five

Blood donation support application: contributions from experts on the tool’s functionality

收藏
DataCite Commons2021-03-25 更新2024-07-28 收录
下载链接:
https://scielo.figshare.com/articles/dataset/Blood_donation_support_application_contributions_from_experts_on_the_tool_s_functionality/14284516
下载链接
链接失效反馈
官方服务:
资源简介:
Abstract Blood donation is a social practice that helps treat diseases and maintain public health. The DoeSangue application was designed and developed to support donor recruitment and loyalty, strengthening health promotion and social engagement. We aimed to assess the DoeSangue application from the perspective of hematology and hemotherapy experts. A methodological, applied and qualitative research was carried out from September 2015 to July 2017 in Fortaleza, Ceará. The study was based on Participatory Interaction Design associated with Symbolic Interactionism. After conducting the first two steps, application design and development in a laboratory and assessment by donor users, the application was validated by eight experts from the Fortaleza’s public blood center. For data collection, the ‘application validation form with experts’ was used based on a Likert-type scale, and a focus group was conducted. The tool was positively assessed by participants, with an average Content Validation Index of 0.88. Evaluators pointed out, among other features, the tool’s ability to promote interactivity, mobilization and social engagement, in addition to contributing to gathering and loyalty of blood donors.

摘要 献血是一项用于辅助疾病治疗、维护公众健康的社会实践。DoeSangue应用程序(DoeSangue)旨在支持献血者招募与留存,强化健康推广与社会参与。本研究旨在从血液学与血液治疗学专家的视角对该应用程序进行评估。研究于2015年9月至2017年7月在巴西塞阿拉州福塔莱萨市开展,属于方法论性、应用性定性研究。本研究基于参与式交互设计(Participatory Interaction Design)与符号互动论(Symbolic Interactionism)展开。在完成前两步——应用程序的实验室设计开发与献血者用户评估——后,来自福塔莱萨公立血液中心的八名专家对该应用程序进行了验证。数据收集环节采用基于李克特量表(Likert-type scale)的《专家应用程序验证表》,并组织了焦点小组讨论。参与者对该工具给出了积极评价,其内容效度指数(Content Validation Index)平均值达0.88。评估者指出,除其他功能外,该工具能够促进交互性、社会动员与公众参与,此外还有助于聚集献血者群体并提升其留存率。
提供机构:
SciELO journals
创建时间:
2021-03-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作