Combining Web-Based Attentional Bias Modification and Approach Bias Modification as a Self-Help Smoking Intervention for Adult Smokers Seeking Online Help: Double-Blind Randomized Controlled Trial.

Si Wen,Joeri B G Van Wijngaarden,Thomas Pronk,Helle Larsen,Raoul P P P Grasman,Marilisa Boffo,Reinout W Wiers

doi:10.2196/16342

Abstract

BackgroundAutomatically activated cognitive motivational processes such as the tendency to attend to or approach smoking-related stimuli (ie, attentional and approach bias) have been related to smoking behaviors. Therefore, these cognitive biases are thought to play a role in maintaining smoking behaviors. Cognitive biases can be modified with cognitive bias modification (CBM), which holds promise as an easy-access and low-cost online intervention. However, little is known about the effectiveness of online interventions combining two varieties of CBM. Targeting multiple cognitive biases may improve treatment outcomes because these biases have been shown to be relatively independent.ObjectiveThis study aimed to test the individual and combined effects of two web-based CBM varieties—attentional bias modification (AtBM) and approach bias modification (ApBM)—in a double-blind randomized controlled trial (RCT) with a 2 (AtBM: active versus sham) × 2 (ApBM: active versus sham) factorial design.MethodsA total of 504 adult smokers seeking online help to quit smoking were randomly assigned to 1 of 4 experimental conditions to receive 11 fully automated CBM training sessions. To increase participants’ intrinsic motivation to change their smoking behaviors, all participants first received brief, automated, tailored feedback. The primary outcome was point prevalence abstinence during the study period. Secondary outcomes included daily cigarette use and attentional and approach bias. All outcomes were repeatedly self-assessed online from baseline to the 3-month follow-up. For the examination of training effects on outcome changes, an intention-to-treat analysis with a multilevel modeling (MLM) approach was adopted.ResultsOnly 10.7% (54/504) of the participants completed all 11 training sessions, and 8.3% (42/504) of the participants reached the 3-month follow-up assessment. MLM showed that over time, neither AtBM or ApBM nor a combination of both differed from their respective sham training in point prevalence abstinence rates (P=.17, P=.56, and P=.14, respectively), and in changes in daily cigarette use (P=.26, P=.08, and P=.13, respectively), attentional bias (P=.07, P=.81, and P=.15, respectively), and approach bias (P=.57, P=.22, and P=.40, respectively), while daily cigarette use decreased over time across conditions for all participants (P<.001).ConclusionsThis RCT provides no support for the effectiveness of combining AtBM and ApBM in a self-help web-based smoking cessation intervention. However, this study had a very high dropout rate and a very low frequency of training usage, indicating an overall low acceptability of the intervention, which precludes any definite conclusion on its efficacy. We discuss how this study can inform future designs and settings of online CBM interventions.Trial RegistrationNetherlands Trial Register NTR4678; https://www.trialregister.nl/trial/4678

Highlights

BackgroundSmoking is one of the major risk factors for preventable diseases and premature deaths [1]
multilevel modeling (MLM) showed that over time, neither attentional bias modification (AtBM) or approach bias modification (ApBM) nor a combination of both differed from their respective sham training in point prevalence abstinence rates (P=.17, P=.56, and P=.14, respectively), and in changes in daily cigarette use (P=.26, P=.08, and P=.13, respectively), attentional bias (P=.07, P=.81, and P=.15, respectively), and approach bias (P=.57, P=.22, and P=.40, respectively), while daily cigarette use decreased over time across conditions for all participants (P
This randomized controlled trial (RCT) provides no support for the effectiveness of combining AtBM and ApBM in a self-help web-based smoking cessation intervention

Summary

Introduction

BackgroundSmoking is one of the major risk factors for preventable diseases and premature deaths [1]. Smokers have been found to selectively pay more attention to smoking-related cues in the environment (ie, smoking-related attentional bias) and to impulsively reach out to these smoking-related cues (ie, smoking-related approach bias [6,7,8,9]) These biases have been related to the urge to smoke, the severity of nicotine dependence, and relapse rates [8,9,10,11]. Activated cognitive motivational processes such as the tendency to attend to or approach smoking-related stimuli (ie, attentional and approach bias) have been related to smoking behaviors. These cognitive biases are thought to play a role in maintaining smoking behaviors. Targeting multiple cognitive biases may improve treatment outcomes because these biases have been shown to be relatively independent

Methods

Results

Discussion

Conclusion