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      Smoking cessation support strategies for Aboriginal and Torres Strait Islander women of reproductive age: findings from the Which Way? study

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          Abstract

          Objective

          To identify smoking cessation support strategies that resonate with Aboriginal and Torres Strait Islander women.

          Design, setting and participants

          A national cross‐sectional survey of Aboriginal and Torres Strait Islander women aged 16–49 years who were smokers or ex‐smokers was conducted online during the period July to October 2020.

          Main outcome measures

          Preferred strategies, providers and locations for smoking cessation support.

          Results

          Among a total of 428 women who participated in the survey, group‐based support and holistic support were the most preferred strategies (preferred by 31.8% and 22.2% of women, respectively). Use of an Aboriginal health service was positively associated with choosing holistic support programs (prevalence ratio, 1.14 [95% CI, ≥ 1.00–1.28]). Women with high or moderate nicotine dependency were more likely to consider group‐based support to be helpful (prevalence ratio, 1.13 [95% CI, ≥ 1.00–1.27]) than those with low nicotine dependency. The most preferred providers for smoking cessation support were Aboriginal health workers (64.3%). Most women (73.4%) preferred face‐to‐face support at an Aboriginal health service, 38.8% preferred online support and 34.8% preferred phone support. A higher percentage of older women (≥ 35 years) preferred online or phone support (prevalence ratio, 1.70 [95% CI, 1.03–2.80]) compared with younger women (16–20 years). Use of an Aboriginal health service was positively associated with preference for an Aboriginal health worker (prevalence ratio, 1.35 [95% CI, 1.12–1.62]), and receiving face‐to‐face support at an Aboriginal health service (prevalence ratio, 1.28 [95% CI, 1.10–1.49]).

          Conclusion

          Aboriginal and Torres Strait Islander women prefer a range of cessation supports, with most women preferring group support and holistic approaches. Cessation supports that resonated with women varied by age, remoteness, nicotine dependence, and whether participants used an Aboriginal health service. Women want support to quit smoking from the Aboriginal health workers at their Aboriginal health service, at their health care providers and in their community. Comprehensive, multifaceted supports are required. Online support and phone‐based support are also preferred by some women, which helps to increase accessibility. Appropriate models of care — including sufficient funding for Aboriginal health services and Aboriginal health workers — are required and should be developed in partnership with communities to implement meaningful and culturally safe cessation care. This research demonstrates the need for and importance of multifaceted, comprehensive cessation support strategies.

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          Most cited references27

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          Mobile phone text messaging and app-based interventions for smoking cessation

          Mobile phone‐based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face‐to‐face support. In addition, mCessation can be automated and therefore provided affordably even in resource‐poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012. To determine whether mobile phone‐based smoking cessation interventions increase smoking cessation rates in people who smoke. For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018. Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone‐based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six‐month follow‐up. We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions . We performed both study eligibility checks and data extraction in duplicate. We performed meta‐analyses of the most stringent measures of abstinence at six months' follow‐up or longer, using a Mantel‐Haenszel random‐effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only. This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high‐income countries. There was moderate‐certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I 2 = 71%; 13 studies, 14,133 participants). There was also moderate‐certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I 2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high‐ and low‐intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I 2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I 2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower‐intensity smoking cessation support (either a lower‐intensity app or non‐app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I 2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings. There is moderate‐certainty evidence that automated text message‐based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate‐certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions. Can programmes delivered by mobile phones help people to stop smoking? Background Tobacco smoking is a leading cause of preventable death. Mobile phones can be used to support people who want to quit smoking. In this review, we have focused on programmes that use text messages or smartphone apps to do so. Search date We searched for published and unpublished studies in October 2018. Study characteristics We included 26 randomised controlled studies (involving over 33,000 people) that compared smoking quit rates in people who received text messages or smartphone apps to help them quit, with people who did not receive these programmes. We were interested in studies that measured smoking for six months or longer. Key results We found that text messaging programmes may be effective in supporting people to quit, increasing quit rates by 50% to 60%. This was the case when they were compared to minimal support or were tested as an addition to other forms of stop‐smoking support. There was not enough evidence to determine the effect of smartphone apps. Quality and completeness of the evidence Most of the studies were of high quality, although three studies had high drop out rates. We are moderately confident in the results of the text messaging interventions, but there were some issues with unexplained differences between study findings and for some comparisons there was not much data. We have low confidence in the results concerning smartphone apps, and more studies are needed in this field.
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              Internet-based interventions for smoking cessation

              Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking. To determine the effectiveness of Internet‐based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults. We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016. We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no‐intervention control, a different Internet intervention, or a non‐Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer. Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six‐month follow‐up or more, reporting short‐term outcomes narratively where longer‐term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). We grouped studies according to whether they (1) compared an Internet intervention with a non‐active control arm (e.g. printed self‐help guides), (2) compared an Internet intervention with an active control arm (e.g. face‐to‐face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age. We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants. There were only four RCTs conducted in adolescence or young adults that were eligible for meta‐analysis. Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non‐active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I 2 = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I 2 = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non‐active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I 2 = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I 2 = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I 2 = 0%); GRADE rating was moderate. Three studies compared tailored with non‐tailored Internet‐based messages, compared to non‐tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I 2 = 57%); GRADE rating was low. Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias. The evidence from trials in adults suggests that interactive and tailored Internet‐based interventions with or without additional behavioural support are moderately more effective than non‐active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown. Can Internet‐based interventions help people to stop smoking?  Background Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide. The Internet is an attractive platform to help people quit smoking because of low costs per user, and it has potential to reach smokers who might not access support because of limited health care availability or stigmatisation. Internet‐based interventions could also be used to target young people who smoke, or others who may not seek traditional methods of smoking treatment. Study Characteristics Up to August 2016, this review found 67 trials, including data from over 110,000 participants. Smoking cessation data after six months or more were available for 35,969 participants. We examined a range of Internet interventions, from a low intensity intervention, for example providing participants with a list of websites for smoking cessation, to intensive interventions consisting of Internet‐, email‐ and mobile phone‐delivered components. We classed interventions as tailored or interactive, or both. Tailored Internet interventions differed in the amount of tailoring, from multimedia components to personalised message sources. Some interventions also included Internet‐based counselling or support from nurses, peer coaches or tobacco treatment specialists. Recent trials incorporated online social networks, such as Facebook, Twitter, and other online forums. Key results In combined results, Internet programmes that were interactive and tailored to individual responses led to higher quit rates than usual care or written self‐help at six months or longer. Quality of evidence There were not many trials conducted in younger people. More trials are needed to determine the effect on Internet‐based methods to aid quitting in youth and young adults. Results should be interpreted with caution, as we rated some of the included studies at high risk of bias, and for most outcomes the quality of evidence was moderate or low.
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                Author and article information

                Contributors
                michelle.kennedy11@newcastle.edu.au
                Journal
                Med J Aust
                Med J Aust
                10.5694/(ISSN)1326-5377
                MJA2
                The Medical Journal of Australia
                John Wiley and Sons Inc. (Hoboken )
                0025-729X
                1326-5377
                17 July 2022
                July 2022
                : 217
                : Suppl 2 ( doiID: 10.5694/mja2.v217.S2 )
                : S19-S26
                Affiliations
                [ 1 ] University of Newcastle Newcastle NSW
                [ 2 ] Hunter Medical Research Institute University of Newcastle Newcastle NSW
                [ 3 ] National Centre for Epidemiology and Population Health Australian National University Canberra ACT
                [ 4 ] Centre for Health Equity University of Melbourne Melbourne VIC
                [ 5 ] Judith Lumley Centre La Trobe University Melbourne VIC
                [ 6 ] Yerin Eleanor Duncan Aboriginal Health Centre Wyong NSW
                [ 7 ] Waminda South Coast Women’s Health and Welfare Aboriginal Corporation Nowra NSW
                [ 8 ] Nunyara Aboriginal Health Clinics, Central Coast Local Health District Gosford NSW
                Author notes
                [*]

                Wiradjuri

                [†]

                Gomeroi

                [‡]

                Noongar

                [§]

                Palawa

                [¶]

                Jerrinja/Cullunghutti/Wandi Wandian

                [**]

                Gamilaroi

                [††]

                Modewa.

                Author information
                https://orcid.org/0000-0001-9691-068X
                https://orcid.org/0000-0002-2770-0686
                Article
                MJA251631 mja21.01184.R4
                10.5694/mja2.51631
                9544708
                35842910
                47d990a6-2b56-4be7-b09a-d14686d9f298
                © 2022 The Authors. Medical Journal of Australia published by John Wiley & Sons Australia, Ltd on behalf of AMPCo Pty Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 20 May 2022
                : 29 September 2021
                : 23 May 2022
                Page count
                Figures: 2, Tables: 1, Pages: 8, Words: 4785
                Funding
                Funded by: National Health and Medical Research Council , doi 10.13039/501100000925;
                Award ID: 1158670
                Award ID: 1161065
                Funded by: National Heart Foundation Aboriginal and Torres Strait Islander Award
                Award ID: 102458
                Categories
                Environment and Public Health
                Women's Health
                Indigenous Health
                Smoking cessation care for Aboriginal and Torres Strait Islander women
                Smoking cessation care for Aboriginal and Torres Strait Islander women
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                smoking,indigenous health
                smoking, indigenous health

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