School Spillover and College Student Health

Pedersen, Daphne E.; Swenberger, Jenelle; Moes, Katlyn

doi:10.1111/soin.12161

Cited by 8 publications

(2 citation statements)

References 75 publications

(112 reference statements)

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“…Using experimental testing and regression analysis, the authors identified the variables influencing the use of mental health services, such as intention to look for help, social support, and self-assessment of mental health. Based on the theory of stress transmission, literature [22] investigated the connection between students' psychological and behavioral well-being in higher education and school spillover effects. The educational spillover effect and unpleasant feelings like restlessness and irritation were found to have a favorable correlation, as revealed by a study conducted on 250 children.…”

Section: Introductionmentioning

confidence: 99%

Path analysis of digitally empowered mental health services for university students

Deng,

Liu

2024

Applied Mathematics and Nonlinear Sciences

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We investigate the viability of using data mining technologies to identify college students’ mental health issues in light of the rising number of these issues. To address the limitations of the traditional Apriori algorithm in data mining of mental health problems, an improved Apriori algorithm is proposed using the classification rule mining method. The relationship between various factors and the mental health problems of college students is better explored by this algorithm. Ultimately, the mental health care pathway that was developed during the exploration was used to conduct a comparative trial between those who received mental health services and those who did not. The experimental group’s mean score in the hyperactive concentration inability dimension was 3.25 after getting mental health care for three weeks, which was 22.6% higher than the control group’s mean score. The aspects of emotional symptoms, pro-social conduct, and total difficulty score also showed significant variations (p<0.05). The mean scores of the experimental group in the pro-social behavior and emotional symptoms dimension in the course of the study and the pre-experiment were 2.17 and 0.57, accordingly, which both demonstrated highly significant differences (p<0.01) in the between-group comparison of the differences in scores at different evaluation times with the control group.

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Section: Introductionmentioning

confidence: 99%

Path analysis of digitally empowered mental health services for university students

Deng,

Liu

2024

Applied Mathematics and Nonlinear Sciences

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“…They need to face reselection of values and rebuilding of personality. They also face enormous pressures related to social selection and possible social elimination (Mei, Chai, Li, & Wang, 2017;Pedersen, Swenberger, & Moes, 2017;Tupler, Hong, Gibori, Blitchington, & Krishnan, 2015).…”

Section: Introductionmentioning

confidence: 99%

Evaluating Implicit Emotions of Chinese University Students With Different Levels of Social Adjustment: Implicit Measurement Based on the Go/No-go Association Task

2018

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In this study, 60 university students were selected as research participants based on the Chinese Student Adjustment Scale. Participants were divided into two groups: high level of social adjustment and low level of social adjustment. Then using the Go/No-go Association Task as the implicit association experimental paradigm, implicit emotions were evaluated by having participants respond to different facial expressions as quickly as possible. The group of participants with higher levels of social adjustment performed better when responding to self-concepts with positive facial expressions, compared to responding to non-self-concepts with either positive or negative facial expressions. Thus, they showed an implicit preference for processing information about self with positive emotions. The group of participants with lower levels of social adjustment did not show the same benefit when responding to self-concepts. Instead, they performed better when responding to other-related concepts with different facial expressions, irrespective of the emotional content. Thus, they manifested an implicit preference for processing information about others with different emotions, suggesting a deficiency in processing their own emotions. In addition, the results validated the objectivity of the Chinese Student Adjustment Scale as an assessment tool.

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Parental Autonomy Support and College Student Academic Outcomes

Pedersen

2017

J Child Fam Stud

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School Spillover and College Student Health

Cited by 8 publications

References 75 publications

Path analysis of digitally empowered mental health services for university students

Path analysis of digitally empowered mental health services for university students

Evaluating Implicit Emotions of Chinese University Students With Different Levels of Social Adjustment: Implicit Measurement Based on the Go/No-go Association Task

Parental Autonomy Support and College Student Academic Outcomes

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