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Abstract

A coalition of community members and human service professionals in the rural central Shenandoah Valley of Virginia has performed a community assessment every 5 years. Overreliance on quantitative surveys and hospital-based Community Health Needs Assessments resulted in earlier assessments failing to identify the needs of vulnerable populations. As the coalition approached the time for a new assessment, their priority was to develop a deeper understanding of community health needs and solutions. An extended co-learning process between coalition, community, and local academic representatives resulted in a plan to develop assessment methods and community health improvement resources suited to this goal. The coalition identified methods rooted in the social determinants of health and utilized a community-based participatory research approach to provide underserved residents the opportunity to contribute to health research and decision making and produce an assessment more reflective of their community. Resources including local interpretation and implications of the World Health Organization’s 10 Social Determinants of Health, a Healthy People 2020 community health services profile, and user-friendly access to community-based secondary data sets were developed for intervention planning. All information, resources, and implications were shared at meetings, in public announcements, and at a public forum. All data remain publicly available on the coalition’s website. Previously held beliefs regarding access to care and quality of life were substantiated through this process, enabling the coalition to better align itself with local political entities and to move forward immediately with community health improvement planning.

Keywords

health equity community-based participatory research community health assessments health disparities academic partnerships social determinants of health

Introduction

A coalition of community members and human service professionals in the rural central Shenandoah Valley in Virginia performs a community assessment every 5 years. Previously, assessments had been completed in conjunction with the local hospital-based Community Health Needs Assessments (CHNAs, required under the Patient Protection and Affordable Care Act). However, overreliance on quantitative surveys and hospital-based CHNAs resulted in earlier community assessments failing to identify community health interests and vulnerable population needs. As they approached the time for a new assessment, their hope was to develop a deeper and broader understanding of community health needs and services. The coalition identified methods rooted in the social determinants of health and utilized a community-based participatory research (CBPR) approach to provide underserved residents the opportunity to contribute to health research and decision making that would produce data more reflective of their community.

CBPR is a collaborative research technique where members of the community take an active role in the development, implementation, and analysis of the study (Viswanathan et al., 2004). Fundamental principles of CBPR include the following: (a) recognizing the community as a unit of identity, (b) building on strengths and resources within the community, (c) facilitating collaborative, equitable involvement of all partners in all phases of the research, (d) integrating knowledge and intervention for mutual benefit of all partners, (e) promoting a co-learning and empowering process that attends to social inequalities, (f) involving a cyclical and iterative process, (g) addressing health from both positive and ecological perspectives, (h) disseminating findings and knowledge gained to all partners, and (i) involving a long-term commitment by all partners (Israel, 2000).

CPBR was chosen as an approach for this project because it builds collective impact and encourages health and associated professionals across disciplines to unite to achieve substantial change in the social determinants of health (Pastor & Morello-Frosch, 2014; Woolf, Zimmerman, Haley, & Krist, 2016). CBPR also offers means to assure that research results and processes improve the health of all communities (Allen et al., 2017). In addition, CBPR tends to pull together community-specific information, thereby improving data quality (Holloman & Newman, 2010).

Two limitations in previous community health assessments in the subject community were underrepresentation of vulnerable populations and planning priorities reflective of health care, rather than community health. In previous assessments, random digit dialing landline surveys were employed limiting responses to people with access to landlines and clearly underrepresenting agency coalition members’ clientele (most of whom use either cell phones or no phones at all). Similarly, the content of the previous survey focused on health conditions and hospital use, rather than eliciting perspectives and resources needed from community members (vulnerable or not). When the local hospital elected to do its own assessment, an opportunity existed for the local health coalition to partner with the local university and develop a more equitable, participatory, community-based approach. Research supporting this decision suggests that CBPR practices are consistent with more effective and efficient studies (Viswanathan et al., 2004), When both community partners and academics are working toward community health priorities, improvements can be amplified and accelerated. Similarly, when participants contribute their thoughts across a wide spectrum, realistic strategies for solving health problems are produced (Wynn et al., 2016). Finally, benefits of conducting CBPR for health include improved capacity among stakeholders, productive outcomes, increased sustainability of project goals, and the possibility of systems change (Jagosh, et al., 2012; Viswanathan et al., 2004).

Method

Community Partnership

Harrisonburg City (estimated population of 50,000) and surrounding Rockingham County (estimated population 75,000) encompass a rural, agricultural environment that is largely White, with a significant Hispanic minority (15% in Harrisonburg City). Harrisonburg City itself is not defined as rural, but services for County residents (population density approximately 80/sq mi) are often either located in Harrisonburg City or simply not available in the County. The Healthy Community Council of Harrisonburg/Rockingham (HCC) was established over 20 years ago by a group of human services professionals, health care organizations, University representatives, and committed citizens to enhance community health, and health and social services. The HCC’s stated mission is to “enhance the quality of life for the community through collaborative efforts of individuals, agencies, and institutions.” Every 5 years, the HCC performs a community assessment, with a twofold goal: (a) to obtain health-related data for use by HCC members and their agencies, and (b) to contribute meaningfully to community health planning and intervention (http://www.healthycommunitycouncil.org/, retrieved May 26, 2017). Three previous community assessments were performed using quantitative surveys. Random digit dialing strategies (landline only) and stakeholder focus groups were employed in conjunction with the local hospital’s CHNA. For the 2016 assessment, the HCC steering committee recognized that the landline strategy and the hospital-directed method significantly underrepresented vulnerable populations, specifically, and community health issues, in general. For the 2016 assessment, the HCC committed to using CBPR to enhance representation, focusing on community health rather than health care needs.

Study Design

The HCC was integrally involved at each stage of the research process, beginning with 18 months of planning, discussion, and co-learning with academic partners (including both authors). Subsequently, the HCC developed a fourfold strategy to complete the 2016 community assessment, meeting their goals for shared data collection and community health improvement planning. The strategy included three resource development elements and a community health priorities survey as follows:

Collect secondary quantitative health data sources for community and coalition use;

Develop a Healthy People 2020 community profile of resources and partners focused on the Healthy People 2020 categorization of the social determinants of health (https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health);

Develop local interpretations, tools, and resources to address the Social Determinants of Health (WHO, The Solid Facts, 2003); and

Survey users of local human services and their representatives, community organizations, parent groups, and community members regarding priority health and quality of life issues in Harrisonburg/Rockingham.

Consistent with a CBPR approach, all data, resources, and survey results were returned to the community via a culminating community summit and a companion website (see http://www.healthycommunitycouncil.org/).

Study Population

The study population refers only to the local survey (No. 4, above). HCC Steering Committee members surveyed approximately 260 people at 24 community, school, workplace, and human services agency meetings. A sampling of community groups surveyed included civic club and parent teacher organization members, disability and immigrant services recipients, transportation assistance program board members, senior and disabled services clients, homeless advocacy organizations, work programs for disabled residents, and similar United Way and publicly funded organizations representing vulnerable residents. Survey respondents were not intended to be representative of the general population and were intentionally drawn from community groups and services likely to include HCC coalition and social service agency clients.

Intervention

A formal intervention was not planned as part of the study design. However, results of the community assessment were intended to contribute to a community health improvement plan (CHIP) by prioritizing community health needs and providing resources and data to support implementation of a new CHIP.

Data Collection and Measurement Methods

Data were collected or resources gathered for all four aspects of the assessment. Measurement methods pertained only to the local survey (No. 4, above). Quantitative secondary data resources were gathered from reputable sources with representative local data (County Health Rankings, The Virginia Atlas, the local hospital CHNA, and the Harrisonburg/Rockingham Youth Data Survey).

The Healthy People 2020 Community Profile was developed by social work students under the guidance of their faculty instructor (author). Organizing according to the five HP 2020 Social Determinants of Health, students contacted health and human services agencies in the region, interviewed agency representatives, and developed a spreadsheet of pertinent information to be shared with HCC members, health planners, and the community at large.

The World Health Organization’s (WHO; 2003) Social Determinants of Health: The Solid Facts, framed the local experience of community health and possible intervention in Harrisonburg/Rockingham. Graduate students under the advice of faculty (author) researched each of the 10 Social Determinants of Health shown to contribute to well (or ill) health around the world, translated findings into the local context, and recommended a set of possible local interventions for use in community health planning.

The local survey incorporated two closed-ended questions regarding personal and community health (Figures 1 and 2), followed by two open-ended questions using a strengths and challenges framework, as follows:

What three features of the Harrisonburg/Rockingham community make this a good place to live? (Community strengths, Figure 3) and

What three features of the Harrisonburg/Rockingham community make this a difficult place to live? (Community challenges, Figure 4)

Figure 1.

Self-reported health.

Figure 2.

Health and quality of life in Harrisonburg/Rockingham.

Figure 3.

Community strengths: What three features of the Harrisonburg/Rockingham community make this a good place to live?

Figure 4.

Community challenges: What three features of the Harrisonburg/Rockingham community make this a difficult place to live?

The surveys were delivered and collected by HCC Steering Committee members at various community meetings and returned to the authors for analysis. Human participants’ oversight was provided by the James Madison University Institutional Review Board. A cover letter explained the survey in accessible language. A Spanish translation was made, and the survey delivered by a Spanish speaking-HCC member to Spanish speaking-community groups. A Kurdish translation was also made; however, the HCC was unable to coordinate survey delivery at the single Kurdish community group meeting within the study period. Surveys were delivered and retrieved between January and April 2016 and all participants’ written consent was obtained prior to survey completion.

Analytic Methods

Qualitative survey data were analyzed using content analysis and Word Clouds to pictorially represent open-ended responses (Brantmeier & Bodle, 2015; McNaught & Lam, 2010) and provide methods for discussing the results in an accessible manner with HCC members and community participants (the type size in Word Clouds increases with the number of responses reflecting each theme, see Figures 3 and 4). The authors served as multiple analysts to develop themes. Triangulation was used with participants to cross-check the wording of questions and concepts assessed (Merriam, 2009; Patton, 2002; Creswell, 2013). Initial coding was done on paper, using consensus coding between authors. An audit trail was maintained in Excel. HCC members provided for triangulation and validation of the qualitative measures and themes, further strengthening methods and analysis (Creswell, 2014; McNaught & Lam, 2010).

Quantitative survey data (Figure 1) were compiled and presented as raw data in bar charts, which were deemed by authors to be the most accessible depiction of community health and personal health data.

Results

Two hundred-sixty surveys were collected from community groups. One hundred fifty-three participants (59% of those surveyed) responded to the self-reported and community health questions. Of these, 67 reported excellent health (44%), 49 (32%) reported good, and 35 (23%) reported fair health (see Figure 1).

Two hundred sixty (100%) participants responded to the community health and quality of life question, with 44 (17%) rating health and quality of life in Harrisonburg/Rockingham as excellent, 169 (65%) as good, 41 (16%) fair, and 6(2%) as poor (see Figure 2).

Content analysis of the open-ended question regarding community strengths revealed strong community values for activities (largely outdoor recreation); people, who were described as “neighborly,” “friendly,” and “diverse”; and the natural beauty of the region. Secondary strengths and qualities included transportation and health care (see Figure 3).

In contrast, a single predominant theme appeared in the analysis of the quality of life community challenges question: transportation. Lack of timely, accessible public transportation and traffic congestion from the university overwhelmed every other response as can clearly be seen in the Word Cloud in Figure 4, below.

In addition to the surveys, secondary data from reliable community health indicators data sets were made available to the HCC and the public via the organization’s website, including publicity for it (Figure 5). The community services profile was developed and included on the website, as were local implications and resources to address the social determinants of health.

Figure 5.

Healthy community council community assessment announcement mailer.

Finally, a public summit was held to announce assessment findings. The meeting was open to the public, with stakeholders and specific interest groups invited. Assessment findings were well received, with a single objection voiced regarding methods. The HCC had previously recognized the challenge of transportation for vulnerable populations in the region, but had been unable to gain public or political traction on the issue up to this point. A local television station interviewed authors and HCC members during the summit, giving widespread (but unmeasurable) coverage to findings. Having recognized the overwhelming challenge to health and quality of life in the surveyed population, the HCC announced that it would adopt transportation as a priority community health challenge and plan to address this long-standing problem in the coming year.

Discussion

This study set out to determine community health strengths and challenges from its most vulnerable members and their representative service providers and to gather data useable by community agencies to plan for health improvements in the future. A great variety of strengths were identified including recreational activities, friendly and diverse people, beautiful environment, safe neighborhoods, parks, and health care. The greatest challenge to quality of life for participants, however, was singular: Transportation was overwhelmingly identified as the single issue making it difficult to live in Harrisonburg/Rockingham. The relationship of transportation to health is well established (see WHO, 2003), and HCC members were enthusiastic to see this locally well-known health challenge clearly appear from the data they collected.

Specific challenges to using a participatory approach include the rural nature of the subject community. CBPR can be done poorly because of assumptions and challenges unique to rural areas: “the focus should be on developing strategies that support participation by marginalized population groups” (Kenny, Farmer, Dickson-Swift, & Hyett, 2014, p. 1914). Rural areas need effective, wide-ranging approaches that engage stakeholders to address individual and environmental factors that contribute to poor health outcomes due to limited resources (Hill et al., 2015). Taking a deep community partnership approach, including comprehensive outreach strategies, leads to high community involvement in the study, investment in results, and increased data validity (Santilli, Carroll-Scott, & Ickovics, 2016). As a result of the CBPR process, the community owns the issues and is more likely to follow through with interventions designed for health impact and rural health disparities reduction (Frerichs, Lich, Dave, & Corbie-Smith, 2016; Zoellner et al., 2012).

Lessons learned and challenges for HCC coalition members and their academic partners were similar. Members resisted participatory assessment for a long period of time, uncertain that qualitative community surveys and the use of secondary data would reveal the community’s “true” health status. Developing an equitable assessment required extensive co-learning to gain buy-in for this innovative approach. Authors were frequently challenged to explain the relationship of quality of life to health, and the validity and value of collecting qualitative over quantitative data to illuminate that relationship. The long-standing nature of the HCC and its firm reputation in the community ensured it could sustain the time it took to learn and institutionalize these unfamiliar concepts.

The HCC’s goal of representing underserved and vulnerable populations’ viewpoints on health and challenges to quality of life was well served by using this participatory, strengths-based method of community assessment. Prior community assessments employed stakeholder focus groups, quantitative surveys of community members, and secondary analysis of hospital data. These prior assessments prioritized (a) overall population health, (b) hospital-derived measures of health, and (c) stakeholder interests above vulnerable populations, quality of life, and community-driven priorities. Community health priorities (transportation in this case) are more readily addressed using this methodology, than the traditional hospital-based community assessment.

New contributions and implications of this research include the use of content analysis using Word Clouds to display assessment data which was a strong fit for this project. It is a simple method of understanding key concepts (Edyburn, 2010), is accessible and user friendly, and supports an equitable partnership and shared leadership between researchers and participants. It also involves the participants more strongly in the iterative process of research and the dissemination of the results and recommendations (Israel et al., 2005). Similarly, engaging HCC Steering Committee members to administer the surveys ensured active buy-in to the research process and ownership of the results. Finally, delivery of assessment results in a public forum and providing community health improvement planning resources ensured the HCC would be confident to take meaningful steps to intervene. HCC members were surprised and pleased to see the results of the health challenges questions (transportation). The finding, delivered in public, strengthened HCC alliances and enhanced political traction on this long-standing public problem. Since this article has been under review, HCC made transportation a 5-year coalition priority, garnered further political capital to address the problem through public meetings and resource identification, and was recently awarded a grant to address transportation needs of rural vulnerable residents.

In conclusion, overreliance on quantitative surveys and hospital-based assessments combined with unfamiliarity of the social determinants of health and participatory methods results in assessments that often fail to equitably address community health. Extensive co-learning among planning groups and partners is necessary to ensure all voices are represented in community assessments and CHIPs.

Limitations of this study are significant when considered from a research perspective. Lack of representative sampling, inter-rater reliability between surveyors, and the evolving study design associated with a jointly owned project of this kind are only a few. However, limitations from the perspective of capacity building seem insignificant when considering the relationships built, credibility gained, and voices heard during this process.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Maria Gilson deValpine

Author Biographies

Maria Gilson deValpine is a professor of nursing at James Madison University. Her research interests include the social determinants of health and rural and remote health disparities. She is currently working on a history of nursing in Alaska.

Laura Hunt Trull is an assistant professor of Social Work at James Madison University. Her research interests include health disparities and the social determinants of health. She recently collaborated to coordinate the RAM Clinic for Western Virginia, which serves a wide variety of health needs in rural and remote parts of the state.

References

Allen

M. L.

Salzberg

Knot

LeMaster

J. W.

Felzein

Westfall

J. M.

. . . Macaulay

A. C.

(2017). Engaging with communities, engaging with patients: Amendment to the NAPCRG 1998 Policy Statement on Responsible Research with Communities. Family Practice, 34, 313-321. doi:10.1093/fampra/cmw074

Brantmeier

N. K.

Bodle

(2015, January). Introduction to qualitative data analysis. Workshop presented for the James Madison University Center for Faculty Innovation, Harrisonburg, VA.

Creswell

J. W.

(2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Thousand Oaks, CA: Sage.

Creswell

J. W.

(2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: Sage.

Edyburn

D. L.

(2010). Would you recognize Universal Design for Learning if you saw it? Ten propositions for new directions for the second decade of UDL. Learning Disability Quarterly, 33(1), 33-41.

Frerichs

Lich

K. H.

Dave

Corbie-Smith

(2016). Integrating systems science and community-based participatory research to achieve health equity. American Journal of Public Health, 106, 215-222.

Hill

J. L.

Olive

N. C.

Waters

C. N.

Estabrooks

P. A.

You

Zoellner

J. M.

(2015). Lack of healthy food options on children’s menus of restaurants in the health-disparate Dan River region of Virginia and North Carolina. Preventing Chronic Disease, 12(40), 1-8.

Holloman

E. L.

Newman

M. C.

(2010). A community-based assessment of seafood consumption along the lower James River, Virginia, USA: Potential sources of dietary mercury exposure. Environmental Research, 110, 213-219. doi:10.1016/j.envres.2010.01.002

Israel

B. A.

(2000). Community based participatory research: Principles, rationale and policy recommendations. In O’Fallen

L. R.

Tyson

F. L.

Dearry

(Eds.), Successful models of community-based participatory research: Final report (pp. 16-29). Research Triangle Park, NC: National Institute of Environmental Health Sciences.

10.

Israel

B. A.

Parker

E. A.

Rowe

Salvatore

Minkler

López

Halstead

(2005). Community-based participatory research: Lessons learned from the Centers for Children’s Environmental Health and Disease Prevention Research. Environmental Health Perspectives, 113(10), 1463-1471.

11.

Jagosh

Macaulay

A. C.

Pluye

Salsberg

Bush

P. L.

Henderson

. . . Greenhalgh

(2012). Uncovering the benefits of participatory research: Implications of a realist review for health research and practice. Milbank Quarterly, 90, 311-346.

12.

Kenny

Farmer

Dickson-Swift

Hyett

(2014). Community participation for rural health: A review of challenges. Health Expectations, 18, 1906-1917.

13.

McNaught

Lam

(2010). Using wordle as a supplementary research tool. The Qualitative Report, 15(3), 630-643.

14.

Merriam

(2009). Qualitative research: A guide to design and implementation. Hoboken, NJ: Jossey-Bass (Wiley).

15.

Pastor

Morello-Frosch

(2014). Integrating public health and community development to tackle neighborhood distress and promote well-being. Health Affairs, 33, 1890-1896.

16.

Patton

M. Q.

(2002). Designing qualitative studies (3rd ed.). Thousand Oaks, CA: Sage.

17.

Santilli

Carroll-Scott

Ickovics

J. R.

(2016). Applying community organizing principles to assess health needs in New Haven, Connecticut. Public Health Policy, 106, 841-847.

18.

Viswanathan

Ammerman

Eng

Garlehner

Lohr

K. N.

Griffith

. . . Whitener

(2004). Community-based participatory research: Assessing the evidence. Evidence Report/Technology Assessment (Summary). (99), 1-8.

19.

Woolf

S. H.

Zimmerman

Haley

Krist

A. H.

(2016). Authentic engagement of patients and communities can transform research, practice and policy. Health Affairs, 35, 590-594.

20.

World Health Organization. (2003). Wilkinson

Marmot

,(Eds.), Social determinants of health: The solid facts (2nd ed.). Geneva: WHO.

21.

Wynn

T. A.

Wyatt

S. B.

Hardy

C. M.

Walker

S. S.

Thomas

T. F.

Williams

A. G.

Partridge

E. E.

(2016). Using community feedback to improve community interventions: Results from the deep South network for cancer control project. Family and Community Health, 39, 234-241.

22.

Zoellner

Motley

Wilkinson

M. E.

Jackman

Barlow

M. L.

Hill

J. L.

(2012). Engaging the Dan River region to reduce obesity: Application of the comprehensive participatory planning and evaluation process. Community Health, 35, 44-56.

Health Equity in Community Assessments: A Participatory Approach in Rural Virginia

Abstract

Keywords

Introduction

Method

Community Partnership

Study Design

Study Population

Intervention

Data Collection and Measurement Methods

Analytic Methods

Results

Discussion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

Author Biographies

References