Why Do Adolescents With Type 1 Diabetes and Their Parents Participate in Focus Groups?

2007 ◽  
Vol 21 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Aaron E. Carroll ◽  
David G. Marrero ◽  
Melinda M. Swenson

Almost all patient-centered research is dependent on voluntary participation by participants. Many forces, however, act to either encourage or inhibit people from deciding to participate. This study explored adolescents’ with Type 1 diabetes and their parents’ reasons for participating in a research study. We recruited adolescents with type 1 diabetes mellitus and their parents to participate in a focus group study. Qualitative analysis of the focus group data followed a set procedure: (a) audio review, (b) reading through transcriptions, (c) discussions among investigators regarding key elements of participants’ perceptions, (d) determination of conceptual themes, and (e) assignment of relevant responses to appropriate thematic constructs. The 10 focus groups involved 59 participants. The three major themes that developed were giving and receiving, desire for peer socialization, and need for validation. Themes captured the reasons adolescents with type 1 diabetes and their parents decided to participate in this research. A better understanding of why people participate in research may help us to meet their needs and desires more completely. Designing research to meet these reasons will have the dual affect of increasing participation while also better serving those who choose to be studied.

Author(s):  
Ellen J. Bass ◽  
Andrew J. Abbate ◽  
Yaman Noaiseh ◽  
Rose Ann DiMaria-Ghalili

There is a need to support patients with monitoring liquid intake. This work addresses development of requirements for real-time and historical displays and reports with respect to fluid consumption as well as alerts based on critical clinical thresholds. We conducted focus groups with registered nurses and registered dietitians in order to identify the information needs and alerting criteria to support fluid consumption measurement. This paper presents results of the focus group data analysis and the related requirements resulting from the analysis.


2009 ◽  
Vol 8 (3) ◽  
pp. 1-21 ◽  
Author(s):  
Anthony J. Onwuegbuzie ◽  
Wendy B. Dickinson ◽  
Nancy L. Leech ◽  
Annmarie G. Zoran

Despite the abundance of published material on conducting focus groups, scant specific information exists on how to analyze focus group data in social science research. Thus, the authors provide a new qualitative framework for collecting and analyzing focus group data. First, they identify types of data that can be collected during focus groups. Second, they identify the qualitative data analysis techniques best suited for analyzing these data. Third, they introduce what they term as a micro-interlocutor analysis, wherein meticulous information about which participant responds to each question, the order in which each participant responds, response characteristics, the nonverbal communication used, and the like is collected, analyzed, and interpreted. They conceptualize how conversation analysis offers great potential for analyzing focus group data. They believe that their framework goes far beyond analyzing only the verbal communication of focus group participants, thereby increasing the rigor of focus group analyses in social science research.


2018 ◽  
Vol 17 (1) ◽  
pp. 160940691775078 ◽  
Author(s):  
Rachel Flynn ◽  
Lauren Albrecht ◽  
Shannon D. Scott

This article discusses four challenges to conducting qualitative focus groups: (1) maximizing research budgets through innovative methodological approaches, (2) recruiting health-care professionals for qualitative health research, (3) conducting focus groups with health-care professionals across geographically dispersed areas, and (4) taking into consideration data richness when using different focus group data collection methods. In light of these challenges, we propose two alternative approaches for collecting focus group data: (a) extended period of quantitative data collection that facilitated relationship building in the sites prior to qualitative focus groups and (b) focus groups by videoconference. We share our experiences on employing both of these approaches in two national research programs.


Author(s):  
Peyton Mason ◽  
Boyd Davis ◽  
Deborah Bosley

In this chapter, we will first discuss what stance is and highlight how we identify and measure stance using multivariate techniques, using an ongoing example taken from an Online Financial Focus Group. We review differences in stance between online real-time focus groups and online chat, as well as between online and face-to-face focus groups; and finally, proffer examples of stance analysis in two very different online focus groups: older adults discussing financial services and teens discussing clothes. As marketers see that online focus groups offer valuable marketing information by understanding the significance of how something is said as well as what is said, their confidence in the use of online focus-group data should increase.


Author(s):  
Sally M. Cohen ◽  
Michael D. Gravelle ◽  
Karen S. Wilson ◽  
Ann M. Bisantz

This paper describes a novel use of interview and focus group data to generate and substantiate hypotheses about a complex environment. In addition, it shows how MacSHAPA, a tool developed for analyzing sequential data, is a useful tool for analyzing these data. Although interviews and focus groups have been used extensively in social science and marketing, there are few examples documenting the use of these techniques in user-centered design. Furthermore, MacSHAPA has not been used to perform content analysis on interview and focus group data. In this paper, interviews and focus groups were collected as part of a larger study to understand human factors issues in quick service restaurant chains. These data were analyzed using MacSHAPA to perform content analysis. The results generated hypotheses that were validated by other data collection activities, and substantiated hypotheses that were derived by other analyses. The shortcomings and tradeoffs of using this analysis method for a human factors investigation are discussed.


JMIR Diabetes ◽  
2017 ◽  
Vol 2 (2) ◽  
pp. e17 ◽  
Author(s):  
Valéria de Cássia Sparapani ◽  
Sidney Fels ◽  
Lucila Castanheira Nascimento

2016 ◽  
Vol 22 (4) ◽  
pp. 854-866 ◽  
Author(s):  
Maria Klara Wolters ◽  
Fiona Kelly ◽  
Jonathan Kilgour

Intelligent cognitive assistants support people who need help performing everyday tasks by detecting when problems occur and providing tailored and context-sensitive assistance. Spoken dialogue interfaces allow users to interact with intelligent cognitive assistants while focusing on the task at hand. In order to establish requirements for voice interfaces to intelligent cognitive assistants, we conducted three focus groups with people with dementia, carers, and older people without a diagnosis of dementia. Analysis of the focus group data showed that voice and interaction style should be chosen based on the preferences of the user, not those of the carer. For people with dementia, the intelligent cognitive assistant should act like a patient, encouraging guide, while for older people without dementia, assistance should be to the point and not patronising. The intelligent cognitive assistant should be able to adapt to cognitive decline.


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