Study protocol: A cluster randomised controlled trial of implementation intentions to reduce smoking initiation in adolescents

Association between age at first reported e-cigarette use and subsequent regular e-cigarette, ever cigarette and regular cigarette use

BACKGROUND AND AIMS

Association of electronic cigarette use and subsequent smoking has received considerable attention, although age of first use has not. This study tested differences in regular (e-cigarettes, cigarettes) and ever (cigarettes) use between e-cigarette user groups: early versus never users, late versus never users, early versus late users and effects of controlling for covariates.

DESIGN

Prospective study with 12- and 24-month follow-up of e-cigarette/cigarette ever/regular use with data from an intervention.

SETTING

Forty-five schools in England (Staffordshire and Yorkshire).

PARTICIPANTS

Never smokers (3289 13-14-year-olds) who were part of a cluster randomized controlled trial.

MEASUREMENTS

The sample was divided into groups of e-cigarette users: early users (at 13-14 years), late users (at 14-15 years) and never users (at 13-14 and 14-15 years). Dependent variables were self-reported regular e-cigarette and cigarette use and ever cigarette use at 15-16 years. Covariates were assessed.

FINDINGS

Early and late users compared with never users were significantly more likely to be regular e-cigarette users [early: odds ratio (OR) = 9.42, 95% confidence interval (CI) = 5.38, 16.49, P < 0.001; late: OR = 6.89, 95% CI = 4.11, 11.54, P < 0.001], ever cigarette users (early: OR = 7.96, 95% CI = 6.02, 10.53, P < 0.001; late: OR = 5.13, 95% CI = 3.85, 6.84, P < 0.001) and regular cigarette users (early: OR = 7.80, 95% CI = 3.99, 15.27, P < 0.001; late: OR = 4.34, 95% CI = 1.93, 9.77, P < 0.001) at age 15-16 years. Late users compared with early users had significantly lower rates of ever use of cigarettes at 15-16 years (OR = 0.48, 95% CI = 0.35, 0.66, P < 0.001), although this difference was non-significant at 12 months after first use of e-cigarettes (OR = 0.89, 95% CI = 0.64, 1.25, P = 0.498). Controlling for covariates did not change the findings.

CONCLUSIONS

Adolescents in England who report using e-cigarettes at age 13-14 years have higher rates of subsequently initiating cigarette use than adolescents who report using e-cigarettes at age 14-15 years, a difference that may be attributable to a longer period of time to initiate cigarette use in former group.

Cognitive-Affective Inconsistency and Ambivalence: Impact on the Overall Attitude-Behavior Relationship

This research explored whether overall attitude is a stronger predictor of behavior when underlying cognitive-affective inconsistency or ambivalence is low versus high. Across three prospective studies in different behaviors and populations (Study 1: eating a low-fat diet, N = 136 adults, eating five fruit and vegetables per day, N = 135 adults; Study 2: smoking initiation, N = 4,933 adolescents; and Study 3: physical activity, N = 909 adults) we tested cognitive-affective inconsistency and ambivalence individually and simultaneously as moderators of the overall attitude-behavior relationship. Across studies, more similar effects were observed for inconsistency compared with ambivalence (in both individual and simultaneous analyses). Meta-analysis across studies supported this conclusion with both cognitive-affective inconsistency and ambivalence being significant moderators when considered on their own, but only inconsistency being significant when tested simultaneously. The reported studies highlight the importance of cognitive-affective inconsistency as a determinant of the strength of overall attitude.

Patterns and predictors of e-cigarette, cigarette and dual use uptake in UK adolescents: evidence from a 24-month prospective study

BACKGROUND AND AIMS

To assess prevalence and predictors of e-cigarettes/cigarettes patterns of use in adolescents in England.

DESIGN

Prospective study with 24-month follow-up of e-cigarette/cigarette ever/regular use with data from an intervention evaluation.

SETTING

Forty-five schools in England (Staffordshire and Yorkshire).

PARTICIPANTS

A total of 3210 adolescents who, at baseline, were aged 13-14 years and had never used e-cigarettes/cigarettes.

MEASUREMENTS

Based on e-cigarette/cigarette ever use at follow-up, six groups were created: (a) never user, (b) e-cigarette only, (c) cigarette only, (d) dual use-order of use unclear, (e) dual use-e-cigarettes used first and (f) dual use-cigarettes used first. Baseline measures were: gender, ethnicity, socio-economic status, impulsivity, family plus friend smoking and smoking-related beliefs (attitude and perceived behavioural control).

FINDINGS

In groups (a) to (f), there were 71.5, 13.3, 3.3, 5.7, 2.9 and 3.4% adolescents, respectively. Among groups using cigarettes, regular smoking was more prevalent in group (f) (dual use-cigarettes used first) [17.6%, 95% confidence interval (CI) = 10.4, 24.8] than in groups (c), (d) and (e) combined (7.3%, 95% CI = 4.7, 9.9). Among groups using e-cigarettes, regular use was less prevalent in group (b) (e-cigarette only) (1.9%, 95% CI = 0.6, 3.2) than in groups (d), (e) and (f) combined (12.2%, 95% CI = 8.9, 15.5). Higher impulsivity plus friends and family smoking were predictive of being in groups (b) to (f) compared with group (a) (never users). Males were more likely to be in group (b) compared to group (a); females were more likely to be in groups (c) to (f) compared to group (a).

CONCLUSIONS

Regular use of e-cigarettes/cigarettes varies across groups defined by ever use of e-cigarettes/cigarettes. Interventions targeted at tackling impulsivity or adolescents whose friends and family members smoke may represent fruitful avenues for future research.

Evidence that an intervention weakens the relationship between adolescent electronic cigarette use and tobacco smoking: a 24-month prospective study

BACKGROUND

The electronic cigarette (e-cigarette) use to subsequent smoking relationship in adolescents has received much attention. Whether an intervention to reduce smoking initiation attenuated this relationship was assessed.

METHOD

Data were from 3994 adolescent never smokers (aged 13-14 years at baseline) as part of a cluster randomised controlled trial. Self-report measures of smoking, e-cigarette use and covariates were assessed and used to predict ever smoked cigarettes, any recent tobacco smoking and regularly smoked cigarettes at 24-month follow-up.

RESULTS

Baseline ever use of e-cigarettes was associated with ever smoked cigarettes (OR=4.03, 95% CI 3.33 to 4.88; controlling for covariates, OR=2.78, 95% CI 2.20 to 3.51), any recent tobacco smoking (OR=3.38, 95% CI 2.72 to 4.21; controlling for covariates, OR=2.17, 95% CI 1.76 to 2.69) and regularly smoked cigarettes (OR=3.60, 95% CI 2.35 to 5.51; controlling for covariates, OR=1.27, 95% CI 1.17 to 1.39) at follow-up. For ever smoked cigarettes only, the impact of e-cigarette use was attenuated in the intervention (OR=1.83) compared with control (OR=4.53) condition. For ever smoked cigarettes and any recent tobacco smoking, the impact of e-cigarette use was attenuated among those with friends who smoked (OR=2.05 (ever smoked); 1·53 (any tobacco use)) compared with those without friends who smoked (OR=3.32 (ever smoked); 2·17 (any tobacco use)).

CONCLUSIONS

This is one of the first studies to show that e-cigarette use was robustly associated with measures of smoking over 24 months and the first to show an intervention to attenuate the relationship. Further research with a broader age range of adolescents is required.

Effectiveness and cost-effectiveness of repeated implementation intention formation on adolescent smoking initiation: A cluster randomized controlled trial

OBJECTIVE

Forming implementation intentions (if-then plans) about how to refuse cigarette offers plus antismoking messages was tested for reducing adolescent smoking.

METHOD

Cluster randomized controlled trial with schools randomized (1:1) to receive implementation intention intervention and messages targeting not smoking (intervention) or completing homework (control). Adolescents (11-12 years at baseline) formed implementation intentions and read messages on 8 occasions over 4 years meaning masking treatment allocation was not possible. Outcomes were: follow-up (48 months) ever smoking, any smoking in last 30 days, regular smoking, and breath carbon monoxide levels. Analyses excluded baseline ever smokers, controlled for clustering by schools and examined effects of controlling for demographic variables. Economic evaluation (incremental cost effectiveness ratio; ICER) was conducted. Trial is registered (ISRCTN27596806).

RESULTS

Schools were randomly allocated (September-October 2012) to intervention (n = 25) or control (n = 23). At follow-up, among 6,155 baseline never smokers from 45 retained schools, ever smoking was significantly lower (RR = 0.83, 95% CI [0.71, 0.97], p = .016) in intervention (29.3%) compared with control (35.8%) and remained so controlling for demographics. Similar patterns observed for any smoking in last 30 days. Less consistent effects were observed for regular smoking and breath carbon monoxide levels. Economic analysis yielded an ICER of $134 per ever smoker avoided at age 15-16 years.

CONCLUSIONS

This pragmatic trial supports the use of repeated implementation intentions about how to refuse the offer of a cigarette plus antismoking messages as an effective and cost-effective intervention to reduce smoking initiation in adolescents. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Strategies for enhancing the implementation of school-based policies or practices targeting risk factors for chronic disease

BACKGROUND

A number of school-based policies or practices have been found to be effective in improving child diet and physical activity, and preventing excessive weight gain, tobacco or harmful alcohol use. Schools, however, frequently fail to implement such evidence-based interventions.

OBJECTIVES

The primary aims of the review are to examine the effectiveness of strategies aiming to improve the implementation of school-based policies, programs or practices to address child diet, physical activity, obesity, tobacco or alcohol use.Secondary objectives of the review are to: Examine the effectiveness of implementation strategies on health behaviour (e.g. fruit and vegetable consumption) and anthropometric outcomes (e.g. BMI, weight); describe the impact of such strategies on the knowledge, skills or attitudes of school staff involved in implementing health-promoting policies, programs or practices; describe the cost or cost-effectiveness of such strategies; and describe any unintended adverse effects of strategies on schools, school staff or children.

SEARCH METHODS

All electronic databases were searched on 16 July 2017 for studies published up to 31 August 2016. We searched the following electronic databases: Cochrane Library including the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; MEDLINE In-Process & Other Non-Indexed Citations; Embase Classic and Embase; PsycINFO; Education Resource Information Center (ERIC); Cumulative Index to Nursing and Allied Health Literature (CINAHL); Dissertations and Theses; and SCOPUS. We screened reference lists of all included trials for citations of other potentially relevant trials. We handsearched all publications between 2011 and 2016 in two specialty journals (Implementation Science and Journal of Translational Behavioral Medicine) and conducted searches of the WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/) as well as the US National Institutes of Health registry (https://clinicaltrials.gov). We consulted with experts in the field to identify other relevant research.

SELECTION CRITERIA

'Implementation' was defined as the use of strategies to adopt and integrate evidence-based health interventions and to change practice patterns within specific settings. We included any trial (randomised or non-randomised) conducted at any scale, with a parallel control group that compared a strategy to implement policies or practices to address diet, physical activity, overweight or obesity, tobacco or alcohol use by school staff to 'no intervention', 'usual' practice or a different implementation strategy.

DATA COLLECTION AND ANALYSIS

Citation screening, data extraction and assessment of risk of bias was performed by review authors in pairs. Disagreements between review authors were resolved via consensus, or if required, by a third author. Considerable trial heterogeneity precluded meta-analysis. We narratively synthesised trial findings by describing the effect size of the primary outcome measure for policy or practice implementation (or the median of such measures where a single primary outcome was not stated).

MAIN RESULTS

We included 27 trials, 18 of which were conducted in the USA. Nineteen studies employed randomised controlled trial (RCT) designs. Fifteen trials tested strategies to implement healthy eating policies, practice or programs; six trials tested strategies targeting physical activity policies or practices; and three trials targeted tobacco policies or practices. Three trials targeted a combination of risk factors. None of the included trials sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials examined multi-strategic implementation strategies and no two trials examined the same combinations of implementation strategies. The most common implementation strategies included educational materials, educational outreach and educational meetings. For all outcomes, the overall quality of evidence was very low and the risk of bias was high for the majority of trials for detection and performance bias.Among 13 trials reporting dichotomous implementation outcomes-the proportion of schools or school staff (e.g. classes) implementing a targeted policy or practice-the median unadjusted (improvement) effect sizes ranged from 8.5% to 66.6%. Of seven trials reporting the percentage of a practice, program or policy that had been implemented, the median unadjusted effect (improvement), relative to the control ranged from -8% to 43%. The effect, relative to control, reported in two trials assessing the impact of implementation strategies on the time per week teachers spent delivering targeted policies or practices ranged from 26.6 to 54.9 minutes per week. Among trials reporting other continuous implementation outcomes, findings were mixed. Four trials were conducted of strategies that sought to achieve implementation 'at scale', that is, across samples of at least 50 schools, of which improvements in implementation were reported in three trials.The impact of interventions on student health behaviour or weight status were mixed. Three of the eight trials with physical activity outcomes reported no significant improvements. Two trials reported reductions in tobacco use among intervention relative to control. Seven of nine trials reported no between-group differences on student overweight, obesity or adiposity. Positive improvements in child dietary intake were generally reported among trials reporting these outcomes. Three trials assessed the impact of implementation strategies on the attitudes of school staff and found mixed effects. Two trials specified in the study methods an assessment of potential unintended adverse effects, of which, they reported none. One trial reported implementation support did not significantly increase school revenue or expenses and another, conducted a formal economic evaluation, reporting the intervention to be cost-effective. Trial heterogeneity, and the lack of consistent terminology describing implementation strategies, were important limitations of the review.

AUTHORS' CONCLUSIONS

Given the very low quality of the available evidence, it is uncertain whether the strategies tested improve implementation of the targeted school-based policies or practices, student health behaviours, or the knowledge or attitudes of school staff. It is also uncertain if strategies to improve implementation are cost-effective or if they result in unintended adverse consequences. Further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.

Do electronic cigarettes increase cigarette smoking in UK adolescents? Evidence from a 12-month prospective study

BACKGROUND

In cross-sectional surveys, increasing numbers of adolescents report using both electronic cigarettes (e-cigarettes) and cigarettes. This study assessed whether adolescent e-cigarette use was associated prospectively with initiation or escalation of cigarette use.

METHODS

Data were from 2836 adolescents (aged 13-14 years at baseline) in 20 schools in England. At baseline, breath carbon monoxide levels, self-reported e-cigarette and cigarette use, sex, age, friends and family smoking, beliefs about cigarette use and percentage receiving free school meals (measure of socioeconomic status) were assessed. At 12-month follow-up, self-reported cigarette use was assessed and validated by breath carbon monoxide levels.

RESULTS

At baseline, 34.2% of adolescents reported ever using e-cigarettes (16.0% used only e-cigarettes). Baseline ever use of e-cigarettes was strongly associated with subsequent initiation (n=1726; OR 5.38, 95% CI 4.02 to 7.22; controlling for covariates, OR 4.06, 95% CI 2.94 to 5.60) and escalation (n=318; OR 1.91, 95% CI 1.14 to 3.21; controlling for covariates, this effect became non-significant, OR 1.39, 95% CI 0.97 to 1.82) of cigarette use.

CONCLUSIONS

This is the first study to report prospective relationships between ever use of e-cigarettes and initiation and escalation of cigarette use among UK adolescents. Ever use of e-cigarettes was robustly associated with initiation but more modestly related to escalation of cigarette use. Further research with longer follow-up in a broader age range of adolescents is required.