Negative social evaluations about aged-care work continue to discredit those who perform this type of work. Drawing on ‘dirty work’ literature from the field of management and stigma theory from the field of psychology, this study examines occupational stigma in the context of aged-care work and its relationship with negative outcomes for people who work in aged care. Findings from a path analysis revealed that aged-care workers (n = 185) who ascribe occupational taints and poor occupational conditions with aged-care work perceive aged-care work as being stigmatized, and in turn, are more likely to internalize this stigma. Through this process of perceiving and internalizing occupational stigma, aged-care workers experience greater psychological distress, job dissatisfaction, and turnover intentions. This research fills a void within the gerontology literature regarding the psychological processes underlying how occupational stigma may come to negatively impact this workforce. Findings offer practical implications for policy reform and managerial training.

Although the influence of psychosocial hazards on mental health has been widely recognized, the complex pattern of psychosocial hazards in the prediction of mental health still needs to be identified. Bayesian networks serve as an important, and as yet untapped, method to achieve this aim. As such, a Bayesian network (BN) was developed to assess the influence of psychosocial hazards on mental health based on survey data from 186 site-based construction practitioners and informed by the literature and expert knowledge. Results indicated that 66% of this target population suffered from poor mental health (i.e., mild, moderate, and severe states). Poor physical environment, contract pressure, and lack of coworker support were the root nodes in the model, which played an important role in determining the probability of other psychosocial hazards. Lack of job control, lack of coworker support, role ambiguity, role conflict, and lack of supervisor support were, relatively, the most influential hazards to mental health. Jointly controlling multiple psychosocial hazards was found to be better for increasing the probability of good mental health than controlling one individual hazard. The predictive inference revealed that managing the combination of lack of job control, lack of coworker support, role conflict, and job insecurity achieved the highest probability (77%) of good mental health among all four-hazard scenarios. Based on this particular scenario, further optimizing poor physical environment resulted in the highest probability (83%) of good mental health for five-hazard scenarios. The proposed BN model can be used as a powerful decision support tool to improve mental health in the construction industry via managing a more targeted subset of psychosocial hazards.

Authentic assessment has theorised benefits for student outcomes in higher education. More needs to be done, however, to empirically test relationships between the critical elements of authenticity and student outcomes, particularly in online learning environments. In this paper we examine whether an online simulation-based learning and assessment design, developed using the tools and functionality within the available university online ecosystem, has measurable ‘authenticity’ in a postgraduate course. In addition, we assess whether the simulation is associated with improvements in student learning behaviours and outcomes. We analyse qualitative data from lecturer and student interviews and student work submitted online, as well as data analytics from the learning management system in both control and experimental conditions. Seven critical elements of authentic assessment were identified including new aspects of authenticity relating to simulation-specific affordances (e.g. emotional content, temporal dimensions and unpredictability). Students watched lecture videos and participated in online discussion more frequently in the online simulation than in the control condition and indicated perceived mastery of, and confidence in, the learning outcomes. These findings make important contributions to authentic assessment theory and have practical implications for simulations built in online ecosystems available in higher education.

Purpose: – This study aims to investigate the extent to which employee outcomes (anxiety/depression, bullying and workers’ compensation claims thoughts) are affected by shared perceptions of supervisor conflict management style (CMS). Further, this study aims to assess cross-level moderating effects of supervisor CMS climate on the positive association between relationship conflict and these outcomes.Design/methodology/approach: – Multilevel modeling was conducted using a sample of 401 employees nested in 69 workgroups.Findings: – High collaborating, low yielding and low forcing climates (positive supervisor climates) were associated with lower anxiety/depression, bullying and claim thoughts. Unexpectedly, the direction of moderation showed that the positive association between relationship conflict and anxiety/depression and bullying was stronger for positive supervisor CMS climates than for negative supervisor CMS climates (low collaborating, high yielding and high forcing). Nevertheless, these interactions revealed that positive supervisor climates were the most effective at reducing anxiety/depression and bullying when relationship conflict was low. For claim thoughts, positive supervisor CMS climates had the predicted stress-buffering effects.Research limitations/implications: – Employees benefit from supervisors creating positive CMS climates when dealing with conflict as a third party, and intervening when conflict is low, when their intervention is more likely to minimize anxiety/depression and bullying.Originality/value: – By considering the unique perspective of employees’ shared perceptions of supervisor CMS, important implications for the span of influence of supervisor behavior on employee well-being have been indicated.