Using job strain and organizational justice models to predict multiple forms of employee performance behaviours among Australian policing personnel

The overall purpose of this investigation was to examine the relationship between stress-related working conditions and three forms of employee performance behaviours: in-role behaviours, citizenship behaviours directed at other individuals and citizenship behaviours directed at the organization. The potentially stressful working conditions were based on the job strain model (incorporating job demands, job control and social support) as well as organizational justice theory. A sample of Australian-based police officers (n = 640) took part in this study and the data were collected via a mail-out survey. Multiple regression analyses were undertaken to assess both the strength and the nature of the relationships between the working conditions and employee performance and these analyses included tests for additive, interactional and curvilinear effects. The overall results indicated that a significant proportion of the explained variance in all three outcome measures was attributed to the additive effects of demand, control and support. The level of variance associated with the organizational justice dimensions was relatively small, although there were signs that specific dimensions of justice may provide unique insights into the relationship between job stressors and employee performance. The implications of these and other notable findings are discussed.

Using causal mapping to find new avenue for organizational fit research

Although organizational fit is strongly linked to important psychological outcomes such as motivation, satisfaction, turnover and performance, there is still a lot of confusion about definitions and conceptualizations of the construct. One reason for this is that fit researchers have almost exclusively conducted theory-driven nomothetic studies that have utilized varying approaches to the term. In this paper, we call for exploratory research that listens to how workers construct their own sense of fit and suggest that researchers should adopt idiographic data gathering techniques, coupled with nomothetic analysis tools, to do so. To enable this, we explain how fit researchers might use causal maps and thereby develop a stronger understanding of organizational fit that is grounded in how people conceive it.

Lost in translation? Emotional intelligence, affective economies, leadership and organizational change

Not until the late 1990s did the rational/emotional binary embedded in mainstream literature on educational leadership and management come under challenge. Now the emotional dimensions of organisational change and leadership are widely recognised in the leadership, organisational change and school improvement literature. However, the dissolution of the binary did not draw from feminist social theory, critical organisational theory, the sociology of emotions or critical pedagogy. Instead, the strongest influence in educational leadership and administration has been from psychological theory, management theory and brain science, mobilised particularly through Goleman's notion of emotional intelligence. This article undertakes a feminist deconstruction of two texts: one from organisational theory by Goleman and the other on educational leadership and school improvement, in order to explore how ‘emotion’ has been translated into educational leadership. As a counterpoint, I identify the gaps and silences, appropriations and marginalisation identified from feminist perspectives. I argue that the emotional labour of teaching and leading cannot be individualised because emotion is both relational and contextual.

Bayesian networks and decision trees in the diagnosis of female urinary incontinence

This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult women presenting with urinary incontinence symptoms. A Bayesian Network was developed in collaboration with an expert specialist who regularly utilizes a non-automated diagnostic algorithm in clinical practice. The original Bayesian network was later refined using a more connected approach. Diagnoses determined from all automated approaches were compared with the diagnoses of a single human expert. In most cases, Bayesian networks were found to be at least as accurate as the Decision Tree approach. The refined Connected Bayesian Network was found to be more accurate than the Original Bayesian Network accurately discriminated between diagnoses despite the small sample size. In contrast, the Connected and Decision Tree approaches were less able to discriminate between diagnoses. The Original Bayesian Network was found to provide an excellent basis for graphically communicating the correlation between symptoms and laxity defects in a given anatomical zone. Performance measures in both networks indicate that Bayesian networks could provide a potentially useful tool in the management of female pelvic floor dysfunction. Before the technique can be utilized in practice, well-established learning algorithms should be applied to improve network structure. A larger training data set should also improve network accuracy, sensitivity, and specificity.

Working around a contested diagnosis : borderline personality disorder in adolescence

This discourse analytic study sits at the intersection of everyday communications with young people in mental health settings and the enduring sociological critique of diagnoses in psychiatry. The diagnosis of borderline personality disorder (BPD) is both contested and stigmatized, in mental health and general health settings. Its legitimacy is further contested within the specialist adolescent mental health setting. In this setting, clinicians face a quandary regarding the application of adult diagnostic criteria to an adolescent population, aged less than 18 years. This article presents an analysis of interviews undertaken with Child and Adolescent Mental Health Services (CAMHS) clinicians in two publicly funded Australian services, about their use of the BPD diagnosis. In contrast with notions of primacy of diagnosis or of transparency in communications, doctors, nurses and allied health clinicians resisted and subverted a diagnosis of BPD in their work with adolescents. We delineate specific social and discursive strategies that clinicians displayed and reflected on, including: team rules which discouraged diagnostic disclosure; the lexical strategy of hedging when using the diagnosis; the prohibition and utility of informal ‘borderline talk’ among clinicians; and reframing the diagnosis with young people. For clinicians, these strategies legitimated their scepticism and enabled them to work with diagnostic uncertainty, in a population identified as vulnerable. For adolescent identities, these strategies served to forestall a BPD trajectory, allowing room for troubled adolescents to move and grow. These findings illuminate how the contest surrounding this diagnosis in principle is expressed in everyday clinical practice.

Training improves interobserver reliability for the diagnosis of scaphoid fracture displacement

Background The diagnosis of displacement in scaphoid fractures is notorious for poor interobserver reliability.

Questions/purposes We tested whether training can improve interobserver reliability and sensitivity, specificity, and accuracy for the diagnosis of scaphoid fracture displacement on radiographs and CT scans.

Methods Sixty-four orthopaedic surgeons rated a set of radiographs and CT scans of 10 displaced and 10 nondisplaced scaphoid fractures for the presence of displacement, using a web-based rating application. Before rating, observers were randomized to a training group (34 observers) and a nontraining group (30 observers). The training group received an online training module before the rating session, and the nontraining group did not. Interobserver reliability for training and nontraining was assessed by Siegel’s multirater kappa and the Z-test was used to test for significance.

Results There was a small, but significant difference in the interobserver reliability for displacement ratings in favor of the training group compared with the nontraining group. Ratings of radiographs and CT scans combined resulted in moderate agreement for both groups. The average sensitivity, specificity, and accuracy of diagnosing displacement of scaphoid fractures were, respectively, 83%, 85%, and 84% for the nontraining group and 87%, 86%, and 87% for the training group. Assuming a 5% prevalence of fracture displacement, the positive predictive value was 0.23 in the nontraining group and 0.25 in the training group. The negative predictive value was 0.99 in both groups.

Conclusions Our results suggest training can improve interobserver reliability and sensitivity, specificity and accuracy for the diagnosis of scaphoid fracture displacement, but the improvements are slight. These findings are encouraging for future research regarding interobserver variation and how to reduce it further.

A hybrid intelligent system and its application to fault detection and diagnosis

This paper proposes a hybrid system that integrates the SOM (Self Organizing Map) neural network, the kMER (kernel-based Maximum Entropy learning Rule) algorithm and the Probabilistic Neural Network (PNN) for data visualization and classification. The rationales of this hybrid SOM-kMER-PNN model are explained, and the applicability of the proposed model is demonstrated using two benchmark data sets and a real-world application to fault detection and diagnosis. The outcomes show that the hybrid system is able to achieve comparable classification rates when compared to those from a number of existing classifiers and, at the same time, to produce meaningful visualization of the data sets.