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
- 来源:
- 关键词:AddressAffectAfricanAfrican AmericanApplications GrantsAwardBiologicalCivil RightsClientColorCommunitiesConsciousCrowsDataData AnalysesDevelopmentDoctor of PhilosophyEconomicsEducationEffectivenessElectronic MailEligibility DeterminationEmployeeEnsureEvaluationFacultyFeedbackFellowshipFosteringFundingGhanaGoalsGrantGrowth and Development functionHealthHealth PersonnelHealth ProfessionalHealth Services ResearchImmigrantImprisonmentIndianaIndividualInequalityInstitutionInterruptionInterventionIntervention StudiesInterviewInvestigationJusticeKnowledgeLifeMachine LearningManuscriptsMeasuresMental HealthMental Health ServicesMentorsMentorshipMethodologyMethodsMinorityMotivationNational Institute of Mental HealthOccupationsOrganizational CultureOutcomeParentsParticipantPerformancePerformance at workPersonal SatisfactionPersonnel TurnoverPersonsPoliciesPopulationPopulation AnalysisPositioning AttributeProceduresProcessProductivityProtocols documentationPublishingQualitative MethodsRaceRacial EquityResearchResearch AssistantResearch MethodologyResearch PersonnelResistanceSchoolsSecureSeriesServicesSocial WorkSocietiesSolidStrategic PlanningStructural RacismStudentsSupervisionSurveysSystemTerrorismTimeTrainingUnited StatesUnited States National Institutes of HealthUniversitiesVoiceWorkWorkplaceWritingYouthanti-racismbasecareercareer developmentclinical epidemiologycommunity based participatory researchcommunity engaged researchconcept mappingcopingdepressive symptomsexperiencehealth economicsimplementation strategyimprovedinnovationinsightinterestmembermental health organizationmid-career facultyparent grantprofessional atmosphereprofessorpsychosocialracial discriminationracial disparityracial diversityracial minorityracismrecruitretention ratesegregationskillssocialsuccesssupportive environmenttenure tracktraitwillingness
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
服务研究与临床流行病学分支首席
服务和干预研究部
国家心理健康研究所 / NIH
办公室:301.443.3747
电子邮件:michael.freed@nih.gov
回复:R34 MH119411多样性补充的候选人资格声明(PI:
印第安纳大学萨达基福岛)
亲爱的弗里德博士,
我正在向我的父母赠款R34提交NIH多样性补充的请求。这
补充要求是支持印第安纳州助理教授的埃里克·凯尔(Eric Kyere)博士
大学(IU)社会工作学院。 Kyere博士有资格获得多样性补充
最初来自加纳的永久居民。他是一个积极进取的学校目标
提高种族平等和正义,使他成为这种补充的理想候选人。
Kyere博士也是美国的少数族裔,对
了解结构种族主义的机制和因素,并确定方法
解决这个问题。为了继续他的研究工作,他一直在准备
在IU任职。这种多样性补充是帮助Kyere博士达到他的绝佳机会
正如我们在所附建议中所描述的那样的职业目标。我们的补充研究目标(即
解决心理健康劳动力中的种族分布)与当前
NIMH通过招聘来加强学术和心理健康劳动力的战略计划
并保留潜水员背景的人。确保潜水员学术的成功
教师不仅对少数教师至关重要,而且对我们招募更多的潜水员至关重要
有时会使我们的心理健康员工多样化的学生和学员。我们的努力
最终,可以改善我们少数派客户的服务访问和质量。补充会
帮助Kyere博士的职业发展,因为他将自己的知识和技能应用于新的
根据父母R34的目标2和3的项目,并制定了将帮助他的初步数据
对外部资金更具竞争力。他将在IU申请任期和晋升
2022-2023学年以及该奖项的时机将是理想的选择。
为了通过这种多样性补充来支持他的职业目标,我们创造了支持
提供质量心理的环境。
感谢您对该提议的考虑。请让我知道您是否需要其他
信息。
真挚地,
SADAAKI FUKUI,博士,MSW。
副教授
印第安纳大学社会工作学院
史蒂文·艾伦·马丁(Ma Steven Allen Martin)
研究管理副总裁
印第安纳大学
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Sadaaki Fukui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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