The area of domestic labor including managing the home, ways to clean and keep up the home, and work load simplification has a long history in home economics-related Extension programs. A slightly different issue regarding work in the home has emerged in recent decades as more women have taken on greater responsibility for employment outside the home (Dolan, 1987), but most husbands have failed to balance that shift with a proportional increase in responsibility for the domestic labor (Thompson, 1991). Although a gradual increase in men's domestic labor participation has been reported (Gershuny, 1988), even among dual earner, childless couples, most husbands continue to do less than their wives (Marshall, 1990).

Family scholars anticipated that this imbalance would result in widespread negative emotion among wives (Goldner, 1988). Certainly, intense negative emotions have been reported by a some wives (Hochschild, 1989), but research has indicated that only about one out of three wives feel that the division of labor in their marriage is unfair (Benin, 1988) and even fewer report having negative emotions regarding the inequality in division of domestic labor (Gershuny & Robinson, 1988). Surprisingly, data from national samples have consistently failed to link negative emotions with domestic labor inequality (Booth, Johnson, White, & Edwards 1984).

This paper addresses what is referred to here as the domestic labor puzzle--that is, why do some women experience negative emotion regarding domestic labor inequality and others do not? To address this question, meanings associated with domestic labor are examined as a way to better understand possible connections between domestic labor division and emotional outcomes regarding that labor. The particular focus of this paper is on connections between the latter two dimensions: (a) meaning--regarding domestic labor, and (b) affect--in terms of emotional outcomes associated with that labor.

Three aspects of meaning regarding domestic labor as reported by wives are specifically considered in the research presented here: (a) self-identity, (b) equality importance, and (c) fairness. These three aspects of meaning are treated as dimensions, each of which may take on different possible values, so the pattern of domestic labor meaning for a given wife is contingent on her particular combination of meanings within the three dimensions.

Self-identity is the first dimension considered. It is defined as the extent to which a wife feels domestic labor is important to her sense of purpose, is a high priority, is a meaningful way to show she cares, is an essential function in her home, and a means of self expression. Despite recent changes in gender roles, it is still generally assumed that women will identify with domestic work as a part of who they are (0akley, 1974).

Equality importance, the second aspect of domestic labor meaning, is defined as the extent to which the wife considers domestic labor equality to be important. Equality deals with the relative contribution judged against an ideal standard taken to be a 50-50 split (Thompson, 1991). Although equity rules have been considered as a way to judge fairness (Scanzoni & Polonko, 1980), the importance of equality as an aspect of meaning does not seem to have been considered in previous research.

A third aspect of domestic labor meaning is fairness defined here in terms of the wife's perception of the degree of fairness in the division of domestic labor. Fairness has emerged as a salient variable in previous literature. Unfairness has been reported to correlate with negative emotion. Yet surprisingly few couples view lopsided labor division in their relationship as being unfair (Benin & Agnostinelli, 1988). Marshall (1990) found positive correlation between lack of fairness and negative emotions, but not between domestic labor inequality and fairness, or between domestic labor inequality and negative emotions.

Two additional measures were used to assist in verification analysis of the above three meaning variables. Thompson (1991) concludes that for many women it is the appreciation and responsiveness of others, especially husbands, that really matter in family work. Appreciation refers to the degree of grateful recognition; responsiveness refers to the husband's readiness to pitch in and help.

Meaning patterns among dual-earner, childless couples were chosen for examination in the research reported here to minimize issues associated with child care and unequal employment participation between spouses (Marshall, 1990). Data were obtained using a survey with items adapted from (a) Hochschild's (1989) research that lead to The Second Shift, (b) the National Survey of Families and Households (Center for Demography and Econology, 1988), and (c) additional items developed specifically for this study.

A snowball sampling technique was used (Chadwick, Bahr, & Albrecht, 1984), beginning with dual-earner couples with whom the authors were acquainted, and then expanded as respondents identified additional dual-earner, childless couples. Survey instruments were distributed in two areas; northern Utah and southern California. As additional potential respondents were identified, surveys were sent by mail with a personal letter of instruction and an invitation to participate. Only questionnaires completed by both spouses were eligible for analysis. Data collection was conducted between June and October 1991, and an 81.1 percent response rate resulted in 146 completed surveys.

The volunteer respondents qualified for this study if they were married, childless, and each spouse was employed or attending school in some combination to equal being out of the home "at least 35 hours each week." All the wives in the sample were employed to some degree; 68 percent worked full-time, the remainder had some kind of education/work combination.

In order to be more representative of the U.S. population a quota sample (Chadwick, Bahr, & Albrecht 1984) was selected from the 146 completed surveys. Quota selection was used to achieve an operational sample that was adjusted to more closely match the dual-earner couples from the National Survey of Families and Households (NSFH--a 1987-88 probability sample) on the basis of three parameters--age, education, and income with a discrepancy range of not more than 10 percent. After the quota sample was achieved, 118 surveys out of the original 146 qualified for the analysis. In comparison with the NSFH sample, the snowball sample was slightly younger (mean age 25.1 years versus the NSFH 27.5 years), had a lower mean income ($38,900 versus $41,800), and had slightly more years of schooling (4.37 versus 4.1, 4 = some college).

The measures for this study were developed in five groups: (a) demographics--wives' age, wives' education, and family income; (b) domestic labor division based on husband responses and wife responses regarding hours each of them typically spent per week in domestic labor; (c) wives' negative emotion regarding domestic labor; (d) wives' domestic labor meaning--self identity, equality importance, and fairness; and (e) wives' perception of their husbands' appreciation and responsiveness.

Data were analyzed using SPSS (Statistical Package for the Social Sciences) software, frequency distributions were examined for each variable, and five domestic labor meaning patterns/cluster groups were derived using cluster analysis based on the patterns of response to three standardized variables--self identity, equality importance, and fairness. Validity of the cluster solution was checked by testing for the presence of significant differences (ANOVAs) between the clusters on two external variables reported in the literature--appreciation and responsiveness (Aldenderfer & Blashfield, 1984).

An overview of the analysis performed to indicate the relationship between the three major variables is shown in Table 1. Each wife under study was placed into one of the five cluster groups. Then the level of inequality experienced and a measure of negative emotion experienced were calculated for wives in each of the five meaning cluster groups. For purposes of analysis, the five meaning groups were placed in ascending order according to the level of inequality experienced (very low, low, medium, high, and very high). Based on the literature of previous research, it was hypothesized that emotional outcome would not be correlated with level of inequality experienced. Rather emotional outcome was expected to be arranged in a scrambled order (e.g. illustrated in Table 1 as positive, negative, very positive, very positive, and very negative). This analysis was designed to ascertain if an understanding of the pattern of wives domestic labor meaning (the center variable Table 1) would serve as a coherent and insightful connection between the division of domestic labor (the variable on the left) and her emotional outcome (the variable on the right).

The analysis is organized around the five cluster group domestic labor meaning patterns (see Table 2). Each of the five cluster groups is labeled with a one-word description chosen to describe the labor division/meaning pattern for that cluster. The variables under focus in Table 2 are: (a)the percent of total sample size within each cluster; (b) the percent of wives reporting high domestic labor inequality (wife contributed more than 60% of the combined husband and wife domestic labor); (c) the meaning cluster components of self-identity, equality unimportance, and fairness, with a designation of L=Low when the cluster group score was below the entire sample fifty percentile score, and H=high--when the cluster group score was at or above the entire sample fifty percentile score.

For cluster A (labeled Egalitarian), a relatively low percent (18.2%) of wives reported domestic labor inequality, importance to self identity was low (L) indicating that the wives of this cluster did not consider domestic labor to be important to their sense of self-identity, equality unimportance was low (L) indicating that labor division equality was definitely important to the wives of this cluster, and fair division was high (H) indicating that division of domestic labor between them and their husbands seemed fair. In short, their division of labor life style and their pattern of domestic labor meaning seemed to be egalitarian. Note how a low percent of wives experiencing domestic labor inequality (18.2%) are matched with a low percent reporting high negative emotion (18.2%).

The domestic labor meaning pattern associated with this cluster adds further insight. Egalitarian cluster wives did not report high negative emotion associated with domestic labor because according to the three meaning components, things were going well -- equality was important to them and each felt that the labor division with their spouse was fair.

For cluster D (labeled Conflicted) wives indicated that their domestic labor arrangement was unfair (fair division = L), which seems to conflict with the rest of their response pattern--they did not consider domestic labor to be important to their self-identity (importance to self-identity = L), equality was not important to them (equality unimportance was H), and they did not report a high degree of domestic labor inequality in their marriages.

However, wives in the Traditional (cluster B) group experienced a high degree of domestic labor inequality (72.7%), yet they indicated that domestic labor was important to their self-identity, that their domestic labor division was fair, and that domestic labor equality was unimportant to them. The traditional group experienced minimal levels of negative emotion (13.6%). The Quasi-Traditional (cluster F) is quite similar to the Traditional Group in the fact that they experience higher inequality and their negative emotion is low. The only variable that is different is that domestic labor is not tied to part of their self-identity.

In comparing meaning patterns, traditional cluster wives perfectly contrast the unsynchronized (cluster C) wives, yet the division of labor within the two groups is very similar. Unsynchronized cluster wives and husbands seem out-of-step with each other. The husbands participate in domestic labor minimally as if their wives had traditional values when in fact quite the opposite is the case as indicated by the wives meaning pattern. Clearly, traditional and quasi-traditional wives experienced the least negative emotion and unsynchronized cluster wives experienced an enormous amount, with 62.5% of them reporting high negative emotion. With the measures of inequality, meaning patterns, and negative emotion that are presented for each cluster group in Table 2 it is possible to piece together the connection between domestic labor division and emotional outcomes.

On the inequality/negative emotion premise, it would be expected that the quasi-traditional, traditional, and unsynchronized cluster wives (all with higher percentages of inequality) would also respectively report an escalating percent of high negative emotion. However, this premise has not been verified in previous research (Hochschild, 1989) and is not borne out here either.

Instead of high negative emotion the quasi-traditional and traditional cluster groups have the lowest percent of wives (12.5% and 13.6%) reporting negative emotion with regard to domestic labor. Even though half of the quasi-traditional cluster wives were experiencing high inequality only one-eighth of them reported high negative emotion, a result that is more understandable in light of the fact that domestic labor division equality was unimportant to these wives and they felt their labor division was fair.

Compared to the quasi-traditional cluster nearly 50% more of the Traditional cluster wives (72.7%) were experiencing high inequality, yet only 1.1 percent more of them (for a total of 13.6%) reported negative emotion outcomes. No doubt this lack of response in terms of negative emotion can in part be accounted for by the fact that Traditional cluster wives were the only cluster group that indicated domestic labor was meaningful and important to their self-identity. These wives saw domestic labor as important to their "sense of purpose" and of "high priority." Equality was unimportant to them and, contrary to the domestic labor inequality/negative emotion premise, these wives felt that inequality in their own domestic labor division was fair.

The unsynchronized cluster group contains the highest percent of wives in the sample experiencing high inequality; that is, 87.6% or a 20% increase compared to the traditional cluster group. Yet the percent of unsynchronized cluster wives that reported high negative emotion was 62.5%; or a full 360% increase compared to the traditional cluster group. This tremendous outpouring of negative emotion is no doubt partially attributable to the high proportion of wives that were experiencing inequality but it was further accentuated by the negative meaning domestic labor had for these women. Even though equality was important to them (equality unimportant = L), they were experiencing a high degree of domestic labor inequality and domestic labor was not important to their self identity. Hence they felt a tremendous sense of unfairness and negative emotion.

The research reported here represents an attempt to move beyond linear analysis and look at what meaning domestic labor has in connection to inequality and negative emotions. When meaning patterns/cluster groups were taken into account, themes emerged that helped resolve the domestic labor puzzle and made visible connections between division of labor and emotions regarding that labor.

Five distinctive meaning clusters were identified: two that were somewhat traditional (clusters B & F), two that were more contemporary and egalitarian (clusters A & D), and one with tremendous inequality and high negative emotion (cluster C) but consisted of only a fraction of the sample population (13.6 percent). In short, each group's pattern of meaning seemed to logically connect that group's domestic labor division and emotional outcome. In this regard the domestic labor meaning patterns of self identity, equality importance, and fairness combined to solve a piece of the domestic labor puzzle.

Extension professionals can use this information to help provide insight for their clientele as they examine their own domestic labor division. As more women enter the workforce, they need to examine what meaning domestic labor has to them. This research could be used to visualize the meaning patterns/clusters and help them better understand what part domestic labor plays as a part of their self-identity, importance of equality and fairness.

Aldenderfer, M.S., & Blashfield, R.K. (1984). Cluster analysis. Newbury Park, CA: Sage Publications.

Benin, M. H., & Agnostinelli, J. (1988). Husbands' and wives' satisfaction with the division of labor. Journal of Marriage and the Family, 50, 349-361.

Booth, A., Johnson, D.R., White, L., & Edwards, J.N. (1984). Women, outside employment, and marital instability. American Journal of Sociology, 90, 567-583.

Center for Demography and Econology, (1988). National survey of families and households. Madison: University of Wisconsin.

Chadwick, B.A., Bahr, H.M. & Albrecht, S.L. (1984). Social science research methods. Englewood Cliffs, NJ: Prentice-Hall.

Darling, C. A. (1995). An evolving historical paradigm: from `home economics' to `family and consumer sciences'. Journal of Consumer Studies and Home Economics, 19, 367-379.

Dolan, E. M. & Scannell, E. (1987). Husbands' and wives' household work: Moving toward egalitarianism? Journal of Consumer Studies and Home Economics, 11, 367-299.

Gershuny, J. & Robinson, J. P. (1988). Historical changes in the household division of labor. Demography, 25, 537-551.

Thompson, L. (1991). Family work: Women's sense of fairness. Journal of Family Issues, 12, 181-196.

Gershuny, J. & Robinson, J. P. (1988). Historical changes in the household division of labor. Demography, 25, 537-551.

Goldner, V. (1988). Generation and gender: Normative and covert hierarchies. Family Process, 27, 17-31.

Hochschild, A. (1989). The second shift. NY: Viking Penguin Inc.

Marshall, C. (1990). Housework in dual-earner families: Does the division of labor make a difference in the quality of family life. Doctoral dissertation, Provo, UT: Brigham Young University.

Oakley, A. (1974). The sociology of housework. NY: Random House.

Scanzoni, J., & Polonko, P. (1980) A conceptual approach to explicit marital negotiation. Journal of Marriage and the Family, 42, 31-44.

Thompson, L. (1991). Family Work: Womens' sense of fairness. Journal of Family Issues, 12, 181-196.

Ohio 4-H in 1993 developed a comprehensive education program for K-2 or five- to eight-year-old children. The program and curriculum were based on the National 4-H, K-3 Youth in 4-H: Guidelines for Programming (National 5-8 Curriculum Task Force, 1991.) Further advances in the goals and philosophy of the program were conducted in 1996 that were consistent with the National Association for the Education of Young Children's position statement on developmentally appropriate practice in the primary grades (Bredekamp & Copple, 1997). The Ohio philosophy and system believed there should be a comprehensive educational plan that provides a total framework including a defined curriculum format, volunteer education, participation guidelines, and a flexible delivery system.

The goal of Ohio's five-to-eight-year-old program is to promote healthy development in children by enhancing life skills (social-interaction, self-esteem, physical mastery, making choices, and learning to learn) through developmentally appropriate learning experiences. Features of the program include short-term, success oriented, non-competitive, and fun activities based on a broad array of subject areas.

The program is unique in that it provides parameters as well as a defined framework for adults and youth volunteers to work within (Scheer, 1997). There is some flexibility, but the flexibility is kept to a minimum to maintain high quality and consistency across counties.

To evaluate the K-2 program, a stakeholder evaluation was developed. Stakeholder evaluations are vital for improving a program, indicating stakeholder expectations, and guiding evaluation objectives for the program under review (Lawrence & Cook, 1982). This type of evaluation measures individual perceptions of stakeholders who have a share in the success or failure of a program. Stakeholder evaluations help to modify or adjust a program to ensure it is meeting its goals. The survey gave respondents an opportunity, in an anonymous and confidential method, to voice their opinions about how to improve the program.

The purpose of the study was to learn the perceived value and acceptance level of the 4-H K-2 Program and the K-2 Curriculum. The data will provide information needed to improve the program by measuring stakeholder perceptions of: life skill enhancement, curriculum and program benefits, non-competitive activities; and improving the program through open-ended questions.

The sample population consisted of three stakeholder groups: 4-H agents/program assistants, program volunteers, and parents of participating children. Each group is a critical component in the success of the program; without their "buy-in" it would be impossible for it to succeed and be effective. Three surveys were developed with input from agents, volunteers, and state Extension faculty to assess stakeholder perceptions. Each survey was one page (front and back) for quick completion.

All 88 county Extension offices in Ohio received the surveys. The agents and program assistants were asked to complete the Extension Professional Survey and to randomly distribute surveys to program volunteers and parents of participating children.

The surveys consisted of demographic questions (type of group setting, ethnicity of self and children, number of children in group, age of children, etc.). There were five Likert items (strongly agree to strongly disagree) asking respondents whether they perceived the children improved in: self-esteem, making friends, making choices or decisions, learning skills, and physical skills (movement or coordination). Other questions asked whether the curriculum and program was beneficial for their children or group members, and were non-competitive activities best for young children. Finally, there were open-ended questions related to what the respondents liked most and least about the program and what suggestions they have to improve it.

Of the 88 counties in Ohio, 50% (44) responded to the survey. Thirty-six agents and 8 program assistants, 144 volunteers, and 277 parents returned completed surveys. The following descriptive statistics are percentages of those who responded according to each stakeholder group (that is, parents, agents, and volunteers).

Eighty-two percent of the parents, 81% of the volunteers, and 91% of the agents reported the curriculum as beneficial for the children. Eighty-six percent of the parents, 85% of the volunteers, and 98% of the agents/program assistants agreed or strongly agreed that non-competitive activities were best for the children. The stakeholders agreed or strongly agreed that overall the program was beneficial for children (91% of the parents, 90% of the volunteers, and 98% of agents/program assistants).

The respondents were asked to indicate if their children or 4-H members improved in the five life skill program objectives. On a Likert scale from "strongly disagree" to "strongly agree," the stakeholders reported that their children improved in life skills as seen in Table 1.

(Percentages are based on stakeholders responding as either "strongly agree" or "agree" that their children or members improved in that life skill area). *PA = Program Assistants

There were numerous positive and few negative comments about the program. Suggestions on ways to improve the curriculum and program included the following: "have more meetings so my home-schooler can be with other children," "lacks livestock activities," "keep the program separate from the older kids in 4-H," and "let children ride and handle horses like the older youth."

The results provided clear information that the stakeholders of Ohio's 4-H program believe it is beneficial and effective in improving life skills for five- to eight-year-old children. The parents, volunteers, and agents/program assistants perceived non-competitive activities were best for children. The research literature has empirically shown that children in this age group have a difficult time handling and understanding competition (Johnson & Johnson, 1989; Minuchin, 1977). Even though research has shown non-competitive activities are best for children, it is just as important for stakeholders in the program to accept and believe in this perspective.

Ohio's program was not largely supported when first implemented, based on agent feedback from volunteers and program observations. The current findings support that, over time, if an Extension program is grounded in research and well-structured, it will gain support and become an established state-wide effort. There is always room for continuous improvement, which Ohio is doing by addressing the suggestions for making it better. For example, additional activities and curriculum are currently under review and development and there have been additional activities added in the animal subject area, within the program parameters and philosophy (Scheer, 1997).

Other states could benefit from using stakeholder evaluations to determine the immediate concerns of the people directly involved in the success or failure of a program. The findings in a stakeholder evaluation contributes to the strategy of data triangulation in evaluation research (Reichardt & Cook, 1979). Regardless of the results, whether positive or negative, the data will help policy makers and program administrators make informed decisions for future program directions.

Bredekamp S., and Copple, C. (Eds.). (1997). Developmentally appropriate practice in early childhood programs. Washington, DC: NAEYC.

Johnson, D. W., & Johnson, R. T. (1989). Cooperation and competition: Theory and research. Edina, MN: Interaction Book Co.

Lawrence, J. E. S., & Cook, T. J. (1982). Designing useful evaluations: The stakeholder survey. Evaluation and Program Planning, 5, 327-336.

Minuchin, P. (1977). The middle years of childhood. Monterey, CA: Brooks.

National 5-8 Curriculum Task Force. (1991). K-3 youth in 4-H: Guidelines for programming. Families, 4-H and Nutrition, Cooperative State Research, Education, and Extension Service. Washington, DC: US Department of Agriculture.

Reichardt, C. S., & Cook, T. D. (1979). Beyond qualitative versus quantitative methods. In T. D. Cook & C. S. Reichardt (Eds.), Qualitative and quantitative methods in evaluation research (pp. 7 - 32). Beverly Hills, CA: Sage.

Scheer, S. D. (1997). Programming parameters for 5-to-8-year-old children in 4-H. Journal of Extension, 35(4).

Migrant farmworkers have been an element of Minnesota's agricultural community since the early 1800s, making up 60% of the farmworker labor force in the state. The majority are Chicano/Latino and come from southern Texas, with smaller numbers from California and Mexico. Migrants live in Minnesota each year from April through October, harvesting sugar beets, fruits, and vegetables, and working in canning factories and meat packing plants. Many travel with their nuclear and extended families, bringing children to maintain family unity. Most migrant farmworkers in Minnesota live in poverty.

Interviews with migrant farmworkers and service providers in Minnesota showed that diet-related diseases common to this population were obesity/overweight, cardiovascular disease, diabetes, and anemia (Thomas, Fang, Hones, Mgeni, & Rode, 1995). Contributory problems included lack of adequate housing and cooking facilities, poor food choices or habits, limited availability of fruits and vegetables, and lack of fluoridated water (Minnesota Department of Health, 1997). Others have also indicated that adequate refrigeration in migrant camps is generally problematic (Thomas, et al., 1995).

In Minnesota, a recent study of Chicano/Latino children including migrant families found that parents were aware that their children needed healthy diets, but lack of money prohibited them from providing adequate nutrition (Compean, 1994). Migrant children frequently have health needs that are not addressed because of their migratory lifestyle, poverty, poor education, and language barriers. Health problems include overweight, anemia, infectious diseases, dental caries, lead exposure, and immunization status (Minnesota Department Health, 1997).

In general, non-migrant rather than migrant children show an earlier independence related to food selection and preparation. Non-migrant children are more alone after school and caring for themselves (Crockett & Sims, 1995). Skipping meals, snacking on high energy but low nutrient foods, and eating foods away from home, especially at fast food restaurants are typical eating habits of non-migrant adolescents that are risk factors in the development of chronic disease as an adult. The prevalence of risk behaviors for children of migrant farmworkers related to adoption of less healthful food selection and preparation activities is not well known, but may be related to the length of time their families lived in the U.S. after immigration.

Extension nutrition education staff working with migrant farmworkers in Minnesota were concerned that young children often had major responsibility for meal preparation in the home because parent time away from the field meant lost income. They were also concerned about reports that many migrant farmworker families were purchasing food on a daily basis at nearby, higher priced convenience stores.

The first step in designing effective nutrition education programming for migrant farmworker children involves a study of current behaviors and knowledge upon which to apply a theoretical base. An understanding of non-migrant children's food selection and preparation responsibilities may not be directly transferable to a migrant audience.

The present study was conducted to investigate the understanding that migrant farmworker children have concerning nutrition concepts, and responsibilities they have for food purchasing and preparation within their socioeconomic and cultural framework. A richer understanding of their world and needs would increase the service community's effectiveness in providing nutrition education programming. The three primary objectives of the current study were to determine (a) whether children of migrant farmworkers assume major responsibility for food purchasing, meal planning and food preparation at a young age, (b) whether cooking and refrigeration facilities were adequate, and (c) what nutrition concepts need to be considered when teaching these children about planning meals or making food choices.

Semi-structured questions in individual interviews were developed to gather preliminary information for program and material development by the state Extension Service. Questions were written and reviewed by Extension personnel, service providers, other nutrition professionals, and educators indigenous to the target population for clarity, sensitivity, and face validity and revised prior to pre-testing.

Most children of migrant farmworkers lived in work camps close to fields, while others lived in nearby motels. The migrant camps are isolated, usually 5-10 miles from the nearest small town with a grocery store. The concrete block housing units typically contain one or two bedrooms and have gas camp stoves and refrigerators. Children were selected for interviews upon availability by age and gender in a consecutive manner as they arrived in communal locations throughout the time period that the interviewer was present in the camps. An adult guardian provided consent for the children to be interviewed.

Interviews were conducted privately in convenient communal locations in the camps, such as the laundry rooms or outdoor picnic tables. All interviews were conducted by a bilingual graduate student formally trained in interviewing techniques and with extensive teaching experience with children in Mexico and Guatemala. A bilingual Extension staff member indigenous to the population and well-known to the children was also present during all interviews to clarify questions and responses as needed.

Sample size was determined by the investigators as the interviews progressed. After interviewing about 20 children, the interviewer was hearing many similarities in responses without obtaining new or different information; therefore, sample size was limited to 22. The tape-recorded summaries were read by two other bilingual Extension professionals as they listened to the tapes to check for accuracy, minimize the interviewer's bias, and correct possible errors in translation of Spanish vocabulary and grammar. Consistent themes were identified based on the study questions. Children interviewed were from 9 to 12 years of age (mean age of 10.4+ or - 1.2 years) and about half were girls (n = 12). Most reported living outside of Minnesota for most of the year.

Responsibilities for Food Purchasing, Selection, and Preparation

Almost all children responded that their family shopped at a major supermarket for their main food purchasing. The shopping frequency was typically weekly with a few families shopping on a monthly basis. Children said they influenced the selection of food for their household by asking parents to purchase some types of groceries, mainly candy, sweets, or breakfast cereal, although some said they also request particular kinds of meat. The mother usually decided what kinds of food to purchase, with the father making some decisions occasionally. About half of the children said that there are foods they would like to eat but were not available to them because they cost too much. Meat was mentioned most often, followed by milk, cereal, and sweets.

From the interview responses, it was evident that young children (ages 9-12) were preparing at least one meal a day for themselves and siblings. The food of choice for the morning and evening meals was eggs. Other commonly prepared foods were: chorizo (sausage), pasta (macaroni and cheese, spaghetti), beans and tortillas, sandwiches, soups, and breakfast cereals. None of the children responded that they prepared frozen, pre-prepared convenience foods or foods that needed to be cooked in a microwave. All of the children stated that they had refrigerators at home. When asked about ways that foods can become "not safe" to eat, few children were able respond with common food handling problems that contribute to food borne illness in families.

The migrant children indicated that they made food choices based on what was available in the home or what their siblings preferred to eat, but were not the primary food purchasers for the household. They tended to be involved in food selection to a greater extent at the morning and noon meals. Children reported eating beans, tortillas, and soups which are staples of the traditional Mexican diet but also reported eating breakfast cereals, pizza, and ice-cream which have been documented as foods that are initially added to the Hispanic diet upon entry in the United States. Most children stated that they seldom ate at restaurants.

Nutrition and Health Perceptions

Migrant children had difficulty describing a healthy person with few making the connection between food and good health. Healthy meant being strong and having good teeth or being able to do whatever one wants. When asked what they needed to know to be healthy, few spoke of knowing about nutrition or healthful foods. Only a few children spoke confidently about foods that were high fat or low fat foods. Most considered candy or sweets to be high fat foods and said their parents did not talk about limiting fat in the family meals. Sugar was seen as bad because it was associated with excess calories. School was a major source of nutrition education, while several mentioned that their parents taught them about nutrition at home.

The extent of food purchasing and preparation responsibilities of the migrant farmworker children interviewed for the current study was not unlike that of non-migrant children in the U.S (Baranowski, et al., 1993). The earlier dependence on younger children for caring for themselves and siblings indicates the need for more extensive life skill education for all children.

When Mexicans immigrate to the United States, diets tend to be quickly fortified by more variety, but traditional methods of cooking, such as using the stove top methods of stewing or frying most foods, may be retained (Lang, 1992). The use of alternative cooking methods for youth may be an important focus for food preparation education if the availability of adequate cooking facilities allow for baking or broiling.

Dietary intake typically is negatively affected by adoption of American eating habits (Lang, 1992). However, the current study indicated that the frequent consumption of processed or fast foods that occurs with non-migrant children may not occur to the same extent for the migrant children interviewed. Nutrition knowledge among the children interviewed was lacking especially as it related to intake of fat and sugar. From the interview results, it was evident that the value or appreciation for more healthful eating habits, including low fat food preparation, appears to be needed for both migrant farmworkers and their children.

Given the food preparation responsibilities reported by children in this study, education about safe food handling practices is warranted. Basic nutrition concepts related to food selection for themselves and siblings is also needed especially as it relates to dietary fat and sugar. Several factors should be considered when implementing a nutrition education program for migrant farmworker children. It may be important to include foods that are commonly used in the migrant children's homes. Nutrition educators need to understand traditional food and health customs to provide culturally relevant nutrition education. Health education for migrant children and decisions regarding nutrition care and practices should be based on a "family" approach due to the importance of family in this culture (Morrison, Rienzo & Frazee, 1995).

Baranowski, T., Domel, S., Gould, R., Baranowski, J., Leonard, S., Treiber, F., & Mullis, R. (1993). Increasing fruit and vegetable consumption among 4th and 5th grade students: Results from focus groups using reciprocal determinism. Journal of Nutrition Education 25, 114-120.

Compean, M.C. (1994). La cara humana de la pobreza: Los ninos Chicanos-Latinos en Minnesota. (The Human Face of Poverty: Chicano-Latino Children in Minnesota), St. Paul: Chicano/Latino Advocacy and Community Empowerment through Research (HACER).

Crockett, S. J., & Sims L.S. (1995). Environmental influences on children's eating. Journal of Nutrition Education, 27, 235-250.

Lang, S. (1992). Understanding Hispanic diets. Human Ecology Forum, Cornell University, 7-10.

Migrant farmworkers and their families in Minnesota: Health and nutritional status and resources, economic contributions, collaborative resources and emerging issues. Report to the Legislature. St. Paul: Minnesota Department of Health 1997; 1-65.

Morrison, S. Rienzo, B., Frazee, C. (1995). Developing health education for Hispanic migrant preschool youth. Journal of Health Education, 26, 207-210.

Thomas, E., Fang, R., Hones, C., Mgeni, Y., & Rode, P. (1995). Bitter sugar: Migrant farmworker nutrition and access to service in Minnesota. St. Paul, MN: Minnesota Food Education and Resource Center, Urban Coalition.

Author's Notes: This manuscript is being submitted as the Minnesota Agricultural Experiment Station Publication No. 98-1-18-009 for the Project No. MIN-18-026. The work represented in this manuscript was funded through the Food Stamp Nutrition Education Program.

University Extension Master Gardeners have been utilized by all fifty states to help meet consumer demands for horticultural information (Barton, 1988; Guest, 1997; Norman, 1986; Roberts, 1982). Extension makes a significant investment in training these horticultural volunteers (Meyer & Hanchek, 1997; Ruppert, Bradshaw & Stewart, 1997). Understanding better who volunteers as a Master Gardener may be helpful in targeting training and management programs to their needs (Clary et al., 1998).

A survey was conducted of randomly selected current and former Missouri Master Gardeners to identify the demographics of volunteers attracted to the program, and to determine if Master Gardeners fit the pattern of volunteers in general, or if the program attracts atypical volunteers. Of the 417 surveys sent out, 282 responses were received for a 67.6% response rate.

From its inception in 1983, over 1,600 volunteers have been trained in the Missouri Master Gardener program at 32 sites around the state, and 1,050 were active when this article was written. The core course training program consists of 30-45 hours of classroom instruction, depending on location and instructor availability. During the first year, after completing core course classroom instruction, Master Gardener trainees are required to donate hours of service, conducting educational horticulture programs equivalent to their training hours to their local extension center in order to become certified Master Gardeners. In succeeding years, active Master Gardener status is maintained by donating 20 or more hours of volunteer time.

Sixty-eight percent of survey respondents indicated they were presently active in the program while 32% said they were inactive. When asked the extent of their involvement, 22.4% indicated they had contributed no volunteer hours during the past year; 20.9% had volunteered up to 20 hours; 31.4% had volunteered between 20 and 40 hours; and 25.3% had contributed over 40 hours of volunteer Master Gardener time. Females accounted for 65% of respondents and males 35%.

Results presented in Table 1 indicate that Missouri Master Gardeners were slightly older than Master Gardeners in metropolitan Atlanta, GA (Rohs & Westerfield, 1996) or San Antonio, TX (Finch, 1997). Because age categories in the various studies were not identical, direct comparisons were not always possible. Nearly 60% of Missouri Master Gardeners were 50 or older, while only 55% of Atlanta Master Gardeners fell into the same age brackets and only 48% of San Antonio Master Gardeners were 45 or older. However, in Missouri, those in their 40's comprised the largest demographic group, and nearly equal numbers of respondents were represented in the 40-, 50- and 60-year-old age brackets.

The majority of Missouri Master Gardeners were married with children (Table 1). Over 95% had been married at some point, and 82.5% were still married. Fewer than 5% of Missouri Master Gardeners were single, compared to 16% of Atlanta Master Gardeners in this category (Rohs & Westerfield, 1996). Missouri Master Gardeners were also more likely to have children than Atlanta metropolitan Master Gardeners (86.2% vs. 79%). Table 1 indicates the age distribution of children of Master Gardener volunteers. Totals are greater than 100% because respondents may have children in more than one age bracket. From the data it is evident that most children of Master Gardeners were adults, whereas very few were of preschool age.

Missouri Master Gardeners were well-educated (Table 2). All were at least high school graduates and nearly 90% had some schooling beyond the secondary level. Over 50% had at least a college degree and 22% had post-graduate work beyond the baccalaureate level.

Missouri Master Gardeners were moderately wealthy. One-third had a household income of $60,000 or greater, and nearly another one-quarter had a household income between $40,000 and $60,000. Only 10.3% came from households with less than $20,000 income. In comparison, Rohs and Westerfield (1996) reported 12% of metropolitan Atlanta Master Gardeners with an income of less than $20,000, 36% between $20,000 and $50,000, and 52% with more than $50,000 income. Finch (1997) reported average income levels by zip code of residence in San Antonio. According to his findings, 10% lived in low income neighborhoods (under $15,000), 23% in moderate income neighborhoods ($15,000 to $24,000), 24% in middle income areas ($24,001 to $36,000), and 43% in upper income communities (over $36,000).

The largest occupational group of Missouri Master Gardeners was retired, at 26.9% (Table 2). This corresponded very closely with data from Rohs & Westerfield (1996), who found 29% of Atlanta Master Gardeners were retired. The second largest occupational category was homemakers at 14.6%, substantially lower than the 24% for this category reported from Atlanta. Occupational categories accounting for approximately 5 to 10% of the total each were, in order: horticulture/agriculture, professional, trade, medical, sales/service, business/commerce, and education. Occupations falling into the "other" category were government, student, arts, unemployed, and volunteer.

Missouri Master Gardeners were more likely to be from small towns or rural areas than from medium or large cities (Table 3). Of the respondents to the survey, 53.9% lived in rural areas or towns under 25,000 population, 24.3% lived in cities between 25,000 and 250,000 population, and 21.7% lived in large cities, based on the zip code of their residence. This means Master Gardeners are over-represented in small communities and medium-sized communities and under-represented in large metropolitan areas. According to 1990 census data, only 10% of the state's population lives in communities under 25,000; 7.7% live in cities with a population between 25,000 and 250,000; and 82.3% of Missourians live in metropolitan areas over 250,000.

Master Gardeners tend to be long-term residents of their communities. Of the survey respondents, 57.2% had lived at their current residence for more than 10 years, and 24.3% had lived there between 5 and 10 years. Only 18.5% were new residents of less than 5 years. This compares to a more mobile Master Gardener population in Atlanta (Rohs & Westerfield, 1996), where the percentages were 42% for those more than 10 years, 31% for those between 5 and 10 years, and 27% for residents under 5 years at their present location.

Missouri Master Gardener volunteer demographics fit the pattern of volunteers in general as reported by Smith (1994). He stated that long-term residents, those from smaller communities, and those with higher education and income levels were more likely to be volunteers than new residents, those from large communities, or those with less education or low income levels.

Knoke & Thomson (1977) related life stage to volunteerism. They found that unmarried persons under 40 years of age with no children at home, young parents with school age children, and older parents (over 40 years of age) with children of any age were more likely to volunteer than were young married people under 40 with no children, young parents with pre-school children, older couples over 40 with no children in the home, or singles over 40 with no children or spouse in the home. This pattern does not hold true for Missouri Master Gardeners.

Demographic data proved to be a poor predictor of intent to continue volunteering in the Master Gardener program. When asked to respond on a Likert scale of one to seven, "Based on your experience, how likely are you to volunteer for the Master Gardener program in the future?", no statistical differences were noted in responses by those of various ages, relationship status, income level, occupation, level of education, number of years at current residence, or number of years active in the Master Gardener program.

However, those presently active and those with greater hours of volunteer service in the past year were more likely to respond positively to the question. In addition, females were more likely than males to indicate a stronger intent to continue volunteering in the Master Gardener program. Therefore, demographics alone can not be used to predict continued involvement as a Master Gardener volunteer.

Barton, B. (1988, October-November). Becoming a Master Gardener. Flower and Garden, 32: pp. 52, 58-59, 64-65.

Clary, E.G., Snyder, M., Ridge, R.D., Copeland, J., Stukas, A.A., Haugen, J., & Miene, P. (1998). Understanding and assessing the motivation of volunteers: A functional approach. Journal of Personality and Social Psychology, 74(6): 1516-1530.

Finch, C. R. (1997). Profile of an active Master Gardener chapter.HortTechnology, 7(4), 371-376.

Guest, M. (1997, November-December). Master Gardeners. National Gardening, 20(6): 50-53.

Knoke, D., & Thomson, R. (1977). Voluntary association membership trends and the family life cycle. Social Forces 56(1): 48-65.

Meyer, M.H., & Hanchek, A.M. (1997). Master Gardener training costs and payback in volunteer hours. HortTechnology, 7(4): 368-370.

Norman, C. (1986, November). America's hardest working garden volunteers. National Gardening, pp. 48-50.

Roberts, R. (1982, January). Master Gardeners: Helping others to grow. The Family Food Garden, pp. 36-43.

Rohs, F.R., & Westerfield, R.R. (1996). Factors influencing volunteering in the Master Gardener program. HortTechnology, 6(3), 281-285.

Ruppert, K.C., Bradshaw, J., & Stewart, A.Z. (1997). The Florida Master Gardener program: History, use and trends. HortTechnology, 7(4), 348-353.

Smith, D.H. (1994). Determinants of voluntary association participation and volunteering: A literature review. Nonprofit and Voluntary Sector Quarterly, 23(3), 243-263.

"Learning by doing" has been the fundamental principle of 4-H since its inception. Projects are a major curriculum emphasis. Since 1912, projects have diversified from the basic corn, pigs, tomatoes, flowers, sewing, and canning topics to more than 100 project areas (Extension Committee on Organization and Policy,.1985). In the West Virginia 4-H program, a project is defined as a "method for teaching girls and boys many new skills. A variety of topics is offered. Members share in setting goals, making decisions, learning and evaluating" (4-H Volunteer Visions, 1996, p.2).

Project completion is defined by a three-fold process; a project exhibit as specified by a particular project, a completed project booklet, and a 4-H activity record (Division of Family and 4-H Youth Development, 1996b). Project completion is frequently used to determine awards and recognition relative to individual 4-H member's progress.

Each year, many questions arise regarding project selection, content, usage, costs, completion, and how this educational methodology for learning is beneficial to youth participants. Demonstrating positive results, however, has been difficult, and reported advantages of participation are often more suggestive than definitive.

This baseline study was designed to gain information on project completion of the project areas of animal science and food preparation in 1996-1997. This information will be useful to Extension personnel and local leaders in adjusting 4-H programs to more effectively meet the needs of youth. In addition, information obtained may promote further study to provide a practical approach in counseling youth relative to joining and participating in specific 4-H projects and activities.

Data collected in this study are baseline for 4-H Animal Science and Food Preparation project areas for 1996-1997. New projects were added in 1996-1997 and are not consistent with previous curriculum. Therefore, the results of this study do not generalize to other project areas or to previous studies. Terminology and semantics of "project completion" have very limited identification in current literature. In addition there are, by policy, no standards or requirements for 4-H membership that an individual must complete a project.

Project completion has been an area of interest and concern for a long time. In 1930, project completion in West Virginia was about 50%. With a concerted effort, project completion was increased to 72% by 1940, and by 1946 was 79% (Rapking, 1980). Snyder and Rogers (1986) reported that project completion rate in 1960 in West Virginia was 77%. A study by Snyder and Rogers determined a 58% rate in 1986.

Project completion as a statistic is of little consequence. In dealing with the question of project completion, there are two fundamental questions: (a) Why is project completion important? and (b) How can project completion be achieved? (Rapking, 1980)

In answering the first question, what is important is what happens to a young person who joins 4-H. Youth development is the mission of 4-H and allows individuals to acquire knowledge and life skills that enable them to become productive citizens and catalysts for positive change to meet the needs of a diverse and changing society (Divsion of Family and 4-H Youth Development, 1996b).

Helping youth become capable, contributing, and caring members of society requires an understanding of youth and their basic needs. Some basic needs identified are: (a) youth want to belong. This helps them grow and establish feelings of personal worth gained from the value that others place on them; (b) youth want to achieve. Children need tasks that are challenging but within their reach, and they need to know that their efforts are worthwhile and appreciated; and (c) youth want to become independent. They need to know that someone cares despite their shortcomings (Washington State University Cooperative Extension, 1994). Youth need to develop a positive view of themselves and their relationship to the world in which they live. If they can view themselves as capable individuals who can deal with daily challenges and have a realistic understanding of their abilities, they have a greater chance for success.

Project completion is also important because youth need to have the experiences of committing themselves to a challenging task and the reinforcement of successfully completing the task. It seems to be easier for people to start things than to complete them. Farmers only partially adopt many innovations. Families begin nutritional changes, but have trouble seeing them through. Communities begin a development process, but many lose energy and interest along the way, and the process languishes. What young people learn about seeing things through to the end will affect what they do as adults.

To address the question of how project completion can be achieved, youth educators (both volunteer and paid staff), must choose teaching techniques that will help 4-H members to learn, while incorporating activities of listening, seeing, and doing. Rapking (1980) described a general strategy which included being sure that the 4-H member and the project are compatible. Project selection requires that parents and leaders work closely to help the youth assess his or her abilities and resources as well as interests in selecting a project.

When the task is completed it is important that parents and leaders help the youth assess how well he or she has done and to feel good about what was accomplished. This does not mean that every child will win first prize or should expect to. It does mean that, with appropriate support, every child has the potential to be successful in advancing his or her skills and producing a product of which they can be proud.

The habit of seeing things through to the end most likely begins in childhood, so it's particularly important to understand factors that affect completion of 4-H projects. Many youth complete none of the projects they select, while others may complete one or more.

Scott, Clark and Reagan (1990) conducted a study designed to identify factors that influenced 4-H clothing project completion. An analysis of reasons for project completion in one project can provide useful information for leaders and agents in other project and program areas. Findings of the study were that both parental encouragement and role models were significant factors affecting project completion. Of the 83 youth studied, 48% were encouraged to complete a project by parents, and 69% had been praised by parents for doing a good job. Role models tend to be a strong influence on youth.

Leadership also proved to be highly significant in clothing project completion. Local leaders were reported helpful to project completion by 47% of the youth. A higher percentage (69%) reported that the 4-H agent was helpful in project completion. Youth who were more aware of 4-H clothing opportunities were more likely to complete a project. Incentives proved to be significantly correlated with project completion.

Scott, Clark, & Reagan (1990) also concluded that specific factors influence project completion among 4-H youth. Intervention by Extension agents and parents can increase success. Educating parents about their influence on the level of achievement reached by their children in 4-H projects can lead to more youth participation and completion of projects. Involvement of parents as leaders is an ideal way to increase awareness of the 4-H program. This study pointed out that a high percentage of youth depended on their 4-H agent for help in project completion rather than their local leader. Ideally, local leaders help youth to complete projects, thus allowing agents more time to train more leaders. Therefore, special efforts must be made to find people genuinely concerned with leading the 4-H projects and helping youth understand the leader's role is to help with projects.

Evidence cited by Scott, Clark & Reagan (1990) showed that members took the clothing project to develop their sewing skills. Members viewed learning to sew and receiving praise from their parents as incentives. However, the members discovered the project also included competition and record keeping, factors that may not be strong incentives for project completion. Perhaps projects could be modified to emphasize doing rather than evaluating and competing. In any case, all goals should be identified in the presentation of projects to potential 4-H members. This study indicated the importance of factors that encourage and support youth in completing and following through on what they start.

Youth research supports the findings of the Scott, Clark, & Reagan study (1990). Jenson (1982) found that parental encouragement seemed to be the most potent reason for joining 4-H. Weber and McCullers (1986) found that 4-H professionals selected parental involvement as the item needing most emphasis in 4-H programming. Whether parents or other adults serve as leaders, the need exists for more leader training and active involvement with club members.

Stephens (1983) found that the three major reasons for failure of youth groups were absence of a leader, lack of commitment, and need for leader support. Coward (1978) and Culbert (1983) showed that publicity and awareness also affect participation. Once members decide to participate in an activity, leaders and agents must understand the recognition members are seeking through participation. Adults need competence in effectively using incentives and recognition when working with youth.

The indirect target population for this study included 4-H members enrolled in animal science and food preparation projects during 1996-1997. Their enrollment, selection and completion of projects were recorded and maintained by the direct target population, which included the agent responsible for 4-H in each county.

The descriptive method of research using the inquiry form technique was utilized. Information was gathered through a 4-H Project Review Summary Form developed by the investigators. This method of research was deemed appropriate because of its ability to describe the current status of a problem, to become familiar with phenomena, to gain insights, and to describe the characteristics of a group or situation.

Following a review of literature, a 4-H Project Review Summary Form was developed to gather data from Extension agents responsible for 4-H in regards to the project enrollment and completion of animal science and food preparation projects. At the deadline date, 42 counties or 76.4% had returned the project review summary. Data were organized and analyzed to indicate total number of projects youth were enrolled in, number completed, and percentage completion. A summary table of the data was constructed.

Each year many questions arise regarding projects and completion rates in the West Virginia 4-H Program. This project review of the 4-H Animal Science and Food Preparation projects was undertaken to gain information on the completion rate of these respective projects. This information may be useful to Extension personnel and local leaders in adjusting 4-H programs to more effectively meet the needs of youth. In addition, information obtained may promote further study to provide a practical approach in counseling youth relative to joining and participating in specific 4-H projects and activities (see table 1).

Data in Table 1 illustrates the project information for the Animal Science project areas for the 1996-1997 4-H year.

In the animal science area, new project curriculum was introduced in the beef and dairy subject matter areas for the 1996-1997 4-H year. The new North Central juried curriculum (Bite Into Beef 1, On the Mooove Beef 2, Leading the Charge Beef 3, Dig Into Dairy 1, Moooving Ahead Dairy 2, and Leading the Way Dairy 3) is designed so that each project book contains activities for three years.

The 4-H'ers must complete at least seven achievement level activities each year and if enrolled with an animal they need to select beef heifer, feeder calf, market steer, or dairy record guide to accompany the respective project. If enrolled without an animal, 4-H'ers are to consult with their Extension agent regarding usage of the self-determined project as a resource to complete the North Central curriculum. Data indicate project completion rates in the beef areas ranged 66.96% to 85.83%. In the dairy project area, the completion rates ranged from 73.68% to 91.67%.

Project leader training was conducted at the county level upon request and at state events such as Volunteer Leaders Weekend to introduce the new curriculum and provide technical support for working with the 4-H youth.

The turkeys project book was revised for the 1996-1997 4-H year. Six out of eleven or 54.54% of the 4-H'ers completed the project. No project training was conducted in this project area.

Project data are illustrated in Table 1 for other animal science project areas in which youth were enrolled during the 1996-1997 4-H year. An overall project completion rate for the animal science area was 71.8%.

In food preparation, information was based on the usage of a nationally juried food curriculum purchased from Purdue University. Four age-graded manuals, entitled "Six Easy Bites," "Tasty Tidbits," "You're the Chef," and "Foodworks" address healthy food selection, smart food purchasing, food preparation, food safety, food preservation and food careers. "Six Easy Bites" (Level A) and "Tasty Tidbits" (Level B) are each designed to be used for two years. "You're the Chef" (Level C) and "Foodworks" (Level D) are designed to be used for three years.

Information was also collected on two additional projects: "Fit It All Together I" and "Fit It All Together II." These projects have been used in West Virginia for a number of years. Their use was discontinued at the end of the 1997-98 4-H year. Data were collected on the number of members enrolled in each project and the number of members completing a project. Percent completion rates were determined (see Table 2).

It is interesting to note that the completion rates (60.82% to 61.00%) are approximately the same for youth ranging from approximately nine years of age to approximately 15 years, when enrolled in projects using the new manuals. Older youth enrolled in "Foodworks" reported a somewhat lower rate of completion (53.33%).

Data from the two projects that have been in use for a number of years also present interesting findings. "Fit It All Together I" had a high enrollment but a low rate of completion (37.52%). The reason for the low completion rate may be due to the manual being used in a school classroom setting rather than a club setting. The classroom setting may have provided less individualized supervision than was available in the club setting. Finally, "Fit It All Together II" had the lowest enrollment of any of the Food Preparation projects. However, it had the highest completion rate (74.07%) of all projects.

This was the first time food preparation project manuals designed for multiple year enrollment were used in West Virginia. While concern was expressed when the projects were introduced, there were many positive comments made as the program year progressed. Follow-up study needs to be conducted on the number of years each manual is actually used by individual youths and if project interest is sustained, determined by project completion rates. Project leader training for use of the new project manuals was conducted at the county level when requested and at a statewide in-service training session. Additionally, the state nutrition and health specialist was available for face-to-face and telephone consultation as needed. An overall completion rate for all Food Preparation projects was 62.58% for the 1996-1997 4-H year.

This study was designed to gain information on project completion in the 1996-1997 4-H animal science and food preparation projects. A need exists for further study to determine and understand factors affecting completion. In addition, there is a need to define project completion and its importance in providing a viable educational program for 4-H youth. Whether an exhibition at the fair or a project display makes a completed project are valid questions that need to be answered by youth educators. In addition, youth educators need to determine if youth performing a certain number of learning exercises to achieve a subject matter expertise, based on individual goal setting, is project completion. Completion rate could also be one measure for evaluating project curricular content and project support by leaders and/or parents to increase the achievement of the youth.

Coward, R. (1978). Greater awareness -- Extension's key to program success. Journal of Extension, (16) 11-17.

Culbert, D. (1983) Factors contributing to nonenrollment of 4-H club members in Southeastern Florida. Unpublished master's thesis, Gainesville: University of Florida.

Division of Family and 4-H Youth Development (1996a). Glossary of 4-H terms and understanding youths. (fact sheet) 4-H Volunteer Visions. Morgantown: West Virginia University Extension Service.

Division of Family and 4-H Youth Development (1996b). West Virginia guide to 4-H projects. Morgantown: West Virginia University Extension Service.

Extension Committee on Organization and Policy (ECOP) Subcommittee on 4-H. (1985). Extension's 4-H: Towards the 90's. Extension Service, United States Department of Agriculture. Washington, DC: Author.

Jenson, G. (1982). 4-H winners: What do we know about them! Journal of Extension 20, 13-17.

Rapking, M. (1980). Project completion. In West Virginia University Extension Service, West Virginia guide to 4--H projects. Morgantown, WV: West Virginia University.

Scott, D. H., Clark, V. L., & Reagan, S. (1990). Helping participants complete what they start -- Factors affecting 4-H project completion. Journal of Extension (On-line), 28. Available: gopher://gopher.ext.vt.edu:70/00/joe/1990fall/a6

Stephens, W. (1983). Explanations for failures of youth organizations. (Nova Scotia, Canada Research Report) in Scott, D.H. & Reagan, S. (1990). Helping participants complete what they start--Factors affecting 4-H project completion. Journal of Extension, 28(3), Available on-line at www.joe.org

Snyder, G. and Rogers, R. (1986, April). Status report of 4-H completion rates 1984-1985 4-H Year. Paper presented at the annual meeting of the West Virginia Association of Extension 4-H Agents, Wheeling, West Virginia.

Washington State University Cooperative Extension Service (1994). Leaders R Us Publication # EM4872. Pullman, WA: Author.

Weber, J. A., & McCullers, J. C. (1986) The blue ribbon: An American way of life. Journal of Extension, 24 (Fall), 20-22.

One popular technique for obtaining information on human knowledge, attitudes, behavioral preferences, and similarities or the lack of them is the inclusion of Likert-type (for example, 1 = strongly disagree, 5 = strongly agree) or dichotomous (such as, yes/no) scales in survey questionnaires. Frequency analysis, t-test, and measures of central tendency are the traditional statistical methods for analyzing survey responses (Santos, Lippke & Pope, 1998). However, such procedures do not account for correlation occurring at and/or between scale level responses. This leaves out the more important attribute of being able to detect and evaluate unobservable patterns. From such patterns, one is able to describe and explain behavioral traits shared within and/or uniquely associated with some groups of respondents.

One approach to analyzing subjective perceptions, to gain insights from survey responses, is through factor analysis (Kim and Mueller, 1978). Factor analysis is a statistical variable reduction procedure, which extracts a small number of latent variables or "constructs" from among a larger set of observed variables. This paper discusses factor analysis in SAS(R) and proposes its use as an additional statistical test for Likert-based surveys in Extension. (NOTE: Common factors, component, and constructs are used interchangeably in this paper.)

The terminal solution to factor analysis is achieved through a series of steps that involved the use of several PROC FACTOR runs which can be executed together as one program. Typical procedure output would include:

Simple Statistics and Table of Eigenvalues

Once specified as a procedure of choice, PROC FACTOR automatically generates simple statistics and a table of eigenvalues (discussed later). This part contains the information on the relative sizes of variance accounted for by each extracted component.

Extraction of Initial Factors

For new users of factor analysis, the use of the maximum likelihood method option facilitates the extraction of common factors and provides a significance test for determining the number of factors to retain (Hatcher, 1994; SAS Institute Inc., 1985). There are alternative methods, such as the use of the NFACT= option, to initial common factor extraction.

Rotation to Terminal Solution

Very seldom will common factors extracted during the initial run have a clear-cut loading of observed variables on them. Sometimes, a number of observed variables will have two- or three-way moderate loading, making it difficult to interpret the factor pattern generated by PROC FACTOR. In such cases, a remedial procedure referred to as rotation is used to effect a linear transformation such that the variable loading in one construct is maximized while minimizing the loading of the same for all the others. A rotated factor pattern usually takes on a simple structure since transformation minimizes multiple loading. Based on the number of variables that loaded and the simplicity of resulting structure, one can then tentatively retain selected common factors. At this point, any construct that does not meet the minimum requirement for loading of at least three variables is dropped from the analysis.

The three key determinants for retaining a certain number of common factors are the position of the factors in the SCREE plot, the proportion of variance accounted for by the individual factor, and overall interpretability of all retained factors.

Position in the Scree Plot

"Scree" is a word used to describe loose stones or rocky debris at the base of a hill or cliff. In factor analysis, a scree plot graphically groups factors, which makes it easy to separate the retainable constructs from those that are not useful. Groups of factors tend to separate because a "break" or an abrupt jump in eigenvalue, which is the amount of variance that is accounted for by a given factor, occurs. The larger the eigenvalue the more meaningful the common factor is. Consequently, the process facilitates identification of common factors eligible for retention. Since more than one break can occur in the plot, decisions based on scree plot position are usually reinforced with the use of the other two determinants.

Proportion of Accounted Variance

The hierarchical position of factors in the table of eigenvalues is determined by the proportion of common variance in the data set accounted for by the individual factors (Table 1). The intersection of the items labeled "Proportion" in the table and the factor number on top gives the amount of variation attributed to that particular factor. There is no rule on the extent of contribution a common factor needs in order for it to be retained. Arbitrary values of at least 10% for individual components or 70-80% of the total percent of variance are commonly used.

The following are the test criteria for interpretability and how they can be satisfied by candidate component factors:

1. Minimum of three variables loading per factor:
Initial extraction is usually sufficient to generate a good number of meaningful constructs. However, if there is a failure to come up with an acceptable number of constructs, then using the NFACT= option is an alternative approach. The option forces the procedure to extract a user-entered number of factors. Another option is to add more relevant question items (specifically targeted to constructs that did not meet the minimum loading requirement), re-administering the survey, and then running factor analysis again.

2. Simplicity of structure:
All input factors loading on to a specific construct should exhibit one-way moderate to high loading (coefficient of .40 or greater) and very low complementary loading (ideally approaching zero) on other constructs. This is usually referred to as "having a simple structure."

3. Variables that loaded high on each construct should subscribe to the same concept that is distinctly different from those shared and measured by the variables supporting the other constructs.

To name a construct is to identify all variables that loaded high on it, and then looking at the predominant common theme, concept, or content that each of the variables has contributed. The process of attaching a meaning to a retained factor, as related to the objectives and science of the study, is called "interpretation". For a successful interpretation, all observed variables that loaded highly on a particular construct should share the same thematic or conceptual perspective. Such conceptual domain must be distinctly different from the dimensions addressed by the variables loading highly on the other constructs.

A typical tabular presentation of results of factor analysis would include (a) a list of loading of the rotated factor pattern with component number and labels as headings, (b) a list of the final communality estimates (squared multiple correlations for predicting variables from the estimated factors) indicated by "h2" heading, (c) the questionnaire items aligned with their corresponding loading and "h2" values, and (d) component names (optional). Usually the table is footnoted with the total number of respondents providing valid responses, and the rating scale used. Putting Cronbach's alpha (Cronbach, 1951) coefficient and values of the common variance accounted for by each component is also desirable. A sample presentation of result from an actual survey is shown in Table 2.

Under traditional survey analysis, the researcher would have been satisfied having frequency analysis done on the survey total of 23 Likert-type variables. It is from such frequencies that the researcher would have deduced the relative importance of each variable. The higher the frequency count on a certain issue, the more popular is the issue to the greater proportion of the respondents. To interpret the result, the researcher would have to rank each observed variable in decreasing order of frequency, and then devote the discussion to the first three or five high-ranking variables. For numeric variables, correlation of observed variables with demographic variables would have been done at this point.

However with factor analysis and using the information from the table above, one is able to identify three major areas of concern that impact all the respondents, namely: (component 1) government subsidies, (component 2) government regulations, and (component 3) food safety. In the process, factor analysis had detected and eliminated redundant variables (which measure the same construct as the other observed variables) and only retained those which effectively influence the three extracted components. From here on, the three components can now be used as inputs to predictive models or as benchmarks to developing indices for measuring social and/or behavioral attributes on surveys of similar nature.

There are other useful implications in this exercise. One could have used only the 12 observed variables (questions) that loaded high on the three components and still come up with the same conclusion as if all 23 original Likert-type variables had been used. Also, while the example looked at a 3-component model in our example, one should not hesitate to explore 2-, 4- or 5-component models, which may be more appropriate for some other types of surveys.

Instances of a specific variable behaving against expectations, such as failing to measure an attribute that one intended it to measure, should serve as a signal to investigate the possible cause(s) of the unexpected outcome. Questionnaire design and consistency of scale usually cause such an error. Indeed, the power of factor analysis lies on the iterative fine-tuning that one does while using the procedure. It is through such persistence that a researcher improves his/her chance of uncovering the hidden dimensions of the constructs that he/she sought to identify and measure in a survey.

Finally, the task of interpretation is easy when the criteria discussed earlier have been satisfied. Once the decision is made to retain a set of constructs, the researcher should be able to intellectually synthesize and describe the common thread that binds all the variables involved in each construct, and relate them to the objective(s) of the survey. In the end, it is the researcher's subject matter expertise, professional experience, and his/her interpretive ability that determine the utility of the set of component factors that he/she chose to retain.

Factor analysis has been available for use for decades but surprisingly few people design their surveys to be amenable to the use of the procedure. The most glaring deficiencies of many surveys are inadequate sample size, using too many scales, and an insufficient number of Likert-type variables allocated to each targeted construct. With the advent of computers, the availability of easy-to-use software, and the potentially useful information that can be gained from using the procedure, the use of factor analysis in Likert-based Extension surveys should be encouraged.

Exploratory data analysis is the most popular application of factor analysis but some use it to iteratively refine and confirm their models in the light of new data or current research. Others use the procedure as an intermediate process to develop indices designed to measure attributes that could not be reliably predicted by the original variables. Factor analysis is a powerful analytical tool and using it would certainly benefit and enhance the data processing capability of any Extension program.

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Santos, J.R.A., Lippke, L., & Pope, P. (1998). PROC FACTOR: A tool for extracting hidden gems from a mountain of variables. Proceedings of the Twenty-Third Annual SAS Users Group International Conference. (pp. 1330-1335). Cary, NC: SAS Institute.

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Data for this paper were derived from the "1994 National Agricultural and Food Policy Preference Survey" of Dr. Lawrence Lippke (Texas Agricultural Extension Service) and Benny Lockett (Cooperative Extension Program, Prairie View A&M University).

This article is online at http://www.joe.org/joe/1999october/ent-rb.html.

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