Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 3 |
Descriptor
Classification | 3 |
Psychological Patterns | 3 |
Adolescents | 2 |
Behavior Problems | 2 |
High School Students | 2 |
Mental Health | 2 |
Questionnaires | 2 |
Screening Tests | 2 |
Affective Behavior | 1 |
Anxiety | 1 |
Child Behavior | 1 |
More ▼ |
Source
Grantee Submission | 3 |
Author
Dowdy, Erin | 2 |
Furlong, Michael J. | 2 |
Moore, Stephanie A. | 2 |
Nylund-Gibson, Karen | 2 |
Heffernan, Cristina | 1 |
Heffernan, Neil T. | 1 |
Wang, Yutao | 1 |
Publication Type
Reports - Research | 3 |
Speeches/Meeting Papers | 1 |
Education Level
Secondary Education | 3 |
High Schools | 2 |
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Audience
Location
California | 2 |
Laws, Policies, & Programs
Assessments and Surveys
Strengths and Difficulties… | 2 |
What Works Clearinghouse Rating
Moore, Stephanie A.; Dowdy, Erin; Nylund-Gibson, Karen; Furlong, Michael J. – Grantee Submission, 2019
Dual-factor models of mental health are increasingly supported but little is known about longitudinal trends in dual-factor mental health. The current study used latent profile analysis (LPA) to empirically identify dual-factor mental health classes at each of Grades 9 through 12 and latent transition analysis (LTA) to examine stability of classes…
Descriptors: Mental Health, Models, High School Students, Adolescents
Moore, Stephanie A.; Dowdy, Erin; Nylund-Gibson, Karen; Furlong, Michael J. – Grantee Submission, 2019
Using latent profile analysis (LPA), this study empirically identified dual-factor mental health subtypes, with a goal of examining structural stability of emerging latent classes over three high school years. Profiles' relations with distal indicators of well-being, psychosocial distress, and self-reported grades were examined to explore the…
Descriptors: Mental Health, Classification, Adolescents, High School Students
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables