Utilization of services in a randomized trial testing phone- and web-based interventions for smoking cessation

Investigating factors influencing overweight and obesity among adult households in Ethiopia: a multilevel ordered analysis of 2016 EDHS data

Background

In both high- and low-income countries, including Ethiopia, overweight and obesity have emerged as public health issues of the 21st century. Hence, obtaining conclusive evidence concerning the factors that influence adults' body mass index is important. Therefore, using representative data, our study sought to provide solid evidence on factors influencing overweight and obesity among adults in Ethiopia.

Methods

The 2016 Ethiopia Demographic and Health Survey (EDHS), a dataset composed of a nationally representative sample of the survey, served as the basis for the study. Both descriptive and analytic findings were produced using STATA version 14. The data collection were conducted from January to June 2016. A total sample of 39,749 adults, 18 years and older, were included. Predictors were assessed using multivariable ordinal logistic regression analysis, and the results were presented as an adjusted proportional ratio (POR) with a 95% confidence interval. Statistical significance was declared at a p-value of <0.05.

Results

Overall, the magnitude of overweight and obesity among adults in Ethiopia was 8.5% (95% CI: 8.2% to 8.7%) and 2.9% (95% CI: 2.7% to 3.1%), respectively. Predictor variables such as smoking (POR = 0.53, 95% CI: 0.42-0.67); being female (POR = 1.21, 95% CI: 1.13-1.30); being married (POR = 1.91, 95% CI: 1.26-2.90); having a secondary education (POR = 1.42, 95% CI: 2.23-1.64); having a diploma and above education (POR = 1.78, 95% CI: 1.44-2.21); having a poorer (POR = 1.22, 95% CI: 1.13-1.31), middle (POR = 1.30, 95% CI: 1.20-1.40), richer (POR = 1.35, 95% CI: 1.25-1.47), and richest (POR = 3.13, 95% CI: 2.79-3.51) wealth index rating; and having a rural residence (POR = 0.48, 95% CI: 0.43-0.54) were significantly associated with overweight and obesity.

Conclusions

Overall, 8.5% and 2.9% of Ethiopian adults were overweight and obese, respectively. Factors such as smoking, sex, marital status, educational status, wealth index, residence, and region were significantly associated with overweight and obesity among adult households. As a result, enhancing lifestyle modifications is enormous, and it is necessary to have more tangible evidence concerning the factors influencing body mass index utilizing more representative data from local and global.

Epidemiological Association of Current Smoking Status with Hypertension and Obesity among Adults Including the Elderly in Korea: Multivariate Analysis of a Nationwide Cross-Sectional Study Excluding Grades 2-3 Hypertension Cases

Smoking is a major global health issue that contributes to various chronic diseases, while hypertension and obesity are considered significant health concerns due to their associated complications, such as cardiovascular diseases and metabolic disorders. In this study, we investigated the associations between current smoking status, hypertension, and obesity among the Korean population, excluding individuals with high blood pressure (systolic blood pressure ≥ 160 mmHg or diastolic blood pressure ≥ 100 mmHg) and those taking antihypertensive medications. Data from the 2015 Korea National Fitness Assessment, encompassing 3457 individuals, were analyzed. Logistic regression analysis was used to examine the effects of current smoking and other variables on hypertension and obesity. The results showed that, among the population that excludes specific hypertension criteria, current smoking status was not significantly associated with hypertension or obesity. However, sex and body mass index were significantly associated with hypertension, and age, sex, and blood pressure were significantly associated with obesity. Future research should utilize larger sample sizes and longitudinal designs to confirm these findings and include a broader range of hypertensive participants to better control for potential confounding variables.

Investigation of the Association between Bilateral Selective Anterograde Cerebral Perfusion and Postoperative Ischemic Stroke in Obese Patients with Emergency Surgery for Acute Type A Aortic Dissection

Background and objectives: The relationship between cerebral perfusion and new postoperative ischemic stroke in obese patients is not well defined. The aim of this study was to investigate the association between selective bilateral anterograde cerebral perfusion and new postoperative ischemic stroke in obese patients with emergency surgery for acute type A aortic dissection. Materials and methods: A total of 292 patients with emergency surgery for acute type A aortic dissection were included in this study. Patients with hemorrhagic stroke or ischemic stroke with severe neurological dysfunction at admission that were not candidates for surgery; patients who died in the first 48 h after intensive care admission and patients with incomplete medical records were excluded. Results: The mean age was 59.42 ± 10.68 years and the mean Euroscore was 9.12 ± 1.63. Obesity was present in 76.4%, the incidence of new postoperative ischemic stroke was 27.5%, and the postoperative mortality rate was 26.7%. The mean cardiopulmonary bypass time was 206.81 ± 75.48 min, the aortic cross-clamp time was 118.2 ± 46.42 min, and 90% of cases required cerebral perfusion. The mean cerebral perfusion time was 30.8 ± 24.41 min. Obese patients had a higher frequency of in-hospital death (p = 0.009), smoking (p = 0.036), hypertension (p = 0.023), left common carotid artery dissection (p < 0.001), right common carotid artery dissection (p = 0.029), femoral artery cannulation (p = 0.026), aortic root replacement (p = 0.009), aortic valve replacement (p = 0.005) and early reintervention for bleeding (p = 0.004). Using logistic regression, selective bilateral anterograde cerebral perfusion over 40 min in obese patients was independently associated with new postoperative ischemic stroke (OR = 2.35; 95%CI = 1.36-4.86; p = 0.021). Conclusions: A patient-tailored strategy for cerebral perfusion should be considered in obese patients, considering the high atheromatous burden of the supra-aortic vessels in these patients and the potential risk of atheromatous embolization associated with this technique.

Who benefits from guided internet-based interventions? A systematic review of predictors and moderators of treatment outcome

To our knowledge, no systematic review has been conducted on predictors or moderators of treatment outcome across diagnoses in guided internet-based interventions (IBIs) for adults. To identify who benefits from this specific format and therein inform future research on improving patient-treatment fit, we aimed to aggregate results of relevant studies. 2100 articles, identified by searching the databases PsycInfo, Ovid Medline, and Pubmed and through snowballing, were screened in April/May 2021 and October 2022. Risk of bias and intra- and interrater reliability were assessed. Variables were grouped by predictor category, then synthesized using vote counting based on direction of effect. N = 60 articles were included in the review. Grouping resulted in 88 predictors/moderators, of which adherence, baseline symptoms, education, age, and gender were most frequently assessed. Better adherence, treatment credibility, and working alliance emerged as conclusive predictors/moderators for better outcome, whereas higher baseline scores predicted more reliable change but higher post-treatment symptoms. Results of all other predictors/moderators were inconclusive or lacked data. Our review highlights that it is currently difficult to predict, across diagnoses, who will benefit from guided IBIs. Further rigorous research is needed to identify predictors and moderators based on a sufficient number of studies. PROSPERO registration: CRD42021242305.

Nicotine receptor partial agonists for smoking cessation

Background

Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist). This is an update of a Cochrane Review first published in 2007.

Objectives

To assess the effectiveness of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation.

Search methods

We searched the Cochrane Tobacco Addiction Group's Specialised Register in April 2022 for trials, using relevant terms in the title or abstract, or as keywords. The register is compiled from searches of CENTRAL, MEDLINE, Embase, and PsycINFO. 

Selection criteria

We included randomised controlled trials that compared the treatment drug with placebo, another smoking cessation drug, e‐cigarettes, or no medication. We excluded trials that did not report a minimum follow‐up period of six months from baseline.

Data collection and analysis

We followed standard Cochrane methods. Our main outcome was abstinence from smoking at longest follow‐up using the most rigorous definition of abstinence, preferring biochemically validated rates where reported. We pooled risk ratios (RRs), using the Mantel‐Haenszel fixed‐effect model. We also reported the number of people reporting serious adverse events (SAEs).

Main results

We included 75 trials of 45,049 people; 45 were new for this update. We rated 22 at low risk of bias, 18 at high risk, and 35 at unclear risk.

We found moderate‐certainty evidence (limited by heterogeneity) that cytisine helps more people to quit smoking than placebo (RR 1.30, 95% confidence interval (CI) 1.15 to 1.47; I2 = 83%; 4 studies, 4623 participants), and no evidence of a difference in the number reporting SAEs (RR 1.04, 95% CI 0.78 to 1.37; I2 = 0%; 3 studies, 3781 participants; low‐certainty evidence). SAE evidence was limited by imprecision. We found no data on neuropsychiatric or cardiac SAEs.

We found high‐certainty evidence that varenicline helps more people to quit than placebo (RR 2.32, 95% CI 2.15 to 2.51; I2 = 60%, 41 studies, 17,395 participants), and moderate‐certainty evidence that people taking varenicline are more likely to report SAEs than those not taking it (RR 1.23, 95% CI 1.01 to 1.48; I2 = 0%; 26 studies, 14,356 participants). While point estimates suggested increased risk of cardiac SAEs (RR 1.20, 95% CI 0.79 to 1.84; I2 = 0%; 18 studies, 7151 participants; low‐certainty evidence), and decreased risk of neuropsychiatric SAEs (RR 0.89, 95% CI 0.61 to 1.29; I2 = 0%; 22 studies, 7846 participants; low‐certainty evidence), in both cases evidence was limited by imprecision, and confidence intervals were compatible with both benefit and harm.

Pooled results from studies that randomised people to receive cytisine or varenicline found no clear evidence of difference in quit rates (RR 1.00, 95% CI 0.79 to 1.26; I2 = 65%; 2 studies, 2131 participants; low‐certainty evidence) and reported SAEs (RR 0.67, 95% CI 0.44 to 1.03; I2 = 45%; 2 studies, 2017 participants; low‐certainty evidence). However, the evidence was limited by imprecision, and confidence intervals incorporated the potential for benefit from either cytisine or varenicline. We found no data on neuropsychiatric or cardiac SAEs.

We found high‐certainty evidence that varenicline helps more people to quit than bupropion (RR 1.36, 95% CI 1.25 to 1.49; I2 = 0%; 9 studies, 7560 participants), and no clear evidence of difference in rates of SAEs (RR 0.89, 95% CI 0.61 to 1.31; I2 = 0%; 5 studies, 5317 participants), neuropsychiatric SAEs (RR 1.05, 95% CI 0.16 to 7.04; I2 = 10%; 2 studies, 866 participants), or cardiac SAEs (RR 3.17, 95% CI 0.33 to 30.18; I2 = 0%; 2 studies, 866 participants). Evidence of harms was of low certainty, limited by imprecision.

We found high‐certainty evidence that varenicline helps more people to quit than a single form of nicotine replacement therapy (NRT) (RR 1.25, 95% CI 1.14 to 1.37; I2 = 28%; 11 studies, 7572 participants), and low‐certainty evidence, limited by imprecision, of fewer reported SAEs (RR 0.70, 95% CI 0.50 to 0.99; I2 = 24%; 6 studies, 6535 participants). We found no data on neuropsychiatric or cardiac SAEs.

We found no clear evidence of a difference in quit rates between varenicline and dual‐form NRT (RR 1.02, 95% CI 0.87 to 1.20; I2 = 0%; 5 studies, 2344 participants; low‐certainty evidence, downgraded because of imprecision). While pooled point estimates suggested increased risk of SAEs (RR 2.15, 95% CI 0.49 to 9.46; I2 = 0%; 4 studies, 1852 participants) and neuropsychiatric SAEs (RR 4.69, 95% CI 0.23 to 96.50; I2 not estimable as events only in 1 study; 2 studies, 764 participants), and reduced risk of cardiac SAEs (RR 0.32, 95% CI 0.01 to 7.88; I2 not estimable as events only in 1 study; 2 studies, 819 participants), in all three cases evidence was of low certainty and confidence intervals were very wide, encompassing both substantial harm and benefit.

Authors' conclusions

Cytisine and varenicline both help more people to quit smoking than placebo or no medication. Varenicline is more effective at helping people to quit smoking than bupropion, or a single form of NRT, and may be as or more effective than dual‐form NRT. People taking varenicline are probably more likely to experience SAEs than those not taking it, and while there may be increased risk of cardiac SAEs and decreased risk of neuropsychiatric SAEs, evidence was compatible with both benefit and harm. Cytisine may lead to fewer people reporting SAEs than varenicline. Based on studies that directly compared cytisine and varenicline, there may be no difference or a benefit from either medication for quitting smoking.

Future trials should test the effectiveness and safety of cytisine compared with varenicline and other pharmacotherapies, and should also test variations in dose and duration. There is limited benefit to be gained from more trials testing the effect of standard‐dose varenicline compared with placebo for smoking cessation. Further trials on varenicline should test variations in dose and duration, and compare varenicline with e‐cigarettes for smoking cessation.

Can medications like varenicline and cytisine (nicotine receptor partial agonists) help people to stop smoking and do they cause unwanted effects?

Key messages

· Varenicline can help people to stop smoking for at least 6 months. Evidence shows it works better than bupropion and using only one type of nicotine replacement therapy (e.g. only patches). Quit rates might be similar to using more than one type of nicotine replacement therapy at the same time (e.g. patches and gum together).

· Cytisine can help people to stop smoking for at least 6 months. It may work as well as varenicline, but future evidence may show that while it helps, it is not quite as helpful as varenicline.

· Future studies should test the effectiveness and safety of cytisine compared with varenicline and other stop‐smoking medications, and should also  investigate giving cytisine or varenicline at different doses and for different lengths of time.

What are 'nicotine receptor partial agonists'?

Smoking tobacco is extremely bad for people’s health. For people who smoke, quitting is the best thing they can do to improve their health. Many people find it difficult to quit smoking. Nicotine receptor partial agonists (NRPAs) are a type of medication used to help people to stop smoking. They help to reduce the withdrawal symptoms people experience when they stop smoking, like cravings and unpleasant mood changes. They also reduce the pleasure people usually experience when they smoke. The most widely‐available treatment in this drug type is varenicline. Cytisine is another, similar medication. They may cause unwanted effects such as feeling sick (nausea) and other stomach problems, difficulties sleeping, abnormal dreams, and headache. They may also lead to potentially serious unwanted effects, such as suicidal thoughts, heart problems and raised blood pressure.

What did we want to find out?

We wanted to find out if using NRPAs can help people to quit smoking, and if they cause unwanted effects. We wanted to know:

· how many people stopped smoking for at least 6 months; and

· how many people had unwanted effects.

What did we do?

We searched for studies that investigated NRPAs used to help people quit smoking. People in the studies had to be chosen at random to receive an NRPA, or another NRPA, placebo (medication like the NRPA but with no active ingredients) or no treatment. They had to be adult tobacco smokers who wanted to stop smoking.

What did we find?

We found 75 studies that compared NRPAs with:

· placebo or no medicine;

· nicotine replacement therapy, such as patches or gum;

· bupropion (another medicine to help people stop smoking);

· another NRPA;

· e‐cigarettes.

The USA hosted the most studies (28 studies). Other studies took place in a range of countries across the world, some in several countries.

Main results

People are more likely to stop smoking for at least six months using varenicline than using placebo (41 studies, 17,395 people), bupropion (9 studies, 7560 people), or just one type of nicotine replacement therapy, like patches alone (11 studies, 7572 people). They may be just as likely to quit as people using two or more kinds of nicotine replacement therapy, like patches and gum together (5 studies, 2344 people).

Cytisine probably helps more people to stop smoking than placebo (4 studies, 4623 people) and may be just as effective as varenicline (2 studies, 2131 people).

For every 100 people using varenicline to stop smoking, 21 to 25 might successfully stop, compared with only 18 of 100 people using bupropion, 18 of 100 people using a single form of nicotine‐replacement therapy, and 20 of 100 using two or more kinds of nicotine‐replacement therapy. For every 100 people using cytisine to stop smoking, 18 to 23 might successfully stop.

The most common unwanted effect of varenicline is nausea, but this is mostly at mild or moderate levels and usually clears over time. People taking varenicline likely have an increased chance of a more serious unwanted effect that could result in going to hospital, however these are still rare (2.7% to 4% of people on varenicline, compared with 2.7% of people without) and may include many that are unrelated to varenicline. People taking cytisine may also have a slightly increased chance of serious unwanted effects compared with people not taking it, but this may be less likely compared with varenicline.

What are the limitations of the evidence?

The evidence for some of our results is very reliable. We’re very confident that varenicline helps people to quit smoking better than many alternatives. We’re less sure of some other results because fewer or smaller studies provided evidence.

Several results suggest one treatment is better or less harmful than another, but the opposite could still be true.

How up to date is the evidence?

The evidence is up to date to 29 April 2022.

Nicotine receptor partial agonists for smoking cessation

BACKGROUND

Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist). This is an update of a Cochrane Review first published in 2007.

OBJECTIVES

To assess the effectiveness of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialised Register in April 2022 for trials, using relevant terms in the title or abstract, or as keywords. The register is compiled from searches of CENTRAL, MEDLINE, Embase, and PsycINFO.  SELECTION CRITERIA: We included randomised controlled trials that compared the treatment drug with placebo, another smoking cessation drug, e-cigarettes, or no medication. We excluded trials that did not report a minimum follow-up period of six months from baseline.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our main outcome was abstinence from smoking at longest follow-up using the most rigorous definition of abstinence, preferring biochemically validated rates where reported. We pooled risk ratios (RRs), using the Mantel-Haenszel fixed-effect model. We also reported the number of people reporting serious adverse events (SAEs).

MAIN RESULTS

We included 75 trials of 45,049 people; 45 were new for this update. We rated 22 at low risk of bias, 18 at high risk, and 35 at unclear risk. We found moderate-certainty evidence (limited by heterogeneity) that cytisine helps more people to quit smoking than placebo (RR 1.30, 95% confidence interval (CI) 1.15 to 1.47; I2 = 83%; 4 studies, 4623 participants), and no evidence of a difference in the number reporting SAEs (RR 1.04, 95% CI 0.78 to 1.37; I2 = 0%; 3 studies, 3781 participants; low-certainty evidence). SAE evidence was limited by imprecision. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than placebo (RR 2.32, 95% CI 2.15 to 2.51; I2 = 60%, 41 studies, 17,395 participants), and moderate-certainty evidence that people taking varenicline are more likely to report SAEs than those not taking it (RR 1.23, 95% CI 1.01 to 1.48; I2 = 0%; 26 studies, 14,356 participants). While point estimates suggested increased risk of cardiac SAEs (RR 1.20, 95% CI 0.79 to 1.84; I2 = 0%; 18 studies, 7151 participants; low-certainty evidence), and decreased risk of neuropsychiatric SAEs (RR 0.89, 95% CI 0.61 to 1.29; I2 = 0%; 22 studies, 7846 participants; low-certainty evidence), in both cases evidence was limited by imprecision, and confidence intervals were compatible with both benefit and harm. Pooled results from studies that randomised people to receive cytisine or varenicline showed that more people in the varenicline arm quit smoking (RR 0.83, 95% CI 0.66 to 1.05; I2 = 0%; 2 studies, 2131 participants; moderate-certainty evidence) and reported SAEs (RR 0.67, 95% CI 0.44 to 1.03; I2 = 45%; 2 studies, 2017 participants; low-certainty evidence). However, the evidence was limited by imprecision, and confidence intervals incorporated the potential for benefit from either cytisine or varenicline. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than bupropion (RR 1.36, 95% CI 1.25 to 1.49; I2 = 0%; 9 studies, 7560 participants), and no clear evidence of difference in rates of SAEs (RR 0.89, 95% CI 0.61 to 1.31; I2 = 0%; 5 studies, 5317 participants), neuropsychiatric SAEs (RR 1.05, 95% CI 0.16 to 7.04; I2 = 10%; 2 studies, 866 participants), or cardiac SAEs (RR 3.17, 95% CI 0.33 to 30.18; I2 = 0%; 2 studies, 866 participants). Evidence of harms was of low certainty, limited by imprecision. We found high-certainty evidence that varenicline helps more people to quit than a single form of nicotine replacement therapy (NRT) (RR 1.25, 95% CI 1.14 to 1.37; I2 = 28%; 11 studies, 7572 participants), and low-certainty evidence, limited by imprecision, of fewer reported SAEs (RR 0.70, 95% CI 0.50 to 0.99; I2 = 24%; 6 studies, 6535 participants). We found no data on neuropsychiatric or cardiac SAEs. We found no clear evidence of a difference in quit rates between varenicline and dual-form NRT (RR 1.02, 95% CI 0.87 to 1.20; I2 = 0%; 5 studies, 2344 participants; low-certainty evidence, downgraded because of imprecision). While pooled point estimates suggested increased risk of SAEs (RR 2.15, 95% CI 0.49 to 9.46; I2 = 0%; 4 studies, 1852 participants) and neuropsychiatric SAEs (RR 4.69, 95% CI 0.23 to 96.50; I2 not estimable as events only in 1 study; 2 studies, 764 participants), and reduced risk of cardiac SAEs (RR 0.32, 95% CI 0.01 to 7.88; I2 not estimable as events only in 1 study; 2 studies, 819 participants), in all three cases evidence was of low certainty and confidence intervals were very wide, encompassing both substantial harm and benefit.

AUTHORS' CONCLUSIONS

Cytisine and varenicline both help more people to quit smoking than placebo or no medication. Varenicline is more effective at helping people to quit smoking than bupropion, or a single form of NRT, and may be as or more effective than dual-form NRT. People taking varenicline are probably more likely to experience SAEs than those not taking it, and while there may be increased risk of cardiac SAEs and decreased risk of neuropsychiatric SAEs, evidence was compatible with both benefit and harm. Cytisine may lead to fewer people reporting SAEs than varenicline. Based on studies that directly compared cytisine and varenicline, there may be a benefit from varenicline for quitting smoking, however further evidence could strengthen this finding or demonstrate a benefit from cytisine. Future trials should test the effectiveness and safety of cytisine compared with varenicline and other pharmacotherapies, and should also test variations in dose and duration. There is limited benefit to be gained from more trials testing the effect of standard-dose varenicline compared with placebo for smoking cessation. Further trials on varenicline should test variations in dose and duration, and compare varenicline with e-cigarettes for smoking cessation.

Pattern of cigarette smoking: intensity, cessation, and age of beginning: evidence from a cohort study in West of Iran

BACKGROUND

Smoking is a social epidemic and one of the main risk factors for premature deaths and disabilities worldwide. In the present study, we investigated the Pattern of Cigarette Smoking: intensity, cessation, and age of the beginning.

METHODS

Data collected from the recruitment phase of Ravansar (a Kurd region in western Iran) Non-Communicable Disease (RaNCD) cohort study was analyzed by using Chi-square test, univariate and multivariate logistic regressions, Poisson regression, and linear regression.

RESULTS

Totally 10,035 individuals (47.42% males) participated in the study. Mean age was lower for males (47.45 yr) than for females (48.36 yr). Prevalence of smoking was 20% (36.4% of males and 5.23% of females). Compared to female participants, males showed a 7-fold higher prevalence of smoking and started smoking about 4 years earlier. Being married, having a lower BMI, living in rural areas, and being exposed to secondhand smoke (SHS) were predictors of higher smoking prevalence rates. Furthermore, current exposure to SHS, higher smoking intensity, later smoking initiation, male gender, younger age, lower education, and lower BMI were related to lower likelihood of stopping smoking. Heavy smokers began to smoke about 4 years earlier than casual smokers did. Finally, being divorced/ widow/ widower/ single and childhood exposure to SHS were found to increase the likelihood of becoming a smoker.

CONCLUSIONS

Based on present research results, health programs specific to smoking cessation should take socio-demographic factors, smoking history, and current smoking behavior into account.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further.

OBJECTIVES

To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy).

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer.

DATA COLLECTION AND ANALYSIS

For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model.

MAIN RESULTS

Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.

Telephone counselling for smoking cessation

BACKGROUND

Telephone services can provide information and support for smokers. Counselling may be provided proactively or offered reactively to callers to smoking cessation helplines.

OBJECTIVES

To evaluate the effect of telephone support to help smokers quit, including proactive or reactive counselling, or the provision of other information to smokers calling a helpline.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP for studies of telephone counselling, using search terms including 'hotlines' or 'quitline' or 'helpline'. Date of the most recent search: May 2018.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials which offered proactive or reactive telephone counselling to smokers to assist smoking cessation.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. We pooled studies using a random-effects model and assessed statistical heterogeneity amongst subgroups of clinically comparable studies using the I2 statistic. In trials including smokers who did not call a quitline, we used meta-regression to investigate moderation of the effect of telephone counselling by the planned number of calls in the intervention, trial selection of participants that were motivated to quit, and the baseline support provided together with telephone counselling (either self-help only, brief face-to-face intervention, pharmacotherapy, or financial incentives).

MAIN RESULTS

We identified 104 trials including 111,653 participants that met the inclusion criteria. Participants were mostly adult smokers from the general population, but some studies included teenagers, pregnant women, and people with long-term or mental health conditions. Most trials (58.7%) were at high risk of bias, while 30.8% were at unclear risk, and only 11.5% were at low risk of bias for all domains assessed. Most studies (100/104) assessed proactive telephone counselling, as opposed to reactive forms.Among trials including smokers who contacted helplines (32,484 participants), quit rates were higher for smokers receiving multiple sessions of proactive counselling (risk ratio (RR) 1.38, 95% confidence interval (CI) 1.19 to 1.61; 14 trials, 32,484 participants; I2 = 72%) compared with a control condition providing self-help materials or brief counselling in a single call. Due to the substantial unexplained heterogeneity between studies, we downgraded the certainty of the evidence to moderate.In studies that recruited smokers who did not call a helpline, the provision of telephone counselling increased quit rates (RR 1.25, 95% CI 1.15 to 1.35; 65 trials, 41,233 participants; I2 = 52%). Due to the substantial unexplained heterogeneity between studies, we downgraded the certainty of the evidence to moderate. In subgroup analysis, we found no evidence that the effect of telephone counselling depended upon whether or not other interventions were provided (P = 0.21), no evidence that more intensive support was more effective than less intensive (P = 0.43), or that the effect of telephone support depended upon whether or not people were actively trying to quit smoking (P = 0.32). However, in meta-regression, telephone counselling was associated with greater effectiveness when provided as an adjunct to self-help written support (P < 0.01), or to a brief intervention from a health professional (P = 0.02); telephone counselling was less effective when provided as an adjunct to more intensive counselling. Further, telephone support was more effective for people who were motivated to try to quit smoking (P = 0.02). The findings from three additional trials of smokers who had not proactively called a helpline but were offered telephone counselling, found quit rates were higher in those offered three to five telephone calls compared to those offered just one call (RR 1.27, 95% CI 1.12 to 1.44; 2602 participants; I2 = 0%).

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that proactive telephone counselling aids smokers who seek help from quitlines, and moderate-certainty evidence that proactive telephone counselling increases quit rates in smokers in other settings. There is currently insufficient evidence to assess potential variations in effect from differences in the number of contacts, type or timing of telephone counselling, or when telephone counselling is provided as an adjunct to other smoking cessation therapies. Evidence was inconclusive on the effect of reactive telephone counselling, due to a limited number studies, which reflects the difficulty of studying this intervention.

Prevalence and Predictors of Obesity and Overweight among Adults Visiting Primary Care Settings in the Southwestern Region, Saudi Arabia

Introduction

Obesity is becoming the most common health problem of the 21st century, as it will contribute significantly to the high prevalence of cardiovascular disease in developing countries. The main objective of our study was to estimate the prevalence of obesity and overweight among adults attending primary health care settings, southwestern region of the Kingdom of Saudi Arabia.

Methods

The studied population was composed of adults visiting primary health care centres in the southwestern region of Saudi Arabia. A cross-sectional study was carried out on a representative sample of 1681 adult patients. Obesity and overweight were defined according to the WHO standards. Statistical analysis was conducted using the statistical package SPSS 17.0. Logistic regression analysis was used to identify independent predictors of obesity and overweight in the studied population.

Results

Data on body mass index (BMI) measurement was recorded for 1649 out of 1681 participants (98.1%). The overall mean weight was 74.1 ± 15.81 kg; and that for men was 77.69 ± 16.14 kg vs. 69.37 ± 14.02 kg for women with significant statistical difference of p < 0.001. The overall prevalence of overweight and obesity was, respectively, 38.3% and 27.6%. Smoking was not significantly associated with obesity, whereas hypertension was significantly associated with obesity. The risk of overweight or obesity significantly increased from the highest to the lowest monthly income; it passed from 1.67 CI 95% = [1.24-2.25] within the category 5000-7000 SAR to 2.23 CI 95% = [1.71-2.90] within the category less than 5000 SAR.

Conclusion

Our study showed high prevalence of overweight and obesity which should be considered as a public health concern to be followed by specific interventions at the community level with multidisciplinary activities starting from childhood as a primordial prevention program.

Quitline treatment dose predicts cessation outcomes among safety net patients linked with treatment via Ask-Advise-Connect

The efficacy of tobacco treatment delivered by state quitlines in diverse populations is well-supported, yet little is known about associations between treatment dose and cessation outcomes following the implementation of Ask-Advise-Connect (AAC), an electronic health record-based systematic referral process that generates a high volume of proactive calls from the state quitline to smokers. The current study is a secondary analysis of a 34-month implementation trial evaluating ACC in 13 safety-net clinics in Houston, TX. Treatment was delivered by a quitline and comprised up to five proactive, telephone-delivered multi-component cognitive-behavioral treatment sessions. Associations between treatment dose and abstinence were examined. Abstinence was assessed by phone six months after treatment enrollment, and biochemically confirmed via mailed saliva cotinine. Among smokers who enrolled in treatment and agreed to follow-up (n = 3704), 29.2% completed no treatment sessions, 35.5% completed one session, 16.4% completed two sessions, and 19.0% completed ≥three sessions. Those who completed one (vs. no) sessions were no more likely to report abstinence (OR: 0.98). Those who completed two (vs. no) sessions were nearly twice as likely to report abstinence (OR: 1.83). Those who completed ≥three (vs. no) sessions were nearly four times as likely to report abstinence (OR: 3.70). Biochemically-confirmed cessation outcomes were similar. Most smokers received minimal or no treatment, and treatment dose had a large impact on abstinence. Results highlight the importance of improving engagement in evidence-based treatment protocols following enrollment. Given that motivation to quit fluctuates, systematically offering enrollment to all smokers at all visits is important.

•

The majority of smokers received minimal or no evidence-based tobacco treatment.

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Smokers who completed 0 or 1 treatment sessions were unlikely to achieve abstinence.

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Completion of 2 calls doubled the likelihood of abstinence at 6 months.

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Completion of ≥3 calls was associated with a near quadrupling of abstinence rates.

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Improving engagement in evidence-based treatment protocols is a research priority.

User characteristics of national smoking cessation services in Korea: who chooses each type of tobacco cessation program?

BACKGROUND

Relatively little is known about which characteristics of smokers are related to choosing a specific type of smoking cessation service. The user characteristics of different smoking cessation services were compared to determine the service preferred by user characteristics.

METHODS

The characteristics of adult smokers from Korea National Health and Nutrition Examination Survey (3762) and registered users of national smoking cessation services operated through the web (14,762), at Public Health Center-based Smoking Cessation Clinics (PHC-based SCCs) (335,532), and by telephone (Quitline) (2983) were compared.

RESULTS

Females and younger aged were more in web and telephone-based cessation service users, while aged 50 years or older were more in PHC-based SCCs users. Although manufacturing and production workers were the most prevalent among smokers in the general population, office workers and others including housewives and unemployed were most prevalent among the users of Quitline and PHC-based SCCs, respectively. The number of cigarettes smoked per day was twice as high among cessation service users as in general population. Smokers with greater nicotine dependency were most prevalent in the web-based service. Overseas users were in the web-based cessation service.

CONCLUSION

Identifying user-specific characteristics by the type of cessation services looks necessary to develop and offer appropriate cessation services.

Retrospective reports of former smokers: Receiving doctor's advice to quit smoking and using behavioral interventions for smoking cessation in the United States

The study investigated the over-time changes and racial/ethnic disparities in the quality of health care services for cigarette smoking cessation in the U.S. from 2007 to 2015. The primary measures included receiving a doctor's advice to quit smoking in the year before smoking cessation and using behavioral interventions for smoking cessation (telephone helplines and web-based interventions) while trying to quit smoking. The study was conducted from January to July 2018. We used merged data from the 2010-11 and 2014-15 Tobacco Use Supplement to the Current Population Survey. The sample sizes were 7011 and 12,025, respectively, for the analyses corresponding to two primary measures. The rate of receiving a doctor's advice to quit increased significantly from 66% (SE = 2%) in 2007 to 73% (SE = 4%) in 2015. The rate of usage of telephone helplines or web-based interventions for smoking cessation increased only from 3% (SE = 1%) in 2007 to 5% (SE = 1%) in 2015. These positive trends remained even after adjusting for several important factors. For both measures, the rates were consistently lower among Hispanic smokers than Non-Hispanic Black/African American and White smokers. Despite the availability of states' behavioral interventions for cessation of tobacco use, utilization of these interventions remains very low, indicating that smokers may not be aware of these free resources, may have misconceptions about these interventions being evidence-based, or there are barriers for using these interventions.

Predictors of engagement in post-discharge quitline counseling among hospitalized smokers

Quitlines provide evidence-based tobacco treatment and multiple calls yield higher quit rates. This study aimed to identify subgroups of smokers with greater quitline engagement following referral during hospitalization. Data were from a randomized clinical trial assessing the effectiveness of fax referral (referral faxed to proactive quitline) versus warm handoff (patient connected to quitline at bedside) (n = 1054). Classification and regression trees analyses evaluated individual and treatment/health system-related variables and their interactions. Among all participants, warm handoff, higher ratings of the tobacco treatment care transition, and being older predicted completing more quitline calls. Among patients enrolled in the quitline, higher transition of care ratings, being older, and use of cessation medication post-discharge predicted completing more calls. Three of the four factors influencing engagement were characteristics of treatment within the hospital (quality of tobacco treatment care transition and referral method) and therapy (use of cessation medications), suggesting potential targets to increase quitline engagement post-discharge.

The Family Check-Up Online Program for Parents of Middle School Students: Protocol for a Randomized Controlled Trial

Background

Research has established that skillful family management during adolescence protects youth from a variety of mental health and behavioral problems. Interventions associated with this research have focused on parenting skills as the mediator that links early risk factors with a profile of later behavioral risk, including problem behavior, substance use, and school failure. Fortunately, positive changes in family management skills have been linked to meaningful improvements in adolescent behavior, and these improvements have been significant across a variety of cultural groups.

Objective

We describe the background, research design, and intervention components of an electronic health version of the Family Check-Up program that is targeting middle school children and is being evaluated in a randomized controlled trial for its usability, feasibility, and efficacy.

Methods

We used an iterative formative research process to develop an electronic health version of the Family Check-Up program. In our ongoing randomized controlled trial, eligible families are randomly assigned to 1 of 3 conditions: Family Check-Up Online-only (n≈100), Family Check-Up Online + Coach (n≈100), and a waitlist control condition (middle school as usual; n≈100). We are conducting assessments at baseline, 3 months following randomization (posttest), and at follow-ups scheduled for 6 months and 12 months.

Results

This randomized controlled trial project was funded in 2015. Participant recruitment was completed in spring 2018 and enrollment is ongoing. Follow-up assessments will be completed in 2019.

Conclusions

The innovative Family Check-Up Online program has the potential to help address many of the barriers that more traditional school-based behavioral mental health implementation strategies have yet to solve, including staffing and resources to implement family-centered support within schools.

Trial Registration

ClinicalTrials.gov NCT03060291; https://clinicaltrials.gov/ct2/show/NCT03060291 (Archived by WebCite at http://www.webcitation.org/70f8keeN4)

Trial Registration

RR1-10.2196/11106

Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol

BACKGROUND

Smoking is one of the most avoidable health risk factors, and yet the quitting success rates are low. The usage of tailored health messages to support quitting has been proved to increase quitting success rates. Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items-for instance, motivational messages aimed at smoking cessation-for each user based on his or her profile. The goals of this study are to analyze the perceived quality of an mHealth recommender system aimed at smoking cessation, and to assess the level of engagement with the messages delivered to users via this medium.

METHODS

Patients participating in a smoking cessation program will be provided with a mobile app to receive tailored motivational health messages selected by a health recommender system, based on their profile retrieved from an electronic health record as the initial knowledge source. Patients' feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. This paper details the implementation and evaluation protocol that will be followed.

DISCUSSION

This study will explore whether a health recommender system algorithm integrated with an electronic health record can predict which tailored motivational health messages patients would prefer and consider to be of a good quality, encouraging them to engage with the system. The outcomes of this study will help future researchers design better tailored motivational message-sending recommender systems for smoking cessation to increase patient engagement, reduce attrition, and, as a result, increase the rates of smoking cessation.

TRIAL REGISTRATION

The trial was registered at clinicaltrials.org under the ClinicalTrials.gov identifier NCT03206619 on July 2nd 2017. Retrospectively registered.

Association of Smoking with General and Abdominal Obesity: Evidence from a Cohort Study in West of Iran

Background: This study aimed to examine the association between smoking and obesity among adults in Kermanshah Province, west of Iran.

Study design: A cross-sectional study.

Methods: A total of 8822 participants, aged 35-65 yr, form Ravansar Non-communicable Disease (RaNCD) cohort study (2014-2016) were enrolled. Smoking habits were categorized in terms of smoking status (current, former and never smokers) and smoking intensity (light, moderate and heavy). General obesity was defined as body mass index (BMI) ≥30 kg/m2 and abdominal obesity were defined as a waist to hip ratio (WHR) ≥0.9 for men and ≥0.85 for women. Multiple logistic regressions were used to examine the association between general and abdominal obesity with smoking status and smoking intensity while controlling for age, sex, years of education and wealth index.

Results: Overall, 12% were current smokers, 8.4% former smokers and 79.6% never smokers. The prevalence of light, moderate and heavy smokers among current smokers was 30.8%, 18%, and 51.2%, respectively. The prevalence of general obesity was 27.6%, while the prevalence of abdominal obesity was 82.3%. The probabilities of general and abdominal obesity for current smokers were lower than never smokers by 34% and 36%, respectively. The probability of abdominal obesity for heavy smokers was 31% lower than light smokers. We did not observe significant associations between smoking intensity and general obesity.

Conclusions: Current smokers compared to never smokers were less likely to be obese. The reverse association between smoking and obesity; however, should not be interpreted as a causal relationship.

Internet-based interventions for smoking cessation

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, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

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.

SEARCH METHODS

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.

SELECTION CRITERIA

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.

DATA COLLECTION AND ANALYSIS

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.

MAIN RESULTS

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 (I2 = 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, I2 = 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 (I2 = 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, I2 = 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, I2 = 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 (I2 = 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.

AUTHORS' CONCLUSIONS

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.

IMPLEMENTATION, RECRUITMENT AND BASELINE CHARACTERISTICS: A RANDOMIZED TRIAL OF COMBINED TREATMENTS FOR SMOKING CESSATION AND WEIGHT CONTROL

Background

Two-thirds of treatment-seeking smokers are obese or overweight. Most smokers are concerned about gaining weight after quitting. The average smoker experiences modest post-quit weight gain which discourages many smokers from quitting. Although evidence suggests that combined interventions to help smokers quit smoking and prevent weight gain can be helpful, studies have not been replicated in real world settings.

Methods

This paper describes recruitment and participant characteristics of the Best Quit Study, a 3-arm randomized controlled trial testing tobacco cessation treatment alone or combined with simultaneous or sequential weight management. Study participants were recruited via tobacco quitlines from August 5, 2013 to December 15, 2014.

Results

Statistical analysis on baseline data was conducted in 2015/2016. Among 5082 potentially eligible callers to a tobacco quitline, 2540 were randomized (50% of eligible). Compared with individuals eligible but not randomized, those randomized were significantly more likely to be female (65.7% vs 54.5%, p < 0.01), overweight or obese (76.3% vs 62.5%, p < 0.01), more confident in quitting (p < 0.01), more addicted (first cigarette within 5 min: 50.0% vs 44.4%, p < 0.01), and have a chronic disease (28.6% vs. 24.4%, p < 0.01). Randomized groups were not statistically significantly different on demographics, tobacco or weight variables. Two-thirds of participants were female and white with a mean age of 43.

Conclusions

Adding weight management interventions to tobacco cessation quitlines was feasible and acceptable to smokers. If successful for cessation and weight outcomes, a combined intervention may provide a treatment approach for addressing weight gain with smoking cessation through tobacco quitlines.

Trial registration

Clinicaltrials.gov NCT01867983.

More Than a Text Message: Dismantling Digital Triggers to Curate Behavior Change in Patient-Centered Health Interventions

Digital triggers such as text messages, emails, and push alerts are designed to focus an individual on a desired goal by prompting an internal or external reaction at the appropriate time. Triggers therefore have an essential role in engaging individuals with digital interventions delivered outside of traditional health care settings, where other events in daily lives and fluctuating motivation to engage in effortful behavior exist. There is an emerging body of literature examining the use of digital triggers for short-term action and longer-term behavior change. However, little attention has been given to understanding the components of digital triggers. Using tailoring as an overarching framework, we separated digital triggers into 5 primary components: (1) who (sender), (2) how (stimulus type, delivery medium, heterogeneity), (3) when (delivered), (4) how much (frequency, intensity), and (5) what (trigger's target, trigger's structure, trigger's narrative). We highlighted key considerations when tailoring each component and the pitfalls of ignoring common mistakes, such as alert fatigue and habituation. As evidenced throughout the paper, there is a broad literature base from which to draw when tailoring triggers to curate behavior change in health interventions. More research is needed, however, to examine differences in efficacy based on component tailoring, to best use triggers to facilitate behavior change over time, and to keep individuals engaged in physical and mental health behavior change efforts. Dismantling digital triggers into their component parts and reassembling them according to the gestalt of one's change goals is the first step in this development work.

Differential prevalence of established risk factors for poor cessation outcomes among smokers by level of social anxiety

BACKGROUND AND OBJECTIVES

Despite clear associations between social anxiety (SA), high prevalence of smoking, and cessation failure, little is known about factors contributing to these relationships. Moreover, the extent to which smokers with moderate SA represent an at-risk group of smokers is also unknown. This study examined the extent to which established risk factors for poor cessation (eg, sociodemographic, smoking history, mental health comorbidity) are prevalent among smokers with low, moderate, and high levels of SA.

METHODS

Participants (N = 2,637) were adult smokers from a web-based smoking cessation trial. Nineteen characteristics considered risk factors for poor cessation outcomes were assessed at baseline. Those associated with social anxiety were subsequently compared by SA level.

RESULTS

Regression models indicated that 10/19 risk factors were associated with SA. Compared to smokers with low SA, those with moderate and high SA endorsed 4/10 and 10/10 risk factors as more prevalent or severe, respectively. Compared to smokers with low SA, High SA was associated with greater sociodemographic risk factors, while both moderate and high SA was associated with more severe mental health symptoms.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

Smokers with moderate and high levels of SA endorse more risk factors for poor cessation outcomes than those with low levels of SA, particularly mental health symptoms. These factors may help explain the differential smoking outcomes of socially anxious smokers. Results suggest that smokers with both moderate and high levels of SA would likely benefit from cessation interventions that address and consider these risk factors. (Am J Addict 2017;26:176-182).

How US Smokers Refer to E-cigarettes: An Examination of User-Generated Posts From a Web-Based Smoking Cessation Intervention, 2008-2015

INTRODUCTION

A challenge in Electronic Nicotine Delivery System (ENDS) research is how to refer to these devices in ways that are meaningful to current or potential users. The objectives of this study were to: (1) describe the frequency of ENDS terms in a web-based smoking cessation intervention; and (2) determine whether terms vary by US geographic region and date.

METHODS

Data were drawn from public posts between 2008-2015 on http://BecomeAnEX.org and limited to US users. We conducted "exact" and "fuzzy" searches to find posts containing ENDS keywords using custom Python scripts, and extracted geocoding data and date for each post. We examined counts and frequencies of ENDS terms by unique user, by unique user and region, and by unique user and date.

RESULTS

We identified 1023 unique US website users who had written a post containing one or more ENDS keywords. Posters were majority female (79%), educated (78% attended at least some college), and had a median age of 47 years. Overall, 92% of ENDS posters employed the term "e-cigarette" or a derivation. Derivations of "vape" became increasingly popular in 2013, whereas "NJoy" and "blu" were employed by fewer than 2% of posters. We found no variation in frequency of ENDS terms by US region.

CONCLUSIONS

Researchers may have confidence that "e-cigarette" and "vape" are recognizable terms among US treatment-seeking smokers. Conversely, terms such as "ENDS," commonly employed by researchers and public health advocates, are not used by smokers and may be an impediment to tobacco control research.

IMPLICATIONS

Researchers may have confidence that "e-cigarette," and, to a lesser extent, "vape" are recognizable terms among US adult smokers referring to ENDS (including accessories, brand names, and actions). Conversely, terms such as "electronic nicotine delivery systems," commonly employed by researchers and public health advocates, are not used by US smokers and may be an impediment to tobacco control research and practice.

Population Health Management for Older Adults: Review of Interventions for Promoting Successful Aging Across the Health Continuum

Background: The older adult population is expanding, living longer, with multiple chronic conditions. Understanding and managing their needs over time is an integral part of defining successful aging. Population health is used to describe the measurement and health outcomes of a population. Objectives: To define population health as applied to older adults, summarize lessons learned from current research, and identify potential interventions designed to promote successful aging and improved health for this population. Method: Online search engines were utilized to identify research on population health and health interventions for older adults. Results: Population health management (PHM) is one strategy to promote the health and well-being of target populations. Interventions promoting health across a continuum tend to be disease, risk, or health behavior specific rather than encompassing a global concept of health. Conclusion: Many existing interventions for older adults are simply research based with limited generalizability; as such, further work in this area is warranted.

Young Adult Utilization of a Smoking Cessation Website: An Observational Study Comparing Young and Older Adult Patterns of Use

Background

There is little research on how young adults or young adult subgroups utilize and engage with Web-based cessation interventions when trying to quit smoking. Addressing this knowledge gap is important to identify opportunities to optimize the effectiveness of online cessation programs across diverse young adult users.

Objective

This study examines utilization of the BecomeAnEX.org smoking cessation website among young adults and young adult subgroups compared with older adults to identify patterns of use by age, gender, and race/ethnicity.

Methods

Study participants were 5983 new registered users on a free smoking cessation website who were aged 18 to 70 years. Website utilization was tracked for 6 months; metrics of use included website visits, pages per visit, length of visit, and interaction with specific website features. Differences in website use by age were examined via bivariate analyses and multivariate logistic regression adjusted for age, gender, and race/ethnicity. Interactions were examined to determine differences by gender and race/ethnicity within young (18- to 24-year-olds and 25- to 34-year-olds) and older (35 years and older) adult segments.

Results

A greater percentage of young adults aged 18 to 34 years visited the site only once compared with older adults aged 35 years and older (72.05% vs 56.59%, respectively; P<.001). Young adults also spent less time on the site and viewed fewer pages than older adults. In adjusted analyses, young adults were significantly less likely than older adults to visit the site more than once (18-24 years: adjusted odds ratio [AOR] 0.58, 95% CI 0.49-0.68, P<.001; 25-34 years: AOR 0.56, 95% CI 0.50-0.64, P<.001), spend more than 3 minutes on the site (18-24 years: AOR 0.67, 95% CI 0.57-0.79, P<.001; 25-34 years: AOR 0.56, 95% CI 0.49-0.64, P<.001), view 12 or more pages (18-24 years: AOR 0.72, 95% CI 0.61-0.83; P<.001; 25-34 years: AOR 0.67, 95% CI 0.59-0.76, P<.001), utilize the BecomeAnEX.org community (18-24 years: AOR 0.61, 95% CI 0.48-0.79, P<.001; 25-34 years: AOR 0.73, 95% CI 0.60-0.88, P<.001), or utilize Separation Exercises (18-24 years: AOR 0.68, 95% CI 0.51-0.89, P<.01; 25-34 years: AOR 0.77, 95% CI 0.63-0.94, P<.01). Gender differences in utilization were more pronounced among young adults compared with older adults, with lower levels of utilization among young men than young women. For all age groups, utilization was higher among whites and African Americans than among Hispanics and other racial minorities, with one exception—BecomeAnEX.org community utilization was significantly higher among Hispanic young adults compared with white and African American young adults.

Conclusions

Results point to important areas of inquiry for future research and development efforts. Research should focus on enhancing demand and increasing engagement among younger adults and men, examining strategies for capitalizing on young adult developmental needs, and increasing utilization of effective site features among diverse young adult users.

Nicotine receptor partial agonists for smoking cessation

BACKGROUND

Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist).

OBJECTIVES

To review the efficacy of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's specialised register for trials, using the terms ('cytisine' or 'Tabex' or 'dianicline' or 'varenicline' or 'nicotine receptor partial agonist') in the title or abstract, or as keywords. The register is compiled from searches of MEDLINE, EMBASE, and PsycINFO using MeSH terms and free text to identify controlled trials of interventions for smoking cessation and prevention. We contacted authors of trial reports for additional information where necessary. The latest update of the specialised register was in May 2015, although we have included a few key trials published after this date. We also searched online clinical trials registers.

SELECTION CRITERIA

We included randomised controlled trials which compared the treatment drug with placebo. We also included comparisons with bupropion and nicotine patches where available. We excluded trials which did not report a minimum follow-up period of six months from start of treatment.

DATA COLLECTION AND ANALYSIS

We extracted data on the type of participants, the dose and duration of treatment, the outcome measures, the randomisation procedure, concealment of allocation, and completeness of follow-up.The main outcome measured was abstinence from smoking at longest follow-up. We used the most rigorous definition of abstinence, and preferred biochemically validated rates where they were reported. Where appropriate we pooled risk ratios (RRs), using the Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Two trials of cytisine (937 people) found that more participants taking cytisine stopped smoking compared with placebo at longest follow-up, with a pooled risk ratio (RR) of 3.98 (95% confidence interval (CI) 2.01 to 7.87; low-quality evidence). One recent trial comparing cytisine with NRT in 1310 people found a benefit for cytisine at six months (RR 1.43, 95% CI 1.13 to 1.80).One trial of dianicline (602 people) failed to find evidence that it was effective (RR 1.20, 95% CI 0.82 to 1.75). This drug is no longer in development.We identified 39 trials that tested varenicline, 27 of which contributed to the primary analysis (varenicline versus placebo). Five of these trials also included a bupropion treatment arm. Eight trials compared varenicline with nicotine replacement therapy (NRT). Nine studies tested variations in varenicline dosage, and 13 tested usage in disease-specific subgroups of patients. The included studies covered 25,290 participants, 11,801 of whom used varenicline.The pooled RR for continuous or sustained abstinence at six months or longer for varenicline at standard dosage versus placebo was 2.24 (95% CI 2.06 to 2.43; 27 trials, 12,625 people; high-quality evidence). Varenicline at lower or variable doses was also shown to be effective, with an RR of 2.08 (95% CI 1.56 to 2.78; 4 trials, 1266 people). The pooled RR for varenicline versus bupropion at six months was 1.39 (95% CI 1.25 to 1.54; 5 trials, 5877 people; high-quality evidence). The RR for varenicline versus NRT for abstinence at 24 weeks was 1.25 (95% CI 1.14 to 1.37; 8 trials, 6264 people; moderate-quality evidence). Four trials which tested the use of varenicline beyond the 12-week standard regimen found the drug to be well-tolerated during long-term use. The number needed to treat with varenicline for an additional beneficial outcome, based on the weighted mean control rate, is 11 (95% CI 9 to 13). The most commonly reported adverse effect of varenicline was nausea, which was mostly at mild to moderate levels and usually subsided over time. Our analysis of reported serious adverse events occurring during or after active treatment suggests there may be a 25% increase in the chance of SAEs among people using varenicline (RR 1.25; 95% CI 1.04 to 1.49; 29 trials, 15,370 people; high-quality evidence). These events include comorbidities such as infections, cancers and injuries, and most were considered by the trialists to be unrelated to the treatments. There is also evidence of higher losses to follow-up in the control groups compared with the intervention groups, leading to a likely underascertainment of the true rate of SAEs among the controls. Early concerns about a possible association between varenicline and depressed mood, agitation, and suicidal behaviour or ideation led to the addition of a boxed warning to the labelling in 2008. However, subsequent observational cohort studies and meta-analyses have not confirmed these fears, and the findings of the EAGLES trial do not support a causal link between varenicline and neuropsychiatric disorders, including suicidal ideation and suicidal behaviour. The evidence is not conclusive, however, in people with past or current psychiatric disorders. Concerns have also been raised that varenicline may slightly increase cardiovascular events in people already at increased risk of those illnesses. Current evidence neither supports nor refutes such an association, but we await the findings of the CATS trial, which should establish whether or not this is a valid concern.

AUTHORS' CONCLUSIONS

Cytisine increases the chances of quitting, although absolute quit rates were modest in two recent trials. Varenicline at standard dose increased the chances of successful long-term smoking cessation between two- and three-fold compared with pharmacologically unassisted quit attempts. Lower dose regimens also conferred benefits for cessation, while reducing the incidence of adverse events. More participants quit successfully with varenicline than with bupropion or with NRT. Limited evidence suggests that varenicline may have a role to play in relapse prevention. The most frequently recorded adverse effect of varenicline is nausea, but mostly at mild to moderate levels and tending to subside over time. Early reports of possible links to suicidal ideation and behaviour have not been confirmed by current research.Future trials of cytisine may test extended regimens and more intensive behavioural support.

Combined pharmacotherapy and behavioural interventions for smoking cessation

BACKGROUND

Both behavioural support (including brief advice and counselling) and pharmacotherapies (including nicotine replacement therapy (NRT), varenicline and bupropion) are effective in helping people to stop smoking. Combining both treatment approaches is recommended where possible, but the size of the treatment effect with different combinations and in different settings and populations is unclear.

OBJECTIVES

To assess the effect of combining behavioural support and medication to aid smoking cessation, compared to a minimal intervention or usual care, and to identify whether there are different effects depending on characteristics of the treatment setting, intervention, population treated, or take-up of treatment.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in July 2015 for records with any mention of pharmacotherapy, including any type of NRT, bupropion, nortriptyline or varenicline.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials evaluating combinations of pharmacotherapy and behavioural support for smoking cessation, compared to a control receiving usual care or brief advice or less intensive behavioural support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

Search results were prescreened by one author and inclusion or exclusion of potentially relevant trials was agreed by two authors. Data was extracted by one author and checked by another.The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically validated rates if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Fifty-three studies with a total of more than 25,000 participants met the inclusion criteria. A large proportion of studies recruited people in healthcare settings or with specific health needs. Most studies provided NRT. Behavioural support was typically provided by specialists in cessation counselling, who offered between four and eight contact sessions. The planned maximum duration of contact was typically more than 30 minutes but less than 300 minutes. Overall, studies were at low or unclear risk of bias, and findings were not sensitive to the exclusion of any of the six studies rated at high risk of bias in one domain. One large study (the Lung Health Study) contributed heterogeneity due to a substantially larger treatment effect than seen in other studies (RR 3.88, 95% CI 3.35 to 4.50). Since this study used a particularly intensive intervention which included extended availability of nicotine gum, multiple group sessions and long term maintenance and recycling contacts, the results may not be comparable with the interventions used in other studies, and hence it was not pooled in other analyses. Based on the remaining 52 studies (19,488 participants) there was high quality evidence (using GRADE) for a benefit of combined pharmacotherapy and behavioural treatment compared to usual care, brief advice or less intensive behavioural support (RR 1.83, 95% CI 1.68 to 1.98) with moderate statistical heterogeneity (I² = 36%).The pooled estimate for 43 trials that recruited participants in healthcare settings (RR 1.97, 95% CI 1.79 to 2.18) was higher than for eight trials with community-based recruitment (RR 1.53, 95% CI 1.33 to 1.76). Compared to the first version of the review, previous weak evidence of differences in other subgroup analyses has disappeared. We did not detect differences between subgroups defined by motivation to quit, treatment provider, number or duration of support sessions, or take-up of treatment.

AUTHORS' CONCLUSIONS

Interventions that combine pharmacotherapy and behavioural support increase smoking cessation success compared to a minimal intervention or usual care. Updating this review with an additional 12 studies (5,000 participants) did not materially change the effect estimate. Although trials differed in the details of their populations and interventions, we did not detect any factors that modified treatment effects apart from the recruitment setting. We did not find evidence from indirect comparisons that offering more intensive behavioural support was associated with larger treatment effects.

The Effectiveness of Prompts to Promote Engagement With Digital Interventions: A Systematic Review

Background

Digital interventions have been effective in improving numerous health outcomes and health behaviors; furthermore, they are increasingly being used in different health care areas, including self-management of long-term conditions, mental health, and health promotion. The full potential of digital interventions is hindered by a lack of user engagement. There is an urgent need to develop effective strategies that can promote users’ engagement with digital interventions. One potential method is the use of technology-based reminders or prompts.

Objective

To evaluate the effectiveness of technology-based strategies for promoting engagement with digital interventions.

Methods

Cochrane Collaboration guidelines on systematic review methodology were followed. The search strategy was executed across 7 electronic databases: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, Web of Science, the Education Resources Information Center (ERIC), PsycINFO, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). Databases were searched from inception to September 13, 2013, with no language or publication type restrictions, using three concepts: randomized controlled trials, digital interventions, and engagement. Gray literature and reference lists of included studies were also searched. Titles and abstracts were independently screened by 2 authors, then the full texts of potentially eligible papers were obtained and double-screened. Data from eligible papers were extracted by one author and checked for accuracy by another author. Bias was assessed using the Cochrane risk of bias assessment tool. Narrative synthesis was performed on all included studies and, where appropriate, data were pooled using meta-analysis. All findings were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Results

A total of 14 studies were included in the review with 8774 participants. Of the 14 studies, 9 had sufficient data to be included in the meta-analyses. The meta-analyses suggested that technology-based strategies can potentially promote engagement compared to no strategy for dichotomous outcomes (relative risk [RR] 1.27, 95% CI 1.01-1.60, I²=71%), but due to considerable heterogeneity and the small sample sizes in most studies, this result should be treated with caution. No studies reported adverse or economic outcomes. Only one study with a small sample size compared different characteristics; the study found that strategies promoting new digital intervention content and those sent to users shortly after they started using the digital intervention were more likely to engage users.

Conclusions

Overall, studies reported borderline positive effects of technology-based strategies on engagement compared to no strategy. However, the results have to be interpreted with caution. More research is needed to replicate findings and understand which characteristics of the strategies are effective in promoting engagement and how cost-effective they are.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Effective pharmacotherapies are available to help people who are trying to stop smoking, but quitting can still be difficult and providing higher levels of behavioural support may increase success rates further.

OBJECTIVES

To evaluate the effect of increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in May 2015 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount of behavioural support. The intervention condition had to involve person-to-person contact. The control condition could receive less intensive personal contact, or just written information. We did not include studies that used a contact-matched control to evaluate differences between types or components of support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

One author prescreened search results and two authors agreed inclusion or exclusion of potentially relevant trials. One author extracted data and another checked them.The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Forty-seven studies met the inclusion criteria with over 18,000 participants in the relevant arms. There was little evidence of statistical heterogeneity (I² = 18%) so we pooled all studies in the main analysis. There was evidence of a small but statistically significant benefit from more intensive support (RR 1.17, 95% CI 1.11 to 1.24) for abstinence at longest follow-up. All but four of the included studies provided four or more sessions of support to the intervention group. Most trials used NRT. We did not detect significant effects for studies where the pharmacotherapy was nortriptyline (two trials) or varenicline (one trial), but this reflects the absence of evidence.In subgroup analyses, studies that provided at least four sessions of personal contact for the intervention and no personal contact for the control had slightly larger estimated effects (RR 1.25, 95% CI 1.08 to 1.45; 6 trials, 3762 participants), although a formal test for subgroup differences was not significant. Studies where all intervention counselling was via telephone (RR 1.28, 95% CI 1.17 to 1.41; 6 trials, 5311 participants) also had slightly larger effects, and the test for subgroup differences was significant, but this subgroup analysis was not prespecified. In this update, the benefit of providing additional behavioural support was similar for the subgroup of trials in which all participants, including controls, had at least 30 minutes of personal contact (RR 1.18, 95% CI 1.06 to 1.32; 21 trials, 5166 participants); previously the evidence of benefit in this subgroup had been weaker. This subgroup was not prespecified and a test for subgroup differences was not significant. We judged the quality of the evidence to be high, using the GRADE approach. We judged a small number of trials to be at high risk of bias on one or more domains, but findings were not sensitive to their exclusion.

AUTHORS' CONCLUSIONS

Providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking has a small but important effect. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 25%, based on a pooled estimate from 47 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support.

Quitline Use and Outcomes among Callers with and without Mental Health Conditions: A 7-Month Follow-Up Evaluation in Three States

Objectives. To examine abstinence outcomes among tobacco users with and without a reported mental health condition (MHC) who enrolled in state tobacco quitline programs. Methods. Data were analyzed from a 7-month follow-up survey (response rate: 41% [3,132/7,459]) of three state-funded telephone quitline programs in the United States that assessed seven self-reported MHCs at quitline registration. We examined 30-day point prevalence tobacco quit rates for callers with any MHC versus none. Data were weighted to adjust for response bias and oversampling. Multivariable logistic regression was used to examine cessation outcomes. Results. Overall, 45.8% of respondents reported ≥1 MHC; 57.4% of those reporting a MHC reported ≥2 MHCs. The unadjusted quit rate for callers with any MHC was lower than for callers with no MHC (22.0% versus 31.0%, P < 0.001). After adjusting for demographics, nicotine dependence, and program engagement, callers reporting ≥1 MHC were less likely to be abstinent at follow-up (adjusted OR = 0.63, 95% CI = 0.51–0.78, P < 0.001). Conclusions. More intensive or tailored quitline programs may need to be developed among callers with MHCs as their quit rates appear to be lower than callers without MHCs.

Cessation Outcomes Among Quitline Callers in Three States During a National Tobacco Education Campaign

Introduction

Antismoking mass media campaigns, such as the Centers for Disease Control and Prevention’s Tips from Former Smokers (Tips) campaign, increase the number of tobacco users calling tobacco quitlines. Few studies have investigated long-term tobacco use cessation for callers during antismoking media campaigns. Studies have suggested that callers during campaigns may be less committed to quitting and have lower quit rates. This study examines tobacco user cessation outcomes 7 months after quitline enrollment during the 2012 Tips campaign (March 19 through June 10, 2012).

Methods

We analyzed data for 715 tobacco users who enrolled in the Nebraska, North Carolina, or Texas state quitline multiple-call programs during the 2012 Tips campaign and responded to a 7-month postenrollment survey (38.5% survey response rate). We used multivariable logistic regression analyses to determine whether 7-day and 30-day point prevalence abstinence rates 7 months after enrollment were related to level of exposure to the campaign.

Results

In multivariable models, only lower nicotine dependence and higher call completion were associated with higher odds of 7-day and 30-day abstinence 7 months after enrollment. Tips campaign exposure was not associated with abstinence.

Conclusion

Once enrolled in quitline counseling, quitline callers achieved similar outcomes regardless of Tips campaign exposure levels. While the campaign did not appear to directly affect odds of tobacco abstinence through quitlines, antismoking mass media campaigns such as Tips are valuable in increasing tobacco users’ exposure to quitlines and thus increasing their likelihood of making a quit attempt and eventually achieving tobacco abstinence.

A randomised controlled trial to prevent smoking relapse among recently quit smokers enrolled in employer and health plan sponsored quitlines

OBJECTIVE

To test adding an interactive voice response (IVR)-supported protocol to standard quitline treatment to prevent relapse among recently quit smokers.

DESIGN

Parallel randomised controlled trial with three arms: standard quitline, standard plus technology enhanced quitline with 10 risk assessments (TEQ-10), standard plus 20 TEQ assessments (TEQ-20).

SETTING

Quit For Life (QFL) programme.

PARTICIPANTS

1785 QFL enrolees through 19 employers or health plans who were 24+ h quit.

INTERVENTIONS

QFL is a 5-call telephone-based cessation programme including medications and web-based support. TEQ interventions included 10 or 20 IVR-delivered relapse risk assessments over 8 weeks with automated transfer to counselling for those at risk.

MAIN OUTCOME MEASURES

Self-reported 7-day and 30-day abstinence assessed at 6-month and 12-month post-enrolment (response rates: 61% and 59%, respectively). Missing data were imputed.

RESULTS

1785 were randomised (standard n=592, TEQ-10 n=602, TEQ-20 n=591). Multiple imputation-derived, intent-to-treat 30-day quit rates (95% CI) at 6 months were 59.4% (53.7% to 63.8%) for standard, 62.3% (57.7% to 66.9%) for TEQ-10, 59.4% (53.7% to 65.1%) for TEQ-20 and 30-day quit rates at 12 months were 61.2% (55.6% to 66.8%) for standard, 60.6% (56.0% to 65.2%) for TEQ-10, 54.9% (49.0% to 60.9%) for TEQ-20. There were no significant differences in quit rates. 73.3% of TEQ participants were identified as at-risk by IVR assessments; on average, participants completed 0.41 IVR-transferred counselling calls. Positive risk assessments identified participants less likely (OR=0.56, 95% CI 0.42 to 0.76) to be abstinent at 6 months.

CONCLUSIONS

Standard treatment was highly effective, with 61% remaining abstinent at 12 months using multiple imputation intent-to-treat (intent-to-treat missing=smoking quit rate: 38%). TEQ assessments identified quitters at risk for relapse. However, adding IVR-transferred counselling did not yield higher quit rates. Research is needed to determine if alternative designs can improve outcomes.

TRIAL REGISTRATION NUMBER

NCT00888992.

Randomized Controlled Trial of the Combined Effects of Web and Quitline Interventions for Smokeless Tobacco Cessation

BACKGROUND

Use of smokeless tobacco (moist snuff and chewing tobacco) is a significant public health problem but smokeless tobacco users have few resources to help them quit. Web programs and telephone-based programs (Quitlines) have been shown to be effective for smoking cessation. We evaluate the effectiveness of a Web program, a Quitline, and the combination of the two for smokeless users recruited via the Web.

OBJECTIVES

To test whether offering both a Web and Quitline intervention for smokeless tobacco users results in significantly better long-term tobacco abstinence outcomes than offering either intervention alone; to test whether the offer of Web or Quitline results in better outcome than a self-help manual only Control condition; and to report the usage and satisfaction of the interventions when offered alone or combined.

METHODS

Smokeless tobacco users (N= 1,683) wanting to quit were recruited online and randomly offered one of four treatment conditions in a 2×2 design: Web Only, Quitline Only, Web + Quitline, and Control (printed self-help guide). Point-prevalence all tobacco abstinence was assessed at 3- and 6-months post enrollment.

RESULTS

69% of participants completed both the 3- and 6-month assessments. There was no significant additive or synergistic effect of combining the two interventions for Complete Case or the more rigorous Intent To Treat (ITT) analyses. Significant simple effects were detected, individually the interventions were more efficacious than the control in achieving repeated 7-day point prevalence all tobacco abstinence: Web (ITT, OR = 1.41, 95% CI = 1.03, 1.94, p = .033) and Quitline (ITT: OR = 1.54, 95% CI = 1.13, 2.11, p = .007). Participants were more likely to complete a Quitline call when offered only the Quitline intervention (OR = 0.71, 95% CI = .054, .093, p = .013), the number of website visits and duration did not differ when offered alone or in combination with Quitline. Rates of program helpfulness (p <.05) and satisfaction (p <.05) were higher for those offered both interventions versus offered only quitline.

CONCLUSION

Combining Web and Quitline interventions did not result in additive or synergistic effects, as have been found for smoking. Both interventions were more effective than a self-help control condition in helping motivated smokeless tobacco users quit tobacco. Intervention usage and satisfaction were related to the amount intervention content offered. Usage of the Quitline intervention decreased when offered in combination, though rates of helpfulness and recommendations were higher when offered in combination.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00820495; http://clinicaltrials.gov/ct2/show/NCT00820495.

The effectiveness of technology-based strategies to promote engagement with digital interventions: a systematic review protocol

Background

Digital interventions provide effective and potentially cost-effective models for improving health outcomes as they deliver health information and services that are widely disseminated, confidential, and can be tailored to needs of the individual user. Digital interventions have been used successfully for health promotion, mental health, and for enabling self-management of long-term conditions. However, their effectiveness is limited by low usage rates, with non-engagement a major challenge. Hence, it is crucial to find effective strategies to increase user engagement with digital interventions.

Objective

This systematic review will aim to evaluate the effectiveness of technology-based strategies to promote engagement with digital interventions.

Methods

We will follow Cochrane Collaboration guidelines on systematic review methodology. The search strategy will be executed across seven e-databases (including MEDLINE, EMBASE, PsycINFO, CINAHL) using the concepts “digital intervention” and “engagement”, limited by study type (randomized controlled trial). Grey literature and reference lists of included studies will be searched. Titles and abstracts will be independently screened by 2 authors. Then the full text of potentially eligible papers will be obtained and double screened. Data from eligible papers will be extracted by 1 author and checked for accuracy by another author. Bias will be assessed using the Cochrane bias assessment tool. Narrative synthesis will report on all included studies, and where appropriate, data will be pooled using meta-analysis. All findings will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Sources of heterogeneity will be further investigated if required.

Results

Our research is in progress. The final draft of the systematic review is being written and will be submitted before the end of 2015.

Conclusions

The review findings will inform researchers and digital intervention providers about optimal use of technology-based strategies to promote engagement with digital interventions.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews: CRD42014010164; http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42014010164#.VTZmmiFViko (Archived by WebCite at http://www.webcitation.org/6XxQC8fT8).

Relationship between smoking and obesity: a cross-sectional study of 499,504 middle-aged adults in the UK general population

BACKGROUND

There is a general perception that smoking protects against weight gain and this may influence commencement and continuation of smoking, especially among young women.

METHODS

A cross-sectional study was conducted using baseline data from UK Biobank. Logistic regression analyses were used to explore the association between smoking and obesity; defined as body mass index (BMI) >30 kg/m2. Smoking was examined in terms of smoking status, amount smoked, duration of smoking and time since quitting and we adjusted for the potential confounding effects of age, sex, socioeconomic deprivation, physical activity, alcohol consumption, hypertension and diabetes.

RESULTS

The study comprised 499,504 adults aged 31 to 69 years. Overall, current smokers were less likely to be obese than never smokers (adjusted OR 0.83 95% CI 0.81-0.86). However, there was no significant association in the youngest sub-group (≤40 years). Former smokers were more likely to be obese than both current smokers (adjusted OR 1.33 95% CI 1.30-1.37) and never smokers (adjusted OR 1.14 95% CI 1.12-1.15). Among smokers, the risk of obesity increased with the amount smoked and former heavy smokers were more likely to be obese than former light smokers (adjusted OR 1.60, 95% 1.56-1.64, p<0.001). Risk of obesity fell with time from quitting. After 30 years, former smokers still had higher risk of obesity than current smokers but the same risk as never smokers.

CONCLUSION

Beliefs that smoking protects against obesity may be over-simplistic; especially among younger and heavier smokers. Quitting smoking may be associated with temporary weight gain. Therefore, smoking cessation interventions should include weight management support.

Utilization of a Web-based vs integrated phone/Web cessation program among 140,000 tobacco users: an evaluation across 10 free state quitlines

Background

Phone-based tobacco cessation program effectiveness has been established and randomized controlled trials have provided some support for Web-based services. Relatively little is known about who selects different treatment modalities and how they engage with treatments in a real-world setting.

Objective

This paper describes the characteristics, Web utilization patterns, and return rates of tobacco users who self-selected into a Web-based (Web-Only) versus integrated phone/Web (Phone/Web) cessation program.

Methods

We examined the demographics, baseline tobacco use, Web utilization patterns, and return rates of 141,429 adult tobacco users who self-selected into a Web-Only or integrated Phone/Web cessation program through 1 of 10 state quitlines from August 2012 through July 2013. For each state, registrants were only included from the timeframe in which both programs were offered to all enrollees. Utilization data were limited to site interactions occurring within 6 months after registration.

Results

Most participants selected the Phone/Web program (113,019/141,429, 79.91%). After enrollment in Web services, Web-Only were more likely to log in compared to Phone/Web (21,832/28,410, 76.85% vs 23,920/56,892, 42.04%; P<.001), but less likely to return after their initial log-in (8766/21,832, 40.15% vs 13,966/23,920, 58.39%; P<.001). In bivariate and multivariable analyses, those who chose Web-Only were younger, healthier, more highly educated, more likely to be uninsured or commercially insured, more likely to be white non-Hispanic and less likely to be black non-Hispanic, less likely to be highly nicotine-addicted, and more likely to have started their program enrollment online (all P<.001). Among both program populations, participants were more likely to return to Web services if they were women, older, more highly educated, or were sent nicotine replacement therapy (NRT) through their quitline (all P<.001). Phone/Web were also more likely to return if they had completed a coaching call, identified as white non-Hispanic or “other” race, or were commercially insured (all P<.001). Web-Only were less likely to return if they started their enrollment online versus via phone. The interactive Tobacco Tracker, Cost Savings Calculator, and Quitting Plan were the most widely used features overall. Web-Only were more likely than Phone/Web to use most key features (all P<.001), most notably the 5 Quitting Plan behaviors. Among quitlines that offered NRT to both Phone/Web and Web-Only, Web-Only were less likely to have received quitline NRT.

Conclusions

This paper adds to our understanding of who selects different cessation treatment modalities and how they engage with the program in a real-world setting. Web-Only were younger, healthier smokers of higher socioeconomic status who interacted more intensely with services in a single session, but were less likely to re-engage or access NRT benefits. Further research should examine the efficacy of different engagement techniques and services with different subpopulations of tobacco users.

Effective Tobacco Cessation via Health Coaching: An Institutional Case Report

Background:

Tobacco abuse is a well-recognized scourge on health and healthcare costs. Attempts to facilitate tobacco cessation are rarely better than marginally effective.

Primary Objective:

To describe an observational trial of an existing and highly successful tobacco cessation program featuring health coaching as the primary intervention. Core components of program design and data are presented and may serve as a model for other public health settings.

Methods:

Health coaching and three complementary program components (auriculotherapy, alpha-electrical stimulation, and relaxation techniques) are presented. Quit rates at 6 months for 161 patients over 3 years are provided featuring 30-day point prevalence smoke free and intent-to-treat values. Comparisons for telephonic vs in-clinic health coaching, free choice vs mandated participation, and program costs are provided.

Results:

Point prevalence quit rate was 88.7% while the more conservative intent-to-treat quit rate was 51.6%. Telephonic and in-clinic health coaching were not significantly different at any time point. Smoke-free rates at 6 and 12 months were 76.9% and 63.2%, respectively.

Conclusions:

Two cost-effective smoking cessation models featuring health coaching are presented. Point prevalence (30-day) above 80% and an enduring effect was seen. Personal and societal burdens (health and financial) of tobacco use might be greatly impacted if such programs were successfully implemented on a larger scale.

Use of non-assigned interventions in a randomized trial of internet and telephone treatment for smoking cessation

INTRODUCTION

A recent meta-analysis of Internet interventions for smoking cessation found mixed evidence regarding effectiveness. One explanation may be differential use of non-assigned cessation treatments-including other Internet programs-that either amplify or mask study intervention effects. We examined the impact of non-assigned treatment use on cessation outcomes in The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation.

METHODS

Participants were randomized to a basic Internet (BI) comparison condition (N = 675), enhanced Internet (EI: N = 651), or EI plus telephone counseling (EI+P: N = 679). The primary outcome was 30-day point prevalence abstinence (ppa) at 3 and 6 months. Assigned intervention use was assessed with automated tracking data. Assessment of non-assigned treatments included pharmacotherapy, behavioral, alternative, and non-study Internet treatments. Univariate and multivariate logistic regression models examined whether non-assigned treatment use was associated with 30-day ppa.

RESULTS

About 70% of participants used at least one non-assigned treatment. A higher rate of non-study Internet treatment among BI participants was the only treatment group difference at both 3 and 6 months. Multivariate models controlling for condition and baseline predictors of non-assigned treatment use showed that high-intensity non-study Internet treatment was positively associated with 30-day ppa at 3 and 6 months, and pharmacotherapy and behavioral treatment use was negatively associated with 30-day ppa at 6 months.

CONCLUSIONS

Non-assigned treatment use is an important factor to consider when evaluating Internet cessation interventions. Results highlight methodological issues in selecting a comparison condition. Researchers should report non-assigned treatment use alongside main trial outcomes.

Smokers' Treatment Expectancies Predict Smoking Cessation Success

INTRODUCTION

Smokers' treatment expectancies may influence their choice of a particular medication as well as their medication experience.

AIMS

This study examined the role of smokers' treatment expectancies to their smoking cessation outcomes in a completed, randomized, placebo-controlled trial of naltrexone for smoking cessation, controlling for perceptions of treatment assignment.

METHODS

Treatment seeking cigarette smokers (N = 315) were randomized to receive either naltrexone (50 mg) or placebo in combination with nicotine patch and behavioral counseling. Expectancies for naltrexone as a smoking cessation aid were assessed at baseline and 4 weeks after the quit date.

RESULTS

More positive baseline medication expectancies predicted higher quit rates at one month in the naltrexone (OR =1.45, p =.04) group but were associated with lower quit rates in the placebo group (OR =.66, p =.03). Maintaining and/or increasing positive medication expectancies in the first month of treatment was associated with better pill adherence during this interval in the naltrexone group (ps <.05). Positive baseline medication expectancies were also associated with the perception of having received naltrexone over placebo among all participants.

CONCLUSIONS

Positive medication expectancies in smokers may contribute to better treatment response. Assessing treatment expectancies and attempting to maintain or improve them may be important for the delivery, evaluation, and targeting of smoking cessation treatments.

Usage and effectiveness of a fully automated, open-access, Spanish Web-based smoking cessation program: randomized controlled trial

BACKGROUND

The Internet is an optimal setting to provide massive access to tobacco treatments. To evaluate open-access Web-based smoking cessation programs in a real-world setting, adherence and retention data should be taken into account as much as abstinence rate.

OBJECTIVE

The objective was to analyze the usage and effectiveness of a fully automated, open-access, Web-based smoking cessation program by comparing interactive versus noninteractive versions.

METHODS

Participants were randomly assigned either to the interactive or noninteractive version of the program, both with identical content divided into 4 interdependent modules. At baseline, we collected demographic, psychological, and smoking characteristics of the smokers self-enrolled in the Web-based program of Universidad Nacional de Educación a Distancia (National Distance Education University; UNED) in Madrid, Spain. The following questionnaires were administered: the anxiety and depression subscales from the Symptom Checklist-90-Revised, the 4-item Perceived Stress Scale, and the Heaviness of Smoking Index. At 3 months, we analyzed dropout rates, module completion, user satisfaction, follow-up response rate, and self-assessed smoking abstinence.

RESULTS

A total of 23,213 smokers were registered, 50.06% (11,620/23,213) women and 49.94% (11,593/23,213) men, with a mean age of 39.5 years (SD 10.3). Of these, 46.10% (10,701/23,213) were married and 34.43% (7992/23,213) were single, 46.03% (10,686/23,213) had university education, and 78.73% (18,275/23,213) were employed. Participants smoked an average of 19.4 cigarettes per day (SD 10.3). Of the 11,861 smokers randomly assigned to the interactive version, 2720 (22.93%) completed the first module, 1052 (8.87%) the second, 624 (5.26%) the third, and 355 (2.99%) the fourth. Completion data was not available for the noninteractive version (no way to record it automatically). The 3-month follow-up questionnaire was completed by 1085 of 23,213 enrolled smokers (4.67%). Among them, 406 (37.42%) self-reported not smoking. No difference between groups was found. Assuming missing respondents continued to smoke, the abstinence rate was 1.74% (406/23,213), in which 22,678 were missing respondents. Among follow-up respondents, completing the 4 modules of the intervention increased the chances of smoking cessation (OR 1.95, 95% CI 1.27-2.97, P<.001), as did smoking 30 minutes (OR 1.58, 95% CI 1.04-2.39, P=.003) or 1 hour after waking (OR 1.93, 95% CI 1.27-2.93, P<.001) compared to smoking within the first 5 minutes after waking.

CONCLUSIONS

The findings suggest that the UNED Web-based smoking cessation program was very accessible, but a high level of attrition was confirmed. This could be related to the ease of enrollment, its free character, and the absence of direct contact with professionals. It is concluded that, in practice, the greater the accessibility to the program, the lower the adherence and retention. Professional support from health services and the payment of a reimbursable fee could prevent high rates of attrition.

"I miss the care even though I know it's just a machine": an explorative study of the relationship between an Internet-based smoking cessation intervention and its participants

This study aimed to investigate how users perceive the different elements of an internet based smoking cessation intervention and to see if the program meet needs and expectations of people in a smoking cessation process. Nine semi-structured interviews were conducted in February 2010. Participants were recruited via the homepage of the smoking cessation program Dit Digitale Stopprogram (Your Digital Quit Program) operated by the Danish Cancer Society. The main result was that participants established a relationship to the program which influenced their smoking cessation process. Participants perceived the program as caring and found it supportive. However, the program also created feelings of frustration, disappointment and anger. Some participants in the last phase of cessation experienced text messages from the program as smoking cues. The study concluded that individual interpretations of the different elements in an Internet-based smoking cessation intervention can have both positive and negative impact on the smoking cessation process of participants.

Randomized trial of a smartphone mobile application compared to text messaging to support smoking cessation

BACKGROUND

Text messaging has successfully supported smoking cessation. This study compares a mobile application with text messaging to support smoking cessation.

MATERIALS AND METHODS

Young adult smokers 18-30 years old (n = 102) participated in a randomized pretest-posttest trial. Smokers received a smartphone application (REQ-Mobile) with short messages and interactive tools or a text messaging system (onQ), managed by an expert system. Self-reported usability of REQ-Mobile and quitting behavior (quit attempts, point-prevalence, 30-day point-prevalence, and continued abstinence) were assessed in posttests.

RESULTS

Overall, 60% of smokers used mobile services (REQ-Mobile, 61%, mean of 128.5 messages received; onQ, 59%, mean of 107.8 messages), and 75% evaluated REQ-Mobile as user-friendly. A majority of smokers reported being abstinent at posttest (6 weeks, 53% of completers; 12 weeks, 66% of completers [44% of all cases]). Also, 37% (25%of all cases) reported 30-day point-prevalence abstinence, and 32% (22% of all cases) reported continuous abstinence at 12 weeks. OnQ produced more abstinence (p<0.05) than REQ-Mobile. Use of both services predicted increased 30-day abstinence at 12 weeks (used, 47%; not used, 20%; p = 0.03).

CONCLUSIONS

REQ-Mobile was feasible for delivering cessation support but appeared to not move smokers to quit as quickly as text messaging. Text messaging may work better because it is simple, well known, and delivered to a primary inbox. These advantages may disappear as smokers become more experienced with new handsets. Mobile phones may be promising delivery platforms for cessation services using either smartphone applications or text messaging.

Using multiple imputations to accommodate time-outs in online interventions

BACKGROUND

Accurately estimating the period of time that individuals are exposed to online intervention content is important for understanding program engagement. This can be calculated from time-stamped data reflecting navigation to and from individual webpages. Prolonged periods of inactivity are commonly handled with a time-out feature and assigned a prespecified exposure duration. Unfortunately, this practice can lead to biased results describing program exposure.

OBJECTIVE

The aim of the study was to describe how multiple imputations can be used to better account for the time spent viewing webpages that result in a prolonged period of inactivity or a time-out.

METHODS

To illustrate this method, we present data on time-outs collected from the Q(2) randomized smoking cessation trial. For this analysis, we evaluate the effects on intervention exposure of receiving content written in a prescriptive versus motivational tone. Using multiple imputations, we created five complete datasets in which the time spent viewing webpages that resulted in a time-out were replaced with values estimated with imputation models. We calculated standard errors using Rubin's formulas to account for the variability due to the imputations. We also illustrate how current methods of accounting for time-outs (excluding timed-out page views or assigning an arbitrary viewing time) can influence conclusions about participant engagement.

RESULTS

A total of 63.00% (1175/1865) of participants accessed the online intervention in the Q(2) trial. Of the 6592 unique page views, 683 (10.36%, 683/6592) resulted in a time-out. The median time spent viewing webpages that did not result in a time-out was 1.07 minutes. Assuming participants did not spend any time viewing a webpage that resulted in a time-out, no difference between the two message tones was observed (ratio of mean time online: 0.87, 95% CI 0.75-1.02). Assigning 30 minutes of viewing time to all page views that resulted in a time-out concludes that participants who received content in a motivational tone spent less time viewing content (ratio of mean time online: 0.86, 95% CI 0.77-0.98) than those participants who received content in a prescriptive tone. Using multiple imputations to account for time-outs concludes that there is no difference in participant engagement between the two message tones (ratio of mean time online: 0.87; 95% CI 0.75-1.01).

CONCLUSIONS

The analytic technique chosen can significantly affect conclusions about online intervention engagement. We propose a standardized methodology in which time spent viewing webpages that result in a time-out is treated as missing information and corrected with multiple imputations.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00992264; http://clinicaltrials.gov/ct2/show/NCT00992264 (Archived by WebCite at http://www.webcitation.org/6Kw5m8EkP).

Cost-effectiveness of internet and telephone treatment for smoking cessation: an economic evaluation of The iQUITT Study

BACKGROUND

Internet and telephone treatments for smoking cessation can reach large numbers of smokers. There is little research on their costs and the impact of adherence on costs and effects.

OBJECTIVE

To conduct an economic evaluation of The iQUITT Study, a randomised trial comparing Basic Internet, Enhanced Internet and Enhanced Internet plus telephone counselling ('Phone') at 3, 6, 12 and 18 months.

METHODS

We used a payer perspective to evaluate the average and incremental cost per quitter of the three interventions using intention-to-treat analysis of 30-day single-point prevalence and multiple-point prevalence (MPP) abstinence rates. We also examined results based on adherence. Costs included commercial charges for each intervention. Discounting was not included given the short time horizon.

RESULTS

Basic Internet had the lowest cost per quitter at all time points. In the analysis of incremental costs per additional quitter, Enhanced Internet+Phone was the most cost-effective using both single and MPP abstinence metrics. As adherence increased, the cost per quitter dropped across all arms. Costs per quitter were lowest among participants who used the 'optimal' level of each intervention, with an average cost per quitter at 3 months of US$7 for Basic Internet, US$164 for Enhanced Internet and US$346 for Enhanced Internet+Phone.

CONCLUSIONS

'Optimal' adherence to internet and combined internet and telephone interventions yields the highest number of quitters at the lowest cost. Cost-effective means of ensuring adherence to such evidence-based programmes could maximise their population-level impact on smoking prevalence.

Telephone counselling for smoking cessation

BACKGROUND

Telephone services can provide information and support for smokers. Counselling may be provided proactively or offered reactively to callers to smoking cessation helplines.

OBJECTIVES

To evaluate the effect of proactive and reactive telephone support via helplines and in other settings to help smokers quit.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register for studies of telephone counselling, using search terms including 'hotlines' or 'quitline' or 'helpline'. Date of the most recent search: May 2013.

SELECTION CRITERIA

randomized or quasi-randomised controlled trials in which proactive or reactive telephone counselling to assist smoking cessation was offered to smokers or recent quitters.

DATA COLLECTION AND ANALYSIS

One author identified and data extracted trials, and a second author checked them. The main outcome measure was the risk ratio for abstinence from smoking after at least six months follow-up. We selected the strictest measure of abstinence, using biochemically validated rates where available. We considered participants lost to follow-up to be continuing smokers. Where trials had more than one arm with a less intensive intervention we used only the most similar intervention without the telephone component as the control group in the primary analysis. We assessed statistical heterogeneity amongst subgroups of clinically comparable studies using the I² statistic. We considered trials recruiting callers to quitlines separately from studies recruiting in other settings. Where appropriate, we pooled studies using a fixed-effect model. We used a meta-regression to investigate the effect of differences in planned number of calls, selection for motivation, and the nature of the control condition (self help only, minimal intervention, pharmacotherapy) in the group of studies recruiting in non-quitline settings.

MAIN RESULTS

Seventy-seven trials met the inclusion criteria. Some trials were judged to be at risk of bias in some domains but overall we did not judge the results to be at high risk of bias. Among smokers who contacted helplines, quit rates were higher for groups randomized to receive multiple sessions of proactive counselling (nine studies, > 24,000 participants, risk ratio (RR) for cessation at longest follow-up 1.37, 95% confidence interval (CI) 1.26 to 1.50). There was mixed evidence about whether increasing the number of calls altered quit rates but most trials used more than two calls. Three studies comparing different counselling approaches during a single quitline contact did not detect significant differences. Of three studies that tested the provision of access to a hotline two detected a significant benefit and one did not.Telephone counselling not initiated by calls to helplines also increased quitting (51 studies, > 30,000 participants, RR 1.27; 95% CI 1.20 to 1.36). In a meta-regression controlling for other factors the effect was estimated to be slightly larger if more calls were offered, and in trials that specifically recruited smokers motivated to try to quit. The relative extra benefit of counselling was smaller when it was provided in addition to pharmacotherapy (usually nicotine replacement therapy) than when the control group only received self-help material or a brief intervention.A further eight studies were too diverse to contribute to meta-analyses and are discussed separately. Two compared different intensities of counselling, both of which detected a dose response; one of these detected a benefit of multiple counselling sessions over a single call for people prescribed bupropion. The others tested a variety of interventions largely involving offering telephone counselling as part of a referral or systems change and none detected evidence of effect.

AUTHORS' CONCLUSIONS

Proactive telephone counselling aids smokers who seek help from quitlines. Telephone quitlines provide an important route of access to support for smokers, and call-back counselling enhances their usefulness. There is limited evidence about the optimal number of calls. Proactive telephone counselling also helps people who receive it in other settings. There is some evidence of a dose response; one or two brief calls are less likely to provide a measurable benefit. Three or more calls increase the chances of quitting compared to a minimal intervention such as providing standard self-help materials, or brief advice, or compared to pharmacotherapy alone.

Internet-based interventions for smoking cessation

BACKGROUND

The Internet is now an indispensable part of daily life for the majority of people in many parts of the world. It offers an additional means of effecting changes to behaviour such as smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialized Register. There were no restrictions placed on language of publication or publication date. The most recent search was conducted in April 2013.

SELECTION CRITERIA

We included randomized and quasi-randomized trials. 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.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed and extracted data. Methodological and study quality details were extracted using a standardized form. We extracted smoking cessation outcomes of six months follow-up or more, reporting short-term outcomes where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). Clinical and statistical heterogeneity limited our ability to pool studies.

MAIN RESULTS

This updated review includes a total of 28 studies with over 45,000 participants. Some Internet programmes were intensive and included multiple outreach contacts with participants, whilst others relied on participants to initiate and maintain use.Fifteen trials compared an Internet intervention to a non-Internet-based smoking cessation intervention or to a no-intervention control. Ten of these recruited adults, one recruited young adult university students and two recruited adolescents. Seven of the trials in adults had follow-up at six months or longer and compared an Internet intervention to usual care or printed self help. In a post hoc subgroup analysis, pooled results from three trials that compared interactive and individually tailored interventions to usual care or written self help detected a statistically significant effect in favour of the intervention (RR 1.48, 95% CI 1.11 to 2.78). However all three trials were judged to be at high risk of bias in one domain and high statistical heterogeneity was detected (I² = 53%), with no obvious clinical explanation. Pooled results from two studies of an interactive, tailored intervention involving the Internet and automated phone contacts also detected a significant effect (RR 2.05, 95% CI 1.42 to 2.97, I² = 42%). Results from a sixth study comparing an interactive but non-tailored intervention to control did not detect a significant effect, nor did the seventh study, which compared a non-interactive, non-tailored intervention to control. Three trials comparing Internet interventions to face-to-face or phone counselling also did not detect evidence of an effect, nor did two trials evaluating Internet interventions as adjuncts to other behavioural interventions. A trial in college students increased point prevalence abstinence after 30 weeks but had no effect on sustained abstinence. Two small trials in adolescents did not detect an effect on cessation compared to control.Fourteen trials, all in adult populations, compared different Internet sites or programmes. Pooled estimates from three trials that compared tailored and/or interactive Internet programmes with non-tailored, non-interactive Internet programmes did not detect evidence of an effect (RR 1.12, 95% CI 0.95 to 1.32, I² = 0%). One trial detected evidence of a benefit from a tailored email compared to a non-tailored one, whereas a second trial comparing tailored messages to a non-tailored message did not detect evidence of an effect. Trials failed to detect a benefit of including a mood management component (three trials), or an asynchronous bulletin board.

AUTHORS' CONCLUSIONS

Results suggest that some Internet-based interventions can assist smoking cessation at six months or longer, particularly those which are interactive and tailored to individuals. However, the trials that compared Internet interventions with usual care or self help did not show consistent effects and were at risk of bias. Further research is needed despite 28 studies on the subject. Future studies should carefully consider optimising the interventions which promise most effect such as tailoring and interactivity.

Factors associated with use of automated smoking cessation interventions: findings from the eQuit study

The aim was to better understand structural factors associated with uptake of automated tailored interventions for smoking cessation. In a prospective randomized controlled trial with interventions only offered, not mandated, participants were randomized based on the following: web-based expert system (QuitCoach); text messaging program (onQ); both as an integrated package; the choice of using either or both; or a control condition informed of a static website (not considered here). Participants were 3530 smokers or recent quitters recruited from two sources; those seeking smoking cessation information, mostly recruited over the phone, and a cold-contacted group recruited from an Internet panel. More participants (60.1%) initially accepted the intervention they had been offered than used it (42.5%). Uptake of each intervention differed substantially by both recruitment source and modality (phone or web). onQ was a little more popular overall, especially in the information seeker sample. Highest overall intervention uptake occurred in the choice condition. A web-based intervention is most attractive if the offer to use is made by web, whereas a phone-based intervention is more likely to be used if the offer is made over the phone. Providing automated interventions on multiple platforms allows for maximal choice and greatest overall use of some form of help.