































   Advancements in Agricultural Development 
  Volume 4, Issue 4, 2023 
  agdevresearch.org 

 

1. Klae D. O’Brien, Former Graduate Student, University of Idaho, 875 Perimeter Dr., Moscow, ID. 84844, 
orbi5038@vandals.uidaho.edu. 

2. Sarah A. Bush, Assistant Professor of Agricultural Leadership Education, University of Florida, PO Box 112060, Gainesville, 
FL 32611-2060, sab5271@ufl.edu,  https://orcid.org/0000-0002-6706-7037. 

3. Kattlyn J. Wolf, Professor of Agricultural Education, Leadership & Communications, University of Idaho, 875 Perimeter Dr. 

MS2040, Moscow, ID 84844, kwolf@uidaho.edu,  https://oricid.org/0000-0003-1274-6734. 
4. Maggie Elliot, Science & Communications Director, Hop Growers of America. P.O. Box 2885 Yakima, WA 90907, 

melliot@wahops.org.  
 

58 

 

The Communication Preferences of University of Idaho 
Extension Professionals and their Constituents 

 
K. D. O’Brien1, S. A. Bush2, K. J. Wolf3, M. Elliot4 

 
 

 
Article History 
Received: September 4, 2023 
Accepted: December 7, 2023 
Published: December 20, 2023 
 
 
Keywords 
communication channels; 
communication types; census survey; 
COVID-19 
  

Abstract 
As Cooperative Extension Services (CES) grow, agriculture evolves, and 
urbanization increases, Extension professionals are challenged to 
continue meeting the needs of their constituents by providing reliable, 
research-backed information to their communities. This includes utilizing 
appropriate communication means to reach their constituents. 
Therefore, the purpose of this study was to examine the communication 
preferences of University of Idaho CES professionals and their 
constituents and the communication types and channels most used. We 
used a cross-sectional descriptive census survey design and administered 
the survey to all University of Idaho CES faculty and educators. We 
analyzed the data via descriptive statistics, Wilcoxon signed rank tests, 
and paired sample t-tests. University of Idaho CES professionals ranked 
mainly individual communication channels as their preferred method of 
communication. However, they felt their constituents may prefer mass or 
group communication channels more than they do. CES professionals 
should utilize audience segmentation to serve their constituents better. 
COVID-19 also significantly increased the time spent preparing 
communications and utilizing mass communications. While 
technological-based communication increased during COVID-19, it is 
important to consider access and availability to constituents. 
Understanding what resources constituents have available and how they 
prefer to receive their information, can help CES professionals maintain 
relationships with their audiences. 

 

mailto:sab5271@ufl.edu
https://orcid.org/0000-0002-6706-7037
mailto:kwolf@uidaho.edu
https://oricid.org/0000-0003-1274-6734
mailto:melliot@wahops.org


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Introduction and Problem Statement 
 
The Cooperative Extension Service (CES) provides reliable, research-backed information from 
land-grant universities to people, communities, and businesses (Seevers & Graham, 2012). 
Although CES was designed to communicate with the public, it has been referred to as the “best 
kept secret” and needs to be promoted to remain relevant (Ray et al., 2015). CES was founded 
for agricultural and rural constituents’ needs. However, today only 17% of the U.S. population 
resides in rural areas (National Institute of Food and Agriculture [NIFA], 2021), and 10.9% of 
adults are employed in agriculture with 1.3% working on farms (Economic Research Service 
[ERS], 2020). This can pose a gap in communication strategies in urban-based programs 
because communication needs and norms might differ (Webster & Ingram, 2007). CES has 
broadened and adapted programming to encompass an increasingly urban audience, but to 
ensure longevity, CES needs to continue evolving to meet the needs of urban audiences (Ray et 
al., 2015).  
 
CES professionals act as communicators and liaisons of research-backed information and help 
to assist in the cyclical nature of communication (Kurtzo et al., 2019). These individuals must 
rely on new media channels and social trends to determine how to broadcast their messages 
widely. CES professionals utilize many communication channels to send messages to their 
constituents, including electronic sources, face-to-face, phone, print, etc. (Kurtzo et al., 2019). 
CES professionals suggested that understanding how to communicate effectively is an 
important aspect of their job and specifically included listening to constituents and 
reciprocating effective communication (McDowell & Mizuno, 1987). For example, age and 
gender have been shown to have an impact on communication preferences (Lamm et al., 
2016). Understanding constituents’ needs, characteristics, and demographics can help CES 
professionals tailor their communication efforts specifically and increase the likelihood of 
understanding and acceptance (Agunda, 1998).   
 

Theoretical and Conceptual Framework 
 
Diffusion of innovation (DOI) and framing theories served as the theoretical foundation for this 
study. DOI theory describes the process of spreading and eventual acceptance or rejection of 
new innovations through a social system (Rogers, 2003). DOI theory can be initiated by the 
presentation of research-based information from CES professionals, who often serve as change 
agents and influence the decision to accept or reject new information. Those who understand 
their roles and identify as communicators and change agents can utilize the innovation-decision 
process to effectively share information on new research and innovations (Rogers, 2003).  
 
Extension professionals rely on constituents to be receptive and accept the information they 
are providing. Rogers (2003) defines the process of diffusion, “by which an innovation is 
communicated through certain channels over time among the members of a social system” (p. 
11). It is believed communication channels and the social system in which the information is 
being spread have an impact on how the information travels and how constituents perceive it 

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(Rogers, 2003). Mass media can provide the most efficient channel for communicating new 
information with large groups of people. However, interpersonal channels can increase the 
likelihood of audience reception and acceptance of information––especially if those involved in 
the communication have similarities or personal links (Rogers, 2003). 
 
The concepts of framing theory can help to increase the effectiveness of a CES professional’s 
communication (Daamen et al., 2001). Framing theory postulates messages that are specifically 
designed for a selected audience are more easily understood and accepted (Robinson, 2013). 
Understanding and utilizing the concepts of framing theory can help CES professionals modify 
their messages and programming to fit their constituents and aid in laying a better foundation 
for the message to be used (Robinson, 2013). Framing and DOI theories together can allow 
information to be specifically tailored for the selected audience and effectively presented to 
increase the likelihood of it being accepted.  
 
Figure 1 

Conceptual Model of the Relationships between Identity and Communication Preferences 

 
 
In the conceptual model guiding this study, the framing of the information, as impacted by the 
extension professional’s identity and the audience, will then have an influence on the 
communication types and channels utilized. Communication types, individual, group, or mass 
communication, dictate which communication channels are then utilized for the diffusion of 
information (Rogers, 2003). Utilizing the correct communication type is important to 
communicate with constituents efficiently and effectively (Rumble et al., 2022). Additionally, it 
was essential to consider how COVID-19 restrictions impacted the communication usage of CES 
professionals to both minimize the limitations of the study and assess potential long-term 
changes related to communication and program delivery. 
 

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Purpose 
 

The purpose of this research was to examine the communication preferences of University of 
Idaho CES professionals and their constituents and the communication types and channels used 
most commonly. Further, we examined the impact of COVID-19 on communication type and 
channel usage. The objectives for this study were:  
Objective 1: Examine differences in personal and constituent communication channel 

preferences of University of Idaho CES educators and faculty. 
Objective 2: Examine differences in communication channel usage before and during COVID-19 

of University of Idaho CES educators and faculty. 
Objective 3: Examine differences in time spent communicating and communication type usage 

before and during COVID-19 of University of Idaho CES educators and faculty. 
 

Methods 
 
We used a cross-sectional descriptive census survey design. We administered the survey 
through Qualtrics and recruited via email from March 1 to 16, 2021. Our target population 
consisted of University of Idaho CES faculty and educators who all have obtained a master’s or 
doctorate degree and work at a county office, University of Idaho campus, or research and 
experiment station. We sent the survey to 139 individuals and received 72 full responses for a 
response rate of 52%. To handle non-response bias, we compared early and late respondents 
using Mann-Whitney and t-tests (Lindner et al., 2001). There were no significant differences in 
responses.  
 
We developed a census survey following the concepts of Dillman’s Tailored Design Method 
(Dillman et al., 2014). To establish content and face validity, we used previous literature (Kurtzo 
et al., 2019; Narine & Meier, 2020; Seevers & Graham, 2012) to develop items that were 
evaluated by three faculty members from the University of Idaho. The survey included 10 
questions regarding the individual’s communication behavior and preferences and nine 
demographic questions. Respondents indicated how often they utilized communication 
channels during a normal year, before COVID-19 pandemic restrictions, and during the COVID-
19 pandemic. They then ranked the communication channels that they most preferred to those 
they least preferred, followed by ranking the communication channels from most preferred by 
constituents to least preferred by constituents. The communication channels listed were 
Facebook, Instagram, Twitter, YouTube, other social media, walk-in/in-person, text, phone call, 
email, mailed newsletter, emailed/online newsletter, website, magazine, radio, television, or 
other. Respondents ranked their usage of each of these channels based on a 6-point Likert 
scale: never, monthly, biweekly, weekly, daily, or more than daily. Respondents indicated what 
percent of their time communicating was spent in each of the communication types: individual, 
group, and mass (Seevers & Graham, 2012). Respondents categorized their time by entering the 
appropriate percentage for each communication type in a typical year. Respondents were again 
prompted to answer the two questions regarding which communication methods were used 
the most and what percentage of their time was spent communicating via each communication 

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type in reflection of the year spent adhering to COVID-19 restrictions. Respondents were then 
asked to enter a numerical value that represented what percentage of their time during a 
typical week they spend communicating with their constituents and what percentage of their 
time they spend preparing communication materials both prior to and during COVID-19. We 
conducted 12 follow-up interviews where participants confirmed their item responses to assist 
in establishing reliability.  

With a 52% response rate, it was also important to examine the representation of the extension 
educators and faculty across the state based on demographics. Responses based gender, race, 
county type, tenure track, rank, and position title were comparable to University of Idaho 
statistics with <4% difference for all. Respondents’ age ranged from 25 to 68 with a mean of 
47.55 years (SD = 12.07). Time working in extension ranged from .5 years to 39 years with an 
average of 12.19 years (SD = 10.12). Respondents represented 14 extension program areas. 
 
We analyzed the data via descriptive statistics, Wilcoxon signed rank tests, and paired samples 
t-tests. We used descriptive statistics to describe the respondents’ preferred communication 
types and channels. We conducted Wilcoxon signed rank tests to compare personal and 
constituent preferences for communication channels and changes in channel usage based on 
the COVID-19 pandemic. We implemented paired samples t-tests to examine differences in the 
time spent communicating and preparing communication materials and usage of 
communication types before and during COVID-19. 
 

Findings 
 
We utilized Wilcoxon signed rank tests to compare the respondents’ personal communication 
channel preferences with what they indicated as their constituents’ preferred communication 
channel preferences (Table 1). Constituent preferences were ranked statistically significantly 
higher than personal for social media (Z = -2.76, p = .01) and mailed newsletters (Z = -2.37, p = 
.02). The effect size for social media was -.33 indicating a medium effect. For mailed 
newsletters, the effect size was -.28 meaning a small effect. Personal preferences were ranked 
statistically significantly higher than constituents for walk-in (Z = -2.72, p = .02), phone calls (Z = 
-2.55, p = .01), and radio (Z = -2.56, p = .01). The effect size for walk-ins (r = -.32), phone calls (r 
= -.30), and radio (r = -.30) indicated medium effects. The differences between rankings for 
personal and constituent preference for text, emails, online newsletters, website, magazines, 
television, and other communication channels were not statistically significant.  
 
 
 
 
 
 
 
 
 

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Table 1 
Wilcoxon Signed Rank Tests of Communication Channel Preferences (n = 71) 
 Constituent Personal    
      M    SD      M SD Z p r 
Social Media 4.66 2.67 5.66 2.84 -2.76 .01* -.33 
Walk-in 2.92 2.22 2.25 1.73 -2.72 .02* -.32 
Text 5.08 2.60 4.97 2.33 -0.31 .76 -.04 
Phone Call 3.27 1.84 2.73 1.50 -2.55 .01* -.30 
Email 2.99 1.48 3.08 1.66 -0.24 .81 -.02 
Mailed Newsletter 6.83 1.95 7.45 2.10 -2.37 .02* -.28 
Online Newsletter 5.83 2.06 6.15 1.87 -1.22 .22 -.14 
Website 6.39 2.19 6.38 1.93 -0.69 .49 -.08 
Magazine 8.83 1.51 8.65 1.75 -1.26 .21 -.15 
Radio 9.85 0.91 9.48 1.07 -2.56 .01* -.30 
Television 10.73 0.99 10.62 1.03 -0.96 .34 -.11 
Other 10.62 3.04 10.56 3.22 -0.59 .56 -.07 

Note. Significance at the *p <.05 level, 2-Tailed. 1 is most preferred, 12 is least preferred. 
 

We used Wilcoxon signed rank tests to compare the communication channels before and 
during COVID-19 restrictions (Table 2). The usage of the following communication channels 
were statistically significantly higher during COVID-19: Facebook (Z = -4.07, p = .00), Instagram 
(Z = -2.33, p = .02), YouTube (Z = -4.33, p = .00), and magazine (Z = -2.31, p = .02). The effect 
sizes for Instagram (r = -.28) and magazines (r = -.28) were a low effect. The effect size for 
Facebook usage was -.49 meaning a medium effect. YouTube had a large effect size at -.52. -The 
following communication channels usage were statistically significantly lower during COVID-19: 
walk-ins (Z = -6.16, p = .00) and radio (Z = -2.81, p = .01). The effect size for radio was -.34 
meaning a medium effect. The effect size for walk-ins was -.74 indicating a large effect. There 
was no statistical significance for other communication channels. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Table 2 
Before COVID and During COVID Communication Channel Usage (n = 69) 
 Before COVID During COVID    

 M SD M SD Z p r 
Facebook 2.70 1.58 3.09 1.67 -4.07 .00* -.49 
Instagram 1.49 1.13 1.59 1.29 -2.33 .02* -.28 
Twitter 1.13 0.38 1.26 0.76 -1.63 .10  -.20 
YouTube 1.72 1.21 2.28 1.42 -4.33 .00* -.52 
Other Social Media 1.46 1.12 1.62 1.24 -1.75 .08 -.21 
Walk-in 4.07 1.40 2.43 1.28 -6.16 .00* -.74 
Text 3.83 1.79 3.90 1.76 -0.81 .42 -.10 
Phone Call 4.77 1.23 4.71 1.24 -0.86 .39 -.10 
Email 5.14 1.18 5.20 1.16 -0.23 .82 -.03 
Mailed Newsletter 1.78 0.86 1.67 0.72 -0.89 .38 -.11 
Website 2.83 1.63 2.88 1.53 -0.33 .74 -.04 
Magazine 1.45 0.68 1.33 0.63 -2.31 .02* -.28 
Radio 1.51 1.13 1.32 0.95 -2.81 .01* -.34 
Television 1.23 0.94 1.25 1.01 -1.00 .32 -.12 

Note. Significance at the *p <.05 level, 2-tailed. Likert scale: 1 = Never to 6 = more than daily. 
 

We conducted paired sample t-tests to compare how participants spent their time 
communicating before and during COVID-19 restrictions (Table 3). There was a significant 
difference in time spent communicating with constituents through mass communication before 
COVID (M = 14.75, SD = 10.71) and during COVID (M = 23.40, SD = 19.15), t(72) = -4.3, p = .00. 
The effect size for mass communication was -.530 indicating a moderate effect. There was also 
a significant difference in the percentage of time spent preparing communication material 
before COVID (M = 18.35, SD = 14.81) and during COVID (M = 28.39, SD = 19.40), t(72) = -6.44, p 
= .00. The effect size was -.737 meaning a moderate effect. There was not a significant 
difference in the percentage of time spent communicating, individual communication, or group 
communication before and during COVID-19.  

 
 
 
 
 
 
 
 
 
 
 
 
 

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Table 3 
Differences in Participants’ Time Spent Communicating Before and During COVID (n = 72) 
  M SD t p Cohen’s d 
Pair 1       
Before COVID % Spent Communicating    28.89 17.87 -1.92 .060 -.190 
During COVID % Spent Communicating  32.25 21.58    
      
Pair 2       
Before COVID % Preparing Communications 18.35 14.81 -6.44 .000* -.737 
During COVID % Preparing Communications 28.39 19.40    
      
Pair 3       
Before COVID % Individual Communication 36.53 19.91 1.01 .316 .119 
During COVID % Individual Communication 34.22 22.75    
      
Pair 4       
Before COVID % Group Communication 39.56 19.31 1.86 .067 .244 
During COVID % Group Communication 35.43 18.15    
      
Pair 5       
Before COVID % Mass Communication 14.75 10.71 -4.30 .000* -.530 
During COVID % Mass Communication  23.40 19.15    
Note. Significance at the *p <.05 level, 2-Tailed. 
 

Conclusions, Discussion, and Recommendations 
 
The highest-ranked communication channels of University of Idaho CES professionals were 
individual communication, with one channel falling under group. This finding was consistent 
with the most prevalent communication type usage and previous research that suggests 
constituents believe individual communication is more reliable and tailored to their specific 
needs (Licht & Martin, 2007; Rogers, 2003). Individual communication provides an opportunity 
for messages to be specifically framed for the individual (Jenkins et al., 2020), but lacks the 
reach of group and mass communication types, such as social media. Ranking of social media 
fell in the middle for both personal and constituents and indicated varied preferences based on 
high standard deviations and a range from 1 to 12 for both preferences. The variance may be 
based on the influence demographics and backgrounds have on preferences (Agunda, 1998).   
 
The traditional foundation for communication in CES, based on rural needs (Henning et al., 
2014), might explain why participants prefer individual communication more than their 
constituents. This lack of alignment can cause communication gaps. Understanding the 
audience’s needs, preferences for communication, and access to resources aids in efficient 
communication and is essential due to University of Idaho CES professionals reporting they 
spend nearly 50% of their time before and 60% during COVID-19 restrictions communicating 

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and preparing communication. Once the audience’s needs are understood, the concepts of 
framing theory can be applied to specifically target messages, which can increase the likelihood 
of adoption (Daamen et al., 2001). CES professionals can utilize audience segmentation to 
better serve their constituents through tailored research-based information (Lamm et al., 
2016).  
 
The COVID-19 pandemic required University of Idaho CES to rapidly adapt to regulations, which 
is consistent with their need to adjust to the changing times (Narine & Meier, 2020). University 
of Idaho CES professionals responded with an increase in time preparing materials and mass 
communication to combat the decreases in in-person and individual communication. 
Technology has become heavily relied upon during COVID-19 restrictions. However, not all 
Idahoans have access to reliable internet connection that allows constituents to access social 
media and other technology-based content. Understanding what resources constituents have 
available and how they prefer to receive their information can help maintain relationships with 
rural audiences. University of Idaho CES professionals face a unique challenge in meeting 
demographic needs due to Idaho’s growing and urbanizing population. Understanding the 
audience’s demographics can help to better tailor programming and communication materials 
(Curtis et al., 2012).  
 
There were several limitations in this study. We did not survey constituents, but rather 
assumed they would agree with the rankings provided by the respondents. We recommend 
future research be adapted to understand the constituent’s perspective. Responses may have 
differed if respondents were asked to segment their audiences based on demographic groups. 
Further research about how constituents prefer to communicate with CES would help uncover 
this phenomenon. There were limited respondents who indicated they used mass 
communication most often. While we compared early and late respondents and confirmed the 
sample was comparable to demographics across the state, it is still possible that more 
individuals use mass communication efforts. Further research could reveal if or why more CES 
professionals do not use mass communication more often. Due to time constraints, we were 
unable to use test retest to establish reliability and we acknowledge this as a limitation. 
Additionally, we collected survey data during the spring of 2021 when COVID-19 restrictions 
varied across Idaho. This most likely impacted feelings regarding restrictions and a replication of 
this study could reveal different responses. We recommend continued research to learn more 
about the long-term impacts of COVID-19 on the communication efforts of CES professionals.  
 

Acknowledgements 
 
K. O’Brien, conceptualization, methodology, formal analysis, investigation, writing-original 
draft; S. Bush, conceptualization, methodology, writing- reviewing and editing, supervision; K. 
Wolf, writing- reviewing and editing; M. Elliot, writing- reviewing and editing. 
 
 
 

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