Back to the Kitchen: National Childhood Obesity Awareness Month OSU Extension Family & Consumer Sciences Social Media Campaign

Research Protocol

I. Objectives

Social Media Campaign Objectives:

1. To educate the public about relevant topics during National Childhood Obesity Awareness

Month in September 2012

o Childhood obesity education

Topics: health, nutrition, recipes, parenting

o Audience: parents (possibly also teens that would be online)

2. Professional development for Ohio FCS Extension staff to increase use and ease of use in social

media technology.

3. General online marketing of OSU Extension

Stakeholders who could potentially use information garnered from the campaign evaluation would

include: the creator of the social media campaign, the FCS Assistant Director, the Director of

Extension, various county commissioners across the state of Ohio, and the FCS professionals

themselves.

II. Background & Rationale

The Importance of Family Meals

In 1900, 2% of meals were eaten outside the home. In 2010, 50% were eaten away from home and

one in five breakfasts was documented as being from McDonald's. Most family meals took place

about three times a week, lasted less than 20 minutes and were spent watching television or texting

while each family member ate a different microwaved "food." In addition, more meals seemed to be

eaten in the minivan than the kitchen (Hyman, M., 2011).

According to Whitaker, Deeks, Baugham & Specker (2001) over the past few decades, family meals

have undergone changes that have led to negative effects on the eating habits, food choices, family

ties, and the sociability and adjustment of adolescents. Many families now use activities as the

excuse for not sitting down to the dinner table together, rather than seeing it as a choice of

priorities they have made. One variable that affects the amount of time families have to eat healthy

meals together at home is the involvement of children (especially middle and high school aged

children) in school and out-of school activities. In a family meal-time study conducted by Schwartz

(2005), 90% of respondents indicated that their children’s busy schedules during most days of the

week were an influencing factor on whether they chose to eat together. In addition, another study

focused on the eating habits of teens reported that 51% of families surveyed ate fast food as a

family meal one to two times a week. Seven percent said they had fast food for dinner three to four

times a week (University of Minnesota, 2007). However, “planning more meals at home provides an

opportunity for parents and children to consider food preferences and plan menus, allows for

conversation about the day, and creates a setting for adults to model healthful attitudes toward

food and eating” (Gable, Chang & Krull, 2007).

Nancy Gibbs of Time declared in a June, 2006 article that “a dying tradition is coming back” and cites

statistics that have proven that kids who eat family meals are healthier, happier, and better

students. Regular dinnertime has been associated with less adolescent risk for a variety of

internalizing behaviors such as depression, weak self-esteem, suicidal thoughts, attempted suicide,

withdrawn or distressed behavior, and behavioral problems (Eisenburg et al, 2004; Fiese el al., 2002;

Hofferth & Sandberg, 2001). “The older kids are, the more they may need this protected time

together, but the less likely they are to get it” (Gibbs, 2006). Research does indicate that many

parents of school-aged children are overwhelmed with meal planning and preparation (Nicklas,

Morales, Linares, Yang, Baranowski, de Moor, & Berenson, 2004.) Frequency of family meals has

been reported as significantly higher among middle school students than among high school

students, nodding to the demands of the “overscheduled” lives of teenagers and their families

(Neumark-Sztainer, Hannan, Story, Croll & Perry, 2003). Most shocking to some parents might be

the research showing teenagers actually want to eat more meals with their family. In the same

study, although 74% of adolescents indicated that they enjoyed eating meals with their families,

53% reported “different schedules don’t let us eat meals together on a regular basis” (Neumark-

Sztainer, et al. 2003).

Frequency of family mealtime seems to decline as kids reach the teen years. Although a majority of

12-year-olds in a study published by the National Center on Addiction and Substance Abuse (CASA)

at Columbia University (2010) said they had dinner with a parent seven nights a week, only a quarter

of 17-year-olds did. The CASA study also found that the number of adolescents eating with their

family most nights has increased 23% since 1998. These results seem to conflict with other recent

studies, which may warrant more research; most studies show that only about one third of children

and adolescents eat dinner with their families every day (Gillman, et all, 2000; Neumark-Sztainer,

Story, Ackard, Moe, & Perry, 2000).

Influences on family mealtime

Parents have direct control over the home environment and what foods or activities are available in

the house (Rhee, 2008). However, when parents become overwhelmed before even returning home

from work for the evening, they tend to resort to the easiest options for dinner. The major barriers

cited by adults for not having regular dinnertime are typically related to overscheduled calendars,

busy lifestyles, and the challenges of balancing work, family, and children’s activities (Jacob, et al.,

2008).

In a 2001 study, parents reported enjoying the bonding-time they experienced with their children at

meals, but they also reported limited time for meal preparation and frequent multi-tasking at

mealtime. The study showed that they wanted their children’s help with meal preparation, but they

were concerned about the time and “mess” involved. Parents were also frustrated with the limited

range of food items their children would eat, which tends to be a common concern from parents

(Fulkerson, Kubik, Rydell, Boutelle, Garwick, Story, Neumark-Sztainer, & Dudovitz, 2001). To quote a

parent from that study: “Well in my household, I’m the first one that gets there and I start to make

whatever is the quickest thing. When I get home, I’m tired… and I don’t want to do much. Whatever

is done the quickest way that’s what they’re going to eat” (Fulkerson, et al. 2001).

Gender differences seem to play a vital role in family mealtime planning, preparation, and structure.

Adult men and women differ in their responsibility for family meals (Charles & Kerr, 1988; Statistics

Canada, 1999). The Canadian General Social Survey (1999) found that men spent 36% as much time

as women in the preparation and clean-up of meals, but spent as much or more time in consuming

meals. Women, on the other hand, spent more hours cooking and cleaning up. Furthermore, in a

2003 study published in the Journal of the American Dietetic Association, the average frequency of

family meals over a period of one week was highest among children and teens whose mothers were

not employed and lowest among children and teens whose mothers worked full-time (Neumark-

Sztainer, et al. 2003).

In regard to parental employment status and its effect on family mealtime, in a recent study work-

family conflict increased significantly as work hours increased for the high work interference with a

specified “dinnertime group”… but not for the low interference group. This suggests that work hours

are associated with higher levels of work-family conflict specifically when work interferes with

dinnertime. (Jacob, et al. 2008). Perhaps an even more important finding of that same study is only

women benefited from the attenuating effect of not missing dinnertime on the relationship

between work hours and work-family conflict. When the sample was divided by gender, women

demonstrated the negative relationship between work hours and work family conflict. This finding

may support the theory that women feel a greater responsibility for dinnertime and thus experience

greater benefits when they fulfill a responsibility that is consistent with their perceived role (Jacob,

et al. 2008).

Parental education level, another influence on family mealtime, has been shown to be more

strongly related to fruit and vegetable consumption than any other variable of social class (Gibson,

Wardle, & Watts, 1998). Higher parental education has also been associated with health

consciousness in food choices (North & Emmett, 2000). In a 2003 study, adolescents whose parents

were relatively more educated had higher intakes of carbohydrates, protein, fiber, folate, vitamin A,

and calcium; higher consumption of vegetables; and greater likelihood of consuming the

recommended servings of dairy products (Xie, Gilliland, Li, & Rockett). Mothers’ education level was

inversely related to preschool children’s added sugar intake and adolescent’s percentage of energy

from fat (Krant & Siega-Riz, 2002). Exclusive use of whole milk was highest in families in which

parents had less than a high school education, and use of reduced-fat milk was highest among

children who had college-educated parents (Dennison, Erb, & Jenkins, 2001).

Other research has reported that income is also a predictor of eating patterns. As many as 40% of

lower income adolescents do not meet recommended daily consumption of fruit and vegetables

(Neumark-Sztainer, Story, Resnick, & Blum, 1998). Also, cultural differences regarding the types of

foods consumed at family meals as well as other social and environmental influences from peers,

school, or mass media may influence the eating behaviors of minority youth and attenuate or alter

the effect of family meals (Rhee, 2008).

Diet

“Regular dinnertime has been associated with improved dietary quality, healthy food-related

attitudes, behaviors, consumption patterns, and less risky eating and weight control behaviors”

(Gillman et al, 2000; Neumark-Sztainer, et al. 2003; Neumark-Sztainer, Wall, Story, & Fulkerson,

2004; Stanek, Abbot, & Cramer, 1990; Videon & Manning, 2003). Specifically, eating frequency of

family mealtimes has also been associated with increased discussion and knowledge of nutrition-

related topics (Gillespie & Achterberg, 1989). Families who eat together tend to make healthy but

similar meals on a day-to-day basis. Research has shown frequent exposure to an unfamiliar food

can result in increased consumption, liking, and preference for that food (Wardle, Cooke, et al.

2003; Wardle, Herrera, et al. 2003). Research has shown that frequency of family meals has been

positively associated with intakes of fruits, vegetables, grains, and calcium-rich foods, and negatively

associated with soft drink intake.

“In preschool aged children, it seems emphasis should be placed on encouraging parents to provide

home-cooked meals that mirror those eaten by the adults in the family to improve vegetable intake”

(Sweetman, McGowan, Croker, & Cooke, 2011). Frequency of family mealtimes was not associated

with preschoolers’ vegetable consumption or liking, however parental role modeling, ie, eating

similar food, was associated with greater consumption and liking of vegetables (Sweetman, et al,

2011). However, one study with preschoolers showed intake of fruit and vegetables were positively

associated with the number of nights the family ate together (Fitzpatrick, Edmunds, & Dennison,

2007). Because children’s eating habits and food preferences develop early in life and tend to track

into adulthood, the impact of family mealtimes on dietary quality in the early years is extremely

important (Lytle, Seifer, Greenstein, & McGovern, 2000; Lien, Lytle, & Klepp, 2001).

Adolescents who have at least seven family meals during the course of one week have reported

lower intakes of snack foods than youths who reported fewer family meals. (Neumark-Sztainer, et

al. 2003). And a 2009 study suggests the importance of developing healthy eating habits early on, as

regular family meals were positively associated with adolescents’ diets after a 5-year period in

regard to frequency of breakfast, lunch, and dinner meals for males and breakfast and dinner meals

for females. Among males, regular family meals were negatively associated with fast-food intake 5

years later. Regular family meals were also positively associated with daily intakes of vegetables,

calcium-rich food, fiber, calcium, magnesium, potassium, iron, zinc, folate, and vitamins A and B6

among both genders (Burgess-Champoux, Larson, Neumark-Sztainer, Hannan, & Story, 2009).

Another recent study in the Journal of American Dietetic Association found that teens who ate with

their families consumed more fruits and dark green and orange vegetables, two of the healthiest

(Hockett, 2007).

Obesity

“Above and beyond child sex, race, and family SES, children who… eat fewer meals with their

families during kindergarten and first grade are more likely to be clinically overweight at third

grade” (Gable, et al, 2007). The 2007 Gable study found that for each family meal per week that

children do not experience, the risk for persistent overweight increases 1/0.92 times” (Gable, et al,

2007). Similarly, a study published in the Official Journal of the American Academy of Pediatrics

found that children and adolescents were 12% less likely to be overweight in families that had at

least 3 shared family meals per week than those who ate fewer than 3 shared family meals per week

(Hammons & Fiese, 2011). Anderson and Whitaker, from Ohio State University, published an

additional study in the Official Journal of the American Academy of Pediatrics (2010) which suggests

that regressing from modern dietary habits could slash the risk for obesity by 40% for four-year-olds.

Their study, which focused on the relationship between household routines and obesity, charted

three separate family routines: eating an evening meal as a family more than five times a week,

sleeping at least 10.5 hours a night and watching under two hours of TV on weekdays. Among

children whose families practiced all three routines, 14% were obese. In contrast, the figure for

those living in households which had none of the routines was 24.5% (Anderson & Whitaker, 2010).

Age may also be a factor in obesity risk, as well as portion size, which are both affected by the

frequency and dietary quality of family meals. According to Rhee (2008), a “significant jump in the

prevalence of children at risk for overweight and overweight children occurs between preschool

(ages two to five) and grade school (ages six to eleven years)”. Rhee also suggests that portion size

plays an important role in the amount of food a child consumes. One means of circumventing the

impact of large portion sizes may be to allow children to choose their own portion size, or serve

themselves as they get older (Rhee, 2008).

While some research ties family meal-time frequency and obesity prevention and risk, given the

importance of the family environment in regard to healthy eating and activity, some researchers

have suggested a void exists of childhood obesity prevention research that focuses on the family

(Fulkerson, Rydell, Kubik, Lytle, Boutelle, Story, Neumark-Sztainer, Dudovitz, & Garwick, 2010).

However, current USDA funding projects focused on family routines, specifically eating patterns and

routines, and the impact on obesity rates and risk, will likely increase the literature available on this

topic.

How Families can Incorporate Healthier Options and Increase Family Meal-Time

Putting healthier diet strategies into practice like incorporating healthier food choices and habits

into everyday schedules can be difficult for many families. Thus, taking researchers’ advice on how

to utilize their findings with “the average family” is especially important. Community-based

programs have long been a favorite educational tool for dieticians, family life educators and

Extension professionals. However, attracting clientele to face-to-face programs can be difficult

during an era when online education seems to be the norm. Knowing which program topics are

desired from current and potential clientele can help. Research has offered such suggestions:

preferred program ideas from focus group parents in a 2001 study included feeding tips/recipes,

meal planning/preparation, and changing food offerings. Findings indicate a need for creative

programs and professional nutrition guidance to facilitate family engagement in planning and

cooking quick, healthful meals, development of skill building, and increasing healthful food

consumption (Fulkerson, Kubik, Rydell, Boutelle, Garwick, Story, Neumark-Sztainer, & Dudovitz,

2001).

Hands-on learning is extremely essential in developing healthy eating habits for both parents and

children. “Working with families to develop realistic plans for preparing healthful meals at home

may be a feasible starting point” to creating a familial setting for adults to model healthful attitudes

toward food and eating (Gable, et al. 2007). Hands-on programs can also focus on cooking planning

and techniques such as bulk cooking. Parents can be informed that by cooking on weekends and

doubling a favorite recipe, they can enjoy one meal for dinner that evening, and then freeze the rest

to enjoy some evening when they’re too tired to cook. Soups and casseroles are especially good to

freeze and could serve as an easy hands-on learning activity that would allow parents to put this

knowledge into practice.

In regard to making healthier dietary choices available throughout the day, not just at mealtime,

research has shown that since high preference for healthy foods such as fruits and vegetables is a

significant factor in a child’s consumption of these foods, shaping these preferences via frequent

exposure and increasing availability may be an important tool in a child’s life (Rhee, 2008). Also,

behavioral theories suggest that making fruits and vegetables more easily accessible by putting

them in a place where the child can easily reach them (e.g., in a bowl on the table or on a lower

shelf in the refrigerator) and preparing them into sizes that are easy to eat (e.g., fruit cut into bite-

size pieces) may increase the child’s intake of these foods (Rhee, 2008). As children begin to

frequently snack on healthy items, they may be more likely to eat them during mealtimes.

Welcoming kids into the kitchen is also important. A 2006 study reported that in general,

adolescents who prepared food was related to more healthful food choices. Preparing food was

positively associated with fruit consumption in male adolescents and was positively associated with

fruit and vegetable consumption in female adolescents. Preparing was also negatively associated

with soft drink consumption among female adolescents and fried food consumption among male

adolescents. In contrast, frequency of food shopping was related to greater consumption of fried

foods among female adolescents (Larson, Story, Eisenberg, & Neumark-Sztainer, 2006). Teens

should be encouraged to help with meal preparation and may benefit from interventions and

programs that teach skills for cooking and making healthful purchasing decisions.

So how specifically can experts further assist families in practicing healthier dietary and family meal-

time habits? “Family life educators and extension educators can develop resources that promote

family dinnertime for a wide variety of end users. These work and community contexts could

support family dinnertime as an important priority not only by providing education on the benefits

of family meals but by also providing the necessary planning, organization, and cooking skills to

facilitate the attainment of more regular nutritious and healthy family meals” (Jacobs, et al., 2008).

Tools & Resources for Families

Many families look for information on the go, so it comes as no surprise that a wealth of resources

exist online for families who are looking to eat healthier and eat more often at home.

Choosemyplate.gov offers tools and resources for parents, children, and teens focused on topics

such as dietary recommendations, meal planning, and incorporating more physical activity into daily

routines. The Dairy Council of California maintains the Meals Matter website that includes extensive

meal planning information and tools such as shopping lists, and even a food personality quiz.

Sponsored by the JM Smucker company, The Power of Family Meals website features a “recipe of

the day,” and “My Family Meals” feature with recipe box and grocery list options. Similarly, Oregon

State University Extension’s Food Hero website houses a vast array of recipes for families with

children of all ages as well as information on portion size, when to purchase certain fruits and

vegetables in-season, and even helpful downloads. For families who are looking for more in-depth

and educational information about healthier eating habits, the University of Minnesota Extension’s

Family Mealtime online course offers a self-study program for parents and interested adolescents.

Other website resources are focused on inviting children into the kitchen and allowing them to

become acquainted with more healthy food options by involving them in the cooking process.

Kansas State University’s Kids a Cookin’ website features recipes that kids can help prepare

alongside parents and eXtension’s Prepare and Eat More Meals at Home resource site also includes

kid-friendly recipes they can help create and cook, along with parental tips and suggestions for

cooking with kids.

Many apps for Facebook and Smartphones are also available for families, and are more likely to be

utilized than self-study courses online or educational fact sheets. The Super Tracker app from

Choosemyplate.gov allows users to easily track their daily dietary intake and physical activity, while

the Dairy Council of California’s Eat Better, Eat Together Facebook application can post updates on

the user’s Facebook Timeline for their friends to see, which could assist in holding the individual

and/or family more accountable for incorporating healthier food choices and habits into their

lifestyle. Fooducate, a popular mobile phone app gives users the option of scanning any barcode to

receive real-time nutrition information about the food “in the package” and provides them with

more nutritious options on the spot while the Epicurious app focuses mainly on recipes for any

occasion (from weeknight dinners to healthy snacks) and shopping list features. Kids may find Smash

Your Food especially fun, which is an iPhone and iPad app that allows kids to “smash” certain foods

and find out what they’re “made of” (nutrients, fat, oils, etc.) Another popular iPad app for younger

children brings them into a virtual kitchen and introduces them to the fun of cooking with healthy

ingredients - Little Cook. Once they have mastered a virtual kitchen with Little Cook, older kids can

put their knowledge to work with the Big Fork, Little Fork app from Kraft (although parents should

note Kraft products, including hot dogs and macaroni and cheese, are front and center in most

recipes). Big Fork, Little Fork is a good starting point however, to bring kids into the kitchen and get

them excited about cooking.1

Conclusion

Consistent family meal-times are linked to healthier, happier family members of all ages, parents

and children alike. Frequent family meals improve dietary quality, introduce new foods into the

family’s diet, provide de-stress and communication time, and provide children with healthy dietary

1 See Appendix for a complete list of links related to the tools and resources included in this section.

and eating habits they carry into adulthood. Parents can take the benefits of family meal-time to the

next level and include their children in the planning, preparation, and cooking of family meals to

provide even more opportunities for them to learn not just healthy eating practices, but how to

prepare and cook fruits and vegetables and other healthy ingredients. While work, time, and

financial constraints inhibit today’s busy families from adopting healthier eating practices, experts

and educators can offer various hands-on programs, share realistic tools and resources, and provide

support and encouragement to empower them to weave a healthier dietary lifestyle into their daily

routine. Just one family meal at a time can make a difference in the long-term health of parents and

children.

Current Technology

In a technology readiness assessment study (Assessing County Extension Programs’ Readiness to

Adopt Technology) conducted by Oregon State University Extension in 2009, time, money, and

training “were identified as key barriers and constraints that keep faculty and staff from adopting

technology as useful tools” (Diem et al., 2009). A loss of county funding and staff, coupled with a

mass movement of organizational change is not a recipe that will foster acceptance for other

changes, especially technological ones. The Oregon State study also found that Extension

professionals are generally in denial about the importance of current and future technology trends.

Respondents of the study stated that they believed technology would take time away from getting

work completed, that it was not valued by their clientele, and that it would detract value from

programming.

When considering whether these assumptions are true, there are many important statistics to

consider. Wikipedia, the online wiki powerhouse, has over 5 million users who edit, add, and delete

content every day. When it comes to blogging, 346 million people worldwide and 77% of active web

users read blogs. The trend also grew by an astounding 68% in 2008 (Varcoe, 2009). How do

Extension professionals take advantage of new technology trends? In a study conducted by

Elizabeth Wells at Michigan State University Extension, 97% of participants had never edited a wiki,

89% had never exchanged an instant message with a colleague or client and 73% had never posted

an article to a web site or blog.

Extension professionals have also stated that their dedication to traditional clientele prohibits them

from adopting new technology. Many feel that their programs rely on personal contacts and

relationships. “Catering to existing, high-maintenance traditional audiences is being done while

sacrificing the opportunity to reach new audiences” (Diem et al., 2009). While most Extension

professionals feel traditional clientele are resistant to new technology, current trends are showing

otherwise. Jerold Thomas (personal interview, November 18, 2009), innovation and new technology

leader for OSU Extension describes agriculture Extension clients as being one of the fastest groups of

technology adopters. In fact, many of them have taken to “tweeting from the tractor”, surpassing

some technology adopters by ditching their PCs for portable PDAs (Diem et al., 2009). Even hard to

reach audiences, who are generally thought of by professionals to be unreachable via technology

are finding ways to afford or use PCs and Smartphones to connect themselves with the online world.

However, while some clientele may be quick to adopt technology, there are some who will

inevitably be resistant. A balance must be maintained between satisfying older generations of

clientele with face-to-face programming and reaching out to future clientele online.

Extension professionals and clientele are not the only barriers that exist. Extension administration

as well as the bureaucratic organizational structure of the system has proven to be a hindrance as

well. The Oregon State assessment study found an interesting hiring tend with new employees; new

hires generally had the same “technology ethic” as existing staff, especially on the county level

(Diem et al., 2009). Another hurdle that exists is the difference in definition of the word

“programming” among generations of Extension professionals. To older professionals,

programming is seen in the form of tangible curriculum and program content; to the younger

generations, programming can be seen through multiple lenses – not only does it involve

curriculum, but online social networking and education as well.

The Next Generation of Extension Professionals

“Millenials – the American teens and twenty-somethings who are making the passage into

adulthood at the start of a new millennium – have begun to forge their [generational personality]:

confident, self-expressive, liberal, upbeat and open to change” (Taylor & Keeter, 2010, p. 1.) This

generation of young Americans will forever change the way Extension manages professionals, staff,

and programming.

Millenials claim that technology is what sets them apart from previous generations – and with good

reason. “They are history’s first ‘always connected’ generation. Steeped in digital technology and

social media, they treat their multi-tasking hand-held gadgets almost like a body part” (Taylor &

Scott, 2010, p. 1.) Furthermore, they are the “first generation in human history who regard

behaviors like tweeting and texting, along with websites like Facebook, YouTube, Google, and

Wikipedia not as astonishing innovations of the digital era, but as everyday parts of their social lives

Comment [A1]: need to add this citation in other locations where your cite Jerry.

and their search for understanding” (Keeter & Taylor, 2009, p.1.) Extension is an organization that

has facilitated most programming by utilizing a traditional face-to-face method. Only recently have

Extension systems in various states started to experiment with online programming. In a study

conducted by Elizabeth Wells at Michigan State University Extension (2009), 97% of participants had

never edited a wiki, 89% had never exchanged an instant message with a colleague or client and

73% had never posted an article to a website or blog – all of which are second nature to Millenials.

Extension leaders must hear the call to action – programming will have to fundamentally change in

order to accommodate the skills and knowledge of what is being called “Generation Next.” Not only

will staffing be impacted by Millenials, but future clientele will also require different teaching

methodologies and information given via online tools such as social media, etc.

OSU Extension’s Relationship with Current and Future Technology

Before the organization can successfully implement various technologies into our programming, we

must first understand the new definition of “knowledge” and how social media has impacted how it

is shared. This transformation was identified as early as the year 2000 when colleagues addressed

that “Extension is rapidly being drawn into a competitive knowledge marketplace” (King & Boehlje,

2000). However, nine years later we are still struggling with Extension’s role in this new distribution

of knowledge. In recent years and even months, the global population was no longer waiting for

experts to give them information – they were finding it themselves. Today, with the extremely quick

rise in importance of social media, that information is finding them (Qualman, 2009). Extension’s

mission is to take the University to the people. To do so, we should go to where the people “are.”

Today we can find them online and on their PDAs, engaged in a variety of social media. What is

Extension’s role in this? How can we compete? The answer is that we do not compete – we join.

Not only does Google greatly influence how today’s populations are engaging, “the big three”

(Facebook, Twitter, and LinkedIn) have an enormous impact as well. For example, by 2010,

Generation Y outnumbered Baby Boomers - 96% of them have joined some form of a social network

(Qualman, 2009). Let there be no doubt that this is where the vast majority of Extension’s future

clientele are already located – and they should not be ignored.

By encouraging Extension professionals to create and utilize their own social networking accounts, a

new audience can be identified and catered to virtually. Examples include the successful impact of

blog-components of programs. The Move It Miami County blog developed by Extension staff in

Miami County, Ohio has received over 7,500 hits since the beginning of the program, providing

educational, reliable information to nearly 200 participants as well as an average of 70 individuals

each day nationwide who also viewed its content. This statistic brings to light the incredible power

of engaging our audiences virtually. Our organization has traditionally been viewed as focusing on

Outreach. However, we should be moving toward a greater focus on Engagement. Engagement is

what our modern audience craves the most at this particular time, according to Thomas (personal

interview, November 18, 2009). The need for the organization to be more interactive with clientele

will only increase as the expectation of programming and the availability of information online

increases (Diem et al., 2009).

The increased use of smartphones by the global population forces Extension to look at the potential

of utilizing Smartphone technology. With over 2 billion devices in use, mobiles eclipse the estimated

750 million PCs (Siemens, 2009). Similar to modern clientele, professionals may need to be

available 24/7 (as they expect from other sources of information), be active in various forms of

social media, as well as create and edit wikis. “Our learning content must be available to the device

and in the environment they desire” (Siemens, 2008). Eighty-percent of Twitter usage is outside of

the Twitter website; people update anywhere, anytime (Qualman, 2009).

Best Practices and Evaluation of Social Media Campaigns

While it is evident that Extension programming should somehow expand into the social media

realm, many Extension professionals have struggled with this transition. Social media guidelines and

tips for best practices in the field have just now begun to surface. Two of the most helpful social

media guides for Extension programming are the Discover Your Social Web and Discover Your Social

Brand guides published by the Ohio Farm Bureau. Developed by agriculture social media guru Dan

Toland, Both guides offer best practices tips and suggestions, as well as include step-by-step

instructions on how to create social media profiles to engage with clientele. The guides are

extremely user-friendly and offer the best introduction to social media for Extension professionals

interested and/or eager to learn this new method of reaching clientele. According to Toland, “your

brand isn’t a product, it isn’t a jingle or a message, it’s an experience [online]. Instant

communication and social media are firmly entrenched in our lives. People are spending more and

more time on social media and less and less time on your website. So how do you reach them? How

do they keep up with you?” (Toland, 2011).

Evaluation of social media programming, campaigns, and best practices has also been lacking.

However, Amelia Burke, Director of Digital Media for the Center for Health Communications at the

Academy for Educational Development (AED) insists that social media campaigns can be planned

well and in return, evaluated efficiently. A marketer by trade, Burke suggests the use of the

S.O.C.I.A.L. (Strategic Online Communication, Insights, and Learnings) framework for basic program

planning and evaluation when utilizing social media campaigns as a form of programming. By

focusing on goals, target audience, where the audience is and what they are doing, budget, and

evaluation during the program planning process, the S.O.C.I.A.L. framework will already be

integrated into the evaluation of the campaign. According to Burke, while “there is no industry

standard for measuring social media, evaluation frameworks have evolved similarly in that they are

fragmented without one industry standard being held above all else” (Burke, 2011). The S.O.C.I.A.L.

framework suggests that “digital campaigns can be measured through the three-pronged paradigm

of Reach, Insights, and Actions” (Burke, 2011). Thus, a social media campaign can be evaluated by

looking at page impressions, click-through-rates, survey results, and tangible actions taken by

consumers of the information (Facebook comments and other forms of engagement) for example.

Burke also mentions in her article “Planning and Evaluating Digital Media Campaigns for the Public

Sector” (2011) that an exciting aspect of social media technology is that it levels the playing field for

public service fields. As she notes – “you can’t buy attention anymore. Having a huge budget doesn’t

mean anything in social media. Now you get back what you authentically put in. You’ve got to be

willing to play to play” instead of pay to play (Burke, 2011).

III. Procedures A. Research Design

This particular design will follow a causal design in that it seeks to answer if the

program’s anticipated objectives were met and if the method of the campaign’s delivery

was effective in many ways (both as an online educational tool and as a professional

development tool). The evaluation will follow an experimental design by gathering a

census of data from all FCS professionals that participate in the campaign using both pre

and post-test surveys, along with a follow-up survey. A census of all FCS professionals

participating in the campaign should be more than plausible, as there are not many FCS

professionals in Ohio. The pre-test, post-test, and follow-up survey instruments will be

similar in the nature of questions asked, however additional questions will be included

on the post-test to gauge the effectiveness of the campaign as a professional

development tool for participants. Questions that are identical on both the pre-test and

post-test will also be included in the follow-up survey.

The pre and post –test collection of the data will give insight into how much more (or

not) FCS professionals became using social media tools together as a group during the

campaign as well as how effective their social media profiles (personal and professional)

were in respect to reaching and engaging with online clientele before and after the

campaign. The follow-up data will provide information about the “lasting effects” of the

campaign for both FCS professionals and reaching online clientele, as well as give insight

to long-term impacts of the campaign.

B. Sample The sample to be evaluated by pre and post-test surveys will include all FCS

professionals who participate in the social media campaign during the month of

September, 2012.

C. Measurement / Instrumentation

Not all of the indicators listed below are needed to answer the evaluation questions.

However, these indicators are based on the social media campaign’s overall logic model.

The information most needed involves the questions of the effectiveness of the

campaign as a professional development tool, and if the campaign met its

objectives/impact. The S.O.C.I.A.L. Framework will be utilized to assist in finding the

impact fan pages and Twitter feeds had with online clientele. Focus groups are not listed

as sources in the chart below as focus group questions will be all-encompassing and

involve each output and objective in some form.

Outputs Short-Term Impact Medium-Term Impact Long-Term Impact

#, % of participants who

answer they felt the

trainings before the

campaign were helpful.

(pre-test & post-test)

Reach of FCS

professionals’ posts

during the campaign

(initial reach and

virality.) (post-test and

Insights data)

#, % of FCS

professionals reporting

examples of families

incorporating healthy

eating practices into

their daily eating habits.

(post-test & follow-up,

social media

engagement)

#, % of FCS

professionals reporting

a decline in families

eating fast-food meals

and meals outside of

the home and/or

improvement of eating

and dietary habits.

(post-test & follow-up,

social media

engagement)

#, % of participants who

answer they received

appropriate and helpful

best practices and user

guides to prepare them

for the campaign. (pre-

test & post-test)

Amount of engagement

via posts with online

clientele. (post-test and

Insights data)

#, % of FCS

professionals answering

they incorporate social

media tools into their

programming efforts

more often (post-test &

follow-up)

#, % of participants in

the campaign who are

referred to as leaders in

Extension in respect to

integrating social media

tools into their

programming efforts.

(follow-up)

#, % of participants who

answer they felt they

received an adequate

amount of support from

other FCS professionals

as well as the campaign

director during the

campaign. (post-test)

#, % of FCS

professionals

(participants) who

answer that they felt a

hands-on experience

allowed them to gain a

better understanding of

how to best utilize

social media tools in

Extension

programming. (post-

test)

Reach of online

clientele re-sharing

campaign information

via posts on their own

social media profiles.

(Insights data)

Steady increase of

online clientele looking

to and engaging with

Extension posts via

social media sites.

(follow-up and Insights

data)

Difference in #, % of

participants who

answer they are now

comfortable utilizing

social media tools. (on

pre and post-tests)

D. Detailed Study Procedures Risks will be minimized to participants by the project PI and co-PI collecting information

via an online survey where participants can answer anonymously. All survey responses

will be kept confidential and with the PI and co-PI in hard-copy form in a locked cabinet.

Personal information from participants will be stored for three years prior to completion

of the study.

The table below describes the timeline and responsibilities of the social media campaign

evaluation process in 2012 – 2013.

Evaluation Activity

Date Person Responsible

Campaign Pre-Test sent via e-mail to FCS professionals participating in the campaign.

Early August, 2012 Campaign director (myself)

Pre-campaign focus group meeting.

Mid-August, 2012 Campaign director

Pre-test and focus group results organized

Late August, 2012 Campaign director

Social Media Campaign

September, 2012 Campaign director

Campaign post-test sent via e-mail to FCS professionals who participated.

Early October, 2012 Campaign director

Post-campaign focus group meeting.

Mid-October, 2012 Campaign director

Post-test and focus group results organized and analyzed in comparison with pre-test results

Late October, 2012 Campaign director

Evaluation results report created and distributed among stakeholders

November, 2012 Campaign director

Poster or concurrent session given at OSU Extension annual conference

December, 2012 Campaign director, FCS campaign participants

Follow –up survey sent via e-mail to FCS professionals who participated in the campaign

May, 2013 Campaign director

Follow-up data organized and June, 2013 Campaign director

analyzed in comparison to pre and post-test results Second evaluation report created and distributed among stakeholders

June – July, 2013 Campaign director

Poster or concurrent session given at OSU Extension annual conference

December, 2013 Campaign director, FCS campaign participants

E. Internal Validity The data collection tools utilized to collect data will be internally validated via a small

group review process in which two FCS professionals, two non-FCS Extension

professionals, and one social media professional will review the surveys and questions

before implementation of the evaluation is to take place. By involving professionals with

a range of expertise, the relevance, appropriateness, and effectiveness of the data

collection tools can be assessed and validated. Thus, criterion and face validity will also

be included in this process.

F. Data Analysis Data analysis of the evaluation results will take place by organizing the pre and post

survey results via a spreadsheet. The results will then be analyzed by finding

percentages of how respondents answered. Open-ended question responses will be

organized in narrative form. Focus group data will also be organized in narrative form

and according to question. Key words will be identified from those results by creating a

“Wordle” image. The campaign director (project co-PI) will be responsible for organizing

and analyzing the data. The campaign director will then work with FCS administration

professionals to interpret the results of the data analysis.

The results of the data analysis will be shared with stakeholders – FCS administrative

professionals, OSU Extension Administrative Cabinet, and FCS professionals in a report

form. The report will be in PowerPoint presentation form and contain many graphs and

visuals, including actual screen captures of examples of online engagement with

clientele during the campaign, and evidence of impact such as screen shots of Facebook

Insight information. This report will be posted on the OSUE FCS website under

professional resources and will also be communicated during either a poster or

concurrent session presentation at the OSU Extension annual conferences in 2012 and

2013. The 2013 poster or presentation session will include data from the follow-up

survey. National presentations are also another possible outlet for sharing results, as

well as a Camtasia-type video that could be posted on the OSU Extension YouTube

channel if the impact of the campaign is substantial. The results of the evaluation can

also be submitted to national Extension and FCS-related journals to ensure the spread of

its use.

IV. Bibliography

Nutrition / Family Meals

Anderson, S. E., Must, A., Curtin, C., & Bandini, L. G. (February 01, 2012). Meals in Our Household: Reliability and Initial

Validation of a Questionnaire to Assess Child Mealtime Behaviors and Family Mealtime Environments. Journal of the

Academy of Nutrition and Dietetics, 112, 2, 276-284.

Anderson, S.E. & Whitaker, R.C. (February 2010). Household Routines and Obesity in US Preschool-Aged Children. Official

Journal of the American Academy of Pediatrics, 125, 420-428.

Burgess-Champoux, T. L., Larson, N., Neumark-Sztainer, D., Hannan, P. J., & Story, M. (March 01, 2009). Are Family Meal

Patterns Associated with Overall Diet Quality during the Transition from Early to Middle Adolescence?. Journal of Nutrition

Education and Behavior, 41, 2, 79-86.

Cason, K. L. (January 01, 2006). Family mealtimes: more than just eating together. Journal of the American Dietetic

Association, 106, 4, 532-3.

Charles, N., & Kerr, M. (1988). Women, food and families. Manchester: Manchester University Press.

Committee on Prevention of Obesity in Children and Youth. (2005). Preventing Childhood Obesity: Health in the Balance.

Washington, DC National Academies Press.

Davidson, R., & Gauthier, A. (January 01, 2010). A cross-national multi-level study of family meals. International Journal of

Comparative Sociology, 51, 5, 349-365.

Dennison, B.A., Erb, T.A., & Jenkins, P.L. (2001). Predictors of dietary milk fat intake by preschool children. Preventive Medicine,

33, 536-542.

Eisenburg, M.E., Olsen, R.E., Neumark-Sztainer, D., Story, M., & Bearinger, L.H. (2004). Correlations between family meals and

psychosocial well-being among adolescents. Archives of Pediatrics and Adolescent Medicine, 158, 792-96.

Hammons, A. J., & Fiese, B. H. (January 01, 2011). Is frequency of shared family meals related to the nutritional health of

children and adolescents?. Pediatrics, 127, 6, 1565-74

Hofferth, S.L., & Sandberg, J.F. (2001). How American children spend their time. Journal of Marriage and the Family, 63, 295-

308.

Hyman, M. (January 2011). How eating at home can save your life. The Huffington Post. [Online] Retrieved

from: http://www.huffingtonpost.com/dr-mark-hyman/family-dinner-how_b_806114.html

Fiese, B.H., Foley, K.P., & Spagnola, M. (2006). Routine and ritual elements in family mealtimes: Context for child well-being and

family identity. In R.W. Larson, A.R. Wiley, & K.R. Branscomb (Eds.), Family mealtime as a context of development and

socialization (pp. 67-89). Ann Arbor, MI: Wiley Periodicals.

Fiese, B.H., Tomcho, T.J., Douglas, M., Josephs, K., Poltrock, S., & Baker, T. (2002). A review of 50 years of research on naturally

occurring family routines and rituals: Cause for celebration? Journal of Family Psychology, 16, 381-90.

Fitzpatrick, E., Edmunds, L.S., & Dennison, B.A. (2007). Positive effects of family dinner are undone by television viewing.

Journal of the American Dietetic Association, 107, 666-671.

Fulkerson, J. A., Kubik, M. Y., Rydell, S., Boutelle, K. N., Garwick, A., Story, M., Neumark-Sztainer, D., ... Dudovitz, B. (May 01,

2011). Focus Groups with Working Parents of School-aged Children: What's Needed to Improve Family Meals?. Journal of

Nutrition Education and Behavior, 43, 3, 189-193.

Fulkerson, J.A., Neumark-Sztainer, D., & Story, M. (April 2006). Adolescent and parent views of family meals. Journal of the

American Dietetic Association, 106 (4), 526-533.

Fulkerson, J. A., Rydell, S., Kubik, M. Y., Lytle, L., Boutelle, K., Story, M., Neumark-Sztainer, D., ... Garwick, A. (January 01, 2010).

Healthy Home Offerings via the Mealtime Environment (HOME): feasibility, acceptability, and outcomes of a pilot

study.Obesity (silver Spring, Md.), 18, 69-74.

Gable, S., Chang, Y., Krull, J. (January, 2007). Television Watching and Frequency of Family Meals Are Predictive of Overweight

Onset and Persistence in a National Sample of School-Aged Children. Journal of the American Dietetic Association, 101, 1.

Gibbs, N., & Miranda, C. A. (June 12, 2006). The Magic of the FAMILY MEAL. Time, 167, 24.

Gibson, E.L., Wardle, J., Watts, C.J. (1998). Fruit and vegetable consumption, nutritional knowledge and the beliefs in mothers

and children. Appetite, 31, 205-228.

Gillespie, A.H., & Achterberg, C.L. (1989). Comparison of family interaction patterns related to food and nutrition. Journal of the

American Dietetic Association, 89, 509-512.

Gillman, M.W., Rifas-Shirman, S.L., Frazier, A.L., Rockett, H.R.H., Camargo, C.A., Field, A.E., et al. (2000). Family dinner and diet

quality among older children and adolescents. Archives of Family Medicine, 9, 235-40.

Jacob, J.I., Allen, S., Hill, E.J., Mead, N.L., Ferris, M. (June, 2008). Work Interference with Dinnertime as a Mediator and

Moderator between Work Hours and Work and Family Outcomes. Family and Consumer Sciences Research Journal, 36, 4,

310-27.

Krantz, S., Siega-Rez, A.M. (2002). Sociodemographic determinants of added sugar intake in preschoolers 2 to 5 years old.

Journal of Pediatrics, 140, 667-672.

Larson, N.I., Story, M., Eisenberg, M.E., Neumark-Sztainer, D. (2006). Food preparation and purchasing roles among

adolescents: Associations with sociodemographic characteristics and diet quality. Journal of the American Dietetic

Association, 106(2), 211-218.

Larson, N.I., Neumark-Sztainer, D., Hannan, P., & Story, M. (September 2007). Family meals during adolescence are associated

with higher diet quality and healthful meal patterns during young adulthood. Journal of the American Dietetic Association,

107 (9), 1502-1510.

Larson, R.W., Branscomb, K.R., & Wiley, A.R. (2006). Forms and functions of family mealtimes: Multidisciplinary perspectives.

New Directions for Child and Adolescent Development, 111, 1-15.

Lien, N., Lytle, L.A., & Klepp, K.I. (2001). Stability in consumption of fruit, vegetables, and surgery foods in a cohort from age 14

to age 21. Preventive Medicine, 33, 217-226.

Lytle, L.A., Seifert, S., Greenstein, J., & McGovern, P. (2000). How do children’s eating patterns and food choices change over

time? Results from a cohort study. American Journal of Health Promotion, 14, 222-228.

Neumark-Sztainer, D., Hannan, P.J., Story, M., Croll, J., & Perry, C. (2003). Family meal patterns: Associations with

sociodemographic characteristics and improved dietary intake among adolescents. Journal of the American Dietetic

Association, 103, 317-322.

Neumark-Sztainer, D., Story, M., Ackard, D., Moe, J., & Perry, C. (2000). The “family meal”: Views of adolescents. Journal of

Nutrition Education, 32(6), 329-334.

Neumark-Sztainer, D., Story, M., Resnick, M.D., & Blum, R.W. (1998). Lessons learned about adolescent nutrition from the

Minnesota Adolescent Health Survey. Journal of the American Dietetic Association, 98, 1449-1455.

Neumark-Sztainer, D., Wall, M., Story, M., & Fulkerson, J.A. (2004). Are family meal patterns associated with disordered eating

behaviors among adolescents? Journal of Adolescent Health, 35, 350-359.

Nicklas, T.A., Morales, M., Linares, A., Yang, S.J., Baranowski, T., de Moor, C., & Berenson, G. (2004). Children’s meal patterns

have changed over a 21-year period: The Bogalusa Heart Study. Journal of the American Dietetic Association, 104, 753-761.

North, K., & Emmett, P. (2000). Multivariate analysis of diet among three-year-old children and associations with socio-

demographic characteristics. The Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC) Study Team. European

Journal of Clinical Nutrition, 54, 73-80.

Patrick, H., & Nicklas, T. A. (January 01, 2005). A review of family and social determinants of children's eating patterns and diet

quality. Journal of the American College of Nutrition, 24, 2, 83-92.

Rhee, K. (January, 2008). Childhood Overweight and the Relationship between Parent Behaviors, Parent Style, and Family

Functioning. The Annals of the American Academy, AAPSS, 615.

Stanek, K., Abbot, D., & Cramer, S. (1990). Diet quality and the eating environment of preschool children. Journal of the

American Dietetic Association, 90, 1582-1584.

Sweetman, C., McGowan, L., Croker, H., & Cooke, L. (January 01, 2011). Characteristics of family mealtimes affecting children's

vegetable consumption and liking.Journal of the American Dietetic Association, 111, 2, 269-273.

Statistics, Canada. (1999). Overview of the time use of Canadians in 1998. Catalog No. 12F0080XIE. Ottawa, Canada.

Videon, T.M., & Manning, C.K. (2003). Influences on adolescent eating patterns: The importance of family meals. Journal of

Adolescent Health, 32, 365-373.

Wardle, J., Cooke, L., Gibson, E.L., Sapochnik, M., Sheiham, A., & Lawson, M. (2003). Increasing children’s acceptance of

vegetables; a randomized trial of parent-led exposure. Appetite, 40, 155-162.

Wardle, J., Herrera, M.L., Cooke, L., & Gibson, E.L. (2003). Modifying children’s food preferences: The effects of exposure and

reward on acceptance of an unfamiliar vegetable. Eur J Clin Nutr, 57, 341-48.

Xie, B., Gilliland, F.D., Li, Y.F., & Rockett, H.R. (2003). Effects of ethnicity, family income, and education on dietary intake among

adolescents. Preventative Medicine, 36, 30-40.

Technology / Evaluation

Armour, S. (2005 November 6). Generation Y: They’ve arrived at work with a new attitude. USA Today. Retrieved (April 12, 2011) from: http://www.usatoday.com

Arnold, S. & Place, N. (2010 February). What Influences Agents to Pursue a Career in Extension? Journal of Extension. [Online], 48(1) Article 1RIB1. Available at: http://www.joe.org/joe/2010february/rb1.php

Bachtel, D. (1989). Where are Future Agents Coming From? Journal of Extension. [Online], 27(3) Article 3RIB2. Available at: http://www.joe.org/joe/1989fall/rb2.php

Barford, I. & Hester, P. (March-April 2011). Analyzing Generation Y Workforce Motivation. Defense AT&L brief. Retrieved from: http://www.dau.mil

Borr, M. & Young, R.B. (2010 February). Retirement and Attrition Trends of Extension Professionals in North Dakota. Journal of Extension. [Online], 48(1) Article 1RIB4. Available at: http://www.joe.org/joe/2010february/rb4.php

Burke, A. (2011 May 22). Planning and Evaluating Digital Media Campaigns for the Public Sector. Social Marketing Quarterly. Retrieved (February 15th, 2012) from: http://www.socialmarketingquarterly.com/planning-and-evaluating-digital-media-campaigns-public-sector

Byington, T. (2010 December). Keys to Successful Mentoring Relationships. Journal of Extension. [Online], 48(6) Article 6TOT8. Available at: http://www.joe.org/joe/2010december/tt8.php

Carlson, C., Deloitte, & Touche. Traditionalists, Baby Boomers, Generation X, Generation Y (and Generation Z) Working Together: What Matters and How They Learn? United Nations Joint Staff Pension Fund: Executive Office, Talent Management Team brief. Retrieved (April 4, 2011) from: http://www.un.org/

Chesney, C. (1992). Work Force 2000: Is Extension Agriculture Ready? Journal of Extension. [Online], 30(2) Article 2FUT2. Available at: http://www.joe.org/joe/1992summer/fut2.php

Coates, D. (2004, June). Weblogs as a disruptive technology for Extension. Journal of Extension [Online], 42(3) Article 3COM1. Available at: http://www.joe.org/joe/2004june/comm1.php

Diem, K., Gamble, K., Hino, J., Martin, D., & Meisenbach, T. (2009, October). Assessing county Extension programs’ readiness to adopt technology; an OSU case study of two Oregon counties. Oregon: Author.

Frank, F., Finnegan, R., & Taylor, C. (2004). The Race for Talent: Retaining and Engaging Workers in the 21st Century. Retrieved (March 5, 2011) from: http://www.commerce.uct.ac.za

Harriman, L. & Daugherty, R. (1992). Staffing Extension for the 21st Century. Journal of Extension. [Online], 30(4) Article 4FUT1. Available at: http://www.joe.org/joe/1992winter/fut1.php

HR Council for the Nonprofit Sector, EKOS Research Associates, Inc. (2010 June). Why Nonprofit? University student perceptions of careers in the nonprofit sector. (Research report.) Retrieved from: http://hrcouncil.ca/newsroom/documents/HRC_Why_Nonprofit_0610.pdf

Keeter, S. & Taylor, P. (2009, December 11). The Millenials. (Research publication). Retrieved (May 5, 2011) from Pew Research Center website: http://www.pewresearch.org

Keeter, S. & Taylor, P. (2010 February). Millenials: A Portrait of Generation Next. (Research report). Retrieved from Pew Research Center website: http://www.pewresearch.org/millenials

King, D., Boehlje, M. (1992, October). Extension: on the brink of extinction or distinction? Journal of Extension [Online], 38(5) Article 5COM1. Available at: http://www.joe.org/joe/2000october/comm1.php

Louisiana Department of Civil Service. (2007 April). Workforce Horizons: Planning Tomorrow’s Workforce Today. (Volume Two, Issues 13). Retrieved from: http://www.louisdl.louislibraries.org

Milburn, L., Mulley, S. & Kline, C. (2010 December). The End of the Beginning and the Beginning of the End: Decline of Public Agricultural Extension in Ontario. Journal of Extension. [Online], 48(6) Article 6FEA7. Available at: http://www.joe.org/joe/2010december/a7.php

Qualman, E. (2009 November). Statistics show social media is bigger than you think. Retrieved (November 23, 2009) from http://socialnomics.net.

Safrit, R.D. & Owen, M. (2010 April). A Conceptual Model for Retaining County Extension Program Professionals. Journal of Extension. [Online], 48(2) Article 2FEA2. Available at: http://www.joe.org/joe/2010april/a2.php

Seevers, B. & Dormody, T. (2010 December). Turning an Extension Aide into an Extension Agent. Journal of Extension. [Online], 48(6) Article 6IAW1. Available at: http://www.joe.org/joe/2010december/iw1.php

Seger, J. (2011 February). The New Digital [St]age: Barriers to the adoption and adaptation of new technologies to deliver Extension programming and how to address them. Journal of Extension. [Online], 49(1) Article 1FEA1. Available at: http://www.joe.org/joe/2011february/a1.php

Siemens, G. (2009). Knowledge and our structures of learning. Retrieved (November 25, 2009) from http://www.elearnspace.org.

Stehulak, N. (2000 June). The Gift of a New Generation. Journal of Extension. [Online], 38(3) Article 3COM1. Available at: http://www.joe.org/joe/2000june/comm1.php

The Ohio State University Extension. (2008). Launching the strategic plan: see yourself in Extension’s future. Columbus, Ohio: College of Food, Agriculture and Environmental Sciences division of Communication and Technology.

Toland, D. (2011, November). Discover Your Social Brand: an Ohio Farm Bureau guide to creating, managing, and maintaining your Facebook business page. Ohio Farm Bureau Federation. Columbus, Ohio.

Toland, D. (2010 August). Discover Your Social Web: an Ohio Farm Bureau guide to social media, version 2.0. Ohio Farm Bureau Federation. Columbus, Ohio.

Trunk, P. (2007 July 5). What Gen Y Really Wants. Time. Retrieved (April 12, 2011) from: http://www.time.com

USDA, (2009). Salary analysis of Cooperative Extension Service positions, December 2007, Cooperative State Research Education and Extension Service, USDA. Washington, D.C: Retrieved from http://www.csrees.usda.gov/about/human_res/pdfs/report2009.pdf

Varcoe, L. (2009 February). Blogging grows by 68%. Retrieved (November 24, 2009) from http://libbyvarcoe.wordpress.com.

Wells, E. (2009). MSUE Educators' perceptions of the use of technology in their work. Michigan; Author