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Journal of Poverty

ISSN: 1087-5549 (Print) 1540-7608 (Online) Journal homepage: http://www.tandfonline.com/loi/wpov20

Barriers to program completion of a voluntarycapacity-building group intervention forindividuals living in poverty

Elizabeth A. Wahler & Amanda Adhami

To cite this article: Elizabeth A. Wahler & Amanda Adhami (2018): Barriers to program completionof a voluntary capacity-building group intervention for individuals living in poverty, Journal ofPoverty

To link to this article: https://doi.org/10.1080/10875549.2017.1419528

Published online: 08 Jan 2018.

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Barriers to program completion of a voluntarycapacity-building group intervention for individuals livingin povertyElizabeth A. Wahler and Amanda Adhami

Indiana University School of Social Work, Indianapolis, Indiana, USA

ABSTRACTAlthough poverty is a multifaceted social problem perpetuatedby structural forces, interventions often require attendance andparticipation in programs that can be difficult for peopleexperiencing poverty-related barriers. This project utilized sec-ondary data from an evaluation of a 15-session group-basedcapacity-building intervention (Getting Ahead in a Just Gettin’-By World) to examine predictors of program completion.Results indicated that only lack of interest (inversely) and beliefin the possibility of changing the future (positively) were pre-dictive of program completion. No other barriers were signifi-cantly associated with completion. Limitations, as well asimplications for practice and future research, are discussed.

ARTICLE HISTORYReceived 11 September 2016Accepted 3 July 2017

KEYWORDSEconomic mobility; efficacy;getting ahead; hope;poverty

Poverty is a pervasive problem in America, affecting nearly 15% of thepopulation (U.S. Census Bureau, 2015). Though there has been a steadygrowth in real per capita GDP, the US poverty rate has stagnated despitechanges in labor force, increases in antipoverty programs that encouragework, and federal programs and tax provisions that have aimed to reducepoverty (Hoynes, Page, & Huff Stevens, 2006). The “war on poverty” inAmerica has been long, challenging, and largely unsuccessful; many strategiesutilized for helping people in poverty have merely assisted them in getting by,rather than getting ahead, and poverty continues to be difficult to escape(Aaronson & Mazumder, 2008; Corak, 2013).

Many different factors affect the poverty level, including systemic andstructural forces as well as individual barriers to economic mobility. Overthe years, changes in poverty at a structural level have been influenced by thechanges in labor market opportunities, female labor force participation,family structure, government assistance, and immigration (Hoynes et al.,2006). Furthermore, poverty is perpetuated at the structural level by unem-ployment rates, median wages, and wage inequality in the lower half of thewage distribution. At the microlevel, the effects of poverty are often

CONTACT Elizabeth A. Wahler bwahler@iupui.edu Indiana University School of Social Work, 902 W. NewYork Street, ES 4158, Indianapolis, IN 46202, USA.

JOURNAL OF POVERTYhttps://doi.org/10.1080/10875549.2017.1419528

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interrelated and can serve as barriers to economic mobility and stability.Families living in poverty are confronted with high unemployment rates, joband earnings discrimination, and poor educational systems, which can leadto poor living conditions, nutrition, and increased susceptibility to illness anddisease (Austin et al., 2004). Additionally, poverty can also result in higherstress levels (Mirowsky & Ross, 2003), lower levels of self-efficacy (Dahling,Mellow, & Thompson, 2013), smaller social support networks (Cattell, 2001),and physical health problems (Bravemen, Cubbin, Egerter, Williams, &Pamuk, 2010; Mirowsky & Ross, 2003). While serving to effectively blockattempts at employment, education, and resultant economic mobility, theseproblems might also act to prevent individuals in poverty from even beingable to participate in capacity-building programs that could improve theirability to eventually overcome both structural and individual barriers toeconomic mobility. Thus, this project aimed to explore potential barriers toprogram completion in a capacity-building antipoverty program.

Poverty-related interventions

A multitude of interventions have been enacted in an attempt to mitigatepoverty, dating back to President Lyndon Johnson’s “war on poverty.” Today,governmental programs such as Social Security, TANF (TemporaryAssistance for Needy Families), SNAP (Supplemental Nutrition AssistanceProgram), and the Earned Income Tax Credit are used to help alleviatepoverty. Additionally, many private institutions and religious organizationshave created interventions to assist people living in poverty.

Notably, many of the interventions provided for individuals living inpoverty entail a great amount of effort and resources which can make itdifficult for low-resource individuals to partake in these services. For exam-ple, in a previous study of eligible nonparticipants in the food stamp program(prior to SNAP), many reported that they did not apply for food benefits dueto the application process, level of perceived stigma associated with foodstamps, required number of trips made to the office, number of hours spentapplying, and overall bad experiences (Bartlett, Burstein, & Hamilton, 2004).Moreover, applicants for antipoverty programs are often subjected to finger-prints, perjury threats, or home visits to assure they are indeed poor andeligible for services (Bertrand, Mullainathan, & Shafir, 2004). These processescan be burdensome and humiliating, decreasing the number of eligibleindividuals who successfully receive the benefit.

Multiple barriers can hinder the participation of individuals living inpoverty in these programs. Some of those barriers could be institutionalbarriers, such as location of services, administrative barriers, poor commu-nication between agencies and clients, or lack of cultural sensitivity, andsome could be personal barriers, such as psychological barriers, cultural or

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religious beliefs, family concerns, lack of education, or lack of basic readingor writing skills (Community Tool Box, 2014). Programs including Medicaid,TANF, and SNAP often refer individuals to alternative agencies to addressindividual barriers such as transportation services, literacy or language ser-vices, and work obligations, thus adding to the burden of applying forservices (Perreira et al., 2012).

Capacity-building programs have been formed to try to alleviate structural,psychological, and social barriers to antipoverty programs and economicmobility, focusing on helping participants develop increased knowledgeabout poverty, personal resourcefulness, self-efficacy, leadership ability,access to financial institutions, and social networks (Bradshaw, 2005).However, these programs still require individuals to overcome at leastsome potential barriers in order to attend and participate. Barriers whichare logistical in nature such as transportation, childcare, work obligations, orlimited services in individuals’ communities may discourage even the mosthighly motivated individuals from participating and taking advantage ofthese programs and services (Lewinson & Collard, 2012). Additionally, indi-viduals may hesitate from participating in such programs due to a lack ofself-efficacy or hope for the future. An individuals’ perception of themselveshas a direct impact on the likelihood of performing certain behaviors;individuals with low self-efficacy may be less inclined to have motivationand willingness to participate in programs, whereas individuals with higherperceived self-efficacy might have the ability to effect and maintain change,as well as motivation to persevere and overcome obstacles (Atkins, 2010).

In summary, poverty is perpetuated by both structural and individualbarriers. Despite programs that have been created to assist individuals inbuilding the capacity for overcoming barriers and increasing the possibilityof economic stability and mobility, individuals may have obstacles thatprevent them from participating or completing such programs. Thus, thisstudy aims to explore barriers to program completion in a national sample ofvoluntary participants in a capacity-building antipoverty program.

Methods

This study used secondary data from a nationwide sample of participants(n = 332) in an outcome study of a capacity-building program called GettingAhead in a Just-Gettin’-By World ([GA], DeVol, 2013a, 2013b). GA is anationally and internationally used 45-hour manualized workshop designedto help people living in poverty learn about the structural causes of povertyand the effects of poverty on the community and individual. The goal of theprogram is to help individuals living in poverty gain an understanding ofhow they, their families, and their communities are affected by poverty; learnhow to avoid financial predators; identify financial, physical, social, and

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psychological resources that can help improve their ability to become eco-nomically mobile; and set goals for beginning to increase those resources.Groups are facilitated by two people—one who is a trained facilitator and onewho has graduated from GA and experienced living in poverty firsthand—and use a “flat” structure in which facilitators and group members are equalin order to facilitate discussions. The program uses a strengths-basedapproach and emphasizes that people living in poverty are the experts ontheir own lives and on the community’s treatment of them. GA is voluntary,and participants are paid for their time in GA. GA emphasizes and educatesabout the structural explanations for poverty, so participants are aware of themany outside factors that contribute to the perpetuation of poverty, yet triesto empower participants to begin to overcome those barriers by instillinghope and understanding of concrete individual strategies for improving thepossibility of rising in economic class. Additionally, the program requiresthat people of different economic classes are involved in the group in orderto increase participants’ social capital (DeVol, 2013a). Research on GA hasestablished that it appears to facilitate improvements in social support, self-efficacy, hope, goal-directed planning and behavior, and mental health andwell-being (Brisson, 2011; Jindra & Jindra, 2016; Wahler, 2016).

In the original study, 27 sites facilitating eligible GA groups between thedates of August 1, 2014, and July 31, 2015, were invited to participate.Eligibility criteria included having a group scheduled to both begin andend during the evaluation timeframe, conducting these groups in Englishand with adults 18+ only, and following all model fidelity elements listed bythe GA creator (see DeVol, 2013a). These sites were comprised of profes-sional agencies serving individuals in poverty, such as homeless shelters, foodbanks, or agencies responsible for administering TANF benefits, as well assome churches, and represented the entire pool of known sites meeting theeligibility criteria. Nineteen of the invited, eligible sites agreed to participatein this evaluation (a 70% participation rate). Each site was mailed the scriptsto read to participants about the study, baseline and follow-up surveys, andreturn mailing supplies. All participating sites were responsible for readingthe scripts to their groups to invite participants to participate, and consentingparticipants were then given a survey upon entering GA and again uponfinishing the program. Surveys were placed in an envelope by the participantsand mailed to principal investigators. Code numbers were assigned to parti-cipants, so no identifying info was obtained. All research procedures wereapproved by the university’s Institutional Review Board.

Measures

The following variables were examined as potential factors impacting pro-gram completion: self-identified potential barriers (including difficulty with

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social support, difficulty with transportation, lack of interest, trouble gettingoff work, finding a new job, health problems, mental health barriers, orsubstance abuse barriers), perceived possibility of changing the future, andhope. All of these variables were measured at baseline when participantsvoluntarily arrived to the first GA group.

Self-identified barriersAt baseline, participants were asked “Do you think any of the followingmight cause trouble with being able to attend Getting Ahead regularly?”and then were provided a list of options to check. They were instructed tocheck all that apply. Potential barriers included lack of support from friendsor family members (“difficulty with social support”), difficulty finding oraffording transportation to meetings (“difficulty with transportation”), lackof interest in Getting Ahead (“lack of interest”), trouble getting off work,getting a new job that might keep them from attending Getting Ahead(“finding a new job”), and health problems. Additionally, participants wereasked at baseline to self-identify any barriers/problems they currently facedin their lives and were given options that included “mental health problems”and “chemical dependency/addiction.” Checking yes to either of theseoptions was used to identify participants with mental health barriers orsubstance abuse barriers for this study.

Perceived possibility of changing the futureThis variable was measured by the baseline survey question, “Overall, on ascale of 1–10 (1 = not likely at all and 10 = extremely likely), how likely is itthat you can change your future so it is better than your life at this presenttime?”

HopeHope was measured by the baseline score on the six-item State Hope Scale(Snyder et al., 1996). This instrument is able to detect potential changes inoverall hope using Snyder’s cognitive model of hope, defined by the totalamount of goal-directed energy and future-oriented planning.

DemographicsAge, gender, and race were included as demographic variables. Age wasmeasured using the participant’s current age in years at baseline, genderwas measured based on whether the participant indicated they were maleor female, and race was measured based on whether the participant self-identified as White, Black, Native American, Asian, Latino, or Other.Because of sample size and the number of predictors in the model, thesecategories were collapsed into White and Non-White for the purpose ofthis analysis.

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Analytic plan

To examine barriers to program completion, bivariate analyses were con-ducted examining differences in baseline characteristics for the completionversus noncompletion group. Variables that were significantly different forthe two groups were then entered into a logistic regression analysis to testwhich variables were the strongest predictors of completion of the program(coded as 1) or noncompletion (coded as 0). All analyses were conductedusing SPSS version 23.0.

Findings

Univariate predictors

There were three baseline characteristics that were significantly associatedwith the likelihood of completing the program, having a lack of interest inthe program, believing they might find a new job that would interfere withthe program, and believing in the possibility of changing the future.Participants who lacked interest in the program or thought they might finda new job were less likely to complete GA. Additionally, participants whocompleted the program had higher belief that there was a possibility ofchanging their future when compared to their present circumstances.Although not rising to the level of statistical significance in this sample,several trends were identified when examining differences between baselinecharacteristics and completion status; participants with mental health bar-riers, substance abuse barriers, and health problems were less likely tocomplete the program than their counterparts without those barriers (seeTable 1).

Multivariate predictors

To determine the baseline characteristic that was most predictive of programcompletion, the three variables significant at the bivariate level were includedin a binary logistic regression analysis (see Table 2). Two of the threevariables retained significance when predicting program completion in themultivariate analysis—lack of interest in the program and perception of thepossibility to change the future. Thinking they might find a new job was nolonger significant when controlling for lack of interest in the program andperceived possibility of changing the future. The most significant predictorwas the belief in the possibility of changing the future; for every increase of 1on the scale of 1-10 participants self-rated their belief in this possibility, theywere 1.14 times more likely to finish the program. Thus, individuals whothought it was extremely likely they could change their future and answeredthis question with a score of 10 would be 11.4 times as likely to complete

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than someone who thought it was not at all likely they could change theirfuture. Also, participants who reported a lack of interest when beginning GAwere 79% less likely to finish the program. Notably, although the model wassignificant, the Nagelkerke R2 was only .08 which indicated that there were

Table 1. Baseline characteristics by completion StatusCompletion status (% or M)

Demographic category N Completed (n = 212)Did not complete

(n = 116) X2 or t

RaceWhite 227 65.2% 34.8% .01Non-White 105 64.8% 35.2%

Age 37.6 36.8 −.57GenderFemale 223 65.9% 34.1% .28Male 108 63.0% 37.0%

Difficulty w/social supportYes 51 62.7% 37.3% .09No 277 65.0% 35.0%

Difficulty w/transportationYes 144 63.9% 36.1% .15No 188 66.0% 34.0%

Lack of interestYes 16 25% 75% 11.6***No 312 66.7% 33.3%

Trouble getting off workYes 28 67.9% 32.1% .15No 296 64.2% 35.8%

Finding a new jobYes 59 54.2% 45.8% 3.3*No 268 66.8% 33.2%

Health problemsYes 61 62.3% 37.7% .18No 267 65.2% 34.8%

Mental health barrierYes 104 62.5% 37.5% .44No 228 66.2% 33.8%

Substance abuse barrierYes 54 59.3% 40.7% .96No 278 66.2% 33.8%

Possibility to change the future 8.18 7.50 −2.57**Hope 26.87 26.99 .11

*p ≤ .05, **p ≤ .01, ***p ≤ .001.

Table 2. Results of logistic regression analysisPredictor B Wald Ex(B) 95% CI

Lack of interest −1.59 7.04** .21 .06-.66Finding a new job −.53 3.03 .59 .33–1.07Possibility to change the future .13 5.50* 1.14 1.02–1.26

Omnibus X2 18.95***Nagelkerke R2 .08% Correctly classified 68.2

*p ≤ .05, **p ≤ .01, ***p ≤ .001.

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many predictors of program completion not captured by the variablesincluded in this model.

Discussion

Although this sample was a convenience sample of individuals in a singletype of capacity-building program and the results therefore cannot necessa-rily be generalized to other types of antipoverty or capacity-building pro-grams, the findings of this study still have important implications foragencies serving individuals living in poverty. First, the findings suggestthat one of the most important factors for predicting program completionwas whether participants believed it was possible to improve their futurecircumstances. These findings imply that capacity-building or antipovertyprograms should work to instill a sense of hope and self-efficacy at thebeginning of the program in order to keep participants invested and attend-ing so they can benefit from the program. Many people in poverty havedecreased self-efficacy and feel hopeless about their own ability to changetheir future (Dahling et al., 2013), for good reason when considering thestructural and societal barriers they face. However, without perceiving thepossibility of improved circumstances in their future, many individuals mightbe reluctant to persist in capacity-building efforts when faced with obstacles.

Another factor found to predict program completion in this sample waslack of interest in the program itself, providing empirical support that a “one-size-fits-all” approach to capacity building does not work. Although it cer-tainly makes sense that people who are not interested in a program do notcomplete it, people in poverty are often referred or even mandated toprograms that may not interest them. Many programs admit everyone whois eligible to their services without inquiring about their interests or findingout if the program meets those interests. The findings of this study indicatethat it is important to inquire about participants’ interests and try to findappropriate programs that match the individual’s wants, needs, and goals.This could be particularly difficult in rural areas, however, in which theremay be few programs from which to choose. Although this may not alwaysbe practical due to staffing and training needs, programs in these areas mightconsider offering more than one service aimed at achieving the same goal soparticipants can choose which one best meets their needs and wants.Additionally, other fields such as healthcare, substance abuse treatment,and mental health services have begun investigating the use of telemedicinetechnology, mobile phone applications, or other types of technology-assistedservices to improve access for rural or isolated populations (Benavides-Vaello, Strode, & Sheeran, 2013; Duncan, Velasquez, & Nelson, 2014;Nelson & Bui, 2010; Rollman, Belnap, & Rotondi, 2014; Staton-Tindallet al., 2012); agencies serving people in poverty who also live in rural areas

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might consider using technological approaches to increase access and varietyof services provided for the individuals served. The poverty intervention fieldcan similarly learn from healthcare, mental health, and substance abusetreatment that shared decision-making and matching clients with servicesbased on interests and needs can result in better attendance, participation,and outcomes (Barry & Edgman-Levitan, 2012; Lee & Emanuel, 2013; Waltzet al., 2014). Thus, organizations should try to find ways to offer a variety ofservices so individuals in poverty can determine which one they are mostinterested in attending and which one matches their needs, schedules, andresources. This could help boost participation and completion rates andsubsequent life improvements for these individuals.

Last, many people who are in poverty are searching for jobs (or searchingfor better jobs, if already employed but still in poverty) when they beginservices, and the findings from this study suggest that they may beginservices with the intention of completing them, but eventually need to dropout because of a new job requiring attendance at the time the program isoffered. If possible, agencies offering groups or other services to people inpoverty should consider offering these groups at multiple times so peoplewho begin new jobs can still find a way to participate in the program if theiremployment prevents them from attending at their original time.

Implications for future research

Because belief in the possibility of having a better future was one of thestrongest predictors of program completion, these findings suggest thatfuture research should focus on differences in level of optimism, hope, orefficacy for individuals in poverty. What factors predict whether or notpeople believe it is possible to change their future? What things can capa-city-building agencies and service providers add to their curriculum that willhelp instill a greater sense of optimism and efficacy? Additionally, this projectonly examined barriers to program completion in a single type of capacity-building program; future research should examine whether similar barriersare observed in other types of capacity-building antipoverty programs.

Implications for practice

Agencies serving individuals in poverty should consider addressing efficacyand belief in the possibility of a better future beginning in the assessmentor initial meeting. If individuals do not have any belief that there’s apossibility of improving their future, they may be less likely to participatein services or complete a program, and without participating in anyservices they are reducing the chances that their future circumstanceswill improve. Also, agencies should assess interest in the program from

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new participants, use shared decision-making, and attempt to match ser-vices to interests and needs whenever possible. If not possible to offermultiple services at the same agency, then referrals to other agencies mayimprove the chances someone in poverty will complete services that couldimprove their circumstances.

Limitations

This study used a convenience sample of participants in GA, so it isunknown whether the findings of this study apply to all GA participants.However, this sample represented all known adult, English-speaking GAparticipants from all US groups providing GA with model fidelity, so it isexpected that results would be similar for other participants. Also, becauseonly GA participants were included in this project, it is unknown whethersimilar barriers would be found for participants in other types of antipovertyor capacity-building programs.

Funding

This work was supported by DeVol & Associates, LLC.

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