Dr Natasha Noble

Background: Young people's gambling behaviours are associated with a range of individual, interpersonal and community factors. This study explored the association between exposure to types of gambling advertising and promotions and adolescent gambling behaviours. Methods: Students from two states answered gambling questions as part of the 2017 Australian Secondary Students¿ Alcohol and Drug (ASSAD) Survey. Students reported gambling behaviours (gambling in the last month, types of gambling activities), exposure to gambling promotions during the last 30 days (e.g. ads for gambling on TV, online, live studio crosses), and were assessed for problem gambling. Principal Component Analysis suggested four groups of gambling promotion exposure. Logistic regression analyses examined the association between gambling promotion exposure and student gambling, engagement in hard gambling activities in the last month, and problem or at risk gambling, controlling for a range of student characteristics. Results: Most students (81%) had been exposed to some form of gambling promotion or advertisement in the last month, most commonly TV, social media and sporting event advertisements. Exposure to online gambling ads (including websites, pop-ups on websites, and social media) in the last month was significantly associated with gambling in the last month, and being classified as an at risk or problem gambler; but not with participating in hard gambling activities. After adjusting for exposure to gambling advertising across categories, no other advertising exposure types were associated with adolescent gambling behaviours. Conclusions: Study findings point to the need to impose restrictions on gambling advertisements and promotions, particularly those presented online.

Introduction: The detection of harmful alcohol use and the delivery of brief advice in primary care are less than optimal. Given limited health care resources, deciding where best to allocate funding to optimize health outcomes is imperative. A simple data-based tool could be useful when access to specialist health economic advice is unavailable. This study aimed to examine the utility of a simple data-based calculator to facilitate priority setting in general practice for reducing alcohol-related harm. Methods: A simple algorithm was developed within Microsoft Excel to allow comparison of hypothetical intervention scenarios that aimed to increase detection and brief advice for harmful alcohol use in general practice. The calculator accommodated varying implementation costs, size of effect and reach for each scenario created. The incremental costs of the intervention scenarios, the incremental number of successes (i.e. abstinence or drinking at safe levels) and the incremental costs-effectiveness ratio (ICER) were calculated for each hypothetical scenario and compared with a usual care scenario. Results: In the hypothetical scenarios modelled, increasing both the detection of harmful alcohol consumption and the provision of brief advice produced the greatest number of incremental successes above baseline. Increasing detection alone produced fewer incremental successes but was the most cost-effective approach, as indicated by the lowest ICER. Discussion: The data-based calculator provides a simple method of exploring reach and cost-effectiveness outcomes without the need for any specific skills. Although this approach has limitations, the calculator can be used by decision makers to guide intervention planning.

Background and Objectives: Primary care physicians (PCPs) have a key role in providing care for people with dementia and their carers, however, a range of barriers prevent them from delivering optimal care. We reviewed studies on PCPs' perceptions of barriers to providing optimal dementia care, including their methodological quality, whether they focused on barriers related to diagnosis and/or management, and the patient-, provider-, and system-level barriers identified. Research Design and Methods: Studies were included if they were quantitative studies published since 2006 which reported on PCPs' perceptions of the barriers to providing dementia care. The methodological quality of identified studies was assessed using an adapted version of accepted rating criteria for quantitative studies. Data were extracted from studies which were rated as "moderate" or "strong" quality. Results: A total of 20 studies were identified, 16 of which were rated as "moderate" or "strong" methodological quality. Patient-related barriers included a reluctance to acknowledge cognitive decline and patient nonadherence to management plans. Provider-related barriers included a lack of training and confidence. System-related barriers included a lack of time during consultations and lack of support services. Discussion and Implications: This review highlights a range of barriers to dementia diagnosis and management from studies rated as being methodologically adequate. Future studies should also utilize theory-driven approaches to exploring a comprehensive range of barriers to optimal dementia care across the care trajectory.

Background: This cross-sectional study aimed to explore, among a sample of patients attending one of four Aboriginal Health Services (ACCHSs), the degree of concordance between self-report and medical records for whether screening for key healthcare items had ever been undertaken, or had been undertaken within the recommended timeframe. Methods: Across the four ACCHSs, a convenience sample of 109 patients was recruited. Patients completed a self-report computer survey assessing when they last had preventive care items undertaken at the service. ACCHS staff completed a medical record audit for matching items. The degree of concordance (i.e. the percentage of cases in which self-reports matched responses from the medical record) was calculated. Results: Concordance was relatively high for items including assessment of Body Mass Index and blood pressure, but was substantially lower for items including assessment of waist circumference, alcohol intake, physical activity, and diet. Conclusions: Reliance on either patient self-report or medical record data for assessing the level of preventive care service delivery by ACCHSs requires caution. Efforts to improve documentation of some preventive care delivery in medical records are needed. These findings are likely to also apply to patients in other general practice settings.

There is increasing interest in the use of brief screening tools to improve detection of depression in the primary care setting. The aim of the present study was to compare the accuracy of the two-item Patient Health Questionnaire (PHQ-2) against the nine-item Patient Health Questionnaire (PHQ-9) for detecting depression among general practice patients. A cross-sectional sample of 3626 adults attending 12 Australian general practices was recruited. Participants completed the PHQ-2 and PHQ-9 via a touchscreen computer. Depression was defined as a PHQ-9 score =10. The area under the curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value were calculated. The PHQ-2 had good overall accuracy relative to the PHQ-9 for discriminating between cases and non-cases of depression, with an AUC of 0.92 (95% confidence interval 0.90-0.93). The PHQ-2 threshold of =3 was the best balance between sensitivity (91%) and specificity (78%) for detecting possible cases of depression. For clinical use, the optimal threshold was =2, with only 2% of possible cases missed.

Objective: There is a growing body of literature examining the clustering of health risk behaviours, but little consensus about which risk factors can be expected to cluster for which sub groups of people. This systematic review aimed to examine the international literature on the clustering of smoking, poor nutrition, excess alcohol and physical inactivity (SNAP) health behaviours among adults, including associated socio-demographic variables. Method: A literature search was conducted in May 2014. Studies examining at least two SNAP risk factors, and using a cluster or factor analysis technique, or comparing observed to expected prevalence of risk factor combinations, were included. Results: Fifty-six relevant studies were identified. A majority of studies (81%) reported a 'healthy' cluster characterised by the absence of any SNAP risk factors. More than half of the studies reported a clustering of alcohol with smoking, and half reported clustering of all four SNAP risk factors. The methodological quality of included studies was generally weak to moderate. Males and those with greater social disadvantage showed riskier patterns of behaviours; younger age was less clearly associated with riskier behaviours. Conclusion: Clustering patterns reported here reinforce the need for health promotion interventions to target multiple behaviours, and for such efforts to be specifically designed and accessible for males and those who are socially disadvantaged.

Background: Indigenous Australians are a socially disadvantaged group who experience significantly poorer health and a higher prevalence of modifiable health behaviours than other Australians. Little is known about the clustering of health risks among Indigenous Australians. The aims of this study were to describe the clustering of key health risk factors, such as smoking, physical inactivity and alcohol consumption, and socio-demographics associated with clusters, among a predominantly Aboriginal sample. Methods: Participants (n = 377) attending an Aboriginal Community Controlled Health Service (ACCHS) in regional/rural New South Wales, Australia, in 2012-2013 completed a self-report touch screen health risk survey. Clusters were identified using latent class analysis. Results: Cluster 1 ('low fruit/vegetable intake, lower risk'; 51 %) consisted of older men and women; Cluster 2 ('risk taking'; 22 %) included younger unemployed males with a high prevalence of smoking, risky alcohol, and illicit drug use. Cluster 3 ('inactive, overweight, depressed'; 28 %) was characterised by younger to mid aged women likely to have experienced emotional or physical violence. Conclusions: If future research identifies similar stable clusters of health behaviours for this population, intervention approaches targeting these clusters of risk factors should be developed and tested for Aboriginal and Torres Strait Islander Australians.

Background: Alcohol disproportionately affects socially disadvantaged groups including Aboriginal and Torres Strait Islander Australians. Methods to assess alcohol intake for disadvantaged communities need to be able to capture variable or episodic drinking. The ability of a seven-day diary to capture typical consumption for a predominantly Aboriginal sample has not been assessed. Objective: One aim of this paper was to examine agreement between a seven-day retrospective diary and 'usual' drinking assessed by a modified version of the Alcohol Use Disorders Identification Test question 3 (AUDIT-3m; two questions). Other aims were to describe drinking patterns as reported in the seven-day diary. Method: In 2012, consecutive adults attending an Aboriginal Community Controlled Health Service completed a cross-sectional health risk survey on a touch screen laptop (n = 188). Alcohol consumption questions included the retrospective diary and AUDIT-3m. Agreement was assessed using weighted kappa analysis. Results: There was good agreement between the two measures of consumption; however, the AUDIT-3m questions identified more current drinkers. Respondents who were drinkers (54%) tended to consume large amounts per drinking occasion: almost half (46%) of diary completers reported nine or more standard drinks on at least one occasion in the last week. Conclusions: The seven-day diary did not adequately capture variability in alcohol consumption common among this sample. Although the AUDIT-3m appeared acceptable, alternative approaches to assess usual or risky alcohol consumption, such as asking about specific drinking occasions, or allowing participants to respond in non-standard drink sizes, also need to be considered for indigenous and other disadvantaged communities.

Modifiable health risk behaviors such as smoking, overweight and obesity, risky alcohol consumption, physical inactivity, and poor nutrition contribute to a substantial proportion of the world's morbidity and mortality burden. General practitioners (GPs) play a key role in identifying and managing modifiable health risk behaviors. However, these are often underdetected and undermanaged in the primary care setting. We describe the potential of eHealth to help patients and GPs to overcome some of the barriers to managing health risk behaviors. In particular, we discuss (1) the role of eHealth in facilitating routine collection of patient-reported data on lifestyle risk factors, and (2) the role of eHealth in improving clinical management of identified risk factors through provision of tailored feedback, point-of-care reminders, tailored educational materials, and referral to online self-management programs. Strategies to harness the capacity of the eHealth medium, including the use of dynamic features and tailoring to help end users engage with, understand, and apply information need to be considered and maximized. Finally, the potential challenges in implementing eHealth solutions in the primary care setting are discussed. In conclusion, there is significant potential for innovative eHealth solutions to make a contribution to improving preventive care in the primary care setting. However, attention to issues such as data security and designing eHealth interfaces that maximize engagement from end users will be important to moving this field forward.

Background: Tailored feedback has been shown to be effective for modifying health risk behaviours and may aid the provision of preventive care by general practitioners (GPs). However, provision of tailored patient feedback for vulnerable or socially disadvantaged groups is not well explored. The aims of this study were to examine the acceptability and effectiveness of providing generic compared to tailored feedback on self-reported health risk behaviours among a high need sample of people attending an Aboriginal Community Controlled Health Service (ACCHS). Methods: Participants attending two ACCHSs in regional New South Wales completed a touch screen health risk survey and received either generic or tailored health risk feedback. Participants were asked to complete an exit survey after their appointment. The exit survey asked about feedback acceptability and effectiveness. Self-reported ease of understanding, relevance and whether the generic versus tailored feedback helped patients talk to their GP was compared using Chi-square analysis; The mean number of survey health risks talked about or for which additional actions were undertaken (such as provision of lifestyle advice or referral) was compared using t-tests. Results: Eighty seven participants (36 % consent rate) completed the exit survey. Tailored feedback was rated as more relevant and was more likely to be shown to the participant's GP than generic feedback. There was no difference in the mean number of health risk topics discussed or number of additional actions taken by the GP by type of feedback. Conclusions: Tailored and generic feedback showed no difference in effectiveness, and little difference in acceptability, among this socially disadvantaged population. Completing a health risk survey and receiving any type of feedback may have overwhelmed more subtle differences in outcomes between the generic and the tailored feedback. Future work to rigorously evaluate the longer-term effectiveness of the provision of tailored health risk feedback for Aboriginal Australians, as well as other high need groups, is still needed. Trial Registration: Australian New Zealand Clinical Trials Registry ANZCTRN12614001205628. Registered 11 November 2014.