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Addiction plays a key role in continued tobacco use. The study assessed association of perceived personal addiction and the perceived addictiveness of different forms of tobacco with type of tobacco product used, demographic characteristics and socio-cultural factors.A cross-sectional survey of 607 adult tobacco users with age 18 years and above attending a general medicine out-patient department was conducted. Participants were asked questions on perceived personal addiction to tobacco use and perception of addiction on tobacco products. Logistic regression was applied to investigate the association between demographic characteristics, type of tobacco, socio-cultural factors and addiction perceptions.The odds of perceived addiction (PA) were lower among smokeless tobacco (SLT) users [OR (95% CI): 0.57 (0.37, 0.89) P = 0.01]. An increase in the odds of PA was seen as age increased [OR (95% CI):1.02 (1.00, 1.03) P = 0.01] and participants with secondary education and above had higher odds of PA compared to participants with no formal education [OR (95% CI): 1.68 (1.09, 2.58) P = 0.02]. The odds of perceiving SLT products to be addictive was lower among SLT users [OR (95% CI): 0.48 (0.30, 0.75) P = 0.002)] compared to combustible tobacco users. The odds of perceiving SLT products to be addictive was lower [(OR (95% CI): 0.35 (0.18, 0.67) P = 0.002)] among females. Participants with secondary education and above had higher odds of perceiving combustible [OR (95% CI): 1.80 (1.17, 2.77) P = 0.008)] and SLT products [OR (95% CI): 1.98 (1.20, 3.30) P = 0.008)] to be addictive compared to no schooling.There is a need to raise awareness in India of the addictiveness of tobacco, particularly for users of SLT, younger people and those with less education.

Physical and mental health risks often commence during young adulthood. Vocational education institutions are an ideal setting for understanding how health-risks cluster together in students to develop holistic multiple health-risk interventions. This is the first study to examine clustering of tobacco smoking, fruit intake, vegetable intake, alcohol consumption, physical inactivity, overweight/obesity, depression, and anxiety in vocational education students and the socio-demographic characteristics associated with cluster membership. A cross-sectional survey with vocational education students (n = 1134, mean age = 24.3 years) in New South Wales, Australia. Latent class analysis identified clusters and latent class regression examined characteristics associated with clusters. Four clusters were identified. All clusters had moderate inadequate fruit intake and moderate overweight/obesity. Cluster 1 (13% of sample) had “high anxiety, high inadequate vegetable intake, low tobacco, and low alcohol use.” Cluster 2 (16% of sample) had “high tobacco smoking, high alcohol use, high anxiety, high depression, and high inadequate vegetable intake.” Cluster 3 (52% of sample) had “high risky alcohol use, high inadequate vegetable intake, low depression, low anxiety, low tobacco smoking, and low physical inactivity.” Cluster 4 (19% of sample) was a “lower risk cluster with high inadequate vegetable intake.” Compared to cluster 4, 16–25-year-olds and those experiencing financial stress were more likely to belong to clusters 1, 2, and 3. Interventions for vocational education students should address fruit and vegetable intake and overweight/obesity and recognize that tobacco use and risky alcohol use sometimes occurs in the context of mental health issues.

BACKGROUND: A number of school‐based policies or practices have been found to be effective in improving child diet and physical activity, and preventing excessive weight gain, tobacco or harmful alcohol use. Schools, however, frequently fail to implement such evidence‐based interventions. OBJECTIVES: The primary aims of the review are to examine the effectiveness of strategies aiming to improve the implementation of school‐based policies, programs or practices to address child diet, physical activity, obesity, tobacco or alcohol use. Secondary objectives of the review are to: Examine the effectiveness of implementation strategies on health behaviour (e.g. fruit and vegetable consumption) and anthropometric outcomes (e.g. BMI, weight); describe the impact of such strategies on the knowledge, skills or attitudes of school staff involved in implementing health‐promoting policies, programs or practices; describe the cost or cost‐effectiveness of such strategies; and describe any unintended adverse effects of strategies on schools, school staff or children. SEARCH METHODS: All electronic databases were searched on 16 July 2017 for studies published up to 31 August 2016. We searched the following electronic databases: Cochrane Library including the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; MEDLINE In‐Process & Other Non‐Indexed Citations; Embase Classic and Embase; PsycINFO; Education Resource Information Center (ERIC); Cumulative Index to Nursing and Allied Health Literature (CINAHL); Dissertations and Theses; and SCOPUS. We screened reference lists of all included trials for citations of other potentially relevant trials. We handsearched all publications between 2011 and 2016 in two specialty journals (Implementation Science and Journal of Translational Behavioral Medicine) and conducted searches of the WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/) as well as the US National Institutes of Health registry (https://clinicaltrials.gov). We consulted with experts in the field to identify other relevant research. SELECTION CRITERIA: 'Implementation' was defined as the use of strategies to adopt and integrate evidence‐based health interventions and to change practice patterns within specific settings. We included any trial (randomised or non‐randomised) conducted at any scale, with a parallel control group that compared a strategy to implement policies or practices to address diet, physical activity, overweight or obesity, tobacco or alcohol use by school staff to 'no intervention', 'usual' practice or a different implementation strategy. DATA COLLECTION AND ANALYSIS: Citation screening, data extraction and assessment of risk of bias was performed by review authors in pairs. Disagreements between review authors were resolved via consensus, or if required, by a third author. Considerable trial heterogeneity precluded meta‐analysis. We narratively synthesised trial findings by describing the effect size of the primary outcome measure for policy or practice implementation (or the median of such measures where a single primary outcome was not stated). MAIN RESULTS: We included 27 trials, 18 of which were conducted in the USA. Nineteen studies employed randomised controlled trial (RCT) designs. Fifteen trials tested strategies to implement healthy eating policies, practice or programs; six trials tested strategies targeting physical activity policies or practices; and three trials targeted tobacco policies or practices. Three trials targeted a combination of risk factors. None of the included trials sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials examined multi‐strategic implementation strategies and no two trials examined the same combinations of implementation strategies. The most common implementation strategies included educational materials, educational outreach and educational meetings. For all outcomes, the overall quality of evidence was very low and the risk of bias was high for the majority of trials for detection and performance bias. Among 13 trials reporting dichotomous implementation outcomes—the proportion of schools or school staff (e.g. classes) implementing a targeted policy or practice—the median unadjusted (improvement) effect sizes ranged from 8.5% to 66.6%. Of seven trials reporting the percentage of a practice, program or policy that had been implemented, the median unadjusted effect (improvement), relative to the control ranged from ‐8% to 43%. The effect, relative to control, reported in two trials assessing the impact of implementation strategies on the time per week teachers spent delivering targeted policies or practices ranged from 26.6 to 54.9 minutes per week. Among trials reporting other continuous implementation outcomes, findings were mixed. Four trials were conducted of strategies that sought to achieve implementation 'at scale', that is, across samples of at least 50 schools, of which improvements in implementation were reported in three trials. The impact of interventions on student health behaviour or weight status were mixed. Three of the eight trials with physical activity outcomes reported no significant improvements. Two trials reported reductions in tobacco use among intervention relative to control. Seven of nine trials reported no between‐group differences on student overweight, obesity or adiposity. Positive improvements in child dietary intake were generally reported among trials reporting these outcomes. Three trials assessed the impact of implementation strategies on the attitudes of school staff and found mixed effects. Two trials specified in the study methods an assessment of potential unintended adverse effects, of which, they reported none. One trial reported implementation support did not significantly increase school revenue or expenses and another, conducted a formal economic evaluation, reporting the intervention to be cost‐effective. Trial heterogeneity, and the lack of consistent terminology describing implementation strategies, were important limitations of the review. AUTHORS' CONCLUSIONS: Given the very low quality of the available evidence, it is uncertain whether the strategies tested improve implementation of the targeted school‐based policies or practices, student health behaviours, or the knowledge or attitudes of school staff. It is also uncertain if strategies to improve implementation are cost‐effective or if they result in unintended adverse consequences. Further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.

Addiction to tobacco is one of the main drivers of continued tobacco use. This study explored whether perceived addiction, type of tobacco and demographic characteristics were associated with past quit attempts (PQA), intention and self-efficacy to quit among combustible tobacco (CT) or smokeless tobacco (SLT) users in India.A cross-sectional survey was conducted among adult tobacco users (N = 607) attending an out-patient department in Mumbai. Logistic regression analysis was used to investigate the association between demographic characteristics, type of tobacco, addiction perceptions and cessation behaviours.Being 'a little addicted' (adjusted odds ratio, AOR [95% confidence interval, CI] 2.75 [1.83, 4.11], P 0.0001) or 'quite addicted' (AOR [95% CI] 2.93 [1.53, 5.62], P 0.0012) was associated with lower odds of making a PQA compared to 'not addicted at all'. Being a SLT user (AOR [95% CI] 0.64 [0.41, 0.99], P = 0.047) and female (AOR [95% CI] 0.46 [0.26, 0.81], P = 0.0068) was associated with lower odds of making a PQA. There was a significant decrease in the odds of intention to quit as age increased by 1 year (AOR [95% CI] 0.98 [0.97, 0.99], P = 0.0018). Being identified as 'a little addicted' (AOR [95% CI] 0.28 [0.14, 0.55], P = 0.0003), 'quite addicted' (AOR [95% CI] 0.16 [0.07, 0.39], P 0.0001) or 'very addicted' (AOR [95% CI] 0.09 [0.04, 0.19], P 0.0001) was associated with lower odds of self-efficacy to quit compared to 'not addicted at all'.Lack of awareness about addiction may inhibit cessation, particularly among less educated and female users of SLT and CT products.

AIM Aims were to test the effectiveness of an organizational change intervention integrating smoking cessation treatment into usual alcohol and other drug (AOD) treatment, compared with usual care, on (1) 7-day point prevalence abstinence (PPA) at 8 weeks follow-up; (2) prolonged abstinence; (3) cigarettes smoked per day; (4) number of quit attempts; and (5) offer and use of nicotine replacement therapy (NRT). All outcomes were assessed at 8 weeks and 6.5 months follow-up. DESIGN Cluster-randomized controlled trial, with AOD service as unit of randomization, conducted January 2015-March 2016. SETTING Thirty-two eligible services (provided face-to-face client sessions to ≥ 50 clients/year) in Australia were randomized to control (usual care; n = 15) or intervention (n = 17) groups by an independent blinded biostatistician. PARTICIPANTS Eligible participants (≥ 16 years, current smoker) completed surveys at the service at baseline (n = 896) and telephone follow-up surveys (conducted by blinded assessors) at 8 weeks (n = 471; 53%) and 6.5 months (n = 427; 48%). INTERVENTION Intervention services received an intervention to establish routine screening, assessment and delivery of smoking cessation care. MEASUREMENTS Primary outcome was biochemically verified 7-day PPA at 8-week follow-up. Secondary outcomes included verified and self-reported prolonged abstinence, self-reported 7-day PPA, cigarettes/day, quit attempts and offer and use of NRT. Intention-to-treat analyses were performed, assuming missing participants were not abstinent. FINDINGS At 8 weeks, the findings in verified 7-day PPA between groups [2.6 versus 1.8%, odds ratio (OR) = 1.72, 95% confidence interval (CI) = 0.5-5.7, P = 0.373] were inconclusive as to whether a difference was present. Significantly lower mean cigarettes/day were reported in the intervention group compared to the usual care group at 8 weeks [incidence rate ratio (IRR) = 0.88, 95% CI = 0.8-0.95, P = 0.001] but were similar at 6.5 months (IRR = 0.96, 95% CI = 0.9-1.02, P = 0.240) follow-up. At both follow-ups the intervention group reported higher rates of NRT use. CONCLUSIONS Integrating smoking cessation treatment into addiction services did not significantly improve short-term abstinence from smoking.

Background Smoking tobacco, poor nutrition, risky alcohol use, and physical inactivity (SNAP) behaviors tend to cluster together. Health benefits may be maximized if interventions targeted multiple health risk behaviors together rather than addressing single behaviors. The internet has wide reach and is a sustainable mode for delivery of interventions for multiple health behaviors. However, no systematic reviews have examined the long-term effectiveness of internet-based interventions on any combination of or all SNAP behaviors in adults aged 18 years or older. Objective This systematic review examined, among adults (aged ≥18 years), the effectiveness of internet-based interventions on SNAP behaviors collectively in the long term compared with a control condition. Methods The electronic databases Medline, PsycINFO, Embase, CINAHL, and Scopus were searched to retrieve studies describing the effectiveness of internet-based interventions on ≥2 SNAP behaviors published by November 18, 2019. The reference lists of retrieved articles were also checked to identify eligible publications. The inclusion criteria were randomized controlled trials or cluster randomized controlled trials with adults examining an internet-based intervention measuring the effect on ≥2 SNAP behaviors at least 6 months postrecruitment and published in English in a peer-reviewed journal. Two reviewers independently extracted data from included studies and assessed methodological quality using the Quality Assessment Tool for Quantitative Studies. A robust variance estimation meta-analysis was performed to examine the long-term effectiveness of internet-based interventions on all 4 SNAP risk behavior outcomes. All SNAP outcomes were coded so they were in the same direction, with higher scores equating to worse health risk behaviors. Results The inclusion criteria were met by 11 studies: 7 studies measured the effect of an internet-based intervention on nutrition and physical activity; 1 study measured the effect on smoking, nutrition, and physical activity; and 3 studies measured the effect on all SNAP behaviors. Compared with the control group, internet-based interventions achieved an overall significant improvement across all SNAP behaviors in the long term (standardized mean difference –0.12 [improvement as higher scores = worse health risk outcomes], 95% CI –0.19 to –0.05; I2=1.5%, P=.01). The global methodological quality rating was “moderate” for 1 study, while the remaining 10 studies were rated as “weak.” Conclusions Internet-based interventions were found to produce an overall significant improvement across all SNAP behaviors collectively in the long term. Internet-based interventions targeting multiple SNAP behaviors have the potential to maximize long-term improvements to preventive health outcomes.

Purpose: Individuals diagnosed with a high-grade hematological malignancy are at high risk for psychosocial distress. This study aimed to examine the effectiveness of a web-based information tool a...

Uptake of online and telephone services targeting health behaviours is low among vocational education students and barriers and facilitators are unknown. This study aimed to explore barriers and facilitators to uptake of online and telephone services for smoking, nutrition, alcohol, and physical activity (SNAP) risk behaviours via semi-structured individual telephone interviews with fifteen vocational education students. Two authors independently completed thematic analysis, classified themes according to the COM-B (Capability, Opportunity, Motivation, Behaviour) framework, and discussed disagreements until consensus was reached. Facilitators to uptake of online (e.g., desire to learn something new, cost-free, accessible) and telephone services (e.g., prefer to talk to provider, complements online support) primarily related to capability and opportunity. For telephone services, difficulty understanding accent/language was a capability-related barrier. Opportunity-related barriers for online and telephone services were preference for face-to-face interaction and lack of time, while preference for apps/online programs was a barrier for telephone services. For online and telephone services, not wanting to change SNAP behaviours was a motivation-related barrier and being able to change SNAP risk behaviours themselves was a motivation-related barrier for online services. Barriers and facilitators to online and telephone services are relevant for designing interventions vocational education students are more likely to use.

To determine diabetes patient's adherence to five self-care behaviours (diet, exercise; medication, self-monitoring of blood glucose [SMBG] and foot care) in low- and middle-income countries.Systematic review.We searched MEDLINE, CINAHL, PUBMED, SCOPUS, PsycINFO, EMBASE, Cochrane library and EMCARE for the period January 1990 - June 2017.Title, abstract and full text screening were done according to eligibility criteria. A narrative synthesis of the literature was conducted.A total of 7,109 studies were identified of which 27 met the review eligibility criteria and were included. All the studies used self-report of adherence to diabetes self-care. Studies reported adherence rates in two major forms: (a) mean number of days participants performed a recommended dietary behaviour/activity during the past week; and (b) proportions of participants adhering to a recommended self-care behaviour. Mean number of days per week participants adhered to a self-care behaviour ranged from 2.34.6 days per week for diet, 5.5-6.8 days per week for medication, 1.8-5.7 days per week for exercise, 0.2-2.2 days per week for SMBG and 2.2-4.3 days per week for foot care. Adherence rates ranged from 29.9%-91.7% for diet, 26.0%-97.0% for medication taking, 26.7%-69.0% for exercise, 13.0%-79.9% for self-monitoring of blood glucose and 17.0%-77.4% for foot care.Although most diabetes patients do not adhere to recommended self-care behaviours, adherence rates vary widely and were found to be high in some instances.Health services in low- and middle-income countries should monitor adherence to diabetes self-care behaviours rather than assume adherence and resources should be invested in improving adherence to the self-care behaviours. Large-scale accurate monitoring of adherence to diabetes self-care behaviour is needed and consideration should be given to choice of measurement tool for such exercise.目的: 在于确定中低收入国家的糖尿病患者是否坚持五种自我护理行为(节食、锻炼;药物治疗、 自我血糖监测(简称为“SMBG”)和足部护理)。 设计: 系统综述。 资料来源: 我们在1990年1月至2017年6月期间搜索了MEDLINE、CINAHL、PUBMED、SCOPUS、PsycINFO、EMBASE、Cochrane Library和EMCARE。 综述方法: 根据合格标准来筛选标题、摘要和全文。对文献进行了叙述性综合。 结果: 共确定了7109项研究,其中27项研究符合综述合格标准并得以纳入。所有研究都使用了坚持糖尿病自我护理的自我报告。研究报告了两种主要形式的坚持率:(a) 研究对象在过去一周内采取推荐节食行为/活动的平均天数;(b) 坚持自我护理推荐行为的研究对象比例。每周坚持自我护理行为的平均天数从每周节食2.3-4.6天、每周服药5.5-6.8天、每周锻炼1.8-5.7天、每周自我血糖监测0.2-2.2天和每周足部护理2.2-4.3天不等。坚持率从饮食29.9%-91.7%,服药26.0%-97.0%,锻炼26.7%-69.0%,自我血糖监测13.0%-79.9%和足部护理17.0%-77.4%不等。 结论: 虽然大多数糖尿病患者不坚持推荐的自我护理行为,但是坚持率的差异还是很大,甚至在某些情况下还很高。 影响: 中低收入国家的卫生服务部门应监控糖尿病自我护理行为的坚持情况,而不是假设在坚持中,并应投入众多资源来提高对自我护理行为的坚持情况。需要对糖尿病自我护理行为的坚持情况进行大规模精确监测,并且应考虑为此类锻炼所选的评估工具。.

Continued smoking after a cancer diagnosis is associated with poor treatment outcomes and reduced life expectancy. We aimed to identify the stability of smoking status after diagnosis including quit attempts and quit intentions. Participants with a first primary cancer diagnosis were recruited via two state-based registries in Australia. Questionnaires were mailed at approximately 6 months (T1), 1 year (T2), 2 years (T3), and 3.5 years (T4) post-diagnosis. Smoking status and quitting intentions were assessed at each time point. A cohort of 1444 people was recruited. People who indicated that they were more than 9 months post-diagnosis are excluded from analysis, leaving 1407 eligible study participants. Sixty-six (37%) of the 178 self-reported smokers at diagnosis had quit in the 6-month post-diagnosis (T1), the remaining 112 (63%) reported being a current smoker. Of the smokers at T1, 40% intended to quit: with 8% having quit smoking by T2; 11% quit by T3; 12% quit by T4. Of those who reported at T1 that they intended to quit in the next 6 months, 10% or fewer reported having quit at any subsequent time point. Quitting attempts decreased in frequency over time post-diagnosis. Less than 15% of respondents who had quit at or shortly before diagnosis reported relapse to smoking at each time point. The majority of smokers diagnosed with cancer continue to smoke beyond diagnosis, even in the context of an intention to quit and attempts to do so. Cancer survivors who smoke remain motivated to quit well beyond the initial diagnosis. There are clear positive clinical effects of smoking cessation for those who have undergone treatment for cancer, both for short-term treatment outcomes, and for long-term survivorship. Given the substantial rates of continued smoking among those who report smoking at diagnosis and their continued attempts to quit during survivorship, there is a need for improved cessation support initiatives for people diagnosed with cancer. These initiatives need to continue to be offered to smokers long after the initial diagnosis and treatment.

To our knowledge, no systematic reviews have examined the effectiveness of virtual reality (VR) interventions across all smoking, nutrition, alcohol, physical activity, and/or obesity (SNAPO) risk factors. This systematic review assessed the effectiveness of VR interventions on reducing SNAPO risks compared to control groups or other interventions. MEDLINE, EMBASE, Scopus, PsycINFO, and CENTRAL were searched to identify eligible studies published to 7 October 2021. Two reviewers independently completed screening, data extraction and quality assessment. Twenty-six studies were included, five on smoking, twelve on physical activity (PA), six on obesity, one on PA and obesity, one on obesity and nutrition, and one on obesity, nutrition and PA. VR was effective for smoking cessation in three studies and for smoking reduction in four studies. Seven studies had significantly higher PA in the VR group, and one study found significantly higher PA in a comparator group. Two studies showed VR was more effective at reducing BMI or weight than comparators. Three multiple health risks studies showed mixed results. The remaining studies found no significant difference between VR and control/comparators. VR appears promising for the treatment of smoking, nutrition, PA, and obesity risks; however, further randomised trials are needed.

Rural and remote residents are more likely to smoke tobacco than those in major cities. However, they may experience unique systemic, provider, and individual barriers to accessing smoking cessation treatments, including distance and limited resources. Understanding the effectiveness of smoking cessation interventions in this population is important due to higher smoking-related disease burden and death compared to those in major cities.Medline, EMBASE, Scopus, PsychINFO, and Cochrane Library were searched until 19-02/2021. Inclusion criteria were randomised controlled trials (RCTs), cluster RCTs, randomised trials, or cluster randomised trials investigating behavioural interventions and pharmacotherapies for smoking cessation in rural and remote populations compared with a control or another smoking cessation treatment; and published in English. Given there is no internationally-standardised rurality index, definitions of 'rural' and 'remote' used by authors of studies were applied to reflect their country. Exclusion criteria were studies of non-combustible smoking cessation; and studies with urban participants in the sample. Two reviewers independently screened records for eligibility, extracted data from studies utilising a modified Cochrane Effective Practice and Organisation of Care Group form, and rated methodological quality using the Quality Assessment Tool for Quantitative Studies.Sixteen studies were included. Meta-analysis revealed a statistically significant treatment effect of individual face-to-face counselling on smoking cessation (RR 2.35, 95% CI 1.16-4.76, IDespite limited resources in rural and remote settings, individual face-to-face counselling for smoking cessation appears promising. Given the limited number of studies, further research about the effectiveness of smoking cessation interventions in rural and remote populations is warranted.

Objective:To describe strategies used to recruit and retain young adults in nutrition, physical activity and/or obesity intervention studies, and quantify the success and efficiency of these strategies.Design:A systematic review was conducted. The search included six electronic databases to identify randomised controlled trials (RCT) published up to 6 December 2019 that evaluated nutrition, physical activity and/or obesity interventions in young adults (17–35 years). Recruitment was considered successful if the pre-determined sample size goal was met. Retention was considered acceptable if ≥80 % retained for ≤6-month follow-up or ≥70 % for >6-month follow-up.Results:From 21 582 manuscripts identified, 107 RCT were included. Universities were the most common recruitment setting used in eighty-four studies (79 %). Less than half (46 %) of the studies provided sufficient information to evaluate whether individual recruitment strategies met sample size goals, with 77 % successfully achieving recruitment targets. Reporting for retention was slightly better with 69 % of studies providing sufficient information to determine whether individual retention strategies achieved adequate retention rates. Of these, 65 % had adequate retention.Conclusions:This review highlights poor reporting of recruitment and retention information across trials. Findings may not be applicable outside a university setting. Guidance on how to improve reporting practices to optimise recruitment and retention strategies within young adults could assist researchers in improving outcomes.

Introduction E-cigarettes containing nicotine may potentially assist cessation in a heavily nicotine-dependent population with high relapse and tobacco-related burden. This study aims to determine alcohol and other drug (AOD) health-care provider and client awareness, use and attitudes regarding harm reduction and safety of e-cigarettes. Methods The study was part of a larger cluster randomised controlled trial with 32 Australian AOD services. At a post-intervention survey conducted October 2016, health-care providers were asked whether they believed e-cigarettes could help smokers quit tobacco, whether they believe e-cigarettes are safer than tobacco smoking and whether they would recommend e-cigarettes to clients who are interested in quitting smoking. At the 6-month follow-up survey conducted January 2015-March 2016, AOD clients were asked about their e-cigarette knowledge, ever use, current use, reasons for use and place of purchase. Results One hundred and eighty health-care providers and 427 AOD clients responded. A minority of health-care providers agreed with the statements that e-cigarettes could help smokers quit tobacco (30%), while just under one-third (25%) agreed that e-cigarettes were safer than tobacco smoking. However, only 19% would recommend e-cigarettes. Most AOD clients (93%) reported awareness of e-cigarettes, 39% reported ever use; however, only 7% reported current use. Of those reporting ever use, 52% used a nicotine e-cigarette. The most common reasons for e-cigarette use were 'wanted to try' (72%) and 'help cut down smoking' (70%). Discussion and conclusions Both AOD health-care providers and clients are aware of e-cigarettes but are cautious in using and recommending their use.

Background: This systematic review described the association between electronic nicotine delivery systems and electronic non-nicotine delivery systems (ENDS/ENNDS) use among non-smoking children and adolescents aged

Background This systematic review described the association between electronic nicotine delivery systems and electronic non-nicotine delivery systems (ENDS/ENNDS) use among non-smoking children and adolescents aged Methods We searched five electronic databases and the grey literature up to end of September 2020. Prospective longitudinal studies that described the association between ENDS/ENNDS use, and subsequent tobacco use in those aged < 20 years who were non-smokers at baseline were included. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess risk of bias. Data were extracted by two reviewers and pooled using a random-effects meta-analysis. We generated unadjusted and adjusted risk ratios (ARRs) describing associations between ENDS/ENNDS and tobacco use. Findings A total of 36 publications met the eligibility criteria, of which 25 were included in the systematic review (23 in the meta-analysis) after exclusion of overlapping studies. Sixteen studies had high to moderate risk of bias. Ever users of ENDS/ENNDS had over three times the risk of ever cigarette use (ARR 3·01 (95% CI: 2·37, 3·82; p2: 82·3%), and current cigarette use had over two times the risk (ARR 2·56 (95% CI: 1·61, 4·07; p2: 77·3%) at follow up. Among current ENDS/ENNDS users, there was a significant association with ever (ARR 2·63 (95% CI: 1·94, 3·57; p2: 21·2%)), but not current cigarette use (ARR 1·88 (95% CI: 0·34, 10·30; p = 0·47, I2: 0%)) at follow up. For other tobacco use, ARR ranged between 1·55 (95% CI 1·07, 2·23) and 8·32 (95% CI: 1·20, 57·04) for waterpipe and pipes, respectively. Additionally, two studies examined the use of ENNDS (non-nicotine devices) and found a pooled adjusted RR of 2·56 (95% CI: 0·47, 13·94, p = 0.035). Conclusion There is an urgent need for policies that regulate the availability, accessibility, and marketing of ENDS/ENNDS to children and adolescents. Governments should also consider adopting policies to prevent ENDS/ENNDS uptake and use in children and adolescents, up to and including a ban for this group.

Health risk factors such as tobacco smoking, inadequate fruit intake, inadequate vegetable intake, risky alcohol consumption, physical inactivity, obesity, anxiety and depression often commence during adolescence and young adulthood. Vocational education institutions enrol many students in these age groups making them an important setting for addressing multiple health risk factors. This systematic review examined (i) co-occurrence of health risk factors, (ii) clustering of health risk factors, and (iii) socio-demographic characteristics associated with co-occurrence and/or clusters of health risks among vocational education students. MEDLINE, PsycINFO, EMBASE, CINAHL and Scopus were searched to identify eligible studies published by 30 June 2020. Two reviewers independently extracted data and assessed methodological quality using the National Heart, Lung and Blood Institute Quality Assessment Tool. Five studies assessed co-occurrence and three studies clustering of health risks. Co-occurrence of health risk factors ranged from 29–98% and clustering of alcohol use and tobacco smoking was commonly reported. The findings were mixed about whether gender and age were associated with co-occurrence or clustering of health risks. There is limited evidence examining co-occurrence and clustering of health risk factors in vocational education students. Comprehensive assessment of how all these health risks co-occur or cluster in vocational education students is required.

Background Real-time video counselling for smoking cessation uses readily accessible software (e.g. Skype). This study aimed to assess the short-term effectiveness of real-time video counselling compared to telephone counselling or written materials (minimal intervention control) on smoking cessation and quit attempts among rural and remote residents. Methods An interim analysis of a three-arm, parallel group randomised trial with participants (n = 655) randomly allocated to; 1) real-time video counselling; 2) telephone counselling; or 3) written materials only (minimal intervention control). Participants were daily tobacco users aged 18 years or older residing in rural or remote areas of New South Wales, Australia. Video and telephone counselling conditions offered up to six counselling sessions while those in the minimal intervention control condition were mailed written materials. The study measured seven-day point prevalence abstinence, prolonged abstinence and quit attempts at 4-months post-baseline. Results Video counselling participants were significantly more likely than the minimal intervention control group to achieve 7-day point prevalence abstinence at 4-months (18.9% vs 8.9%, OR = 2.39 (1.34–4.26), p = 0.003), but the video (18.9%) and telephone (12.7%) counselling conditions did not differ significantly for 7-day point prevalence abstinence. The video counselling and minimal intervention control groups or video counselling and telephone counselling groups did not differ significantly for three-month prolonged abstinence or quit attempts. Conclusion Given video counselling may increase cessation rates at 4 months post-baseline, quitlines and other smoking cessation services may consider integrating video counselling into their routine practices as a further mode of cessation care delivery. Trial registration www.anzctr.org.au ACTRN12617000514303.

Background Some sub-types of haematological cancers are acute and require intensive treatment soon after diagnosis. Other sub-types are chronic, relapse over many years and require life-long cycles of monitoring interspersed with bouts of treatment. This often results in significant uncertainty about the future, high levels of depression and anxiety, and reduced quality of life. Little is known about how to improve care for haematological cancer survivors. This study explored qualitatively, in a sample of haematological cancer survivors, (i) their unmet needs experienced as a result of their disease and treatment; and (ii) strategies that may help address these needs. Methods Semi-structured interviews were conducted with 17 adult haematological cancer survivors. Data was analysed using qualitative content analysis. The Supportive Care Framework guided data collection and analysis. Results Participants had a mean age of 57 years (SD 13). Most were male (n = 10, 59%). Five themes emerged from the data: (i) changes in unmet needs across the care trajectory (with greatest unmet needs experienced soon after diagnosis, at discharge from hospital and with cancer recurrence); (ii) informational unmet needs requiring improved patient-centred communication; (iii) uncertainty about treatment and the future; (iv) coordinated, tailored and documented post-treatment care planning as a strategy for optimal care delivery; and (v) ongoing support services to meet psychosocial and practical unmet needs by involving peer support, less bureaucratic transport services and flexible work arrangements. Conclusions To our knowledge, this is the first qualitative investigation using the Supportive Care Framework to explore unmet needs of haematological cancer survivors. Our findings offer fresh insights into this important area of study. Written, take-home care plans which provide simple but tailored guidance on where to seek additional support may help decrease uncertainty and feelings of vulnerability post-treatment for adult haematological cancer survivors. Future research should further develop and test strategies aimed at addressing unmet needs of haematological cancer survivors identified in this study.

BACKGROUND Smoking tobacco, poor nutrition, risky alcohol use, and physical inactivity (SNAP) behaviors tend to cluster together. Health benefits may be maximized if interventions targeted multiple health risk behaviors together rather than addressing single behaviors. The internet has wide reach and is a sustainable mode for delivery of interventions for multiple health behaviors. However, no systematic reviews have examined the long-term effectiveness of internet-based interventions on any combination of or all SNAP behaviors in adults aged 18 years or older. OBJECTIVE This systematic review examined, among adults (aged ≥18 years), the effectiveness of internet-based interventions on SNAP behaviors collectively in the long term compared with a control condition. METHODS The electronic databases Medline, PsycINFO, Embase, CINAHL, and Scopus were searched to retrieve studies describing the effectiveness of internet-based interventions on ≥2 SNAP behaviors published by November 18, 2019. The reference lists of retrieved articles were also checked to identify eligible publications. The inclusion criteria were randomized controlled trials or cluster randomized controlled trials with adults examining an internet-based intervention measuring the effect on ≥2 SNAP behaviors at least 6 months postrecruitment and published in English in a peer-reviewed journal. Two reviewers independently extracted data from included studies and assessed methodological quality using the Quality Assessment Tool for Quantitative Studies. A robust variance estimation meta-analysis was performed to examine the long-term effectiveness of internet-based interventions on all 4 SNAP risk behavior outcomes. All SNAP outcomes were coded so they were in the same direction, with higher scores equating to worse health risk behaviors. RESULTS The inclusion criteria were met by 11 studies: 7 studies measured the effect of an internet-based intervention on nutrition and physical activity; 1 study measured the effect on smoking, nutrition, and physical activity; and 3 studies measured the effect on all SNAP behaviors. Compared with the control group, internet-based interventions achieved an overall significant improvement across all SNAP behaviors in the long term (standardized mean difference –0.12 [improvement as higher scores = worse health risk outcomes], 95% CI –0.19 to –0.05; I2=1.5%, P=.01). The global methodological quality rating was “moderate” for 1 study, while the remaining 10 studies were rated as “weak.” CONCLUSIONS Internet-based interventions were found to produce an overall significant improvement across all SNAP behaviors collectively in the long term. Internet-based interventions targeting multiple SNAP behaviors have the potential to maximize long-term improvements to preventive health outcomes.

peer-reviewed There is a need for effective interventions that improve the health and wellbeing of school and childcare staff. This review examined the efficacy of workplace interventions to improve the dietary, physical activity and/or sleep behaviours of school and childcare staff. A secondary aim of the review was to assess changes in staff physical/mental health, productivity, and students' health behaviours. Nine databases were searched for controlled trials including randomised and non-randomised controlled trials and quasi-experimental trials published in English up to October 2019. PRISMA guidelines informed screening and study selection procedures. Data were not suitable for quantitative pooling. Of 12,396 records screened, seven articles (based on six studies) were included. Most studies used multi-component interventions including educational resources, work-based wellness committees and planned group practice (e.g., walking groups). Multiple outcomes were assessed, findings were mixed and on average, there was moderate risk of bias. Between-group differences in dietary and physical activity behaviours (i.e., fruit/vegetable intake, leisure-time physical activity) favoured intervention groups, but were statistically non-significant for most outcomes. Some of the studies also showed differences favouring controls (i.e., nutrient intake, fatty food consumption). Additional robust studies testing the efficacy of workplace interventions to improve the health of educational staff are needed. PUBLISHED peer-reviewed

BACKGROUND A high proportion of vocational education students smoke tobacco, have inadequate nutrition (ie, low fruit and vegetable intake), drink alcohol at risky levels, or are physically inactive. The extent to which vocational education students will sign up for proactively offered online and telephone support services for multiple health risk behaviors is unknown. OBJECTIVE The aim of this study is to examine the uptake of proactively offered online and telephone support services for smoking, nutrition, alcohol consumption, and physical activity risk behaviors, individually and in combination, among vocational education students in the Technical and Further Education (TAFE) setting. The characteristics associated with the uptake of online or telephone services for smoking, nutrition, alcohol consumption, and physical activity risk behaviors were also examined. METHODS Vocational education students enrolled in a TAFE class in New South Wales, Australia, which ran for 6 months or more, were recruited to participate in a cluster randomized controlled trial from May 2018 to May 2019. In the intervention arm, participants who did not meet the Australian health guidelines for each of the smoking, nutrition, alcohol consumption, and physical activity risk behaviors were provided electronic feedback and proactively offered online and telephone support services. Uptake of support was measured by whether participants signed up for the online and telephone services they were offered. RESULTS Vocational education students (N=551; mean age 25.7 years, SD 11.1; 310/551, 56.3% male) were recruited into the intervention arm. Uptake of the proactive offer of either online or telephone services was 14.5% (59/406) for fruit and vegetables, 12.7% (29/228) for physical activity, 6.8% (13/191) for smoking, and 5.5% (18/327) for alcohol use. Uptake of any online or telephone service for at least two health behaviors was 5.8% (22/377). Participants who were employed (odds ratio [OR] 0.10, 95% CI 0.01-0.72) and reported not being anxious (OR 0.11, 95% CI 0.02-0.71) had smaller odds of signing up for online or telephone services for smoking, whereas participants who reported not being depressed had greater odds (OR 10.25, 95% CI 1.30-80.67). Participants who intended to change their physical activity in the next 30 days had greater odds (OR 4.01, 95% CI 1.33-12.07) of signing up for online or telephone services for physical activity. Employed participants had smaller odds (OR 0.18, 95% CI 0.06-0.56) of signing up for support services for at least two behaviors. CONCLUSIONS Although the uptake of proactively offered online and telephone support services is low, these rates appear to be higher than the self-initiated use of some of these services in the general population. Scaling up the proactive offer of online and telephone services may produce beneficial health outcomes. CLINICALTRIAL Australian New Zealand Clinical Trials Registry: ACTRN12618000723280; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375001.

BACKGROUND Real-time video communication technology allows virtual face-to-face interactions between the provider and the user, and can be used to modify risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. No systematic reviews have examined the effectiveness of individual real-time video counseling for addressing each of the risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. OBJECTIVE This systematic review aims to examine the effectiveness of individually delivered real-time video counseling on risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. METHODS The MEDLINE (Medical Literature Analysis and Retrieval System Online), EMBASE (Excerpta Medica Database), PsycINFO, Cochrane Register of Controlled Trials, and Scopus databases were searched for eligible studies published up to November 21, 2019. Eligible studies were randomized or cluster randomized trials that tested the effectiveness of individual real-time video communication interventions on smoking, nutrition, alcohol, physical activity, and obesity in any population or setting; the comparator was a no-intervention control group or any other mode of support (eg, telephone); and an English-language publication. RESULTS A total of 13 studies were eligible. Four studies targeted smoking, 3 alcohol, 3 physical activity, and 3 obesity. In 2 of the physical activity studies, real-time video counseling was found to significantly increase physical activity when compared with usual care at week 9 and after 5 years. Two obesity studies found a significant change in BMI between a video counseling and a documents group, with significantly greater weight loss in the video counseling group than the in-person as well as the control groups. One study found that those in the video counseling group were significantly more likely than those in the telephone counseling group to achieve smoking cessation. The remaining studies found no significant differences between video counseling and telephone counseling or face-to-face counseling for smoking cessation, video counseling and face-to-face treatment on alcohol consumption, video counseling and no counseling for physical activity, and video counseling and face-to-face treatment on BMI. The global methodological quality rating was moderate in 1 physical activity study, whereas 12 studies had a weak global rating. CONCLUSIONS Video counseling is potentially more effective than a control group or other modes of support in addressing physical inactivity and obesity and is not less effective in modifying smoking and alcohol consumption. Further research is required to determine the relative benefits of video counseling in terms of other policy and practice decision-making factors such as costs and feasibility.

Background Real-time video communication technology allows virtual face-to-face interactions between the provider and the user, and can be used to modify risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. No systematic reviews have examined the effectiveness of individual real-time video counseling for addressing each of the risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. Objective This systematic review aims to examine the effectiveness of individually delivered real-time video counseling on risk factors for smoking, nutrition, alcohol consumption, physical activity, and obesity. Methods The MEDLINE (Medical Literature Analysis and Retrieval System Online), EMBASE (Excerpta Medica Database), PsycINFO, Cochrane Register of Controlled Trials, and Scopus databases were searched for eligible studies published up to November 21, 2019. Eligible studies were randomized or cluster randomized trials that tested the effectiveness of individual real-time video communication interventions on smoking, nutrition, alcohol, physical activity, and obesity in any population or setting; the comparator was a no-intervention control group or any other mode of support (eg, telephone); and an English-language publication. Results A total of 13 studies were eligible. Four studies targeted smoking, 3 alcohol, 3 physical activity, and 3 obesity. In 2 of the physical activity studies, real-time video counseling was found to significantly increase physical activity when compared with usual care at week 9 and after 5 years. Two obesity studies found a significant change in BMI between a video counseling and a documents group, with significantly greater weight loss in the video counseling group than the in-person as well as the control groups. One study found that those in the video counseling group were significantly more likely than those in the telephone counseling group to achieve smoking cessation. The remaining studies found no significant differences between video counseling and telephone counseling or face-to-face counseling for smoking cessation, video counseling and face-to-face treatment on alcohol consumption, video counseling and no counseling for physical activity, and video counseling and face-to-face treatment on BMI. The global methodological quality rating was moderate in 1 physical activity study, whereas 12 studies had a weak global rating. Conclusions Video counseling is potentially more effective than a control group or other modes of support in addressing physical inactivity and obesity and is not less effective in modifying smoking and alcohol consumption. Further research is required to determine the relative benefits of video counseling in terms of other policy and practice decision-making factors such as costs and feasibility.

BACKGROUND: Despite the existence of effective interventions and best‐practice guideline recommendations for childcare services to implement evidence‐based policies, practices and programmes to promote child healthy eating, physical activity and prevent unhealthy weight gain, many services fail to do so. OBJECTIVES: The primary aim of the review was to examine the effectiveness of strategies aimed at improving the implementation of policies, practices or programmes by childcare services that promote child healthy eating, physical activity and/or obesity prevention. The secondary aims of the review were to: 1. Examine the cost or cost‐effectiveness of such strategies; 2. Examine any adverse effects of such strategies on childcare services, service staff or children; 3. Examine the effect of such strategies on child diet, physical activity or weight status. 4. Describe the acceptability, adoption, penetration, sustainability and appropriateness of such implementation strategies. SEARCH METHODS: We searched the following electronic databases on February 22 2019: Cochrane Central Register of Controlled trials (CENTRAL), MEDLINE, MEDLINE In Process, Embase, PsycINFO, ERIC, CINAHL and SCOPUS for relevant studies. We searched reference lists of included studies, handsearched two international implementation science journals, the World Health Organization International Clinical Trials Registry Platform (www.who.int/ictrp/) and ClinicalTrials.gov (www.clinicaltrials.gov). SELECTION CRITERIA: We included any study (randomised or nonrandomised) with a parallel control group that compared any strategy to improve the implementation of a healthy eating, physical activity or obesity prevention policy, practice or programme by staff of centre‐based childcare services to no intervention, 'usual' practice or an alternative strategy. Centre‐based childcare services included preschools, nurseries, long daycare services and kindergartens catering for children prior to compulsory schooling (typically up to the age of five to six years). DATA COLLECTION AND ANALYSIS: Two review authors independently screened study titles and abstracts, extracted study data and assessed risk of bias; we resolved discrepancies via consensus. We performed meta‐analysis using a random‐effects model where studies with suitable data and homogeneity were identified; otherwise, findings were described narratively. MAIN RESULTS: Twenty‐one studies, including 16 randomised and five nonrandomised, were included in the review. The studies sought to improve the implementation of policies, practices or programmes targeting healthy eating (six studies), physical activity (three studies) or both healthy eating and physical activity (12 studies). Studies were conducted in the United States (n = 12), Australia (n = 8) and Ireland (n = 1). Collectively, the 21 studies included a total of 1945 childcare services examining a range of implementation strategies including educational materials, educational meetings, audit and feedback, opinion leaders, small incentives or grants, educational outreach visits or academic detailing, reminders and tailored interventions. Most studies (n = 19) examined implementation strategies versus usual practice or minimal support control, and two compared alternative implementation strategies. For implementation outcomes, six studies (one RCT) were judged to be at high risk of bias overall. The review findings suggest that implementation strategies probably improve the implementation of policies, practices or programmes that promote child healthy eating, physical activity and/or obesity prevention in childcare services. Of the 19 studies that compared a strategy to usual practice or minimal support control, 11 studies (nine RCTs) used score‐based measures of implementation (e.g. childcare service nutrition environment score). Nine of these studies were included in pooled analysis, which found an improvement in implementation outcomes (SMD 0.49; 95% CI 0.19 to 0.79; participants = 495; moderate‐certainty evidence). Ten studies (seven RCTs) used dichotomous measures of implementation (e.g. proportion of childcare services implementing a policy or specific practice), with seven of these included in pooled analysis (OR 1.83; 95% CI 0.81 to 4.11; participants = 391; low‐certainty evidence). Findings suggest that such interventions probably lead to little or no difference in child physical activity (four RCTs; moderate‐certainty evidence) or weight status (three RCTs; moderate‐certainty evidence), and may lead to little or no difference in child diet (two RCTs; low‐certainty evidence). None of the studies reported the cost or cost‐effectiveness of the intervention. Three studies assessed the adverse effects of the intervention on childcare service staff, children and parents, with all studies suggesting they have little to no difference in adverse effects (e.g. child injury) between groups (three RCTs; low‐certainty evidence). Inconsistent quality of the evidence was identified across review outcomes and study designs, ranging from very low to moderate. The primary limitation of the review was the lack of conventional terminology in implementation science, which may have resulted in potentially relevant studies failing to be identified based on the search terms used. AUTHORS' CONCLUSIONS: Current research suggests that implementation strategies probably improve the implementation of policies, practices or programmes by childcare services, and may have little or no effect on measures of adverse effects. However such strategies appear to have little to no impact on measures of child diet, physical activity or weight status.

Among people who inject drugs (PWIDs) the prevalence of tobacco smoking exceeds 80%; making smoking cessation intervention a priority for this population. This study aims to examine staff and client perspectives from a supervised injecting facility regarding: i) whether an organizational change intervention increased rates of smoking cessation care delivery (pre- to post-intervention); and ii) acceptability of the intervention.A pre-and-post intervention pilot study in a supervised injecting facility was conducted in Sydney, Australia between July 2014-December 2015. The intervention employed an organizational change approach and included six components. Cross-sectional samples of staff (pre n = 27, post n = 22) and clients (pre n = 202, post n = 202) completed online surveys pre and post intervention.From pre to post-intervention staff reported smoking cessation practices significantly increased for the provision of verbal advice (30% to 82%; p 0.001), offer of free or subsidized nicotine replacement therapy (30% to 91%; p 0.001), referral to a general practitioner (19% to 64%; p = 0.001), and follow-up to check on quit smoking progress (18.5% to 64%; p = 0.001). Significantly more clients reported receiving all smoking cessation strategies post-intervention. Over 85% of staff agreed that it was acceptable to address client smoking as part of usual care and 95% of clients agreed that it was acceptable to be asked by staff about their tobacco smoking.Increasing the provision of smoking cessation care using an organizational change approach is both feasible for staff and acceptable to staff and clients of supervised injecting facilities.

Due to fewer cancer services in rural locations, rural survivors may have unique unmet needs compared to urban survivors. This study compared among rural and urban haematological cancer survivors the most common "high/very high" unmet supportive care needs and the unmet need scores for five domains (information, financial concerns, access and continuity of care, relationships and emotional health). Survivors' socio-demographics, rurality, cancer history and psychological factors associated with each unmet need domain were also explored. A total of 1511 haematological cancer survivors were recruited from five Australian state cancer registries and 1417 (1145 urban, 272 rural) allowed extraction of their residential postcode from registry records. A questionnaire that contained the Survivor Unmet Needs Survey was mailed to survivors. Dealing with feeling tired was the most common "high/very high" unmet need for rural (15.2%) and urban (15.5%) survivors. The emotional health domain had the highest mean unmet need score for rural and urban survivors. Rurality was associated with a decreased unmet emotional health domain score whereas travelling for more than 1 h to treatment was associated with increased unmet financial concerns and unmet access and continuity of care. Depression, anxiety and stress were associated with increased unmet need scores for all five domains. Unmet need domain scores generally did not differ by rurality. Travelling for more than 1 h to treatment was associated with increased unmet need scores on two domains. Telemedicine and increased financial assistance with travel and accommodation may help those travelling long distances for treatment.

Purpose This study aimed to compare support persons of haematological cancer survivors living in rural and urban areas in regard to the type, prevalence and factors associated with reporting unmet needs. Methods One thousand and four (792 urban and 193 rural) support persons of adults diagnosed with haematological cancer were recruited from five Australian state population-based cancer registries. Participants completed the Support Person Unmet Needs Survey (SPUNS) that assessed the level of unmet needs experienced over the past month across six domains. Results Overall, 66% of support persons had at least one ‘moderate, high or very high’ unmet need and 24% (n = 182) reported having multiple (i.e. 6 or more) ‘high/very high’ unmet needs in the past month. There were no significant differences between rural and urban support persons in the prevalence of multiple unmet needs or mean total unmet needs scores. There were however significant differences in the types of ‘high/very high’ unmet needs with support persons living in rural areas more likely to report finance-related unmet needs. Support persons who indicated they had difficulty paying bills had significantly higher odds of reporting multiple ‘high/very high’ unmet needs. Conclusions This is the first large, population-based study to compare the unmet needs of support persons of haematological cancer survivors living in rural and urban areas. Findings confirm previous evidence that supporting a person diagnosed with haematological cancer correlates with a high level of unmet needs and highlight the importance of developing systemic strategies for assisting support persons, especially in regard to making financial assistance and travel subsidies known and readily accessible to those living in rural areas.

Nicotine replacement therapy (NRT) use to support client smoking quit attempts is low and inconsistent at alcohol and other drug (AOD) treatment services. This study examined predictors of any NRT use and combination NRT use among AOD clients who were smokers.The study was part of a cluster-RCT of an organisational change intervention to introduce smoking cessation support as part of routine treatment in 32 AOD services. The intervention provided AOD services with free NRT and training. Service clients completed baseline (n = 896), 8-week (n = 471) and 6.5-month (n = 427) follow-up surveys. Mixed-model logistic regression examined whether baseline socio-demographic and smoking variables were associated with single and combination NRT use.At 8-weeks follow-up 57% (n = 269/471), and at 6.5-months 33% (n = 143/427) of participants reported using at least one form of NRT. Odds of NRT use at 8-weeks follow-up were greater among participants from treatment vs control group (OR = 3.69, 95%CI 1.8-7.4; p 0.001), higher vs lower nicotine dependence (OR = 1.74 95%CI 1.1-2.8; p = 0.024), or those motivated to quit (OR = 1.18 95%CI 1.0-1.4; p = 0.017). At 6.5-months, only the treatment arm remained significant. Combination NRT use at the 8-week follow-up was higher among those in treatment vs control group (OR = 2.75 95%CI 1.4-5.6; p = 0.005), or with higher vs lower nicotine dependence (OR = 2.12 95%CI 1.2-3.8; p = 0.014). No factors were associated with combination NRT use at 6.5-months.An organisational change intervention that supplied AOD services with NRT training and products to provide to clients during treatment significantly increases client single form and combination NRT use in the short term.