NC1171: Individual, family, and community factors associated with resilience in diverse, rural, low-income families

(Multistate Research Project)

Status: Active

NC1171: Individual, family, and community factors associated with resilience in diverse, rural, low-income families

Duration: 10/01/2019 to 09/30/2024

Administrative Advisor(s):


NIFA Reps:


Statement of Issues and Justification

Need and Importance


 


America needs rural communities. They provide affordable energy, clean drinking water, safe and inexpensive food, and opportunities for recreation (Zwagerman, 2017). Prosperity in rural areas is important to all Americans. Despite this, the population in rural areas is declining (USDA, 2017). Characteristics of rural communities often pose multiple and intersecting challenges to the economic, physical, and mental well-being of rural residents. These characteristics include geographic isolation, lack of economic diversification, sparse resources, inadequate or insufficient healthcare, and limited social services and childcare providers among others (Burton et al., 2013; Mammen & Sano, 2018; Walker & Manoogian, 2011). Rural communities also present fewer educational opportunities and have lower median household income levels than urban areas (Crocket, Carlo, & Temmen, 2016).



Approximately 47 million adults and 13.4 million children live in rural communities in the United States (US Census, 2016). Nearly 20% of these children live in poverty, placing the United States 36th in rankings of rural childhood poverty in developed nations, just below Belarus and above Russia (Save the Children, 2017). Although the median income in rural areas has increased modestly since 2011, growth still lags behind urban areas, with wages in rural areas averaging 25% lower than those in urban areas (USDA, 2017). Mental health has been declining among disadvantaged Americans since the mid-1990s (Goldma, Glei, & Weinstein, 2018), with rural, low-income Americans potentially at greater risk for mental health problems than their urban counterparts (Meit et al., 2014).



Between 2010 and 2016, rural communities as a whole experienced population loss for the first time in recorded history. This decline in population varied by region, with the most loss in areas affected by agriculture (e.g., the Midwest) and reductions in manufacturing industries (e.g., East Coast). The population decline has been attributed to out-migration of young adults, lowered fertility rates, and increased mortality rates in working aged adults (USDA, 2017). Part of this unusual trend in mortality is caused by the high rate of non-prescription opioid addiction in rural areas (Keyes et al., 2014). The combination of population decline, shrinking economies, and increasing mortality rates of working adults produces an overall weakening of the economic and social fabric of rural communities leaving residents vulnerable to other adversities, such as natural and manmade disasters (Frey, 2018). Thus, the accumulation of adverse events and circumstances in rural communities may contribute to further negative outcomes for individuals and families.



Despite their vulnerability, many individuals and families living in rural areas demonstrate the capacity for resilience in the face of a variety of adverse events (Conger & Conger, 2002; Cutter et al., 2016; Orthner, Jones-Sanpei, & Williamson, 2004; Yancura, Barnett, Sano, & Mammen, in press). Resilience is generally defined as “the capacity of a system to adapt successfully to significant challenges that threaten the function, viability, or development of that system” (Masten, 2018, p. 12). In other words, resilient individuals, families, and communities are able to survive, and potentially thrive, through adversity. Interestingly, resilience in rural areas appears to be driven by social capital (Cutter et al., 2016). Social capital (e.g., skills, knowledge, social cohesiveness) has been defined as "the networks, norms, and trust that facilitate coordination and cooperation for mutual benefit" (Putnam, 2000, p. 19). In contrast, resilience in urban areas tends to be driven by economic capital (i.e., wealth and income) (Cutter et al., 2016). Although resilience in urban areas has been covered in the research literature, the factors that promote individual, family, and community resilience in rural areas have received less attention (Orthner et al., 2004). It is critical to determine both the unique needs and resources within rural areas, as well as the best mechanisms for supporting rural families in order to increase the likelihood of resilience in rural communities.



Resilience in rural communities aligns with the top priorities of the US Department of Agriculture (USDA) with its first strategic goal of assisting “rural communities to create prosperity so they are self-sustaining, re-populating, and economically thriving” (USDA Strategic Plan, 2014). The Research Education and Economics mission area of USDA specifically addresses “rural prosperity” (REE, 2014) and the National Institutes of Food and Agriculture (NIFA) science goal calls for research to foster the “development of human capital and communities” (USDA Strategic Plan 2014). The proposed project to examine the interconnections of individual, family, and community factors linked to rural, low-income families’ resilience is in alignment with the current priorities.


 


Technical Feasibility


 


Data from Rural Families Speak about Health (RFSH, the previous project of this team) focused on child and family health. Quantitative data (e.g., BMI, maternal depression, household food security, child internal and external behaviors, financial stress) collected during Wave 1 (N = 444) were complemented with qualitative data (e.g., changes in health, barriers and enablers to health) collected during Wave 2 (N = 85) to examine individual-, family-, and community-level factors and policies that enhance health. Additionally, case study data (Wave 3 data, N = 23) were collected in order to understand nuanced experiences of rural families in the context of the Affordable Care Act. Utilizing three waves of the previously-collected RFSH data, we aim to examine individual and family resiliency. The proposed project will build upon and update previous data collection to understand resilience in individuals, families, and communities.



Due to the geographic, social, and economic diversity of rural communities, we propose to collect community-level data using a variety of community asset assessment techniques, including windshield or walking tours, key informant/leader interviews, asset mapping, inventories, and analysis of public records and data (Sharpe, Greaney, & Royce, 2000). Information collected at the community level will be later complemented with families’ perceptions of the accessibility and usefulness of community resources. Community-level data will be integrated with other family- and individual-level variables in order to identify and analyze multi-level patterns of and influences on resilience. For example, once data at the community- and family-level have been collected, we will analyze how community capital, such as the infrastructure or youth programs, may influence family resilience in this community.



This multi-state research team has been in existence since 1998 (NC223, NC1011, NC1171) and has a history of using its complementary strengths to develop research questions, design studies, and conduct quantitative and qualitative analyses to produce innovative, multidisciplinary studies. Several team members began their work with the project as graduate students and now are junior, mid-career faculty. The team has spanned distance and time by using technologies to communicate and share data files via a Box site, a website, conference calls, annual on-site meetings, Skype meetings, and recently, Slack team messaging software. Our team updates our governance document annually, and the team uses a tracking tool to facilitate collaboration among team members in developing presentations, policy briefs, manuscripts, and other products. Our governance document encourages and facilitates multi-state collaborations on presentations and documents by requiring new team members and authors from non-data collection states to include at least two members from data collecting sites. For the next phase of this project, we will have working groups comprised of members across states for instrument development, data collection procedures, and data management. Further, our team will continue to have various writing groups of complementary expertise to answer research questions and disseminate our results.



Over the 20 years of our project, the work of this team has produced approximately 100 peer-reviewed publications. In addition, this group has produced an edited peer reviewed book entitled, Rural families and work. Recently, our team showcased research across the twenty years in a Family Science Review special issue on rural families. Our reach has broad impact with more than 150 peer reviewed conference proceedings and presentations at both the national and international levels. Furthermore, students affiliated with the project have produced 10 theses and dissertations, with several more progress. In 2017, members of the NC1171 team received an Innovation in Teaching Award from the Association of Public and Land Grant Universities to transform NC1171 case studies into animated vignettes. The aim of this grant was to bring real stories from rural families to life in the undergraduate classroom to educate students about an often overlooked form of family diversity - rurality. These vignettes will be made available to extension agencies. We secured approximately $700,000 for multi-state and $66,000 for individual states to support research and outreach pertaining to NC1171 (current as of 11/27/2018). In addition to these scholarly outputs, the team has provided numerous outreach consultations and educational presentations to rural communities.



Advantages of Working as a Multistate Effort



This project builds upon a longstanding multi-state, multidisciplinary effort consisting of family scientists, family economists, nutritional scientists, social workers, extension specialists, psychologists, and sociologists. The study of many states representing different geographic regions allows for a comparison of different contextual factors, such as access to community resources, and a range of adverse events. Each state is also characterized by a different population profile. Race/ethnicity, culture, and acculturation are all important to understand factors related to family resiliency. This diversity allows researchers, Extension personnel, other educators, and community stakeholders to further understand relevant issues, develop research agendas, and create products (e.g., curricula, programs, policy briefs) that recognize the unique context and diverse needs of rural America. A multistate collaboration also allows the team to address a range of current challenges to and resources for resiliency in low-income rural families. A further and potentially most important aspect of a multistate, integrated project, is the ability of each member to contribute according to expertise. Research faculty from a variety of academic disciplines will be responsible for research design, analysis, and distribution of results to the scholarly community. Extension faculty will be responsible for translating these research results into products for the general public (see below).



This multi-state collaboration is uniquely positioned to contribute to the body of knowledge regarding the resilience of low-income families in rural America. Rather than taking a deficit approach, we take a strengths-based approach to understand ways to sustain or build upon existing individual, family, and community strengths (Saleebey, 1996). Practitioners increasingly utilize strengths-based approaches with their clients, but research on the mechanisms or processes by which individuals and families develop these strengths is still limited (Orthner et al., 2004). Furthermore, in order to inform policy and practice, there is a critical need to understand “which system or systems to target, at what levels, and when” to bolster and capitalize on these strengths (Masten & Monn, 2015, p. 16).


 


Impacts of this Work


 


This project will lead to impacts at multiple levels (i.e., individual, family, community, state, and national). Involving project members representing a variety of disciplines and position responsibilities (e.g., teaching, extension/outreach, research) in developing and implementing the dissemination plan will expand the capacity of the land-grant system to educate and train graduate students; enrich the curricula of courses in sociology, economics, human development and family sciences, and nutrition and health; inform Cooperative Extension programming; and further extend expertise of the land grant system to support prosperity in rural America.


Specific outcomes related to this work will correspond with faculty expertise described above. For example, research faculty will be responsible for the distribution of results such as refereed conference presentations and peer-reviewed journals to the scholarly community in their respective academic disciplines (e.g., family science, child development, rural sociology). Extension faculty will be responsible for translating research results for the general public, Potential products include, but are not limited to, policy briefs, educational materials for families, and community workshops.


The return on investment for building resilience at the individual, family, and community levels is high. While there are many variables involved in cost-benefit calculations for evidence-based prevention programs, estimates are that funding such initiatives offers a greater societal savings than the cost of the intervention itself (Peterson, Florence, Thomas, & Klevens, 2017). Working toward such savings may mitigate the $124 billion lost per year due directly and indirectly to adverse childhood experiences (Fang, Brown, Florence, & Mercy, 2012). Some estimates note that a national implementation of an evidence-based prevention program could yield $16 billion in lifetime savings per annual cohort of children (Peterson, Florence, Thomas, & Klevens, 2017). Funding this research and outreach plan will provide much-needed data upon which organizations and communities can obtain funding and resources needed to engage in prevention and intervention efforts.

Related, Current and Previous Work

Our Previous Work


 


Our previous work produced by RFS (NC223, NC1011) and RFSH (NC1171) projects documented risk and protective factors of poor, rural families. Below is a summary of our main findings surrounding economic security and family health.


Risk and Protective Factors of Rural, Low-Income Families


 


Economic security. Economically secure families are better prepared to play important roles in the viability and vitality of their communities. Yet, low-income families in rural areas face a multitude of challenges in their quest for economic security. Our previous findings consistently documented that many of the families did not earn enough income to keep them out of poverty (Bauer, Braun, & Dyk, 2003; Bauer, Braun, & Olsen, 2000). Although employment is fundamental to income security, economic opportunities are scarce in rural areas. Even if rural residents obtained employment, maintaining employment can be challenging due to lack of community infrastructure, limited childcare options, unreliable transportation, lack of human capital and instrumental resources (Bird, 2004; Bird, Dolan, & Seiling, 2011). Having younger children, suffering poor health, being a single parent, and stressful situations (e.g., domestic violence, incarceration, unexpected death) complicated mothers’ employability.


 


Rural families utilized various means to make ends meet. For example, family and social support mitigated rural families’ hardships (Mammen, Dolan, & Seiling, 2015) and buffered them against economic challenges (Kohler, Anderson, Oravecz, & Braun, 2004). Public assistance including Medicaid, TANF, SNAP, Supplemental Nutrition Program for Women, Infants and Children (WIC), free or reduced price School Breakfast and School Lunch, Section 8 (subsidized housing), Low-Income Home Energy Assistance Program (LIHEAP), and transportation assistance (Mammen, Berry, Bird, & Chandler, 2018) increased rural families’ resiliency. In particular, the Federal Earned Income Tax Credit (EITC), a refundable federal tax credit was found to be a significant benefit for rural, working families. These benefits include increased purchasing power, encouragement for single mothers to remain employed, decreased child poverty, reduced income inequality, increased savings, and more support for rural communities (Mammen, Bauer, & Lass., 2009; Mammen & Lawrence, 2006).


 


Health challenges. The overall goal of NC1171 was to understand interplays among individual, family, community, and policy contexts on health outcomes of rural, low-income families. Our findings showed that being poor and living in a rural location contribute to greater vulnerability to physical and mental health issues such as obesity and, in particular, depressive symptoms. For example, previous research found that transportation difficulties confined some women to their homes, thereby diminishing opportunities for physical activity in spaces beyond their immediate environments; food insecurity and unstable food supplies contributed to erratic eating patterns which resulted in overweight and/or obesity (Olson & Bove, 2005). Additionally, health issues were associated closely with depressive symptoms. Mothers who screened positively for depression were more likely to report health issues (Braun & Rudd, 2003) and have doctor visits (Simmons, Huddleston-Casas, & Berry, 2008; Simmons, Berry, Huddleston-Casas, & Dyk, 2006). Obesity preventing behaviors such as exercise and good nutrition were significantly less likely when high degrees of depressive symptoms were present (Burney, Routh, Greder, & Greer, 2015).


Access to healthcare provides physical, mental, and financial protection to individuals and families from expected and unexpected health conditions (Byrne & Greder, 2014). Lack of access to healthcare significantly impacts individuals’ abilities to obtain and maintain employment, provide effective care for children and dependents, and contribute positively to their community (Dyk, Radunovich, & Sano, 2018). Lack of health insurance coverage is especially linked to delayed preventative care and treatment and poorer health outcomes (Anderson, Dobkin, & Gross, 2012). Increasing individuals’ health literacy is also identified as a key factor to increase health status as well as access to healthcare. More Spanish-speaking mothers reported difficulties understanding health information that doctors or health professionals shared with them than English-speaking mothers (Greder, Sano, Mammen, & Doudna, 2014). Many Spanish-speaking mothers relied on informal social networks to seek health information (Romero de Slowing, 2012), highlighting the importance of social networks in their health seeking behaviors. In addition to strengthening existing networks, expanding available resources such as creating flexible hours for doctor’s visit, utilizing bilingual translator at the visit, and providing free transportation to a hospital serve as protective factors for rural, low-income families.


 


In sum, our previous work identified many risk and protective (formal and informal) factors of rural, low-income families. The proposed project will allow us to move beyond identifying factors associated with resilience to better understanding the processes by which rural, low-income mothers bounce back from various types of adversity.


 


Review of CRIS and Other Multistate Projects


 


Before describing the need for additional research on resilience processes among rural, low-income families, we note related existing multi-state projects. Based on our review of CRIS, there are a few ostensibly related projects but none that duplicate our proposal. We identified the following multistate projects:


 



  • NC_1030: Sustainable Families, Firms, and Communities in Times of Disruption

  • NE1749: Enhancing Rural Economic Opportunities, Community Resilience, and Entrepreneurship

  • NC1196: Food Systems, Health, and Well-being: Understanding Complex Relationships and Dynamics of Change

  • W4001: Social, Economic, and Environmental Causes and Consequences of Demographic Change in Rural America


 


The common theme is assessing what is associated with survival and growth among families, food systems, and communities. For example, an aim of Project W4001 are to examine causal pathways linking population change to prosperity and well-being. This project involves examining long-term stressors and new shocks linked to inequality, prosperity, and well-being in populations. Project W4001 takes a macro, demographic approach, whereas our proposed project takes a more micro, human development and family science approach to studying resilience in the face of adversity in mothers. Thus, our proposed project is novel compared to other multistate projects.


 


Need for Additional Research


 


Individual and Family Resilience


 


A clear understanding of the processes and mechanisms of family resiliency in rural areas, as well as the best methods for supporting rural families, is limited, warranting additional research to provide insights. Therefore, the proposed project aims to address this gap in the literature by (a) assessing community capacity in rural areas and (b) examining resiliency among rural low-income families with attention to three levels - individual, family, and community. We will use the new data collection to supplement existing RFS and RFSH data.


 


An ecological systems framework continues to guide the work of our multistate collaboration, but for the proposed next steps, we also integrate and rely heavily upon a risk and resiliency framework. The ecological systems model, more specifically the Process-Person-Context-Time (PPCT) model (Bronfenbrenner & Morris, 2006), emphasizes understanding the dynamic interrelationship between a developing person in various contexts over time, that is, the proximal processes driving human development. The lives of rural, low-income families are complex, therefore we must consider the confluence of multiple factors. “Many low-income [and rural] families are functioning well, although the mechanisms by which they adapt and cope with the demands of their lives are not well known” (Orthner et al., 2004, p. 167). Thus, key to helping low-income families is to move beyond simply identifying factors correlated with resilience to investigating the mechanisms by which they are able to thrive in the face of adversity.



Resilience is a dynamic process by which individuals or groups adapt positively to adverse circumstances; it is not the process of evading risk but rather successfully drawing up resources to navigate through stressful experiences (Masten, 2018). Individual and family resiliency is optimized when protective factors are strengthened at all three interactive levels of the socioecological model - individual, family, and community levels (Benzies & Mychasiuk, 2009, p. 103). Individual protective factors include a positive outlook, internal locus of control, effective coping skills, education and training, health. Family protective factors include family structure, flexibility, social support, adequate income, and adequate housing. Community protective factors include safe neighborhoods, access to quality school and child care, and affordable housing (e.g., Benzies & Mychasiuk, 2009; Walsh, 2002). Due to the interactions of many factors within and across systems levels, there are diverse pathways to adaptation (Masten, 2018). Toward understanding these diverse pathways, we will investigate the variety of risk (i.e., vulnerability) and protective (i.e., asset) factors and processes associated with resilience across a range of significant stressors experienced by rural, low-income families.


 


Community Resilience


 


Because resilience depends on interconnected systems (Henry et al., 2015; Masten, 2018), we will build on existing research to understand further community-level factors that create a positive cascade to individuals and families. Despite the recognized importance of multi-level influences on individual and family well-being and resilience, fewer studies have focused on the outer systems (e.g., neighborhood and communities; Darling, 2008) and on rural communities, specifically. From our 20 years of research, we know that rural low-income families often depend on community resources (Mammen, Berry, Bird, & Chandler, 2018) and close relationships (Mammen, Dolan, & Seiling, 2015) to overcome hardships. Understanding the role of community and how community risk factors (e.g., poverty) and protective factors (e.g., sense of belonging, closely-knit communities) impact individuals’ and families’ well-being is critical for the implementation of effective programs and policies serving low-income families in rural communities (Seccombe, 2004).


 


For this project, communities are defined as spatial and social units where families meet their basic needs; maintain social interactions and networks; develop a collective identity; and come together to change their physical, social, and political environments (Minkler, Wallerstein, & Wilson, 2008). The pathways by which communities influence individuals’ and families’ risk and resilience vary by community characteristics such as, history, geography (e.g., coastal versus mountain), economic development, demographic composition, services and organizations, natural and economic resources, and educational systems, among others


 


Communities and neighborhoods can have both positive and negative cascading effects on individuals and families. Neighborhoods and communities in rural areas may offer some protection to vulnerable families through their social environments (Clarke et al., 2014). Residents in rural communities often share a sense of belonging and highly value social connections (Fleming, Ysasi, Harley, & Bishop, 2018). This sense of belonging and social connections become essential pillars for the social capital of these communities. Neighborhoods can also hinder individuals’ capacity to cope with daily challenges; studies have found that less cohesive or closely-knit communities may increase the risk of anxiety and depression (Cutrona et al., 2000; Elliot, 2000; Ross, 2000).


 


Rural communities are experiencing a range of demographic and social changes that require different resources to promote resilience among their residents than in the past. U.S. demographic trends show an increase in the aging population (USDA, 2017) and the number of racial and ethnic minorities, including immigrants from Latin America (Burton, Lichter, Baker & Eason, 2013; Lichter, 2012), but a population loss in rural areas (USDA, 2017). One consequence is greater out-migration of young residents, negatively impacting economic growth and potentially decreasing community capacity for resilience in the future (USDA, 2017).


At the same time, many rural communities are experiencing challenging social problems, including rising numbers of suicides, opioid addictions, health disparities, and the number of families living in poverty (CDC, 2017; 2018; USDA, 2017). If these trends are not addressed adequately, rural communities’ ability to recover in the face of adversity may wane. To avoid this, rural communities will benefit from thorough assessments of their communities in order to develop effective ways to identify, mobilize, and utilize community assets and and address community needs.


 


The Community Capitals Framework (Flora & Flora 2013) and the following three key community-related constructs are relevant to this project: community resilience, community capital, and community capacity building. First, community resilience refers to the adaptive capacities of communities, typically in the face of natural disasters and other emergencies (Norris et al., 2008). Despite researchers’ regular use of the term, there is no consensus on how to operationalize or to measure community resilience (Patel et al., 2017). Nonetheless, common areas of interest in the study of community resilience include local knowledge, community networks and relationships, communication, health, governance/leadership, resources, economic investment, outlook, and preparedness (Patel et al., 2017).


Second is community capital, commonly defined as financial and social capital. For this project, we also include natural capital (e.g., geography, natural resources), cultural capital (i.e., values that promote self-sufficiency and sustainability), human capital (e.g., knowledge, skills, education), political capital (e.g., access capacity to influence policy and its implementation), and built capital (e.g,. infrastructural capacity). Communities must draw from existent resources, or develop or leverage additional resources, of capital to address current and emergent needs to be resilient and sustainable (Flora & Flora, 2013; Pitzer & Streeter, 2015). A third related construct is community-capacity building, or the extent to which communities can build strengths and assets (i. e. capital) to confront social and public health issues (Goodman et al., 1999). The capacity of a community to address various challenges with available resources (e.g., community capitals) will have direct and indirect impacts on families living in these communities, especially on low-income families and families of color who typically face additional burdens and have limited access to economic and social capital resources (Seccombe, 2004).


 


There is a critical need to understand better the needs and strengths of rural families or these families will continue to face severe economic and social challenges and result in cascading adverse effects across systems. As Walsh (2016) stated: “It is not enough to bolster the resilience of vulnerable families so that they can ‘beat the odds’; a multilevel approach requires larger systems support to change their odds” (p. 630). Thus, it is imperative to understand how to capitalize on individual, family, and community assets. In so doing, government, extension, and non-profit organizations can effectively use limited resources to achieve desired outcomes.


 

Objectives

  1. Objective #1 - Community Capacity: To assess community capacity to support resilience in diverse rural low-income families.
  2. Objective #2 - Individual and family resilience processes: To examine individual and family resilience processes from the perspective of rural, low-income mothers.

Methods

The procedure will occur in phases within each objective, as described below.

 

Procedure for Objective 1

 

Phase 1: Community Profiles

 

An Executive Committee will be formed with representatives of all the states. The committee will select rural communities within participating states using data from the Federal Office of Rural Health Policy (FORHP). After communities are selected, the team will conduct county-level assessments, which are commonly used in the field of public health to identify, mobilize, and activate community resources to address health needs (Sharpe et al., 2000) and have become a form of best practice in the field. The team will use the Community Toolbox (Center for the Community Health and Development, 2017) for guidance on methodologies and strategies. Although community assessments commonly are used to tackle health-related issues, this type of assessment has also been used to address other issues such as children well-being, crime, safety, and environmental issues (Myers & Stoto, 2006).

 

For this project, community assets are defined as persons, places, services, businesses, or any other community resource that improves the quality of community life and fosters resilience (Center for the Community Health and Development, 2017). Community needs can be defined as gaps between what the community currently has and what would be considered as adequate for attaining, improving and maintaining the quality of community life (2017). In order to compare and contrast communities in different states, the proposed community assessments will be more general and focused on community assets and resources that foster resilience. These assessments will also include community-level information and indicators that are accessible, measurable, possible to collect across different counties, and relevant for the understanding of resilience and the role that communities play in the process. Representatives in each team will collaborate in the creation of the community profiles during the first phase of Objective 1. Input from the community will be gathered during Phase 2. The team will begin the assessment process by developing community profiles using public data sources. Community profiles are a critical component of community assessments by providing up-to-date data describing communities. These profiles will also facilitate comparisons among counties. To describe the communities, data will be collected including: physical aspects, infrastructure, patterns of settlement, commerce and industry, demographics, history, community leaders, formal and informal, community culture (formal and informal), institutions and organizations, government and leadership, social structures, and attitudes and values. Initially, we will use public data records (e.g., U.S. census), national datasets, Robert Wood Johnson Foundation County (RWJF) Health Rankings, Google Maps street view, among others.

 

Descriptions of the counties will include a description narrative, region maps, assets maps of each county, and a list of gaps in knowledge, data, and areas in need of community-based input to be addressed during phase 2. Community profiles will be available to all the participating states, and the technical team will create a database that will include the profiles of all the communities for analysis and comparison. The Planning and Coordination team in collaboration with the Executive Board will select a state or a group of states that will be responsible for housing and protecting the collected data and for sharing the information with all participating states. Community profiles will be developed during the first two years of the project (See Timeline) and will inform data collection at the individual and family levels (Objective 2.).

 

Phase 2: Community-Based Data Collection

 

After community profiles are completed, gaps in information will be identified, and a community-level data collection plan will be developed. The technical team will train other team members in community data collection methods. Potential data collection methods commonly used for community assessments include community forums or focus groups, windshield and walking tours of communities, inventories, and photovoice (Center for the Community Health and Development, 2017; Sharpe et al., 2000).

 

Additionally, it is expected that each state will conduct at least 10-12 semi-structured interviews with community stakeholders in the selected counties. Stakeholders may include school board members, Department of Health staff, faith-based leaders, government officials, Extension leaders, and informal leaders in the community. Key informant interviews are frequently used in community assessments, and their purpose is to include a broader set of opinions about the community and its assets (Center for the Community Health and Development, 2017; Sharpe et al., 2000). Findings from the interviews will be triangulated with previously collected data and will be integrated to the community profiles developed during Phase 1.

 

Given the importance of recognizing the needs, characteristics, and challenges of individual communities, each state will determine if further data is needed to complete the assessment of their communities. Any additional data will be added to the community assessments. All community-based data will be compiled into a larger, multistate community dataset. Final community assessments will be produced and shared with all the participating states. Community assessments will be then linked to the individual and family level data (see Objective 2) and further analysis will be conducted.

 

Procedure for Objective 2

 

Phase 1: Identify Areas for Further Investigation in Existing Data

 

During the first two years while team members are selecting rural counties and collecting community-level data, we will conduct a content-analysis (Hsieh & Shannon, 2015) of the existing RFS/RFSH datasets for risk, protective, and resilience factors in rural, low-income families.

 

Phase 2: Administer Surveys to Collect New Data

 

Keeping consistent with our previous projects’ (RFS, RFSH) procedures, we propose a mixed-methods design (Mammen & Sano, 2012; 2018). First, we will collect quantitative survey data followed by qualitative interview data with a subset of participants. We will administer surveys to approximately 300 mothers (or the primary caregiver of the target child) residing in rural communities (i.e., approximately 20 interviews per participating state). In addition to rural residency, another major criterion for participation is having a household income that is 185% above the poverty line. This number has practical significance because many assistance programs, such as the Supplemental Nutrition Assistance Program (SNAP), use 185% to determine eligibility (Office of the Assistant Secretary of Planning and Evaluation, nd).

 

Sampling procedures will depend on our team’s resources at the time of data collection. One likely option will be to administer surveys using Qualtrics Panel Service (Qualtrics, Provo, UT), an online survey service that can screen potential participants to meet our sampling criteria, including residence zip code. Benefits of using Qualtrics’ Panel Service include reduced time and energy to recruit participants, as well as reduced costs. This method was validated recently in a meta-analysis of ninety independent samples with 32,121 participants; online survey methods produced comparable values to conventional survey methods (Walter, Seibert, Goering, & O’Boyle, 2018).

 

In order to maximize the number and diversity of respondents, we plan to take a multimodal approach to data collection - self-administered online survey, mailed survey, and in-person verbal interview. Strengths of online data collection include convenience for participants and researchers, low question order effects, and low social desirability bias (Bowling, 2005). Online survey data collection may not be a viable option for all rural residents, however. According to the Pew Research Center (Anderson, 2018), nearly a quarter of rural residents stated that high-speed, reliable internet access is a major problem, and 34% indicated it was a minor problem. Thus, for participants who have limited internet access or for whom self-administered online surveys are too challenging, they may complete a mailed survey or participate an in-person interview.

 

Regardless of sampling method, all participants will answer the same survey questions. We recognize the potential biases inherent in different data collection modes (Bowling, 2005), however, we believe the benefits of gaining a large diverse sample of rural, low-income mothers outweighs the potential limitations. We will track recruitment and data collection mode for each participant, so that we can test if there are systematic differences in responses.

 

Individual survey measures. Mothers will report on strengths, vulnerabilities, and experiences at three levels - individual (i.e., mother and target child), family, and community. In addition to standard demographic questions (e.g., age, race, ethnicity, education, income, employment), mothers will assess their current individual risk factors. One potential measure of vulnerability and risk is the Adverse Childhood Experiences (ACEs) Questionnaire, a measure of stressful or traumatic events, including abuse, neglect, or growing up with family members dealing with substance use issues. ACEs have been implicated in a number of adult health problems (e.g., Felitti et al., 1998). Other potential measures of adversity include chronic and acute stressors (e.g., major life events, work stressors, financial strain). For the purposes of unpacking the resilience process, it is critical to measure the timing, duration, and severity of stressors (Card & Barnett, 2015). Individual protective factors that are common across conceptual and measurement models of resilience include disposition (e.g., personal competence, locus of control, perseverance, emotion regulation, optimism), coping strategies, and social resources, such as kinship support (Masten, 2018).

 

Resilience modeled as an outcome is often assessed by health indicators, particularly mental health. Mothers will rate their mental health (e.g., depressive symptoms, perceived stress, life satisfaction, psychological well-being) and physical health (e.g., overall health, chronic health conditions, nutrition, sleep). Given the opioid crisis occurring in many rural communities, we will include questions about substance use and abuse. There are a few direct measures of adult resilience, such as the Brief Resilience Scale (BRS; Smith et al., 2008). Among fifteen resilience measures, the BRS is one of only three scales with strong psychometric ratings (Windle et al., 2011).

 

Similar to our team’s past data collection protocol, mothers also will report on the health and well-being of one target child who resides in the home with them. We will include age- and developmentally-appropriate measures of children’s internalizing and externalizing issues, such as the Child Behavior Checklist (CBCL) which our team used in NC1171. The CBCL is a widely used measure for children aged 2-3 or 4-18 assessing areas including anxiety, depression, social problems, and risky behavior (Achenbach, 1991; 1992). Other measures of well-being and resilience include children’s physical health and academic achievement.

 

Family survey measures. We will assess both family-level strengths (e.g., cohesion) and challenges (e.g., housing). Mothers’ will rate current romantic partner relationship quality (e.g., support, conflict, satisfaction), parent-child relationship quality (e.g., warmth, conflict, involvement), and parenting. Mothers will report on family unit-level experiences, such as family routines and rituals and family life satisfaction. Further, we will measure family adaptability, family cohesion, and family communication (e.g., Olson, 2000). We will also include questions to capture other household members and extended family (e.g., grandmothers) who may be a support or a challenge.

 

Community survey measures. To complement the objective data we will collect about the community for Objective 1, mothers will rate the availability, accessibility, and utility of community formal and informal supports. In addition, mothers will answer questions about their community, such as a psychological sense of community, community cohesion, and community satisfaction.

 

The survey will consist of a set of core measures across states to address Objective 2, while also allowing flexibility for individual states to include additional items as appropriate. Once survey data collection is complete, a data management team comprised of members across states will merge datasets from each state and clean the data (e.g., create scales, check for outliers). The data management team will also create a project codebook that provides scale and descriptive information for the core measures across states. The central data management and project-wide codebook will facilitate data consistency across and communication between states.

 

Because the design is inherently multilevel (i.e., individuals/families nested within communities), analyses will need to account for nesting using multilevel modeling (Hox, 2002). Depending on a writing team’s research question, the analysis may examine resilience as a characteristic, as an outcome, or as a process (Card & Barnett, 2015). Further, because resilience is a product of interactions among the different levels, analyses will move beyond direct associations to consider interactive and multiplicative associations. We can test pathways of resilience or pathways or protective processes (Masten, 2018). Additionally, to capture potential cascading resilience effects of mothers to their children, we can model mothers’ risks and assets to their parenting and, in turn, child outcomes (Doty et al., 2017; Masten, 2001). Cascading resilience will also be modeled from the community level to the individual and family levels

 

Phase 3: Conduct Case Studies

 

To gain a deeper understanding of resilience processes theorized in the literature and from the RFS/RFSH datasets, we will conduct semi-structured interviews with approximately 150 mothers (i.e., 10 per state). At the end of the quantitative survey in Phase 2, Qualtrics will display a prompt asking whether participants would be interested in participating in face-to-face interview. We will then use purposive sampling using county and individual survey data to ensure the subset of mothers represent a wide range of backgrounds and experiences (Mammen & Sano, 2012). These interviews will provide the opportunity for deeper insight into rural, low-income mothers’ experiences, including strengths, challenges, and adaptive strategies in the face of adversity. Because perceptions are a critical factor in resilience, the qualitative interviews will provide rich data on dynamic resilience processes. We will take an abductive approach to analyzing the qualitative interview data (Timmermans & Tavory, 2012): We will use an deductive approach by searching for concepts and themes from existing literature and conceptual models of individual, family, and community resilience. At the same time, we will use an inductive approach to allow for the emergence of new resilience concepts.

Measurement of Progress and Results

Outputs

  • Output 1: Community profiles of each participating data collection site, including asset mapping.
  • Output 2: Quantitative, multistate dataset of mothers’ reports of individual, family, and community factors related to resilience, health, and family relationships.
  • Output 3: Case studies of purposively selected rural low-income families across participating states.
  • Output 4: Comprehensive linked multistate dataset of community profiles and survey data to examine between- and within-community experiences of rural, low-income families.
  • Output 5: Presentations and publications, including peer reviewed publications and presentations, policy briefs, training materials, targeting diverse audiences (i.e., researchers, practitioners, policymakers, students, community members).

Outcomes or Projected Impacts

  • Impact 1: Improved knowledge of community-level assets and challenges related to individual and family resilience among rural, low-income mothers.
  • Impact 2: New and strengthened partnerships with county and state stakeholders and organizations in order to promote health and resilience among diverse rural low-income families.
  • Impact 3: Improved understanding of the multilevel factors and process of resilience among rural, low-income mothers.
  • Impact 4: Development of undergraduate, Master’s, and doctoral trained researchers in multi-method data collection, analysis, and dissemination focused on rural, low-income families.
  • Impact 5: Improved policy considering the multi-level factors associated the health, well-being, and resilience of rural low-income families.
  • Impact 6: Informed extension educators and community partners via presentations, publications, and locally-based curricula, in order to mobilize rural community capacity in a strengths-based manner.

Milestones

(0):(See Appendix for timeline.)

Projected Participation

View Appendix E: Participation

Outreach Plan

Team members will form into topical working groups to disseminate findings appropriate to their respective professional communities. Potential products include: refereed publications, state, regional, national and international conference presentations, policy and information briefs, web-based trainings and training materials. One example is conducting a two-part seminar with researchers and practitioners about the community data collection process and findings (Part 1) and feasible, actionable community-based approaches to support rural individuals and families (Part 2). Another example is to host a collective conversation with Cooperative Extension dedicated to sharing identified approaches to grow community-level resilience factors and processes. A regularly-maintained website will be used to communicate information about the project to interested stakeholders. Team members will work with graduate and undergraduate students so that students will be trained as researchers and practitioners who understand the complexity and importance of research on rural low income families and communities. Several of the researchers involved in the current project began as graduate students on previous related projects (i.e., NC223, NC1011, NC1171).


Additionally, we will translate research findings to inform the development of Extension materials or programs. Materials or programs might target rural individuals, families, or communities. Materials will be made available through the eXtension Foundation’s website, highlighted via nationally available synchronous and asynchronous webinars, and distributed by Extension educators throughout the country. Examples of such products include culturally sensitive information on feeding and nutrition for Spanish-speaking families, programs that support family knowledge about important issues (e.g., how to work well with your physician; managing children’s screen time; developmentally appropriate parenting practices), and community-level programs that strengthen community-wide opportunities (e.g., developing community forums on opioids).

Organization/Governance

Literature Cited

Achenbach, T. (1992). Manual for the Child Behavior Checklist/2-3 and 1992 Profile. Burlington, VT: University of Vermont Department of Psychiatry.


Achenbach, T. (1991). Manual for the Child Behavior Checklist/4 - 18 and 1991 Profile. Burlington, VT: University of Vermont Department of Psychiatry.


Anderson, M. (2018, September). About a quarter of rural Americans say access to high-speed internet is a major problem. Retrieved from http://www.pewresearch.org/fact-tank/2018/09/10/about-a-quarter-of-rural-americans-say-access-to-high-speed-internet-is-a-major-problem/


Anderson, M., Dobkin, C., & Gross, T. (2012). The effect of health insurance coverage on the use of medical service. American Economic Journal: Economic Policy, 4(1), 1-27. doi:10.1257/pol.4.1.1


Bauer, J. W., Braun, B., & Dyk, P. H. (2003). Health and the economic well-being of rural families. A public policy fact sheet. National Council on Family Relations.


Bauer, J. W., Braun, B., & Olson, P. D. (2000). Welfare to well‐being framework for research, education, and outreach. Journal of Consumer Affairs, 34(1), 62-81. doi:10.1111/j.1745-6606.2000.tb00084.x


Benzies, K., & Mychasiuk, R. (2009). Fostering family resiliency: A review of the key protective factors. Child & Family Social Work, 14, 103-114.


Bird, C. (2004). Education and training: Understanding the factors that influence the opportunity   to pursue additional education or training for low-income, rural women (Unpublished master's thesis). University of Minnesota, Minneapolis, MN.


Bird, C. L., Dolan, E. M., & Seiling, S. B. (2011). Resources as the key to rural employment. In J.Bauer & E. Dolan (Eds.), Rural families and work: Context and problems (pp. 137-156). New York, NY: Springer.


Bowling, A. (2005). Mode of questionnaire administration can have serious effects on data quality. Journal of Public Health, 27(3), 281-291.


Braun, B., & Rudd, M. (2003). About mental health: Maryland rural families speak. Issue Brief. Retrieved from https://sph.umd.edu/sites/default/files/files/MentalHealthResearchBrief.pdf


Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (pp. 793-828). Hoboken, NJ: John Wiley & Sons.


Burney, J., Routh, B., Greder, K., Greer, B. (2015). Associations between maternal depression and family nutrition and physical activity behaviors. Rural Families Speak about Health. Retrieved from https://iastate.box.com/s/e39g12cdgdq3rjzf4pusuea7ncujnvsx


Burton, L.M., Garrett-Peters, R., & Eason, J. (2011). Morality, identity, and mental health in rural ghettos. In L. Burton, S. Kemp, M. Leung, S. Matthews, & D. Takeuchi (Eds.), Communities, neighborhoods, and health: Expanding the boundaries of place. New York, NY: Springer.


Burton, L. M., Kemp, S. P., Leung, M., Matthews, S. A., & Takeuchi, D. T. (2011). Communities, neighborhoods, and health. New York, NY: Springer.


Burton, L. M., Lichter, D. T., Baker, R. S., & Eason, J. M. (2013). Inequality, family processes, and health in the “new” rural America. American Behavioral Scientist, 57, 1128–1151. doi:10.1177/0002764213487348


Byrne, M. & Greder, K. (2014). Health Insurance access and participation among Latinos in Iowa. Policy Brief. Iowa State University, Ames, IA.


Card, N. A., & Barnett, M. A. (2015). Methodological considerations in studying individual and family resilience. Family Relations, 64, 120-133.


Center for Community Health and Development. (2017). Chapter 3, Section 1: Developing a plan for assessing local needs and resources. Lawrence, KS: University of Kansas. Retrieved from the Community Tool Box: https://ctb.ku.edu/en/table-of-contents/assessment/assessing-community-needs-and-resources/develop-a-plan/main


Center for Disease Control (2017). Suicide in rural America. Retrieved from https://www.cdc.gov/ruralhealth/Suicide.html


Center for Disease Control (2018). Leading causes of death in rural America. Retrieved from https://www.cdc.gov/ruralhealth/cause-of-death.html


Clarke, P., Morenoff, J., Debbink, M., Golberstein, E., Elliott, M. R., & Lantz, P. M. (2014). Cumulative exposure to neighborhood context: Consequences for health transitions over the adult life course. Research on Aging, 36(1), 115-142.


Conger, R. D., & Conger, K. J. (2002). Resilience in Midwestern families: Selected findings from the first decade of a prospective, longitudinal study. Journal of Marriage and Family, 64,361–373.


Crockett, L. J., Carlo, G., & Temmen, C. (2016). Ethnic and racial minority youth in the rural United States: An overview. In Rural ethnic minority youth and families in the United States (pp. 1-12). Springer, Cham.


Cutrona, C.E., Russell, D.W., Hessling, R. M., Brown, P. A., & Murry, V. (2000). Direct and moderating effects of community context on the psychological well-being of African American women. Journal of Personality and Social Psychology, 79(6), 1088–1101.  


Cutter, S. L., Ash, K. D., & Emrich, C. T. (2016). Urban–rural differences in disaster resilience. Annals of the American Association of Geographers, 106(6), 1236-1252.


Darling, N. (2007). Ecological systems theory: The person in the center of the circles. Research in Human Development, 4, 203-217.


Doty, J. L., Davis, L., & Arditti, J. A. (2017). Cascading resilience: Leverage points in promoting parent and child well-being. Journal of Family Theory & Review, 9, 111-126. doi:10.1111/jftr.12175


Dyk, P. D., Radunovich, H., Sano, Y. (2018). Health challenges faced by rural, low-income families: Insights into health disparities. Family Science Review, 22(1).


Elliott M. (2000). The stress process in neighborhood context. Health Place, 6(4), 287-299.


Fang, X., Brown, D. S., Florence, C. S., & Mercy, J. A. (2012). The economic burden of child maltreatment in the United States and implications for prevention. Child Abuse & Neglect, 36(2), 156-165. doi:10.1016/j.chiabu.2011.10.006


Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245-258.


Fleming A.R., Ysasi N.A., Harley D.A., & Bishop M.L. (2018). Resilience and strengths of rural communities. In D. Harley, N. Ysasi, M. Bishop, & A. Fleming (Eds.), Disability and vocational rehabilitation in rural settings. New York, NY: Springer.


Flora, C., & Flora, J. (2013). Rural communities: Legacy and change (4th ed.). Boulder, CO: Westview.


Frey, N. (2018). Place satisfaction and perceived recovery after Hurricane Sandy on Staten Island’s East Shore. Environmental Hazards, 17(1), 40-55.


Goldman, N., Glei, D. A., & Weinstein, M. (2018). Declining mental health among disadvantaged Americans. PNAS, 115(28), 7290-7295.


Goodman, R. M., Speers, M. A., McLeroy, K., Fawcett, S., Kegler, M., Parker, E., Smith, S. R., Sterling, T. D., & Wallerstein, N. (1999). Identifying and defining the dimensions of community capacity to provide a basis for measurement. Health Education and Behavior, 25(3), 258-278.


Greder, K., Sano, Y., Mammen, S., & Doudna, K. (2014, November). Relationships between health and rural low-income mothers’ internet use. Poster symposium presented at the annual meeting of the National Council on Family Relations, Baltimore, MD.


Henry, C. S., Morris, A. S., & Harrist, A. W. (2015). Family resilience: Moving into the third wave. Family Relations, 64, 22-43.


Hox, J. (2002). Multilevel analysis: Techniques and applications. Mahwah, NJ: Lawrence Erlbaum.


Hsieh, H., & Shannon, S. E. (2015). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277-1288.


Keyes, K. M., Cerdá, M., Brady, J. E., Havens, J. R., & Galea, S. (2014). Understanding the rural–urban differences in nonmedical prescription opioid use and abuse in the United States. American Journal of Public Health, 104(2), e52-e59.


Kohler, J. K., Anderson, E. A., Oravecz, L., & Braun, B. (2004). Relationship constellations and dynamics of low-income rural mothers. Affilia, 19(2), 160-173. doi:10.1177/0886109903262772


Lichter, D. T. (2012). Immigration and the new racial diversity in rural America. Rural Sociology, 77(1), 3-35.


Mammen, S., & Lawrence, F. (2006). Use of the earned income tax credit by rural working families. Proceedings of the 33rd Conference of the Eastern Family Economics-Resource Management Association, 29-37.


Mammen, S., Bauer, J. W., & Lass, D. (2009). Life satisfaction among rural low-income mothers: The influence of health, human, personal, and social capital. Applied Research in Quality of Life, 4(4), 365-386. doi:10.1007/s11482-009-9086-6


Mammen, S., Berry, A. A., Bird, C., & Chandler, K. D. (2018). Rural low-income families’ quest for economic security: It takes more than a paycheck. Family Science Review, 22(1), 9-25.


Mammen, S., & Sano, Y. (2012). Gaining access to economically marginalized rural populations: Lessons learned from nonprobability sampling. Rural Sociology, 77(3), 462-482.


Mammen, S., & Sano, Y. (2018). Rural, low-income families and their well-being: Findings from 20 years of research. Family Science Review, 22(1), 1-8.


Mammen, S., Dolan, E., & Seiling, S. B. (2015). Explaining the poverty dynamics of rural families using an economic well-being continuum. Journal of Family and Economic Issues, 36(3), 434-450. doi:10.1007/s10834-014-9405-4


Masten, A. S. (2018). Resilience theory and research on children and families: Past, present, and promise. Journal of Family Theory & Review, 10, 12-31. doi:10.1111/jftr.12255


Masten, A. S., & Monn, A. R. (2015). Child and family resilience: A call for integrated science, practice, and professional training. Family Relations, 64(1), 5-21.


Meit, M., Knudson, A., Gilbert, T., Yu, A. T., Tanenbaum, E., Ormson, E., TenBroeck, S., Bayne, A., Popat, S., & NORC Walsh Center for Rural Health Analysis. (2014). The 2014 update of the rural-urban chartbook. Bethesda, MD: Rural Health Research & Policy Centers. Retrieved from https://ruralhealth.und.edu/projects/health-reform-policy-research-center/pdf/2014-rural-urban-chartbook-update.pdf


Minkler, M., Wallerstein, N., & Wilson, N. (2008). Improving health through community organization and community building. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education: Theory, research, and practice (pp. 287-312). San Francisco, CA, US: Jossey-Bass.


Myers, S., & Stoto, M. A. (2006). Criteria for assessing the usefulness of community health assessments: A literature review (TR-314-CDC). Santa Monica, CA: RAND. Retrieved from https://www.rand.org/pubs/technical_reports/TR314.html


Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L. (2008). Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41(1-2), 127-150.


Office of the Assistant Secretary of Planning and Evaluation. (nd). U.S. federal poverty guidelines used to determine financial eligibility for certain federal programs. Retrieved from https://aspe.hhs.gov/poverty-guidelines


Olson, C. M., & Bove, C. F. (2005). Obesity in rural women: Emerging risk factors and hypotheses. In R. T. Coward, L. A. Davis, C. H. Gold, H. Smiciklas-Wright, L E. Thorndyke, & F. W. Vondracek (Eds.), Rural Women's Health: Linking Mental, Behavioral, and Physical Health (pp. 63-81). New York, NY: Springer.


Olson, D. H. (2000). Circumplex model of marital and family systems. Journal of Family Therapy, 22, 144-167.


Orthner, D. K., Jones-Sanpei, H., & Williamson, S. (2004). The resilience and strengths of low-income families. Family Relations, 53, 159-167.


Patel, S. S., Brooke Rogers, M., Amlôt, R., & Rubin, G. J. (2017). What do we mean by ‘community resilience’? A systematic literature review of how it is defined in the literature. PLoS Currents, 1, 9. doi:10.1371/currents/dis.db775aff25efc5ac4f0660ad9c9f7db2


Peterson, C., Florence, C., Thomas, R., & Klevens, J. (2017). Cost-benefit analysis of two child abuse and neglect primary prevention programs for US states. Prevention Science, 19(6), 705-715. doi:10.1007/s11121-017-0819-8


Pew. (2014). Changing patterns in U.S. immigration and population: Immigrants slow population decline in many counties. Retrieved from: https://www.pewtrusts.org/en/research-and-analysis/issue-briefs/2014/12/changing-patterns-in-us-immigration-and-population


Pitze, K. A., & Streeter, C. L. (2015). Mapping community capitals: A potential tool for social work. Advances in Social Work, 16(2), 358-371.


Qualtrics. (2018). Provo, UT: Author. https://www.qualtrics.com


Rappaport, J. (1984). Studies in empowerment: Introduction to the issue. Prevention in Human Science, 3, 1-7.


Romero de Slowing, F. (2012) “Le tengo fe” How do women’s networks influence the health competence of Latina immigrant mothers living in a rural Midwestern state? (Unpublished master’s thesis). Iowa State University, Ames, IA.


Ross, C. E. (2000). Neighborhood disadvantage and adult depression. Journal of Health and Social Behavior, 41(2),177-187.


Saleebey, D. (1996). The strengths perspective in social work practice: Extensions and cautions. Social Work, 41(3), 296-305.


Sampson, R., Morenoff, J., & Gannon-Rowley, T. (2002). Assessing "neighborhood effects": Social processes and new directions in research. Annual Review of Sociology, 28, 443-478.


Save the Children. (2017). Growing up in rural America:  U.S. Complement to the end of childhood report.  Fairfield, CN: Author.  


Seccombe, K. (2004) “Beating the odds” versus “changing the odds:” Poverty, resilience, and family policy. Journal of Marriage and Family, 64(2), 384-394. doi:10.1111/j.1741-3737.2002.00384.x


Sharpe, P. A., Greaney, M. L., Lee, P. R., & Royce, S. W. (2000). Assets-oriented community assessment. Public Health Reports, 115(2-3), 205-211.


Simmons, L. A., Anderson, E. A., & Braun, B. (2008). Health needs and health care utilization among rural, low-income women. Women & Health, 47(4), 53-69.


Simmons, L. A., Berry, A. A., Huddleston-Casas, C. A., & Dyk, P. H. (2006). Low-income rural mothers experiencing depression: Characteristics associated with self-reporting. American Public Health Association, Boston, MA.


Simmons, L. A., Huddleston-Casas, C., & Berry, A. A. (2008). Low-income rural women and depression: Factors associated with self-reporting. American Journal of Health Behavior, 31(6), 657-666.


Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Bernard, J. (2008). The Brief Resilience Scale: Assessing the ability to bounce back. International Journal of Behavioural Medicine, 15, 194-200.


Timmermans, S. & Tavory, I. (2012). Theory construction in qualitative research: From grounded theory to abductive analysis. Sociological Theory, 30(3), 167-186.


US Census. (2016, December). New Census data show differences between urban and rural populations (Release Number CB16-210). Retrieved from https://www.census.gov/newsroom/press-releases/2016/cb16-210.html  


U.S. Department of Agriculture, National Institute of Food and Agriculture (NIFA). (2014). NIFA strategic plan for FY 2014-2018. Washington DC: Author.


United States Department of Agriculture USDA. (2017). Rural America at a glance: 2017 edition (Economic information bulletin 182). Retrieved from https://www.ers.usda.gov/webdocs/publications/85740/eib182_brochure%20format.pdf?v=0


United States Department of Agriculture USDA. (2017). Research, Education, and Economics Action Plan Progress Report, 2016. Washington DC: Author.


Walker, S. K., Manoogian, M. M. (2011). Child care: A challenge for rural families to meet economic, personal, and family needs. In Bauer, J. W., Dolan, E. M. (Eds.), Rural families and work: Contexts, problems, and solutions. New York, NY: Springer.


Wallerstein, N. (1992). Powerlessness, empowerment, and health: Implications for health promotion programs. American Journal of Health Promotion, 6, 197-205.


Wallerstein, N. (2006, February). What is the evidence on effectiveness of empowerment to improve health?  (Health Evidence Network report.) Copenhagen, WHO Regional Office for Europe. Retrieved from http://www.euro.who.int/Document/E88086.pdf


Walsh, F. (2002). A family resilience framework: Innovative practice implications. Family Relations, 51(2), 130-137.


Walter, S., Seibert, S., Goering, D., O’Boyle, E. (2018). A tale of two sample sources: Do results from online panel data and conventional data converge?  Journal of Business and Psychology, Retrieved from https://link.springer.com/content/pdf/10.1007%2Fs10869-018-9552-y.pdf. https://doi.org/10.1007/s10869-018-9552-y.


Williams, D. R., & Collins, C. (2001). Racial residential segregation: A fundamental cause of racial disparities in health. Public Health Reports, 116(5), 404–416.


Windle, G., Bennett, K. M., & Noyes, J. (2011). A methodological review of resilience measurement scales. Health and Quality of Life Outcomes, 9(8), 1-18.


Yancura, L., Barnett, M., Mammen, S., & Sano, Y., (under review). Complementary analyses of grandparent contributions to low-income rural families. Child & Family Social Work.


Zwagerman, J. (2017, January). Rural America matters to all Americans. Retrieved from http://theconversation.com/rural-america-matters-to-all-americans-69756

Attachments

Land Grant Participating States/Institutions

AZ, CA, FL, HI, IA, IN, KS, KY, MI, MS, MT, NC, OK, OR, TN, WA

Non Land Grant Participating States/Institutions

Log Out ?

Are you sure you want to log out?

Press No if you want to continue work. Press Yes to logout current user.

Report a Bug
Report a Bug

Describe your bug clearly, including the steps you used to create it.