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ERIC Number: EJ1219875
Record Type: Journal
Publication Date: 2019-Aug
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1053-1890
EISSN: N/A
Understanding Open Access Data Using Visuals: Integrating Prospective Studies of Children's Responses to Natural Disasters
Shah, Hazel J.; Lai, Betty S.; Leroux, Audrey J.; La Greca, Annette M.; Colgan, Courtney A.; Medzhitova, Julia
Child & Youth Care Forum, v48 n4 p563-583 Aug 2019
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.
Springer. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Institute of Mental Health (DHHS/NIH); National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 1R03MH11384901; 1634234