ORCID Profile
0000-0002-4741-3326
Current Organisation
Organisation
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: JMIR Publications Inc.
Date: 28-02-2022
Abstract: rtificial intelligence (AI) for use in healthcare and social services is rapidly developing, but this has significant ethical, legal, and social implications (ELSI). Theoretical and conceptual research in AI ethics is rapidly expanding empirical research is needed to understand the values and judgements of members of the public, who will be the ultimate recipients of AI-enabled services. o assess and compare Australians’ general and particular judgements regarding the use of AI, to compare Australians’ judgements about different healthcare and social service applications of AI, and to determine the attributes of health and social service AI systems that Australians consider most important. e conducted a survey of the Australian population using an innovative s ling and weighting methodology involving two s le components, one from an omnibus survey using a s le selected by scientific probability s ling methods, and one from a non-probability s led online panel. The online panel s le was calibrated to the omnibus survey s le using behavioural, lifestyle and socio-demographic variables. Univariate and bivariate analyses were performed. e included weighted responses from 1950 Australians in the online panel, along with a further 2498 from the omnibus survey for a subset of questions. Both weighted s les were socio-demographically well spread. An estimated 60% of Australians support the development of AI in general, but in specific healthcare scenarios this diminishes to between 27 and 43%, and for social service scenarios between 31 and 39%. While all ethical and social dimensions of AI presented were rated as important, accuracy was consistently the most important and reducing costs the least important speed was also consistently lower in importance. Four in five Australians valued continued human contact and discretion in service provision more than any speed, accuracy, or convenience that AI systems might provide. he ethical and social dimensions of AI systems matter to Australians. AI systems should augment rather than replace humans in the provision of both health and social services, and these AI systems should reflect human values. There must be meaningful and active participation of ethicists, social scientists and the public in AI development and implementation, particularly in sensitive and value-laden domains such as healthcare and social services.
Publisher: JMIR Publications Inc.
Date: 10-2021
DOI: 10.2196/24200
Abstract: The use of government health data for secondary purposes, such as monitoring the quality of hospital services, researching the health needs of populations, and testing how well new treatments work, is increasing. This increase in the secondary uses of health data has led to increased interest in what the public thinks about data sharing, in particular, the possibilities of sharing with the private sector for research and development. Although international evidence demonstrates broad public support for the secondary use of health data, this support does not extend to sharing health data with the private sector. If governments intend to share health data with the private sector, knowing what the public thinks will be important. This paper reports a national survey to explore public attitudes in Australia toward sharing health data with private companies for research on and development of therapeutic drugs and medical devices. This study aims to explore public attitudes in Australia toward sharing government health data with the private sector. A web-based survey tool was developed to assess attitudes about sharing government health data with the private sector. A market research company was employed to administer the web-based survey in June 2019. The survey was completed by 2537 in iduals residing in Australia. Between 51.8% and 57.98% of all participants were willing to share their data, with slightly fewer in favor of sharing to improve health services (51.99%) and a slightly higher proportion in favor of sharing for research and development (57.98%). There was a preference for opt-in consent (53.44%) and broad support for placing conditions on sharing health information with private companies (62% to 91.99%). Wide variability was also observed in participants’ views about the extent to which the private sector could be trusted and how well they would behave if entrusted with people’s health information. In their qualitative responses, the participants noted concerns about private sector corporate interests, corruption, and profit making and expressed doubt about the Australian government’s capacity to manage data sharing safely. The percentages presented are adjusted against the Australian population. This nationally representative survey provides preliminary evidence that Australians are uncertain about sharing their health data with the private sector. Although just over half of all the respondents supported sharing health data with the private sector, there was also strong support for strict conditions on sharing data and for opt-in consent and significant concerns about how well the private sector would manage government health data. Addressing public concern about sharing government health data with the private sector will require more and better engagement to build community understanding about how agencies can collect, share, protect, and use their personal data.
Publisher: Springer Science and Business Media LLC
Date: 04-04-2023
DOI: 10.1007/S40520-023-02390-2
Abstract: Postoperative delirium (POD) is a major complication following a surgical procedure. There is evidence that improving knowledge about POD could enhance POD care and patient outcomes. The study aimed to evaluate whether the amount of delirium education among registered nurses working in post-anaesthetics care units (PACU) impacts on their self-reported confidence and competence in recognising and managing delirium as well as prior knowledge on factors that influence the risk of delirium onset for older people. The current study utilised an online survey on delirium care practice among registered nurses in PACUs. The survey consisted of 27 items. There were questions about confidence and competence in delirium care, knowledge about delirium risk factors, and ranked responses to two case scenario questions to evaluate the application of POD care. There were also demographic questions, including previous experience with delirium care education. A total of 336 responses were generated from registered nurses working in PACU. Our findings found substantial variability among the respondents about their delirium care education. The amount of delirium education did not influence the PACU registered nurses’ confidence or competence in delirium care. In addition, previous education did not have an impact on their knowledge about delirium risk factors. These findings suggested that the quantity of prior education about delirium did not improve the confidence, competence, knowledge, or case scenario questions of PACU registered nurses. Thus, delirium care education needs to be transformed to ensure it has a positive effect on delirium care clinical practice by registered nurses in PACU.
Publisher: Wiley
Date: 06-07-2019
Publisher: Informa UK Limited
Date: 28-09-2017
DOI: 10.1080/00365521.2017.1384053
Abstract: Indications for endoscopic retrograde cholangiopancreatography (ERCP) have received little attention, especially in scientific or objective terms. To review the prevailing ERCP indications in the literature, and to propose and evaluate a new ERCP indication system, which relies on more objective pre-procedure parameters. An analysis was conducted on 1758 consecutive ERCP procedures, in which contemporaneous use was made of an a-priori indication system. Indications were based on the objective pre-procedure parameters and ided into primary [cholangitis, clinical evidence of biliary leak, acute (biliary) pancreatitis, abnormal intraoperative cholangiogram (IOC), or change/removal of stent for benign/malignant disease] and secondary [combination of two or three of: pain attributable to biliary disease ('P'), imaging evidence of biliary disease ('I'), and abnormal liver function tests (LFTs) ('L')]. A secondary indication was only used if a primary indication was not present. The relationship between this newly developed classification system and ERCP findings and adverse events was examined. The indications of cholangitis and positive IOC were predictive of choledocholithiasis at ERCP (101/154 and 74/141 procedures, respectively). With respect to secondary indications, only if all three of 'P', 'I', and 'L' were present there was a statistically significant association with choledocholithiasis (χ An a-priori-based indication system for ERCP, which relies on pre-ERCP objective parameters, provides a more useful and scientific classification system than is available currently.
Publisher: Elsevier BV
Date: 08-2018
Publisher: Cold Spring Harbor Laboratory
Date: 02-2023
DOI: 10.1101/2023.01.30.23285209
Abstract: Applications of AI (artificial intelligence) have the potential to improve aspects of healthcare. However, studies have shown that healthcare AI algorithms also have the potential to perpetuate existing inequities in healthcare, performing less effectively for marginalised populations. Studies on public attitudes toward AI outside of the healthcare field have tended to show higher levels of support for AI amongst socioeconomically advantaged groups that are less likely to be sufferers of algorithmic harms. We aimed to examine the sociodemographic predictors of support for scenarios related to healthcare AI. The AVA-AI survey was conducted in March 2020 to assess Australians’ attitudes toward artificial intelligence in healthcare. An innovative weighting methodology involved weighting a non-probability web-based panel against results from a shorter omnibus survey distributed to a representative s le of Australians. We used multinomial logistic regression to examine the relationship between support for AI and a suite of sociodemographic variables in various healthcare scenarios. Where support for AI was predicted by measures of socioeconomic advantage such as education, household income, and SEIFA index, the same variables were not predictors of support for the scenarios presented. Variables associated with support for healthcare AI across all three scenarios included being male, having computer science or programming experience, and being aged between 18 and 34 years. Other Australian studies suggest that this group have a higher level of perceived familiarity with AI. Our findings suggest that while support for AI in general is predicted by indicators of social advantage, these same indicators do not predict support for healthcare AI. Artificial intelligence has the potential to perpetuate existing biases in healthcare datasets, which may be more harmful for marginalised populations. Support for the development of artificial intelligence tends to be higher amongst more socioeconomically privileged groups. Whilst general support for the development of artificial intelligence was higher amongst socioeconomically privileged groups, support for the development of healthcare artificial intelligence was not. Groups that were more likely to support healthcare artificial intelligence were males, those with computer science experience, and younger people. Healthcare artificial intelligence is becoming more relevant for the public as new applications are developed and implemented. Understanding how public attitudes differ amongst sociodemographic subgroups is important for future governance of healthcare AI.
Publisher: Wiley
Date: 16-06-2022
DOI: 10.1111/AJO.13553
Abstract: Socio‐economic (SE) status is closely linked to health status and the mechanisms of this association are complex. One important adverse effect of SE disadvantage is vulnerability to cancer and cancer is a major cause of morbidity and mortality in Australia. We aimed to estimate the effect of SE status on mortality rates from ovarian, cervical, and endometrial cancer. National mortality data were obtained from the Australian Bureau of Statistics (ABS) for the calendar years from 2001 to 2018, inclusive. In idual deaths were grouped by the ABS Index of Relative Socio‐economic Advantage and Disadvantage. Population data were obtained to provided denominators allowing calculation of mortality rates (deaths per 100 000 women aged 30–79 years). Statistical analyses performed included tabulating point‐estimates of mortality rates and their changes over time and modelling the trends of rates using maximum likelihood method. Age‐standardised mortality rates for ovarian and cervical cancer fell over the study period but increased for endometrial cancer. There was clear evidence of a SE gradient in the mortality rate for all three cancers. This SE gradient increased over the study period for ovarian and cervical cancer but remained unchanged for endometrial cancer. Women at greater SE disadvantage have higher rates of death from the commonest gynaecological cancers and this gradient has not reduced over the last two decades. After the COVID‐19 pandemic efforts must be redoubled to ensure that Australians already at risk of ill health do not face even greater risks because of their circumstances.
Publisher: BMJ
Date: 23-09-2020
Abstract: We examined to what extent perceived neighbourhood crime moderates, associations between type 2 diabetes mellitus (T2DM) and perceived local amenities, recreational facilities, footpaths and public transit, and potential mediation of environmental characteristics—T2DM association by physical activity, social contact, sleep and body mass index (BMI). The 45 and Up Study data of 36, 224 in iduals collected from 2010 to 2015 were analysed in 2019 using multilevel logistic regression to examine the association between T2DM and clustering of unfavourable built environment, and any difference in the association with increasing unfavourable environment and area disadvantage. We performed causal mediation analyses stratified by crime to examine whether crime moderated the strength of identified local amenities–T2DM pathways. The results showed that irrespective of crime, perceived lack of local amenities was associated with increased odds of developing T2DM, and BMI mediated 40% and 30.3% of this association among those who reported unsafe and safe daytime crime, respectively. The proportion mediated by BMI among those who reported unsafe and safe night-time crime was 27.3% and 35.1%, respectively. Walking mediated 5.7% of the local amenities–T2DM association among those who reported safe daytime crime. The odds of T2DM increased with rising unfavourable environment and area disadvantage. The results suggest that the availability of neighbourhood amenities may lower T2DM risk by increasing walking and reducing BMI regardless of area crime. Policies to enhance access to local amenities and prevent crime, especially in disadvantaged areas, may support healthy behaviour and physical health that can potentially reduce T2DM risk.
Publisher: Hindawi Limited
Date: 2012
DOI: 10.1155/2012/675724
Publisher: Asian Institute of Research
Date: 30-12-2020
Publisher: Wiley
Date: 23-01-2018
DOI: 10.1111/AJO.12766
Abstract: Rising rates of caesarean section (CS) have been attributed, in part, to maternal-choice CS (MCCS). There are few published data regarding maternal and perinatal risks comparing MCCS with planned vaginal birth (VB) in uncomplicated first pregnancies to inform choice. We report the results of a pragmatic patient-preference cohort study of private patients in Australia: 64 women planning MCCS and 113 women planning VB. There were few differences in outcome between the two groups. The study highlighted the well-recognised difficulties in undertaking prospective research into MCCS.
Publisher: No publisher found
Date: 2016
Publisher: Wiley
Date: 02-05-2023
DOI: 10.1111/WVN.12649
Abstract: With the increase in life expectancy around the globe, the incidence of postoperative delirium (POD) among older people (≥65 years) is growing. Previous studies showed a wide variation in the incidence of POD, from 4% to 53%, with a lack of specific evidence about the incidence of POD by specific surgery type among older people. The aim of this systematic review and meta‐analysis was to determine the incidence of POD by surgery type within populations 65 years and over. Databases including PubMed, Cochrane library, Embase, and CINAHL were searched until October 2020. Due to the relatively higher number of meta‐analyses undertaken in this area of research, a streamlined systematic meta‐analysis was proposed. A total of 28 meta‐analyses (comprising 284 in idual studies) were reviewed. Data from relevant in idual studies ( n = 90) were extracted and included in the current study. Studies were grouped into eight surgery types and the incidence of POD for orthopedic, vascular, spinal, cardiac, colorectal, abdominal, urologic, and mixed surgeries was 20%, 14%, 13%, 32%, 14%, 30%, 10%, and 26%, respectively. POD detection instruments were different across the studies, with Confusion Assessment Method (CAM & CAM‐ICU) being the most frequently adopted. This study showed that POD incidence in older people undergoing surgery varied widely across surgery type. The more complex surgeries like cardiac and abdominal surgeries were associated with a higher risk of POD. This highlights the need to include the level of surgery complexity as a risk factor in preoperative assessments.
Publisher: JMIR Publications Inc.
Date: 22-08-2022
DOI: 10.2196/37611
Abstract: Artificial intelligence (AI) for use in health care and social services is rapidly developing, but this has significant ethical, legal, and social implications. Theoretical and conceptual research in AI ethics needs to be complemented with empirical research to understand the values and judgments of members of the public, who will be the ultimate recipients of AI-enabled services. The aim of the Australian Values and Attitudes on AI (AVA-AI) study was to assess and compare Australians’ general and particular judgments regarding the use of AI, compare Australians’ judgments regarding different health care and social service applications of AI, and determine the attributes of health care and social service AI systems that Australians consider most important. We conducted a survey of the Australian population using an innovative s ling and weighting methodology involving 2 s le components: one from an omnibus survey using a s le selected using scientific probability s ling methods and one from a nonprobability-s led web-based panel. The web-based panel s le was calibrated to the omnibus survey s le using behavioral, lifestyle, and sociodemographic variables. Univariate and bivariate analyses were performed. We included weighted responses from 1950 Australians in the web-based panel along with a further 2498 responses from the omnibus survey for a subset of questions. Both weighted s les were sociodemographically well spread. An estimated 60% of Australians support the development of AI in general but, in specific health care scenarios, this diminishes to between 27% and 43% and, for social service scenarios, between 31% and 39%. Although all ethical and social dimensions of AI presented were rated as important, accuracy was consistently the most important and reducing costs the least important. Speed was also consistently lower in importance. In total, 4 in 5 Australians valued continued human contact and discretion in service provision more than any speed, accuracy, or convenience that AI systems might provide. The ethical and social dimensions of AI systems matter to Australians. Most think AI systems should augment rather than replace humans in the provision of both health care and social services. Although expressing broad support for AI, people made finely tuned judgments about the acceptability of particular AI applications with different potential benefits and downsides. Further qualitative research is needed to understand the reasons underpinning these judgments. The participation of ethicists, social scientists, and the public can help guide AI development and implementation, particularly in sensitive and value-laden domains such as health care and social services.
Publisher: Wiley
Date: 28-11-2018
DOI: 10.1111/AJO.12926
Abstract: Improvements in success rates of assisted reproduction led to predictions that infertility surgery in both women and men would become extinct in developed countries. We sought to identify the changes in reproductive surgery that occurred between 2001 and 2015 to determine whether these predictions have been accurate. The Australian Institute of Health and Welfare (AIHW) national procedural dataset and the Australian Medicare Benefits Scheme (MBS) claims database were searched for procedure data for male and female reproductive surgery and assisted reproduction from January 2001 to December 2015. The denominators were based on annual point estimates of the total population aged 25-44 years (female) and 25-55 years (male) from the Australian Bureau of Statistics (ABS). This dataset provides procedures undertaken but not their indications. Over the study period the incidence of tubal surgery fell by 66%, vasectomy reversal by 33%, and surgical varicocoelectomy by 50%. In contrast, the rate of hysteroscopic myomectomy increased by 48%, hysteroscopic septoplasty by 125%, and laparoscopy for severe endometriosis increased by 84%. In vitro fertilisation oocyte retrievals increased by 90%. The rate of abdominal myomectomy was unchanged. Fertility surgery is not dead but has evolved.
Publisher: MDPI AG
Date: 14-12-2022
DOI: 10.3390/MATH10244744
Abstract: In the age of data, data mining provides feasible tools with which to handle large datasets consisting of data from multiple sources. However, there is limited research on retrieving statistical information from data when data are confidential and cannot be shared directly. In this paper, we address this problem and propose a framework for performing data analysis using data from multiple sources without revealing true values for privacy purposes. The proposed framework includes three steps. First, data custodians in idually mask data before publishing then, the masked data collection is used to reconstruct the density function of the original dataset, from which res led values are generated last, existing data mining techniques are applied directly to the res led data. This framework utilises the technique of reconstructing an original density function from noise-masked data using the moment-based density estimation method, which plays an essential role. Simulation studies show that the proposed framework performs well analysis results from the res led data are comparable to those of the original data when the density of the original data is estimated well. The proposed framework is demonstrated in data clustering analysis using the ex le of a real-life Australian soybean dataset. Results from the k-means algorithms with two and three fitted clusters are presented to show that cluster analysis using res led data can well replicate that of the original data.
Publisher: Elsevier BV
Date: 06-2021
Publisher: Insight Medical Publishing
Date: 2019
Publisher: JMIR Publications Inc.
Date: 14-09-2020
Abstract: he use of government health data for secondary purposes, such as monitoring the quality of hospital services, researching the health needs of populations, and testing how well new treatments work, is increasing. This increase in the secondary uses of health data has led to increased interest in what the public thinks about data sharing, in particular, the possibilities of sharing with the private sector for research and development. Although international evidence demonstrates broad public support for the secondary use of health data, this support does not extend to sharing health data with the private sector. If governments intend to share health data with the private sector, knowing what the public thinks will be important. This paper reports a national survey to explore public attitudes in Australia toward sharing health data with private companies for research on and development of therapeutic drugs and medical devices. his study aims to explore public attitudes in Australia toward sharing government health data with the private sector. web-based survey tool was developed to assess attitudes about sharing government health data with the private sector. A market research company was employed to administer the web-based survey in June 2019. he survey was completed by 2537 in iduals residing in Australia. Between 51.8% and 57.98% of all participants were willing to share their data, with slightly fewer in favor of sharing to improve health services (51.99%) and a slightly higher proportion in favor of sharing for research and development (57.98%). There was a preference for opt-in consent (53.44%) and broad support for placing conditions on sharing health information with private companies (62% to 91.99%). Wide variability was also observed in participants’ views about the extent to which the private sector could be trusted and how well they would behave if entrusted with people’s health information. In their qualitative responses, the participants noted concerns about private sector corporate interests, corruption, and profit making and expressed doubt about the Australian government’s capacity to manage data sharing safely. The percentages presented are adjusted against the Australian population. his nationally representative survey provides preliminary evidence that Australians are uncertain about sharing their health data with the private sector. Although just over half of all the respondents supported sharing health data with the private sector, there was also strong support for strict conditions on sharing data and for opt-in consent and significant concerns about how well the private sector would manage government health data. Addressing public concern about sharing government health data with the private sector will require more and better engagement to build community understanding about how agencies can collect, share, protect, and use their personal data.
Publisher: Cold Spring Harbor Laboratory
Date: 27-01-2022
DOI: 10.1101/2022.01.27.22269895
Abstract: The Omicron variant of SARS-CoV-2 is now overtaking the Delta variant in many countries. Results showing that sera from double vaccinated in iduals have minimal neutralizing activity against Omicron may indicate that the higher rate of transmission is due to evasion from vaccine-induced immunity. However, there is little information about activation of recall responses to Omicron in vaccinated in iduals. We measured inflammatory mediators, antibodies to the SARS-CoV-2 spike and nucleocapsid proteins, and spike peptide-induced release of interferon gamma in whole blood in 51 vaccinated in iduals infected with Omicron, in 14 infected with Delta, and in 18 healthy controls. The median time points for the first and second s les were 7 and 14 days after symptom onset, respectively. Infection with Omicron or Delta led to a rapid and similar increase in antibodies to the SARS-CoV-2 spike and nucleocapsid proteins and spike peptide-induced interferon gamma in whole blood. Both the Omicron and the Delta infected patients had a mild and transient increase in inflammatory parameters. The results suggest that vaccine-induced immunological memory yields similar coverage for the Omicron and Delta variants.
No related grants have been discovered for Pauline ding.