August 2007
Volume 45 Number 4

Research in Brief

Extension Educators' Views of Scholarship and Performance Evaluation Criteria

Kent D. Olson
Professor and Area Program Leader, Agricultural Business Management
Department of Applied Economics
University of Minnesota
St. Paul, Minnesota
kdolson@umn.edu

Jennifer A. Skuza
Extension Professor
Director, Urban 4-H Youth Development
University of Minnesota
St. Paul, Minnesota
skuza@umn.edu

Charles R. Blinn
Professor and Extension Specialist
Department of Forest Resources
University of Minnesota
St. Paul, Minnesota
cblinn@umn.edu

Introduction

The core values of land-grant universities are historically based on research and outreach. Enhancing scholarly activity within Extension is one way to bolster the land-grant mission while continuing its legacy. Boyer (1990) considers scholarship as having four distinct yet overlapping functions: discovery, integration, application, and teaching. In this view, scholarship is more than engaging in original research. It is also stepping back from a study to search for relationships, build connections between theory and practice, and effectively communicate new knowledge to others. Boyer's depiction of scholarship may require scholars to redefine their current view of scholarship.

To ensure that this contemporary definition of scholarship would be taken seriously, Boyer (1990) challenged scholars to develop standards and evaluation approaches for scholarly work. This challenge was addressed by Glassick, Huber, and Maeroff (1997), who assert that guidelines for scholarship evaluation need to be developed, clarified, and understood among colleagues. In other words, there needs to be a shared understanding of scholarship among colleagues and a clear process for evaluating scholarly work. This understanding needs to reflect contemporary views as well as the core values of the institution. From that base, annual review, promotion evaluations, and scholarship assessment reform are possible.

The faculty senate at Oregon State University (OSU) undertook the challenge to define and articulate characteristics of scholarship that apply across academic disciplines and department missions to provide a theoretical foundation for reviewing and revising tenure and promotion guidelines (Weiser & Houglum, 1998). While Boyer's (1990) work influenced its development, the OSU model has a stronger emphasis on outputs to validate scholarship. For instance, OSU's promotion and tenure criteria assess the extent to which scholarly achievement is "original, significant, and useful to others" (Weiser & Houglum, 1998, p. 3).

The University of Wisconsin-Extension applied Boyer's (1990) broader thinking of scholarship (also see Lynton & Elman, 1987; Lynton, 1995) to promotion and tenure criteria in the hope that the scholarship documentation would better match the probationary faculty's portfolio development (Wise, Retzleff, & Reilly, 2002). As a part of that effort, outreach was described as "a particular and distinct form of scholarly activity deeply embedded in the University's mission to create, integrate, transfer, and apply knowledge" (University of Wisconsin-Madison Council on Outreach, 1997, p. 35). University of Wisconsin-Extension faculty members also adopted the following revised definition of scholarship: "creative intellectual work; reviewed by the scholar's peers who affirm its value; added to our intellectual history through its communication; and valued by those for whom it was intended" (UWEX Articles of Faculty Governance, Appendix I.B. 2001).

One of the core values of the University of Minnesota Extension Service (herein referred to as Extension) is that "Scholarship and research guide our educational programs" (Casey, Morse, & Markell, 2004, p. 28). The organization has a historic legacy of research-based programming and audience engagement. To become a more responsive organization with higher quality programs that have better documented impact, a task force was formed in 2005 to develop a shared understanding of scholarship in relation to promotion standards and assessment tools. This article reports the results of a survey of Regional Extension Educators (REEs) within Extension that solicited thoughts on their definition of scholarship, extent of its use in their everyday work, and its importance in performance evaluation. Documenting this information was critical to the success of bolstering our organization's ability to enhance scholarship.

Methods

A survey containing both categorical and open-ended questions was developed and conducted on-line using Survey Monkey (Survey Monkey) from September 7 - 16, 2005. The survey included the following sections: demographics, defining scholarship, current use of scholarship within Extension, how scholarship was related to staff and faculty's work, and scholarship and performance evaluation. The development of some survey questions was influenced by Boyer's (1990) model of scholarship. Scholarship was not defined for study participants either before or within the survey.

The analysis presented here focuses on how scholarship was currently defined and conducted by REEs, as well as their perspectives about the importance of various factors that may influence performance evaluation. REEs, who have statewide responsibility, are the largest group of faculty within the University of Minnesota Extension Service. REEs hold professional and academic positions with academic ranks (i.e., Assistant Extension Professor, Associate Extension Professor, and Extension Professor) without tenure. Administratively, they are organized into five Capacity Areas based on broad subject matter areas: Agriculture, Food, and Environment; Community Vitality; Family Development; Natural Resources and Environment; and Youth Development.

REEs are the focus of this article because they are the only group within Extension that is subject to new performance evaluation and promotion guidelines that add scholarship as one of the primary criteria. (Extension also includes local Extension educators as well as administrative, civil service, and other professional and academic staff members but they are not included in this analysis since they are not subject to these new guidelines.)

Survey responses were analyzed using SAS (SAS Institute). Fisher exact tests were used to evaluate independence of responses in cross-tabulations to test the strengths of relationships between responses to survey questions (SAS Institute; Rosner, 1995). Likert scores were averaged and used to rank responses within questions and t-tests were used to determine and compare the strength of answers.

Results

Ninety-one (91) useable surveys were completed by REEs in five Capacity Areas (Table 1). These 91 REEs represented 75% of the potential total number of REEs in these five capacity areas at the time of the survey. These REEs had worked in Extension an average of 14.6 years; the minimum was 0.25 years and the maximum was 34 years. They all had 100% Extension appointments.

Definition of Scholarship

When asked to provide open-ended comments about what came to their mind when thinking about scholarship as it related to their work, common themes were that it 1) is a research-based or discipline-based approach that grounds the foundation of our work, 2) is a focused area of study or research, 3) is a process (e.g. research, programmatic, teaching), 4) provides valued results (e.g. published work, public), and 5) is a field of study.

The REEs indicated that being valued by the intended audience was the most essential criteria for determining whether Extension work is scholarship (Table 2). The response average was significantly (p<0.05) higher than all other averages. However, other criteria also received high rankings: communicated to others, contributes to a body of knowledge, and creative intellectual work. Review by peers was the lowest ranked criteria. This lowest ranking is reinforced by the fact that when tested with a t-test, its average score (3.40) was significantly (p<0.05) lower than the other criteria's average scores.

Even though scholarship was not defined prior to or within the survey, the REEs overwhelmingly agreed with Boyer's (1990) classification of scholarship as discovery, integration, application, and teaching (Table 3).

Use of Scholarship in Extension Work

On average, REEs said that 29% of their work was currently dedicated to scholarship; the median was 20%. Not all capacity areas had similar levels of scholarship. However, they thought that 37% of their work should be dedicated to scholarship; the median was 25%. Fisher's exact test shows a strong relationship (p<0.0000) between the current percent of time dedicated to scholarship and the amount of time that these respondents felt should be dedicated to this endeavor (Table 4). Respondents who spent less than 30% of their time currently dedicated to scholarship were most strongly supportive of increasing their role in this area. For example, of the 27 REEs who indicated they currently dedicate 0-10% of their time to scholarship, 16 indicated they should increase their time on scholarship.

In terms of the role of scholarship within their Extension work, the statement with the highest response average was that REEs used others' scholarship in their work (Table 5). Being aware of scholarship in their field and sharing their scholarship with intended audiences were also frequently cited. The response average was significantly greater than "Some" application (p<0.001) for these three criteria. Contributing and participating in scholarship, sharing scholarship with peers, and, generating scholarship were less frequently cited by the REEs.

REEs were most strong in their belief that improving scholarship was important to the sustainability of Extension (Table 6). They overwhelming indicated that scholarship should be expected of all those with academic rank (i.e., Assistant Professor, Associate Professor, Professor) and of themselves. They were not as strong in their agreement that scholarship should be expected of people in local educator positions; the average response for this statement, while significant by itself, was significantly (p<0.05) lower than for other statements.

When asked through an open-ended question about the barriers that hinder their ability to increase their amount of scholarship, the following themes emerged from REE responses: 1) time constraints (i.e., too much paperwork and travel, would take away from program delivery), 2) lack of money (i.e., to attend professional meetings, to do the necessary research), and 3) lack of incentives, support, and direction (i.e., Extension culture does not reward scholarship, supervisor does not support scholarship, need practical guidance from supervisors). It is important to note that time constraints was the dominant theme depicting the types of barriers followed by the other concerns that may impede one's ability to increase levels of scholarship.

The Relationship of Scholarship to Performance Evaluation

The REEs selected several factors that should have significant or great influence on (or even dominate) their performance evaluation within Extension: program development, program evaluation, program management and delivery, scholarship, service to Extension committees and work teams, and service to field or discipline (Table 7). While scholarship was one of those factors, it was not the most important one noted. Program management and delivery received a higher response average and was significantly greater (p<0.001) than the average for scholarship. Program development was also considered more important than scholarship (p<0.05). The importance of scholarship was not significantly different from program evaluation and service to the field or discipline. Service to Extension committees and work committees and service to community had statistically equal scores (p<0.10). Revenue generation and seniority, years of service, or academic rank were not ranked highly by the REEs for influencing or impacting their performance evaluations.

Conclusions

Regional Extension Educators overwhelmingly agreed with statements about scholarship in each of the four categories described by Boyer (1990): discovery, integration, application, and teaching. This broad conceptualization of scholarship also meshed with themes that emerged from open-ended comments about what came to their mind when thinking about scholarship as it related to their work.

Even though scholarship was not formally defined in the survey or its introductory note, REEs thought they were engaged in scholarship although their level of engagement was not uniform across capacity areas. Although they were very strong in their belief that improving their scholarship was important to the sustainability of Extension, they did not think they should increase their scholarship work to the exclusion of other work. In fact, the importance of program management and delivery may be a barrier to increasing the amount of scholarship generated by REEs. An organizational challenge may lie in bridging program and scholarship in everyday work so that both areas receive adequate investment.

Furthermore, it is important to note that REEs indicated that time constraints, lack of money, and lack of organizational support and structure were other significant barriers. These are important considerations that may require further exploration in order to build a culture that supports Extension scholarship. Their most important factors for determining whether Extension work is scholarship are whether the work is valued by the intended audience and it contributes to a body of knowledge. These factors reflect the core values of outreach and research found in land-grant universities and provide a foundation for enhancing Extension's scholarly activity.

Interestingly, the REEs indicated that while it was important, scholarship was not the most important factor for influencing or impacting their performance evaluations. The most important factors were program management and delivery and program development. So even with the increased emphasis on scholarship, it was not seen as important as the long-established Extension activities of program management, delivery, and development.

Developing a shared understanding of scholarship through ongoing support by administration, developing and communicating a clear process of evaluating scholarly work, and aligning that effort with performance evaluation and demonstrating it as an important priority in performance evaluation are important first steps toward enhancing scholarly activity. Last, if Extension wants to increase the importance of scholarship in REEs' work and performance evaluations, these results show the need to spend considerable time building a culture that has greater support, removing barriers, and providing both monetary and non-monetary reward systems for scholarship.

References

Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Princeton, NJ: The Carnegie Foundation for the Advancement of Teaching.

Casey, C. H., Morse, G. W., & Markell, J. (2004). Strategic planning framing concepts. St. Paul, MN: University of Minnesota Extension Service. Available at: http://www.extension.umn.edu/jump/compact05/summary.html

Glassick, C. E., Huber, M. T., & Maeroff, G. I. (1997). Scholarship assessed: Evaluation of the professoriate. A Special Report to the Carnegie Foundation for the Advancement of Teaching. San Francisco, CA: Jossey-Bass Publishers.

Lynton, E. A. (1995). Making the case for the professional service. Washington DC: American Association for Higher Education.

Lynton, E. A., & Elman, S. E. (1987). New priorities for the University: Meeting society's needs for applied knowledge and competent individuals. San Francisco, CA: Jossey-Bass Publishers.

Rosner, B. (1995). Fundamentals of biostatistics. (4th ed.). Belmont, CA: Duxbury Press.

SAS Institute Inc, (c) 2002-2003. SAS 9.1, Cary, NC.

Survey Monkey. Available at: http://www.surveymonkey.com

University of Wisconsin-Extension Articles of Faculty Governance. Appendix I.B, Criteria for Faculty appointment and Promotion in UW-Extension. (2001). Retrieved March 20, 2006, from http://www1.uwex.edu/secretary/policies/section8/

University of Wisconsin-Madison, Council on Outreach. (1997). Commitment to the Wisconsin idea: A guide to documenting and evaluating excellence in outreach scholarship. Madison, WI: Office of Outreach Development, University of Wisconsin-Madison.

Weiser, C. H., & Houglum, L. (1998). Scholarship unbound for the 21st century. Journal of Extension [On-line], 36(4). Available at: http://www.joe.org/joe/1998august/a1.html.

Wise, G., Retzleff, D., & Reilly, K. (2002). Adapting scholarship reconsiders and scholarship assessed to evaluate University of Wisconsin-Extension outreach faculty for tenure and promotion. Journal of Higher Education Outreach and Engagement, 7(3):5-17.

Low Resources in a High Stakes Game: Identifying Viable Rural Community Partners

Susan M. Fritz
Associate Vice Chancellor
Associate Dean
College of Agricultural Sciences and Natural Resources
University of Nebraska-Lincoln
Lincoln, Nebraska
sfritz1@unl.edu

Amy E. Boren
Lecturer
Department of Agricultural Leadership, Education, and Communication
University of Nebraska-Lincoln
Lincoln, Nebraska
aboren2@unl.edu

Denise Trudeau
Assistant Professor
Department of Interdisciplinary Studies
Virginia Tech
Blacksburg, Virginia
dtrudeau@vt.edu

Daniel W. Wheeler
Professor and Head
Department of Agricultural Leadership, Education, and Communication
University of Nebraska-Lincoln
Lincoln, Nebraska
dwheeler1@unl.edu

Introduction

Higher education institutions are operating in an era of shrinking budgets (Acker, 2001). This fiscal austerity translates into challenges in adequately addressing institutional mission and demonstrating impacts. No place is that more of a challenge than in Cooperative Extension. Community needs can be considerable, and in some parts of the country, neglecting these needs can result in ruin. Across the nation, communities are disappearing as a result of the national trend of negative growth in rural counties (U.S. Census Bureau, 2000).

Regardless of these shifts in population, Cooperative Extension has a statewide programming mission to serve the educational needs of all citizens at all age levels. Unfortunately, limited resources require tough choices in programming. High-priority programs that produce the greatest impacts, and from an accountability standpoint, stand up to public scrutiny, are valued (Bogue, 1998). From a community leadership perspective, it is often difficult to respond to the myriad of community requests that are made of faculty. To compound the problem, it is often even more difficult to decide which of the potential community partners will benefit the most from an infusion of leadership programming.

How can theory be used by Extension faculty to help prioritize requests for community leadership development? This article proposes to address that very question by forging a link between community capital theory (Flora & Flora, 2004) and community survival indicators (Luther & Wall, 1988).

The Theoretical Framework

Linking theory to practice is an essential part of the land-grant mission. Thus, the work on community capitals by Flora and Flora (2004) was chosen for theoretical framework for the research reported here. In their work, Flora and Flora (2004) describe the different resources available within community and how these resources translate into capital for the community. Luther and Wall (1988) identify specific, community attributes that tend to indicate the viability of a particular community. Linking these two perspectives together may help to identify where the greatest programming impacts can be achieved for the greatest number of people.

Community Capitals

According to Flora and Flora (2004), there exist both tangible and intangible resources in every community, no matter how remote or impoverished. Expanding on the literature concerning these intangible and tangible capitals, Flora and Flora (2004) carefully assembled a comprehensive list of seven capitals that may be found in a community.

Intangible capitals consist of those unseen assets that community members possess, both individually and corporately. Human capital consists of the knowledge, skills, and abilities of individual community members and how those individual assets can be invested into the community as a whole. Cultural capital includes the general values and attitudes held by a community, including the way they tend to approach life in general. Political capital is generally thought of as the amount of power a community has to determine the availability of resources and influence the distribution of those resources. Social capital is comprised of the social networks and the amount of collaboration found among community members as well as between communities. A key component of social capital is mutual trust.

Tangible capitals are the visible assets that a community possesses. Financial capital primarily consists of money that is used for investment into the community rather than for individual consumption. An important part of financial capital is its ability to be translated into other assets such as built capital. Built capital is comprised of the assets that have been constructed in and around the community. Roads, bridges, public services, and buildings are all part of a community's built capital. This provides a foundation for community development and growth. Natural capital includes the natural resources found in and around a community: landscape, water, flora, and fauna all are part of a community's natural capital.

Community Survival Indicators

In 1988, Luther and Wall published the results of their research into the economic trends, quality of life, kind of leadership, and future plans of 18 communities across 14 states, from Texas to North Dakota and Ohio to California. After careful analysis, patterns of characteristics emerged from their case studies of these towns (Luther & Wall, 1988). These patterns of characteristics indicated that certain community traits tend to be found in successful, vital towns, such as a willingness to invest in the future (Luther & Wall, 1988). The discovery of these patterns of characteristics led to their compilation in a list of 20 Clues to Rural Community Survival. Figure 1 lists the 20 clues, or community survival indicators, in numerical order. These indicators of community survival provide helpful signs of community viability that can be used in a subjective manner to profile a community.

Purpose and Methods

Purpose

The seven community capitals and the 20 community survival indicators provide ways of examining a community to determine its potential for survival and for growth. Community capital theory (Flora & Flora, 2004) provides broad descriptions of the various forms of capital that a community may possess. Community survival indicators (Luther & Wall, 1988) provide specific signs of community potential for viability. Integrating the community capitals and community survival indicators could provide a theory-based guide to assist Extension faculty in determining where to invest their limited resources for a maximum return. Thus, the purpose of the research reported here was to integrate the community capitals with community survival indicators to create a guide to help determine the most viable community partners.

Integration by Graduate Panel

Fifteen leadership education graduate students volunteered to participate in a group exercise to integrate community capital theory (Flora & Flora, 2004) and community survival indicators (Luther & Wall, 1988). First, the students reviewed descriptions of the community capitals (Flora & Flora, 2004) and the community survival indicators (Luther & Wall, 1988). The students were then led through a group process to categorize the 20 indicators of community survival under the seven community capitals. Because of the broad application of some of the clues, participants were permitted to categorize the clues under more than one capital. Last, through the use of brainstorming, the students identified specific examples of the community survival indicators that are common to most rural communities.

Results of Graduate Panel

Table 1 reports the results of integrating the seven community capitals and the 20 community survival indicators. Several of the indicators were listed twice, and one ("Inclusive culture where women are seen in leadership roles") was listed three times. Nineteen community survival indicators were listed under the intangible capitals, and 10 were listed under the tangible capitals. Table 2 reports the results of the brainstorming session to identify specific community examples of the community survival indicators. One hundred and eleven examples were listed for the 20 community survival indicators, or more than five examples, on average, for each indicator.

Validation by Expert Panel

The results of the graduate panel were presented at the 2005 Conference of the Association of Leadership Educators (ALE). Seventeen participants were presented with the results of the panel of graduate students. These participants were asked to review the results and make any additions or changes they deemed necessary. The results were collected and reviewed. One addition was made ("Community members volunteer for fire department."), but no other changes or additions were made (see Table 3). These results were then compiled and sent back to the participants for validation. Seven participants responded affirmatively. The other participants did not respond.

Conclusions and Recommendations

It appears that the community survival indicators are highly concentrated in the intangible community capitals, including social, cultural, human, and political capital. This may be good news to Extension faculty working in communities, as these intangible capitals rely so much on the human component of a community and can be maximized with cooperation of community residents. In the development of strong, viable communities, it can be easy to focus solely on the tangible capitals. Our research indicates that it is the intangibles that matter most. It is important to issue a caveat, however, about minimizing the importance of tangible capitals for community viability. Certainly, future research is needed to determine the relative importance of one category (intangible, tangible) to the other in predicting community survival.

We believe that the integration of community capitals with community survival indicators has resulted in a concrete, less subjective guide that can assist those who are trying to make rural community partner decisions. The decision to choose one community over another is a difficult one at best, and any help in facilitating this process is welcome. The guide provides some specific examples of how the indicators of rural community survival might look to an external evaluator.

When attempting to determine where scant resources should be invested, Extension faculty may wish to consult the guide and see what kinds of indicators for survival are in evidence in the communities that are seeking assistance. In addition, we believe there is potential for sharing the guide with community leaders as a means of auditing their community's health and potential. This could help communities to take their own inventory and begin to maximize their potential for viability.

References

Acker, D. (2001). Budget cutbacks: Some strategies for deans, directors, and the staff they lead. Journal of Extension [On-line], 39(2). Available at: http://www.joe.org/joe/2001april/comm1.html

Ayres, J., Leistritz, L., & Stone, K. (1992). Rural retail business survival: Implications for community developers. Journal of the Community Development Society, 23(2), 11 — 21.

Bogue, E. G. (1998). Quality assurance in higher education: The evolution of system and design ideals. New Directions for Institutional Research, 99, 7-12.

Flora, C. B., & Flora, J. A. (2004). Rural communities: Legacy and change (2nd ed.). Boulder, CO: Westview Press.

Luther, V., & Wall, M. (1988). 20 clues to rural community survival: A community case study project. Lincoln, NE: Heartland Center for Leadership Development.

U. S. Census Bureau. (2000). State & County QuickFacts. Retrieved February 26, 2005 at http://www.census.gov/main/www.cen2000.html

Youth Perceptions of Ohio 4-H

Greg Homan
Extension Educator
Van Wert County
Van Wert, Ohio
homan.14@osu.edu

Jeff Dick
Extension Educator
Williams County
Bryan, Ohio
dick.7@osu.edu

Jason Hedrick
Extension Educator
Ohio State University Extension, Putnam County
Ottawa, Ohio
hedrick.10@osu.edu

Ohio State University Extension

Introduction

Heinsohn and Lewis (1995) report, ". . . at any given time, participation in 4-H, Scouts, and other youth organizations is skewed with 9 to 11 year-olds comprising over half of the participants." They go on to state, "A look at early adolescence tells us youth leaving these programs to do something else is a part of the developmental process rather than a programming glitch." "They want to pursue interests and activities of their own, not their parents' choosing. Also there are many more activities for teens to choose from, many of which they can access themselves."

According to Thompson (1998), "The three reasons non re-enrollees ranked as most important in their decision to not re-enroll were (1) they were too busy; (2) other activities were more important; and (3) they did not have enough time for 4-H activities." The researcher concluded that it is not how many activities teens are involved with, but how important 4-H is to them in comparison to the other activities that determines whether they remain in 4-H." Thompson (1998) reports "Ohio 4-H has had little problem attracting preteen 4-H members to the program, but has experienced difficulty retaining the members through the teen years." Thompson (1998), citing a study by Nichols (1973), reported that "members with high participation levels were less likely to drop out and that participation levels were inversely related to their age at initial enrollment." Thompson also cites Beasley (1980), stating, "Peer influence is an important factor in recruitment and retention." In Leeds' (1997) study of 4-H members in Union County, Ohio, she found "The high school age participants expressed frustration that 4-H sometimes felt as though it was focused toward younger members."

The purpose of the study reported here was to explore the perceptions youth report about 4-H.

Methods and Procedures

The descriptive and correlation study was conducted to assess youth perceptions of 4-H. Nine cooperating schools, located in five northwest Ohio counties, were chosen by the researchers. These include: Crestview Local Schools, Coldwater Exempted Village Schools, Delphos St. Johns Parochial Schools, Miller City Local Schools, Edgerton Local Schools, Fort Jennings Local Schools, Mill Creek West Unity Schools, Montpelier Exempted Village Schools, and Wayne Trace Local Schools. Three written questionnaires were designed and tailored for past 4-H members, current 4-H members, and those who have never joined 4-H. The instruments were designed to be short and cover multiple aspects of 4-H. Five related questions were evaluated using Cronbach's alpha with a reliability coefficient of .83 to provide a test of reliability.

This research was reviewed and accepted by the Human Subjects Review Board at The Ohio State University. Written parental permission was obtained for participants who took part in the study. Anonymity and confidentiality of participants and their individual responses were maintained throughout the project. The researchers administered the instruments in the spring of 2005 to the participating schools.

Youth in grades 4, 7, and 10 were invited to participate in the study, with 1,462 students providing usable data from the nine cooperating schools. Five-point anchored Likert-type questions were developed measuring levels of agreement (from "Strongly Disagree" to "Strongly Agree"). Questions were analyzed using Kruskal Wallis tests to determine significant differences in sample responses based on group identifiers. Pearson correlations were used to determine interrelation between various components of the research.

Research questions included:

1. Is there a difference in perception of 4-H among youth who are currently enrolled in 4-H, those who were former members of 4-H (but left the organization), and those who never enrolled in 4-H?


2. Is there a difference in perception of 4-H among 4th, 7th, and 10th grade students?

Results

Difference in Perception Based on 4-H Enrollment

1. Is there a difference in perception of 4-H among youth who are currently enrolled in 4-H, those who were former members of 4-H (but left the organization), and those who never enrolled in 4-H?

When evaluating the perception of 4-H perceived by youth, a significant difference was found (Table 1) indicating that youth who are members of 4-H or were former members of 4-H are more likely to agree that 4-H is "fun" and "cool," and less likely to agree that 4-H is "boring (p<.01)."

Difference in Perception Based on Grade

2. Is there a difference in perception of 4-H among 4th, 7th, and 10th grade students?

A significant difference was found in the perceptions of 4-H among youth in the 4th, 7th, and 10th grades (p<.01). The older the youth, the less favorable they viewed Ohio 4-H (Table 2).

Difference in Perception Based on Age

When evaluating the likelihood of continued involvement in 4-H and the level of perceived encouragement from parents and friends, there was a significant difference based on age (p<.01). Older youth were less likely to agree that they intend to stay in 4-H, that their parents want them in 4-H, or that their friends want them in 4-H (p<.01) (Table 3).

Summary

• Youth who are currently involved in 4-H perceive the organization more favorable than youth who have never been involved in 4-H (p<.01). 4-H members agree more strongly that 4-H is "fun" and "cool," and are less likely to agree that 4-H is "boring".


• Older youth are less likely to find 4-H as appealing (p<.01). As youth age, they are less likely to agree that 4-H is "fun" and "cool," and are more likely to agree that 4-H is "boring".


• Older youth are less likely to report that they intend to remain involved in 4-H and also indicate that their parents and friends are less likely to encourage them to remain involved in 4-H (p<.01). There is a significant decrease in the level of agreement to statements such as "I will stay in 4-H," "My Parents want me in 4-H," and "My friends want me in 4-H" when comparing 4th, 7th, and 10th grade students.

Discussion

Youth have a variety of activity choices from which to select. It is important to listen to youth perceptions of 4-H if it is to remain successful in meeting the needs of diverse youth. We need to critically evaluate 4-H programs to make sure that they are attractive to youth. Youth will gravitate to those activities that they perceive as "fun," "cool," and of interest to them. Those who have experience with 4-H (members and even past members that left the organization) believe 4-H is more attractive than those that were never a member.

The research reported here indicates that there is a significant difference in the perceptions of Ohio 4-H based on age. Older youth are less likely to indicate that they find the program attractive and are more likely to leave the 4-H program.

References

Davis, J. A. (1971). Elementary survey analysis. Englewood, New Jersey: Prentice-Hall.

Heinsohn, A., & Lewis, R. (1995). Why do teens drop out?: A developmental view. Journal of Extension [On-line], 33(1). Available at: http://www.joe.org/joe/1995february/comm1.html

Leeds, C. F. (1997). Perceptions of union county 4-H members about the 4-H program. Thesis, The Ohio State University.

Thompson, P.L. (1998). Factors related to the retention of Ohio teen 4-H members. Thesis, The Ohio State University.

Ultrasound Technology Helps Youth Raise Industry-Acceptable Market Animals

Scott A. Nash
Extension Educator, Youth Development
Bingham County
Blackfoot, Idaho
snash@uidaho.edu

University of Idaho

Introduction

4-H animal projects have always provided youth with an opportunity to raise market animals that end up in the food chain. Through the 4-H program, youth develop and enhance life skills such as goal setting, responsibility, record keeping, and cooperation as well as build self-esteem. The popularity of animal projects continues to grow and has spread to many non-agriculturally based families.

Because of the growth of the project, it became apparent all participants lacked knowledge. This was evidenced after the 1995 Eastern Idaho State Fair when the steers were harvested--a USDA beef grader predicted that 23% of the market steers exhibited at the state fair would grade choice or better. Up to that point in time, data were only available on the steers that went to the packing plant located over 150 miles away. Youth were not able to travel to the plant to view the carcasses from their animals. There were no carcass data available on the market hogs and market lambs. The lack of available carcass information meant a lack of educational opportunities for 4-H exhibitors.

The lack of available carcass information and the low quality of animals exhibited at Idaho fairs was a concern to 4-H volunteers. Market animal fair committees in southeastern Idaho counties had been introduced to the use of ultrasound prior to 1995. They were excited about the possibility of gaining carcass information and saw it as an educational tool to teach participants.

The use of ultrasound as a tool to estimate composition of live animals was introduced to the livestock industry in the 1950's (Price, Pfost, Pearson, & Hall, 1958). Subsequent improvement in ultrasound technology has allowed for 90% accuracy when predicting 12th rib back fat in beef cattle (Brethour, 1992) and 82% accuracy when estimating ribeye area (REA) (Perkins, Green, & Hamlin, 1992). More studies indicate that correlations between ultrasound estimates of rib and rump fat thickness in beef cattle and their subsequent carcass measurements range from 0.57 to the low 0.90s. Correlations between ultrasound predictions of beef ribeye area and carcass REA measurements range from 0.43 (Smith, Oljen, Dolzeal, Gill, & Behrens 1992) to 0.83 (Robinson, McDonald, Hammond, & Turner, 1992).

Computer software has become available for predicting percent intramuscular fat (IMF) (marbling) from real-time ultrasound scans. Brethour (1992) reported a correlation of 0.77 between ultrasound predicted IMF and carcass marbling score. A 1998 Iowa State University Beef Research report listed correlations between ultrasound predicted IMF and carcass marbling scores ranging from 0.40 to 0.80, where 0.70 is fairly common. A study conducted by Nash, Harrison, Packham, Panting, and Duckett at the University of Idaho in 2000 to monitor changes in beef IMF over time indicated an ultrasound predicted IMF accuracy of 82% when compared to carcass measures of marbling.

The accuracy of ultrasound estimates of the 10th rib backfat and loin-eye area in swine has been reported at 83% and 12th rib fat in sheep at 63% (Houghton & Turlington, 1992). Ultrasound estimated ribeye area in sheep was reported to be 82% accurate by Panting, et al., in 2000. Duckett and Klein conducted a study in 1997 to compare the accuracy between trained visual evaluators' estimates of carcass traits in swine and ultrasound predictions of the same traits. The study found an R² value of 0.39 when visual estimates of carcass traits by trained swine evaluators were compared to actual carcass data and an R² value of 0.62 when ultrasound estimates of carcass traits were compared to actual carcass data. The findings in this study indicate that ultrasound values are more accurate than visual estimates by trained evaluators. The same study determined that ultrasound predictions of swine carcass traits, hanging carcass measurements and standing carcass measurements were the same (p <.05) (Duckett & Klein, 1997).

Today's purebred swine producers rely on ultrasound data to estimate breeding values on their animals (Moeller, 2002). According to the National Centralized Ultrasound Processing Lab (CUP), data on over 200,000 head of cattle are processed annually through the lab (2005). The CUP lab also reported that 24 beef cattle breed associations use the ultrasound data to develop carcass Expected Progeny Differences (EPDs) for use in seed stock selection.

In 1996 the Eastern Idaho State Fair (EISF) market animal committee had the opportunity to use ultrasound and decided to implement the technology to predict carcass measures on the market steers exhibited at the fair. According to ultrasound estimates, less than 28% of the steers exhibited at the 1996 EISF had enough percent IMF to qualify for the USDA Choice quality grade. This percentage is well below industry average. Also in 1996, the market hogs were scanned in Caribou County (a small southeast Idaho county) and found to have less than 50% fat free lean, which is also below industry average. Starting in 1999 and continuing through 2006, in addition to the market steers, all of the market hogs and market lambs were scanned at EISF.

Materials and Methods

Four University of Idaho Extension educators wrote grants and received funds from the Idaho Beef Council to attend training and certification in ultrasound technology. Once trained, the educators implemented an educational program using ultrasound technology to estimate carcass measurements of the market animals exhibited at the Eastern Idaho State Fair.

Educational workshops were also developed to reach youth and adults throughout southeastern Idaho. At the workshops, market steers, lambs, and hogs were scanned. Workshop participants were then educated about the carcass estimates, what they meant and how the market animals fit USDA specifications. Educators taught over 500 youth and adults about current USDA meat animal carcass specifications and industry standards. Workshops were also held to teach proper animal selection, care, and nutrition. The majority of workshop participants exhibited market animals at county fairs in southeast Idaho with 25% of them exhibiting market animals at EISF.

Ultrasound technology was then implemented as an evaluation tool on market steers, lambs and hogs at six county fairs in southeast Idaho and at the 1999 EISF. During weigh-in at the fair, each 4-H animal was ultrasounded by a trained and certified technician. The steers were scanned in a beef cattle chute, while hogs were scanned in a swine ultrasound chute, and sheep exhibitors held their lambs like they were exhibiting them in the show ring. Vegetable oil was poured over the animals' backs between the 12th and 13th rib on steers and lambs, and between the 10th and 11th rib on hogs. The ultrasound technician located the proper image of each animal's ribeye/loin-eye using a transducer, then froze a cross-sectional image on the ultrasound screen and traced the image using electronic calipers. A horizontal image was taken across the 11th, 12th and 13th ribs of steers to determine the percentage of IMF (marbling). Values were entered into a computer program from three independent images to calculate the percentage of IMF.

Each youth received a picture of his or her animal's ribeye/loin-eye area and backfat thickness. Steer exhibitors also received the percentage of IMF in their animals' ribeyes. Youth were then able to determine how their animals compared to industry standards. Adult volunteers and fair boards implemented a carcass contest using ultrasound data to determine the top carcass animals. The EISF junior livestock committee provided market animal judges with ultrasound information to use as a tool when evaluating the animals. Sponsors provided cash awards for the exhibitors of the top three ultrasound carcass animals in each species. Youth were rewarded for raising animals that fit industry standards.

Results

Data collected from 632 market hogs indicate the average hog's loin-eye area was 6.58 inches² in 1999 but increased 17% to 7.72 inches² in 2006 (Figure 1). At the same time, backfat decreased 27% from 0.84 inches in 1999 to 0.61 inches in 2006. During the same period, the percent lean increased from just under 50% to 54.38%. Percent lean is based on the muscle-to-fat ratio. These data indicate that swine have become leaner and more muscular.

Figure 1.
Swine Loin-eye Area

Data collected at the Eastern Idaho State Fair Junior Beef Show on 206 steers indicate that the percentage of steers with enough IMF to reach the USDA Choice grade improved from 28% in 1996 to 67% in 2006 (Figure 2), which is an increase of 130%. Quality grade is based upon the amount of marbling or flecks of fat in the muscle. More marbling in the muscle means a higher percentage of IMF and thus a higher quality grade. A higher percentage of IMF should also correlate with better eating quality of the meat.

Figure 2.
Percent Steers Grading Choice

Data collected from 947 market lambs at southeast Idaho fairs shows an increase in ribeye area while maintaining an industry-acceptable fat thickness. An increase in ribeye area means a bigger "lamb chop."

In 1999, the average ribeye area for lambs was 2.71 inches² and fat thickness was 0.17 inches. In 2006, the average ribeye area for lambs was 3.11 inches² (Figure 3) with a fat thickness of 0.20 inches. The 14.7% increase in muscle with an acceptable fat thickness provides a more industry-preferred product.

Figure 3.
Lamb Ribeye Area

4-H youth and volunteer leaders have utilized ultrasound information to aid in their animal selection and management practices, which has led to an increase in animal quality. Youth participants have voiced support for the use of ultrasound technology. One 4-H member said, "Now I can look at my pig and tell if he's too fat. Before we used ultrasound, I didn't know the difference and my pig was just a pig." Another youth added, "When my animal meets industry standards, I know I did my best." A third youth shared:

I have learned to look at animals that have the potential to meet industry-acceptable standards. When I pick out my steer for the next year, I am better prepared to pick a steer that will meet the standards and make the buyer happy.

Over $1,000 in cash awards and prizes has been donated by sponsors for exhibitors of ultrasound carcass award winners at EISF, indicating community support for the use of the technology. Buyers at the EISF 4-H livestock auction are now using ultrasound data to identify animals with more muscle, more IMF, and less backfat. In 1996, 60% of the hogs and 22% of the steers were purchased for personal use; however, in 2006, 100% of the hogs and 60% of the steers were purchased for personal use.

Conclusions and Recommendations

The use of technology continues to increase and serve a valuable role in our society. Ultrasound provides a state-of-the-art approach to evaluating meat animals. Today's farmers and ranchers producing 4-H animals are using ultrasound information for the selection of their seed stock. Youth who raise 4-H animal projects are stewards of animal agriculture because the animals they produce end up in the food chain.

Through the 4-H program, youth develop and enhance life skills such as goal setting, responsibility, record keeping, and cooperation as well as build self-esteem. These skills are learned by doing. Introducing ultrasound technology as an evaluation tool allows youth to increase their knowledge about the quality of the animals they raise. Today's youth are not intimidated by the use of this so called "new technology." As technology continues to be a part of everyday life, it is important to use it as a tool to enhance the education of 4-H participants.

References

Brethour, J. R. (1992). The repeatability and accuracy of ultrasound in measuring backfat in cattle. Journal of Animal Science, 70:1039.

Centralized Ultrasound Processing Annual Progress Report. (2005). The National CUP Lab and Technology Center. Ames, IA.

Duckett, S. K., & Klein, T. A. (1997). Ultrasound: A tool for evaluating carcass quality in live animals. University of Idaho Department of Animal and Veterinary Science Research Brief. University of Idaho, Moscow, ID.

Houghton, P. L., & Turlington, L. M. (1992). Application of ultrasound for feeding and finishing animals. A review. Journal of Animal Science, 70:930-941.

Iowa State University Beef Research Report. (1998). A.S. Leaflet R1529. Iowa State University, Ames, IA.

Moeller, S. J. (2002). Evolution and use of ultrasonic technology in the swine industry. Journal of Animal Science, 80 (E. Suppl. 2):E19-E27.

Nash, S. A., Harrison, S. N., Packham, J. H., Panting, R. R., & Duckett, S. K. (2000). Monitoring changes in carcass quality across time-on-feed using real-time ultrasound to optimize endpoints. Case study. The Professional Animal Scientist, 16:202-205.

Panting, R. R., Harrison, S. N., Jensen, J. C., Nash, S. A., Packham, J. H., Whittier, D., & Duckett, S. K. (2000). Utilizing real-time ultrasound to predict carcass quality of lambs. Journal of Animal Science, 78 (W. Suppl. 1):W3 05.

Perkins, T. L., Green, R. D., & Hamlin, K. E. (1992a). Evaluation of ultrasonic estimates of carcass fat thickness and longissimus muscle area in beef cattle. Journal of Animal Science, 70:1002-1010.

Price, J. F., Pfost, H. B., Pearson, A. M., & Hall, C. W. (1958). Some observation on the use of ultrasound measurements for determining fatness and leanness in live animals. Journal of Animal Science, 17:1156 (Abs.).

Robinson, D. L., McDonald, C. A., Hammond, K. & Turner, J.W. (1992). Live animal measurement of carcass traits by ultrasound: Assessment and accuracy of sonographers. Journal of Animal Science, 70:1667-1676.

Smith, M.T., Oljen, J.W., Dolzeal, H. C., Gill, D. R., & Behrens, B. D. (1992). Evaluation of ultrasound for prediction of carcass fat thickness and longissimus muscle area in feedlot steers. Journal of Animal Science, 70:29-37.

Knowledge and Behavior Improvement Through a Skin Cancer Action Approach Exhibit

Nedra K. Christensen
Professor, Extension Specialist
Utah State University
Salt Lake City, Utah
nedrac@ext.usu.edu

D. Pauline Williams
Clinical Nutrition Manager
Primary Children's Medical Center
Salt Lake City, Utah
pauline.williams@intermountainmail.org

Roxanne Pfister
Data Manager - Statistics, Epidemiology Center
Utah State University
Logan, Utah
roxane@cc.usu.edu

Mike Pace
Associate Extension Professor
Utah State University
Brigham City, Utah
mikep@ext.usu.edu

Matt Palmer
Associate Extension Professor
Utah State University
Ephraim, Utah
mattp@ext.usu.edu

Introduction

Skin cancer (both melanoma and non-melanoma types) is now the most common form of cancer in the United States according to Harris and Alberts (2004). "Nearly one million new cases are reported each year, which is estimated to be one in six Americans who will develop skin cancer in their lifetime" (Diepgen, 2002). The risk of developing skin cancer is increased by exposure to excessive amounts of total time in the sun and from frequent or severe sunburns. The amount of time farmers and other agriculturalists spend outside increases their risk for skin cancer. Primary preventative measures include wearing protective clothing, using sunscreen with an appropriate sun protection factor, wearing a hat, and avoiding the sun by seeking shade (Stanton, 2004).

The purpose of the study reported here was to change sun exposure behaviors in agriculturalists through a skin cancer action approach exhibit. Educational conversations, skin cancer brochures, sunscreen, and wide-brimmed hats were provided at agriculture conferences (Farm Bureau, Cattlemen, Wool Growers, Grazing, and Extension Service). An improvement in sun safe behavior and a decrease in skin cancer were expected. The project design was patterned after similar hat trade programs from various Extension services, including Wisconsin, Iowa, Minnesota, and Indiana (Burwell, 2004).

Objectives/Purpose

The purposes of the study were to:

1. Decrease unprotected UV exposure by increasing use of wide-brimmed hats, protective clothing, and sunscreen.


2. Increase knowledge of skin cancer risks through action learning techniques.


3. Determine related factors associated with safe sun behaviors as assessed from a self reported questionnaire.

Methods

Subjects

Participants attending agricultural conferences were recruited to participate in the study. The incentives of a tightly woven wide-brimmed hat, sunscreen with a SPF rating of 15 or higher, and educational materials were presented in an exhibit style at the Utah Grazing Conference, Utah Farm Bureau Conference, Utah Cattlemen and Wool Growers meetings, Utah Farmers Union, and various county Extension programs.

Demographic analysis showed 56.1% of the participants were male and 43.9% female. Four percent were under age 20; 20.4% age 21-35; 25.4% age 36-50; 38% age 51-65; and 11.9% age 66 and above. The majority of subjects, 56.1%, were from rural areas, 29.4% from suburban areas, and 14.5% from urban areas.

Funding Support

Utah State University Extension awarded a $10,600 competitive grant to the Trade your Hat--Sun and Skin Cancer Team for a skin cancer awareness exhibit and hat exchange for a 2-year period. The funds were used to create a Trade Your Hat exhibit, purchase sun-safe hats, and create a skin cancer survey. In addition, the Utah State Health Department donated sunscreen samples and skin cancer awareness and prevention brochures.

Design

The Trade Your Hat program was designed to educate participants in an exhibit style format using written materials, brief conversation with Extension personnel, and action learning. The use of written materials and narrative approaches, such as conversations, has been shown to improve health related behaviors (Udermann, 2004; Slater, 2003). Action learning, developed in the 1940's, helps "real people resolv[e] and tak[e] action on real problems in real time and learn while doing so" (Marquardt, 2004). The components of action learning include:

• A problem, project, or challenge;


• Questioning and reflection about the problem;


• Taking action on the problem; and


• Committing to change.

The Trade Your Hat program used action learning to address the problem of skin cancer in agriculturalists. The exhibit based learning provided the opportunity for participants to question and reflect on skin cancer through discussion with Extension agents and reading brochures. Distribution of wide-brimmed hats and sunscreen with a rating of SPF 15 or higher allowed the participants to take action in preventing skin cancer. Use of pre and post surveys encouraged commitment to change behaviors over time.

Participants were asked to trade in their "unsafe" hat (such as a baseball cap) that did not protect the ears or neck and fill out a pre-survey in exchange for a wide-brimmed hat, sunscreen, and educational brochure. A total of 720 hats, sunscreen, and brochures were distributed. After 250 pre-surveys were distributed, the hats, sunscreen, and educational materials were given without requiring a survey to be completed.

The surveys contained five questions asking about personal sun behaviors and three questions regarding personal skin cancer health history. The participants were also asked to identify whether twelve genetic or behavior factors would place a person at high risk for skin cancer. This question was scored as a knowledge test. Participants were then asked for a self-report of which of the twelve factors characterized them personally. Demographic questions regarding age, gender, occupation, and type of residence (urban, suburban, or rural) were also asked.

Participants completed pre-surveys at the Trade Your Hat exhibits. Post surveys, with the same questions, were mailed 3 months later.

• 250 pre-surveys were completed.


• 221 pre-surveys had complete address information to send post-surveys.


• 145 post-surveys were returned, for a 65% return rate.

The pre- and post-surveys were approved through the Utah State University Institutional Review Board (IRB) process, and participants were required to sign a consent form.

Data Analysis

Paired t-tests were calculated for pre- to post-surveys. Questions on knowledge of skin cancer risk factors and actual sun behaviors were analyzed. Behavior questions were based on a Likert scale of 1-5 (1 being never practice this behavior and 5 being daily practice of behavior). Correlations were calculated between the amount of time spent in the sun and wearing a wide-brimmed hat, a baseball cap, sunglasses, sun-protective clothing, and using sunscreen with a SPF rating of 15 or higher when outside. In addition, the perceived risk of developing skin cancer was correlated to the same variables.

Results

Sun Exposure Practices Prior to Exhibit

Many participants, 46.9%, had long-term daily exposure to the sun between 10 a.m. and 3 p.m., as was to be expected with agriculturalists. Time spent outdoors was significantly correlated to the self-reported prevalence of skin cancer and precancerous lesions (r=-0.178, p=0.008). Use of SPF 15 sunscreen was significantly correlated with use of wide-brimmed hats (r=0.168, p=0.012), baseball caps (r=-0.195, p=0.004), and sunglasses (r=0.167, p=0.012).

Prior to the exhibit the percentage of participants reporting behaviors showed:

• 33.2% never wore a wide-brimmed hat outside,


• 27.4% rarely wore a wide-brimmed hat outside,


• 23.6% wore baseball caps daily,


• 32.7% wore sunglasses daily,


• 13.4% used sunscreen with a rating of SPF 15 or higher daily,


• 16.4% used SPF 15 sunscreen often, and


• 70.2% rarely or never used SPF 15 sunscreen.

The participants with a self-perceived risk for skin cancer portrayed better sun-safe behaviors. Perceived risk for skin cancer was significantly correlated with use of SPF 15 sunscreen (r=-0.293, p=0.000), frequency of regular checkups for skin cancer (r=0.260, p=0.000), and an overall lower prevalence of skin cancer or precancerous lesions (r=0.256, p=0.000).

Behavior Changes Post Exhibit

Paired t-tests were used to compare subjects' behavior at the time of the pre- and post-surveys to determine if education would change behavior. The behaviors examined were time spent outdoors, use of wide-brimmed hats, baseball caps, sunglasses, protective clothing, and sunscreen. The use of a full wide-brimmed hat (p=0.000) and use of protective clothing (tight weave fabrics, long-sleeved shirts, pants, etc.) when outside (p=0.000) significantly increased. There was a trend toward decreasing the use of baseball caps (p=0.054). The frequency of sunscreen use did not increase. (Figure 1 shows participants' behavior at the time of the pre-survey and at the time of the post-survey using paired samples.)

Figure 1.
Participants' Behaviors at Time of Pre- and Post-Surveys


Likert scale , 1 = never, 5 = daily. *significant at p = 0.000, ** p=0.054, ***p=0.069

Correlation studies were done to further compare behavior. Use of SPF 15 sunscreen at the time of the pre-survey was correlated to lack of skin cancer lesions at (r=-0.137, p=0.042), and perceived risk for skin cancer (r=-0.293, p=0.000). The use of protective clothing when outside was also significantly correlated (r=-0.293, p=0.008) with lack of skin cancer or precancerous lesions.

Knowledge Changes Post Exhibit

Knowledge scores were correlated with factors placing a person at risk for skin cancer. Paired t tests were used to compare the pre- and post-skin cancer knowledge of subjects. Overall knowledge of risk factors significantly improved from 8.7 ± 2.04 to 9.1 ± 1.82 (p=.014) from a total possible correct of 12. Specific knowledge changes are listed in Table 1. There was not a significant difference in survey results for geographic residence (rural vs. urban), gender, or age.

Discussion

Summary

Approximately 80% of skin cancers occur in locations on the body frequently exposed to the sun (Diepgen, 2002). Harris (2004) stated that limiting unprotected UV exposure is the primary preventative measure for skin cancer. Exhibit style programs using brochures, brief conversations, and action learning can be effective in limiting unprotected UV exposure.

The results of the study reported here were consistent with a similar study done by Stanton, Janda, Baade, and Anderson (2004), which also found a positive correlation between perceived risk of skin cancer and improvement in certain sun-safe behaviors. Participants who viewed themselves at high risk for skin cancer showed better sun-safe behaviors, such as sunscreen use and regular medical checkups.

Improvement in knowledge regarding risk for skin cancer and many sun exposure practices were the result of the study. Behaviors that showed significant improvement were an increased use of a full wide-brimmed hat, protective clothing, and sunglasses. There was a trend toward decreasing the sole use of baseball caps. There was no significant change in time involved in outdoor activities/work, yet this was expected as we were targeting agriculturalists that are required to be outside.

Limitations

Increased use of a wide-brimmed hat, for participants, was probably due in large part to the provision of the hat (the swapping of an unsafe hat for a safe one) at the exhibit. The authors recognize that funding for hats may not be possible in all community programs.

Conclusions

Community based skin cancer awareness programs, presented by Extension Services, can improve sun exposure behaviors and overall knowledge of skin cancer risk factors. Possible Extension programs could include:

• Sun safe brochures or handouts provided at livestock, grazing, 4-H, or other meetings,


• Articles in Extension newsletters providing information on sun safe behaviors such as wearing wide-brimmed hats, sunscreen, and long-sleeved shirts, and


• Application for grants or solicitation of donors to provide wide-brimmed hats for a Trade Your Hat event.

Our results showed an increased use of wide-brimmed hats and protective clothing after participating in an educational skin-cancer exhibit. Educating the public on risk factors for skin cancer and sun-safe behaviors can decrease the risk and prevalence of skin cancer.

References

Burwell, C. E. (2004). Agricultural community is aware of skin cancer risks. Journal of Extension [On-line], 42(2). Available at: http://www.joe.org/joe/2004april/rb8.shtml

Diepgen, T. L., & Mahler, V. (2002). The epidemiology of skin cancer. Br J Dermatol, 146(S61):1-6.

Harris, R., & Alberts, D. (2004). Strategies for skin cancer prevention. Int J Dermatol, 43:243-251.

Marquardt, M. (2004). Harnessing the power of action learning. Training and Development, 58:26-32.

Slater, M. D., Buller, D. B., Water, E., Archibeque, M., LeBlanc M. (2003). A test of conversational and testimonial messages versus didactic presentations of nutrition information. J Nutr Educ Behav, 35:255-259.

Stanton, W., Janda, M., Baade, P., & Anderson, P. (2004). Primary prevention of skin cancer: A review of sun protection in Australia and internationally. Health Promotion International, 19(3):369-78.

Udermann, B. E., Spratt, K. F., Donelson, R. G., Mayer, J., Graves, J. E., Tillotson, J. (2004). Can a patient educational book change behavior and pain in chronic low back pain? The Spine Journal, 4:425-435.

Forest Certification and Nonindustrial Private Forest Landowners: Who Will Consider Certifying and Why?

David C. Mercker
Extension Forester
The University of Tennessee
Jackson, Tennessee
dcmercker@utk.edu

Donald G. Hodges
Professor, Forest Economics
The University of Tennessee
Knoxville, Tennessee
dhodges2@utk.edu

Introduction

Most consumers are vaguely familiar with the concept of an objective third party certifying products to assure a high standard, or consistency, in product quality. The certification label that is affixed to electrical appliances by the Underwriters Laboratory, thereby assuring that appliances meet or exceed standards of quality and safety, is an example (Maser & Smith, 2001). The USDA Certified Organic label associated with certain fruits and vegetables at grocery stores is another, as are Quality Beef and Quality Pork Assurance Programs. Certification has evolved in a number of industrial sectors including automobiles, chemicals, footwear, apparel, and fisheries (Sasser, 2001).

Forest Certification is a relatively new development and deals not with the final product, but with the practice of forestry, growth of the product, harvesting of the product, and ecological impacts associated with harvesting of the product (Klingberg, 2003). There were few calls for certifying forests until the mid-to-late 1990s. Forest certification now is gaining widespread attention by a variety of stakeholders, including environmentalist, policy makers, professional foresters, social activists, loggers, and the public (Viana, Jamison, Donovan, Elliot, & Gholz, 1996; Mater, 1999).

The situation for forest certification in the United States is somewhat unique when compared to the global picture because a large percentage of the total forest area in the U.S. is under nonindustrial private forest (NIPF) ownership. NIPF forests have traditionally filled an important niche in U. S. wood production, a role that is becoming even more crucial with the decline in timber harvesting on public lands. More recently the problem has been exacerbated with the rapid sell-off of vast expanses of forestry industry lands (American Tree Farm System, 2005).

The largest portion of the nation's forestland is located east of the Mississippi River, where 88% of all NIPF owners are located (Butler & Leatherberry, 2004). Even more significant is the strong regional identity of the 13 southeastern states. NIPF landowners in the Southeast number 5 million and control 89% of the forest area (Wear & Greis, 2002). Further, nearly 60% of the nation's timber production is produced by these 13 states, with a striking 18% of the world's industrial timber products originating from the South (Prestemon & Abt, 2002). Wood production in the Southeast is expected to increase by over 50% between 1995 and 2040, or an average of 1.6% per year (Prestemon & Abt, 2002; Wear & Greis, 2002).

The timber resources of the southeastern region of the U. S. are essential to both regional and global economies. This region will retain the distinction as the single largest producer of timber products in the world for the foreseeable future (Prestemon & Abt, 2002). Uniquely, these lands are principally owned, controlled, managed, purchased, and sold by NIPF landowners.

If forest products originating on privately owned forests are to be included in certification, a better understanding of how this vital ownership category will accept certification is essential. The study reported here was designed to assess awareness, acceptance, and opinions regarding forest certification of NIPF landowners in west Tennessee and to develop a profile of who would consider certifying and why. The information is important if viable certification programs are to be developed and implemented for this ownership category. In time, market forces could require large-scale certification, and the needs and preferences of Tennessee NIPF landowners should be considered for them to remain competitive.

Study Area

The study includes nine counties within the 18-county Forest Inventory and Analysis West Tennessee Region. The nine counties were selected because they represent 70% of the total forest area in the region (Schweitzer, 2000). Because compiling and mailing to landowner populations is costly, three counties were randomly selected from the list of nine for survey purposes (Carroll, Hardeman, and Weakley counties). The three counties include 564,300 acres (223,369 hectares) of forestland for an average percent forest cover of 47.8 per county. NIPF landowners own 81% of the forestland in the three study counties.

Methodology

Mail surveys were used for data collection. The survey instrument provided questions about owners and ownership characteristics. The original database of landowners was obtained from the Tennessee State Division of Property Assessment. Only landowners controlling 40 acres or more of forestland were targeted for the study. A 50% random sample was drawn from the landowner list for the three counties, making the sample 1,153.

A draft version of the survey questionnaire was developed and pre-tested. The Dillman tailored design method was followed as closely as possible (Dillman, 2000). On August 6, 2004, postcards were mailed to the 1,153 landowners notifying them of the project. Questionnaires and cover letters were mailed 2 weeks later. 1Landowners were assured that the information would be kept confidential. The respondents were given the opportunity to receive a summary of the results for participating in the study. On November 23, the survey officially ended. One hundred and three of the individuals were omitted (because they did not own land, owned less than 40 acres, were deceased, or were undeliverable as addressed). This brought the eligible target population to 1,050. A total of 532 individuals returned questionnaires for a total response rate of 50.7%. 1

In late November, telephone surveys were conducted to test for non-response bias. None of the variables for the non-respondents showed a significant difference between the respondents (α = 0.05).

Data Analysis

The survey consisted of 22 questions with a total of 78 response variables. Participants were asked to read a definition of forest certification and then were asked a binary (yes/no) question of their willingness to consider certification. This became the prominent dependent variable from which the demographic and attitudinal variables were examined. Chi-square tests were used to examine relationships between variables when data were nominal, and Spearman's correlations when data were ordinal or interval. Results were reported as statistically significant when P ≤ .05.

Results

Section 1. The Forestland

Landowners were asked how many acres of forestland they own (Φ = 216.6, Md = 122), how they acquired the majority of their land (71.2% had purchased the land), and how many more years they intended to retain their forestland (84.6% intended to retain their land for more than 15 years). None of these variables was found to be significantly related with landowners' willingness to consider certification. However, tenure (in years) of ownership was significant (Φ = 21.0, Md = 16.0). Landowners new to forest ownership were more likely to consider certification than those with longer ownership tenures (Χ²= 74.74, P = 0.0478).

People own forestland for many reasons. Participants were provided 14 common reasons for owning forestland and asked to indicate the importance of each reason. The most important reasons for owning forestland were: 1) pass on to children or heirs, 2) enjoy scenery, 3) supply food and habitat for wildlife, and 4) long-term financial investment (Table 1). Of the 14 reasons for owning forestland, only two reasons were significantly related to landowner's willingness to consider certification: 1) timber production (Χ²=19.26, P=0.0007) and 2) recreation other than hunting and fishing (Χ²=18.0, P= 0.0012).

Sixty-nine percent of the landowners indicated that they had harvested or cut trees from their forestland, yet there was no significant relationship between harvest history and willingness to consider certification. Landowners who had used a professional forester to plan, mark, or contract the harvest did not show more willingness to consider certification.

Section 2. Landowner Forestry Education and Assistance

Nearly one-half (48.4%) of the landowners indicated that they had received information about their forestland, with the State Division of Forestry, consulting foresters, and loggers being the top three sources (Table 2). One-fourth (26.1%) of the landowners had participated in government cost-share assistance programs for forestry or wildlife practices. Slightly more than half (54.7%) of the landowners felt it was important or very important to stay up-to-date with new forestry practices and programs.

Landowners who had received information or advice about their forestland were more likely to consider certification (Χ²=14.34, P=0.0002) than those who had not. Participation in government cost-share assistance programs was not significantly related to willingness to consider certification, nor was awareness of, nor membership in, a county forestry association. However, those who believe that it is important "to stay up-to-date with new forestry practices and programs," was significant (Χ²=36.61, P<.0001).

Section 3. Forest Certification

To investigate landowner's perception of certification, a series of questions with categorical responses were given. Only 2.9% of the respondents indicated they were familiar or very familiar with forest certification, and 80.0% were not at all familiar. Familiarity with certification was not significantly related to willingness consider certification.

Landowners were asked to read the following definition of forest certification and answer the questions that followed:

Forest certification means that forests are managed in a sustainable manner and that trees are harvested with environmentally sound practices. These management practices are certified by objective third parties. Landowner participation is voluntary.

Landowners who would consider certification were most trusting of the State Division of Forestry followed by consulting foresters and were least trusting of environmental organizations as objective third-party certifiers (Table 3).

Landowners showed very little familiarity with any of the four certification systems active in the U.S. The percent of respondents indicating either "familiar or very familiar" was: Green Tag (1.6), Sustainable Forestry Initiative (3.8), American Tree Farm (3.2), and Forest Stewardship Council (2.8). Familiarity with any of the certification systems was not significantly related with willingness to consider certification.

To assess the respondent's perceived benefits of certification, a series of statements related to what certification could accomplish were provided. When the perceived benefits were correlated with only those landowners who would consider certification, a highly significant relationship existed between all variables (Table 4). In other words, landowners with a willingness to consider certification believed strongly that certification would accomplish all of the listed benefits, including lessening the need for forestry regulation (P<.0001).