Formal features of cyberspace: Relationships between Web page complexity and site traffic

Usability of state public health department websites for communication during a pandemic: A heuristic evaluation

Study aims were to investigate how usable COVID-19 dedicated state public health websites in the US were, and whether case counts in different geographical regions in the US were related to website usability. 16 state websites representing the 2 highest and the 2 lowest case count states in each region were selected. Five experts used a heuristic evaluation procedure to independently rate all 16 websites on a severity scale of 0-4. Usability criteria published by the US Department of Health and Human Services and criteria on risk communication and data dashboards were used. Analyses involved cross tabulation of usability criteria with case counts, comparison of usability scores using Mood's median tests, test of differences in average usability scores using ANOVA and post-hoc tests, and identification of correlations between case counts and usability scores. Results from the Mood's median test showed that the median usability scores for the states were significantly different from each other at the 5% level of significance (df = 15, chi-square = 38.40; p = 0.001). ANOVA showed statistically significant differences between the mean usability scores for the states at the 5% level of significance (F = 6.33, p < 0.05). Although not statistically significant, results from a correlation analysis between case count and usability scores showed a negative correlation (r = -0.209, p = 0.437) indicating that the higher the case count, the better the usability score. Overall, the websites fared well on usability, but many websites were used as an information and data repository. These websites must communicate infection risk better.

RELEVANCE TO INDUSTRY

The study applies to public health agency websites that communicate essential information during a pandemic.

Content Analysis as a Best Practice in Technical Communication Research

Content analysis is a powerful empirical method for analyzing text, a method that technical communicators can use on the job and in their research. Content analysis can expose hidden connections among concepts, reveal relationships among ideas that initially seem unconnected, and inform the decision-making processes associated with many technical communication practices. In this article, we explain the basics of content analysis methodology and dispel common misconceptions, report on a content analysis case study, reveal the most important objectives associated with conducting high quality content analyses, and summarize the implications of content analysis as a tool for technical communicators and researchers.

Communication strategies in cosmetic surgery websites: an application of Taylor's six-segment message strategy wheel

Using Taylor's six-segment message strategy wheel as a theoretical framework, this study examines the communication approach (transmission or ritual) and message strategy (ego, social, sensory, routine, acute need, or ration) of cosmetic surgery websites. A content analysis revealed a fairly even division between transmission and ritual approaches. Ration strategy was the exclusive strategy in the websites adopting a transmission approach. No routine or acute need strategies were observed. Websites incorporating the ritual approach used ego, social, and sensory strategies. Human female models and natural objects were incorporated to deliver emotional persuasion. Implications for cosmetic surgery web marketers are discussed.