Understanding advanced and extended professional practice

The Advanced Pharmacy Practice Framework Steering Committee (now replaced by the Pharmacy Practitioner Development Committee) undertook work to develop an advanced pharmacy practice recognition model. As part of that work, and to assure clarity and consistency in the terminology it uses, the Committee collated the definitions used in literature sources consulted. Most recently, this involved a review of the meaning attributed to the terms ‘advanced’ and ‘extended’ when used in the context of describing aspects of professional practice. Both terms encompass the acquisition of additional expertise. While ‘advanced’ practice involves the acquisition of additional expertise to achieve a higher performance level, ‘extended’ practice relates specifically to scope of practice and involves the acquisition of additional expertise sufficient to provide services or perform tasks that are outside the usual scope of practice of the profession. Performance level operates independently of scope of practice but both must be elucidated to fully describe the professional practice of an individual practitioner.

Professional indemnity insurance, performance and pre-emptive negligence: The impact of ‘non-claims’

As part of Australian licensing requirements professional valuers are required to maintain a level of professional indemnity insurance. A core feature of any insurance cover is that the insured has an obligation to notify their insurer of both actual and potential claims. An actual claim clearly will impact upon future policies and premiums paid. Notification of a potential claim, whether or not the notification crystallises into an actual claim, also can have an impact upon the insured’s claims history and premiums. The Global Financial Crisis continues to impact upon business practices and land transactions both directly and indirectly. The Australian valuation profession is not exempt from this impact. One example of this ongoing impact is reflected in a worrying practice engaged in by some financial institutions in respect of their loan portfolios. That is, even though the mortgagor is not in default, some institutions are pre-emptively issuing notices of demand regarding potential losses. Further, in some instances such demands are based only on mass appraisal valuations without specific consideration being given to the individual lot in question. The author examines the impact of this practice for the valuation profession and seeks to provide guidance for the appropriate handling of such demands.

EFL teachers' professional dilemmas with moral curriculum reform in Indonesia

This project explored how EFL teachers working in different sectors in Indonesia experienced moral education reform. Teachers working in either state schools or Islamic private schools were interviewed and their classes were observed. The thesis indicated that systemic investment in teachers' professionalism contributed to teachers' emerging dilemmas and their resolutions. Teachers in the better resourced state sector reported more dilemmas related to the implementation of the reform and resolved these dilemmas by using professional judgement, while teachers in the less resourced sector reported dilemmas related to their context and failed to implement the curriculum.

Making the transition from pharmacy student to pharmacist: Australian interns' perceptions of professional identity formation

Objectives The experience of transitioning from university to practice influences professional identity formation. It is unclear how this transitioning experience influences pharmacy interns' professional identities. This study aims to examine pharmacy interns' perceptions of their transition from university to the workplace and the influence this had on their pharmacist identities. Methods A qualitative approach using in-depth interviews was adopted for this study. Fifteen interns (community and hospital) from one school of pharmacy in Australia were interviewed. Questions were asked about the nature of their current intern role, their university experiences, how they saw themselves as pharmacists and their perceptions of the transition to practice. Key findings The interns interviewed entered the workplace valuing patient-focused aspects of practice and contributing to patient care. The nature of work meant there were limited opportunities to enact these aspects of their professional identities. The interns were challenged by interactions with patients and doctors, and experienced difficulties reconciling this with their university-derived professional identities. Also, the interns lacked the confidence and strategies to overcome these challenges. Some were exploring alternative ways of being pharmacists. Conclusions This paper argues that graduates' experience of the transition to practice was challenging. This was due to nascent professional identities formed in university and a lack of workplace experiences enabling patient-centred practices. The interns' formation of professional identities was highly responsive to the context of work. To facilitate the development of Australian patient-centred pharmacy practice, supporting professional identity formation should be a focus within pharmacy education.

BIM and PLM: Comparing and learning from changes to professional practice across sectors

This paper explores the effects of PLM and BIM on professional practice. It draws on existing literature documenting the experiences of both communities of practice to explain shifts in professional boundaries. A review of case study based literature compares the nature of changes triggered by PLM and BIM relative to the new activities, roles/responsibilities and knowledge competencies, and supply chain relationships. The paper synthesises these changes and reflects PLM and BIM experiences against each other so as to contrast the continuing evolution of professional practice and lessons learned.

Learning experiences for the transition to professional work

A better educated workforce contributes to a more informed and tolerant society with higher economic output, and this is also associated with higher levels of personal health, interpersonal trust and civic and social engagement. Against this backdrop, the role of universities has expanded, as university learning has moved beyond providing an education to preparing students for leadership positions within society. This article examines the effectiveness of final-year learning experiences from the perception of recent graduates. The aim is to improve undergraduate curriculum to facilitate the transition to professional employment. An online quantitative and qualitative survey instrument was developed to investigate graduates’ perceptions of their different learning experiences and assessment types in their senior year. Four hundred and twelve alumni from five universities completed the survey. Our results indicate that graduates value case studies, group work and oral presentations, and that graduates rate lectures and guest lectures from practitioners as the least important in their transition to work. The results validate the use of graduate capability frameworks and mapping the development of the skills over the curriculum. These results are useful for curriculum designers to assist with designing programmes on the transition to professional work.

A blended learning approach to the teaching of professional practice in architecture

This paper reports on a number of blended learning activities conducted in two subjects of a Master of Architecture degree at a major Australian university. The subjects were related to “professional practice” and as such represent a little researched area of architectural curriculum. The research provides some insight into the student perceptions of learning opportunity and engagement associated with on-line delivery modes. Students from these two subjects were surveyed for their perceptions about the opportunity for learning afforded by the on-line components, and also for their perceived level of engagement. Responses to these perceptions of traditional and on-line modes of delivery are compared and analysed for significant differences. While students were generally positive in response to the learning experiences, analysis of the results shows that students found the traditional modes to assist in their learning significantly more than on-line modes. Students were neutral regarding the opportunity for engagement that on-line modes provided. Analysis of the students’ gender, age and hours of paid work was also conducted to ascertain any relationship with attitudes to the flexibility of on-line delivery; no significant relationship was detected. This study has shown that students were generally resistant to on-line engagement opportunities and their ability to support learning.

A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Statistically assisted fluid registration algorithm - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.

A lagrangian formulation for statistical fluid registration

We defined a new statistical fluid registration method with Lagrangian mechanics. Although several authors have suggested that empirical statistics on brain variation should be incorporated into the registration problem, few algorithms have included this information and instead use regularizers that guarantee diffeomorphic mappings. Here we combine the advantages of a large-deformation fluid matching approach with empirical statistics on population variability in anatomy. We reformulated the Riemannian fluid algorithmdeveloped in [4], and used a Lagrangian framework to incorporate 0 th and 1st order statistics in the regularization process. 92 2D midline corpus callosum traces from a twin MRI database were fluidly registered using the non-statistical version of the algorithm (algorithm 0), giving initial vector fields and deformation tensors. Covariance matrices were computed for both distributions and incorporated either separately (algorithm 1 and algorithm 2) or together (algorithm 3) in the registration. We computed heritability maps and two vector and tensorbased distances to compare the power and the robustness of the algorithms.

A nonconservative Lagrangian framework for statistical fluid registration - SAFIRA

In this paper, we used a nonconservative Lagrangian mechanics approach to formulate a new statistical algorithm for fluid registration of 3-D brain images. This algorithm is named SAFIRA, acronym for statistically-assisted fluid image registration algorithm. A nonstatistical version of this algorithm was implemented, where the deformation was regularized by penalizing deviations from a zero rate of strain. In, the terms regularizing the deformation included the covariance of the deformation matrices Σ and the vector fields (q). Here, we used a Lagrangian framework to reformulate this algorithm, showing that the regularizing terms essentially allow nonconservative work to occur during the flow. Given 3-D brain images from a group of subjects, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the nonstatistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the nonconservative terms, creating four versions of SAFIRA. We evaluated and compared our algorithms' performance on 92 3-D brain scans from healthy monozygotic and dizygotic twins; 2-D validations are also shown for corpus callosum shapes delineated at midline in the same subjects. After preliminary tests to demonstrate each method, we compared their detection power using tensor-based morphometry (TBM), a technique to analyze local volumetric differences in brain structure. We compared the accuracy of each algorithm variant using various statistical metrics derived from the images and deformation fields. All these tests were also run with a traditional fluid method, which has been quite widely used in TBM studies. The versions incorporating vector-based empirical statistics on brain variation were consistently more accurate than their counterparts, when used for automated volumetric quantification in new brain images. This suggests the advantages of this approach for large-scale neuroimaging studies.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.