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      Internet-based interventions for smoking cessation

      1 , 2 , 3 , 4 , 5 , 3 , 6
      Cochrane Tobacco Addiction Group
      Cochrane Database of Systematic Reviews
      Wiley

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          Abstract

          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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          Most cited references183

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          Individual behavioural counselling for smoking cessation.

          Individual counselling from a smoking cessation specialist may help smokers to make a successful attempt to stop smoking.
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            Group behaviour therapy programmes for smoking cessation

            Group therapy offers individuals the opportunity to learn behavioural techniques for smoking cessation, and to provide each other with mutual support. To determine the effect of group‐delivered behavioural interventions in achieving long‐term smoking cessation. We searched the Cochrane Tobacco Addiction Group Specialized Register, using the terms 'behavior therapy', 'cognitive therapy', 'psychotherapy' or 'group therapy', in May 2016. Randomized trials that compared group therapy with self‐help, individual counselling, another intervention or no intervention (including usual care or a waiting‐list control). We also considered trials that compared more than one group programme. We included those trials with a minimum of two group meetings, and follow‐up of smoking status at least six months after the start of the programme. We excluded trials in which group therapy was provided to both active therapy and placebo arms of trials of pharmacotherapies, unless they had a factorial design. Two review authors extracted data in duplicate on the participants, the interventions provided to the groups and the controls, including programme length, intensity and main components, the outcome measures, method of randomization, and completeness of follow‐up. The main outcome measure was abstinence from smoking after at least six months follow‐up in participants smoking at baseline. We used the most rigorous definition of abstinence in each trial, and biochemically‐validated rates where available. We analysed participants lost to follow‐up as continuing smokers. We expressed effects as a risk ratio for cessation. Where possible, we performed meta‐analysis using a fixed‐effect (Mantel‐Haenszel) model. We assessed the quality of evidence within each study and comparison, using the Cochrane 'Risk of bias' tool and GRADE criteria. Sixty‐six trials met our inclusion criteria for one or more of the comparisons in the review. Thirteen trials compared a group programme with a self‐help programme; there was an increase in cessation with the use of a group programme (N = 4395, risk ratio (RR) 1.88, 95% confidence interval (CI) 1.52 to 2.33, I 2 = 0%). We judged the GRADE quality of evidence to be moderate, downgraded due to there being few studies at low risk of bias. Fourteen trials compared a group programme with brief support from a health care provider. There was a small increase in cessation (N = 7286, RR 1.22, 95% CI 1.03 to 1.43, I 2 = 59%). We judged the GRADE quality of evidence to be low, downgraded due to inconsistency in addition to risk of bias. There was also low quality evidence of benefit of a group programme compared to no‐intervention controls, (9 trials, N = 1098, RR 2.60, 95% CI 1.80 to 3.76 I 2 = 55%). We did not detect evidence that group therapy was more effective than a similar intensity of individual counselling (6 trials, N = 980, RR 0.99, 95% CI 0.76 to 1.28, I 2 = 9%). Programmes which included components for increasing cognitive and behavioural skills were not shown to be more effective than same‐length or shorter programmes without these components. Group therapy is better for helping people stop smoking than self‐help, and other less intensive interventions. There is not enough evidence to evaluate whether groups are more effective, or cost‐effective, than intensive individual counselling. There is not enough evidence to support the use of particular psychological components in a programme beyond the support and skills training normally included. Background One approach to help people who are trying to quit smoking is to offer them group‐based support. Participants meet regularly, with a facilitator who is typically trained in smoking cessation counselling. Programme components are varied. A perceived strength of this approach is that participants provide each other with support and encouragement. The outcome of interest was not smoking at least six months from the start of the group programme. Study characteristics We identified 66 trials comparing group‐based programmes to other types of support, or comparing different types of group programme. The most recent search was in May 2016. Results & quality of evidence In 13 trials (4395 participants) people in the control conditions were provided with a self‐help programme. There was a benefit for the group‐based approach, with the chance of quitting increased by 50% to 130%. This means that if five in 100 people were able to quit for at least six months using self‐help materials, eight to 12 in 100 might be successful if offered group support. We judged the quality of this evidence as moderate, because studies did not report methods in enough detail to exclude possible bias. There was also evidence of a benefit of group support compared to advice and brief support from a healthcare professional (14 trials, 7286 participants), although the difference was smaller and more variable. We rated this as low‐quality evidence, because of the variability as well as possible risk of bias. There was also low‐quality evidence of a benefit in studies that did not provide the control group with any help to quit (9 trials, 1098 participants). Six trials (980 participants) compared group format with individual face‐to‐face counselling; there was no sign that one approach was more helpful than the other. The remaining studies compared different types of group programmes; typically they did not show differences, so it is not possible to show which components of group‐based programmes are most helpful.
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              Online support for smoking cessation: a systematic review of the literature.

              To examine the efficacy and acceptability of online, interactive interventions for smoking cessation and to identify treatment effect moderators and mediators. A systematic review and meta-analysis of the literature (1990-2008) was conducted, finding 11 relevant randomized controlled trials. Data were extracted and risk ratios and risk differences estimated with a random effects model. There was no evidence of publication bias. Included trials were of variable methodological quality. Web-based, tailored, interactive smoking cessation interventions were effective compared with untailored booklet or e-mail interventions [rate ratio (RR) 1.8; 95% confidence interval (CI) 1.4-2.3] increasing 6-month abstinence by 17% (95% CI 12-21%). No overall effect of interactive compared with static web-based interventions was detected but there was significant heterogeneity, with one study obtaining a clear effect and another failing to find one. Few moderating or mediating factors were evaluated in studies and those that were had little effect. Pooled results suggest that only interventions aimed at smokers motivated to quit were effective (RR 1.3, 95% CI 1.0-1.7). Fully automated interventions increased smoking cessation rates (RR 1.4, 95% CI 1.0-2.0), but evidence was less clear-cut for non-automated interventions. Overall, the web-based interventions evaluated were considered to be acceptable and user satisfaction was generally high. Interactive, web-based interventions for smoking cessation can be effective in aiding cessation. More research is needed to evaluate the relative efficacy of interactive web-based interventions compared with static websites.
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                Author and article information

                Journal
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                September 04 2017
                Affiliations
                [1 ]University of Bristol; MRC Integrative Epidemiology Unit, UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology; 12a Priory Road Bristol UK BS8 1TU
                [2 ]University of Bristol; Bristol Medical School; Bristol UK
                [3 ]Lee Kong Chian School of Medicine, Nanyang Technological University; Centre for Population Health Sciences (CePHaS); Singapore Singapore
                [4 ]Catholic University of Croatia; Zagreb Croatia
                [5 ]Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh; Allergy & Respiratory Research Group and Asthma UK Centre for Applied Research; Teviot Place Edinburgh UK EH8 9AG
                [6 ]University of Ljubljana; Department of Family Medicine, Faculty of Medicine; Ljubljana Slovenia
                Article
                10.1002/14651858.CD007078.pub5
                6703145
                28869775
                b97e5718-739c-4b26-b0ec-50cb43ae33eb
                © 2017
                History

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