Effects of a Text Messaging Smoking Cessation Intervention Among Online Help Seekers and Primary Health Care Visitors in Sweden: Protocol for a Randomized Controlled Trial Using a Bayesian Group Sequential Design

Implementing smoking cessation in routine primary care-a qualitative study

Background

The use of digital tools has been proposed as a solution to some of the challenges of providing preventative services in primary care. Although there is a general acceptance among patients to use digital self-help tools to quit smoking, and healthcare organizations are increasingly urged to incorporate these tools in clinical practice, it is unclear how and for whom these innovations can be incorporated into clinical practice.

Objectives

To explore health care professionals' perceptions about smoking cessation practice in routine primary care and the use of digital tools in this work.

Methods

A qualitative study with nine in-depth telephone interviews with health care professionals working in primary care in Sweden. Convenience sampling and snowball technique was used as recruitment strategy. Informants included registered, district and auxiliary nurses as well as behavioral therapists. All informants were female, between 43 and 57 years old and experience of working with smoking cessation in primary care and possibility to recommend digital interventions to smokers.

Results

Informants described smoking cessation practice in primary care as (i) identifying smoking patients, (ii) pursuing standardized routines for smoking cessation practice and (iii) keeping smoking cessation practice on the agenda. Digital tools were described by informants to be used in different ways: (i) replicating practice, (ii) complementing practice and (iii) enabling access to health care practitioners. Finally, the analysis showed that patients' expectations and behaviors contributed to how and when smoking cessation practice was conducted, including the use of digital tools.

Conclusions

Implementing smoking cessation practice in primary care in Sweden encompass continuous work of reaching smoking patients, building buy-in among peers and keeping tobacco on the practice agenda. Digital interventions are used to replicate, complement and enabling access to care. The findings suggest that poor continuity of staff and negative attitudes towards preventative work may challenge smoking cessation practice. However, societal changes in the awareness of the health risks of tobacco use including shifting social norms regarding the acceptance of smoking may contribute to a normalization of speaking about smoking in primary care practice. Increased knowledge is needed on how, and for whom digital tools can be incorporated in clinical practice.

Effects of a text messaging smoking cessation intervention amongst online help-seekers and primary health care visitors: findings from a randomised controlled trial

BACKGROUND

Smoking continues to be a leading risk factor for several diseases globally. We hypothesised that an intervention delivered via text messages could help individuals who were looking to quit.

METHODS

A two-arm, parallel-groups, randomised controlled trial was employed. Both groups received treatment as usual, with the intervention group also receiving a 12-week text messaging intervention. Participants were adult, weekly or more frequent smokers, recruited online and in primary health care centres. Research personnel were blinded, while participants were not. Primary outcomes were prolonged abstinence and point prevalence of abstinence, 3 and 6 months post-randomisation. All randomised participants were included in analyses.

RESULTS

Between 18 September 2020 and 16 June 2022, we randomised 1012 participants (intervention: 505, control: 507). Outcome data was available for 67% (n = 682) of participants at 3 months and 64% (n = 643) at 6 months. At 3 months, the odds ratio (OR) of prolonged abstinence was 2.15 (95% compatibility interval [CoI] = 1.51; 3.06, probability of effect [POE] > 99.9%, p < 0.0001), and for point prevalence of abstinence, it was 1.70 (95% CoI = 1.18; 2.44, POE = 99.8%, p = 0.0034) in favour of the text messaging intervention. At 6 months, the OR of prolonged abstinence was 2.38 (95% CoI = 1.62; 3.57, POE > 99.9%, p =  < 0.0001), and for point prevalence, it was 1.49 (95% CoI = 1.03; 2.14, POE = 98.3%, p = 0.0349) in favour of the text messaging intervention. Analyses with imputed data were not markedly different.

CONCLUSIONS

Amongst general population help-seekers-who on average had smoked for 25 years-access to a 12-week text messaging intervention produced higher rates of self-reported smoking abstinence in comparison to treatment as usual only. The intervention could be part of the societal response to the burden which smoking causes; however, findings are limited by risk of bias due to attrition, self-reported outcomes, and lack of blinding.

TRIAL REGISTRATION

The trial was preregistered in the ISRCTN registry on 27/07/2020 (ISRCTN13455271).

Avoiding Under- and Overrecruitment in Behavioral Intervention Trials Using Bayesian Sequential Designs: Tutorial

Reducing research waste and protecting research participants from unnecessary harm should be top priorities for researchers studying interventions. However, the traditional use of fixed sample sizes exposes trials to risks of under- and overrecruitment by requiring that effect sizes be determined a priori. One mitigating approach is to adopt a Bayesian sequential design, which enables evaluation of the available evidence continuously over the trial period to decide when to stop recruitment. Target criteria are defined, which encode researchers' intentions for what is considered findings of interest, and the trial is stopped once the scientific question is sufficiently addressed. In this tutorial, we revisit a trial of a digital alcohol intervention that used a fixed sample size of 2129 participants. We show that had a Bayesian sequential design been used, the trial could have ended after collecting data from approximately 300 participants. This would have meant exposing far fewer individuals to trial procedures, including being allocated to the waiting list control condition, and the evidence from the trial could have been made public sooner.

Effectiveness of a digital intervention versus alcohol information for online help-seekers in Sweden: a randomised controlled trial

BACKGROUND

The ubiquity of Internet connectivity, and widespread unmet needs, requires investigations of digital interventions for people seeking help with their drinking. The objective of this study was to test the effectiveness of a digital alcohol intervention compared to existing online resources for help seekers.

METHODS

This parallel randomised controlled trial included 2129 risky drinkers with access to a mobile phone and aged 18 years or older. Randomised sub-studies investigated consent procedures and control group design. Simple computerised randomisation was used. Participants were aware of allocation after randomisation; research personnel were not. The digital intervention was designed around weekly monitoring of alcohol consumption followed by feedback and tools for behaviour change. Primary outcomes were total weekly consumption (TWC) and frequency of heavy episodic drinking (HED), measured 2 and 4 months post-randomisation.

RESULTS

Between 25/04/2019 and 26/11/2020, 2129 participants were randomised (intervention: 1063, control: 1066). Negative binomial regression was used to contrast groups, with both Bayesian and maximum likelihood inference. The posterior median incidence rate ratio (IRR) of TWC was 0.89 (95% CI = 0.81;0.99, 98.2% probability of effect, P-value = 0.033) at 2 months among 1557 participants and 0.77 (95% CI = 0.69;0.86, > 99.9% probability of effect, P-value < 0.001) at 4 months among 1429 participants. For HED, the IRR was 0.83 (95% CI = 0.75;0.93, > 99.9% probability of effect, P-value = 0.0009) at 2 months among 1548 participants and 0.71 (95% CI = 0.63;0.79, probability of effect > 99.9%, P-value < 0.0001) at 4 months among 1424 participants. Analyses with imputed data were not markedly different.

CONCLUSIONS

A digital alcohol intervention produced self-reported behaviour change among online help seekers in the general population. The internal and external validity of this trial is strong, subject to carefully considered study limitations arguably inherent to trials of this nature. Limitations include higher than anticipated attrition to follow-up and lack of blinding.

TRIAL REGISTRATION

The trial was prospectively registered ( ISRCTN48317451 ).

Strategies to improve smoking cessation rates in primary care

BACKGROUND

Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials).

OBJECTIVES

To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).

MAIN RESULTS

We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.