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We used a retrospective cohort study to measure the impact of caring for children on female Australian researchers. Our aim was to see whether caring for children was associated with reduced outputs and collaboration. Women were randomly selected for inclusion if they published a first author paper in one of three Australian journals during 2007 to 2015, women who did not publish during this time were not included. One-hundred and sixty women were approached and 95 (59%) completed a survey on their history of caring for children. Two key outcomes were the women's publication and citation counts, which were accessed from Scopus. We also examined the number of authors, affiliations and countries on their published papers, as a reduction in these numbers could indicate an impaired ability to collaborate. We examined the probability of being first or last author as a measure of esteem. There was a small increase in publication counts after the first child that was reversed after the second child. Average citations counts declined after children, particularly after the second child. There was some evidence of a reduced collaboration with overseas collaborators after the first child. The probability of being the last author increased after the second child. Three women were identified as statistically influential and all three had children and were in the top 10% of overall publications and citations. After removing these women the estimated changes in outcomes were noticeably different for most of the outcomes. The repeated presence of statistically influential women shows that it may be impossible to find an "average impact" of caring for children when considering research output. Adjustments may need to be made individually, with women explaining how caring for children has altered their career. [ABSTRACT FROM AUTHOR]

In recent years policy makers and social scientists have devoted considerable attention to wellbeing, a concept that refers to people’s capacity to live healthy, creative and fulfilling lives. Two conceptual approaches dominate wellbeing research. The objective approach examines the objective components of a good life. The subjective approach examines people’s subjective evaluations of their lives. In the objective approach how subjective wellbeing relates to objective wellbeing is not a relevant research question. The subjective approach does investigate how objective wellbeing relates to subjective wellbeing, but has focused primarily on one objective wellbeing indicator, income, rather than the comprehensive indicator set implied by the objective approach. This paper attempts to contribute by examining relationships between a comprehensive set of objective wellbeing measures and subjective wellbeing, and by linking wellbeing research to inequality research by also investigating how subjective and objective wellbeing relate to class, gender, age and ethnicity. We use three waves of a representative state-level household panel study from Queensland, Australia, undertaken from 2008 to 2010, to investigate how objective measures of wellbeing are socially distributed by gender, class, age, and ethnicity. We also examine relationships between objective wellbeing and overall life satisfaction, providing one of the first longitudinal analyses linking objective wellbeing with subjective evaluations. Objective aspects of wellbeing are unequally distributed by gender, age, class and ethnicity and are strongly associated with life satisfaction. Moreover, associations between gender, ethnicity, class and life satisfaction persist after controlling for objective wellbeing, suggesting that mechanisms in addition to objective wellbeing link structural dimensions of inequality to life satisfaction. [ABSTRACT FROM AUTHOR]

Introduction: A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context. Methods: The Household Income Labour Dynamics in Australia (HILDA) survey was used to construct a JEM for job control, job demands and complexity, job insecurity, and fairness of pay. Population median values of these variables for all employed people (n = 20,428) were used to define individual exposures across the period 2001 to 2012. The JEM was calculated for the Australian and New Zealand Standard Classification of Occupations (ANZSCO) at the four-digit level, which represents 358 occupations. Both continuous and binary exposures to job stressors were calculated at the 4-digit level. We assessed concordance between the JEM-assigned and individually-reported exposures using the Kappa statistic, sensitivity and specificity assessments. We conducted regression analysis using mental health as an outcome measure. Results: Kappa statistics indicate good agreement between individually-reported and JEM-assigned dichotomous measures for job demands and control, and moderate agreement for job insecurity and fairness of pay. Job control, job demands and security had the highest sensitivity, while specificity was relatively high for the four exposures. Regression analysis shows that most individually reported and JEM measures were significantly associated with mental health, and individually-reported exposures produced much stronger effects on mental health than the JEM-assigned exposures. Discussion: These JEM-based estimates of stressors exposure provide a conservative proxy for individual-level data, and can be applied to a range of health and organisational outcomes. [ABSTRACT FROM AUTHOR]