Identifying content-based engagement patterns in a smoking cessation website and associations with user characteristics and cessation outcomes: a sequence and cluster analysis

Tobacco smoking is the greatest cause of sickness and early death worldwide, with 8 million people dying each year from a smoking-related condition. The use of pharmaceutical or behavioural assistance improves smokers' chances of quitting; nonetheless, the majority of smoking cessation efforts are unassisted.

Engagement with web-based smoking cessation interventions is a strong predictor of data retention in clinical trials and successful behaviour change.

WebQuit is a web-delivered smoking intervention based on Acceptance and Commitment Therapy (ACT), which suggests that psychological flexibility is supported by six core processes:

• Acceptance
• Cognitive defusion,
• Being present
• Self as context
• Values
• Committed action

Using WebQuit as a case study, a smoking cessation website grounded in ACT, we intended to identify sequence clusters of material consumption and evaluate their connections with baseline features, shift to a critical mechanism of action, and smoking cessation.

Participants were adult smokers assigned to the WebQuit arm in a randomized controlled trial (n = 1,313). WebQuit contains theory-informed content including goal setting, self-monitoring and feedback, and values- and acceptance-based exercises. Similarities between sequences were assessed. Associations between sequence clusters and baseline characteristics, acceptance of cravings at 3 months and self-reported 30-day point prevalence abstinence at 12 months were analyzed with linear and logistic regression.

Three qualitatively different sequence clusters were identified.

• “Disengagers” (576/1,313) almost exclusively used the goal-setting feature.
• “Tryers” (375/1,313) used goal setting and two of the values- and acceptance-based components (“Be Aware,” “Be Willing”).
• “Committers” (362/1,313) primarily used two of the values- and acceptance-based components (“Be Willing,” “Be Inspired”), goal setting, and self-monitoring and feedback.

Committers saw increases in a key mechanism of action and greater odds of quit success. Future WebQuit users may benefit from being directed to the values- and acceptance-based exercises and self-monitoring and feedback features via reminders over the course of the program