There is widespread public and academic interest in understanding the uses and effects of digital media. Scholars primarily use self-report measures of the quantity or duration of media use as proxies for more objective measures, but the validity of these self-reports remains unclear. Advancements in data collection techniques have produced a collection of studies indexing both self-reported and log-based measures. To assess the alignment between these measures, we conducted a meta-analysis of this research. Based on 106 effect sizes, we found that self-reported media use only moderately correlates with logged measurements, that self-reports were rarely an accurate reflection of logged media use, and that measures of problematic media use show an even smaller association with usage logs. These findings raise concerns about the validity of findings relying solely on self-reported measures of media use. The materials needed to reproduce the analysis and an article preprint are available at: https://osf.io/dhx48/.

In the last 10 years, many canonical findings in the social sciences appear unreliable. This so-called “replication crisis” has spurred calls for open science practices, which aim to increase the reproducibility, replicability, and generalizability of findings. Communication research is subject to many of the same challenges that have caused low replicability in other fields. As a result, we propose an agenda for adopting open science practices in Communication, which includes the following seven suggestions: (1) publish materials, data, and code; (2) preregister studies and submit registered reports; (3) conduct replications; (4) collaborate; (5) foster open science skills; (6) implement Transparency and Openness Promotion Guidelines; and (7) incentivize open science practices. Although in our agenda we focus mostly on quantitative research, we also reflect on open science practices relevant to qualitative research. We conclude by discussing potential objections and concerns associated with open science practices.

The influence of digital media on personal and social well-being is a question of immense public and academic interest. Scholars in this domain often use retrospective self-report measures of the quantity or duration of media use as a proxy for more objective measures, but the validity of these self-report measures remains unclear. Recent advancements in log-based data collection techniques have produced a growing collection of studies indexing both self-reported media use and device-logged measurements. Herein, we report a meta-analysis of this body of research. Based on 104 effect sizes, we found that self-reported media use was only moderately correlated with device-logged measurements, and that these self-report measures were rarely an accurate reflection of logged media use. These results demonstrate that self-reported measures of the quantity or duration of media use are not a valid index of the amount of time people actually spend using media. These findings have serious implications for the study of media use and well- being, suggesting that cautiousness is warranted in drawing conclusions regarding media effects from studies relying solely on self-reported measures of media use.

Moral intuitions are a central motivator in human behavior. Recent work highlights the importance of moral intuitions for understanding a wide range of issues ranging from online radicalization to vaccine hesitancy. Extracting and analyzing moral content in messages, narratives, and other forms of public discourse is a critical step toward understanding how the psychological influence of moral judgments unfolds at a global scale. Extant approaches for extracting moral content are limited in their ability to capture the intuitive nature of moral sensibilities, constraining their usefulness for understanding and predicting human moral behavior. Here we introduce the extended Moral Foundations Dictionary (eMFD), a dictionary-based tool for extracting moral content from textual corpora. The eMFD, unlike previous methods, is constructed from text annotations generated by a large sample of human coders. We demonstrate that the eMFD outperforms existing approaches in a variety of domains. We anticipate that the eMFD will contribute to advance the study of moral intuitions and their influence on social, psychological, and communicative processes.Recent work suggests that morally-laden messages play an instrumental role in fomenting moral outrage online (

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