Poverty Simulations With Health Professional Students: Evidence of Impact

Abstract

Poverty is one of the most significant determinants of health inequity in the United States, yet students of the health professions are more likely to come from higher rather than from lower income families, separating them economically from many of the individuals they will serve. Poverty simulations can expose health professional students to experiences of those living in poverty and provide a more holistic, structural perspective of poverty that informs their later practice. We sought to understand the current state of poverty simulations being utilized throughout the United States. Through a review of abstracts via Ovid and Google Scholar, we identified nine articles that focus directly on describing poverty simulations in university-based programs with health or social work university students and that incorporate some form of pre- and postevaluation methods. After a careful review of these articles, we describe the distinct differences in components and contexts between the simulations, including Bridging the Gaps–Pittsburgh’s Experiential Poverty Exercise, and how effects on students is determined across the various simulations. Additionally, we review how unique aspects of the Bridging the Gaps–Pittsburgh’s Experiential Poverty Exercise can serve as a model for providing multidisciplinary graduate students the opportunity to increase their knowledge and shift attitudes about people experiencing poverty before working with them as health professionals. In presenting the current status of these simulations, we seek to develop recommendations regarding the components and context of poverty simulations as well as approaches to assessing effects.

Keywords

poverty simulation student attitudes health professional training health equity

Poverty is one of the most significant determinants of health inequity in the United States (Braveman, Arkin, Orleans, Proctor, & Plough, 2017). While poverty is measured in multiple ways at the federal level, generally people living in households below the federal poverty guidelines (currently, e.g., families of four who live below $25,094/year) are considered poor and qualify for federal assistance (U.S. Census Bureau, 2017). Additionally, those unable to meet the basic costs of living (food, clothing, shelter, and utilities), even above poverty guidelines, may be captured in poverty statistics and eligible for assistance through federal and state-funded programs (UC Davis Center for Poverty Research, 2018; U.S. Department of Health and Human Services, 2018; Fox, 2017). More than 40 million Americans live in poverty, with women, Black and Latino individuals, and people with disabilities disproportionately represented among the poor (U.S. Census Bureau, 2017; U.S. Department of Health and Human Services & Agency for Healthcare Research and Quality, 2011).

Individuals living below the poverty level have greater barriers and less access to care and are less likely to have a source of ongoing care compared with those above the poverty level (U.S. Department of Health and Human Services & Agency for Healthcare Research and Quality, 2011). Living in poverty is associated with higher disease burden and reduced life-expectancy (Adler & Newman, 2002; Braveman, Egerton, & Barclay, 2011), poorer birth outcomes (Nagahawatte & Goldenberg, 2008), and conditions that affect health including the following: food insecurity (Cook et al., 2004; Cook & Frank, 2008; Walker, Keane, & Burke, 2010), poor quality of housing (Saegert & Evans, 2003), and inadequate education (Woolf, Johnson, Phillips, & Philipsen, 2007). In addition, numerous studies have demonstrated the ways in which the quality of care for low-income individuals is not comparable to that of others, which perpetuates inequitable outcomes (Institute of Medicine, 2002; Marmot & Commission on Social Determinants of Health, 2007).

Health professional students are more likely to come from higher income families than many individuals they will serve. From 1987 through 2005, between 48% and 51% of entering medical students came from the highest quintile of family income, while less than 5.5% of students came from the lowest quintile (Grbic, Jones, & Case, 2015). Subsequently, between 2010 and 2015, 19 million people gained Medicaid coverage under the Patient Protection and Affordable Care Act of 2010 (Robert Wood Johnson Foundation, 2016), increasing the number of formerly uninsured, largely low-income individuals able to access medical care. Research suggests health professional attitudes toward low-income patients are not always empathetic or free of negative judgments, potentially affecting provision of care (Loignon, Boudreault-Fournier, Truchon, Labrousse, & Fortin, 2014; Loignon et al., 2015; Wayne, Timm, Serna, Solan, & Kalishman, 2010).

The disconnect between the economic status (and associated life experiences) of health professionals and low-income populations in the United States can perpetuate existing health inequities in quality of care and health outcomes (Elias et al., 2016). Many health professionals will work intimately with populations struggling with poverty; therefore, providing adequate training to increase their understanding and reduce negative attitudes about underserved populations is critical for professional competence. Health professional students who gain an understanding of obstacles experienced by individuals with limited resources may be more effective and compassionate providers (Yang, Woomer, Agbemenu, & Williams, 2014). As such, there are documented efforts to expose medical, nursing, dental, psychiatric, pharmaceutical, and allied health care professional students to training that encourages less judgmental negative attitudes and stereotypes toward patients who are labeled as “poor” or “underserved” (Loignon et al., 2015; Mundon, Anderson, & Najavits, 2015; Thompson et al., 2015; Yang et al., 2014).

Students may struggle to understand those in poverty; those focusing on individual traits may identify laziness, personal choices, and lack of hard work as the determinants of poverty (Richey Smith, Ryder, Bilodeau, & Schultz, 2016; Vliem, 2015). These students may develop cynical or apathetic attitudes, adopt stereotypic assumptions, or overestimate the role of “hard work” in lifting individuals out of poverty (Richey Smith et al., 2016). These negative impressions of low-income people can interfere with equitable provision of social and health services (Loignon et al., 2015). Conversely, health professional students may learn to recognize structural factors that lead to poverty and affect health, such as discrimination, low wages, and differing educational opportunities (Richey Smith et al., 2016; Vliem, 2015). Students who consider the role of structural barriers within poverty have a greater desire to engage in advocacy and to indicate an interest in working with the poor (Richey Smith et al., 2016), which can increase the effectiveness of their professional interactions with low-income populations.

With increased recognition of the importance of social determinants of health, educators of health professionals are seeking effective mechanisms to broaden students’ understanding of these factors. Efforts at increasing student knowledge about poverty have been attempted conventionally through a combination of didactic presentations and clinical experiences (Johnson, Guillet, Murphy, Horton, & Todd, 2015) and to a lesser extent through poverty simulations and exercises (Patterson & Hulton, 2011). Poverty simulations can expose health professional students to a more holistic structural perspective and provide opportunities to learn in a structured and comfortable educational environment prior to, or in conjunction with, real world experiences (Yang et al., 2014). Simulations, generally (1) are imitative representations or models of an actual system or process designed for people to learn about a process without actually going through it and (2) use a simulated device to examine a problem without direct experimentation (Simulation, 2019). Poverty simulations aim to raise student awareness of issues confronted by those living in poverty and may include, for example, requiring participants to conduct online and in-person searches for specific resources (e.g., child care or assistance programs) to gain a sense of their accessibility, affordability, and eligibility requirements under prescribed circumstances or requiring participants to develop and manage a budget. Poverty simulations found in the literature vary widely from short on-line experiences to intensive, interactive, and community-based experiences; all aimed, to differing degrees, to expose students to poverty-related processes and issues. These simulations may challenge students to develop budgets at the poverty level, identify needed resources, and experience navigating social service systems. Simulations may be incorporated into existing curricula, associated with practice-based experiences, or conducted as stand-alone exercises and, in the literature, have primarily incorporated undergraduates. Evidence of the effect on students’ knowledge and attitudes about poverty varies across these examples.

Our simulation, developed within a full-time internship program (Bridging the Gaps–Pittsburgh) and utilized for over a decade, focuses primarily on graduate students in the health sciences and social work and incorporates specific components that differentiate it from others. This simulation, the Experiential Poverty Exercise (EP Exercise), has been shown to significantly improve students’ awareness of poverty. As faculty and graduate students engaged in Bridging the Gaps–Pittsburgh, and as creators of the EP Exercise, we sought to understand the current state of poverty simulations utilized throughout the United States and evidence of their effect on students. This article reviews the state of existing poverty simulations and the ways in which the EP Exercise in Bridging the Gaps–Pittsburgh aligns with and differs from these simulations. By understanding the current status of these simulations in the training of health professionals, we seek to develop recommendations for the implementation of poverty simulations in a variety of contexts in order to increase the preparedness of future health professionals to better serve those in poverty.

Method

The authors conducted a literature search for poverty simulations between 2002 and 2017 via OVID and Google Scholar, using combinations of search terms: poverty, poverty simulation, experiential learning, poverty exercise, interdisciplinary poverty training, and professional training. We located 51 articles via the search terms poverty simulation and experiential + poverty. Through a review of abstracts, we identified nine articles that focused directly on describing a poverty simulation in university-based programs with health or social work students with some form of pre- and postevaluation methods. We then isolated common, as well as unique, facets of the simulations and determined ways in which the EP Exercise of Bridging the Gaps–Pittsburgh compares with the nine described simulations, including demonstrated effects on student attitudes. All procedures have been approved by the University of Pittsburgh Institutional Review Board and considered exempt (STUDY19010096).

Results

The nine reviewed simulations differed across several facets, including (1) level and disciplines of students, (2) simulation structure and components, (3) use of financial management and budgeting, (4) exposure duration and context, (5) delivery method (online vs. in-person), and (6) methods of student attitude assessment, including quantitative evaluation and participant perspectives. See Table 1 for a summary of major components of the nine reviewed simulations from our search of the literature and those of Bridging the Gaps–Pittsburgh. Tables 2 and 3 include an overview of the various assessment methods used for each simulation, including Bridging the Gaps–Pittsburgh. We describe the distinct differences between the reviewed simulations, the unique aspects of Bridging the Gaps–Pittsburgh’s EP Exercise, and how effects on students are determined across the various simulations.

Table 1.

Characteristics of the Bridging the Gaps–Pittsburgh Experiential Poverty Exercise and the Nine Reviewed Simulations.

Authors	n (Total)	Level	Discipline	Delivery method	Simulation resource	Simulation duration
Bridging the Gaps–Pittsburgh Experiential Poverty Exercise	52 (19, 16, 17)^a	Majority graduate	Interdisciplinary: medical, public health, social work, pharmacy, dentistry and (undergraduate) nursing	In-person (faculty)	Experiential Poverty Exercise (self-created)	5 hours
Clarke, Sedlacek, and Watson (2016)	108	Early professional	Pharmacy	In-person (combination of community volunteers, faculty, and university staff)	CAPS	3 hours
Johnson, Guillet, Murphy, Horton, and Todd (2015)	Not reported	Undergraduate	Nursing	In-person (didactic—faculty, practicum in community setting)	In their shoes (self-created)	3 days (2 didactic classes; 1 Practicum day)
Lampiris, White, Sams, White, and Weintraub (2017)	158 (80, 78)^b	Graduate	Dental	In-person (1st year: staff from the United Way of the Triangle; 2nd year: faculty)	CAPS	3 hours
Menzel, Willson, and Doolen (2014)	98^c	Undergraduate	Nursing	Online (faculty in simulation roles, faculty-led debrief session)	Second Life—Simulation Program (self-created)	2.5 hours
Noone, Sideras, Gubrud-Howe, Voss, and Mathews (2012)	209^c	Undergraduate	Nursing	In-person (faculty led; community/staff volunteers)	CAPS	3 hours
Patterson and Hulton (2011)	43	Undergraduate	Nursing	In-person (community/staff volunteers)	CAPS	3 hours
Richey Smith, Ryder, Bilodeau, and Schultz (2016)	373 (240, 127, 113, 36, 30)^d	Undergrad/early professional	Multiple-discipline: pharmacy, physical assistant, communication science and disorder	Online (faculty facilitators)	SPENT	50 minutes
Vliem (2015)	44^c	Undergraduate	Nursing	Online (faculty arranged field experience)	SPENT	2 hours (online game + 90 minute field experience with individuals in poverty)
Yang, Woomer, Agbemenu, and Williams (2014)	233 (83, 75, 75)^e	Undergraduate	Nursing	In-person (faculty, staff, community members from local agencies)	CAPS	2 hours

Note. CAPS = Community Action Poverty Simulation developed by the Missouri Community Action Network.

THree years (2015, 2016, and 2017). ^bTwo years (2015 and 2016). ^cStudy contains both intervention (those exposed to the poverty exercise/simulation) and control participants. ^dFive disciplines, breakdown only available for pre–post. ^eThree semesters.

Table 2.

Quantitative Assessment Procedures of the Bridging the Gaps–Pittsburgh Experiential Poverty Exercise and the Nine Reviewed Simulations.

Authors	n (Total)	No. of pre/postassessments	Time between pre and post	Quantitative measure	Measure	Focus of measure	No. of Qs	Assessment type	Statistical significance	Significance of individual Qs
Bridging the Gaps–Pittsburgh Experiential Poverty Exercise	52^a	52	7 weeks	Y	PAAUS (Self-Developed)	Awareness, understanding and attitudes	9Q	Paired t-test	Yes	Reported elsewhere
Clarke, Sedlacek, and Watson (2016)	108	108	7 days (up to 3 days prior and 3 days post)	Y	ATP Short Form	Attitudes	21Q	Paired t-test	Yes, for individual questions and for the Stigma and Structural factors (p ≤ .05)	15 of 21
Johnson, Guillet, Murphy, Horton, and Todd (2015)	Not reported	NA	NA	N
Lampiris, White, Sams, White, and Weintraub (2017)	158^b	127	None—retrospective reporting on change	Y	1. Understanding of Low-income challenges (self-developed) 2. Value of exercise	Understanding and Value	1. 5Q 2. 1Q	1. Descriptive Statistics 2. Cochran-Mantel-Haenszel statistic	1. NA 2. Yes (p = .0022)	Not assessed
Menzel, Willson, and Doolen (2014)	98^a	51 (33 intervention; 18 control)	Up to 2 weeks (1 week before to 1 week after simulation)	Y	ATP Long Form + 8 additional questions on health and poverty	Attitudes and relationship of poverty to health	45Q	1. Independent t-tests (control vs. intervention)2. Paired t-tests (within group)	1. No, for scale as a whole; Yes, for some individual questions (p ≤ .05)2. No, for scale as a whole; Yes, for some individual questions (p ≤ .05)	1. 5 of 452. 8 of 45
Noone, Sideras, Gubrud-Howe, Voss, and Mathews (2012)	209	178 (103 intervention; 75 control)	6 to 7 weeks	Y	ATP Short Form	Attitudes	21Q	ANCOVA (control vs. intervention)		Not assessed
Patterson and Hulton (2011)	43	43	Not reported	Y	ATP Short Form	Attitudes	21Q	Paired t-test	Yes, for individual questions and for the stigma factor (p < .05)	4 of 21
Richey Smith, Ryder, Bilodeau, and Schultz (2016)	373	306	1 to 2 weeks	Y	Undergrad Perceptions of Poverty Tracking Survey	Attitudes, empathy, and commitment	39Q	Paired t-test	Yes, overall scale score (p < .0005)	Not assessed
Vliem (2015)	44	44 (18 intervention; 26 control)	~1 semester	Y	ATP Short Form	Attitudes	21Q	1. Independent t-tests (control vs. Intervention.2. Paired t-tests (within group)	1. Yes, overall scale (p < .01); none of the 3 factors2. Yes, 2 items in the Stigma factor (p < .05)	2 of 21
Yang, Woomer, Agbemenu, and Williams (2014)	233	199 (137^c; 62^d)	2 hours	Y	1. Poverty Simulations Reaction Questionnaire^c 2. ATP Short Form^d	1. Understanding/ Attitudes^c 2. Attitudes^d	1. 5Q^c 2. 21Q^d	Paired t-test	1. Individual questions (p < .001)^c 2. Yes, overall scale score and Stigma factor (p < .001)^d	1. 5 of 5^c 2. Not assessed^d

Note. PAAUS = Poverty Attitude, Awareness and Understanding Survey; ATP = Attitude Toward Poverty Scale; ANCOVA = analysis of covariance; NA = not applicable.

Three cohorts. ^bTwo cohorts. ^cCohorts I and II only. ^dCohort III only.

Table 3.

Qualitative Procedures of the Bridging the Gaps–Pittsburgh Experiential Poverty Exercise and the Nine Reviewed Simulations.

Authors	n (Total)	Qualitative participants	Qualitative measure	Method	No. of Qs	Results format
Bridging the Gaps–Pittsburgh Experiential Poverty Exercise	52^a	52	Y	Discussion-based qualitative feedback	NA (open-ended discussion)	Reported elsewhere
Clarke, Sedlacek, and Watson (2016)	108		N
Johnson, Guillet, Murphy, Horton, and Todd (2015)	Not reported	Not reported	Y	Discussion-based qualitative feedback	Not specified	Informal discussion summary
Johnson, Guillet, Murphy, Horton, and Todd (2015)	158^b	99	Y	Written qualitative feedback	3Q	Summary of comments
Lampiris, White, Sams, White, and Weintraub (2017)	98^a		N
Noone, Sideras, Gubrud-Howe, Voss, and Mathews (2012)	209		N
Patterson and Hulton (2011)	43	43	Y	Written qualitative feedback	4Q	Categorized into themes with representative quotes
Richey Smith, Ryder, Bilodeau, and Schultz (2016)	373	373	Y	Written qualitative feedback	Not specified	Categorized into themes with representative quotes
Vliem (2015)	44		N
Yang, Woomer, Agbemenu, and Williams (2014)	233	199 (137^c; 62^d)	Y	1. Written Poverty Simulation Reaction Questionnaire^c 2. Follow-up survey–influence on practice^d	1. 3Q^c 2. Not specified^d	1. Not reported^c 2. Categorized into themes with representative quotes^d

Note. NA = not applicable.

Three cohorts. ^bTwo cohorts. ^cCohorts I and II only. ^dCohort III only.

Level and Disciplines of Participants

Six poverty simulations enroll undergraduate nursing students exclusively (Table 1; Johnson et al., 2015; Menzel et al., 2014; Noone et al., 2012; Patterson & Hulton, 2011; Vliem, 2015; Yang et al., 2014). The majority of these nursing programs indicate simulations should help future nurses to provide patient-centered care and to appreciate the link between poverty and health. Each of these simulations were implemented within a university class curriculum, such as a didactic community health course entitled “Community as Partner: Care of Vulnerable Groups” or the course “Childrearing Families: Wellness and Health Promotion” (Patterson & Hulton, 2011; Vliem, 2015).

Of the three simulations not provided for nursing students, one involved second-year pharmacy students, without clarifying undergraduate or graduate level (Clarke et al., 2016). In this program, didactic and experiential requirements for learning about social determinants of health are placed throughout the curriculum of the 4-year professional program. A second simulation included a multidisciplinary group, which consisted of students in early years of a PharmD program, physician assistant students, and undergraduates pursuing careers in communication disorders (Richey Smith et al., 2016). These students experienced the online poverty simulation at the same university but in their separate discipline-based classes. The final reviewed simulation was offered to third-year dental students as a part of their university curriculum (Lampiris et al., 2017).

Simulation Structure and Components

Simulations Using Community Action Poverty Simulation

Five of the poverty simulations utilized a kit created by Missouri Community Action Network (Clarke et al., 2016; Lampiris et al., 2017; Noone et al., 2012; Patterson & Hulton, 2011; Yang et al., 2014), a statewide association of agencies united to end poverty (Missouri Community Action Network, 2017; Table 1). This kit, the Community Action Poverty Simulation (CAPS) is a 3-hour, in-person poverty simulation developed to educate and sensitize participants to the realities of living with poverty. Participants play the role of one of 26 low-income families, ranging from an elderly person living alone to a multigenerational family with children (Clarke et al., 2016; Lampiris et al., 2017; Noone et al., 2012; Patterson & Hulton, 2011; Yang et al., 2014). Participants are seated in the middle of a large room with tables around the perimeter, where mock “resources” are located (i.e., pawn shop, childcare center, employer, grocery store, etc.). Approximately 15 volunteers, trained in an hour-long orientation, portray these community resource representatives with whom students interact (Patterson & Hulton, 2011). Participants simulate going to work and school, buying food, paying bills, and obtaining services, and then experience scenarios that affect their daily lives and expenses (Clarke et al., 2016; Lampiris et al., 2017; Noone et al., 2012; Patterson & Hulton, 2011; Yang et al., 2014). Scenarios may help or hinder families’ abilities to meet their personal and financial responsibilities; some families gain employment or receive financial assistance, while others incur unexpected expenses. Luck-of-the-draw cards are drawn by families during the simulation. Good luck may provide unexpected funds such as a cash birthday present, and bad luck may bring an illness or a repair bill (Clarke et al., 2016).

Simulations Using SPENT

Two experiential poverty simulations incorporated a free, online game, SPENT (Richey Smith et al., 2016; Vliem, 2015). SPENT, created by the ad agency McKinney for pro bono client Urban Ministries of Durham (Urban Ministries of Durham, 2012), is a scenario driven simulation with a monetary component (i.e., every action made in the game can dramatically decrease the amount of available money). Depending on participant decisions, the simulation takes approximately 10 to 25 minutes to complete. During the simulation, facilitators ask students to note their decisions for use in classroom discussion (Richey Smith et al., 2016). In the two online simulations that utilize SPENT, pharmacy (Richey Smith et al., 2016) or nursing (Vliem, 2015) students are each assigned the role of a working, poor, single-parent family with an income between 100% and 133% of the Federal Poverty Level. Next, scenarios are introduced that affect participants’ finances based on their decisions (Richey Smith et al., 2016; Vliem, 2015). For example, a scenario may require the player to decide whether to call-in sick to work. If the player calls-in sick, they receive a “strike” and a decrease in their amount of money; three “strikes” and they are released from employment. The game ends when the player runs out of money or completes the month with money left-over to use for the next month’s rent (Richey Smith et al., 2016).

Simulation Using Second Life

The eighth reviewed simulation incorporated an experiential element from the Second Life virtual reality platform (Second Life, 2018). In this simulation, the design team created two families with poverty-related factors that nursing students often encountered in their community clinical experiences, with avatars corresponding to each character (Menzel et al., 2014). One family is a matriarchal homeless family who experiences job losses, subsequent eviction, and the loss of health insurance. This family has a variety of poor health conditions. Additionally, the adults do not have education beyond high school, and the children face challenges in school. The other family is an immigrant family whose members face language, legal documentation, educational, and cultural barriers. Participants are introduced to scenarios based on their assigned family and navigate these scenarios via their avatars. Faculty (in the form of avatars) act as resource representatives, and participants complete life tasks within an allotted amount of time.

Simulation Using “In Their Shoes.”

For the last simulation reviewed, Johnson et al. (2015) describe the faculty-created simulation for nursing students, “In Their Shoes.” This simulation consists of several scenarios of clients needing health and social services, based on experiences faculty members encountered in their public health nursing practice, and range from a low-income family of six to a homeless adolescent mother. This simulation sends participants into the community on a scavenger hunt to locate resources for the people in their scenario. For example, students assigned the adolescent mother scenario often decided to visit legal services to learn more about the emancipation process. Students were required to use public transportation to get to relevant resources (Johnson et al., 2015).

Financial Management and Budgeting

Seven of the reviewed simulations mandated students to create monthly budgets for assigned families and provided students scenarios that would affect their budget, such as rent increases, unemployment, and injury (Clarke et al., 2016; Lampiris et. al., 2017; Menzel et al., 2014; Noone et al., 2012; Patterson & Hulton, 2011; Richey Smith et al., 2016; Vliem, 2015). Some poverty simulations have an active budgeting component, requiring participants to adjust their budgets in response to events. The simulations that utilize CAPS give budgets to each family unit, and the participants must actively monitor and maintain that budget throughout the simulation (Clarke et al., 2016; Lampiris et al., 2017; Noone et al., 2012; Patterson & Hulton, 2011; Yang et al., 2014). The budget is affected by the different scenarios and associated budgeted expenses, such as daycare costs and health care needs. While SPENT does have a monetary component, the online program calculates the changing monthly balance based on user decisions without the participant having the power to otherwise adjust the overall budget. Second Life participants must stay within allotted funds as they navigate scenarios, and “In Their Shoes” does not require budgeting within the simulation.

Exposure Duration and Context

Across the nine reviewed simulations, the exposure duration and context in which they were conducted varied greatly (Table 1). Of those reporting simulation duration, the length ranged from 50 minutes (including discussion) to multiple sessions across three days with an average length of approximately 3 hours. Many of the simulations were conducted within the framework of a curriculum, which ranged from a semester-long course to isolated events, such as a single lecture. Those that exist within a curriculum structure also varied across type of class; several simulations were part of mandatory courses in population-based care or community health. Overall, the simulation contexts varied in the amount and type of exposure health professional students received for working with individuals in poverty.

Delivery Method

The delivery method for the nine poverty simulations range from entirely online to real world engagement (Table 1). Three simulations primarily used online delivery with the remaining six utilizing in-person methods. The two simulations that used the SPENT curriculum were primarily facilitated online (Richey Smith et al., 2016; Vliem, 2015), with one providing an additional faculty-arranged field experience, a church dinner for those in poverty in the community (Vliem, 2015). The third with online delivery, Second Life, trained faculty to play roles interacting with students in the web-based simulation (Menzel et al., 2014). Of the six simulations using in-person delivery, the five CAPS-based simulations utilized a faculty-led format with community and staff volunteers to work community service stations (Clarke et al., 2016; Lampiris et al., 2017; Noone et al., 2012; Patterson & Hulton, 2011; Yang et al., 2014). The sixth in-person simulation, “In Their Shoes,” sent students on a community-based scavenger hunt, via public transportation, to access health and social services, influencing student understanding of the challenges faced by underserved populations (Johnson et al., 2015).

Three of the reviewed simulations sought to compare two differing delivery approaches to facilitate understanding poverty. In the first, researchers examined whether the interactive virtual poverty simulation created in Second Life would improve baccalaureate nursing students’ empathy with people living in poverty compared with a self-study module (Menzel et al., 2014). In the second, the intervention group utilized CAPS, and the control group was assigned the standard undergraduate nursing curriculum on poverty at the university (Noone et al., 2012). The third recruited students to participate in SPENT and/or the relevant assessment measures and utilized those students who consented only to the measures as a control group (Vliem, 2015).

Assessment of Simulation Effects

Of the nine poverty simulations reviewed, eight conducted quantitative pre- and posttesting to evaluate change in attitudes and perceptions of poverty among the participants (Table 2; Clarke et al., 2016; Lampiris, et al., 2017; Menzel et al., 2014; Noone et al., 2012; Patterson & Hulton, 2011; Richey Smith et al., 2016; Vliem, 2015; Yang et al., 2014).

Six of the simulations utilized a version of the Attitude Toward Poverty Scale (ATPS) for the pre- and postsurveys (Clarke et al., 2016; Menzel et al., 2014; Noone et al., 2012; Patterson & Hulton, 2011; Vliem, 2015; Yang et al., 2014). This scale uses a 5-point Likert-type response option, ranging from strongly agree to strongly disagree. While the scale was originally developed as a 37-item questionnaire, it is also used in shorter form with 21 items split into three factors: stigma, structural perspective, and personal deficiency (Yang et al., 2014). Both the original ATPS and the short-form version have been previously validated with a Cronbach’s alpha of .93 and .87, respectively (Atherton et al., 1993; Ritten, Waldrop, & Wink, 2015; Yun & Weaver, 2010). The three factors in the short-form version also showed internal consistency (Cronbach’s alpha ranging from .50 to .70; Yang et al., 2014). Five of these six simulations used the short-form version of the scale.

Two of the simulations used self-developed quantitative survey measures—one as its sole assessment measure (Lampiris et al., 2017) and the other as a measure with two study cohorts followed by the ATPS in a later cohort (Yang et al., 2014). The seventh program utilized the Undergraduate Perceptions of Poverty Tracking Survey to measure student attitudes (Richey Smith et al., 2016). The creators of this scale specifically validated it for use in undergraduate populations, adding questions about understanding of, and empathy for, those living in poverty and student commitment to addressing poverty. These additions complement the previously validated ATPS questions on general attitudes toward those living in poverty (Blair, Brown, Schoepflin, & Taylor, 2014). See Table 2 for brief descriptions of the quantitative assessment procedures for the studies included in this analysis.

Four of the nine simulations conducted testing in relatively close temporal proximity to the poverty simulation, for example, less than 2 weeks between the pre- and posttests, to analyze the effects of the simulation (Clarke et al., 2016; Menzel et al., 2014; Richey Smith et al., 2016; Yang et al., 2014). The time between pre- and posttests varied from 2 hours to approximately 15 weeks. Two of the nine simulations conducted testing at the beginning and end of their specific curriculum to determine effects of the poverty simulation and other core assignments on attitudes toward underserved populations (Noone et al., 2012; Vliem, 2015). One simulation used retrospective data collection methods to conduct pre- and posttest assessments simultaneously on self-reported changes (Lampiris et al., 2017). Finally, one simulation did not report the amount of time between assessments (Patterson & Hulton, 2011).

Among other statistical procedures, six simulations used paired t-testing to compare understanding and attitudes toward poverty between pre- and postsimulation among those exposed (Clarke et al., 2016; Menzel et al., 2014; Patterson & Hulton, 2011; Richey Smith et al., 2016; Vliem, 2015; Yang et al., 2014). Two of these simulations revealed a statistically significant change for the overall scale regarding attitude toward poverty (Richey Smith et al., 2016; Yang et al., 2014). The remaining four simulations found statistically significant individual questions or one or two statistically significant factors (Clarke et al., 2016; Menzel et al., 2014; Patterson & Hulton, 2011; Vliem, 2015). The most common factor or question of statistical significance among these studies is the ATPS short-form “stigma” factor, which includes questions such as follows: “Poor people think they deserve to be supported” and “An able-bodied person collecting welfare is ripping off the system” (Yun & Weaver, 2010).

As three of the nine simulations included control groups along with those exposed to the poverty simulation, two of these studies also conducted independent t-test measures to assess differences between these two groups (Menzel et al., 2014; Vliem, 2015). One of these found significant differences between the groups on individual questions (Menzel et al., 2014), and the other found statistical significance on the scale overall between the two groups (p < .01), where the intervention group’s attitudes toward people in poverty significantly improved over those in the control group (Vliem, 2015). The third of these simulations conducted an analysis of covariance on post-test ATPS scores given the differences on pretest measures, finding that corrected posttest mean scores for the experimental group were significantly higher than for the control group (Noone et al., 2012). The final simulation utilized a Cochran–Mantel–Haenszel statistic on their self-developed one-question measure on the value of the poverty exercise with statistically significant results (Lampiris et al., 2017).

Participant Perspectives

Four of the nine reviewed simulations supplemented their quantitative methods by collecting qualitative reflections in oral or written form (Table 3; Lampiris et al., 2017; Patterson & Hulton, 2011; Richey Smith et al., 2016; Yang et al., 2014). The one simulation that did not collect quantitative data did gather student perceptions in a discussion-based format (Johnson et al., 2015).

Shared perceptions covered three major topics: (1) reflections on the simulation process, (2) thoughts on awareness and challenges of poverty, and (3) ways the exercise influences practice. Student reflections on the simulation process ranged from eye-opening, good experiences to concerns about the exercise not being taken seriously by peers (Lampiris et al., 2017; Richey Smith et al., 2016); others discussed the value and challenges of the exercise for experiencing the “reality” of poverty (Patterson & Hulton, 2011) and for sharing knowledge about poverty with fellow participants (Lampiris et al., 2017). Students indicated the simulation raised awareness and understanding about barriers and challenges faced by those in poverty and the resources to address those challenges. For example, participants identified barriers to health care (Yang et al., 2014), frustration with long lines for services (Patterson & Hulton, 2011), and challenges for accessing resources, including transportation (Johnson et al., 2015). Finally, participants in several of the simulations identified ways the exercise would affect their future and current health practice, which included being mindful during treatment of the challenges low-income patients face and the types of resources potentially available (Johnson et al., 2015; Lampiris et al., 2017; Yang et al., 2014).

Bridging the Gaps–Pittsburgh and the EP Exercise

An additional simulation, the Experiential Poverty Exercise of Bridging the Gaps–Pittsburgh (EP Exercise), differs in keyways from the simulations reviewed in the literature. Bridging the Gaps–Pittsburgh is a full-time, 8-week multidisciplinary program of graduate-level students from the schools of pharmacy, medicine, public health, and social work, as well as a cohort of senior nursing students at the University of Pittsburgh. Bridging the Gaps–Pittsburgh is a member, and follows the program model, of the Bridging the Gaps Network (Bridging the Gaps, 2018), a collaboration among multiple universities that provide health professional training in Pennsylvania and New Jersey and more than 100 community organizations. The program requires students to work directly with underserved populations and discover their health concerns and needs, while providing outreach and support to organizations on the “front lines” of health care. Each summer, the EP Exercise is conducted with 16 to 20 Bridging the Gaps–Pittsburgh students. Unlike eight of the nine simulations reviewed, which focus on undergraduate students, the EP Exercise primarily engages graduate students. Also, compared with eight of the nine simulations, Bridging the Gaps–Pittsburgh provides a longer, 5-hour exposure in the EP Exercise, conducted in-person during one of 8 weekly, day-long reflective sessions and facilitated by the program director.

To prepare for the EP Exercise, students research specific governmental resources (e.g., Medicaid and SNAP [Supplemental Nutrition Assistance Program]), as well as costs of living (e.g., local housing, childcare, grocery lists, medication, transportation) and are required to bring corresponding documentation to the EP Exercise. Before the simulation component begins, students receive an hour presentation on poverty statistics in the United States, including breakdown by gender, race, age, (dis)ability, and rurality. At the beginning of the EP Exercise, the students are assigned to sit together in one of five family scenarios, including a recently single mother with two children and two jobs, two married families with multiple children, a single man in drug and alcohol recovery, and an elderly woman living alone. Each “family” group then completes a month’s budget tailored to their family needs, including employment income from classifieds and cost of living information collected from their peers. The faculty facilitator and graduate assistant act as supplemental “government” resources regarding eligibility criteria for assistance programs as needed.

Once each group’s budget is calculated, the facilitator introduces multiple “life event” scenarios that require adjusting the family budget and discussing the effects of any decision on the family. For example, apartment rent may increase by 15%, and the family must recalculate their monthly budget to determine whether they can remain or afford to move. Another scenario is that of managing a sick child, wherein students must decide to stay home from work despite employer mandates otherwise, allow the child to be at home alone, or determine who might be available in their lives to assist. Other scenarios include cancelled critical bus lines, a broken vehicle, and gaining a new job that requires purchasing professional clothing. Students are advised to prepare to defend their decisions to the larger group. At the conclusion of the exercise, students debrief as a large group, comparing decisions made after each “life event” scenario and learning of the resulting effects on different families. Students have the opportunity to discuss surprises and frustrations and to discover knowledge among their peers of different professional training. The facilitator leads students in a discussion of the social and structural determinants affecting families’ available options and ways they differentially affect family members.

The Bridging the Gaps–Pittsburgh program administers internally developed pre- and posttests regarding students’ knowledge and attitudes about poverty via questions using a 5-point Likert-type scale. Similar to two reviewed studies (Lampiris et al., 2017; Richey Smith et al., 2016), facilitators of Bridging the Gaps–Pittsburgh determined changes in awareness are necessary before expecting meaningful changes in attitudes. As such, the Bridging the Gaps–Pittsburgh measure (Poverty Attitude, Awareness and Understanding Survey [PAAUS]) includes seven questions to explore student awareness of poverty aspects, and two questions regarding attitudes about poverty that students will carry into future practice. Assessing 3 years of cohorts using paired t-tests, the nine-question scale indicates statistically significant change in students’ combined awareness and attitudes (p < .0001). Individual questions also indicate statistically significant change and are reported elsewhere.

In addition to quantitative assessment, Bridging the Gaps–Pittsburgh collected participant reflections on the EP Exercise. Similar to other reported qualitative reflections, participants noted learning about the frustrations and challenges faced by those in poverty along with the vast array of resources. Additional reflections from EP Exercise participants include: comments about the diversity of families in the scenarios (e.g., race/ethnicity, sexuality/gender identity, and disability status), the relevance of other factors affecting poverty (e.g., adverse childhood events, minimum/living wage issues, and student loan debt), differences in geographic location (e.g., urban vs. rural), and the importance of the group debriefing portion of the session to their learning during the poverty exercise experience.

Discussion

In this article, we sought to identify and compare existing poverty simulations. We also reviewed how the EP Exercise, within the context of a multidisciplinary and graduate-level program such as Bridging the Gaps–Pittsburgh, can serve as a model to expose future health professionals to challenges underserved populations face. Through this exploration, we uncovered potential recommendations around participant characteristics as well as simulation context, components, and assessment that could inform those seeking to implement poverty simulations in the future.

Multidisciplinary Participants and Interdisciplinary Learning

The majority of poverty simulations reviewed were geared toward undergraduate nursing students, and only one of the simulations, aside from Bridging the Gaps–Pittsburgh, incorporates multiple disciplines (Richey Smith et al., 2016). Bridging the Gaps–Pittsburgh is the only program in which students from five different health profession-related disciplines (pharmacy, nursing, medicine, public health, and social work) experience the simulation together, for dynamic interdisciplinary learning. In the Bridging the Gaps–Pittsburgh program, students find going through the EP Exercise in close collaboration with those of different health professional training to be extremely helpful in expanding their knowledge of underserved populations, resources, and systems. For example, the knowledge of pharmacy students on medication resources can be invaluable to a student group tasked with problem solving for an elderly woman in poverty. These interactions also provide opportunities for clinically oriented students to gain a wider perspective on patients’ lives and access to resources. Medical students, for example, often indicate surprise and appreciation of social work students’ awareness of services when trying to problem-solve for their assigned families. In Bridging the Gaps–Pittsburgh, we have found these interdisciplinary interactions to enhance learning and shift attitudes in poverty simulations. Also, based on student feedback, we expect discussions across disciplines, which raise student awareness of each discipline’s strengths, may contribute to future collaborative work—particularly for those who choose to work with vulnerable populations.

Amount and Context of Exposure Matter

Across the reviewed simulations, the amount and type of exposure to learning varied greatly from a relatively brief online experience with discussion (Richey Smith et al., 2016) to an entirely in-the-field experience over several days (Johnson et al., 2015). As the direct comparison of the quantitative measures utilized in all simulations is not possible due to the use of differing scales, the amount of exposure to learning cannot be directly correlated with the significant results found. However, we posit that the amount as well as quality of the exposure may create differing effects for students of various backgrounds and professional levels. For example, the in-person nature of the EP Exercise of Bridging the Gaps–Pittsburgh augments intentionally interdisciplinary aspects of the broader internship program. The immersive elements of an in-person exercise allow for the direct reflection or sharing of frustrations and resources to occur in real-time among participants. Students who have limited experience with real world budgeting challenges, or with challenges specifically tied to living below the poverty level, learn a tremendous amount from their peers who have personal life experience or professional training in identifying resources and strategies for managing budgets.

Another challenge in comparing exposure time within the reviewed simulations is the differing contexts in which they were conducted. Some of these simulations took place within courses where additional material on poverty is presented, and others accompany field-placements, practicums, or other forms of direct community exposure. From this variation, we acknowledge the effects of the simulation in isolation may not capture the entire exposure students have or will receive. For example, Bridging the Gaps–Pittsburgh, tailoring the Bridging the Gaps model (Bridging the Gaps, 2018), fully immerses students in the lived experiences of the regions’ most vulnerable populations four days per week for eight weeks each summer. Students also experience their intensive community site placement in interdisciplinary pairs allowing for opportunities to trade knowledge and perspectives and to provide peer support. Didactic and reflective days are held once per week for the duration of the practicum. The EP Exercise is held the second week of the program, after students have spent 6 days working directly with specific populations served by host community organizations. During the extensive EP Exercise debrief, students are invited to draw connections between their simulation experience and their observations working with the populations at their site. Throughout the 8-week practicum, the facilitators refer students back to their experience budgeting and making decisions in the EP Exercise to enhance understanding of populations with which they are working. Other reflective sessions in this program typically include speakers on topics related to vulnerable populations (e.g., health inequities, community violence, health literacy, oral health) in addition to discussion among interns regarding their experiences working directly with vulnerable populations.

Importance of Simulation Debriefing and Discussion

Discussion among participants may bolster the effects of the simulation by allowing students to learn from each other’s experiences as well as to process their reactions to the exercise. Those planning to conduct poverty simulations may want to intentionally include participant discussion to augment simulation evaluation and to enhance the effects of the simulation itself. An additional critical simulation element that may generate changes in attitude is that of assigning participants roles and the scenarios that accompany them. These stressful events, such as unexpected medical expenses, increases in housing costs or loss of childcare, can cause the participants significant frustration. Discussion after the simulation is critical for participants to process the experience beyond the mathematical challenges of budgeting at the poverty level. Student feedback on the EP Exercise consistently indicates the importance of these discussions. One reviewed simulation found that, while role playing during the simulation is admittedly not likely to result in an exact replication of the experience of poverty, the students participating in the simulation gained empathy about the range of possible experiences those that are impoverished might experience (Yang et al., 2014).

Assessment Types and Findings

Over the years that Bridging the Gaps–Pittsburgh has conducted the EP Exercise, we sought to develop a quality improvement measure to capture the effect of the EP Exercise on the awareness and future attitudes of the interns. Over time, this goal organically resulted in our PAAUS measure. In this review, most of the simulations utilize the ATPS in either its long or short form. This scale, in addition to focusing on attitudes rather than awareness or understanding, has 21 questions (compared with 9 in PAAUS) and has primarily been used and validated in undergraduate-level students. As discussed, different simulation forms may be more appropriate for graduate advanced students who are closer to direct entry into practice than those earlier in their professional careers, which suggests measures that can capture varying levels of students’ perceptions of poverty may be necessary to correspond to differing simulation applications.

Additionally, further exploration of the appropriate constructs for various simulations should be considered. While attitudes toward those in poverty may capture one aspect of the effects of a poverty simulation, measures should account for the upstream concepts of awareness and understanding of poverty, which likely change in students before shifts in attitudes are possible. In addition to Bridging the Gaps–Pittsburgh’s measure, two of the reviewed simulations considered this challenge and utilized either their own understanding-based measure (Lampiris et al., 2017) or the UTTPS, a validated augmented version of the ATPS (Richey Smith et al., 2016). Moving forward, simulations should consider the audience, context, and constructs for measurement when selecting a form of assessment. Finally, collecting qualitative data on student perceptions contributes to the overall understanding of the impact of poverty simulations.

Conclusion

While introductory, online, or brief simulations may be effective for students earlier in their training as a method to introduce concepts on challenges and resources related to poverty, advanced graduate-level students may benefit from an immersive, in-person, interdisciplinary experience. In-person poverty simulations can be time- and resource-intensive and, as such, need to demonstrate purpose and effectiveness. Measures should reflect that awareness and understanding logically precede attitude and be able to capture changes at each stage. Ideally, these measures could incorporate aspects of the simulation that are enhanced due to the stage of graduate student education and training as well as the potential benefits of interdisciplinary exchanges. Finally, the timing of pre–post testing should be taken into consideration so simulation context can be better understood; whether a posttest is held the day of the simulation or weeks after additional exposure, as well as the nature of that exposure, clearly affects findings.

Beyond training health professional students, we have provided modified versions of the EP Exercise to Med-Ped residents as part of their training and to volunteers at a local free clinic. We believe that members of many organizations, including foundations, governing boards, hospital administration, and legislators may find the process of engaging in an intensive poverty simulation to be startling and potentially instructive.

Poverty is a key social determinant of health that affects inequities in access to care and quality of care. Understanding how poverty and other social determinants create health inequity is an important component of all health professional education (Clarke et al., 2016). Simulations, such as the EP Exercise in Bridging the Gaps–Pittsburgh, can serve as models for how to incorporate an interdisciplinary, in-person, intensive exposure to graduate health professional students. The results of this review of poverty simulations indicate that participation leads to greater empathy for the experiences of low income people and higher levels of understanding of barriers to health care, and students who experience poverty simulations have a greater endorsement of a structural perspective on the link between poverty and health (Noone et al., 2012; Vliem, 2015). While simulations may vary in context, length, and delivery method, exposing future health professionals to challenges faced by the poor and the structural nature of their situations may affect their interactions as professionals. Students who develop an appreciation for the structural challenges of poverty can become professionals who collaborate across health professional-related disciplines to positively affect the range of determinants that influence health. Likewise, health professional students who gain understanding about, and empathy for, those whose lives are affected by the challenges of poverty, can provide more compassionate and competent care, favorably affecting health outcomes.

Footnotes

Acknowledgements

The authors acknowledge Suzanne Colvin, MA, for her early work in developing what would become the EP Exercise.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jessica R. Thompson

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