Early family experiences and the financial behavior of college students: the impact of gender and gambling

2001 ◽  
Author(s):  
Bryan Gayle Miller
2008 ◽  
Author(s):  
Krista K. Fritson ◽  
Theresa A. Wadkins ◽  
Pat Gerdes ◽  
David Hof

2019 ◽  
Vol 5 (4) ◽  
pp. 21-26
Author(s):  
Purvi Nishad ◽  
Anjali Mathur ◽  
Anshu ◽  
Nisha Chacko

The present study was to assess the impact of modernization among the college students across gender, socio cultural settings and socio economic groups among adolescent boys and girls in the age group of 17 to 21 year.


2020 ◽  
pp. 003151252098308
Author(s):  
Bianca G. Martins ◽  
Wanderson R. da Silva ◽  
João Marôco ◽  
Juliana A. D. B. Campos

In this study we proposed to estimate the impact of lifestyle, negative affectivity, and college students’ personal characteristics on eating behavior. We aimed to verify that negative affectivity moderates the relationship between lifestyle and eating behavior. We assessed eating behaviors of cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE)) with the Three-Factor Eating Questionnaire-18. We assessed lifestyle with the Individual Lifestyle Profile, and we assessed negative affectivity with the Depression, Anxiety and Stress Scale-21. We constructed and tested (at p < .05) a hypothetical causal structural model that considered global (second-order) and specific (first-order) lifestyle components, negative affectivity and sample characteristics for each eating behavior dimension. Participants were 1,109 college students ( M age = 20.9, SD = 2.7 years; 65.7% females). We found significant impacts of lifestyle second-order components on negative affectivity (β = −0.57–0.19; p < 0.001–0.01) in all models. Physical and psychological lifestyle components impacted directly only on CR (β=−0.32–0.81; p < 0.001). Negative affectivity impacted UE and EE (β = 0.23–0.30; p < 0.001). For global models, we found no mediation pathways between lifestyle and CR or UE. For specific models, negative affectivity was a mediator between stress management and UE (β=−0.07; p < 0.001). Negative affectivity also mediated the relationship between thoughts of dropping an undergraduate course and UE and EE (β = 0.06–0.08; p < 0.001). Participant sex and weight impacted all eating behavior dimensions (β = 0.08–0.34; p < 0.001–0.01). Age was significant for UE and EE (β=−0,14– −0.09; p < 0.001–0.01). Economic stratum influenced only CR (β = 0.08; p = 0.01). In sum, participants’ lifestyle, negative emotions and personal characteristics were all relevant for eating behavior assessment.


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