of emotional reactions and experiences of stress. Similarly, the third a priori code response was further inductively grouped into the themes of economic motivation and cognitive dissonance. Finally, researchers employed the use of an audit trail to assist in establishing rigor for this study by documenting decision-making, inferences, and critical reflections about both the research process and analysis to further facilitate methodological awareness (Connolly & Reilly, 2007; Lincoln & Guba, 1986; Merriam, 2002).

Findings

Participants

A total of 99 undergraduate and graduate students (n = 77 or 78% males; n = 22 or 22% females) participated in the study. Students were from the following colleges and programs: College of Health 43.3% (nursing 33%; physician assistant 6.2%; health promotion 4.1%); College of Education and Professional Studies 30.9% (social work 24.7%; Criminology and criminal justice 6.2%); College of Science and Engineering 14.4% (biomedical 14.4%); and “Other” (11.4%). Students were primarily between the ages of 21-25 years of age (43.4%) and identified as Caucasian (70.4%), African American (18.4%), Asian/Pacific Islander (7.1%), and “Other” (4.1%). Additionally, 7.3% of the students identified as Hispanic/Latinx.

The institution reported an enrollment of 11,945 students the semester the simulation occurred (N = 4,733 or 40% males; N = 7,212 or 60% female). Therefore, the simulation overrepresented the male student population. Student enrollment by college that semester was: College of Health 25%, College of Education and Professional Studies 21%, and College of Science and Engineering 24%. The Colleges of Health and Education and Professional Studies were overrepresented in the simulation; however, the faculty who recruited students for this particular simulation date were primarily from these two colleges. The institution did not report data on age. Finally, race/ethnicity data that semester were the following: Caucasian (66.6%), African American (11.2%), and Asian/Pacific Islander (3.6%). No category exists for “Other” on the institutional data. However, institutional data identified 9.7% as Hispanic/Latinx. Thus, there was a slight underrepresentation of Caucasians, African Americans, and Asian/Pacific Islanders and a slight overrepresentation of Hispanic/Latinx (UWF, 2020).

Themes

Strain

As previously discussed, Agnew’s (1992) GST posits three sources of strain: (1) the failure to achieve positively valued goals, (2) the presence of noxious stimuli, and (3) the removal of positive stimuli. Participants in the simulation articulated numerous examples of ways they experienced tangible and intangible sources of strain, which will be discussed below with exemplars from the data.

Failure to Achieve Positively Valued Goals

The first source of strain suggests the inability to accomplish a valued goal. Concerning meeting basic needs such as food and housing, one participant stated, “‪[T]here wasn't enough time for us to get to the grocery store and go to the utility company and pay off the mortgage… she was in line to go pay the mortgage but time ran out so then when we got back, we were evicted.” Furthermore, one participant noted, “‪I'm really big on like, time management, and being able to have time to sit down and plan everything, and there wasn't any time between stuff. It was just like, Okay, next…So I think the whole time part just was just stressed me out.” Interestingly, in the large group debrief, participants discussed the realization of how the stress of trying to meet basic needs mitigated the opportunity to enjoy downtime with family/loved ones. For example, one participant articulated, “[W]e didn't have no social leisure conversation situation…it was still kind of like all work no play…[it] wasn’t really that ‘How are you, how was your day going?’ and still priorities that need to be met.” This inability to meet a goal, such as breaking the cycle of poverty or even attending school, is summarized in this quote, “Once you're in poverty like there's no way out…my family that I was in, was like two grandparents who had to take in the kids because their mom [went] to jail. And like, what do you do? [O]ne got a disability check, and one worked… I [can’t] really go back to school …like, how do you get out of that situation?”

Presence of Noxious Stimuli and/or Removal of Positive Stimuli

Additionally, participants verbalized other opportunities within the simulation that could be argued as either the inclusion of harmful stimuli or the elimination of positive stimuli. One such example dealt with the concept of time and realizing how important that construct is when it comes to the ability to prioritize activities of daily living (e.g., paying the bills, working, dealing with unexpected events, traveling to and from appointments multiple times). Several participants simply stated things such as, “There wasn’t enough time,” while another acknowledged a realization that “Time…time is like a big deal.” One participant elaborated on a specific situation they encountered, recalling that even though they were not evicted from their house during the simulation, they experienced utilities being “cut off.” As a result, they tried to go to the bank, “I was waiting in line to get a paycheck, and they’re like ‘okay time is over [up],’ and it’s like I have no money…what do you mean time is over [up]…I need money because I sat here for seven whole minutes, so I could have been doing other stuff to try to help the family out.”

The frustration was explicated by others who also recognized the snowball or domino effect that one crisis for an individual living in poverty could initiate. For example, a participant reflected, “[S]ome unfortunate event can just derail everything you worked for, and that doesn't necessarily mean you don't work hard or that you've made poor choices, it's just pure circumstance that sometimes something can go wrong and everything you’ve worked to save up and work towards it can just be gone right away, and then you have to start over again.”

This notion of the snowball or domino effect was acknowledged within the context of how it impacted the loss of resources. In removing positive stimuli, a participant recounted, “I think it’s eye-opening to see how quickly you can go from having [a] house to you’re in a situation. We [were] about to pay the mortgage that day, but I was at work late, and I couldn’t go pay the mortgage…our whole family [was] now without a house.”

Participants also recognized the value that education contributes as a benefit that, when excluded, facilitated an increased strain. This was considered through the lens of formalized education discussed within the context of medications and contraception as detailed in this example, “[P]eople just don't know that…there are resources that can help them get their medications, not have babies. And then it just kind of a constant never-ending cycle because then they get sick and they go to the hospital and then they get a huge hospital bill, and they don't have childcare and then their child is taken away.” Outside of traditional education, participants experienced a less tangible idea of “not knowing the rules.”

Reactions

Poverty simulation participants shared various emotional reactions to the perceived strains associated with the simulation. These reactions fell into two categories or themes: (1) emotional reactions and (2) experiences of stress. While it is difficult to fully separate stress from other emotions due to the link between our physiological and emotional responses, participants could describe these two types of reactions.

Emotional Reactions

Frustration. Participants who discussed feeling frustrated did so within the context of feeling trapped or unable to move forward and accomplish things. Even basic tasks became very difficult when basic needs, such as transportation, were unavailable regularly. One participant noted frustration due to an inability to make sustained progress when navigating the tasks necessary for each week of the poverty simulation (i.e., work, school, paying bills, obtaining food, etc.). When the family began to progress, something unexpected would happen that would push them backward. As one participant noted, “It was really frustrating because I felt like right when we were getting the hang of things, it was like a little change, like a bad luck card. We were the people that got robbed of all of our transportation passes."

Another area of frustration was the difficulty in accessing necessary services. One participant shared, "It's just so frustrating that you go to one place on one side of town for one resource, and to get to the other side, you have to use so many resources for transportation to do that. But you need the resources that are on both sides of town, and you have to pick and choose because it's so hard to get back and forth.” Because services were not available in the same place, participants may not have been able to access all of the services they needed due to limited resources such as time or access to transportation

Desperation. Desperation was expressed as a response to poverty, particularly regarding being able to move forward or make any kind of progress. This feeling of being desperate was compounded when participants kept trying to perform basic tasks or access basic resources but were prevented by lack of time or inability to access transportation. One person stated, “The desperation really shows when you're just stuck in a cycle and you don't know what to do. You're really stuck.” Some of the choices participants made related to feelings of desperation and not having any alternative. One participant explained the situation that influenced the family’s decision to allow their son to deal drugs during the simulation. “Because he's a dropout, and we needed money, and I needed to get a job. I needed to take care of bills. I had 10 dollars [the day] their dad left. He was the breadwinner. So I was desperate.” The family could not purchase food or pay bills due to the lack of resources such as transportation or individuals' ability to work full-time, so they decided to do whatever it took to make sure the family could be provided for.

Another participant noted that the lack of healthcare access for a family member led to feelings of hopelessness and desperation in their family sharing: “But [in] America, if you don’t have money, then you just have to deal with what you have. And sometimes that's just resorting to dying in the most peaceful ways, maybe, rather than being able to get help because some people they're in certain financial stability to where they are unable to get help, no matter what they do and how much they're going to save up for.” While specific to physical health, this participant's comment illustrates the lack of ability to access necessary services or resources, leading to a sense of desperation.

Experiences of other emotional reactions. In addition to the more common emotional reactions noted above, some other reactions from participants included anger, confusion, and anxiety. Although only mentioned by one participant, anger (being “pissed”) was another emotional response felt due to the helplessness he felt at being unable to accomplish basic tasks. When asked how he felt during the simulation, he expressed that he felt: “Pissed off that I didn’t have enough time. I had to wait in line. I didn't get my paycheck one night. I [was] kind of pissed off, actually.”

Several participants noted feeling confused about what to do and where to go. There were many needs and responsibilities, pulling them in different directions. Some participants noted that they experienced confusion about how to prioritize and/or accomplish basic tasks, much less large goals that would help them move beyond poverty. One participant noted, “I think I was just kind of confused. I didn't know what to expect. I got home and didn’t know if we would still have a house or a car. [Because] we didn’t half the time. So I never knew what was going on.”

There was an acknowledgment of feelings of anxiety related to poverty because there are so many unknowns as well as so many tasks and responsibilities to be addressed with limited time and resources. One participant volunteered, “You need to pay for the house, but we also need to get the kids food, and our… grandkids are saying, [they] haven't fed us, we're hungry. And my anxiety started creeping up.” One participant noted that being anxious made it more difficult to be organized and focus on daily tasks because the person is concerned about what could happen next. This anxiety seemed to compound and build as time went by, and more needs and responsibilities fell through the cracks. In this example, anxiety kept her from keeping track of what bills she had paid and what responsibilities had been met, creating more anxiety down the road when she was not sure what she had and had not taken care of. She described it this way: “When I'm anxious, I’m not thinking about keeping records. I'm not thinking about being organized and what could go wrong later like I'm in that moment.”

Experiences of Stress

As noted earlier, several participants did not express a specific emotional reaction but an overall feeling of being stressed. Stress appeared to encompass more of the physiological reactions to the strain of poverty. One participant noted that stress caused an inability to focus on smaller but important tasks, like keeping documentation related to financial obligations. One participant shared, “And so if you're stressing about what bills to pay [and] have to pay all of them, at the top of my list is not asking for a receipt and putting it in a space that I can find it later. That's just not my mindset when you're trying to figure things, but I've also been on that side where they asked for a receipt, and it's frustrating and adds to it when you can't find it, and no one believes you, and you're like, I'm not intentionally trying to get away from paying the bills. I want to pay a bill, and I've already paid it.”

Similarly, other participants shared how when they felt stressed, it was difficult to focus on daily tasks like work or school. Related to the more physiological component of stress, one participant who acted as a parent in the simulation made reference to the physiological component of stress by saying, “My blood pressure shot up to the roof!” While discussing the overwhelming feeling of stress that took place during the simulation, one participant mentioned a link between poverty and substance abuse, “After hearing about some of these stressful events, you can understand why somebody might turn to substance abuse to kind of escape that difficulty.”

Responses

As previously discussed, those who live in poverty experience a wide array of everyday life stressors that are frequent and long in duration. Such stressors are common and continuous occurrences in impoverished individuals' lives. Agnew's (1992) general strain theory states that people who respond to stressors with negative emotions and maladaptive coping mechanisms are more likely to engage in crime; however, most individuals living in poverty do not commit crime (Delgado, 1985; Green, 2010). Indeed, only a small proportion of focus group participants reported doing so. It is important to note that participants' responses were organic. That is, focus group moderators did not specifically ask participants about their asocial or illicit behavior during the simulation.

Criminal Responses

Economic Motivation. Among participants who admitted to engaging in crime, the most common offense was drug dealing. In addition to drug dealing, participants also reported committing theft, robbery, and burglary. Interestingly, these types of offenses are utilitarian and economic in nature. Coinciding with this observation, responding to poverty with criminal behavior was often framed in response to poor economic conditions. The general need for funds was continuously entwined in participants’ reasoning for their illegal behavior. As evidence, one participant discussed their unemployment status as a motivation to sell drugs: "I was an unemployed mother, so I had to keep waiting in line to get an application to fill out [to receive assistance]. But there was an opportunity for me to sell drugs … I didn't get caught, so it was quick, easy money."

Similarly, parenthood and the need to care for children were mentioned as drivers for illegal behavior. One participant explained this dilemma: “You’re really stuck, you know? You’re trying to do anything you can to keep your family alive and surviving, but that might lead to illegal things. The parent … they’re trying to take care of their kids.” A separate participant noted that their family unit had a conversation about getting the father’s prescription medication and selling it because they needed the money; however, this particular family did not follow through with their plan.

Another economically-relevant motivation to engage in criminality was the need for transportation passes. Each individual was required to have a transportation pass to visit any of the locations within the poverty simulation; however, transportation passes had to be purchased. As such, several participants turned to illegally obtaining transportation passes for themselves and their families. One such participant explained how their need for transportation passes pushed them to engage in theft to pay their bills and avoid eviction: “Had I not stolen transportation passes from social services on my way home from school, we wouldn't have been able to pay the bills because we had no transportation. We had a car, but we had no passes. Had I not stolen those, we probably would have been one of the families in the shelter.”

Another participant noted that after stealing transportation passes from other people, a witness to their crime approached them, asking if they were willing to sell some of the passes they had just stolen. It is important to highlight that participants were not engaging in violence but in economic crimes that they believed would essentially give them a leg up during the simulation. One participant noted: "Sometimes you can't provide, and [crime is] what you resort to." Indeed, similar to the parent discussed above, multiple participants communicated the notion of feeling “stuck”: “The desperation really shows when you’re just stuck in a cycle and you don’t know what else to do.”

Cognitive Dissonance. While crime was not the only option for these participants to turn to, they felt compelled to resort to criminal offending because it was the most viable option to obtain funds, especially when legitimate means were pursued first (e.g., being denied services and assistance by social services). Although some participants took no issue with committing a crime (e.g., one participant reported that they "loved being [the] drug dealer"), others struggled with the ethical dilemma of engaging in behavior they knew was wrong. Take, for example, the unemployed mother discussed above. This participant acknowledged that drug dealing "skewed [their] ethics." Other participants described a similar struggle. For example, one participant who sold drugs stated the following: "[D]rugs are bad, and people need to stay away from them. For this [simulation], I really had to sell drugs. I kind of have to do it [to] get some more money."

Another participant who committed theft said: "I felt really bad … my heart was really pounding like I was really doing something illegal … it's not even real, and I just feel so bad. Like I almost cried. I did not want to steal her money or her transportation [passes]. How are they gonna go where they want to get their passes from?" One participant who contemplated but ultimately decided not to engage in crime stated:

I contemplated [selling drugs] because there was nothing else that I could do to get money … And it would never, like, that stuff never crossed my mind, and I never thought that would cross my mind to ever be okay with that [but] when the mortgage people are knocking on your door saying you’re about to get evicted and when you get a health alert saying hey, you haven’t eaten in three weeks … what do you do? I just realized how easy it is to fall into some[thing] that wasn’t your only option, and so [the poverty simulation] really shed a lot of light on that.

These statements highlight a cognitive dissonance between adequately providing for themselves and their families while engaging in illegal behavior to do so. One participant notably observed: “Poverty can lead to illegal activities and ... as a society, we tend to think people who do illegal activities, we tend to label them as evil and [that] they don't have any morals. But we don't know the situation, where they come from, or how they're trying to help their families.”

Discussion

Poverty simulations offer insights into the varied sources of strain experienced by impoverished families and communities, including the compounding impact of multiple strains on the individual or family unit. For example, there is an inverse link between poverty and health; however, health is often viewed as secondary when there are competing strains on the family, such as obtaining and sustaining affordable housing, the inability to pay essential bills, and the lack of affordable health insurance and access to quality health care (Hackman et al., 2010; Hartman, et al., 2020; Kim et al., 2013; McEwen et al., 2010; Proctor et al., 2016). The current study examined students’ decision-making processes as they experienced multiple sources of strain while going through the poverty simulation. The focus groups and large group discussions allowed for an exploration of students’ experiences during the simulation, as well as reflections after the simulation ended.

Poverty simulations have highlighted time constraints on the family unit (Smith-Carrier et al., 2019). According to Aloè (2019), “[T]he well-being of the household must be assessed based on its income and of its structure–that is directly connected with its time requirements” (p. 285). The idea of time and its relation to poverty has a longstanding history in the literature dating back to Vickery’s (1977) inquiries into time poverty and its relationship to monetary poverty. Research supports that individuals can be money and time poor (Goodin et al., 2005; Vickery, 1977). When families must spend time and resources traveling to and navigating the process of obtaining community services and resources, they often lack time and the financial means to enjoy leisure activities and opportunities for relaxation and renewal, therefore posing challenges to healthy family bonding and resilience (Orthner & Mancini, 1990). In other words, the inability to engage in what is frequently referred to as free time—designated by Goodin et al. (2005) as “discretionary time” (p. 44)—has implications on family wellbeing. The poverty simulation experience underscores the challenges of day-to-day life in impoverished families and the constant struggle to meet basic needs.

Students experienced a range of emotions in the poverty simulation, much like the emotions described by individuals experiencing poverty in the real world (Conger et al., 2002; Hackman et al., 2010; McEwen et al., 2010), as well as the stress and strain associated with it. Students acknowledged feelings of frustration, sadness, and anxiety. They also empathized with impoverished populations and voiced their improved understanding of poverty-associated shame, embarrassment, guilt, depression, and desperation and how these experienced emotions played a role in their decision-making during the simulation.

Findings from focus group interviews illustrated and substantiated the link between poverty and crime that is described in the literature (Pratt & Cullen, 2005; Hay et al., 2007); however, only a small portion of participants who experienced negative emotional reactions from the snowballing impact of the various forms of strain (e.g., housing insecurity, inability to pay bills, lack of affordable health care) associated with poverty engaged in criminal activity to meet the basic needs of their family. The post-simulation debriefing revealed that most of those who resorted to crime to meet their basic needs did so for economic reasons. Furthermore, the commission of offenses developed organically during the simulation itself.

The poverty simulation experience contributed to participant empathy when treated as a real-world scenario rather than a game to be won. The poverty simulation scenario offered insight into the complex and dense temporal scaffolding of human experience. For example, students felt frustrated when feeling trapped in a cycle of poverty. Providing basic needs was challenging due to difficulty obtaining transportation passes to and from appointments with community service providers. Participants felt that each time they made progress financially, another economic hardship or family emergency would create additional setbacks (e.g., inability to acquire medication).

In closing, participants noted that the poverty simulation experience offered context to their study of marginalized populations, as well as the stress and strain that may contribute to criminal activity.

Limitations

This study did not, and was not meant to, examine the accuracy or level of reality of the poverty simulation; however, limitations of any simulation may include a reality gap (i.e., simulations cannot possibly replicate all real-life scenarios). Additionally, the time and resources needed to prepare and organize complex simulations adequately can create barriers to success. Processes and procedures are necessary to efficiently and effectively deliver complex simulation scenarios due to many moving parts, such as multiple family units and community services. Therefore, implementing a quality improvement process can mitigate these challenges over time. Though demographic data capture student participation by discipline, it did not differentiate between undergraduate and graduate students. Consideration should also be given to the time commitment of the simulation. Several students left after the simulation and did not participate in the focus groups. Finally, though all focus group leaders were faculty members at the university, not all had experience in qualitative data collection and/or focus group facilitation. Facilitators skilled in high-value debriefing are key to any successful simulation, as they can promote reflection so that key learnings are reinforced.

Policy Implications and Future Research

Poverty simulations provide rich opportunities for students to gain different perspectives. Criminal justice and criminology students can benefit from participating in poverty simulations in multiple ways. For example, students can better understand how present circumstances (i.e., living in poverty) can impact an individual’s involvement in crime. Additionally, upon graduation, some students may enter the criminal justice field as a practitioner. Prior research indicates that poverty simulations increase empathy toward impoverished individuals (Phillips et al., 2020). During the focus groups, participants also discussed how the poverty simulation would translate into practice in their field of study. Thus, the poverty simulation provides insight into the experiences of marginalized, underserved populations often caught up in the criminal justice system.

Future research should consider a discipline-specific poverty simulation, with debriefing and focus group questions tailored to criminal justice and criminology students. In addition, future research could explore differences in participant responses based on simulation roles. How do they react to strain if assigned roles of children/adolescents versus adults/seniors? It would also be interesting to conduct a poverty simulation among criminal justice professionals (e.g., law enforcement) and compare their experiences with college students.

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Contributors

Dr. Chrystina Y. Hoffman joined the faculty at the University of West Florida in Fall 2019 and conducts research, broadly, on victimization. Her research has examined questions such as whether children or adolescents who have been bullied experience greater consequences in adulthood, whether international students face the same victimization risk as domestic students, whether experiencing violent victimization impacts future expectations, and what factors motivate or hinder college students’ decisions to intervene. Dr. Hoffman’s work has been published in peer-reviewed publications such as Deviant Behavior, Youth Violence & Juvenile Justice, Journal of Interpersonal Violence, Victims & Offenders, and Crime & Delinquency.

Dr. Dana R. Dillard is an Assistant Professor at Mississippi State University and a Licensed Clinical Social Worker. She has over 20 years of practice experience that includes medical social work, school social work, and non-profit program design and implementation. She became involved with the burn community and fire service during a service-learning course in 2000 and developed an interest that drives her commitment to practice and research with these populations. Her research areas include the individual and systemic impact of burn injuries in relation to identity, aftercare/reintegration and program development/interventions; the fire service with attention to mental health/suicide and program development/interventions; the intersection of trauma and identity; interprofessional education; and the recreational camp setting within social work practice.

Dr. Erin King is an Assistant Professor in the Department of Social Work at the University of West Florida, and a licensed clinical social worker (LCSW). Her practice experience relates primarily to the intersection of trauma, mental health, and substance abuse in women, and mental health counseling with children, adolescents, and adults. Her research interests concentrate on the influence of trauma on mental health, most recently work-related trauma and its influence on child welfare worker and first responder mental health, and personal and work-related outcomes.

Dr. Angela Blackburn earned a Ph.D. in Nursing (Ethics Specialization) from the University of Southern Mississippi. Her area of research interest includes caring science, worksite wellness, ethics, and qualitative research methods. She completed the Caritas Coach Education Program® (CCEP) offered by the Watson Caring Science Institute (WCSI) to advance the philosophies, theories, and educational-clinical-research practices of Caring Science in 2021. Dr. Blackburn was selected as a 2022-2023 Watson Caring Science Postdoctoral/Senior Scholar, where she will participate in a one-year exclusive personal study with Dr. Jean Watson to expand knowledge of Caring Science. Dr. Blackburn served as Interim Chairperson for the School of Nursing (2018-2020) and graduate program director (2011-2018). She serves on the Ascension Gulf Coast Ethics Integration Committee, and she served as the University of West Florida Institutional Review Board (2020-2022 chairperson). She is a board member of Sigma Theta Tau International Honor Society of Nursing, Upsilon Kappa Chapter.