Hazel J Shah1, Betty S Lai2, Audrey J Leroux3, Annette M La Greca4, Courtney A Colgan2, Julia Medzhitova2. 1. Centers for Disease Control and Prevention, 1600 Clifton Road NE, C-09, Atlanta, GA 30333, USA. 2. Lynch School of Education and Human Development, Boston College, 316A Campion Hall, 140 Commonwealth Ave, Chestnut Hill, MA 02467, USA. 3. Department of Educational Policy Studies, Georgia State University, P.O. Box 3977, Atlanta, GA 30302, USA. 4. Department of Psychology, University of Miami, P.O. Box 249229, Coral Gables, FL 33124, USA Published online: 1 March 2019.
Abstract
BACKGROUND: As access to open data is increasing, researchers gain the opportunity to build integrated datasets and to conduct more powerful statistical analyses. However, using open access data presents challenges for researchers in understanding the data. Visuals allow researchers to address these challenges by facilitating a greater understanding of the information available. OBJECTIVES: This paper illustrates how visuals can address the challenges that researchers face when using open access data, such as: (1) becoming familiar with the data, (2) identifying patterns and trends within the data, and (3) determining how to integrate data from multiple studies. METHOD: This paper uses data from an integrative data analysis study that combined data from prospective studies of children's responses to four natural disasters: Hurricane Andrew, Hurricane Charley, Hurricane Katrina, and Hurricane Ike. The integrated dataset assessed hurricane exposure, posttraumatic stress symptoms, anxiety, social support, and life events among 1707 participants (53.61% female). The children's ages ranged from 7 to 16 years (M = 9.61, SD = 1.60). RESULTS: Visuals serve as an effective method for understanding new and unfamiliar datasets. CONCLUSIONS: In response to the growth of open access data, researchers must develop the skills necessary to create informative visuals. Most research-based graduate programs do not require programming-based courses for graduation. More opportunities for training in programming languages need to be offered so that future researchers are better prepared to understand new data. This paper discusses implications of current graduate course requirements and standard journal practices on how researchers visualize data.
BACKGROUND: As access to open data is increasing, researchers gain the opportunity to build integrated datasets and to conduct more powerful statistical analyses. However, using open access data presents challenges for researchers in understanding the data. Visuals allow researchers to address these challenges by facilitating a greater understanding of the information available. OBJECTIVES: This paper illustrates how visuals can address the challenges that researchers face when using open access data, such as: (1) becoming familiar with the data, (2) identifying patterns and trends within the data, and (3) determining how to integrate data from multiple studies. METHOD: This paper uses data from an integrative data analysis study that combined data from prospective studies of children's responses to four natural disasters: Hurricane Andrew, Hurricane Charley, Hurricane Katrina, and Hurricane Ike. The integrated dataset assessed hurricane exposure, posttraumatic stress symptoms, anxiety, social support, and life events among 1707 participants (53.61% female). The children's ages ranged from 7 to 16 years (M = 9.61, SD = 1.60). RESULTS: Visuals serve as an effective method for understanding new and unfamiliar datasets. CONCLUSIONS: In response to the growth of open access data, researchers must develop the skills necessary to create informative visuals. Most research-based graduate programs do not require programming-based courses for graduation. More opportunities for training in programming languages need to be offered so that future researchers are better prepared to understand new data. This paper discusses implications of current graduate course requirements and standard journal practices on how researchers visualize data.
Authors: Soledad Romero; Boris Birmaher; David A Axelson; Ana-Maria Iosif; Douglas E Williamson; Mary Kay Gill; Benjamin I Goldstein; Michael A Strober; Jeffrey Hunt; Tina R Goldstein; Christianne Esposito-Smythers; Satish Iyengar; Neal D Ryan; Martin Keller Journal: J Clin Psychiatry Date: 2009-10 Impact factor: 4.384