Who Are the “Masses” in Mass Communication Research? Exploring Participants’ Demographic Characteristics Between 2000 and 2014

Abstract

Demographics may influence the results and implications of mass communication research. Yet, there is a dearth of studies exploring the extent to which research in the field reports participants’ demographics and the composition of its study samples. This content analysis takes an identity theory and ecological systems theory approach to examine participants’ demographic characteristics in all mass communication studies conducted in the U.S. and published in six peer-reviewed journals from 2000 to 2014 (N = 1,278). According to our census, three-fourths of the studies reported gender, two-thirds reported age, two-fifths reported race/ethnicity and one-third reported education. While the reporting of demographics improved during the 15-year period, participants continued to be mostly educated, young, White women. In light of these findings, our theoretical framework contends that many of these studies may paint an incomplete picture of the role media play in the lives of the U.S. users and audiences. Furthermore, reporting of participants’ demographics as well as sample composition differed by research methods and subdisciplines, thus revealing a lack of standard protocols across the discipline. Findings from this study encourage researchers to systematically record, report and analyze participant demographics, as well as to take into account participants’ heterogeneity within these demographic groups.

Keywords:

• Demographics
• content analysis
• social identities
• participants’ characteristics
• mass communication research

Notes

1 Only one study (Potter et al., 1993) analyzed slightly more studies over a larger time frame, but its analysis included studies published every three years as opposed to all studies in its time frame.

2 The number of participants in the studies used for this analysis ranged from 1 to 112,038 (M = 1,249.64; SD = 5,804.69). A total of 1,593,291 participants took part in all the studies).

3 The average percentages for participants’ racial/ethnic and gender identities do not add to 100% because this analysis only used the numbers reported in the studies. We did not ‘create’ data for non-reported numbers for the following reasons: (1) it would have meant conceptualizing gender as a dichotomous variable regardless of what answer options researchers would have provided to their participants, (2) it would have been impossible to do for race/ethnicity, and (3) it would not have been possible to take into account the number of participants who may not have answered a demographic question unless that information was clearly indicated, which was rarely the case. These studies were still coded as having reported participants’ gender and/or race/ethnicity.

4 Although not reported here, we coded for demographic variables being included in a study’s research questions or hypotheses. We found that 11% of studies explored gender, 7.9% explored age, 7.7% explored race/ethnicity and 4.2% explored education.