Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals

使用机器学习和混合方法研究开发数据驱动的管理系统来预测心理健康专业人员的工作流动率

基本信息

  • 批准号:
    10375772
  • 负责人:
  • 金额:
    $ 3.88万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-12-18 至 2022-11-30
  • 项目状态:
    已结题

项目摘要

March 11, 2021 Michael C. Freed, Ph.D. Chief, Services Research and Clinical Epidemiology Branch Division of Services and Intervention Research National Institute of Mental Health / NIH Office: 301.443.3747 Email: michael.freed@nih.gov RE: Statement of Candidate Eligibility for a Diversity Supplement to R34 MH119411 (PI: Sadaaki Fukui, Indiana University) Dear Dr. Freed, I am submitting a request for an NIH Diversity Supplement to my parent grant R34. This supplemental request is to support Dr. Eric Kyere who is an assistant professor at Indiana University (IU) School of Social Work. Dr. Kyere is eligible for a diversity supplement as a permanent resident who is originally from Ghana. He is a highly motivated scholar aiming to advance racial equity and justice, making him an ideal candidate for this supplement. Dr. Kyere, who is also a racial minority in the United States, is very passionate about understanding the mechanisms and factors of structural racism and identifying methods to tackle the issue. In order for him to continue his research efforts, he has been preparing for tenure at IU. This diversity supplement is an excellent opportunity to help Dr. Kyere reach his career goals as we describe in the attached proposal. Our supplement research goal (i.e., addressing the racial disparities in the mental health workforce) strongly aligns with the current NIMH strategic plans for strengthening the academic and mental health workforce by recruiting and retaining people from diverse backgrounds. Ensuring the success of diverse academic faculty is critical not only for the minority faculty member but also for us to recruit more diverse students and trainees who eventually will diversify our mental health workforce. Our effort ultimately could improve service access and quality for our minority clients. The supplement will help facilitate Dr. Kyere’s career development as he applies his knowledge and skills to a new project under Aims 2 and 3 of the parent R34 and develops preliminary data that will help him be more competitive for external funding. He will apply for tenure and promotion at IU during the 2022-2023 academic year, and the timing of this award will be ideal. To support his career goals through this diversity supplement, we have created supportive environments to provide quality mentoring. We appreciate your consideration of this proposal. Please let me know if you need additional information. Sincerely, Sadaaki Fukui, PhD., MSW., Associate Professor Indiana University School of Social Work MA Steven Allen Martin Associate Vice President for Research Administration Indiana University
2021年3月11日 Michael C. Freed博士 服务研究及临床流行病学分支主任 服务和干预研究司 国家精神卫生研究所/ NIH 办公室:301.443.3747 电子邮件:michael. nih.gov 回复:R34 MH 119411多元化补充的候选人资格声明(PI: 福井贞明,印第安纳州大学) 尊敬的Freed医生, 我提交了一个申请NIH多样性补充我的父母补助金R34。这 补充请求是支持埃里克·凯尔博士,他是印第安纳州的助理教授 大学(IU)社会工作学院。Kyere博士有资格获得多样性补充, 来自加纳的永久居民。他是一位积极进取的学者, 促进种族平等和正义,使他成为这一补充的理想人选。 博士Kyere也是美国的少数民族,他非常热衷于 了解结构性种族主义的机制和因素, 解决这个问题。为了继续他的研究工作,他一直在准备 在IU。这种多样性补充是一个很好的机会,以帮助博士Kyere达到他的 职业目标,如我们在所附的建议书中所述。我们的补充研究目标(即, 解决精神卫生工作人员中的种族差异)与当前的 NIMH通过招聘加强学术和心理健康工作人员的战略计划 留住不同背景的人确保多样化学术的成功 教师不仅对少数民族教师至关重要,而且对我们招募更多样化的教师也至关重要。 学生和受训者,他们最终将使我们的精神卫生工作者多样化。我们的努力 最终可以改善我们少数族裔客户的服务渠道和质量。补充将 帮助促进Kyere博士的职业发展,因为他将自己的知识和技能应用到一个新的 项目下的目标2和3的父R34和发展的初步数据,这将有助于他 对外部资金更有竞争力。他将在2015年申请IU的终身职位和晋升。 2022-2023学年,这个奖项的时机将是理想的。 为了通过这种多样性补充来支持他的职业目标,我们创建了支持性的 环境,提供优质的指导。 我们感谢你对这个建议的考虑。请让我知道如果你需要更多的 信息. 诚挚的, 福井贞明博士,城市固体废物, 副教授 印第安纳州大学社会工作学院 MA Steven艾伦马丁 研究管理副总裁 印第安纳州大学

项目成果

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Sadaaki Fukui其他文献

Sadaaki Fukui的其他文献

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{{ truncateString('Sadaaki Fukui', 18)}}的其他基金

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals
使用机器学习和混合方法研究开发数据驱动的管理系统来预测心理健康专业人员的工作流动率
  • 批准号:
    10321230
  • 财政年份:
    2019
  • 资助金额:
    $ 3.88万
  • 项目类别:
Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals
使用机器学习和混合方法研究开发数据驱动的管理系统来预测心理健康专业人员的工作流动率
  • 批准号:
    10461312
  • 财政年份:
    2019
  • 资助金额:
    $ 3.88万
  • 项目类别:
Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals
使用机器学习和混合方法研究开发数据驱动的管理系统来预测心理健康专业人员的工作流动率
  • 批准号:
    9895943
  • 财政年份:
    2019
  • 资助金额:
    $ 3.88万
  • 项目类别:

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