Elif Dede Yildirim

Early Career Tenure-track Researcher, Auburn University

4 active projects

Duplicate of Mental Health

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Scientific Questions Being Studied

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational
  • Methods Development

Scientific Approaches

Mental health assessments will be evaluated to examine measurement invariance across racial/ethnic groups, different SES, gender identity, sexual orientation, and geographical locations.

Anticipated Findings

Mental health assessments were shown to be invariant across different samples. The proposed study aims to assess the validity of mental health assessment among historically underrepresented populations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

Duplicate of Duplicate of Mental Health

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Scientific Questions Being Studied

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational
  • Methods Development

Scientific Approaches

Mental health assessments will be evaluated to examine measurement invariance across racial/ethnic groups, different SES, gender identity, sexual orientation, and geographical locations.

Anticipated Findings

Mental health assessments were shown to be invariant across different samples. The proposed study aims to assess the validity of mental health assessment among historically underrepresented populations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

Mental Health

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Scientific Questions Being Studied

Predictors of mental health across racial/ethnic groups, different SES, gender identity, sexual orientation, and geography will be examined using different methodologies including machine learning, mixture modeling, and mixed effect models.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational
  • Methods Development

Scientific Approaches

Mental health assessments will be evaluated to examine measurement invariance across racial/ethnic groups, different SES, gender identity, sexual orientation, and geographical locations.

Anticipated Findings

Mental health assessments were shown to be invariant across different samples. The proposed study aims to assess the validity of mental health assessment among historically underrepresented populations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

Mental_Health_v1

The project aims to assess the links between contextual risk factors, physical activity, and mental health among fathers with young children.

Scientific Questions Being Studied

The project aims to assess the links between contextual risk factors, physical activity, and mental health among fathers with young children.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Ethical, Legal, and Social Implications (ELSI)

Scientific Approaches

The datasets and variables will be explored to assess whether the impact of contextual risk factors impact mental health equally across racial/ethnic groups and different socioeconomic status.

Anticipated Findings

Studies documented the robust associations between paternal mental health and quality of father-child relationships. Further, poor mental health was found to be partially depended on individual's socio-demographic characteristics, including unemployment or unstable job conditions, family instability, residential status, marital status, age, education level, living under the federal poverty line, and race/ethnicity. Yet it remains unclear whether race/ethnicity accounts for the links between contextual risk factors and mental health outcomes in high-risk communities.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

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