Communication Research Reports

Communication Research Reports
Vol. 32, No. 1, January–March 2015, pp. 107–111
ISSN 0882-4096 (print)/ISSN 1746-4099 (online) # 2015 Eastern Communication Association
DOI: 10.1080/08824096.2014.989977
consider because students who use their mobile devices in class take less-detailed notes,
recall less lecture information, and receive lower scores on exams (Kuznekoff &
Titsworth, 2013). Additionally, Johnson (2013) found that students’ use of cell phones
to engage in computer-mediated communication (CMC) during class time (i.e., to
text) was a threat to student engagement and called for instructors to find ways to abate
such behavior. It is important to examine how instructors communicate these policies
in classrooms, as students may respond differently to a policy depending on how it is
presented to them. Therefore, this study explores students’ perceptions of cell phone
policies that instructors present with persuasive messages.
Chaiken’s (1980, 1987) heuristic-systematic model of information processing
(HSM) is a dual-process model of persuasion that posits that individuals can process
a message in one of two ways: systematically or heuristically. Systematic processing
occurs when a receiver is motivated to process all argument-relevant pieces of
information presented in a message. Heuristic processing relies on a few informational cues to come to a judgment on the message (Todorov, Chaiken, & Henderson,
2002). Consistent with the HSM, two hypotheses are proposed:
H1: Participants in the (a) fewer-arguments condition will be more likely to process a
cell phone policy heuristically than participants in the more-arguments condition, and participants in the (b) more-arguments condition will be more likely
to process a cell phone policy systematically than participants in the
fewer-arguments condition.
H2: Participants in the more-arguments condition will hold more favorable attitudes
toward a cell phone policy afterwards than participants in the fewer-arguments
condition.
The HSM also posits that individuals who are motivated to think about a message
tend to process persuasive appeals systematically, whereas people who are not as
highly motivated engage in heuristic processing (Chaiken, 1980). Therefore, the
following hypothesis is proposed:
H3: Participants in the (a) high-involvement condition will engage in greater
systematic processing than participants in the low-involvement condition, and
participants in the (b) low-involvement condition will engage in greater heuristic
processing than participants in the high-involvement condition.
Method
Undergraduates (N ¼ 118; 47 men and 71 women) participated during class time at a
large, mid-Atlantic university. Ages ranged from 18 to 31 (M ¼ 19.97), and 89% were
White.
The study used a 2 (number of arguments: high; low) 2 (involvement: high; low)
experimental design. Participants responded to half of the items, viewed one of two
video clips (more or fewer arguments), then finished the survey. A pilot test for the
manipulation of more or fewer arguments with two groups of participants (n ¼ 138)
who did not participate in the main study revealed a significant difference between the
more-arguments (M ¼ 2.21, SD¼ .89) and fewer-arguments (M ¼ 1.70, SD¼ .74)
108 A. L. Lancaster & A. K. Goodboy
pilot groups, t(133)¼ 3.58, p < .001. A manipulation check of involvement was
successful, with all but 17 participants, who were excluded from further analyses,
responding correctly to the single-item check.
Cell phone use was measured using four forced dichotomy (i.e., yes=no) items that
were developed for this study. Participants used their cell phones to send or receive
text messages (n ¼ 114), surf the Internet (n ¼ 99), make calls (n ¼ 9), and watch
media (n ¼ 13).
Campbell’s (2006) Attitudes toward Mobile Phones scale was used to assess cell
phone policy attitudes. Measurements were conducted for attitudes preexposure
(M ¼ 4.08, SD ¼ 1.35, a ¼ .76) and postexposure (M ¼ 3.79, SD ¼ 1.35, a ¼ .72).
Griffin, Neuwirth, Giese, and Dunwoody’s (2002) systematic and heuristic risk
information processing items were modified to address cell phone policies. For systematic
processing, measurements were conducted for premessage exposure (M ¼ 3.63,
SD¼ 1.17, a ¼ .59) and postmessage exposure (M ¼ 4.50, SD¼ 1.29, a ¼ .61). For heuristic processing, measurements were conducted for premessage exposure (M ¼ 4.78,
SD¼ 1.05, a ¼ .53) and postmessage exposure (M ¼ 4.08, SD¼ 1.26, a ¼ .58).
Participants rated message quality using three 7-point semantic differential items
modified from the 9-point semantic differential items used in Petty, Cacioppo,
and Schumann’s (1983) study. Measurements were conducted for the
more-arguments (M ¼ 3.00, SD ¼ 1.41, a ¼ .88) and fewer-arguments (M ¼ 3.91,
SD ¼ 1.45, a ¼ .86) conditions.
Four 7-point Likert-type items (1 ¼ completely unlikely; 7 ¼ completely likely) were
developed for this study to measure propensity to comply with cell phone policies.
Measurements were conducted for the more-arguments (M ¼ 2.96, SD ¼ 1.43,
a

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