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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]

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]

Materials and Methods: In this paper, we propose a theoretical model based upon previous studies about personal and social network dynamics of job performance. We provide empirical support for this model using real-world data within the context of the Australian radiology profession. An examination of radiologists’ professional network topology through structural-positional and relational dimensions and radiologists’ personal characteristics in terms of knowledge, experience and self-esteem is provided. Thirty one breast imaging radiologists completed a purpose designed questionnaire regarding their network characteristics and personal attributes. These radiologists also independently read a test set of 60 mammographic cases: 20 cases with cancer and 40 normal cases. A Jackknife free response operating characteristic (JAFROC) method was used to measure the performance of the radiologists’ in detecting breast cancers. Results: Correlational analyses showed that reader performance was positively correlated with the social network variables of degree centrality and effective size, but negatively correlated with constraint and hierarchy. For personal characteristics, the number of mammograms read per year and self-esteem (self-evaluation) positively correlated with reader performance. Hierarchical multiple regression analysis indicated that the combination of number of mammograms read per year and network’s effective size, hierarchy and tie strength was the best fitting model, explaining 63.4% of the variance in reader performance. The results from this study indicate the positive relationship between reading high volumes of cases by radiologists and expertise development, but also strongly emphasise the association between effective social/professional interactions and informal knowledge sharing with high performance. [ABSTRACT FROM AUTHOR]

Background: The benefits of clinical supervision are more pronounced for health professionals in rural and remote areas. Most clinical supervision studies to date have occurred in metropolitan centres and have used the survey methodology to capture participant experiences. There is a lack of qualitative research that captures participants’ lived experiences with clinical supervision at the frontline. Methods: Participants were recruited from rural and remote sites of two Australian states using a purposive maximum variation sampling strategy. Data were collected through individual, semi-structured interviews with participants. Data were analysed using content analysis and themes were developed. Sixteen participants from six professions completed the interviews. Results: Eight themes were developed including the content of supervision, context of supervision, value of supervision, increased need for professional support and unique characteristics of rural and remote clinical supervision. Conclusions: This study has highlighted the value of clinical supervision for the rural and remote health professional workforce. Furthermore, it has shed light on the unique characteristics of clinical supervision in this population. This information can be used by organisations and health professionals to ensure clinical supervision partnerships are effective thereby enhancing rural and remote workforce recruitment and retention. [ABSTRACT FROM AUTHOR]

Objectives: Across high-income countries, unemployment rates among workers with disabilities are disproportionately high. The aim of this study was to identify characteristics of employment associated with dropping out of work and assess whether these were different for workers with versus without disabilities. Methods: Using a longitudinal panel study of working Australians (2001 to 2015), the current study estimated Kaplan–Meier curves and Cox proportional hazard regression models to identify predictors of leaving employment, including psychosocial job quality, employment arrangement, and occupational skill level. Effect modification by disability status of the relationship between employment-related factors and exit from the labour market were assessed by including interaction terms and assessing model fit with a likelihood ratio test. Models were adjusted for a range of socio-demographic and health related factors. Results: Compared to those without disability, those with disability had a greater risk of leaving employment (HR 1.26, 95% CI 1.18 to 1.35, p<0.001). Other predictors of exit from work included low-skilled occupation (HR 1.18, 95% CI 1.07 to 1.29, p = 0.001), being in a job with low psychosocial job quality (HR 1.11, 95% CI 1.03 to 1.19, p = 0.007), and casual, labour hire or fixed-term contract employment (HR 1.58, 95% CI 1.48 to 1.69, p<0.001). There was no effect modification by disability status. Conclusions: More research is needed to understand the experiences of workers with disabilities who stay in and leave employment. [ABSTRACT FROM AUTHOR]