Jatin Srivastava

Behavioral performance and visual attention in communication multitasking: A comparison between instant messaging and online voice chat

Participants carried out a visual pattern-matching task on a computer while communicating with a confederate either via instant messaging (IM) or online voice chat. Communicating with a confederate led to a 50% drop in visual pattern-matching performance in the IM condition and a 30% drop in the voice condition. Visual fixations on pattern-matching were fewer and shorter during the communication task and a greater loss of fixations was found in the IM condition than the voice condition. The results, examined within a threaded cognition framework, suggest that distributing the work between the audio and visual channels reduces performance degradation. Implications for media literacy and distracted-driving are discussed.

Media multitasking performance: Role of message relevance and formatting cues in online environments

In this study, strategies involving use of message relevance and formatting cues were tested with the objective of enhancing media multitasking performance. Three memory measures, free recall, aided/cued recall, and recognition were used as dependent variables for the study. The results indicated that multitasking was associated with reduced memory performance for all the dependent measures. Similarly, the performance for high relevance messages was significantly higher than the performance for low relevance messages across all memory measures. Additional analyses revealed that people made more errors during recognition tasks during multitasking. Similarly, more people made errors in free recall tasks during multitasking. Overall, findings suggested that multitasking might have more negative influence on message processing in some contexts than others.

Motivated Selective Attention During Political Ad Processing: The Dynamic Interplay Between Emotional Ad Content and Candidate Evaluation

This study examines the dynamic, real-time interplay between the emotional content of political television ads and individuals’ political attitudes during ad processing based upon the Dynamic Motivational Activation (DMA) theoretical framework. Time-series cross-sectional models were developed to test the effects of three motivational inputs of emotional ads (arousing content, positivity, and negativity) and viewers’ evaluation of the featured candidates on four psychophysiological responses (heart rate, skin conductance level, corrugator electromyography, and zygomatic electromyography). As predicted by the DMA, physiological responses during ad viewing were affected by their own first- and second-order dynamic system feedback effects. These results not only support the predicted dynamic nature of the physiological system but also help disentangle message effects from the moderating and accumulating effects of the physiological system itself. Also as predicted, message motivational inputs interacted with viewers’ political attitudes to determine psychophysiological responses to the ads. Supporters of opposing political candidates showed cardiac-somatic response patterns indicative of disparate attention to the advertised information. Attentional selectivity can be a critical component in determining how information processing influences campaign message reception and effects.

Media multitasking between two conversational tasks

Communication multitasking was examined in three conditions: IM conversation with one partner, two IM conversations at the same time, and IM and phone conversation at the same time. Participants in the multitasking conditions reported higher task demand and a small loss in task performance was evident. Single-task partners assigned to a task the required discussion and deliberation preferred to interact with the multitasking participant via phone, rather than IM. But interactions via phone with one partner led to poorer assessment by a second partner who was shortchanged during the interaction. Multitasking participants who were focused on helping both partners seemed blind to these perceived differences by their single-task partners. The results suggest a strategic model of multitasking, with IM being the preferred choice for tasks that require fewer, shorter exchanges and voice being the preferred choice for tasks that required more discussion and deliberation.

Diffusion of Innovations: Communication Evolution and Influences

Diffusion of innovations research has altered the research trajectories of those in the field of communication. In this article, the authors briefly explore the evolution of diffusion research, in terms of theoretical influences and applied research advances, and then address how the evolution of diffusion of innovations provided the impetus for a communication discipline identity search. An explication of how diffusion of innovations can be viewed as mechanistically affecting media convergence is presented. This piece closes with a call to return to diffusion research, especially given the face of current communication vehicles and media convergence.

Online, mixed, and offline media multitasking

This study examined the role of cultural and socio-demographic factors in predicting frequency of media multitasking behavior in three contexts based on the nature of media combination. A model was proposed to study these relationships; group-level cultural factors and socio-demographic factors were incorporated as exogenous variables, and media ownership, preference for multitasking, and frequencies of online, mixed, and offline media multitasking were included as endogenous variables. Data was collected using an online survey. Results indicated that both age and education significantly influenced online multitasking but for offline multitasking behavior, only age had a significant influence. Media ownership and one of the four group-level cultural factors predicted preference for multitasking, and preference for multitasking predicted frequency of media multitasking in all three contexts. Overall, findings highlight the role of cognitive factors as predictors of online media multitasking behavior. Findings also point towards the importance of individuals preference for multitasking in predicting media multitasking behavior across online, offline, and mixed media multitasking contexts. Age was associated with offline media multitasking behavior.Age and education were associated with online media multitasking behavior.Multitasking preference had a central role in predicting media multitasking.

Reactance to a Tailored Multimedia Intervention Encouraging Teachers to Promote Cover-the-Cough

Teachers were presented tailored multimedia messages encouraging them to offer cover-the-cough instruction to their students. Messages were tailored by grade level (elementary, higher grade) and stage of change (preaction, action). Among teachers in the action stages, message tailoring did not make a difference. Among teachers in the preaction stages, tailored messages were rated lower than were nontailored messages. The lower ratings of the tailored messages, seemingly a reactance response, did not carry over to postintervention self-efficacy. The intervention was effective in improving self-efficacy in elementary school teachers, particularly among those in the preaction stages.

Engaging audiences on social media: Identifying relationships between message factors and user engagement on the American Cancer Society’s Facebook page

Abstract In this study, a content analysis was conducted with posts from American Cancer Society’s (ACS) Facebook page to explore the relationship between message relevance, source characteristics, and message features with the number of likes, comments, and shares received by them. Limited Capacity Model for Motivated Mediated Message Processing (LC4MP) was used as the theoretical foundation for the study. Findings showed that cancer-related posts received more likes, comments and shares than posts that were not related to cancer. Also, posts by the American Cancer Society received more likes, comments, and shares than other source categories. Findings also indicated that though message features were related to likes, comments, and shares, the nature of relationship and the role of different features varied with each measure. Overall, findings highlight the role of motivational activation through message factors in eliciting user response in social media environments.