ArticleCommunication methods and measures2013
Content Analysis as a Foundation for Programmatic Research in Communication.
Article in Communication methods and measures, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Facilitators and Barriers to Self-Volume Management in Older Patients with Chronic Heart Failure and Multimorbidity: A Qualitative Study.Healthcare (Basel, Switzerland) · 2025Article
- Exploring the Perspectives of Lung Cancer Chemotherapy Patients on Self-Management: A Qualitative Interview Study Using the COM-B Model.Patient preference and adherence · 2025Article
- Casual Sexual Scripts on the Screen: A Quantitative Content Analysis.Archives of sexual behavior · 2018Article
- Alcohol harm reduction advertisements: a content analysis of topic, objective, emotional tone, execution and target audience.BMC public health · 2017Article
- Measuring Exposure Opportunities: Using Exogenous Measures in Assessing Effects of Media Exposure on Smoking Outcomes.Communication methods and measures · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Previous arguments that content analyses provide the descriptive foundation for media effects research (McLeod & Reeves, 1980) are extended to include that content analyses can provide a sound and useful foundation for programmatic research by individual communication scientists. I discuss examples from my own work and from that of colleagues in communication and related disciplines. Use of messages sampled and coded in a content analysis in combination with survey data sets or as stimuli in experiments are highlighted. The particular potential for employing larger numbers of randomly sampled messages in experimental designs, and, with use of appropriate statistical methods, being able to generalize to populations of messages, is described.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.