The Journal of Extension - www.joe.org

June 2010 // Volume 48 // Number 3 // Feature Articles // 3FEA5

Engaging the Engagers: Implications for the Improvement of Extension Work Design

Abstract
County Extension agents from the Midwest were surveyed on a variety of psychological variables. Differences among agents in the fields of Family and Consumer Science (FCS), Agriculture and Natural Resources (ANR), and 4H Youth Development (4HYD) were examined as well as differences among highly and lesser engaged agents. Results showed that FCS agents had higher levels of dedication, absorption, and work-family facilitation. ANR agents reported greater work-role salience than other areas and lower family-role salience. Highly engaged agents reported experiencing greater work-family facilitation, positive affectivity, and psychological capital. Implications for design and management of Extension work are discussed.


William S. Weyhrauch
Graduate Student
wsweyhra@ksu.edu

Satoris S. Culbertson
Assistant Professor
satoris@ksu.edu

Maura J. Mills
Assistant Professor
mjmills@ksu.edu

Clive J. Fullagar
Professor
fullagar@ksu.edu

Kansas State University
Manhattan, Kansas

The many land-grant colleges and universities in the United States have three missions: research, teaching, and Extension. The third mission charges institutions with extending knowledge and resources into programs that engage the community and fulfill public needs. Areas of service include Family and Consumer Sciences (FCS), Agriculture and Natural Resources (ANR), and 4H/Youth Development (4HYD), each of which has its own unique mission. FCS agents teach healthy eating and physical activity habits, promote positive quality of life, and encourage maintaining sustainable communities. ANR agents teach conservation; improve the quality of land, air, and water; and create efficient and sustainable animal production, cropping, horticulture, and farming systems. Finally, 4HYD agents promote positive youth and family development by teaching young people leadership, citizenship, and life skills.

Previous research on differences among agents has examined demographic patterns between 4-H agents and volunteers (Culp, McKee, & Nestor, 2005). However, differences among agents likely involve more than their particular missions, job duties, and demographics. Indeed, the types of people who are attracted to jobs in these areas may vary considerably. Likewise, those who stay in their jobs likely have different characteristics from those who resign. Manton and van Es (1985) examined this issue, finding that numerous factors lead to job dissatisfaction and subsequent exit from Extension work, including dissatisfaction with administration, time away from family, and other opportunities.

Purpose/Objectives

In this article, we examine differences among agent classifications regarding level of work engagement, work-family conflict/facilitation, work- and family-role salience, psychological capital, and positive/negative affectivity. The unifying concept driving the choice of these variables was their potential for affecting job satisfaction. Identifying differences among focal areas will provide insight to Extension directors seeking to improve training, selection, and performance management procedures by tailoring them according to their varied work environments. Doing so should subsequently promote greater productivity, mental health, satisfaction, and decrease employee turnover. Additionally, we identify personal and situational characteristics associated with highly engaged Extension workers.

Literature Review

Of interest in the study reported here were a variety of psychological characteristics, including engagement, psychological capital, work-family conflict/facilitation, work- and family-role salience, and positive/negative affectivity. We discuss what these are and their importance to Extension agents.

Engagement

Engagement is "a positive, fulfilling, work-related state of mind" (Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002). It is a lasting, pervasive frame of mind comprised of three components:

  1. Vigor—characterized by energy, effort, and persistence

  2. Dedication—characterized by enthusiasm, inspiration, and pride

  3. Absorption—characterized by total concentration, engrossment in work, and a sense of time passing quickly

Employee engagement is positively related to beneficial outcomes such as job satisfaction, organizational commitment, and organizational citizenship behaviors, and is negatively related to detrimental outcomes, such as turnover intentions (Saks, 2006) and burnout (Schaufeli et al., 2002). At an organizational level, employee engagement has been shown to predict organizational success and financial performance (Harter, Schmidt, & Hayes, 2002).

Psychological Capital

Psychological capital is a state-like construct defined as "an individual's positive psychological state of development" (Luthans, Youssef, & Avolio, 2007, p. 3) and consisting of four components.

  1. Self-efficacy: having the confidence to take on and put in the necessary effort to succeed at challenging tasks

  2. Optimism: making positive attributions about succeeding now and in the future

  3. Hope: persevering toward goals and, when necessary, redirecting paths to goals in order to succeed

  4. Resilience: sustaining effort and bouncing back to attain success when faced with obstacles and adversity

Psychological capital represents individuals' motivational tendencies accumulated through these components. As such, psychological capital can be thought of as positive thought processes that people bring with them to various situations. The greater one's level of psychological capital, the more capable one is of functioning in different situations, adjusting to change, and handling obstacles.

Work-Family Conflict and Facilitation

The interplay individuals have between their work and families can be problematic or beneficial. The problematic interaction, known as "work-family conflict," occurs when the demands of work interfere with personal obligations (Kopelman, Greenhaus, & Connolly, 1983). Work-family facilitation, on the other hand, occurs when participation in multiple roles benefits the individual by facilitating the integration and management of the roles (Hanson, Hammer, & Colton, 2006).

Increased work-family conflict is related to numerous negative outcomes, including:

  • Lower levels of general well-being (Frone, 2000)

  • Lower job satisfaction (Adams, King, & King, 1996)

  • Higher burnout (Burke, 1988)

  • More alcohol use and poorer health (Allen, Herst, Bruck, & Sutton, 2000)

  • Lower performance and increased turnover (e.g., Allen et al., 2000)

Increased work-family facilitation, conversely, has been linked to positive outcomes, including:

  • Lower turnover intentions (Balmforth & Gardner, 2006)

  • Higher job, family, and life satisfaction (Balmforth & Gardner, 2006)

  • Higher organizational commitment (Balmforth & Gardner, 2006)

  • Increased organizational citizenship behaviors (Balmforth & Gardner, 2006)

  • Lower levels of depression for both individuals and their spouses/partners (Hammer, Cullen, Neal, Sinclair, & Shafiro, 2005)

Work and Family Role Salience

Work and family role salience refer to the internalized beliefs and attitudes that individuals have for their work and families (Amatea, Cross, Clark, & Bobby, 1986). That is, they refer to the importance that work and family play in someone's life. For example, some individuals place a strong emphasis on their work, over and above their family lives. These individuals may feel a void in their lives if they do not have what they consider to be successful careers.

Additionally, these individuals may be more likely to identify with work—for example, if you ask where they see themselves in 5 years, they may speak in terms of their career goals. This is in contrast to individuals who place more emphasis on their families and are more likely to respond in terms of familial relationships (e.g., marriage, children). Such family-oriented individuals would be more likely to base their life satisfaction on how they view their family lives.

Of course, it is possible to place importance on both work and family simultaneously and seek a balance. In general, however, people vary in terms of the importance or emphasis they place on each, and this likely changes over time. Role salience is likely to help explain role stress (and may help explain work-family conflict) and may predict the degree of involvement in particular roles (Amatea et al., 1986).

Positive and Negative Affectivity

Positive and negative affectivity can be measured as either state (temporary) or trait (consistent) variables. Positive affectivity indicates a person's tendency to feel enthusiastic, active, and alert. Someone who has high positive affectivity should experience high energy, concentration, and pleasurable relations with others. Conversely, negative affectivity is characterized by distress and displeasure associated with a variety of states, such as anger, contempt, disgust, guilt, fear, and nervousness.

Method

Sample

The sample consisted of county Extension agents who worked throughout a Midwestern state. Informational meetings were held throughout the state to inform agents of the upcoming research in an effort to increase participation. All 245 county Extension agents in the state were asked to participate and subsequently received an email describing the research in further detail. Those agents opting to participate were then sent an email with a link to an online survey. As an incentive to complete the survey, participants were entered into a drawing for a $20 gift card to a popular online retailer.

A total of 104 agents (42%) returned the survey. Of these, 98 individuals (34% male, 98% White) provided sufficient data to be included. The mean age was 41.06 years (SD =12.18). Participants worked an average of 48.81 hours per week (SD = 5.13) and reported a mean tenure of 11.06 years (SD = 9.64). Table 1 contains more detail on our sample to help readers assess the extent to which our results may generalize to their population of interest.

Table 1.
Demographics

Education LevelProportion of Sample
Some college or community college1.9%
Associates (2 yr.) degree< 1.0%
Bachelor's (4-yr) degree52.8%
Master's degree38.7%
Job Area 
Family and Consumer Sciences28.3%
Agriculture and Natural Resources17.9%
4-H and Youth Development44.3%
Urban Area Categories 
Rural area < 2,50027.4%
Urban cluster 2,500 - 4,9999.4%
Urban cluster 5,000 - 49,99936.8%
Urbanized area 50,000 - 199,99917%
Urbanized area > 200,0002.8%
*Note: Percentages may not add up to 100% due to missing data points
**Note: Urban area categories defined by the Bureau of the Census (2000)

The following measures were included in the online survey. Measures were selected based on how well they captured the constructs of interest. Additionally, each measure has demonstrated acceptable reliability and validity in previous studies.

Engagement

We measured engagement using the Utrecht Work Engagement Scale (Schaufeli et al., 2002), a 17-item measure of vigor (6 items; α = 0.84), dedication (5 items; α = 0.89), and absorption (6 items; α = 0.83). Responses ranged from 1 (never) to 7 (always).

Role Salience

We measured role salience using Amatea, Cross, Clark, and Bobby's (1986) scale, with five items measuring work-role salience (α = .62) and five measuring family role salience (α = .81). Responses ranged from 1 (strongly disagree) to 5 (strongly agree).

Work-Family Conflict and Facilitation

We measured work-family conflict and facilitation using eight items from Wayne, Musisca, and Fleeson's (2004) Work-Family Conflict/Facilitation scale. Conflict items (α = 0.77) assessed the extent to which pressures at work interfere with performance at home. Facilitation items (α = 0.64) assessed the extent to which skills, behaviors, or mood from work positively impact one's home life. Responses ranged from 1 (never) to 5 (all the time).

Affectivity

We assessed positive and negative affectivity using the Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1988). The measure is comprised of two 10-item sub-scales consisting of words that describe different positive (α = 0.89) and negative (α = 0.81) feelings and emotions. Responses ranged from 1 (very slightly or not at all) to 5 (extremely) and respondents were asked to rate each word in terms of the extent to which they generally feel this way.

Psychological Capital

We measured psychological capital using Luthans et al.'s (2007) 24-item measure assessing efficacy (α = 0.86), optimism (α = 0.86), hope (α = 0. 79), and resiliency (α =0.63). Responses ranged from 1 (strongly disagree) to 6 (strongly agree).

Results

The first step in our analysis was to investigate what differentiates agents in different focal areas in terms of the variables of interest. Analysis of variance (ANOVA) and subsequent post-hoc tests revealed several notable differences among agent classifications. There were significant differences among job areas in dedication, F (2,77) = 3.21, p < .05, revealing that FCS agents had significantly higher dedication levels than ANR agents (p < .05) and 4HYD agents (p < .05).

There were also significant differences among job areas in absorption, F (2,77) = 3.34, p < .05, with FCS agents reporting greater absorption than 4HYD agents (p < .05). There were no significant differences among job areas in vigor, the third component of engagement.

Analyses also revealed significant differences among job areas in family role salience, F (2,93) = 3.15, p <. 05, with ANR agents having lower family role salience than agents in FCS (p <. 05) and 4HYD (p < . 05). Also, significant differences among job areas in work-family facilitation, F (2,91) = 4.67, p < .05, showed that FCS agents reported greater facilitation than ANR agents (p < .01) and 4HYD agents (p < .05).

Our next step was to look across agent classifications and create a psychological picture of the highly engaged agent. We took each agent's composite engagement score and recoded these scores into groups. This allowed us to examine all agents within a certain range of scores on engagement as a single group. We then tested for factors that set apart those agents who reported the highest levels of overall engagement (composite score between 6.00 and 7.00). ANOVAs and subsequent post-hoc tests revealed that highly engaged agents reported significantly greater work-family facilitation, positive affectivity, and psychological capital than agents at nearly all other levels of engagement (Table 2).

Table 2.
Comparison of Agents by Engagement Level

 Engagement Levels ComparedMean diff.Standard Error
Work-Family facilitation6 vs. 50.66**0.17
 6 vs. 40.75**0.17
 6 vs. 30.98*0.38
Pos. affectivity6 vs. 50.57**0.15
 6 vs. 41.13**0.14
 6 vs. 31.12**0.32
Psychological Capital   
Efficacy6 vs. 50.38*0.2
 6 vs. 40.78**0.2
 6 vs. 30.73*0.44
Hope6 vs. 50.59**0.16
 6 vs. 41.06**0.16
 6 vs. 30.88*0.36
Resilience6 vs. 50.39*0.15
 6 vs. 40.7**0.15
 6 vs. 30.75*0.33
Optimism6 vs. 50.53*0.22
 6 vs. 40.95**0.22
 6 vs. 31.82**0.48
* = p < .05, ** = p < .01
Note: Engagement level 6 is the highest level of engagement. All agents reported engagement of at least level 3

Discussion

The study reported here provides insights regarding differences among agents in different focal areas in terms of various organizationally meaningful constructs. FCS agents exhibited higher levels of dedication and absorption in their work and also had higher levels of work-family facilitation. ANR agents reported greater work-role salience and lower family-role salience than those in other areas. The study also specifies psychological variables associated with highly engaged agents. These results indicated that highly engaged agents experience several positive outcomes, including increased work-family facilitation, positive affectivity, and psychological capital. While this might seem to be self-evident, the evidence that high engagement is associated with other positive outcomes emphasizes the importance of engaging employees.

The study is not without limitations. First, despite our efforts to increase response rates by making multiple contacts with participants, we had a relatively small response rate (42%) from a single state. Thus, it is possible that our results do not accurately reflect the true population parameters and may not generalize to agents in other states. Nevertheless, we argue that 42% is a respectable response rate for this methodology (Baruch, 1999; Van Horn, Green, & Martinussen, 2009). Related to this, those agents who chose to participate may have been atypically more engaged in their work than non-respondents. More research is needed to address whether this may be the case.

Implications

The findings of our study suggest that FCS agents are obtaining greater psychological outcomes from their work, possibly via greater engagement. Research has shown that engagement has a tendency to be contagious (Bakker, 2005). So, one possible avenue to improve engagement is to create systems by which less engaged agents interact and work with highly engaged agents. Mentoring programs, collaborative projects, or breakout sessions at Extension meetings could encourage agents to "catch" engagement from their peers. Other positive psychological states discussed herein can also be increased in agents. For instance, initial studies (e.g., Luthans, Avey, Avolio, Norman, & Combs, 2006) have shown that, because of the state-like nature of Psychological Capital, its four components can be increased through targeted interventions.

Programs designed to incorporate agents' families in the Extension effort might help to increase family-role salience among ANR agents and could improve work-family facilitation. FCS agents could use their expertise in family sciences to help design such programs for their fellow agents in ANR and 4HYD.

A broader implication of our study is that Extension directors should seek to increase employee engagement, because we have shown it to be associated with a variety of positive outcomes. The Job Characteristics Model (JCM; Hackman & Oldham, 1980) provides a theoretical framework for discussing ways to do this.

This model identifies five core job characteristics that can improve employee motivation and engagement.

  • Skill variety: variety of skills required by a job, such as interpersonal communication, computer programming, etc.

  • Task identity: degree to which employees experience the entire process of producing a product/ service

  • Task significance: the extent to which the work has important consequences to others within or outside the organization

  • Autonomy: the degree of control employees have over their daily activities

  • Feedback: the level of information provided to employees, either from within or outside the organization, about their job performance and ways to improve

The JCM has been shown to have a variety of positive employee outcomes, including engagement. Saks (2006) found that a composite score of all five of these job characteristics was positively correlated with employee engagement (ρ = .48).

There are a variety of ways in which jobs can be designed to maximize these characteristics. Below, we provide a few suggestions for Extension work specifically, but encourage Extension directors to be innovative in embedding these characteristics into the workplace.

  • Ensure that there is variety in the nature of tasks and assignments that agents undertake, for example teaching senior adults about finance on one day and youth on leadership adventure on another.

  • Facilitate feedback channels whereby agents can experience the impact that their work has on the lives of the people that they are interacting with.

  • Allow agents to be autonomous in assessing the needs of their clientele as well as the conceptualizing and executing of their work.

Due to our correlational approach, we can draw no conclusions as to cause and effect. Therefore, it would be inappropriate to speculate on why certain differences exist. We recommend that future research be done on the nature of differences among Extension work areas and how engagement and other psychological work outcomes might be affected by these differences. We also recommend that future researchers in this area investigate the similarities among agents. While we focused exclusively on their differences, an analysis of the areas in which they are similar may provide unique insights for Extension work.

Acknowledgements

This research was supported in part by a grant from the Center for Engagement and Community Development, Kansas State University.

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