Advanced data analytics training for behavioral and social sciences research

针对行为和社会科学研究的高级数据分析培训

• 批准号: 10649605
• 负责人: Eric Hekler
• 金额: $ 28.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10649605
• 关键词: Data Analytics; Training; behavioral and social science; social science research

Abstract Objectives: The Advanced Data Analytics Program To (ADAPT) will enhance behavioral and social sciences research, by training a diverse next generation of data scientists who will learn interdisciplinary skills needed for successful careers in behavioral and social sciences health-related data science. Rationale: San Diego is a hub for genomics, mobile technology, behavioral health research and data science in Southern California, yet no data science curriculum for behavioral scientists currently exists. The ADAPT program will fill this gap and intersect the areas of health sciences, informatics, computer science, and statistics in Southern California. Design: ADAPT will educate doctoral students in the behavioral and social sciences to build and further expand an ecosystem for big data analytics that promotes finding, accessing, interoperating, and reusing digital objects and responsibly computing with human subjects’ data in cloud environments. The ADAPT program will be based at the University of California, San Diego (UCSD), with faculty collaborators from San Diego State University. It will be based on two joint doctoral programs (JDPs) at these universities (Clinical Psychology and Public Health/Behavioral Health). Dual mentoring by faculty with expertise in behavioral and social sciences and computer science, biomedical informatics, or statistics will ensure a truly interdisciplinary focus that will cover team science and responsible conduct of research. Key Activities: Trainees will gain expertise through coursework, research experience during rotations and external internships, mentoring and other activities. Existing data science courses were selected for the curriculum, which will also include a new course in cloud-based human subjects’ data computing. Through individualized development plans, ADAPT trainees will work with their faculty mentors to tailor the curriculum and career paths according to students’ interests and skills. Data science coursework will utilize elective course slots in the JDP curricula, will typically be completed in years 1 and 2 of the JDPs. They will provide the foundational knowledge needed for academic and industry rotations and for the start of the trainees’ research phase. Projected Number of Trainees: 6 first or second year JDP students Planned Duration of Appointments: 3 years, renewed annually based on good academic standing Intended Trainee Outcomes: Metrics for success will include number and quality of publications, and rate of academic milestone completion. Trainees who complete the ADAPT program will possess the scientific knowledge needed to be a behavioral health data scientist, understand ethical and regulatory aspects of computing with protected health information, and will become critical members of scientific teams working in academia, government, for-profit and non-profit research institutions.

摘要 目标：高级数据分析计划（ADAPT）将加强行为和社会科学 通过培训多样化的下一代数据科学家，他们将学习所需的跨学科技能， 在行为科学和社会科学以及与健康相关的数据科学领域取得成功。 理由：圣地亚哥是基因组学、移动的技术、行为健康研究和数据科学的中心 南加州，但目前还没有行为科学家的数据科学课程。适配器 该计划将填补这一空白，并交叉健康科学，信息学，计算机科学和统计学领域 在南加州。 设计：ADAPT将教育行为和社会科学的博士生，以建立和进一步扩大 大数据分析生态系统，促进数字对象的查找、访问、互操作和重用 并在云环境中负责任地计算人类受试者的数据。ADAPT计划将基于 在加州大学圣地亚哥分校（UCSD），与圣地亚哥州立大学的教师合作。它 将基于两个联合博士课程（JDP）在这些大学（临床心理学和公共 健康/行为健康）。由具有行为和社会科学专业知识的教师进行双重指导， 计算机科学、生物医学信息学或统计学将确保真正的跨学科重点， 团队科学和负责任的研究行为。 主要活动：学员将通过课程学习、轮换期间的研究经验和 外部实习、指导和其他活动。现有的数据科学课程被选为 课程，其中还将包括一个新的课程，在基于云的人类受试者的数据计算。通过 个性化的发展计划，ADAPT学员将与他们的教师导师合作，定制课程 根据学生的兴趣和技能，数据科学课程将利用选修课 在JDP课程的插槽，通常将在JDP的第1年和第2年完成。他们将提供 学术和行业轮换以及学员研究开始所需的基础知识 相位 预计受训人数：6名一年级或二年级JDP学生 计划的学习时间：3年，根据良好的学术地位每年更新一次 预期受训者成果：成功的衡量标准将包括出版物的数量和质量，以及 完成学业里程碑。完成ADAPT计划的学员将拥有科学的 知识需要是一个行为健康数据科学家，了解道德和监管方面的 使用受保护的健康信息进行计算，并将成为科学团队的重要成员， 学术界、政府、营利和非营利研究机构。

项目成果

E-commerce licensing loopholes: a case study of online shopping for tobacco products following a statewide sales restriction on flavoured tobacco in California.

电子商务许可漏洞：加利福尼亚州全州范围内调味烟草销售限制后在线购买烟草产品的案例研究。

• DOI: 10.1136/tc-2023-058269
• 发表时间: 2023
• 期刊: Tobacco control
• 影响因子: 5.2
• 作者: Leas,EricC;Mejorado,Tomas;Harati,Raquel;Ellis,Shannon;Satybaldiyeva,Nora;Morales,Nicolas;Poliak,Adam
• 通讯作者: Poliak,Adam

Naturalistic Topography Assessment in a Randomized Clinical Trial of Smoking Unfiltered Cigarettes: Challenges, Opportunities, and Recommendations.

• DOI: 10.3390/ijerph182211857
• 发表时间: 2021-11-12
• 期刊: International journal of environmental research and public health
• 作者: Romero DR;Pulvers K;Carter E;Barber C;Satybaldiyeva N;Novotny TE;Oren E
• 通讯作者: Oren E

Switching people who smoke to unfiltered cigarettes: perceptions, addiction and behavioural effects in a cross-over randomised controlled trial.

将吸烟者改用未过滤嘴香烟：交叉随机对照试验中的认知、成瘾和行为影响。

• DOI: 10.1136/tobaccocontrol-2021-056815
• 发表时间: 2023
• 期刊: Tobacco control
• 影响因子: 5.2
• 作者: Pulvers,Kim;Tracy,LaRee;Novotny,ThomasE;Satybaldiyeva,Nora;Hunn,Adam;Romero,DevanR;Dodder,NathanG;Magraner,Jose;Oren,Eyal
• 通讯作者: Oren,Eyal

Testosterone, estradiol, DHEA and cortisol in relation to anxiety and depression scores in adolescents.

• DOI: 10.1016/j.jad.2021.07.026
• 发表时间: 2021-11-01
• 期刊: Journal of affective disorders
• 影响因子: 6.6
• 作者: Chronister BN;Gonzalez E;Lopez-Paredes D;Suarez-Torres J;Gahagan S;Martinez D;Barros J;Jacobs DR Jr;Checkoway H;Suarez-Lopez JR
• 通讯作者: Suarez-Lopez JR

Impact of timing of multimodal analgesia in enhanced recovery after cesarean delivery protocols on postoperative opioids: A single center before-and-after study.

剖宫产术后加速康复中多模式镇痛时机对术后阿片类药物的影响：单中心前后研究。

• DOI: 10.1016/j.jclinane.2022.110847
• 发表时间: 2022
• 期刊: Journal of clinical anesthesia
• 影响因子: 6.7
• 作者: Forkin,KatherineT;Mitchell,RochandaD;Chiao,SunnyS;Song,Chunzi;Chronister,BrianaNC;Wang,Xin-Qun;Chisholm,ChristianA;Tiouririne,Mohamed
• 通讯作者: Tiouririne,Mohamed