Depression, anxiety and stress among Australian nursing and midwifery undergraduate students during the COVID-19 pandemic : A cross-sectional study
- Authors: Wynter, Karen , Redley, Bernice , Holton, Sara , Manias, Elizabeth , McDonall, Jo , McTier, Lauren , Hutchinson, Alison , Kerr, Debra , Lowe, Grainne , Phillips, Nicole , Rasmussen, Bodil
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Nursing Education Scholarship Vol. 18, no. 1 (2021), p.
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- Description: Objectives: To assess depression, anxiety and stress among undergraduate nursing and midwifery students during the COVID-19 pandemic, and identify socio-demographic and educational characteristics associated with higher depression, anxiety and stress scores. Methods: Cross-sectional study during August-September 2020, using an anonymous, online, self-administered survey. E-mail invitations with a survey link were sent to 2,907 students enrolled in the Bachelor of Nursing suite of courses, offered across four campuses of a single university in Victoria, Australia. Depression, anxiety and stress were assessed using the DASS-21. Data on socio-demographic and educational characteristics, self-rated physical health and exposure to COVID-19 were also collected. DASS-21 subscale scores were compared with existing data for various pre-pandemic and COVID-19 samples. Multiple regression was used to investigate factors associated with higher scores on depression, anxiety and stress subscales. Results: The response rate was 22% (n=638). Mean scores on all DASS-21 subscales were significantly higher (p<0.001) than means from all comparative sample data. The proportions of students reporting moderate to severe symptoms of depression, anxiety and stress were 48.5%, 37.2% and 40.2% respectively. Being a woman, being younger, having completed more years of study and having poorer self-rated general health were all significantly associated (p<0.05) with higher scores on at least one DASS-21 subscale. Conclusions: Almost half of participants reported at least moderate symptoms of depression; more than a third reported at least moderate symptoms of anxiety or stress. Poor psychological wellbeing can impact students' successful completion of their studies and therefore, has implications for nursing and midwifery workforce recruitment and retention. During and after pandemics, universities should consider screening undergraduate students not only for anxiety and stress, but also for depression. Clear, low-cost referral pathways should be available, should screening indicate that further diagnosis or treatment is required. © 2021 Walter de Gruyter GmbH, Berlin/Boston.
The first year : the support needs of parents caring for a child with an intellectual disability
- Authors: Douglas, Tracy , Redley, Bernice , Ottmann, Goetz
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Advanced Nursing Vol. 72, no. 11 (Nov 2016), p. 2738-2749
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The need to know : the information needs of parents of infants with an intellectual disability-a qualitative study
- Authors: Douglas, Tracy , Redley, Bernice , Ottmann, Goetz
- Date: 2017
- Type: Text , Journal article
- Relation: Journal of Advanced Nursing Vol. 73, no. 11 (Nov 2017), p. 2600-2608
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- Description: Aim: The aim of this study was to explore the information needs of parents of infants with an intellectual disability in the first year of life. Background: Parents whose infant has an intellectual disability need access to information if they are to facilitate optimal care for their child. A lack of timely, accurate information provision by health professionals, particularly nurses and midwives, can increase parental stress and hinder access to the supports they and their infant require. Design: A qualitative descriptive methodology was used for the study. Methods: Qualitative interviews were undertaken with parents of 11 children with intellectual disabilities in Victoria, Australia in 2014. Data were analysed using descriptive thematic analysis. Findings: Parents experienced challenges accessing quality information during the first year of their child's life. Parents required incremental information provision to build a strong knowledge base to facilitate optimal care for their infants. Three types of knowledge were identified as crucial for parents: knowledge about (1) the infant's condition; (2) the infant's specific needs and (3) available supports and services. Health professionals were the key resource to access this information. Conclusion: Health professionals’ responsibilities include providing relevant, timely information to parents of infants with intellectual disabilities. This study conceptualises three types of information parents need to develop a strong knowledge base to guide their infant's care and provides guidance concerning the optimal timing for the delivery of information. © 2017 John Wiley & Sons Ltd
The impact of covid-19 on psychosocial well-being and learning for australian nursing and midwifery undergraduate students: a cross-sectional survey
- Authors: Rasmussen, Bodil , Hutchinson, Alison , Lowe, Grainne , Wynter, Karen , Redley, Bernice , Holton, Sara , Manias, Elizabeth , Phillips, Nikki , McDonall, Jo , McTier, Lauren , Kerr, Debra
- Date: 2022
- Type: Text , Journal article
- Relation: Nurse Education in Practice Vol. 58, no. (2022), p.
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- Description: Aim: To explore the impact of COVID-19 on psychosocial well-being and learning for nursing and midwifery undergraduate students in an Australian university. Background: The World Health Organization has reported a substantial psychological impact of COVID-19 on healthcare professionals to date. Evidence is lacking, however, regarding university nursing and midwifery students of the pandemic and its impact on their educational preparation and/or clinical placement during the COVID-19 pandemic. Design: Cross-sectional survey of nursing and midwifery undergraduate students enrolled in the Bachelor of Nursing suite of courses from the study institution in August- September 2020. Methods: A cross-sectional self-administered anonymous online survey was distributed to current nursing and midwifery undergraduate students. The survey included three open-ended questions; responses were thematically analysed. Results: Of 2907 students invited, 637 (22%) responded with 288 of the respondents (45%) providing a response to at least one of the three open-ended questions. Three major themes associated with the impact of the pandemic on psychosocial well-being and learning were identified: psychosocial impact of the pandemic, adjustment to new modes of teaching and learning, and concerns about course progression and career. These themes were underpinned by lack of motivation to study, feeling isolated, and experiencing stress and anxiety that impacted on students’ well-being and their ability to learn and study. Conclusions: Students were appreciative of different and flexible teaching modes that allowed them to balance their study, family, and employment responsibilities. Support from academic staff and clinical facilitators/mentors combined with clear and timely communication of risk management related to personal protective equipment (PPE) in a healthcare facility, were reported to reduce students’ stress and anxiety. Ways to support and maintain motivation among undergraduate nursing and midwifery students are needed. © 2021
Ode to form
- Authors: Mestrom, Sanne
- Date: 2012
- Type: Text , Visual art work
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Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
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- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
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- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
Conical averagedness and convergence analysis of fixed point algorithms
- Authors: Bartz, Sedi , Dao, Minh , Phan, Hung
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 82, no. 2 (2022), p. 351-373
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- Description: We study a conical extension of averaged nonexpansive operators and the role it plays in convergence analysis of fixed point algorithms. Various properties of conically averaged operators are systematically investigated, in particular, the stability under relaxations, convex combinations and compositions. We derive conical averagedness properties of resolvents of generalized monotone operators. These properties are then utilized in order to analyze the convergence of the proximal point algorithm, the forward–backward algorithm, and the adaptive Douglas–Rachford algorithm. Our study unifies, improves and casts new light on recent studies of these topics. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Magic and antimagic labeling of graphs
- Authors: Sugeng, Kiki Ariyanti
- Date: 2005
- Type: Text , Thesis , PhD
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- Description: "A bijection mapping that assigns natural numbers to vertices and/or edges of a graph is called a labeling. In this thesis, we consider graph labelings that have weights associated with each edge and/or vertex. If all the vertex weights (respectively, edge weights) have the same value then the labeling is called magic. If the weight is different for every vertex (respectively, every edge) then we called the labeling antimagic. In this thesis we introduce some variations of magic and antimagic labelings and discuss their properties and provide corresponding labeling schemes. There are two main parts in this thesis. One main part is on vertex labeling and the other main part is on edge labeling."
- Description: Doctor of Philosophy
Strongly regular points of mappings
- Authors: Abbasi, Malek , Théra, Michel
- Date: 2021
- Type: Text , Journal article
- Relation: Fixed Point Theory and Algorithms for Sciences and Engineering Vol. 2021, no. 1 (Journal article 2021), p.
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- Description: In this paper, we use a robust lower directional derivative and provide some sufficient conditions to ensure the strong regularity of a given mapping at a certain point. Then, we discuss the Hoffman estimation and achieve some results for the estimate of the distance to the set of solutions to a system of linear equalities. The advantage of our estimate is that it allows one to calculate the coefficient of the error bound. © 2021, The Author(s).
On graphs with cyclic defect or excess
- Authors: Delorme, Charles , Pineda-Villavicencio, Guillermo
- Date: 2010
- Type: Text , Journal article
- Relation: Electronic Journal of Combinatorics Vol. 17, no. 1 (2010), p.
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- Description: The Moore bound constitutes both an upper bound on the order of a graph of maximum degree d and diameter D = k and a lower bound on the order of a graph of minimum degree d and odd girth g = 2k + 1. Graphs missing or exceeding the Moore bound by ε are called graphs with defect or excess ε, respectively. While Moore graphs (graphs with ε = 0) and graphs with defect or excess 1 have been characterized almost completely, graphs with defect or excess 2 represent a wide unexplored area. Graphs with defect (excess) 2 satisfy the equation Gd,k(A) = Jn +B (Gd,k(A) = Jn - B), where A denotes the adjacency matrix of the graph in question, n its order, Jn the n × n matrix whose entries are all 1's, B the adjacency matrix of a union of vertex-disjoint cycles, and Gd,k(x) a polynomial with integer coefficients such that the matrix Gd,k(A) gives the number of paths of length at most k joining each pair of vertices in the graph. In particular, if B is the adjacency matrix of a cycle of order n we call the corresponding graphs graphs with cyclic defect or excess; these graphs are the subject of our attention in this paper. We prove the non-existence of infinitely many such graphs. As the highlight of the paper we provide the asymptotic upper bound of O(64/3 d3/2) for the number of graphs of odd degree d ≥ 3 and cyclic defect or excess. This bound is in fact quite generous, and as a way of illustration, we show the non-existence of some families of graphs of odd degree d ≥ 3 and cyclic defect or excess. Actually, we conjecture that, apart from the Möbius ladder on 8 vertices, no non-trivial graph of any degree ≥ 3 and cyclic defect or excess exists.
Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
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- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
Structural properties and labeling of graphs
- Authors: Dafik
- Date: 2007
- Type: Text , Thesis , PhD
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- Description: The complexity in building massive scale parallel processing systems has re- sulted in a growing interest in the study of interconnection networks design. Network design affects the performance, cost, scalability, and availability of parallel computers. Therefore, discovering a good structure of the network is one of the basic issues. From modeling point of view, the structure of networks can be naturally stud- ied in terms of graph theory. Several common desirable features of networks, such as large number of processing elements, good throughput, short data com- munication delay, modularity, good fault tolerance and diameter vulnerability correspond to properties of the underlying graphs of networks, including large number of vertices, small diameter, high connectivity and overall balance (or regularity) of the graph or digraph. The first part of this thesis deals with the issue of interconnection networks ad- dressing system. From graph theory point of view, this issue is mainly related to a graph labeling. We investigate a special family of graph labeling, namely antimagic labeling of a class of disconnected graphs. We present new results in super (a; d)-edge antimagic total labeling for disjoint union of multiple copies of special families of graphs. The second part of this thesis deals with the issue of regularity of digraphs with the number of vertices close to the upper bound, called the Moore bound, which is unobtainable for most values of out-degree and diameter. Regularity of the underlying graph of a network is often considered to be essential since the flow of messages and exchange of data between processing elements will be on average faster if there is a similar number of interconnections coming in and going out of each processing element. This means that the in-degree and out-degree of each processing element must be the same or almost the same. Our new results show that digraphs of order two less than Moore bound are either diregular or almost diregular.
- Description: Doctor of Philosophy
Linkedness of cartesian products of complete graphs
- Authors: Jorgensen, Leif , Pineda-Villavicencio, Guillermo , Ugon, Julien
- Date: 2022
- Type: Text , Journal article
- Relation: Ars Mathematica Contemporanea Vol. 22, no. 2 (2022), p.
- Relation: http://purl.org/au-research/grants/arc/DP180100602
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- Description: This paper is concerned with the linkedness of Cartesian products of complete graphs. A graph with at least 2k vertices is k-linked if, for every set of 2k distinct vertices organised in arbitrary k pairs of vertices, there are k vertex-disjoint paths joining the vertices in the pairs. We show that the Cartesian product Kd1+1 × Kd2+1 of complete graphs Kd1+1 and Kd2+1 is
You Can’t Beat Relating with God for Spiritual Well-Being: Comparing a Generic Version with the Original Spiritual Well-Being Questionnaire Called SHALOM
- Authors: Fisher, John
- Date: 2013
- Type: Text , Journal article
- Relation: Religions Vol. 2013, no. 4 (2013), p. 325-335
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- Description: The Spiritual Health And Life-Orientation Measure (SHALOM) is a 20-item instrument that assesses the quality of relationships of the respondent with self, others, the environment and/or a Transcendent Other. In the Transcendental domain, four of the five items had the words ‘God, ‘Divine’ and ‘Creator’ replaced by the word ‘Transcendent’ to make the survey more generic by removing any implied reference to any god or religion. Invitations to complete a web survey were sent to people who had published papers in spirituality, or belonged to associations for spirituality or religious studies, as well as the Australian Atheist Forum. 409 respondents from 14 geographic regions, completed the survey. Confirmatory factor analysis revealed that the modified, generic form of SHALOM showed acceptable model fit, comprising four clearly delineated domains of spiritual well-being. The paper analyses the results derived from using the modified, generic version and, in comparison with results of applications of the original survey instrument, concludes with discussion of the comparative utility of each of the versions of SHALOM. Further studies with more people are warranted, but, from evidence presented here, it looks like you can’t beat relating with God for spiritual well-being.
Nursing and midwifery students’ mental health status and intention to leave during Covid-19 pandemic
- Authors: Haririan, Hamidreza , Samadi, Parisa , Lalezari, Elnaz , Habibzadeh, Sajad , Porter, Joanne
- Date: 2022
- Type: Text , Journal article
- Relation: SAGE Open Nursing Vol. 8, no. (2022), p.
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- Description: Introduction: COVID-19 has not only affected the physical health of people but it has also had a major impact on their mental health. Objective: To investigate the nursing, midwifery, and operating room students’ mental health and intention to leave during COVID-19 pandemic. Methods: This cross-sectional study was conducted at the nursing and midwifery school of Tabriz, Iran. Over a period of three months (February–May 2021) and through random sampling, 284 students were selected. The research tool consisted of three parts including demographic information, Depression Anxiety Stress scales, and a questionnaire on intention to leave. Results: More than 20% of the students experienced some degrees of depression, anxiety, and stress. Nearly one-third of participants mentioned a high level of intention to leave. Nursing students had a higher level of a turnover tendency than other students (p =.004). Male students and who experienced moderate to high level of depression displayed greater intention to leave (p =.005). Conclusion: Students suffered from some degrees of stress, anxiety, and depression during the COVID-19, and it strengthened the participants’ intention to leave. Relevant authorities are recommended to improve mental health of the students by providing psychological counseling sessions, reducing their direct contact with patients, and providing personal protective equipment. © The Author(s) 2022.
New Farkas-type results for vector-valued functions : A non-abstract approach
- Authors: Dinh, Nguyen , Goberna, Miguel , Long, Dang , Lopez-Cerda, Marco
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. 182, no. 1 (2019), p. 4-29
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- Description: This paper provides new Farkas-type results characterizing the inclusion of a given set, called contained set, into a second given set, called container set, both of them are subsets of some locally convex space, called decision space. The contained and the container sets are described here by means of vector functions from the decision space to other two locally convex spaces which are equipped with the partial ordering associated with given convex cones. These new Farkas lemmas are obtained via the complete characterization of the conic epigraphs of certain conjugate mappings which constitute the core of our approach. In contrast with a previous paper of three of the authors (Dinh et al. in J Optim Theory Appl 173:357-390, 2017), the aimed characterizations of the containment are expressed here in terms of the data.
Post-modernism and witchcraft history
- Authors: Waldron, David
- Date: 2001
- Type: Text , Journal article
- Relation: The Pomegranate: Journal of Neo-Pagan Thought Vol. 15, no. 7 (2001), p. 16-22
- Full Text: false
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- Description: C1
- Description: 2003003419
Complete catalogue of graphs of maximum degree 3 and defect at most 4
- Authors: Miller, Mirka , Pineda-Villavicencio, Guillermo
- Date: 2009
- Type: Text , Journal article
- Relation: Discrete Applied Mathematics Vol. 157, no. 13 (2009), p. 2983-2996
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- Description: We consider graphs of maximum degree 3, diameter D≥2 and at most 4 vertices less than the Moore bound M3,D, that is, (3,D,−)-graphs for ≤4. We prove the non-existence of (3,D,−4)-graphs for D≥5, completing in this way the catalogue of (3,D,−)-graphs with D≥2 and ≤4. Our results also give an improvement to the upper bound on the largest possible number N3,D of vertices in a graph of maximum degree 3 and diameter D, so that N3,D≤M3,D−6 for D≥5. Copyright Elsevier.
An adaptive splitting algorithm for the sum of two generalized monotone operators and one cocoercive operator
- Authors: Dao, Minh , Phan, Hung
- Date: 2021
- Type: Text , Journal article
- Relation: Fixed Point Theory and Algorithms for Sciences and Engineering Vol. 2021, no. 1 (2021), p.
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- Description: Splitting algorithms for finding a zero of sum of operators often involve multiple steps which are referred to as forward or backward steps. Forward steps are the explicit use of the operators and backward steps involve the operators implicitly via their resolvents. In this paper, we study an adaptive splitting algorithm for finding a zero of the sum of three operators. We assume that two of the operators are generalized monotone and their resolvents are computable, while the other operator is cocoercive but its resolvent is missing or costly to compute. Our splitting algorithm adapts new parameters to the generalized monotonicity of the operators and, at the same time, combines appropriate forward and backward steps to guarantee convergence to a solution of the problem. © 2021, The Author(s).