The decision making process involved when changing career: A qualitative study of registered nurses who have left the profession

Career choice is an important decision an individual has to make during their lifetime. Personal, environmental and organisational factors all assist this decision process as individuals strive for a work-life balance within careers that meet their needs and realise their potential. This research study investigated which factors contributed to the decision process of Registered Nurses (RNs) who have left the profession for a career change. There is currently a global shortage of RNs, which is of major concern to healthcare policy makers in most countries, including Australia. This qualitative study examined the narrative interviews often females over the age of25 years who qualified as RNs but no longer work in nursing. Previously the majority of studies have focused on RNs still employed in the profession and their leaving intentions, rather than decisions made by nurses who have already left nursing. The results suggested that there were several influential factors which related to the work environment, managerial function, and nursing challenges. However, financial remuneration identified in several previous studies as a significant factor, was not supported in this research. Understanding the issues faced by RNs may further assist health organisations, universities and managers to develop strategies to recruit and retain health care professionals

Factors influencing resilience among haematological cancer survivors

Haematological cancers in bone marrow (leukaemia) and the immune system (lymphomas or myeloma) represent the sixth most common adult tumour group in Australia. These cancers often develop without warning and require intensive treatment regimes that last on average eight months, but may continue for a lifetime depending on the diagnosis. Encouragingly, advancing cancer treatments, a key accomplishment of cancer research over the past 40 years, have resulted in a growing community of cancer survivors. Approximately two in three adults diagnosed with haematological cancer (HC) can now expect to survive more than five years. However, they must attempt to navigate the potential side-effects of cancer treatment. Several studies have highlighted the negative physical, social and psychological consequences of a cancer diagnosis such as fear of reoccurrence, infertility, fatigue and depression. However, few studies have explored how these individuals adjust or cope following successful cancer treatment. Cancer survivors who maintain a positive outlook, effectively deal with their health issues and are able to resume normality in their lives are deemed to be resilient. This study aimed to investigate the resilience process that HC survivors adopt following treatment, in order to overcome such adversity. The goal was to enable identification of protective factors that lead to positive mental health outcomes, and risk factors that impede resilience, for the growing HC survivor population. A two-phase, sequential, mixed methods design was adopted. The first (qualitative) developed a model of resilience, by exploring factors that fostered or inhibited HC survivors’ abilities to cope with this health crisis. Data were collected though semi-structured, in-depth, interviews with 23 adult HC survivors from Western Australia (M age = 52.87, SD = 16.72). Thematic and Leximancer software analyses of the interview data identified four main themes and subthemes pertaining to the cancer experience faced by these individuals: (1) the burden associated with a HC diagnosis; (2) resilience: coping with HC; (3) pathways and barriers to resilience; and, (4) survivor outcomes. These themes were then developed into a model, based on the current findings and those that had been identified in the literature. Subsequently, in Phase Two (quantitative), a questionnaire was created using factors that surfaced during the interviews or were identified from the literature. It was first piloted (Stage I) among a convenience sample of 17 mixed cancer survivors to determine clarity, reliability and internal consistency. Afterwards, a large survey was conducted (Stage II) to test the validity of the model developed in Phase One. Twenty-four variables were investigated for their ability to predict resilience and 222 (M age = 54.35, SD = 14.31) eligible questionnaires were obtained. Using a standard multiple regression analysis, the combined effect of the 24 variables accounted for 61% of the variance in resilience scores. Active coping, positive reframing, exercise and support from family and friends were found to positively influence resilience, while self-blame negatively predicted resilience. Only three variables, venting, selfdistraction and substance use, did not contribute significantly. Greater scores on each of the remaining variables; emotional support, instrumental support, planning, acceptance, religion, humour, support (healthcare professional and significant other), appearance, researching information, alternative treatments, time-out and diet, were associated with higher levels of resilience, except for, behavioural disengagement and denial which were negatively correlated. The results identified that higher resilience levels were significantly associated with lower depression and anxiety. In addition, younger participants (\u3c 40 years of age) or those more recently diagnosed (\u3c 5 years) scored significantly higher on depression and anxiety and lower on resilience. The findings highlight that the model developed in this thesis appropriately represented resilience factors identified among other cancer survivor populations. This research contributes to theory, policy and clinical practice, by providing greater insight into the experience of those living with HC and how these individuals cope. Clinicians including psychologists can use the study’s results to improve their clinical assessment and therapeutic approaches to enhance cancer survivor wellbeing. In addition, this information can assist the federal and state governments in formulating improved support infrastructure. Future research should explore how these theoretical findings can be applied practically, and assess the application of this model across cultures

Simplifying Random Satisfiability Problem by Removing Frustrating Interactions

How can we remove some interactions in a constraint satisfaction problem (CSP) such that it still remains satisfiable? In this paper we study a modified survey propagation algorithm that enables us to address this question for a prototypical CSP, i.e. random K-satisfiability problem. The average number of removed interactions is controlled by a tuning parameter in the algorithm. If the original problem is satisfiable then we are able to construct satisfiable subproblems ranging from the original one to a minimal one with minimum possible number of interactions. The minimal satisfiable subproblems will provide directly the solutions of the original problem.Comment: 21 pages, 16 figure

Memory effects in attenuation and amplification quantum processes

With increasing communication rates via quantum channels, memory effects become unavoidable whenever the use rate of the channel is comparable to the typical relaxation time of the channel environment. We introduce a model of a bosonic memory channel, describing correlated noise effects in quantum-optical processes via attenuating or amplifying media. To study such a channel model, we make use of a proper set of collective field variables, which allows us to unravel the memory effects, mapping the n-fold concatenation of the memory channel to a unitarily equivalent, direct product of n single-mode bosonic channels. We hence estimate the channel capacities by relying on known results for the memoryless setting. Our findings show that the model is characterized by two different regimes, in which the cross correlations induced by the noise among different channel uses are either exponentially enhanced or exponentially reduced.Comment: 10 pages, 7 figures, close to the published versio

Interior Point Decoding for Linear Vector Channels

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem. The proposed decoding algorithm is based on a numerical optimization technique so called interior point method with barrier function. Approximate variations of the gradient descent and the Newton methods are used to solve the convex optimization problem. In a decoding process of the proposed algorithm, a search point always lies in the fundamental polytope defined based on a low-density parity-check matrix. Compared with a convectional joint message passing decoder, the proposed decoding algorithm achieves better BER performance with less complexity in the case of partial response channels in many cases.Comment: 18 pages, 17 figures, The paper has been submitted to IEEE Transaction on Information Theor

Finite-Connectivity Spin-Glass Phase Diagrams and Low Density Parity Check Codes

We obtain phase diagrams of regular and irregular finite connectivity spin-glasses. Contact is firstly established between properties of the phase diagram and the performances of low density parity check codes (LDPC) within the Replica Symmetric (RS) ansatz. We then study the location of the dynamical and critical transition of these systems within the one step Replica Symmetry Breaking theory (RSB), extending similar calculations that have been performed in the past for the Bethe spin-glass problem. We observe that, away from the Nishimori line, in the low temperature region, the location of the dynamical transition line does change within the RSB theory, in comparison with the (RS) case. For LDPC decoding over the binary erasure channel we find, at zero temperature and rate R=1/4 an RS critical transition point located at p_c = 0.67 while the critical RSB transition point is located at p_c = 0.7450, to be compared with the corresponding Shannon bound 1-R. For the binary symmetric channel (BSC) we show that the low temperature reentrant behavior of the dynamical transition line, observed within the RS ansatz, changes within the RSB theory; the location of the dynamical transition point occurring at higher values of the channel noise. Possible practical implications to improve the performances of the state-of-the-art error correcting codes are discussed.Comment: 21 pages, 15 figure

Processing and Transmission of Information

Contains reports on three research projects.Lincoln Laboratory (Purchase Order DDL B-00368)United States ArmyUnited States NavyUnited States Air Force (Contract AF19(604)-7400)National Institutes of Health (Grant MH-04737-02)National Science Foundation (Grant G-16526

Belief propagation algorithm for computing correlation functions in finite-temperature quantum many-body systems on loopy graphs

Belief propagation -- a powerful heuristic method to solve inference problems involving a large number of random variables -- was recently generalized to quantum theory. Like its classical counterpart, this algorithm is exact on trees when the appropriate independence conditions are met and is expected to provide reliable approximations when operated on loopy graphs. In this paper, we benchmark the performances of loopy quantum belief propagation (QBP) in the context of finite-tempereture quantum many-body physics. Our results indicate that QBP provides reliable estimates of the high-temperature correlation function when the typical loop size in the graph is large. As such, it is suitable e.g. for the study of quantum spin glasses on Bethe lattices and the decoding of sparse quantum error correction codes.Comment: 5 pages, 4 figure

Asymmetric quantum error correcting codes

The noise in physical qubits is fundamentally asymmetric: in most devices, phase errors are much more probable than bit flips. We propose a quantum error correcting code which takes advantage of this asymmetry and shows good performance at a relatively small cost in redundancy, requiring less than a doubling of the number of physical qubits for error correction

Effective Capacity in Broadcast Channels with Arbitrary Inputs

We consider a broadcast scenario where one transmitter communicates with two receivers under quality-of-service constraints. The transmitter initially employs superposition coding strategies with arbitrarily distributed signals and sends data to both receivers. Regarding the channel state conditions, the receivers perform successive interference cancellation to decode their own data. We express the effective capacity region that provides the maximum allowable sustainable data arrival rate region at the transmitter buffer or buffers. Given an average transmission power limit, we provide a two-step approach to obtain the optimal power allocation policies that maximize the effective capacity region. Then, we characterize the optimal decoding regions at the receivers in the space spanned by the channel fading power values. We finally substantiate our results with numerical presentations.Comment: This paper will appear in 14th International Conference on Wired&Wireless Internet Communications (WWIC