Multi-Level Systems Engineering Analyzer Dashboard: A Semi-Automated Content Analysis for Interview Data

Author(s):  
Zhongyuan Yu ◽  
Hoong Yan See Tao ◽  
Yao Xiao ◽  
Pamela Burke ◽  
Nicole Hutchison ◽  
...  
2021 ◽  
Author(s):  
Jessica D. Austin ◽  
Parisa Tehranifar ◽  
Carmen B. Rodriguez ◽  
Laura Brotzman ◽  
Mariangela Agovino ◽  
...  

Abstract Background There is growing concern that routine mammography screening is overused among older women. Successful and equitable de-implementation of mammography will require a multi-level understanding of the factors contributing to mammography overuse. Methods This explanatory, sequential, mixed-methods study collected survey data (n = 52, 73.1% Hispanic, 73.1% Spanish-speaking) from women ≥ 70 years of age at the time of screening mammography, followed by semi-structured interviews with a subset of older women completing the survey (n = 19, 63.2% Hispanic, 63.2% Spanish-speaking) and providers (n = 5, 4 primary care, 1 obstetrics and gynecology) to better understand multi-level factors influencing mammography overuse and inform potential de-implementation strategies. We conducted descriptive analysis of survey data and content analysis of qualitative interview data. Survey and interview data were examined separately, compared, integrated, and organized according to Norton and Chambers Continuum of Factors Influencing De-Implementation Process. Results Survey findings show that 87.2% of older women believe it is important to plan for an annual mammogram, 80.8% received a provider recommendation, and 78.9% received a reminder in the last 12 months to schedule a mammogram. Per interviews with older women, the majority were unaware of or did not experience overuse and intended to continue mammography screening. Findings from interviews with older women and providers suggest that there are multiple opportunities for older women to obtain a mammogram. Per provider interviews, almost all reported that overuse was not viewed as a priority by the system or other providers. Providers also discussed that variation in mammography screening practices across providers, fear of malpractice, and monetary incentives may be reasons for overuse. Providers identified potential strategies including patient and provider education around harms of screening, leveraging the electronic health record to identify women who may no longer benefit from screening, customizing system-generated reminder letters, and organizing workgroups to develop a standard process of care around mammography screening. Conclusions Multi-level factors contributing to mammography overuse are dynamic and reinforced. To ensure equitable de-implementation, there is a need for more refined theories, models, and frameworks for de-implementation with a strong patient-level component that considers the interplay between multilevel factors and the larger care delivery process.


Author(s):  
Stuart Soroka

In light of the research in other chapters in this volume, this chapter considers some of the important and as-yet-unresolved methodological issues in automated content analysis. The chapter focuses on DICTION in particular, but the concerns raised here also apply to automated content analytic techniques more generally. Those concerns are twofold. First, the chapter considers the importance of aggregation for the reliability of content analyses, both human- and computer-coded. Second, the chapter reviews some of the difficulties associated with testing the validity of the kinds of complex (latent) variables on which DICTION is focused. On the whole, the chapter argues that this (and its companion) volume reflect just some of the many possibilities for DICTION-based analyses, but researchers must proceed with a certain amount of caution as well.


2019 ◽  
Vol 30 (2) ◽  
pp. 157-165 ◽  
Author(s):  
Sarah Lord Ferguson ◽  
Leanne Ewing ◽  
Alessandro Bigi ◽  
Hoda Diba

2020 ◽  
Vol 120 ◽  
pp. 103362 ◽  
Author(s):  
María Martínez-Rojas ◽  
Rubén Martín Antolín ◽  
Francisco Salguero-Caparrós ◽  
Juan Carlos Rubio-Romero

2020 ◽  
Vol 45 (s1) ◽  
pp. 744-764 ◽  
Author(s):  
Anne C. Kroon ◽  
Damian Trilling ◽  
Toni G. L. A. van der Meer ◽  
Jeroen G. F. Jonkman

AbstractThe current study explores how the cultural distance of ethnic outgroups relative to the ethnic ingroup is related to stereotypical news representations. It does so by drawing on a sample of more than three million Dutch newspaper articles and uses advanced methods of automated content analysis, namely word embeddings. The results show that distant ethnic outgroup members (i. e., Moroccans) are associated with negative characteristics and issues, while this is not the case for close ethnic outgroup members (i. e., Belgians). The current study demonstrates the usefulness of word embeddings as a tool to study subtle aspects of ethnic bias in mass-mediated content.


2007 ◽  
Vol 4 (4) ◽  
pp. 1007-1039 ◽  
Author(s):  
Michael Evans ◽  
Wayne McIntosh ◽  
Jimmy Lin ◽  
Cynthia Cates

2017 ◽  
Vol 115 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Gabriela C. Nunez-Mir ◽  
Johanna M. Desprez ◽  
Basil V. Iannone ◽  
Teresa L. Clark ◽  
Songlin Fei

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