Knowledge Reshapes Destiny: The Causal Effects of Education on Attitudes

2020 ◽  
Author(s):  
Ziteng Lei
Keyword(s):  
Causal Effects

Exploring a causal model in observational cohort data: The role of parents and peers in shaping substance use trajectories

2020 ◽  
Author(s):  
Christopher Greenwood ◽  
George Joseph Youssef ◽  
Primrose Letcher ◽  
Elizabeth Spry ◽  
Lauryn Hagg ◽  
...  
Keyword(s):  
Substance Use ◽  
Cannabis Use ◽  
Causal Effects ◽  
Deviant Peers ◽  
Adolescent Relationships ◽  
Cohort Data ◽  
Observational Cohort ◽  
Peer Affiliations ◽  
Role Of Parents ◽  
Adolescent Relationship

Aims: To explore the process of applying counterfactual thinking in examining causal predictors of substance use trajectories in observational cohort data. Specifically, we examine the extent to which quality of the parent-adolescent relationship and affiliations with deviant peers are causally related to trajectories of alcohol, tobacco, and cannabis use across adolescence and into young adulthood. Methods: Data were drawn from the Australian Temperament Project, a population-based cohort study that has followed a sample of young Australians from infancy to adulthood since 1983. Parent-adolescent relationship quality and deviant peer affiliations were assessed at age 13-14 years. Latent curve models were fitted for past month alcohol, tobacco, and cannabis use (n = 1,590) from age 15-16 to 27-28 years (5 waves). Confounding factors were selected in line with the counterfactual framework. Results: Following confounder adjustment, higher quality parent-adolescent relationships were associated with lower baseline cannabis use, but not alcohol or tobacco use trajectories. In contrast, affiliations with deviant peers were associated with higher baseline binge drinking, tobacco, and cannabis use, and an earlier peak in the cannabis use trajectory. Conclusions: Confounding adjustments weakened several estimated associations and the interpretation of such associations as causal is not without limitations. Nevertheless, findings suggested causal effects of both parent-adolescent relationships and deviant peer affiliations on the trajectory of substance use. Causal effects were however more pervasive (i.e., more substance types) and protracted for deviant peer affiliations. The current study encourages the exploration of causal relationships in observational cohort data, when relevant limitations are transparently acknowledged.

Bounding Causal Effects in Ecological Inference Problems

2015 ◽  
Author(s):  
Alejandro Corvalan ◽  
Emerson Melo ◽  
Robert P Sherman ◽  
Matthew Shum
Keyword(s):  
Causal Effects ◽  
Ecological Inference ◽  
Inference Problems

The bidirectional association between Internet addiction and depression: a large-sample longitudinal study among Chinese university students (Preprint)

2020 ◽  
Author(s):  
Wan-Jun Guo ◽  
Xia Yang ◽  
Yu-Jie Tao ◽  
Ya-Jing Meng ◽  
Hui-Yao Wang ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Internet Addiction ◽  
Causal Effects ◽  
Causal Relationships ◽  
Depression Severity ◽  
Large Sample ◽  
Panel Model ◽  
Bidirectional Association ◽  
Predictive Effect

BACKGROUND Evidence indicates that Internet addiction (IA) is associated with depression, but longitudinal studies have rarely been reported, and no studies have yet investigated potential common vulnerability or a possible specific causal relationship between these disorders. OBJECTIVE To overcome these gaps, the present 12-month longitudinal study based on a large-sample employed a cross-lagged panel model (CLPM) approach to investigate the potential common vulnerability and specific cross-causal relationships between IA and CSD (or depression). METHODS IA and clinically-significant depression (CSD) among 12 043 undergraduates were surveyed at baseline (as freshmen) and in follow-up after 12 months (as sophomores). Application of CLPM revealed two well-fitted design between IA and CSD, and between severities of IA and depression, adjusting for demographics. RESULTS Rates of baseline IA and CSD were 5.47% and 3.85%, respectively; increasing to 9.47% and 5.58%, respectively at follow-up. Among those with baseline IA and CSD, 44.61% and 34.48% remained stable at the time of the follow-up survey, respectively. Rates of new-incidences of IA and CSD over 12 months were 7.43% and 4.47%, respectively. Application of a cross-lagged panel model approach (CLPM, a discrete time structural equation model used primarily to assess causal relationships in real-world settings) revealed two well-fitted design between IA and CSD, and between severities of IA and depression, adjusting for demographics. Models revealed that baseline CSD (or depression severity) had a significant net-predictive effect on follow-up IA (or IA severity), and baseline IA (or IA severity) had a significant net-predictive effect on follow-up CSD (or depression severity). CONCLUSIONS These correlational patterns using a CLPM indicate that both common vulnerability and bidirectional specific cross-causal effects between them may contribute to the association between IA and depression. As the path coefficients of the net-cross-predictive effects were significantly smaller than those of baseline to follow-up cross-section associations, vulnerability may play a more significant role than bidirectional-causal effects. CLINICALTRIAL Ethics Committee of West China Hospital, Sichuan University (NO. 2016-171)

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