This is a summary of The Effect of Gender, Ethnicity, and Income on College Students’ Use of Communication Technologies
Authors: Reynol Junco, Dan Merson, and Daniel W. Salter
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This study was done a few years back (as shown in the content), but it is still relevant. It examined how gender, ethnicity, and income shape college students’ ownership and use of communication technology. The authors focused on three tools: cell phones, text messaging, and Instant Messaging (IM). They framed the research around digital inequality, a concept that covers both unequal access to technology and unequal patterns of use once people have it.
Researchers surveyed students at four large, public, four-year universities. Two schools surveyed their entire student body. Two others surveyed randomly selected samples. The total pool reached 38,345 students. The final response count was 4,491, giving an 11.7% response rate. The survey was conducted in 2006/2007 via SurveyMonkey. So, the data are dated, but still very interesting.
Respondents averaged 23 years old. Women made up 62% of the sample, men 38%. The sample was skewed white at 77%, with African-American, Latino-American, and Asian-American students each making up smaller shares. This is interesting, as it is similarly reflected in the Purnell method for cultural competence data outcomes.
The researchers used logistic regression to study cell phone ownership, since ownership is a yes-or-no outcome. They used hierarchical linear regression to study usage patterns, since usage is measured in continuous units such as minutes or the number of texts. They grouped predictors into three blocks: income, ethnicity, and gender.
Cell phone ownership
Ownership was nearly universal. 97% of respondents owned a cell phone. Still, clear gaps showed up. Women were more than twice as likely as men to own one. White students were more than twice as likely as African-American students to own one. Income mattered too. Students from the lowest income bracket, under $9,999 a year, were far less likely to own a phone than students from the median bracket ($50,000–$74,999). Students from the $100,000–$149,999 bracket were more than three times as likely to own one as median-income students.
Cell phone usage
Ownership and usage told different stories. Once students owned a phone, women used it more than men. African-American and Latino students used it more than white students, despite African-American students being less likely to own one in the first place. High-income students, particularly those earning $150,000 or more, also logged more talk time. Gender accounted for roughly two-thirds of the variability explained in this model. Ethnicity explained more of the variance than income did.
Text messaging
A similar pattern held for texting. Being female and being African-American both predicted higher text volume. Students from households earning $100,000 or more sent more texts than those in the median bracket. Gender and the combined effect of income and ethnicity contributed about equally to this model, and for some differences between successful and struggling students it might offer an explanation as well.
Instant Messaging
Instant Messaging (IM) stood apart. None of the three predictors, gender, ethnicity, or income, showed a significant relationship with IM use. The authors suggest this is because IM ties closely to computer access, and computers have become a near-universal, institutionally supported resource on campus. Cell phones, by contrast, are personally funded and not subsidized by universities, which may explain why disparities show up there but not in IM use.
Discussion
The authors argue that digital inequality persists even as raw ownership numbers approach saturation. The gaps aren’t about who has a phone anymore; they’re about who talks more, texts more, and relies more heavily on the device once they have it. Women, they suggest, use technology in ways tied to social connection, which lines up with prior research on gender and internet use. African-American and Latino students may lean on cell phones to stay connected with family and support networks, particularly on predominantly white campuses where they report feeling marginalized.
The authors point out a limitation: even where results reached statistical significance, the models explained a small share of the variance, between 2.8% and 9%. The large sample size let them detect subtle differences, but these differences are modest in practical terms.
Implications
The authors argue that colleges relying on text alerts or cell-based communication for emergencies and campus updates should account for these gaps. They suggest universities consider subsidizing phone access for low-income students through partnerships with service providers, similar to how they already provide computer lab access to students without personal computers. They call for more research into how different student groups respond to different types of messages, from casual peer texts to official emergency alerts.
The study represents one of the earlier academic looks at cell phone use specifically, as most prior digital divide research focused on computers and internet access rather than mobile communication.