The human cost of change : tales from the campus about personal change fatigue, resistance, and resilience

For the last decade, one question has haunted me: what helps people to cope with large-scale organisational change in their workplace? This study explores the construct of personal change resilience, and its potential for identifying solutions to the problems of change fatigue and change resistance. The thesis has emerged from the fields of change management, leadership, training, mentoring, evaluation, management and trust within the context of higher education in Australia at the beginning of the twenty-first century. In this thesis I present a theoretical model of the factors to consider in increasing peoples’ personal change resilience as they navigate large-scale organisational change at work, thereby closing a gap in the literature on the construct of change resilience. The model presented is based on both the literature in the realms of business and education, and on the findings of the research. In this thesis, an autoethnographic case study of two Australian university projects is presented as one narrative, resulting in a methodological step forward in the use of multiple research participants’ stories in the development of a single narrative. The findings describe the experiences of workers in higher education and emphasise the importance of considerate management in the achievement of positive experiences of organisational change. This research makes a significant contribution to new knowledge in three ways. First, it closes a gap in the literature in the realm of change management around personal change resilience as a solution to the problem of change fatigue by presenting models of both change failure and personal change resilience. Second, it is methodologically innovative in the use of personae to tell the stories of multiple participants in one coherent tale presented as a work of ethnographic fiction seen through an autoethnographic lens. By doing so, it develops a methodology for giving a voice to those to whom change is done in the workplace. Third, it provides a perspective on organisational change management from the view of the actual workers affected by change, thereby adding to the literature that currently exists, which is based on the views of those with responsibility for leading or managing change rather than those it affects. This thesis is intended as a practical starting point for conversations by actual change managers in higher education, and it is written in such a way as to help them see how theory can be applied in real life, and how empowering and enabling the actual working staff members, and engaging with them in a considerate way before, during and even after the change process, can help to make them resilient enough to cope with the change, rather than leaving them burned out or disengaged and no longer a well-functioning member of the institution. This thesis shows how considerately managed large-scale organisational change can result in positive outcomes for both the organisation and the individuals who work in it.

A methodology for estimating exposure-controlled crash risk using traffic Police crash data

Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

Keep ahead of the workforce development curve through the establishment of standardised training for rail incident investigators

The Australasian rail industry lacks a consistently accepted standard of minimal training necessary to perform rail incident investigations. Current Australasian courses do not offer the breadth of development required for a comprehensive career pathway in incident investigation (Biggs, Banks & Dovan, 2012; Short, Kains & Harris, 2010).

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

A novel protecting group methodology for syntheses using nitroxides

The methoxyamine group represents an ideal protecting group for the nitroxide moiety. It can be easily and selectively introduced in high yield (typically >90%) to a range of functionalised nitroxides using FeSO4.7H2O and H2O2 in DMSO. Its removal is readily achieved under mild conditions in high yield (70-90%) using mCPBA in a Cope-type elimination process.

A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

Parenting from the outside-in : reflections on parent training during a potential paradigm shift

This article proposes that a paradigm shift that has implications for practitioners of parenting interventions is emerging. This shift represents a challenge to the dominant model of parent training. The Triple P Parenting Program is discussed as an example of parent training programme to highlight the relevant issues for practitioners, including common practitioner objections encountered in dissemination as identified, in part, by Mazzucchelli and Sanders. It is argued that apart fromthese objections, there are more essential concerns in relation to the adoption of parent training programmes by practitioners. Rather, the article argues that parent training is “mind-blind” and that approaches emerging from the field of interpersonal neurobiology represent developmentally sophisticated alternatives for intervention. The Circle of Security programme is discussed as one example of this emerging paradigm shift that integrates attachment, social neuroscience, and psychodynamic theory. Contrasts are highlighted between the models, and considerations for future issues in parent intervention conclude the article.

Alcohol ingestion impairs maximal post-exercise rates of myofibrillar protein synthesis following a single bout of concurrent training

Introduction The culture in many team sports involves consumption of large amounts of alcohol after training/competition. The effect of such a practice on recovery processes underlying protein turnover in human skeletal muscle are unknown. We determined the effect of alcohol intake on rates of myofibrillar protein synthesis (MPS) following strenuous exercise with carbohydrate (CHO) or protein ingestion. Methods In a randomized cross-over design, 8 physically active males completed three experimental trials comprising resistance exercise (8×5 reps leg extension, 80% 1 repetition maximum) followed by continuous (30 min, 63% peak power output (PPO)) and high intensity interval (10×30 s, 110% PPO) cycling. Immediately, and 4 h post-exercise, subjects consumed either 500 mL of whey protein (25 g; PRO), alcohol (1.5 g·kg body mass−1, 12±2 standard drinks) co-ingested with protein (ALC-PRO), or an energy-matched quantity of carbohydrate also with alcohol (25 g maltodextrin; ALC-CHO). Subjects also consumed a CHO meal (1.5 g CHO·kg body mass−1) 2 h post-exercise. Muscle biopsies were taken at rest, 2 and 8 h post-exercise. Results Blood alcohol concentration was elevated above baseline with ALC-CHO and ALC-PRO throughout recovery (P<0.05). Phosphorylation of mTORSer2448 2 h after exercise was higher with PRO compared to ALC-PRO and ALC-CHO (P<0.05), while p70S6K phosphorylation was higher 2 h post-exercise with ALC-PRO and PRO compared to ALC-CHO (P<0.05). Rates of MPS increased above rest for all conditions (~29–109%, P<0.05). However, compared to PRO, there was a hierarchical reduction in MPS with ALC-PRO (24%, P<0.05) and with ALC-CHO (37%, P<0.05). Conclusion We provide novel data demonstrating that alcohol consumption reduces rates of MPS following a bout of concurrent exercise, even when co-ingested with protein. We conclude that alcohol ingestion suppresses the anabolic response in skeletal muscle and may therefore impair recovery and adaptation to training and/or subsequent performance.

A 3D virtual medical imaging suite : bridging the academic-clinical training boundary

Aims The Medical Imaging Training Immersive Environment (MITIE) system is a recently developed virtual reality (VR) platform that allows students to practice a range of medical imaging techniques. The aim of this pilot study was to harvest user feedback about the educational value of the application and inform future pedagogical development. This presentation explores the use of this technology for skills training and blurring the boundaries between academic learning and clinical skills training. Background MITIE is a 3D VR environment that allows students to manipulate a patient and radiographic equipment in order to produce a VR-generated image for comparison with a gold standard. As with VR initiatives in other health disciplines (1-6) the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia “Simulated Learning Environments” grant. Methods Over 80 students undertaking the Bachelor of Medical Imaging Course were randomised to receive practical experience with either MITIE or radiographic equipment in the medical radiation laboratory. Student feedback about the educational value of the software was collected and performance with an assessed setup was measured for both groups for comparison. Ethical approval for the project was provided by the university ethics panel. Results This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value as well as comparative quantitative performance data. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application’s significance as a pre-clinical training tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either during their academic timetables or their clinical placement. Conclusion Student feedback and performance data indicate that MITIE has a valuable role to play in the clinical skills training for medical imaging students both in the academic and the clinical environment. Future work will establish a framework for an appropriate supporting pedagogy that can cross the boundary between the two environments. This project was possible due to funding made available by Health Workforce Australia.

New graduate occupational therapists' perceptions of near-misses and mistakes in the workplace

Purpose - The purpose of this paper is to explore the perceptions of near-misses and mistakes among new graduate occupational therapists from Australia and Aotearoa/New Zealand (NZ), and their knowledge of current incident reporting systems. Design/methodology/approach - New graduate occupational therapists in Australia and Aotearoa/NZ in their first year of practice (n=228) participated in an online electronic survey that examined five areas of work preparedness. Near-misses and mistakes was one focus area. Findings - The occurrence and disclosure of practice errors among new graduate occupational therapists are similar between Australian and Aotearoa/NZ participants. Rural location, structured supervision and registration status significantly influenced the perceptions and reporting of practice errors. Structured supervision significantly impacted on reporting procedure knowledge. Current registration status was strongly correlated with perceptions that the workplace encouraged event reporting. Research limitations/ implications - Areas for further investigation include investigating the perceptions and knowledge of practice errors within a broader profession and the need to explore definitional aspects and contextual factors of adverse events that occur in allied health settings. Selection bias may be a factor in this study. Practical implications - Findings have implications for university and workplace structures, such as clinical management, supervision, training about practice errors and reporting mechanisms in allied health. Originality/value - Findings may enable the development of better strategies for detecting, managing and preventing practice errors in the allied health professions.

Engaging paramedic students in research: A case report

The use of volunteer undergraduate students to support simulated training for peers is common in Paramedic Science. However, there are limited examples of engaging paramedic student-volunteers in research as compared to that reported in cognate disciplines such as Medicine and Nursing. This case report shares our experience with engaging a penultimate year paramedic student in evaluation research. This information we hope will start the dialogue on the epistemology and pedagogies for effective engagement of undergraduate paramedic students as future researchers.

Effect of exercise training on skeletal muscle cytokine expression in the elderly

Aging is associated with increased circulating pro-inflammatory and lower anti-inflammatory cytokines. Exercise training, in addition to improving muscle function, reduces these circulating pro-inflammatory cytokines. Yet, few studies have evaluated changes in the expression of cytokines within skeletal muscle after exercise training. The aim of the current study was to examine the expression of cytokines both at rest and following a bout of isokinetic exercise performed before and after 12 weeks of resistance exercise training in young (n = 8, 20.3 ± 0.8 yr) and elderly men (n = 8, 66.9 ± 1.6 yr). Protein expression of various cytokines was determined in muscle homogenates. The expression of MCP-1, IL-8 and IL-6 (which are traditionally classified as ‘pro-inflammatory’) increased substantially after acute exercise. By contrast, the expression of the anti-inflammatory cytokines IL-4, IL-10 and IL-13 increased only slightly (or not at all) after acute exercise. These responses were not significantly different between young and elderly men, either before or after 12 weeks of exercise training. However, compared with the young men, the expression of pro-inflammatory cytokines 2 h post exercise tended to be greater in the elderly men prior to training. Training attenuated this difference. These data suggest that the inflammatory response to unaccustomed exercise increases with age. Furthermore, regular exercise training may help to normalize this inflammatory response, which could have important implications for muscle regeneration and adaptation in the elderly.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.