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1. Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Author

Jovan, Ferdian, Morgan, Catherine, McConville, Ryan, Tonkin, Emma L., Craddock, Ian, and Whone, Alan

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, I.2.6, I.2.1, J.3
Abstract

Parkinson's disease (PD) is a slowly progressive, debilitating neurodegenerative disease which causes motor symptoms including gait dysfunction. Motor fluctuations are alterations between periods with a positive response to levodopa therapy ("on") and periods marked by re-emergency of PD symptoms ("off") as the response to medication wears off. These fluctuations often affect gait speed and they increase in their disabling impact as PD progresses. To improve the effectiveness of current indoor localisation methods, a transformer-based approach utilising dual modalities which provide complementary views of movement, Received Signal Strength Indicator (RSSI) and accelerometer data from wearable devices, is proposed. A sub-objective aims to evaluate whether indoor localisation, including its in-home gait speed features (i.e. the time taken to walk between rooms), could be used to evaluate motor fluctuations by detecting whether the person with PD is taking levodopa medications or withholding them. To properly evaluate our proposed method, we use a free-living dataset where the movements and mobility are greatly varied and unstructured as expected in real-world conditions. 24 participants lived in pairs (consisting of one person with PD, one control) for five days in a smart home with various sensors. Our evaluation on the resulting dataset demonstrates that our proposed network outperforms other methods for indoor localisation. The sub-objective evaluation shows that precise room-level localisation predictions, transformed into in-home gait speed features, produce accurate predictions on whether the PD participant is taking or withholding their medications., Comment: 11 pages, 4 figures, 4 tables

Published
2023
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2. A Smartphone App to Reduce Sugar-Sweetened Beverage Consumption Among Young Adults in Australian Remote Indigenous Communities: Design, Formative Evaluation and User-Testing

Author

Tonkin, Emma, Jeffs, Lauren, Wycherley, Thomas Philip, Maher, Carol, Smith, Ross, Hart, Jonathon, Cubillo, Beau, and Brimblecombe, Julie

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe disproportionate burden of noncommunicable disease among Indigenous Australians living in remote Indigenous communities (RICs) is a complex and persistent problem. Smartphones are increasingly being used by young Indigenous adults and therefore represent a promising method to engage them in programs seeking to improve nutritional intake. ObjectiveThis study aimed to consult RIC members to inform the content of a smartphone app that can be used to monitor and reduce sugar-sweetened beverage intake in RICs. MethodsThe study was conducted in two phases. The formative phase involved a simulated grocery selection activity with think aloud (“think aloud shop”), a semistructured interview, a questionnaire outlining current smartphone and app use, and a paper prototyping activity. A preliminary end-user testing phase involved a think aloud prototype test and a semistructured interview regarding user satisfaction. Convenience sampling was used to recruit 20 18- to 35-year-old smartphone users for each phase from two RICs in the Northern Territory, Australia. Thematic analysis of transcribed audio recordings was used to identify determinants of food choice from the think aloud shop; themes related to the Theory of Planned Behavior (TPB) from the eating behaviors interview; and usability, comprehension, and satisfaction with the app from the preliminary end-user testing. ResultsSmartphone use in RICs is currently different to that found in urban environments; in particular, extremely low use of Facebook, restricted variety of phone types, and limited Internet access. Findings regarding promoting app engagement indicate that utilizing an opt-in approach to social features such as leader boards and team challenges is essential. The inclusion of games was also shown to be important for satisfaction, as were the use of audio features, contextually embedded dissemination, and streamlined app design for comprehension in this target group. ConclusionsThis research provides critical insights and concrete recommendations for the development of lifestyle improvement apps targeted toward disadvantaged young adults in nonurban settings, specifically RICs. It serves as a framework for future app development projects using a consultative user-centered design approach, supporting calls for the increased use of this strategy in app development.

Published
2017
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3. When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations

Author

Yamagata, Taku, Tonkin, Emma L., Sanchez, Benjamin Arana, Craddock, Ian, Nieto, Miquel Perello, Santos-Rodriguez, Raul, Yang, Weisong, and Flach, Peter

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction
Abstract

In supervised learning, low quality annotations lead to poorly performing classification and detection models, while also rendering evaluation unreliable. This is particularly apparent on temporal data, where annotation quality is affected by multiple factors. For example, in the post-hoc self-reporting of daily activities, cognitive biases are one of the most common ingredients. In particular, reporting the start and duration of an activity after its finalisation may incorporate biases introduced by personal time perceptions, as well as the imprecision and lack of granularity due to time rounding. Here we propose a method to model human biases on temporal annotations and argue for the use of soft labels. Experimental results in synthetic data show that soft labels provide a better approximation of the ground truth for several metrics. We showcase the method on a real dataset of daily activities.

Published
2023

4. Multimodal Indoor Localisation for Measuring Mobility in Parkinson's Disease using Transformers

Author

Jovan, Ferdian, McConville, Ryan, Morgan, Catherine, Tonkin, Emma, Whone, Alan, and Craddock, Ian

Subjects
Computer Science - Machine Learning
Abstract

Parkinson's disease (PD) is a slowly progressive debilitating neurodegenerative disease which is prominently characterised by motor symptoms. Indoor localisation, including number and speed of room to room transitions, provides a proxy outcome which represents mobility and could be used as a digital biomarker to quantify how mobility changes as this disease progresses. We use data collected from 10 people with Parkinson's, and 10 controls, each of whom lived for five days in a smart home with various sensors. In order to more effectively localise them indoors, we propose a transformer-based approach utilizing two data modalities, Received Signal Strength Indicator (RSSI) and accelerometer data from wearable devices, which provide complementary views of movement. Our approach makes asymmetric and dynamic correlations by a) learning temporal correlations at different scales and levels, and b) utilizing various gating mechanisms to select relevant features within modality and suppress unnecessary modalities. On a dataset with real patients, we demonstrate that our proposed method gives an average accuracy of 89.9%, outperforming competitors. We also show that our model is able to better predict in-home mobility for people with Parkinson's with an average offset of 1.13 seconds to ground truth., Comment: 17 pages, 1 figure, 3 tables

Published
2022

7. HyperStream: a Workflow Engine for Streaming Data

Author

Diethe, Tom, Kull, Meelis, Twomey, Niall, Sokol, Kacper, Song, Hao, Perello-Nieto, Miquel, Tonkin, Emma, and Flach, Peter

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control, Statistics - Machine Learning
Abstract

This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabilities. HyperStream overcomes the limitations of other computational engines and provides high-level interfaces to execute complex nesting, fusion, and prediction both in online and offline forms in streaming environments. HyperStream is a general purpose tool that is well-suited for the design, development, and deployment of Machine Learning algorithms and predictive models in a wide space of sequential predictive problems. Source code, installation instructions, examples, and documentation can be found at: https://github.com/IRC-SPHERE/HyperStream.

Published
2019

8. A Guide to the SPHERE 100 Homes Study Dataset

Author

Elsts, Atis, Burghardt, Tilo, Byrne, Dallan, Camplani, Massimo, Damen, Dima, Fafoutis, Xenofon, Hannuna, Sion, Harwin, William, Holmes, Michael, Janko, Balazs, Lopez, Victor Ponce, Masullo, Alessandro, Mirmehdi, Majid, Oikonomou, George, Piechocki, Robert, Sherratt, R. Simon, Tonkin, Emma, Twomey, Niall, Vafeas, Antonis, Woznowski, Przemyslaw, and Craddock, Ian

Subjects
Computer Science - Other Computer Science
Abstract

The SPHERE project has developed a multi-modal sensor platform for health and behavior monitoring in residential environments. So far, the SPHERE platform has been deployed for data collection in approximately 50 homes for duration up to one year. This technical document describes the format and the expected content of the SPHERE dataset(s) under preparation. It includes a list of some data quality problems (both known to exist in the dataset(s) and potential ones), their workarounds, and other information important to people working with the SPHERE data, software, and hardware. This document does not aim to be an exhaustive descriptor of the SPHERE dataset(s); it also does not aim to discuss or validate the potential scientific uses of the SPHERE data.

Published
2018

9. Challenges in Annotation of useR Data for UbiquitOUs Systems: Results from the 1st ARDUOUS Workshop

Author

Yordanova, Kristina, Paiement, Adeline, Schröder, Max, Tonkin, Emma, Woznowski, Przemyslaw, Olsson, Carl Magnus, Rafferty, Joseph, and Sztyler, Timo

Subjects
Computer Science - Computers and Society, Computer Science - Human-Computer Interaction
Abstract

Labelling user data is a central part of the design and evaluation of pervasive systems that aim to support the user through situation-aware reasoning. It is essential both in designing and training the system to recognise and reason about the situation, either through the definition of a suitable situation model in knowledge-driven applications, or through the preparation of training data for learning tasks in data-driven models. Hence, the quality of annotations can have a significant impact on the performance of the derived systems. Labelling is also vital for validating and quantifying the performance of applications. In particular, comparative evaluations require the production of benchmark datasets based on high-quality and consistent annotations. With pervasive systems relying increasingly on large datasets for designing and testing models of users' activities, the process of data labelling is becoming a major concern for the community. In this work we present a qualitative and quantitative analysis of the challenges associated with annotation of user data and possible strategies towards addressing these challenges. The analysis was based on the data gathered during the 1st International Workshop on Annotation of useR Data for UbiquitOUs Systems (ARDUOUS) and consisted of brainstorming as well as annotation and questionnaire data gathered during the talks, poster session, live annotation session, and discussion session.

Published
2018

13. Supporting unsupervised context identification using social and physical sensors

Author

Tonkin, Emma L.

Subjects
005.25
Abstract

Context-awareness is a popular subject in ubiquitous computing, wearable computing and information retrieval. Location, conditions, activity, task and affect are all viewed as useful elements of context-awareness. Devices equipped with appropriate sensors may collect contextual information directly through infrastructural services or indirectly, through inference from observed conditions. This thesis discusses approaches to representing and sharing such data, such as the selection, development or use of semantic ontologies able to support context-awareness. The problem of selecting an appropriate knowledge representation for activities requiring information about context and the cost of developing, accessing and maintaining ontologies suggests that an approach that automates some part of this activity would be beneficial. We suggest that inspiration could and should be drawn from the mechanisms that govern natural language and classification. We explore and extend an existing approach to unsupervised labelling of contexts. We identify failure modes and potential mitigating strategies for an unsupervised approach depending solely on local interactions. A third source of information in context-awareness is the social sensor. Information shared on the social web-Flickr, Facebook or Twitter, for example-is a rich source of localised information both directly and as a data source for unsupervised learning. We examine data taken from social sensors such as social tagging services, Facebook and Twitter, identifying significant variation in content and encoding which we suggest may be of benefit to the primary user populations of the site. We explore tools intended to support access to and reuse of compound terms. We adapt a well-known experiment in socially shared cognition to a crowdsourcing platform, finding support for the view that the context of message production affects message comprehension. We demonstrate examples of the use of crowdsourced data to ground ontology labels in observation. Finally, we use data taken from a number of social networks to demonstrate the tracking of a single concept across time and space, identifying localised variation in its interpretation and prevalence.

Published
2015

23. Current State of Genomics in Nursing: A Scoping Review of Healthcare Provider Oriented (Clinical and Educational) Outcomes (2012–2022).

Author

Thomas, Joanne, Keels, Jordan, Calzone, Kathleen A., Badzek, Laurie, Dewell, Sarah, Patch, Christine, Tonkin, Emma T., and Dwyer, Andrew A.

Subjects
CLINICAL trials, GENETIC testing, GENOMICS, GENETIC counseling, HIGH-income countries
Abstract

In the 20 years since the initial sequencing of the human genome, genomics has become increasingly relevant to nursing. We sought to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012–2022). The included articles were categorized according to the Cochrane Collaboration outcome domains/sub-domains, and thematic analysis was employed to identify key topical areas to summarize the state of the science. Of 8532 retrieved articles, we identified 232 eligible articles. The articles primarily reported descriptive studies from the United States and other high-income countries (191/232, 82%). More than half (126/232, 54.3%) aligned with the "healthcare provider oriented outcomes" outcome domain. Three times as many articles related to the "knowledge and understanding" sub-domain compared to the "consultation process" subdomain (96 vs. 30). Five key areas of focus were identified, including "nursing practice" (50/126, 40%), "genetic counseling and screening" (29/126, 23%), "specialist nursing" (21/126, 17%), "nurse preparatory education" (17/126, 13%), and "pharmacogenomics" (9/126, 7%). Only 42/126 (33%) articles reported interventional studies. To further integrate genomics into nursing, study findings indicate there is a need to move beyond descriptive work on knowledge and understanding to focus on interventional studies and implementation of genomics into nursing practice. [ABSTRACT FROM AUTHOR]

Published
2023
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24. Towards the identification of genetic factors influencing the stability of short tandem repeats

Author

Tonkin, Emma Tamsin

Subjects
572.8, Genetics
Abstract

This work has identified three distinct approaches that can be used to identify genetic factors involved in the STR instability process. We propose that Schizosaccharomyces pombe, a yeast now recognised as being a good model for the study of many cellular processes in higher eukaryotes, is also suitable for the study of STR instability. We have demonstrated that in S. pombe a plasmid based (CAG/CTG)n sequence containing between 25-74 repeat units is stable over approximately 55 mitotic divisions. A frame-dependent reporter gene construct, based on colour, has also been created containing the dinucleotide repeat (CA/GT)12. By following the change in repeat length or colony colour (for the two constructs respectively) in strains containing both known or randomly created genomic disruptions/mutations it will be possible to identify factors that directly impact upon repeat length. One factor that we have considered as a potential candidate is the product of the S. cerivisiae postreplication repair gene RAD5. An increase in the stability of the dinucleotide repeat (CA/GT)n has been demonstrated in strains deleted for this gene (Johnson et al., 1992). Discussed are the attempts that have been made to clone the S. pombe homologue in order to determine whether this function is maintained between species. Also identified, through the technique of Southwestern blotting, are a number of proteins that bind both single stranded [(CAG)10, (CTG)10, (CCG)10, and (CGG)10] and double stranded [(CAG/CTG)10 and (CCG/CGG)10] trinucleotide repeats. The interactions, with the (CCG)10, oligonucleotide, of a group of proteins ranging in size from 18-45 kDa have been demonstrated to be specific. Further identification of these proteins and their function(s) in binding this particular sequence may identify a role in (CCG/CGG)n instability and may in turn suggest other proteins or pathways to be investigated in the future. This work demonstrates that a number of methods are available for the study of STR instability. A combined approach based on the identification of i) novel sequences using reporter gene constructs; ii) proteins that interact with repetitive DNA and iii) candidate sequences, pathways and mechanisms elucidated in other organisms, will in the future, enable short tandem repeat instability to be more fully understood.

Published
1999

25. Toward Enhanced Clinical Decision Support for Patients Undergoing a Hip or Knee Replacement: Focus Group and Interview Study With Surgeons

Author

Grant, Sabrina, primary, Tonkin, Emma, additional, Craddock, Ian, additional, Blom, Ashley, additional, Holmes, Michael, additional, Judge, Andrew, additional, Masullo, Alessandro, additional, Perello Nieto, Miquel, additional, Song, Hao, additional, Whitehouse, Michael, additional, Flach, Peter, additional, and Gooberman-Hill, Rachael, additional

Published
2023
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26. Communities Setting the Direction for Their Right to Nutritious, Affordable Food: Co-Design of the Remote Food Security Project in Australian Indigenous Communities

Author

Ferguson, Megan, primary, Tonkin, Emma, additional, Brimblecombe, Julie, additional, Lee, Amanda, additional, Fredericks, Bronwyn, additional, Cullerton, Katherine, additional, Mah, Catherine L., additional, Brown, Clare, additional, McMahon, Emma, additional, Chatfield, Mark D., additional, Miles, Eddie, additional, and Cadet-James, Yvonne, additional

Published
2023
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28. sj-docx-1-gph-10.1177_2333794X14554698 ��� Supplemental material for Protein Intake and Growth in Preterm Infants: A Systematic Review

Author

Tonkin, Emma L., Collins, Carmel T., and Miller, Jacqueline

Subjects
111099 Nursing not elsewhere classified, FOS: Clinical medicine, FOS: Health sciences, 111403 Paediatrics, 110904 Neurology and Neuromuscular Diseases
Abstract

Supplemental material, sj-docx-1-gph-10.1177_2333794X14554698 for Protein Intake and Growth in Preterm Infants: A Systematic Review by Emma L. Tonkin, Carmel T. Collins and Jacqueline Miller in Global Pediatric Health

Published
2022
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29. Ensuring best practice in genomics education and evaluation: reporting item standards for education and its evaluation in genomics (RISE2 Genomics)

Author

Nisselle, Amy, Janinski, Monika, Martyn, Melissa, McClaren, Belinda, Kaunein, Nadia, Barlow-Stewart, Kristine, Belcher, Andrea, Bernat, John A, Best, Stephanie, Bishop, Michelle, Carroll, June C, Cornel, Martina, Dissanayake, Vajira H W, Dodds, Agnes, Dunlop, Kate, Garg, Gunjan, Gear, Russell, Graves, Debra, Knight, Ken, Korf, Bruce, Kumar, Dhavendra, Laurino, Mercy, Ma, Alan, Maguire, Jane, Mallett, Andrew, McCarthy, Maria, McEwen, Alison, Mulder, Nicola, Patel, Chirag, Quinlan, Catherine, Reed, Kate, Riggs, Erin Rooney, Sinnerbrink, Ingrid, Slavotinek, Anne, Suppiah, Vijayaprakash, Terrill, Bronwyn, Tobias, Edward S., Tonkin, Emma, Trumble, Steve, Wessels, Tina-Marie, Metcalfe, Sylvia, Jordan, Helen, and Gaff, Clara

Abstract

Purpose: \ud Widespread, quality genomics education for health professionals is required to create a competent genomic workforce. A lack of standards for reporting genomics education and evaluation limits the evidence base for replication and comparison. We therefore undertook a consensus process to develop a recommended minimum set of information to support consistent reporting of design, development, delivery, and evaluation of genomics education interventions.\ud \ud Methods: \ud Draft standards were derived from literature (25 items from 21 publications). Thirty-six international experts were purposively recruited for three rounds of a modified Delphi process to reach consensus on relevance, clarity, comprehensiveness, utility, and design.\ud \ud Results: \ud The final standards include 18 items relating to development and delivery of genomics education interventions, 12 relating to evaluation, and 1 on stakeholder engagement.\ud \ud Conclusion: \ud These Reporting Item Standards for Education and its Evaluation in Genomics (RISE2 Genomics) are intended to be widely applicable across settings and health professions. Their use by those involved in reporting genomics education interventions and evaluation, as well as adoption by journals and policy makers as the expected standard, will support greater transparency, consistency, and comprehensiveness of reporting. Consequently, the genomics education evidence base will be more robust, enabling high-quality education and evaluation across diverse settings.

Published
2021

33. Protocol for PD SENSORS: Parkinson’s Disease Symptom Evaluation in a Naturalistic Setting producing Outcome measuRes using SPHERE technology. An observational feasibility study of multi-modal multi-sensor technology to measure symptoms and activities of daily living in Parkinson’s disease

Author

Morgan, Catherine, primary, Craddock, Ian, additional, Tonkin, Emma L, additional, Kinnunen, Kirsi M, additional, McNaney, Roisin, additional, Whitehouse, Sam, additional, Mirmehdi, Majid, additional, Heidarivincheh, Farnoosh, additional, McConville, Ryan, additional, Carey, Julia, additional, Horne, Alison, additional, Rolinski, Michal, additional, Rochester, Lynn, additional, Maetzler, Walter, additional, Matthews, Helen, additional, Watson, Oliver, additional, Eardley, Rachel, additional, and Whone, Alan L, additional

Published
2020
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37. Decisions of Value: Going Backstage Comment on 'Contextual Factors Influencing Cost and Quality Decisions in Health and Care: A Structured Evidence Review and Narrative Synthesis'

Author

Calnan, Michael .W., Tonkin, Emma, Wilson, Annabelle M., Coveney, John, Henderson, Julie, Meyer, Samantha B., McCarthy, Mary Brigid, O’Reilly, Seamus, McGloin, Aileen, Kelly, Edel, and Ward, Paul

Subjects
Value (ethics), Health (social science), Salience (language), Leadership and Management, Process (engineering), 030503 health policy & services, Health Policy, media_common.quotation_subject, Rationality, Management, Monitoring, Policy and Law, Epistemology, 03 medical and health sciences, 0302 clinical medicine, Health Information Management, Narrative, Quality (business), 030212 general & internal medicine, Allocative efficiency, 0305 other medical science, Psychology, Theme (narrative), media_common
Abstract

This commentary expands on two of the key themes briefly raised in the paper involving analysis of the evidence about key contextual influences on decisions of value. The first theme\ud focuses on the need to explore in more detail what is called backstage decision-making looking at how actual decisions are made drawing on evidence from ethnographies about decision\ud making. These studies point to less of an emphasis on instrumental and calculative forms of decision-making with more of an emphasis on more pragmatic rationality. The second related\ud theme picks up on the issue of sources of information as a contextual influence particularly highlighting the salience of uncertainty or information deficits. It is argued that there are a\ud range of different types of uncertainties, not only associated with information deficits, which are found particularly in allocative types of decisions of value. This means that the decision18\ud making process although attempting to be linear and rational, tends to be characterised by a form of navigation where the decision-makers navigate their way through the uncertainties\ud inherent and overtly manifested in the decision-making process.

Published
2018

38. Working with Text : Tools, Techniques and Approaches for Text Mining

Author

Tonkin, Emma, Tourte, Gregory J.l, Tonkin, Emma, Tonkin, Emma, Tourte, Gregory J.l, and Tonkin, Emma

Abstract

What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining. Introduces text analysis and text mining toolsProvides a comprehensive overview of costs and benefitsIntroduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology

Published
2016

39. Analysis of patient domestic activity in recovery from hip or knee replacement surgery:modelling wrist-worn wearable RSSI and accelerometer data in the wild

Author

Holmes, Mike, Song, Hao, Tonkin, Emma L., Perello Nieto, Miquel, Grant, Sabrina, and Flach, Peter

Subjects
Machine Learning, Domestic Sensor Networks, Activity Classification, SPHERE, Wearable Technology, Internet of Things, Digital Health, Movement Classification, Indoor Localisation, Predictive analyses of home healthcare data
Abstract

The UK health service sees around 160,000 total hip or knee replacements every year and this number is expected to rise. Expectations of surgical outcome are changing alongside demographic trends, whilst aftercare may be fractured as a result of resource limitation or other factors. Conventional assessments of health outcomes must evolve to keep up with these changing trends. In practice, patients may visit a health care professional to discuss recovery and will provide survey feedback to clinicians using standardised instruments, such as the Oxford Hip & Knee score, in the months following surgery. To aid clinicians in providing accurate assessment of patient recovery a continuous home health care monitoring system would be beneficial. In this paper the authors explore how the SPHERE sensor network can be used to automatically generate measures of recovery from arthroplasty to facilitate continuous monitoring of behaviour, including location, room transitions, movement and activity; in terms of frequency and duration; in a domestic environment. The authors present a case study of data collected from a home equipped with the SPHERE sensor network. Machine learning algorithms are applied to a week of continuous observational data to generate insights into the domestic routine of the occupant. Testing of models shows that location and activity are classified with 86% and 63% precision, respectively.

Published
2018

41. The relative validity of the Menzies Remote Short-Item Dietary Assessment Tool (MRSDAT) in Aboriginal Australian children aged 6-36 months

Author

Tonkin, Emma, Kennedy, Dani, Golley, Rebecca, Byrne, Rebecca, Rohit, Athira, Kearns, Therese, Hanieh, Sarah, Biggs, Beverley-Ann, Brimblecombe, Julie, Tonkin, Emma, Kennedy, Dani, Golley, Rebecca, Byrne, Rebecca, Rohit, Athira, Kearns, Therese, Hanieh, Sarah, Biggs, Beverley-Ann, and Brimblecombe, Julie

Abstract

The Menzies Remote Short-item Dietary Assessment Tool (MRSDAT) can be used to derive a dietary index score, which measures the degree of compliance with the Australian Dietary Guidelines. This study aimed to determine the relative validity of a dietary index score for children aged 6–24 months, living in a Remote Aboriginal Community (RAC), derived using MRSDAT. This validation study compared dietary index scores derived using MRSDAT with those derived from the average of three 24-h recalls. Participants were aged 6–36 months at the first dietary assessment and were living in a RAC. The level of agreement between the two methods was explored using Lin’s concordance correlation coefficient (CCC), Bland-Altman plots, weighted Cohen’s kappa, and Fischer’s exact and paired t-tests. Forty participants were recruited. The CCC was poor between methods (R = 0.35, 95% CI 0.06, 0.58), with MRSDAT estimating higher dietary intake scores for all food groups except fruit, and higher dietary quality scores by an average of 4.78 points/100. Community-based Aboriginal researchers were central to this validation study. MRSDAT was within the performance range of other short-item dietary assessment tools developed for young children, and shows promise for use with very young children in RACs

Published
2018

42. Increasing nursing capacity in genomics: Overview of existing global genomics resources

Author

Calzone, Kathleen A, Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, Middleton, Anna, Calzone, Kathleen A, Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, and Middleton, Anna

Abstract

Global genomic literacy of all health professions, including nurses, remains low despite an inundation of genomic information with established clinical and analytic validity and clinical utility. Genomic literacy and competency deficits contribute to lost opportunities to take advantage of the benefits that genomic information provides to improve health outcomes, reduce healthcare costs, and increase patient quality and safety. Nurses are essential to the integration of genomics into healthcare. The greatest challenges to realizing their potential in successful integration include education and awareness. Identification of resources, their focus, whether they targeted at nursing, and how to access them, form the foundation for a global genomic resource initiative led by the Global Genomics Nursing Alliance. The aim was to identify existing global genomic resources and competencies, identifying the source, type and accessibility. Cross sectional online descriptive survey to ascertain existing genomic resources. Limited to eighteen countries and seven organizations represented by delegates attending the inaugural meeting in 2017 of the Global Genomics Nursing Alliance. A purposive sample of global nursing leaders and representatives of national and international nursing organizations. The primary method was by online survey administered following an orientation webinar. Given the small numbers of nurse leaders in genomics within our sample (and indeed within the world), results were analyzed and presented descriptively. Those identifying resources provided further detailed resource information. Additional data were collected during a face-to-face meeting using an electronic audience-response system. Of the twenty-three global delegates responding, 9 identified existing genomic resources that could be used for academic or continuing genomics education. Three countries have competence frameworks to guide learning and 5 countries have national organizations for genetics

Published
2018

43. Increasing nursing capacity in genomics: Overview of existing global genomics resources

Author

Calzone, Kathleen A., Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, Middleton, Anna, Calzone, Kathleen A., Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, and Middleton, Anna

Abstract

Background: Global genomic literacy of all health professions, including nurses, remains low despite an inundation of genomic information with established clinical and analytic validity and clinical utility. Genomic literacy and competency deficits contribute to lost opportunities to take advantage of the benefits that genomic information provides to improve health outcomes, reduce healthcare costs, and increase patient quality and safety. Nurses are essential to the integration of genomics into healthcare. The greatest challenges to realizing their potential in successful integration include education and awareness. Identification of resources, their focus, whether they targeted at nursing, and how to access them, form the foundation for a global genomic resource initiative led by the Global Genomics Nursing Alliance. Objectives: The aim was to identify existing global genomic resources and competencies, identifying the source, type and accessibility. Design: Cross sectional online descriptive survey to ascertain existing genomic resources. Settings: Limited to eighteen countries and seven organizations represented by delegates attending the inaugural meeting in 2017 of the Global Genomics Nursing Alliance. Participants: A purposive sample of global nursing leaders and representatives of national and international nursing organizations. Methods: The primary method was by online survey administered following an orientation webinar. Given the small numbers of nurse leaders in genomics within our sample (and indeed within the world), results were analyzed and presented descriptively. Those identifying resources provided further detailed resource information. Additional data were collected during a face-to-face meeting using an electronic audience-response system. Results: Of the twenty-three global delegates responding, 9 identified existing genomic resources that could be used for academic or continuing genomics education. Three countries have competence frameworks t

Published
2018

44. The Global Landscape of Nursing and Genomics

Author

Calzone, Kathleen A, Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, Middleton, Anna, Calzone, Kathleen A, Kirk, Maggie, Tonkin, Emma, Badzek, Laurie, Benjamin, Caroline, and Middleton, Anna

Abstract

Nurses have a pivotal role in bringing the benefits of genomics and precision medicine to everyday health care, but a concerted global effort is needed to transform nursing policy and practice to address widely acknowledged deficits in nurses' genomic literacy. The purpose was to conduct a global country and organization review of nursing engagement with genomics, informing a landscape analysis to assess readiness for integration of genomics into nursing. Global nursing leaders and nursing organizations were recruited using a purposive sampling strategy to complete an online survey that assessed the scope of genomic integration in practice and education, challenges and barriers, and priorities for action. The survey was administered online following an orientation webinar. Given the small numbers of nurse leaders globally, results were analyzed and presented descriptively. Delegates consisted of 23 nurse leaders from across the world. Genomic services were offered predominantly in specialty centers consisting mostly of newborn screening (15/18) and prenatal screening (11/18). Genomic literacy and infrastructure deficits were identified in both practice and education settings, with only one country reporting a genetic/genomic knowledge and skill requirement to practice as a general nurse. These data provide insights into the commitment to and capacity for nursing to integrate genomics, revealing common themes and challenges associated with adoption of genomic health services and integration into practice, education, and policy. Such insights offer valuable context and baseline information to guide the activities of a new Global Genomics Nursing Alliance (G2NA). The G2NA will use the landscaping exercise as a springboard to explore how to accelerate the integration of genomics into nursing healthcare. Genomics is relevant to all healthcare providers across the healthcare continuum. It provides an underpinning for understanding health, risks for and manifestations of d

Published
2018

45. Enabling Healthcare in Smart Homes: The SPHERE IoT Network Infrastructure

Author

Elsts, Atis, Fafoutis, Xenofon, Woznowski, Przemyslaw, Tonkin, Emma, Oikonomou, George, Piechocki, Robert, Craddock, Ian, Elsts, Atis, Fafoutis, Xenofon, Woznowski, Przemyslaw, Tonkin, Emma, Oikonomou, George, Piechocki, Robert, and Craddock, Ian

Abstract

Healthcare professionals currently lack the means to gather unbiased and quantitative multi-modal data about the long-term behaviors of patients in their home environments. SPHERE is a multi-modal platform of non-medical sensors for behavior monitoring in residential environments that aims to overcome this major limitation of healthcare provision by using the inherently cost-efficient and scalable technologies of the Internet of Things (IoT). One of SPHERE's key tasks is to help bring the next-generation low-power wireless networking and sensing technologies from the lab to the field by applying them in real-world environments. In this article we describe the highlights of SPHERE's system requirements, architecture, practical challenges, and design and deployment lessons learned. By leveraging novel IoT technologies such as the IEEE 802.15.4 network protocol, SPHERE has achieved successful initial deployments in 12 volunteer houses at the time of this writing.

Published
2018

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