A Mixed-Methods Comparison of Self-Reported and Conversational Trust in Science

Rumble, Joy N.; Yu-lun, WU; Tully, Kelsey; Ruth, Taylor K.; Ellis, Jason D.; Lamm, Alexa J.

doi:10.4148/1051-0834.2371

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…Before and after the focus group discussions, all participants were asked to take a survey of trust in science, which was adapted from a scale developed by the National Science Board (2018). In the previous study (Rumble et al, 2020), the results showed that participants' trust in science did not sustain throughout the focus group conversations, although the difference was not significant. This study assumed that there might be some unobserved interactions within focus group discussions, which we may seldom consider in research design.…”

Section: Case Descriptionmentioning

confidence: 68%

“…The case we used in this research was part of a larger study that focused on United States consumers' acceptance of biological technologies to combat citrus greening (Rumble et al, 2018;Rumble et al, 2020;Ruth et al, 2019). A third-party company recruited citrus-consuming American residents to join a focus group discussion, which considered participants' age, gender, income, ethnicity, and what their citrus purchasing habits were (Ruth et al, 2019).…”

Section: Case Descriptionmentioning

confidence: 99%

“…Each focus group discussion lasted 90 to 120 minutes and was guided by a moderator. The discussion was audio-recorded and noted to capture the data (Rumble et al, 2020). The moderator's guide was reviewed by a panel of experts and consisted of eight different discussion topics, which were:…”

Section: Case Descriptionmentioning

confidence: 99%

“…This study counted the times that participants expressed distrust in each discussion topic and used the number to simulate the interaction between participants and discussion topics. In the previous study (Rumble et al, 2020), the codes of trust and distrust were used to analyze transcriptions, and distrust codes were found throughout the focus group transcripts, which appeared five times more than trust codes (Rumble et al, 2020). Distrust codes included:…”

Section: Data Collectionmentioning

confidence: 99%

See 3 more Smart Citations

An Application of Social Network Analysis to Focus Group Discussions: Unobserved Interaction Between Participants and Discussion Topics

Wu,

Rumble,

Ruth

et al. 2021

JAE

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While focus group discussions have become popular across the communication research field, some researchers have pointed out the importance of studying group interactions within focus groups. However, most researchers used a qualitative approach and mostly explored the interaction between participants or between participants and the moderator. This study claimed there might be a third and unobservable interaction that occurs between participants and structured discussion topics. An affiliation network in social network analysis was applied to investigate this phenomenon among eight groups of existing focus group conversations. By affiliation network data and network visualization, this study demonstrated diverse structures between groups. The interaction between participants and discussion topics was significantly different between at least two groups. The results showed that social network analysis could be a tool to help examine focus group interactions from qualitative data, and the interaction between participants and discussion topics could be a potential third interaction in focus group studies. This study is limited by comparing the mean difference between groups. Future research may examine short-and long-term causal effects of group interaction on participation or attitude changes after focus group discussions.

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Section: Case Descriptionmentioning

confidence: 68%

Section: Case Descriptionmentioning

confidence: 99%

Section: Case Descriptionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

See 2 more Smart Citations

An Application of Social Network Analysis to Focus Group Discussions: Unobserved Interaction Between Participants and Discussion Topics

Wu,

Rumble,

Ruth

et al. 2021

JAE

View full text Add to dashboard Cite

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Elementary Teachers’ Trust in Science and Scientists Throughout a COVID-19 SSI Unit

Borgerding

Mulvey

2022

Journal of Science Teacher Education

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Testing a Model to Explain how the Public Makes Decisions about Genetic Modification

Lamm

Rumble

et al. 2020

JIAEE

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The international agricultural and extension education field is fairly infantile in its research approach with descriptive, exploratory and process-oriented research taking the forefront over the introduction and testing of theoretical models that strive to answer complex questions. In a time when the world is facing a myriad of global challenges directly related to the agricultural and natural resource system (e.g. food security, climate change, infectious disease management) the discipline must be bold, innovative, and discovery-driven. The research presented here tests a theoretical model that combines two well-known theories, Diffusion of Innovations and Spiral of Silence, in the context of examining public willingness to expose attitudes about genetic modification (GM) in the United States. Structural equation modeling is used to determine the direct and indirect effects theoretical variables can have in a complex decision-making environment. Perceptions of diffusion characteristics of an innovation were found to directly and indirectly effect perceived opinions of others, perceived future trends in attitudes toward GM, and attitude toward GM but they did not have a significant direct or indirect effect on willingness to expose attitudes about GM. The findings revealed the ongoing complexity associated with systems-thinking and the research approaches necessary to answer complex questions. It also showcased that when thoroughly vetted theoretical explanations are tested, they will not always have the expected result. Keywords: systems thinking; decision-making; diffusion; spiral of silence

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A Mixed-Methods Comparison of Self-Reported and Conversational Trust in Science

Cited by 3 publications

References 7 publications

An Application of Social Network Analysis to Focus Group Discussions: Unobserved Interaction Between Participants and Discussion Topics

An Application of Social Network Analysis to Focus Group Discussions: Unobserved Interaction Between Participants and Discussion Topics

Elementary Teachers’ Trust in Science and Scientists Throughout a COVID-19 SSI Unit

Testing a Model to Explain how the Public Makes Decisions about Genetic Modification

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