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Background: Several modifiable risk factors for dementia have been identified, although the extent to which their modification leads to improved cognitive outcomes remains unclear. Objective: The primary aim is to test the hypothesis that a behavior modification intervention program targeting personalized risk factors prevents cognitive decline in community-dwelling, middle-aged adults with a family history of dementia. Methods: This is a prospective, risk factor management, blinded endpoint, randomized, controlled trial, where 1510 cognitively normal, community-dwelling adults aged 40–70 years old will be recruited. Participants will be screened for risk factors related to vascular health (including physical inactivity), mental health, sleep, and cognitive/social engagement. The intervention is an online person-centered risk factor management program: BetterBrains. Participants randomized to intervention will receive telehealth-based person-centered goal setting, motivational interviewing, and follow-up support, health care provider communication and community linkage for management of known modifiable risk factors of dementia. Psychoeducational health information will be provided to both control and intervention groups. Results: The primary outcome is favorable cognitive performance at 24-months post-baseline, defined as the absence of decline on one or more of the following cognitive tests: (a) Cogstate Detection, (b) Cogstate One Card Learning, (c) Cogstate One Back, and (d) Cognitive Function Instrument total score. Conclusion: We will test the hypothesis that the BetterBrains intervention program can prevent cognitive decline. By leveraging existing community services and using a risk factor management pathway that tailors the intervention to each participant, we maximize likelihood for engagement, long-term adherence, and for preserving cognitive function in at-risk individuals.

BACKGROUND Heightened behavioural impulsivity has been advocated as pre-existing risk factors for the development of alcohol use disorder (AUD). Nonetheless, studies investigating impulsivity in adolescent/young adult at-risk drinkers - who are at increased risk of developing AUD - report mixed findings. This may be due to methodological limitations related to definitions of at-risk drinking, the retrospective assessment of alcohol intake, and/or the relatively modest sample size of some studies. METHODS Healthy individuals (N = 814, Mage = 22.50) completed online surveys and a measure of choice impulsivity. Of these, a number also undertook an online measure of response inhibition (n = 627, Mage = 22.66), and a further subgroup submitted real-time alcohol consumption information for a period of 21 days using an app (n = 543, Mage = 22.96). Differences in behavioural impulsivity were assessed as a function of various at-risk alcohol intake categories. Hierarchical multiple regression was employed to determine whether impulsivity predicted alcohol use in the form of a continuous index comprising variables related to intake and consequences of use. RESULTS Significantly greater impulsivity was not evident in heavy, standard binge, high binge, harmful, or hazardous alcohol drinkers as compared to controls, regardless of the criteria employed to categorise these at-risk drinkers. Neither choice impulsivity nor reduced response inhibition significantly predicted the alcohol use index. CONCLUSIONS While results could be attributed to the online nature of this research, it is possible more sensitive measures of behavioural impulsivity are required when assessing non-dependent drinkers.

Introduction: Despite the numerous episodic memory tasks used in neuropsychological assessment, relatively few learning tasks are available, with methods lacking the complexity and sophistication to capture very subtle changes in information acquisition.Method: We adapted a previously validated associative learning task for use within an online framework, utilizing real-world stimuli, in which learning of audio-visual pairs of Chinese characters and English words occurs over 5 days. The aim of this study was to validate our adaptation to the task, provide estimates of rates of learning in both young and older adults, as well as provide a methodological framework for further adaptation and development of the paradigm. A total of 30 young adults and 30 older adults completed 5 days of the Chinese Characters Learning Task (CCLT).Results: Results indicated that rates of learning on the adapted task were comparable to the original paradigm and consistent across variations to testing frequency and duration. Our results also indicate the presence of a significant age-related impairment in the rate and accuracy of learning, with young adults aged 18-45 years performing significantly better than older adults aged 65-85 years, that was not due to differences in reaction time.Conclusions: These findings suggest that daily measurement of cognition via an online platform can detect age-related impairments in learning and is therefore applicable for use within the context of age-related disorders of memory and learning.

ObjectiveTo determine the extent to which deficits in learning over 6 days are associated with β-amyloid–positive (Aβ+) and hippocampal volume in cognitively normal (CN) adults.MethodsEighty CN older adults who had undergone PET neuroimaging to determine Aβ status (n = 42 Aβ− and 38 Aβ+), MRI to determine hippocampal and ventricular volume, and repeated assessment of memory were recruited from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Participants completed the Online Repeatable Cognitive Assessment–Language Learning Test (ORCA-LLT), which required they learn associations between 50 Chinese characters and their English language equivalents over 6 days. ORCA-LLT assessments were supervised on the first day and were completed remotely online for all remaining days.ResultsLearning curves in the Aβ+ CN participants were significantly worse than those in matched Aβ− CN participants, with the magnitude of this difference very large (d [95% confidence interval (CI)] 2.22 [1.64–2.75], p < 0.001), and greater than differences between these groups for memory decline since their enrollment in AIBL (d [95% CI] 0.52 [0.07–0.96], p = 0.021), or memory impairment at their most recent visit. In Aβ+ CN adults, slower rates of learning were associated with smaller hippocampal and larger ventricular volumes.ConclusionsThese results suggest that in CN participants, Aβ+ is associated more strongly with a deficit in learning than any aspect of memory dysfunction. Slower rates of learning in Aβ+ CN participants were associated with hippocampal volume loss. Considered together, these data suggest that the primary cognitive consequence of Aβ+ is a failure to benefit from experience when exposed to novel stimuli, even over very short periods.

Background The alcohol consumption patterns of young adults are of concern. Critically, tertiary students consume greater quantities of alcohol, are at increased risk of injury/harm, and have higher rates of alcohol use disorders as compared to their nonuniversity enrolled peers. The Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ) is one of several tools utilized to explore adverse alcohol-related outcomes among tertiary students. Alcohol intake behavior, assessed via retrospective summary measures, has been linked to BYAACQ score. It is unclear, however, how drinking assessed in real time, in conjunction with variables such as age of drinking onset, might predict severity of adverse alcohol consequences as captured by the BYAACQ. Methods The psychometric properties of the BYAACQ were explored using a large Australian sample of tertiary students (N = 893). A subsample (n = 504) provided alcohol intake information in real time (21 days; event and notification contingent) via a smartphone app (CNLab-A) plus details related to age of drinking onset, drug use, parental alcohol/drug use, and anxiety/depression symptomology. Results Average BYAACQ score was 7.53 (SD = 5.37). Classical and item response theory analyses revealed inconsistencies related to dimensionality, progressive item severity, and male/female differential item functioning. Current drinking-namely, frequency of intake and quantity per drinking occasion-plus age of drinking onset predicted BYAACQ score after controlling for age, other drug use, and depression symptomology. Conclusions The BYAACQ is a sound tool for use with Australian samples. Information related to current drinking, age of drinking onset, and drug use is useful for predicting severity of alcohol use consequences. These markers might enable tertiary institutions to better target students who could benefit from prevention/intervention programs.

Australasia is a region with a high incidence of type 1 diabetes (T1D). There are approximately 140 000 individuals with T1D, and of these 10 000 are children. Although the region covers a huge geographical area, most children with T1D are managed by tertiary academic centers in the major capital cities. Local longitudinal data collection has been in place for several decades in most of these centers, however ongoing national data collection had not been attempted. In 2012, with funding from the Juvenile Diabetes Research Foundation (JDRF) Australian Type 1 Clinical Research Network, a national collaboration was formed to provide ongoing longitudinal collection of T1D patient characteristics and outcomes. The initial phase of this collaboration, known as the Australasian Diabetes Data Network or ADDN, was led by the Australasian Paediatric Endocrine Group (APEG) and thus included only children and adolescents. The next phase, commenced in 2016, will see adult sites added through collaboration with the Australian Diabetes Society (ADS). As most of the initial centers had longitudinal data collection in place the model employed was to establish the transfer and collation of data already collected into a central database. This required the definition of a common data dictionary, ethics and governance procedures and the employment of technology to enable efficient and accurate information transfer and accessibility. The ADDN project received widespread support from the diabetes research community with study investigators representing 20 pediatric centers across the region. The first phase focused on the 5 largest centers and at the end of 2015 these centers were uploading patient data to the ADDN database on a quarterly basis resulting in 5271 patients with 83 506 diabetes visits.

Introduction Research investigating problem drinking often relies on retrospective measures to assess alcohol consumption behaviour. Limitations associated with such instruments can, however, distort actual consumption levels and patterns. We developed the smartphone application (app), CNLab-A, to assess alcohol intake behaviour in real-time. Methods Healthy individuals (N = 671, M age 23.12) completed demographic questions plus the Alcohol Use Questionnaire and a 21-day Timeline Followback before using CNLab-A for 21 days. The app asked participants to record alcohol consumption details in real time. We compared data reported via retrospective measures with that captured using CNLab-A. Results On average, participants submitted data on 20.27 days using CNLab-A. Compared to Timeline Followback, a significantly greater percentage of drinking days (24.79% vs. 26.44%) and significantly higher total intake (20.30 vs. 24.26 standard drinks) was recorded via the app. CNLab-A captured a substantially greater number of high intake occasions at all levels from 8 or more drinks than Timeline Followback. Additionally, relative to the Alcohol Use Questionnaire, a significantly faster rate of consumption was recorded via the app. Conclusions CNLab-A provided more nuanced information regarding quantity and pattern of alcohol intake than the retrospective measures. In particular, it revealed higher levels of drinking than retrospective reporting. This will have implications for how particular at-risk alcohol consumption patterns are identified in future and might enable a more sophisticated exploration of the causes and consequences of drinking behaviour.

As the most widely used recreational drug in Australia, alcohol is often misused or over consumed by young people. Binge drinking, drink driving and unsafe sex after drinking have been identified as major health risks affecting young people. This paper reports on a platform applying mobile technology to help doctors and researchers collect data among young people and inform individuals about their alcohol consumption patterns. This app is available in both the iOS and the Android platforms. The app itself collects information on self-reported alcohol consumption patterns and records it for analysis on a Cloud-based data platform. The app tracks individual alcohol consumption longitudinally with a range of server side analysis components. The range of information collected through the app will improve not only the process of data collection and enhance the accuracy of the collected data for alcohol researchers, but also reduce the workload of doctors and researchers in monitoring and analysis of alcohol consumption patterns and their impact on young people and society more generally.

BackgroundThere are disadvantages—largely related to cost, participant burden, and missing data—associated with traditional electronic methods of assessing drinking behavior in real time. This potentially diminishes some of the advantages—namely, enhanced sample size and diversity—typically attributed to these methods. Download of smartphone apps to participants’ own phones might preserve these advantages. However, to date, few researchers have detailed the process involved in developing custom-built apps for use in the experimental arena or explored methodological concerns regarding compliance and reactivity. ObjectiveThe aim of this study was to describe the process used to guide the development of a custom-built smartphone app designed to capture alcohol intake behavior in the healthy population. Methodological issues related to compliance with and reactivity to app study protocols were examined. Specifically, we sought to investigate whether hazard and nonhazard drinkers would be equally compliant. We also explored whether reactivity in the form of a decrease in drinking or reduced responding (“yes”) to drinking behavior would emerge as a function of hazard or nonhazard group status. MethodsAn iterative development process that included elements typical of agile software design guided the creation of the CNLab-A app. Healthy individuals used the app to record alcohol consumption behavior each day for 21 days. Submissions were either event- or notification-contingent. We considered the size and diversity of the sample, and assessed the data for evidence of app protocol compliance and reactivity as a function of hazard and nonhazard drinker status. ResultsCNLab-A yielded a large and diverse sample (N=671, mean age 23.12). On average, participants submitted data on 20.27 (SD 1.88) out of 21 days (96.5%, 20.27/21). Both hazard and nonhazard drinkers were highly compliant with app protocols. There were no differences between groups in terms of number of days of app use (P=.49) or average number of app responses (P=.54). Linear growth analyses revealed hazardous drinkers decreased their alcohol intake by 0.80 standard drinks over the 21-day experimental period. There was no change to the drinking of nonhazard individuals. Both hazard and nonhazard drinkers showed a slight decrease in responding (“yes”) to drinking behavior over the same period. ConclusionsSmartphone apps participants download to their own phones are effective and methodologically sound means of obtaining alcohol consumption information for research purposes. Although further investigation is required, such apps might, in future, allow for a more thorough examination of the antecedents and consequences of drinking behavior.

Narrowband observations have detected no Ly-alpha emission within a 70 pMpc^3 volume centered on the z = 2.168 quasar PKS 0424-131. This is in contrast to surveys of Ly-alpha emitters in the field at similar redshifts and flux limits, which indicate that tens of sources should be visible within the same volume. The observed difference indicates that the quasar environment has a significant influence on the observed density of Ly-alpha emitters. To quantify this effect we have constructed a semi-analytic model to simulate the effect of a luminous quasar on nearby Ly-alpha emitters. We find the null detection around PKS 0424-131 implies that the minimum isothermal temperature of Ly-alpha emitter host halos is greater than 3.4 x 10^6 K (68% level), corresponding to a virial mass of ~1.2 x 10^12 M_solar. This indicates that the intense UV emission of the quasar may be suppressing the star formation in nearby galaxies. Our study illustrates that low redshift quasar environments may serve as a surrogate for studying the radiative suppression of galaxy formation during the epoch of reionization.

The $47m Australian National eResearch Collaboration Tools and Resources (NeCTAR - www.nectar.org.au) project has recently funded an initiative to establish an Australia-wide endocrine genomics virtual laboratory (endoVL – www.endovl.org.au) covering a range of disorders including type-1, type-2 diabetes, rare diabetes-related disorders, obesity/thyroid disorders, neuroendocrine/adrenal tumours, bone disorders and disorders of sex development. This virtual laboratory will establish a range of targeted databases, clinical registries and support a range of genetically targeted clinical trials leveraging a body of international projects and experiences garnered over many years through a range of EU and MRC funded initiatives. This paper focuses on the plans for endoVL and especially, the systems it leverages in supporting large-scale clinical, collaborative environments.