scispace - formally typeset
M

Marcia Russell

Researcher at Pacific Institute

Publications -  81
Citations -  13626

Marcia Russell is an academic researcher from Pacific Institute. The author has contributed to research in topics: Population & Poison control. The author has an hindex of 44, co-authored 81 publications receiving 13016 citations. Previous affiliations of Marcia Russell include University at Buffalo.

Papers
More filters
Journal ArticleDOI

Antecedents and outcomes of work-family conflict: testing a model of the work-family interface.

TL;DR: Although the model was invariant across gender and race, there were differences across blue- and white-collar workers.
Journal ArticleDOI

Drinking to regulate positive and negative emotions : a motivational model of alcohol use

TL;DR: A motivational model of alcohol use is proposed and tested in which people are hypothesized to use alcohol to regulate both positive and negative emotions and indicates the importance of distinguishing psychological motives for alcohol use.
Journal ArticleDOI

Relation of work–family conflict to health outcomes: A four-year longitudinal study of employed parents

TL;DR: The authors examined the longitudinal relarions of work → family and family → work conflict to self-report (depressive symptomatology, physical health, and heavy alcohol use) and objective cardiovascular (incidence of hypertension) health outcomes.
Journal ArticleDOI

Stress and Alcohol Use: Moderating Effects of Gender, Coping, and Alcohol Expectancies

TL;DR: The findings suggest that tension reduction theories of alcohol use are overly broad and that individual characteristics must be considered to account for stress-related effects on alcohol use and abuse.
Journal ArticleDOI

Development and validation of a three-dimensional measure of drinking motives.

TL;DR: In this paper, the authors developed a 3-factor measure that also assesses enhancement motives and found that enhancement motives are empirically distinct from coping and social motives and that a correlated 3factor model fits the data equally well across race and gender groups in a large representative sample.