August 2004
Volume 42 Number 4

Research in Brief

Measuring Impacts with Young Audiences: Adapting a Life-Skills Instrument for Use with Third- to Fifth-Grade Youth

Doris M. Loeser
Department of Health and Human Development
Montana State University
Bozeman, Montana

Sandra J. Bailey
Family & Human Development Specialist
Department of Health & Human Development
Montana State University
Bozeman, Montana
baileys@montana.edu

Rae Lynn Benson
Lincoln County Extension Agent
Montana State University
Bozeman, Montana
rbenson@montana.edu

Mary Y. Deen
Family & 4-H Youth Development Specialist
Washington State University
Pullman, Washington
mdeen@wsu.edu

Capturing impacts of Extension programming on younger school-age audiences is often difficult and time consuming, yet staff are increasingly asked to document program effectiveness by Extension administrators, granting agencies, and policy makers. The limited literacy skills and concrete reasoning of young school-age children (Piaget, 2002) make the use of written evaluation instruments challenging. Observations and interviews, however, can be very time consuming and costly for programs. The project discussed here sought to develop a means to evaluate youth programming for third to fifth graders that was accurate, useful, ethical, and feasible (Joint Committee on Standards for Educational Evaluation, 1994).

The Washington State University (WSU) Life Skills Evaluation System (http://ext.wsu.edu/lifeskills/) is a Web-based system designed to allow Extension staff to create custom evaluation forms for their programs and generate summary reports on a local, county, and statewide level (Bailey & Deen, 2002). This system is useful in measuring short-term gains in life skills taught in many Extension youth and family programs. The system was developed and successfully tested for validity and reliability for youth and adults ages sixth grade and older.

Many Extension programs, however, are serving youth younger than sixth grade and need easy-to-use methods to measure program outcomes. This article outlines how we are working to adapt an older youth and adult version of the Life Skills System for younger audiences. Implications for others who are designing evaluation tools for young audiences are provided.

The WSU Life Skills Evaluation System was designed by and for Extension staff in the WSU Extension system. From the beginning of the project, a utilization approach to program evaluation was taken asking for participation and feedback from the users of the system, (Patton, 1997). Extension staff selected eight life skills from the Targeting Life Skills model (Hendricks, 1998) that they believed they were teaching through their program. These life skills were:

1. Decision Making,
2. Wise Use of Resources,
3. Communication,
4. Accepting Differences,
5. Leadership,
6. Useful/ Marketable Skills,
7. Healthy Lifestyle Choices, and
8. Self-Responsibility.

Although staff was excited about the new system, we quickly realized the need for a version that could be used with youth under the age of 11 years. We also realized that the version for younger children needed to assess the same skills as the current version because many Extension programs include multiple-age groups.

In meeting this challenge, we encountered several issues related to feasibility and accuracy in evaluation (Joint Committee on Standards for Educational Evaluation, 1994). The current system uses a retrospective pretest/posttest design (Pratt, McGuigan, & Katzev, 2000) to assist in making the evaluation process easier for busy Extension staff. However, because younger children rely more on concrete operations (Piaget, 2002) and may not readily conceptualize their former experience, a retrospective pretest/posttest was deemed to be an unreliable method for age group. Instead, a regular pretest/posttest design was used in which pretests need to be matched with posttests--a more time consuming method.

The second issue relates to accuracy. The instrument is a pencil and paper measurement, requiring reading and comprehension skills. For younger audiences, wording of questions and responses need to be adapted to the cognitive and literacy skills of this age group. Youth need to be able to make a link between program content and life skills taught. This is more difficult for youth in the concrete operational stage (Berk, 1999; Piaget, 2002).

Preparation and Implementation of Pilot

A 4-H Youth Camp, held in the northwest corner of Montana, provided the opportunity to develop and pilot test a Life Skills Evaluation System for younger audiences between the ages of eight and eleven. The study was deemed exempt by our university's Institutional Review Board Human Subjects' Committee. Passive parental consent was obtained through a notice sent to campers' parents.

The 31 indicators used to measure the eight life skills for the current Life Skills Evaluation System were adapted for a younger audience with a lower literacy level (see Appendix). This list was given to the camp director who met with the camp youth leaders. The contributions of youth leaders were instrumental to the planning and implementation of the program.

At the pre-camp retreat, the camp director introduced the process of teaching and evaluating life skills to counselors and worked with them in areas of leadership, communication, and child development. The current version of the Life Skills Evaluation System was used to measure the youth leaders' acquisition of life skills, while also increasing their familiarity with the test process. Following the pre-camp retreat, youth leaders planned camp activities that would help youth learn these skills.

The 4-H Youth Camp, held for 4 days during the summer of 2002, provided recreational activities that incorporated the learning of life skills. For example, in craft activities, campers were introduced to using resources wisely and the importance of recycling. Cabin and mealtime stressed self-responsibility.

Unlike the current Life Skills version, this version used a standard pre- and posttest that were administered by the camp counselors during group cabin time. Sixty-seven youth ages 9 to 13 attended the camp. There were 26 campers ages 9-10; 33 campers ages 11-12; and three campers age 13 years (Figure 1). The response rate for matched pretests and posttests was 97% or 65 of the 67 youth attending the camp. Nearly twice as many girls (n=40) attended the camp than boys (n=22).

Figure 1.
Age and Gender of Youth Campers

The 4-H camp is located in a small community with limited ethnic diversity; therefore, most of the respondents were White (n=39). However, small numbers of other ethnic groups were represented, including American Indian (n=9), Asian American/Pacific Islander (n=5), and those who are Racially Mixed or marked more than one response (n=17). Campers came from homes on farms or ranches, rural non-farm/ranch locations, towns under 50,000, and cities over 50,000 (Figure 2.)

Figure 2.
Ethnicity and Residence of Youth Campers

The Instrument and Testing Process

The Life Skills Evaluation System Version for Youth Ages Eight to Eleven was used to assess the life skills learned during the youth camp. The instrument was composed of 31 indicators, measuring the following eight life skills: Decision Making, Wise Use of Resources, Communication, Accepting Differences, Healthy Lifestyle Choices, and Self-Responsibility. A three-point scale of 1 to 3, with 1 being (never), 2 (sometimes), and 3 (usually), was used, because we determined that a four- or five-point scale might be too complex for younger youth.

Content and construct validity were assessed through a review of literature and expert feedback from Extension staff and specialists. The SAS statistical software package was used in analyzing these data. Using Cronbach's alpha, the instrument was tested for internal reliability, resulting in an alpha of 0.81. We were unable to conduct a factor analysis to determine subscales because a sample size of 100-200 is needed for this statistical test (Tabachnick & Fidell, 1989).

Although the goal of this pilot was to test the instrument reliability and validity, paired t-tests were conducted to assess gains from pretest to posttest. Statistically significant overall gains (p<.05) were made by campers in the life skills presented at camp. As measured by the pretest and posttest self reports, youth made gains in areas of Decision Making, Wise Use of Resources, Communication, Healthy Lifestyle, and Self-Responsibility. Although caution must be used in drawing conclusions given that the intervention was 4 days and there was no comparison group, the use of single-group pretest/posttests design can be supported if situational factors are taken into account (Eckert, 2000). In this case, the youth took the pretest upon arriving at camp, and the youth remained at the camp until the posttest was given.

Overall Patterns

Through this process a number of interesting results were obtained. While changes from pretest to posttest consistently noted an increase in life skills from never to sometimes and usually, this range of possible answers appeared to produce some confusion for this age group. One camper in the 9-to-10-age group replaced the word never with the word no on one of the choice headings, indicating a need for simplification and explanation of terms.

More concrete wording with more distinct choices and fewer nuances may alleviate possible sources of confusion. Possibilities could include a two-part response system of true or false; agree or disagree; a three-part system of no, maybe, yes; or a wider range of choices, such as not at all like me, somewhat like me, like me, and very much like me.

Also, it is important to note the interaction of indicators and possible responses. The use of double negatives, produced by the negatively worded indicator "I do not pick on kids who are different," along with the possible choice of never, was bewildering to these young readers. This pointed to a need for revision of this indicator to a clearly positive statement.

Mixed Results

On some indicators, the change from pretest to posttest did not demonstrate a uniform increase in life skills to the highest response of usually, but toward the center choice of sometimes, with a decrease in the two extreme responses. For instance, on the Decision Making indicator, "I am happy with choices I make," campers moved their preference from usually to the more self-reflective sometimes.

Similarly, there were interesting mixed results in the area of Accepting Differences. The ethnic composition of 63 responding camp members, according to self-reports on the pretest, included 16% Native American, 5% Asian American/ Pacific Islander, 19% Racially Mixed, and 60% White Caucasian backgrounds. On the three indicators regarding relations with children of a different skin color, while three quarters of the campers continued to indicate a preference for the usually option, numbers shifted slightly into the sometimes category in two instances.

First, on the indicator "I play with kids who have a different skin color than I do," campers' preferences decreased in the usually response and increased in the sometimes response. Second, on the indicator "I have friends who have a different skin color than I do," campers' preferences shifted from never to sometimes, while usually remained a high, but unchanged, choice.

While no children with handicaps attended the camp, the four indicators regarding relating to children with handicaps demonstrated small to moderate gains in the usually response. On the indicator, "I play with kids who are handicapped," while the highest number of campers continued to choose the sometimes response, there was a gain from never to usually. On the indicator "I have friends who are handicapped," while the highest number continued to choose never, there was a similar upward shift from this response to usually.

Areas of Greatest Gains 

It appears that the greatest overall gains were made in life skills that could be practiced in camp. For instance, in the life skill Wise Use of Resources, campers showed increases on all indicators. The greatest gains were made on the indicator "I pick up litter when I see it lying around," which may reflect the immediacy of teaching such values in the camp setting. Similarly, in Decision Making, high gains were made on the indicator "I think about my choices before making a decision." In the area of Communication, campers generally made strong gains on all indicators, with the greatest gain being on the indicator "I apologize when I am wrong," closely followed by other communication indicators. This demonstrates the effectiveness of learning communication skills in the camp setting.

Demographics

Indicators pertaining to demographics, which were filled out on both tests, produced some variation from pretest to posttest, reflecting a need for refinement in the process. Counselors perceived that the younger campers, especially the 9-year olds, had difficulty with the demographic questions and needed assistance reading and responding to them. There were inconsistencies from pretest to posttest on ethnicity, current home, and even gender choices.

The need for further explanation of the demographic questions is demonstrated by the campers' choices on the questions regarding their current home and ethnicity. A number of respondents changed current home categories between tests, and four campers chose several categories on either one or both of the tests to creatively describe their place of residence. One person added a written comment that she presently had two homes, a logical response for a youth from divorced parents. Similarly, in addition to campers who changed ethnicity from pretest to posttest, some described themselves using two ethnicity categories. Such inconsistencies can be alleviated by double-checking that all possible choices are listed and given adequate explanation, surveying these variables on the pretest alone, and assistance to campers at the time of testing.

Open-Ended Questions

Campers also responded to open-ended questions with statements that reflected their learning of life skills through camp activities. Responses to the question, "The most important thing I learned from attending Multi-County 4-H Camp is . . . " included comments that demonstrated skill building in the areas of Wise Use of Resources, Self-Responsibility, Communication, and Accepting Differences. One camper wrote, "I learned how to be clean and tidy" and to "respect the camp ground," reflecting increased awareness of Wise Use of Resources. Another camper noted "I learned how to take care of my things," indicating gains in the area Self-Responsibility. Other campers stated, "I learned to think before I talk" and to "get along and be careful about what you say," demonstrating gains in Communication skills.

There were many comments on the importance of interpersonal relations and making new friends at camp. In the area of Accepting Differences, one camper wrote that she learned "to be yourself, get along with others and just have fun." One camper wrote, "I learned that sometimes in life there are things that you have to do and people that you have to get along with that you don't want to." Another stated, "I learned responsibility and how to be kind to people with differences." These voluntary comments demonstrate the success of imparting life skills in this particular setting.

Implications

There are several implications from this pilot study for Extension staff who are planning evaluations with younger audiences. An essential part of planning is the coordination of life skills to be taught with the indicators to be used in the evaluation process. Discussing the life skill indicators and the program content during program planning sets the stage for an increased linkage between the two. A three-step process has been an effective sequence to meet this goal:

• Introduction of life skills to be used to program staff
• Collaborative planning of corresponding activities
• Refining of indicators based on the planned program

Designing an evaluation instrument for this age group that is feasible to administer given the busy schedules of Extension staff is challenging. Our experience found that it is useful to:

• Use close-ended questions to reduce the time needed to respond to questions and for ease in calculating results;
• Use a few open-ended questions to capture anecdotal information;
• Formulate indicators and responses adapted to participants' cognitive level using age-appropriate language;
• Use indicators that describe actual experiences, which youth have had the opportunity to practice in the program (e.g., communication with peers, decision making during activities); and
• Avoid using double negatives.

The limited abstract reasoning skills of the younger age group, grades three to five (ages 8 to 11) (Piaget, 2002), require that separate pretests and posttests be administered before and after the program. Prior to the program, staff needs to be oriented to the method of administering the evaluations to participants. A mechanism for matching pretests and posttests for each participant can include:

• Numbers on youth participants' nametags,
• A master list of names and numbers to match pre and posttests,
• Color-coding of pretests and posttests into two separate groups to avoid confusion, and
• Designating a specific time for staff to administer pre- and posttests.

During the process of administering the tests, it is important to have leaders available to clarify any points of confusion that participants may have, minimizing their frustration and enhancing their ability to respond to indicators:

• Train staff on how to administer the evaluation;
• Orient the youth to the evaluation process (e.g., explaining that they should choose the answer that best describes the youth's situation, thoughts, or feelings.); and
• Use consistent probes to clarify questions youth have in answering questions.

Conclusion

Developing effective ways to evaluate Extension programming for youth under age 11 is difficult. Extension staff often do not have the time or evaluation skills to use complex data collection methods such as observations. This project sought to adapt an evaluation instrument designed for youth and adults sixth grade and older for use with younger audiences. Through the process we have learned the limitations in this data collection method, but have found that it can be reliable and useful for busy Extension staff.

We are continuing to refine the instrument and the data collection process through further testing. With careful planning and administration of a life skills evaluation system that is closely matched to program activities and cognitive skill level of youth, a feasible and reliable system, which measures program outcomes, can be developed for young audiences.

References

Bailey, S. J., & Deen, M. Y. (2002). Development of a web-based evaluation system: a tool for measuring life skills in youth and family programs. Family Relations, 51, 138-147.

Berk, L.  E. (1999). Infants, children, and adolescents. (3rd ed.). Needham Heights, MA: Allyn and Bacon.

Eckert, W.  A. (2000). Situational enhancement of design validity: The case of training evaluation at the World Bank Institute. American Journal of Evaluation, 21, 185-193.

Hendricks, P. (1998). Developing youth curriculum using the targeting life skills model: Incorporating developmentally appropriate learning opportunities to assess impact of life skill development (Tech. Rep. No. 4H-137A). Ames: Iowa State University Extension.

Joint Committee on Standards for Educational Evaluation (1994). The program evaluation standards (2nd ed.). Thousand Oaks, CA: Sage.

Patton, M. Q. (1997). Utilization-focused evaluation (3rd ed.). Thousand Oaks, CA: Sage.

Piaget, J. (2002). The language and thought of the child. (Reprint of 3^rd ed., c1959). New York: Routledge.

Powell, M. F. (1985). A program of life-life skills training through interdisciplinary group process. Journal of Group Psychotherapy, Psychodrama, & Sociometry, 38, 23-34.

Pratt, C. C., McGuigan, W. M., & Katzev, A. R. (2000). Measuring program outcomes: Using retrospective pretest methodology. American Journal of Evaluation, 21, 341-349.

Tabachnick, B. G., & Fidell, L. S. (1989). Using multivariate statistics. New York: HarperCollins.

Appendix: Life Skills Instrument
Third to Fifth Grade

DECISION MAKING	NEVER	SOMETIMES	USUALLY
I think about my choices before making a decision.	1	2	3
I think about what might happen because of my choice.	1	2	3
I am happy with the choices that I make.	1	2	3
When I need to, I ask an adult for help in making a decision.	1	2	3
WISE USE OF RESOURCES	NEVER	SOMETIMES	USUALLY
I recycle at home or at school.	1	2	3
When I get money, I save some of it.	1	2	3
I make time for doing my homework.	1	2	3
I clean my room without my parents reminding me.	1	2	3
I pick up litter when I see it lying around.	1	2	3
When making a project I only take the things I need.	1	2	3
COMMUNICATION	NEVER	SOMETIMES	USUALLY
I do not talk when others are talking.	1	2	3
I listen when someone is talking to me.	1	2	3
I tell people how I feel when they hurt my feelings.	1	2	3
I apologize when I am wrong.	1	2	3
I get along with people.	1	2	3
If I do not understand something I ask for help.	1	2	3
ACCEPTING DIFFERENCES	NEVER	SOMETIMES	USUALLY
I play with kids who have a different skin color than I do.	1	2	3
I have friends who have a different skin color than I do.	1	2	3
I would invite a kid who has a different skin color than I do over to my house to play.	1	2	3
I play with kids who are handicapped.	1	2	3
I have friends who are handicapped.	1	2	3
I would invite a kid with a handicap to my house to play.	1	2	3
I do not pick on kids who are different.	1	2	3
I would have a sleepover with a handicapped kid.	1	2	3
I let others play with me even if they aren't very good at the game.	1	2	3
HEALTHY LIFESTYLE CHOICES	NEVER	SOMETIMES	USUALLY
I choose healthy snacks like vegetables and fruits.	1	2	3
I wear a safety helmet when riding a bike, using a skateboard, or using roller blades.	1	2	3
I talk to someone when I am upset or scared.	1	2	3
I say "no" and don't do what others are doing if it looks dangerous to me.	1	2	3
I like to play outside everyday	1	2	3
SELF RESPONSIBILITY	NEVER	SOMETIMES	USUALLY
I follow a schedule for doing homework.	1	2	3
I watch less than three television programs every day.	1	2	3
I do what I say I am going to do.	1	2	3
I go to an adult and ask for help solving a problem.	1	2	3
I take care of my things.	1	2	3
I ask for permission before I use other people's things.	1	2	3
I wait for my turn when doing an activity.	1	2	3
THANK YOU!!!!!!!!!

Physical Activity Behavior, Dietary Patterns, and Nutrition Knowledge of Third- and Fourth-Grade Students in Western Massachusetts

Hui-Wen Huang
University of Massachusetts
Department of Nutrition
Amherst, Massachusetts
cindy.huang@apex-cro.com

Stella L. Volpe
University of Pennsylvania
School of Nursing
Nutrition Education Building
Philadelphia, Pennsylvania
svolpe@nursing.upenn.edu

Introduction

School-age children may be at nutritional and health risks due to the dramatic increase in physical development and their lack of nutrition knowledge, both of which may be exacerbated in children of low-income. Two of Healthy People 2010's goals are to: 1) "Increase the proportion of persons aged 2 years and older who consume no more than 30 percent of calories from total fat" and 2) "Increase the proportion of adolescents who engage in moderate physical activity for at least 30 minutes on 5 or more of the previous 7 days" (U.S. Department of Health and Human Services, 2000).

These goals should also be applied to Extension programs that are targeted toward low-income communities because this could result in healthier communities, which is a major goal of extension programs. However, little attention has been given to monitoring nutrition knowledge (Resnicow et al., 1997) and physical activity levels in children.

The purpose of the Extension project discussed here was to assess physical activity patterns, and nutrition behavior and knowledge in third- and fourth-grade students in an elementary school in a low-come community. Based on the results, appropriate nutrition and physical activity programs will be developed for children of similar age and socioeconomic status.

Methods

Participants

Sixteen third- and fourth-grade students from low-income families participated in this study. They were 9.3 ± 0.5 years of age and attended an elementary school located in Western Massachusetts. There were 10 boys and 6 girls (11 Caucasian, 3 Asian, 1 African-American, and 1 "other"). Among the 16 children, one boy (Caucasian) did not complete the Nutrition Knowledge and Physical Activity Questionnaire. Therefore, his data was only included for the Youth-Adolescent Questionnaire.

Data Collection

Prior to administering the survey, informed consent forms were reviewed and approved by both the University of Massachusetts Human Subjects Review Committee and the School Committee of the participating elementary school. Written informed consents were obtained from both children and parents. Three individuals from the University of Massachusetts and two classroom teachers implemented three questionnaires on 2 separate days within a week during class time in June of the school year.

Physical activity behaviors were assessed by using a self-administered questionnaire revised from the validated National Children and Youth Fitness Survey (NCYFS) I and II (Pate, Dowda, & Ross, 1990; Ross, 1997; Ross & Gilbert, 1985). It contains physical education (PE) class and leisure time-related participation in approximately 78 different kinds of physical activity. Children were provided with the physical activities, as well as the frequency and duration of the activities in which they had participated during the last year, both within and outside of PE class. They also chose from a list containing eight different settings of community organizations.

The top ten and top five physical activities in which the children most frequently engaged in school and community organizations were respectively ranked. The top three community organizations were also ranked. Finally, there was a question regarding physical activity patterns during each season of the year.

The Youth-Adolescent Questionnaire (YAQ) (Rockett, Wolf, & Golditz, 1995) was used to assess dietary patterns. The YAQ included a list of 151 foods. Reproducibility (Rockett et al., 1995) and validity studies (Rockett & Golditz, 1997) have shown reasonable ability of YAQ to assess children's eating habits. A standard serving size is given for each food, and there are nine frequency-of-use responses for the amount eaten, ranging from "never" or "less than once per month" to "over 6 per day" (Rockett et al., 1995). The Channing Laboratory in the Department of Medicine at Harvard Medical School conducted dietary intake analyses.

Seventeen questions were asked that were developed to evaluate children's nutrition knowledge. This questionnaire consisted of seven true and false questions and 10 multiple-choice questions designed to obtain children's knowledge of general nutrition and nutrition related to physical activity. All the multiple-choice items allowed students an "I don't know" response to minimize guessing. Their nutrition knowledge score was calculated as "1" for a correct response and "0" for incorrect and "I don't know" responses. A score of 17 denoted a perfect score.

Statistical Analyses

Statistical comparisons were accomplished by the student's T-test. A level of significance was set a priori at 0.05. All results are presented as means ± standard deviations (SD).

Results

Physical Activity Behavior

The average PE classes met 2 days per week for about 41.4 minutes per day, which included time for changing clothes and washing up. The most common PE class offerings are listed in Table 1.

Home and neighborhood were ranked as the first places, other than school, for providing physical activity opportunities for these students. The top three community organizations where children usually performed their physical activity are listed in Table 2.

The top five most frequently performed physical activities outside of PE class are listed in Table 3. The average time spent in physical activity was about 2.8 ± 1.0 days/week and 36.5 ± 9.4 minutes/day outside of PE classes. Boys reported that they spent 2.3 ± 1.0 days/week and 34.3 ± 9.5 minutes/day in physical activity. Although girls reported spending more time than boys in physical activity, with 3.5 ± 0.7 days/week and 39.7 ± 9.0 minutes/day, there were no differences between them.

The average days per week these children spent in physical activity during the four seasons varied (Table 4). In the winter, days per week spent on physical activities were significantly lower than any other season.

Dietary Patterns

Average dietary intake for energy, total carbohydrate, total protein, total fat, and selected nutrients compared with the Dietary Reference Intakes (DRIs) (Food and Nutrition Board [FNB], 1997, 1998, 2000) and the Recommended Dietary Allowances (RDAs) (FNB, 1989) are shown in Table 5.

Nutrition Knowledge

The average nutrition knowledge score for boys and girls were 10.8 ± 2.6 and 9.8 ± 1.7, respectively, out of a possible 17, with no differences in scores between genders. The number of children correctly responding to the nutrition knowledge test for each question is listed in Table 6.

Discussion

Although it is generally believed that boys spend substantially more time in physical activity than girls (Sallis, 1993), we did not observe this. We expect that the difference in physical activity habits between boys and girls was minimal due to the young age. Nonetheless, boys and girls did have different preferences in types of physical activities chosen.

School played a major role in providing physical activity for these children because half of the activities performed were in PE classes. As for outside of school, local sports teams or leagues, recreation departments, and scouts were the most popular places for physical activity. Community organizations have long played an important role in providing physical activity opportunities to children (Ross, 1997; Ross & Gilbert, 1985) and should be considered when planning Extension programs.

It has been reported that children are less active in winter than in other seasons, especially in places with cold, long winters (Ross, 1997; Ross & Gilbert, 1985; Stephens, 1993). Conversely, children living in areas where the summers are hot and humid were least active in the summer due to the heat (Baranowski, Thompson, Durant, Baranowski, & Puhl, 1993). It was therefore not surprising that the children in our study, living in Massachusetts, were more physically active in the summer and less physically active in the winter. Because of this difference in activity level during the winter months, efforts need to be made to increase children's physical activity during the winter months.

Although the macronutrient intake distribution in their diets was within the recommended levels, the total energy (kilocalorie) intake of these children was 90% of the RDAs (FNB, 1989), which were established to promote normal growth. The percentage of energy intake from fat was lower than the average of 35% observed in many epidemiological surveys of children (Johnson, Guthrie, Smicklas-Wright, Wang, 1994; National Heart, Lung, and Blood Institute Growth and Health Study Research Group, 1992; Nicklas, Webber, Srinivasan, & Berenson, 1993).

Many studies have showed a trend toward lower percentages of energy intake from dietary fat in recent years; therefore, our results might parallel this trend toward a lower dietary fat consumption. It may be a result of the YAQ, because Rockett et al. (1995) also reported a lower dietary fat (30%) intake compared to the Bogalusa Heart Study and NHANES II which used 24-hour recalls to assess children's dietary intakes (Carroll, Abraham, & Dresser, 1983; Farris & Nicklas, 1993).

These children consumed greater than 100% of the DRIs (FNB, 1997, 1998 & 2000) for almost all vitamins and minerals except calcium and iodine, which were 92% and 39% of the DRIs, respectively (FNB, 1997; Trumbo, Yates, & Schlicker, 2001). The reported consumption of vitamins C, B₁₂, and riboflavin were up to three times above the DRIs (FNB, 1998 & 2001), perhaps because 10 out of the 16 children reported taking vitamin/mineral supplements.

Although the nutrition knowledge of the boys and girls was equal, all children could not correctly indicate the major nutrient source of each food. Nonetheless, they did show a better knowledge of foods high in fat, possibly because these children received more information about fat since this has been a focus of public advertisements.

Regarding the questions about nutrition and exercise, children were not fully aware of what to consume before exercise or that hydration was important for better exercise performance. Therefore, more nutrition education on basic functions of nutrients, food choices, and the importance of hydration is essential for children of this age. In addition, children should be taught the importance of nutrition in exercise.

Summary

• Both school and community organizations provided physical activity opportunities for children.
• This study provides a basis of the type, duration, frequency, and seasonal variations in children's physical activity, which could be used as a reference for developing Extension programs.
• Children's nutrient intakes, especially macronutrients, appear to be similar with what has been documented in many large-scale dietary surveys in this age group.

Limitations

• The surveys took two full class periods, which was difficult for the children and the school.
• The survey we developed was not validated prior to use.
• The small sample size limits the generalizability of our results.

References

Baranowski, T., Thompson, W. O., Durant, R. H. J., Baranowski, J., & Puhl, J. (1993). Observations on physical activity in physical location: Age, gender, ethnicity, and month effects. Research Quarterly for Exercise and Sport, 64, 127-133.

Carroll, M. D., Abraham, S., & Dresser, C. M. (1983). Dietary Intake Source Data: United States 1976-1980. Vital and health statistics (Series 11, No. 231, DHHS publication (PHS) 83-1681). Washington, DC: National Center for Health Statistics.

Farris, R., & Nicklas, T. (1993). Characterizing children's eating behavior. In: R. Suskind, & L. Suskind (Eds.), Textbook of pediatric nutrition (2nd ed.). New York, NY: Raven Press.

Food and Nutrition Board, National Research Council. (1989). Recommended dietary allowances (10th ed.). Washington, DC: National Academy Press.

Food and Nutrition Board, National Research Council. (1997). Dietary reference intakes for: calcium, phosphorus, magnesium, vitamin D, and fluoride. Washington, DC: National Academy Press.

Food and Nutrition Board, National Research Council. (1998). Dietary reference intakes for: thiamin, riboflavin, niacin, vitamin B₆, folate, vitamin B₁₂, pantothenic acid, biotin, and choline. Washington, DC: National Academy Press.

Food and Nutrition Board, National Research Council. (2000). Dietary reference intakes for: vitamin C, vitamin E, selenium, and carotenoids. Washington, DC: National Academy Press.

Johnson, R. K., Guthrie, H., Smicklas-Wright, H., & Wang, M. Q. (1994). Characterizing nutrient intakes of children by sociodemographic factors. Public Health Report, 109, 414-420.

Nicklas, T. A., Webber, L. S., Srinivasan. S. R., & Berenson. G. S. (1993). Secular trends in dietary intakes and cardiovascular risk factors of 10-y-old children: the Bogalusa Heart Study (1973-1988). American Journal of Clinical Nutrition, 57, 930-937.

Pate, R. R., Dowda, M., & Ross, J. G. (1990). Association between physical activity and physical fitness in American children. American Journal of Disabled Children, 144, 1123-1129.

Resnicow, K., Hearn, M., Delano, R. K., Conklin, T., Orlandi, M. A., & Wynder, E. L. (1997). Journal of Health Education, 28 (3), 156-164.

Rockett, H. R. H., & Colditz, G. A. (1997). Assessing diets of children and adolescents. American Journal of Clinical Nutrition, 65 (Suppl.), 1116S-1122S.

Rockett, H. R. H., Wolf, A. M., & Golditz, A. (1995). Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. Journal of the American Dietetic Association, 95, 336-340. 

Ross, J. G. (1997). National children and youth fitness study I & II. Medicine & Science in Sports & Exercise, 29 (6), S170-S189.

Ross, J. G., & Gilbert, G. G. (1985). The national children and youth fitness study: A summary of findings. Journal of Physical Education, Recreation, and Dance, 56 (1), 43-90.

Sallis, J. F. (1993). Epidemiology of physical activity and fitness in children and adolescent. Critical Reviews in Food Science and Nutrition, 33, 403-408.

Stephens, T. (1993). Leisure time physical activity. In: T. Stephens & F. D. Graham (Eds.), Canada's health promotion survey 1990: Technical report (pp. 139-150). Ottawa, Ontario: Health and Welfare Canada.

Trumbo, P., Yates, A. A., Schlicker, S., Poos, M. (2001). Dietary reference intakes: Vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc. Journal of the American Dietetic Association, 101 (3): 294-301.

U.S. Department of Health and Human Services. (2000). Healthy people 2010. McLean, VA: International Medical Publishing, Inc.

Yates, A. A., Schlicker, S. A., & Suitor, C. W. (1998). Dietary Reference Intakes: The new basis for recommendations for calcium and related nutrients, B vitamins, and choline. Journal of the American Dietetic Association, 98, 699-706.

Illinois Extension's Readiness to Address Children, Youth, and Families at Risk

Angela Wiley
Extension Specialist and Assistant Professor
University of Illinois
Urbana-Champaign, Illinois
awiley@uiuc.edu

Andre Mbassa
Research Assistant
University of Illinois
Urbana-Champaign, Illinois
mbassa@students.uiuc.edu

Al Zwilling
CYFAR Project Coordinator
University of Illinois Extension
East Moline, Illinois
azwillin@uiuc.edu

Introduction

Extension's mission has been to "tak[e] the University to the people by conducting research-based educational programs for many of the diverse groups making up our nation," (Rassmussen, 1989). This has gained importance with shifts in demographics (U.S. Census 2000). In response to dynamic needs of American families, Extension has accepted the challenge to more fully address youth, family, and community development. Still, many "needs are not being met because funding and staff are not available," (Rassmussen, 1989). A fundamental challenge is to meet expanding and diverse needs with substantially fewer resources.

Historically, the educator (county agent) connects citizens and land-grant universities by identifying research problems and communicating research findings (Garrett, 2001). In Illinois, units are local Extension points of contact for one or more counties. Unit leaders provide programmatic leadership, assess community needs, and build coalitions to accomplish local goals (Peeples, Zwilling, Wiley, & Spelke, 2000). Like educators (Wiley & Ebata, in press), unit leaders need training to work with emerging issues that impact diverse youth and families at risk. Is Extension ready to meet this challenge?

Illinois Children, Youth and Families at Risk (CYFAR) State Strengthening evaluators examined how unit leaders assess experience, knowledge, and interest in reaching at risk audiences. We look perceptions of at-risk audiences, their programming needs, existing programming, and ideal programming. We evaluate existing strengths and propose training opportunities in areas relevant to at-risk audiences.

Method

In 2000, a sample was selected using a stratified random sampling technique based on the poverty level of the counties (Cook County, home of Chicago, was not included due to skewed population demographics compared to the rest of the state). One quarter (20) was selected using a quartile technique. Units were divided into four quartiles based on poverty level (high, medium, low, and very low), and the same number of units was randomly drawn from each quartile. Surveys were administered via telephone interviews.

The instrument consisted of several rating scales and open-ended questions. Respondents were asked to rate their experience, knowledge, and interest in at risk programming using a five-point scale (1 = very low, 2 = low, 3 = so-so, 4 = high and 5 = very high). Unit leaders responded to open-ended questions about perceptions of at risk audiences, existing and potential programs addressing at risk audiences, and constraints and opportunities for more programming.

We transcribed all information and did interpretative qualitative analyses, specifically open coding (Straus & Corbin, 1998). After several readings, major concepts were identified and coded. Descriptive statistics and cross-tabulations were used to compile the results.

Findings and Discussion

Demographic Profile

• 74% were females, and 26% males.
• 37% had an agriculture-relevant degree.
• 26% were trained in home economics.
• 10% were trained in education.
• 32% had been in Extension more than 25 years.
• 20% had 20-25 years of field experience.
• Average was 19.45 years of experience (range 1-25).

Ratings of Experience, Knowledge and Interest

Over half of unit leaders rated themselves as 3 ("so-so") or below in experience with at-risk programming (Table 1). Forty-two percent felt they have high experience, while only 6% rated themselves as very high. There was great variation in work with at-risk audiences. When asked about their knowledge of at-risk issues, 48% reported "so-so" to low knowledge. These unit leaders rated only slightly higher their knowledge compared to experience with at-risk programming. While not completely confident in their experience and knowledge, a full 88% rated their interest as high or very high in such programming. Local Extension managers need more support and training to do work they really want to do with at-risk audiences.

Unit Leaders' Perceptions of Children, Youth, and Families at Risk

We asked "what comes to your mind when you hear 'children, youth and families at risk?'" Table 2 summarizes Extension unit leaders' perceptions. The first column shows responses in each category. The second shows how many responses in a particular category were the initial answer to the question. This first answer may be an indication of the primacy of a particular category for the respondent.

Respondents used different criteria to define children, youth, and families at risk. While many (69%) talked first about economic situations, they differed on other defining features. These included family structure (e.g., single parent), legal issues (alcohol and drug abuse), age and physical vulnerability (youth and elderly), race and gender (minority status and girls), and social and emotional status (working parents with loosely monitored children and dysfunctional families).

Lack of economic resources is the defining at risk characteristic for these unit leaders. All of them mentioned this, and it was the initial response for nearly 70%. While nearly one quarter of all responses concerned family structure, it was mentioned first by only 16% of unit leaders. This may indicate its relative lower importance when compared to economic stress. Only 13% of all responses concerned race and/or gender, and none mentioned it first.

At Risk Audiences in Need of Programming

We asked "What audiences in your county could benefit from programming for Children, Youth and Families at risk?" Initial responses (Table 3) were almost evenly divided between economically challenged audiences and those with legal and/or social challenges (e.g., alcohol/substance abuse and violence). A smaller number were concerned about audiences with contextual challenges (e.g., geographical context such as urban or rural audience).

Answers to this question likely indicate the at-risk audiences unit leaders perceive to be represented and in need of programming in their communities. Economic challenges, seen as a primary defining feature in Table 2, are also seen as prevalent in the at-risk audiences present in the communities of these unit leaders. While family structure issues were deemed important in defining at risk audiences, families with these challenges were not seen as primary targets for at-risk programming.

It is also notable that audiences with legal/social issues are seen as in need of local programming (nearly one-third of respondents reported this) but are not as important when defining at-risk audiences (Table 2). Both of these findings may reveal that unit leaders see their own at-risk communities as unique when compared to more general at-risk populations.

Finally, three of the unit leaders were concerned that audiences with contextual challenges (in these cases rural families and schools) need programming. Again, this category was not represented in their more general definitions of "at-risk" audiences, perhaps as a result of seeing their own communities as having local problems not represented more broadly. It is also interesting to note that audiences based on race and/or gender were not identified by any unit leaders as needing programming in their communities. This may show that unit leaders are confident that there is enough programming to meet the needs of these audiences or that they do not see audiences with these needs as represented in their communities sufficiently to warrant programming.

Existing Programs for Children, Youth, and Families at Risk

In answering the third question, "What Extension programs are you aware of that address the needs of children, youth and families at risk?," 74% (14) of unit leaders mentioned nutrition programs (Table 4). An equal number reported youth-related programming (e.g., 4-H), while fewer than half (43%) mentioned programs related to education and job training. These figures are interesting when compared to the reported needs of local at-risk audiences. While the reported programming may address some needs of the economically challenged, no unit leader mentioned any existing programming focused on the legal issues (e.g. substance abuse and violence) identified as an important need in the prior question.

Programming in an Ideal World

Finally, respondents were asked, if they had unlimited resources, where they would target more programming for at-risk audiences in their communities (Table 5). About 37% of the unit leaders expressed first the need for more programming in the area of education and job training, and references to this type of programming made up more than a quarter (29%) of their responses. Preschool and after school programs, literacy training, and GED training were also mentioned in this category.

This is not surprising given that economic challenge was the primary criteria in most leaders' definition of children, youth, and families at risk. The need for more programming in this area is probably indicative of the depth of the perceived problem as well as the reality of hard decisions that must be made in the face of limited funding.

Responses in the most commonly mentioned category (27%) concerned organizational changes in Extension. Fourteen of 19 unit leaders identified at least one organizational change. We did not anticipate that this question about ideal programming would elicit answers about how the Extension organization must change to reach at-risk audiences. It was as if most unit leaders could not talk about programming in an ideal world without passionately addressing how to make that world possible. They spoke of:

• Additional staff training,
• More purposive collaboration with other agencies,
• Recruiting and keeping more diverse professional and paraprofessional staff, and
• Reviewing and updating Extension educational materials.

Additionally, three spoke of changing the way Extension does business to actually providing some concrete resources (such as food when needed) and face-to-face direct assistance to at-risk audiences.

Under the "teen/children" category, several respondents mentioned programs to prevent adolescent pregnancy, and one spoke about drug abuse prevention programs. Beyond this, we were surprised that unit leaders did not mention adding programs focused on legal/social challenges, even though many identified this as a need among at-risk audiences in their communities and none mentioned relevant existing programming.

Implications

Extension has always responded to the evolving needs of the public. As in times past, Extension is now called upon to grow and stretch in new directions. This is especially true given the myriad of sources people can now turn to for information. Extension must find ways to underline and expand its reputation as a credible source of research-based information that is relevant to real and pressing social problems. The needs of children, youth, and families at risk are one example.

The results of this survey provide us with a limited picture of how unit leaders in Illinois assess their own experience, knowledge, and interest in providing services to children, youth, and families at risk. We are also given a picture of how these local managers perceive at-risk audiences and, more specifically, what at-risk audiences they believe need Extension programming, the programming that exists, and ideally the targeted programming unit leaders would offer with unlimited resources. We end this article with some general conclusions and suggestions for future training, programming, and inquiry for Extension professionals.

• Given the shifting population, Extension must provide training and support to front-line leaders in areas relevant to at-risk audiences. It is encouraging that these unit leaders were very interested in programming for at-risk audiences. They may lack resources and training, but they do not lack heart.

• The overwhelming attention to economic challenge as the primary defining feature of risk may be related to a local salient reality. It also suggests that continued efforts should be made to raise awareness of the many complex issues that contribute to the vulnerability of families and youth.

• The focus on legal and social challenges present in local communities suggests that unit leaders and their staff might benefit from more training and support in providing appropriate educational support for such audiences and their families.

• Given the salience of economic and legal/social risk, it would be prudent to invest more training and programming resources in these areas. Findings imply that more effort should be focused on sexuality education and pregnancy, and disease and violence prevention programming for youth audiences.

• There is a pressing need for more administrative and infrastructure support for addressing the needs of at-risk audiences. Additional leadership, incentives, and training would benefit the efforts of these local managers.

We believe the findings and implications of this study provide insights for Extension organizations outside Illinois, although population demographics and specific needs may differ. Across the U.S., Extension must provide support for increased attention to children, youth, and families at risk.

References

Garrett, T. A. (2001). Economies of scale and inefficiency in county Extension councils: A case for consolidation.

Knutson, R. D. (1986). Restructuring agricultural economics Extension to meet changing needs. American Journal of Agricultural Economics, 68:1297-1306.

Peeples, G. G., Zwilling, A., Wiley, A.,& Spelke, K. A. (2000). Building Extension capacity and adding strengths in local communities in Illinois. State Strengthening proposal funded by USDA. Urbana, IL: University of Illinois.

Rassmussen, W. D. (1989). Taking the university to the people: Seventy-five years of Cooperative Extension. Ames, IW: Iowa State University Press.

Strauss, A. L., & Corbin, J. (1998). Basics of qualitative research. Second Edition. Newbury Park, CA: Sage Publications.

Wiley, A. & Ebata, A. (in press). Reaching "the American families": Making diversity real in family life education. Family Relations.

Using Focus Group Interviews to Identify Needs for Stepfamily Education

Ruth Anne Foote
Extension Agent, Family and Consumer Sciences
Celina, Ohio
foote.3@osu.edu

Lois Clark
Extension Agent, Family and Consumer Sciences
Wapakoneta, Ohio
clark.21@osu.edu

Nancy Recker
Extension Agent, Family and Consumer Sciences
Lima, Ohio
recker.22@osu.edu

Ohio State University Extension

Introduction

While many family forms exist today, experts predict that by 2010 the family of norm will be the stepfamily (Visher & Visher, 1993). In the past, most stepfamilies were formed following the death of a spouse; today, most stepfamilies follow a divorce. The stepfamily is a unique type of family with special opportunities, strengths, obstacles, and stresses. Myths and unrealistic expectations associated with the stepfamily may lead to inappropriate behaviors and foster feelings of inadequacy among stepfamily members. Stepfamily myths include "instant love," "wicked stepmother," and rapid adjustment to stepfamily life (Stepfamily Association of America).

Research shows couples in a remarriage report lower relationship quality, experience greater conflict, and exhibit less positive problem-solving skills than couples in first marriages (Pasley, 1993). There are many programs for families experiencing divorce; however, few community resources or programs are available for stepfamilies. Studies have shown that it takes many months for stepfamilies to successfully integrate (Papernow, 1998). Most families take several years (Bray & Kelly, 1998) to get to know each other and create positive relationships. Stepfamilies often try to recreate their new families to resemble their former family, thus causing stress. Understanding the differences of stepfamilies can help them understand their feelings.

Focus group interviews are commonly used "to gain information about a specific or focused issue." (Marczak & Sewell, 2003). The intent of a focus group is to promote self-disclosure among participants on subjects participants find difficult to discuss. The focus group will uncover information on human perceptions, opinions, and thoughts that might not be disclosed on a written survey or questionnaire. Focus groups are an economical method to gather information. To determine the specific educational needs of this diverse, specialized, and often at-risk stepfamily audience, focus group interviews were conducted in one urban and two rural counties in Ohio.

Objectives

The objectives of the focus group interviews were to:

• Acquire information relative to stepfamily living,

• Develop relevant educational materials for local audiences,

• Design and format educational components that best meet the needs of these stepfamilies, and

• Determine how stepfamilies would like to receive information.

Sample

Accurate information on the current number of stepfamilies in individual counties is unavailable from the United States Census Bureau because this data is ambiguous and difficult to collect. A preconceived stratified sample is not possible because of the lack of United States Census Bureau data on stepfamilies. As a result, a sample of convenience was used to identify focus group participants. These voluntary participants received no compensation for their involvement in this study.

Stepfamilies in this study included individuals who were stepparents or had lived in a stepfamily. Methods of participant recruitment included promotional news articles and newsletters throughout three counties, contacts through social service agencies, and community members known to be in stepfamily relationships. Focus group questions were mailed to individuals who wanted to participate but were unable to attend. Focus groups were held evenings to accommodate the working schedules of the participants in the three counties.

A total of 28 individuals participated in the discussions; four individuals responded to mail surveys. Two individuals had previously lived in a stepfamily relationship. Eleven couples and four individuals were stepparents. Focus group composition included families with preschoolers, families with school-age children, families with teenagers, and current "empty nesters" with grown stepchildren. Families came from a mixture of socio-economic strata, including limited resource (25%) and middle income (75%). Families' place of residence included rural, non-rural, and urban. Participants were from stepfamilies formed for less than a year through 20 years.

Focus Group Questions

After reviewing stepfamily literature, agents identified common themes and devised questions to meet their objectives. A Family Life specialist reviewed and critiqued the questions. Agents refined, selected, and developed a list of seven open-ended questions. The Family Life specialist then validated these questions before using with the focus groups.

Following are the questions that were developed and validated.

1. Tell what it is like to be part of a stepfamily.
2. What has been your biggest reward?
3. What has been your biggest challenge?
4. What issues do stepfamilies face?
5. If you were looking for information to help you as a stepparent, what would be helpful?
6. What is something you wish you had known before you became part of a stepfamily?
7. What piece of advice would you give someone just starting out as a stepfamily?

Method

Focus groups were held on three separate evenings to accommodate employment schedules. The focus group team consisted of three Family and Consumer Sciences Extension agents; one served as moderator, one as recorder, and one as technical operator. Each focus group was asked the seven open-ended questions in the same sequential order. A tape recorder was used to collect the data. The recorder took notes. Tapes were transcribed. At the conclusion of each discussion, the agents reconstructed the discussions by reviewing the recordings and notes.

A written summary was prepared following each session, and a content analysis was prepared on the transcribed manuscripts. The Extension researchers individually read the manuscript transcripts to identify and validate common themes related to stepfamily living. They met as a group to compare analyses. As a team, they identified primary constructs for developing relevant educational materials, designing and formatting educational components, and determining delivery methods for these audiences.

Results

Primary constructs emerging from the focus group interviews were 1) new family themes, 2) children's issues, 3) issues dealing with former spouses, and 4) communication issues. These are summarized in Table 1.

Focus group participants identified preferred methods for receiving stepfamily information. They wanted information delivered in a form that could be quickly processed and used. Suggestions were made for both adults and children and data was classified into face-face contacts and independent learning. Table 2 summarizes findings.

Implementation and Evaluation

Using focus group findings, Extension agents developed community-based resources for stepfamilies. The development and implementation of asset-building resources for parents and children was fundamental in this process. Resources developed included:

• Blending Families newsletter,

• My Families and Me program and scrapbook for stepchildren,

• Women and Stepfamilies workshop,

• Essay contest for children in stepfamilies, and

• Stepping Stones workshop for parents.

These resources were the basis of implementation for stepfamily programming.

As a result of programming efforts, children changed their perceptions of stepfamilies and gained a greater understanding of their own individual situations. Newsletter usage evaluation surveys indicated participants gained parenting skills and knowledge about living in a stepfamily and became more sensitive to stepfamily issues. Participants ranked the Blending Families newsletter as the most useful source of stepfamily information above books, magazines, newspapers, friends, and family. Discussions in parent workshops dispelled myths, increased positive feelings, and encourage open communication among stepfamily members.

Conclusions

The issues revealed in the focus group interviews provided necessary insight into possibilities for needed educational components for both stepparents and stepchildren. Much of the focus group discussion issues paralleled the available stepfamily research findings. Programming must address the specific concerns and needs of stepfamilies and should include both children and parents. It is apparent that people want to make their new families work and that they are searching for helpful resources.

References

Bray, J. H., & Kelly, J. (1998). Step families. New York: Broadway Books.

Marczak, M., & Sewell, M. (1998). Using focus groups for evaluation. The University of Arizona CYFERNet. Retrieved March 11, 2004, from

Pasley, K. (Spring 1993). What do we know about the marital relationships for stepfamilies? The Stepfamily Association of America Quarterly. Retrieved March 18, 2004 from Stepfamily Association of America database.

Papernow, P. L. (1988). Becoming a stepfamily. Cambridge: Gestalt Institute of Cleveland Press.

Stepfamily Association of America. (1989). Stepfamilies stepping ahead. Lincoln: Stepfamilies Press.

Visher, E. B., & Visher, J. S. (1993). Stepfamilies: Myths and realities. New York: Citadel Press.

Refining Outreach to Woodland Owners in West Virginia--Preferred Topics and Assistance Methods

Daniel J. Magill
Forestry Research Assistant
West Virginia University
Morgantown, West Virginia
dmagill@wvu.edu

David W. McGill
Forest Management Extension Specialist
West Virginia University
Morgantown, West Virginia
dmcgill@wvu.edu

Rory F. Fraser
Professor of Forest Economics
Alabama A&M University
rfenton@hotmail.com

Introduction

As in most states in the eastern U.S., private individuals own the majority of West Virginia's woodlands. An estimated 250,000+ private landowners (Birch, 1996) own more than 9 million forested acres, which comprise about 78% of the forest land area in the state (Gillespie, 2002). The critical economic, social, and ecological roles that woodlands play in the health of our nation are reasons that federal, state, and private agencies spend significant time and money on reaching this segment of our population.

Federal programs that provide cost-sharing assistance for private woodland owners have been available over the past half-century (Zinn, 1995). Despite government incentives, we estimated that less than 15% of these landowners in West Virginia have received forestry assistance, financial or otherwise, in the last 10 years (Fraser & Magill, 2000). From an outreach perspective, the sheer number of landowners contributes to the dilemma for natural resources agencies and educational organizations when attempting to contact landowners and interest them in attending forest-based education programs.

With these challenges faced by natural resource agents with outreach responsibilities, it is crucial to offer private forest landowners the appropriate selection of forestry topics and assistance methods. Assistance methods that facilitate either education or direct application of forestry practices include financial assistance, workshops, and professional technical visits. Financial assistance may be in many forms, but one example includes federal cost-share programs that are designed to encourage stewardship practices on private property. Workshops attempt to educate landowners about forest management opportunities using classroom and outdoor demonstrations. Technical visits are one-on-one meetings between natural resource professionals and landowners, usually taking place on the landowner's property.

To help meet these challenges, we surveyed West Virginia landowners