https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:51348 Wed 28 Feb 2024 15:50:49 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39525 Wed 27 Jul 2022 14:04:09 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:24335 3 months (222 pain patients and 204 opioid substitution therapy (OST) patients). We employed item and scale psychometrics (exploratory factor analyses, confirmatory factor analyses and item-response theory statistics) to refine items to a brief scale. Results: Following removal of problematic items (poor retest-reliability or wording, semantic redundancy, differential item functioning, collinearity or rarity) iterative factor analytic procedures identified a 10-item unifactorial scale with good model fit in the total sample (N= 426; CFI = 0.981, TLI = 0.975, RMSEA = 0.057), and among pain (CFI = 0.969, TLI = 0.960, RMSEA = 0.062) and OST subgroups (CFI = 0.989, TFI = 0.986, RMSEA = 0.051). The 10 items provided good discrimination between groups, demonstrated acceptable test-retest reliability (ICC 0.80, 95% CI 0.60-0.89; Cronbach's alpha = 0.89), were moderately correlated with related constructs, including opioid dependence (SDS), depression and stress (DASS subscales) and Social Relationships and Environment domains of the WHO-QoL, and had strong face validity among advising clinicians. Conclusions: The Opioid-Related Behaviours In Treatment (ORBIT) scale is brief, reliable and validated for use in diverse patient groups receiving opioids. The ORBIT has potential applications as a checklist to prompt clinical discussions and as a tool to quantify aberrant behaviour and assess change over time.]]> Wed 24 Nov 2021 15:52:02 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47131 Wed 14 Dec 2022 15:13:34 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:21113 Wed 11 Apr 2018 13:31:44 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:10918 Wed 11 Apr 2018 10:32:32 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:32909 Wed 09 Feb 2022 15:52:55 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:51633 Wed 01 May 2024 11:50:26 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:13823 Tue 24 Aug 2021 14:27:18 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47397 Tue 08 Aug 2023 15:46:10 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:46524 Tue 05 Sep 2023 14:38:18 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:30663 Thu 31 May 2018 11:47:43 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:43039 4 standard drinks on a single occasion), and (ii) the total number of alcoholic drinks consumed in the past year, adjusted for a range of potential child, parent, family, and peer covariates. Results: Fifty percent of adolescents reported alcohol use and 36% reported bingeing at wave 5 (mean age 16.9 years), and the mean age of initiation to alcohol use for drinkers was 15.1 years. Age of initiation was significantly associated with binge drinking and total quantity of alcohol consumed in unadjusted and adjusted models. Age of first drunkenness was associated with total quantity of alcohol consumed in unadjusted models but not adjusted models and was not associated with subsequent bingeing. Conclusions: Initiating alcohol use earlier in adolescence is associated with an increased risk of binge drinking and higher quantity of consumption in late secondary school, supporting an argument for delaying alcohol initiation for as long as possible to reduce the risk for problematic use in later adolescence and the alcohol-related harms that may accompany this use.]]> Thu 24 Aug 2023 09:26:02 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47431 Thu 19 Jan 2023 16:19:38 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:40305 Thu 07 Jul 2022 16:14:44 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:23227 20 cig/day) compared to light-moderate smoking is unknown. The link between behavioural risk factors and future smoking for both ex and current smokers is also unknown. This study sought to examine these relationships. It is hypothesised that behavioural risk factors will be more strongly associated with heavy smoking. Method: Data from Wave 7 (2007) of the Household and Labour Dynamics in Australia (HILDA) survey was analysed using logistic regression to determine relationships between diet (fruit and vegetable consumption, and unhealthy diet choices), alcohol consumption, obesity and physical activity with light-moderate smoking and heavy smoking. The association between these risk factors and future smoking (2008) was assessed for current and ex-smokers (2007). Results: Obese respondents were less likely to be light/moderate smokers (RRR: 0.53; 95% CI: 0.43, 0.66) but not heavy smokers. Those who consume confectionary weekly were less likely to be light/moderate smokers (RRR: 0.73; 95% CI: 0.61, 0.87), but not heavy smokers. Smokers in 2007 were more likely to continue smoking in 2008 if they consumed 1-4 drinks per occasion (OR: 2.52; 95% CI: 1.13, 5.62). Ex-smokers in 2007 were less likely to relapse in 2008 if they consumed recommended levels of both fruit and vegetables (OR: 0.31; CI: 0.10, 0.91). Conclusion: The relationships between heavy smoking and behavioural risk factors differ from moderate-light smoking. Future primary care interventions would benefit from targeting multiple risk factors, particularly for heavy smokers.]]> Thu 04 Nov 2021 10:40:06 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:35002 Thu 04 Nov 2021 10:40:01 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47847 Thu 02 Feb 2023 16:26:00 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:49210 Sun 07 May 2023 09:29:54 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:18128 Sat 24 Mar 2018 08:04:28 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:21006 N = 1,823) were recruited in 3 states from Australian grade 7 classes. Multinomial logistic analyses compared adolescents who had only had a sip/taste of alcohol (sippers) with adolescents who had consumed at least a whole drink (drinkers) in the past 6 months. The multivariate model assessed a broad range of demographics, parenting practices, peer influences, and adolescent externalizing and internalizing behaviors, and controlled for school clustering. Results: Compared to drinkers, sippers were less likely to come from 1-parent households (odds ratio [OR] = 0.59, 95% confidence interval [CI]: 0.35 to 0.98); less likely to come from low-socioeconomic status (SES) households (OR = 0.54, 95% CI: 0.31 to 0.94); more likely to come from families where parents provide stricter alcohol-specific rules (OR = 1.21, 95% CI: 1.11 to 1.32), stricter monitoring of the child's activities (OR = 1.10, 95% CI: 1.04 to 1.16), more consistent parenting practices (OR = 1.13, 95% CI: 1.05 to 1.23), and more positive family relationships (OR = 1.56, 95% CI: 1.02 to 2.43); and report having fewer substance-using peers (OR = 0.80, 95% CI: 0.70 to 0.91) and greater peer disapproval of any substance use (OR = 1.30, 95% CI: 1.19 to 1.42). After adjustment for confounders, the associations with household composition and SES were no longer significant, but the familial and peer associations remained significant in the multivariate analysis, X²(40) = 1,493.06, p < 0.001. Conclusions: Sipping alcohol has different associations with known predictors of adolescent alcohol use than drinking whole beverages, and sipping may be a distinct or separable behavior. Future research should better define quantities of early consumption and assess the relationship between early sipping and drinking on long-term outcomes separately.]]> Sat 24 Mar 2018 07:50:38 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:27016 Sat 24 Mar 2018 07:30:17 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:26237 sipping only, and drinking only. Results: Combining sipping and drinking into a single category, lifetime consumption was reported by 67.3% of the present sample. Distinguishing lifetime consumption by sipping and drinking: only 7.8% of adolescents had consumed a whole beverage; the remaining 59.6% had only sipped. Consumption of whole beverages was mostly limited to 1 to 2 drinks (84.2% of drinkers). Sipping and drinking were also infrequent: 78.2% of sipping and 60.4% of drinking, occurred less than monthly. Heavy episodic consumption was uncommon (1.2% of the sample). When other population studies were inspected, a clear trend for higher drinking rates were found in those studies where sipping was counted as drinking and vice versa. Conclusions: Consumption of whole beverages appears infrequent in early adolescence, as sipping, but not drinking, was common in our sample. Comparing the present data with international population consumption measures highlights the need to more precisely measure and report adolescent consumption, particularly in relation to sipping.]]> Sat 24 Mar 2018 07:24:04 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:24608 Sat 24 Mar 2018 07:11:55 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:25030 Sat 24 Mar 2018 07:10:49 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:26832  90% retention, and a 3-year follow-up is under way. The data collected include child, familial, parental and peer factors addressing demographics, alcohol use and supply, parenting practices, other substance use, adolescent behaviours and peer influences. The cohort is ideal for prospectively examining predictors of initiation and progression of alcohol use, which increases markedly through adolescence.]]> Mon 23 Sep 2019 13:37:27 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47535 per se.]]> Mon 23 Jan 2023 12:22:54 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:46245 Mon 14 Nov 2022 13:21:59 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39579 Mon 08 Aug 2022 11:35:05 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:48638 4 standard drinks), and alcohol-related harms. Results: At mean age of 12.9 years about one in ten children report parental supply of alcohol which increases to about four in ten children by 17.8 years. Mothers consistently more often supply their daughters with alcohol than their sons, [Wave 5 OR 1.77 (1.53,2.05)], while mothers less often supply sons than their daughters, [Wave 5 OR 0.82 (0.71,0.95)]. Mothers’ supply of alcohol to daughters predicts substantially increased odds of daughters binge drinking, [OR 1.67 (1.10,2.53)] and experiencing alcohol related harms, [OR 1.65 (1.10,2.48)]. Conclusion: There is a need to involve both mothers and fathers and to equally target female and male children in programs to reduce the harmful consequences of parental supply of alcohol to their children.]]> Fri 24 Mar 2023 13:23:51 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:30953 Fri 03 Dec 2021 10:35:52 AEDT ]]>