Best practices: Motivating Supplemental Nutrition Assistance Program (SNAP) Application

Best practices: Motivating Supplemental Nutrition Assistance Program (SNAP) Application

Jacquelyn W. McClelland
Carolyn L. Bird
North Carolina State University

Abstract

Supplemental Nutrition Assistance Program (SNAP) provides resources to aid low-income families in obtaining food. Not all of those eligible for SNAP participate. Those eligible but not participating are at risk for food insecurity and increased rates of obesity. Finding the most effective way to enroll eligible people is critical. This study compares various delivery techniques in motivating older adults’ interest in applying for SNAP.

More In My Basket, an educational program targeting limited-resource audiences and based on the Transtheoretical Model and the Theory of Planned Behavior, encourages SNAP participation and dispels myths about the program. Methods included training 57 Family and Consumer Sciences Extension agents to deliver the program in their counties. Three program delivery formats (group, booth, and individual) were developed, delivered, and evaluated for effectiveness resulting in intention to apply for SNAP benefits.

Findings show that the three information-delivery venues and methods were not equally effective in motivating participating older adults to planned action. Out of 1,430 participants, the majority (65 percent) who indicated intention to apply made the decision as a result of individual consultations. Logistic regression on differences in motivation to enroll based on delivery format, income, race, age, and gender revealed statistically significant differences in the effectiveness due to delivery format and income.

Keywords

SNAP, food insecurity, food stamps, stages-of-change, low-income older adults

Introduction

Food-insecure households are those that have difficulty meeting basic food needs for a healthy and active lifestyle for all household members. In 2010, about 14.5 percent of all households in the United States of America were food insecure, including 5.4 percent with very low food security (USDA a 2012). This issue is being addressed by 15 of the United States Department of Agriculture (USDA) federal nutrition assistance programs of which the Supplemental Nutrition Assistance Program (SNAP) is the largest. SNAP provides crucial monetary support to low-income households to help purchase the food needed for good health, and helps enable low-income individuals make the transition from welfare to work and become self-sufficient (USDA a 2012).

However, a paradox exists: one antidote for food insecurity is receiving SNAP benefits, but many who are eligible for the program do not apply, including about a third of eligible older adults. This situation becomes more intriguing in light of the fact that most adults, including older adults, recognize the importance of additional money for food purchase but they do not take the necessary steps to enroll. Thus, it is apparent that more needs to be done to encourage participation and more needs to be known concerning how to encourage participation by all age groups but especially by older adults. To facilitate reaching as many needy people as possible, the Food and Nutrition Service (FNS) of the USDA has awarded outreach grants to increase program participation among eligible households. An additional purpose of the outreach grants includes developing and implementing effective strategies to inform and educate potentially eligible low-income people not currently participating in SNAP about the nutrition information benefit of the program, eligibility rules, and how to apply (USDA b 2012). This study evaluated the effectiveness of three information-delivery venues and methods in motivating older adult participants to sign up for SNAP benefits.

Literature review

While SNAP has been shown to be highly effective in reducing poverty and assisting families with basic necessities (Zedlewski, Waxman, and Gundersen 2012; Tiehen, Jolliffe, and Gundersen 2012; Neilsen, Garasky, and Chatterjee 2010), it is severely underutilized; in fact, nationwide three in ten eligible people do not participate (USDA c 2012). Participation rates for certain subpopulations are even lower; for example, in 2005 seniors only accounted for 30 percent. Previous work, however, has identified common barriers to enrolling. These can be unique to different individuals, populations, and states. In studying state and local agencies, Stacy Dean of the Center on Budget and Policy Priorities found differences in office efficiency and customer service, benefits waiting periods, and application options across county lines (Zedlewski, Waxman, and Gundersen 2012). Besides the aforementioned administrative variations, reasons some eligible people do not sign up for benefits include lack of awareness, confusion about program rules and requirements, a complex application process, a lack of transportation, a lower level of literacy, and pride. According to the FNS Office of Research and Analysis, reasons that seniors may not participate in SNAP could be the perceived low monthly benefit or fears of giving out personal information (Strayer, Leftin, and Eslami 2011).

Those eligible, but not participating, are at risk for food insecurity and increased rates of obesity. Also, non-participation poses a health risk for children with the result that SNAP has been characterized as “medicine” for children (Perry et al. 2007).

There are many suggestions from the FNS for conducting outreach efforts for SNAP enrollment including partnering with businesses and nonprofits. Some suggestions include using newspaper ads or distributing marketing flyers and brochures at locations that needy individuals are likely to frequent. Other suggestions include distributing literature at community events. While these methods of attracting likely eligible individuals might work with some, especially those who are at that stage of readiness to apply for SNAP (preparation or action stage), it leaves out a segment of the population who know nothing about their eligibility (pre-contemplation stage) or may be at the contemplation stage because they have only recently learned about the program and just need more information or encouragement to take action to sign up (Prochaska, DiClemente, and Norcross 1992). To date no one has researched the best methods to motivate general audiences to enroll for SNAP benefits.

For the most effective outreach the authors decided it might be best to have the delivery format involve as much personal contact as feasible. One other study was found that connected personal contact with successful outreach in general audiences (Mathieson and Kronenfeld 2003).

One of the most underrepresented groups in the SNAP recipient arena is the older adult population (for the purposes of this study, age 60+). No one has reported on the efficacy of using personal contact with older adults in motivating them to apply for SNAP. The authors developed three different delivery techniques for this population. Therefore the primary purpose of this study was to compare three face-to-face delivery techniques in motivating older adults to apply.

Methodology and data

The intervention design. The authors developed More In My Basket (MIMB) (Bird 2012), an educational program including a leader’s guide, a curriculum, food pictures, and a handout targeting the SNAP-eligible audiences. The development was undergirded by the Transtheoretical Stages-of-Change model (Prochaska, DiClemente, and Norcross 1992) and the Theory of Planned Behavior (TPB) (Ajzen and Fishbein 1980). The MIMB program explained the current SNAP enrollment guidelines, demonstrated via visual props how much food could be purchased using typical/average SNAP benefits to seniors and others, and dispelled myths concerning SNAP. MIMB objectives included encouraging SNAP participation and clarifying SNAP eligibility regulations. Methods involved training 57 Family and Consumer Sciences Extension agents to deliver the program in 55 counties across North Carolina. To gain insight into the best method to motivate individuals to apply for SNAP benefits, this study developed three diverse delivery models. These different program delivery formats were used by the agents between October 1, 2011, and September 30, 2012.

The delivery formats follow:

  • Group delivery format. This program format consisted of a presentation to a group of people discussing how extra grocery dollars from SNAP benefits can make a difference. The presentation used colorful, inviting food photographs either held up by the presenter when mentioned, pinned to a display board as presented, or shown in a PowerPoint slideshow to demonstrate the positive impact to a household’s grocery budget, diet, and ability to purchase sufficient food. Through this venue participants see the impact of extra food dollars, from minimum benefits to average benefits, have myths debunked, see the actual SNAP application forms, and understand qualification guidelines and application procedures. The presentation highlighted SNAP program features, including ease of use of the Electronic Benefit Transfer (EBT) card, and allowable food purchases. The typical presentation was 30-45 minutes with participants completing a survey before and after the delivery of the information. This format allows for individual questions and timely answers; some personal contact, albeit without confidentiality; and clarification concerning completing the SNAP application form.
  • Individual consultation format. This program format was used primarily during the Medicare Part-D enrollment time frame (October to December of each year) with agents providing a brief one-on-one SNAP presentation at the end of each individual Medicare Part-D training to highlight key SNAP benefits, assess whether a participant intends to apply, provide a SNAP brochure, and obtain permission to contact the participant by phone a few months later to see if he or she has followed through with an application. Each of the participants completed a survey following the individual consultation. This delivery format allows for direct personal and confidential contact without distractions or interruptions, as well as for individual questions and answers and for direct assistance in completing the SNAP application and process.
  • Booth outreach format. This program format used staffed booths or displays for SNAP outreach in conjunction with other NC Cooperative Extension programs or county-specific events including health, senior, and community fairs, and other types of events. Agents and other staff/volunteers set up a display board showcasing SNAP information and food pictures along with USDA SNAP brochures (handouts), and a sign-up sheet for those interested in being contacted. The agent or volunteer answered questions and took the names and phone numbers of those indicating interest in applying for benefits. The agent also obtained permission to contact them by phone a few months later to see if they had applied. Each person at the booth was asked to complete a survey after reading the booth information. This delivery format allows for personal contact, for questions and answers, although the events occurred in open space with potential distractions and limited or no confidentiality.

To utilize participant’s stage of readiness (Prochaska, DiClemente, and Norcross 1992) to make the decision to apply for SNAP benefits, each delivery format provided information to participants concerning their need to apply for SNAP (pre-contemplation and/or contemplation stages), included information to facilitate their understanding of the qualifications to apply (contemplation and/or action stages), and helped with their application process (action stage). To employ the TPB rationale that human action is guided by attitude toward the behavior in question, perceived social pressure (subjective norm) to perform the behavior, and the ease or difficulty with which one can actually perform the behavior (perceived control), the delivery formats included components targeting each of these areas. For example, to gain a more favorable attitude toward the benefits of application each format used colorful, inviting food photographs either held up by the presenter when mentioned, pinned to a display board while being presented, or shown in a PowerPoint slideshow to demonstrate the positive impact to a household’s grocery budget, diet, and ability to purchase sufficient food. To gain perceived social pressure to perform the behavior the formats differed in provisions: the group format included peer interaction and response, the booth format allowed for peer interaction and the individual consultation did not provide peer pressure. To ease the difficulty of sign-up each format included a guided discovery of the application and application process. The blending of a favorable attitude, positive subjective norm and a high level of perceived control has been shown to increase the likelihood of actually performing the behavior (Ajzen and Fishbein 1980).

Data collection. Data were collected for each delivery format on different forms in recognition of the aforementioned characteristics of the three venues. As such, the forms varied in the data that was collected (refer to Table 1.) The group delivery format survey collected all demographic information; the booth outreach and individual consultation forms collected less data. The booth outreach forms collected gender (based on name) and age, and the individual consultation forms collected gender (based on name), age, household net income, and household size. Program participants were asked to complete in-person surveys prior to the group delivery format program to ascertain their baseline knowledge, their level of food insecurity, and their demographic information, and, if applicable, to identify the extent to which they are currently receiving SNAP benefits or have previously received benefits. At the conclusion of the group delivery program participants completed a second survey to measure knowledge change and to capture changes in motivation to enroll in SNAP.

Measurement. The dependent variable that measures the intent to apply for SNAP benefits was collected through post-program evaluation forms. All forms depicted either a “Yes” or “No” response. Some participants hand wrote comments indicating they were contemplating applying for benefits. These responses were coded as “Maybe” in the SPSS data file. Of the 1,431 older adult participants, 746 (52.1 percent) responded “No” while 420 (29.4 percent) responded “Yes,” and another 23 participants responded “Maybe” (1.6 percent). For analyses, the “Yes” (29.4 percent) and “Maybe” (1.6 percent) responses were combined. Group format participants responded to the survey question “Based on today’s presentation, I am planning to apply for SNAP (food stamp) benefits.” Similarly, the Individual consultation form queried, “After briefly explaining SNAP benefits, does participant think that (s)he will apply?” The Booth evaluation form asked, “Now that you know more about FNS/SNAP benefits, do you plan to apply?” For analyses, “Yes” and “Maybe” responses were combined and given a value of “1” while “No” responses were coded and given a value of “0.”

Survey forms. The questionnaires used for this study were kept as simple as possible to ease the burden of response on the older adult (McClelland, Jayaratne and Bird 2013 while still capturing intent to apply. A participant’s failure to answer a question on the survey resulted in an empty cell in the data bank. Those were not included in the data analysis.

Study sample. The MIMB outreach program is available for all likely-eligible adults in North Carolina. There were no specific exclusion criteria for participating in the program. All participants were made aware of and given an informed consent form in compliance with the guidelines set forth by the authors’ Institutional Review Board.

For the purposes of this study a sub-sample was drawn from the overall MIMB (October 1, 2011-September 30, 2012) data to comprise a sample population of older adults exclusively. Other than age, defined as aged 60 years and above, there were no specific exclusion criteria for inclusion in this sub-sample study. The older adult study participants were determined by the program delivery formats they chose to attend. The study participant demographics and participation by intervention format are given in Table 1.

Table 1. Characteristics and intervention formats for older adults

Participants Older Adults Number Percent
Age (years old) Mean (Std. Dev.) 74.86 (8.176) N/A
Range (Minimum-Maximum) 60 – 102 N/A
Gender Female 1070 74.8
Male 281 19.6
Unreported 80 5.6
Ethnicity/Race White 682 47.7
African American/Black 401 28.0
American Indian/Alaska Native 18 1.3
Asian 2 0.1
Other 8 0.6
Not reported 320 22.3
Household Net Income (Monthly) Less than $500 38 2.7
$500 – $749 100 7.0
$750 – $1,010 170 11.9
$1,011 – $1,272 188 13.1
$1,273 or more 458 32.0
Unreported          477 33.3
Participation by Intervention Format Group delivery 1,168 82%
Individual delivery 56 4%
Booth delivery 196 14%
Total participants 1,430     100%

*Data from More In My Basket’s 2012 federal fiscal year (September 30, 2011 – October 31, 2012) were used for this study.

[Table 1 Summary: Characteristics and intervention formats for older adults.  Participants age ranged from 60 to 102 years of age with a mean age of 74.86 years and standard deviation of 8.176.  Female participants were 1,070 and 74.8 percent of the audience.  Male participants were 281 and 19.6 percent of the audience.  Eighty participants did not report gender and constituted 5.6 percent of the total number of participants.  Ethnicities were 682 White at 47.7 percent, 401 African American or Black at 28 percent, and 18 American Indian or Alaska Native at 1.3 percent.  Another 10 people reported as Asian or Other while 320 elected not to report at 22.3 percent. For household monthly income, 38 participants or 2.7 percent of the population reported less than $500, 100 participants or 7.0 percent had between $500 and $749, 170 participants or 11.9 percent had between $1,011 and $1,272, 458 participants or 32 percent reported $1,273 or more while 477 or 33.3 percent did not report household monthly net income.  For participation by intervention format, there were 1,168 participants or 82% reached through group delivery, another 56 or 4% were reached through the individual delivery format, and 196 or 14% were reached through booth delivery for a total of 1,430 participants. ]

The older adult subsample consisted of 1,430 older adults. Demographic data was collected through completion of the evaluation forms tailored to each intervention format. Nearly 75 percent of the older adult sample was female, with almost half being white (47.7 percent) and 28 percent being African American/Black. The mean age was approximately 75 years with a range from 60 to 102.

The majority (82 percent) participated through group presentations, followed by those visiting the booths (14 percent), and those in the individual sessions (4 percent). A majority of the group presentations were made to older adults in congregate nutrition sites just before lunch was served. The individuals attending congregate nutrition sites in North Carolina have changed over the years but the demographics have remained fairly stable (McClelland et al. 2002; McClelland et al. 2000).

It is difficult to get participants to indicate their household income and thus the data reflect this issue with only about two-thirds (66.7 percent) being willing to answer this question.

While all the monthly net income values appear low enough to represent limited-income people eligible for SNAP benefits, approximately one third (the comparatively highest incomes) could possibly exceed the eligibility range depending on a number of factors. Establishing eligibility involves consideration of various deductions to income and requires determination by the Department of Social Services in North Carolina.

Data analysis. The three program delivery formats (Group, Individual, Booth) were analyzed for effectiveness in motivating application using the Statistical Package for the Social Sciences (IBM 2012). Demographic data and group scores are reported as the mean + standard error of the mean (SEM). Significance for all statistical analyses was set at the level of P<.05.

The model included four independent variables, namely format (group, individual, booth); gender (male, female); net income (“[1] Less than $500; [2] $500 – $749; [3] $750-$1,010; [4] $1,011 – $1,272; [5] $1,273 or more”); and age (continuous variable selected for age 60 and over).

The present study used logistic regression to examine interest in applying for SNAP benefits among older adult participants who attended one of the three different program formats (group sessions, individual consultation, and booth events).

Findings and results

Logistic regression results are presented in Table 2.

Table 2

Results of Hierarchical Logistic Regression Examining Motivation to Apply for SNAP (n = 1,439).

Model Evaluations
Predictor B Wald Exp(B) -2 Log Likelihood Model χ2
Intervention Format 3.082    8.722** 21.799 1025.76 18.380***
Gender .138      .534 1.148 1025.22 18.919***
Net Income -.366 32.472***    .694    991.93 52.202***
Age -.002      .054    .998    991.88 52.255***

*p ≤ .05      **p ≤ .01    ***p ≤ .001

[Table 2 Summary: Results of hierarchical logistic regression examining motivation to apply for SNAP.  Sample size of one thousand, four-hundred-thirty-nine older adults.  Model evaluation results returned significant Wald statistics for both the Intervention format and net income variables.  The -2 Log Likelihood decreased as each of the four variables entered the equation indicating that each variable contributed to explaining the variation in the data.  The Model chi-square statistic was significant at the p-value less than or equal to the point-zero-zero-one level and indicate the statistical significance of the model.]

In this model the outreach intervention format (χ2 = 18.380, p = .000) was one of the significant predictors of intent to apply. Household monthly net income (χ2 = 52.202, p = .000) was the second significant predictor of interest in applying for SNAP. Gender improved model prediction at Step 2 but was not significant (Wald = .056, df=1, p=.812) in the final model. Likewise, age was not a significant predictor (Wald=.054, df=1, p=.817). The model had an overall correct classification rate of 65.5 percent. It classified correctly interest in applying for SNAP at 22.1 percent of the time and more strongly predicted the lack of interest at 90.3 percent.

Outreach program formats were selected in accordance with the venue of the pre-formed audiences. Thus, the program had no control over shaping audience composition. However, it is possible that certain types of venues attracted audiences with specific characteristics other than having low socio-economic status, which is a goal of the program. Thus, the data were examined by type of delivery format to better understand the characteristics of age, race, and gender as potential confounding factors. An overview of participant characteristics by outreach intervention format is given in Table 3 below.

Table 3. Demographic data by delivery format*

Delivery Format Average Age Race Gender
Group 72.50 White 56.0%

Black  34.8%

Male 19.3%

Female 76.8%

Individual 68.57 Not available Male 40.5%

Female 47.3%

Booth 63.06 Not available Male 12.7%

Female 64.5%

*Percentages may not equal 100 due to non-reported information.

[Table 3 Summary: Demographic data by delivery format.  Group delivery format participants were 72.50 years of age, with 56 percent being White and 34.8 percent Black, and 19.3 percent were male and 76.8 percent were female.  Individual delivery format participants were 68.57 years of age, with no race being collected or reported and 40.5 percent were male and 47.3 percent were female. Booth delivery format participants were 63.06 years of age with no race being collected or reported and 12.7 percent were male and 64.5 percent were female.]

Results for income revealed that participants’ interest in applying for SNAP was evenly divided among “Yes” and “No” responses for the three lowest categories (Table 4). Interestingly, as income increased a divergence is evident in interest in applying for the SNAP. This is consistent with other findings that higher income is a primary influencer on interest in participating in SNAP (USDA d 2009) Those with incomes between $1,011and $1,272 gave a negative reply for (65/116) 56 percent of the time and participants reporting income of $1,273 or more gave a “No” response (237/323) 73 percent of the time.

Table 4. Participant intent to apply by household net income.

Number with Net Monthly Household Income

24 with less than $500

48 with $500 – $749

94 with $750 – $1,010

116 with $1,011-$1,272

323 with $1,273 and up

Planning to Apply

13 (55%)

24 (50%)

47 (50%)

51 (44%)

86 (27%)

Not Planning to Apply

11 (45%)

24 (50%)

47 (50%)

65 (56%)

237 (73%)

[Table 4 Summary: Number of participants showing intent to apply by household net income.  Of the 24 participants who reported less than $500, 11 or 45 percent did not plan to apply and 13 or 55 percent did plan to apply.  The 48 participants who reported $500 to $749 were evenly split with 24 or 50 percent planning to apply and the other 24 or 50 percent not planning to apply.  The 94 participants with income between $750 and $1,010 were evenly split with 47 or 50 percent not planning to apply and the other 47 or 50 percent planning to apply.  Of the 116 participants with income between $1,011 and $1,272, 65 or 56 percent did not plan to apply and 51 or 44 percent planning to apply.  Of the 323 participants with income at $1,273 and above, 237 or 73 percent were not planning to apply and 86 or 27 percent were planning to apply.

Participants in the Individual Consultation category reported income with greater dispersion over three categories of income: $750-$1,010 (10.8 percent), $1,011-$1,272 (6.8 percent), and $1,273 or more (10.8 percent) with 20.8 percent having income of $1,272 or less. However, nearly 68 percent (67.6 percent) of these cases did not have income information.

Discussion. All three of the delivery formats were successful in getting older adults to apply for SNAP benefits, albeit not at the same level of intent. Out of 1,431 study participants 64.9 percent of those attending individual consultations indicated intention to apply while 42.4 percent of those attending booth presentations and only 27.1 percent of those attending group sessions indicated intention to apply.

No other study has identified which delivery format is the best at increasing older adults’ intention to apply for SNAP benefits. As shown, the authors found that among the three methods of delivery format, the individual consultation format was more effective than the group format and the group format was more effective than the booth format. Therefore they concur that more direct and confidential personal contact produces more interest in signing up for participation in SNAP benefits by the older adults.

The only other study found in the literature that looked at the advantages of personal-contact models was Mathieson and Kronenfeld (2003). Although not focusing on older adults nor looking at levels or intensity of personal contact, they found that personal contact was better than just distributing literature. They noted that many outreach workers found that they were not successful if they only distributed applications at events or left applications to be picked up by individuals. They also noted, with personal-contact models, that outreach workers can answer questions immediately and explain the program in depth. In addition, outreach workers can assist in the application process including filling out application forms. Specific advantages that they associated with a personal-contact approach include the importance of trust, especially for racial minorities, and reducing application complexity to make the application process as easy as possible for participants.

The authors’ work supports Mathieson and Kronenfeld’s findings and shows that not only is personal contact important but that different delivery methods employing personal contact leads to varying rates of interest in application by older adults. In the case of personal contact, more is better.

The authors surmise that MIMB outreach workers (agents) can also assist in moving an individual through stages of change by interacting with them. The best format for that process is the individual consultation format that allows complete attention to the participant’s needs without distractions or interruptions. In this case they can determine a participant’s level of readiness to apply with a few brief questions and can converse with an individual who is at one stage and can help her or him move toward, or actually to, the action stage which results in application most of the time.

In addition, direct contact in the form of individual consultation is very important to promoting older adult signup because the agents clear up misinformation and confusion about program rules and requirements which the older adult may be unwilling to admit in front of others. The agents can also show the older adults how to navigate the complex application process and assist them with filling out the form. The authors have found that older adults, especially those with limited resources, many times have lower reading ability and difficulty reading fine print due to eyesight issues. Thus, reading and filling out complex forms can appear to be a formidable undertaking to them.

The agents also represent a trustworthy source of information because they have just assisted them with Medicare Part D issues. Combining the Individual Consultation delivery format with Medicare Part D assistance can work to allay the fears of older adults about giving out personal information.

Limitations of the study. The audiences were not randomly chosen but were a convenience sample. Some were participants due to their choices to attend congregate nutrition sites for a hot meal (group format); some chose to ask for help for Medicare Part D (individual consultation format); and some attended an event in their community where the SNAP outreach booth was set up (booth format).

The surveys were kept simple and to the point because of the delivery formats chosen and the difficulty in getting older adults to reply to longer, more involved surveys. Therefore, the opportunity to gather more information as to why individuals changed their attitudes or changed their stage of readiness to apply could not be determined.

This study was not able to determine if individuals followed through with their intent to apply; however, if we believe the theory of planned behavior is factual, then we expect that they did actually apply. For the future, we plan to have a tracking system in place to verify this final step.

Since SNAP is a need-based program, those with higher incomes may, correctly or incorrectly, perceive themselves to be ineligible and this perception could influence their interest in applying for SNAP.

The fact that nearly 68 percent of the individual consultations did not provide income information could be attributed to the personal nature of the individual outreach format and reluctance on the part of either the agent to request the information or the participant to give the information, or some combination of both. Booths are typically set up at large-scale public events, such as health fairs, and thus do not tend to lend themselves to engaging participants in a manner that facilitates collecting potentially sensitive personal information. For that reason, the evaluation instruments for the booth format did not collect income information.

Conclusion

In this study, delivery format significantly predicted intent to apply, as did net income. The authors surmised that the significance of the net income impact was due to perception of eligibility being tied to the amount of income and not to actual eligibility. The authors concluded that many individuals completing the survey forms, who were in those higher income brackets, perceived that they were not eligible because of their income status and, thus, were more likely to indicate no interest in applying.

In conclusion, although the three delivery methods were effective, there is a significant difference in the level of effectiveness of each for the older adult audience. The important finding is the high level of effectiveness of individual consultations to increase older adult motivation to enroll for SNAP. There is a wide-spread need for parallel programs to reach additional older adults in food-insecure households eligible for SNAP benefits.

 

 

References

Ajzen, I., and M. Fishbein. 1980. Understanding Attitudes and Predicting Social Behavior. Englewoods Cliffs, N. J.: Prentice Hall, Inc.

Bird, C. L. 2012. More In My Basket 2012 Food and Nutrition Services – Outreach, North Carolina State University Annual Report. Raleigh, N.C.: North Carolina State University.

IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.

Mathieson, K. M., and J. J. Kronenfeld. 2003. “Barriers to Enrollment and Successful Outreach strategies in CHIP: Reflections on the Arizona experience.” Journal of Health Care for the Poor and Underserved 14(4): 465-477. http://muse.jhu.edu/journals/hpu/summary/v014/14.4.mathieson.html. Accessed March 15, 2013.

McClelland, J. W., L. B. Bearon, A. M. Fraser, R. D. Mustian, and S. Velasquez. 2001. “Reaching Older Adults With Nutrition Education: Lessons Learned During the Partners in Wellness Pilot Project.” Journal of Nutrition for the Elderly 21(2): 59-72.

McClelland, J. W., L. Bearon, S. Velasquez, A. Fraser, E. H. Maier, and R. D. Mustian. 2002. “Profiling Rural Southern Congregate Nutrition Site Participants: Implications for Designing Effective Nutrition Education Programs.” Journal of Nutrition for the Elderly 22(2): 57-70.

McClelland, J. W., K. S. U. Jayaratne, and C. L. Bird. 2013. “Nutrition education brings behavior and knowledge change in limited-resource older adults.” Journal of Extension 51(2). http://www.joe.org/joe/2013april/a1.php

Nielsen, R. B., S. Garasky, and S. Chatterjee. 2010. “Food insecurity and out-of-pocket medical expenditures: Competing basic needs?” Family and Consumer Sciences Research Journal 39(2): 137-151. DOI: 10.1111/j.1552-3934.2010.02052.x

Perry, A., S. Ettinger de Cuba, J. Cook, and D. A. Frank. 2007. Food stamps as medicine, a new perspective on children’s health, children’s sentinel nutrition assessment program [C-SNAP]. A Report.http://www.childrenshealthwatch.org/upload/resource/food_stamps_as_medicine_2007.pdf . Accessed January 31, 2013.

Prochaska, J. O., C. C., DiClemente, and J. C. Norcross. 1992. “In search of how people change. Applications to addictive behaviors.” American Psychologist 47(9): 1102-14.

Strayer, M., J. Leftin, and E. Eslami. 2012. Characteristics of Supplemental Nutrition Assistance Program Households: Fiscal Year 2011. Alexandria, Virginia: U.S. Department of Agriculture Food and Nutrition Service, Office of Research and Analysis. www.fns.usda.gov/ora.

Tiehen, L., D. Jolliffe, and C. Gundersen. 2012. Alleviating poverty in the United States: The critical role of SNAP benefits. Washington, D.C.: Economic Research Service, USDA.

USDA a (U.S. Department of Agriculture, Food and Nutrition Service, Office of Research and Analysis). 2012. Building a healthy America: A profile of the Supplemental Nutrition Assistance Program. Washington, D.C.: USDA. Retrieved September 3, 2013; http://www.fns.usda.gov/ora/MENU/Published/snap/FILES/Other/BuildingHealthyAmerica.pdf

USDA b (U.S. Department of Agriculture, Food and Nutrition Service). “SNAP Outreach Grants.” http://www.fns.usda.gov/snap/outreach/grants.htm. Retrieved: September 3, 2013.

USDA c (US Department of Agriculture, Food and Nutrition Service) Supplemental Nutrition Assistance Program. 2012. Reaching those in need: State Supplemental Nutrition Assistance Program participation rates in 2010—summary. http://www.fns.usda.gov/ORA/menu/Published/SNAP/FILES/Participation/Trends2010Sum.pdf. Accessed January 31, 2013.

USDA d (U.S. Department of Agriculture, Food and Nutrition Service) Office of Research and Analysis. Understanding the Determinants of Supplemental Nutrition Assistance Program Participation, by Nancy R. Burstein, Satyendra Patrabansh, William L. Hamilton, and Sarah Y. Siegel. Project Officer: Rosemarie Downer, Alexandria, VA: December 2009. Accessed September 3, 2013.

Zedlewski, S., E. Waxman, and C. Gundersen. SNAP’s role in the great recession and beyond. 2012.http://feedingamerica.org/how-we-fight-hunger/programs-and-services/public-assistance-programs/~/media/Files/research/SNAP-Roundtable-Summary.ashx?.pdf

http://www.ncsu.edu/ffci/publications/2013/v18-n2-2013-fall-v18-n2-november-2013.php

 

 

Back to table of contents ->https://www.theforumjournal.org/2017/09/01/fall-2013-vol-18-no-2/