Life satisfaction, well-being and safe driving behaviour in undergraduate psychology students

2017 ◽  
Vol 47 ◽  
pp. 143-154 ◽  
Author(s):  
Robert B. Isler ◽  
Samantha A. Newland
Keyword(s):  
Life Satisfaction ◽  
Well Being ◽  
Psychology Students ◽  
Safe Driving ◽  
Driving Behaviour ◽  
Undergraduate Psychology

Different Future Time Perspectives Interplay in Predicting Life Satisfaction

GeroPsych ◽  
2018 ◽  
Vol 31 (3) ◽  
pp. 103-113 ◽  
Author(s):  
Minjie Lu ◽  
Angel Y. Li ◽  
Helene H. Fung ◽  
Klaus Rothermund ◽  
Frieder R. Lang
Keyword(s):  
Life Satisfaction ◽  
Time Perspective ◽  
Well Being ◽  
Future Time Perspective ◽  
Hong Kong Chinese ◽  
Future Time ◽  
Time Perspectives ◽  
Time Extension ◽  
Future Self ◽  
The Relationship

Abstract. This study addresses prior mixed findings on the relationship between future time perspective (FTP) and well-being as well as examines the associations between three aspects of FTP and life satisfaction in the health and friendship domains. 159 Germans, 97 US Americans, and 240 Hong Kong Chinese, aged 19–86 years, completed a survey on future self-views (valence) and life satisfaction. They also reported the extent to which they perceived future time as expanded vs. limited (time extension) and meaningful (openness). Findings revealed that individuals with more positive future self-views had higher satisfaction. However, those who perceived their future as more meaningful or perceived more time in their future reported higher satisfaction even when future self-views were less positive.

Well-being and life satisfaction: Associations observed in an employed population

2013 ◽  
Author(s):  
Nico P. Pronk ◽  
Marcia Lowry ◽  
Abigail S. Katz ◽  
Thomas E. Kottke
Keyword(s):  
Life Satisfaction ◽  
Well Being

Rank Status and Happiness in India: A Panel Ordered Probit Estimation of the Effect of Ordinal Relative Comparison on Well-being

2020 ◽  
Vol 11 (01) ◽  
Author(s):  
T. Lakshmanasamy ◽  
K. Maya
Keyword(s):  
Life Satisfaction ◽  
Fixed Effects ◽  
Reference Group ◽  
Well Being ◽  
Ordered Probit ◽  
Probit Regression ◽  
Differential Effects ◽  
Comparison Income ◽  
Average Reference ◽  
The Rich

Most often the social comparison or relative income hypothesis has been used as an explanation for the lack of systematic relationship between income and happiness, using the ordered probit regression method. The identification of relevant reference group and the estimation of the differential effects of comparison income have been controversial. To overcome these twin issues, this paper uses an ordinal comparison income approach based on rich/poor dichotomy and rank income. The rank income of an individual is defined as his relative position in the income distribution within the reference group and the average income of the reference group is used to define the rich/poor classification. The differential effects of ordinal incomes across life satisfaction distribution is estimated by the panel fixed effects ordered profit regression model using the WVS data for India. The estimated results show that ordinal income comparison, rather than cardinal average reference income, is a better predictor of life satisfaction levels. Raising income level is relatively important for less satisfied people while increasing rank status is important for highly satisfied people in India.

Examining the accuracy of estimated smartphone use: How well-being and usage level predict discrepancies between estimated and actual use

2019 ◽  
Author(s):  
Craig Sewall ◽  
Daniel Rosen ◽  
Todd M. Bear
Keyword(s):  
Public Health ◽  
Social Media ◽  
Life Satisfaction ◽  
Mobile Device ◽  
Screen Time ◽  
Well Being ◽  
Actual Use ◽  
Smartphone Use ◽  
Usage Level

The increasing ubiquity of mobile device and social media (SM) use has generated a substantial amount of research examining how these phenomena may impact public health. Prior studies have found that mobile device and SM use are associated with various aspects of well-being. However, a large portion of these studies relied upon self-reported estimates to measure amount of use, which can be inaccurate. Utilizing Apple’s “Screen Time” application to obtain actual iPhone and SM use data, the current study examined the accuracy of self-reported estimates, how inaccuracies bias relationships between use and well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 393 iPhone users, we found that: a.) participants misestimated their weekly overall iPhone and SM use by 22.1 and 16.6 hours, respectively; b.) the correlations between estimated use and well-being variables were consistently stronger than the correlations between actual use and well-being variables; and c.) the amount of inaccuracy in estimated use is associated with levels of participant well-being as well as amount of use. These findings suggest that estimates of device/SM use may be biased by factors that are fundamental to the relationships being investigated. **This manuscript is currently under review**

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