Sixty years of quantitative communication research summarized: lessons from 149 meta-analyses

ABSTRACT

In an effort to better understand the state of knowledge production in the field of Communication, we examine the results of 149 meta-analyses exploring human communication phenomena. The meta-analyses summarize more than 60 years of quantitative research involving more than 8 million participants. The mean effect estimate is r = .21, and three-quarters of the meta-analyses reported an estimate of less than r = .29. Several trends in the findings from the meta-analyses are examined. The results underscore the notion that communication is a complex and highly contingent phenomenon and highlight some specific instances in which communication variables and processes produce (in)substantial effects. Taken as a whole, this project offers insights about the status of quantitative communication research and the collective efforts of scholars working in our discipline.

KEYWORDS:

• Communication
• quantitative research
• meta-analysis
• research summary

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Stephen A. Rains is Professor of Communication at the University of Arizona.

Timothy R. Levine is Distinguished Professor of Communication at the University of Alabama at Birmingham.

Rene Weber is Professor of Communication at the University of California, Santa Barbara.

Notes

1 Although aggregating multiple effects per meta-analysis was not ideal, it was essential to avoid issues with non-independence. Aggregating effects was necessary in less than 30% of the meta-analyses in our sample.

2 Perhaps Cohen’s (1988) benchmarks are better understood as pre-defined percentiles, which have been replicated in communication scholarship (Weber & Popova, 2012). That is, they reflect the rarity of a given effect estimate in a body of research and might be better labeled as ‘common,’ ‘uncommon,’ and ‘rare.’