Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Feasibility Randomized Controlled Trial

JMIR Form Res. 2023 Dec 22:7:e48958. doi: 10.2196/48958.


Background: Computer-tailored health communication (CTHC), a widely used strategy to increase the effectiveness of smoking cessation interventions, is focused on selecting the best messages for an individual. More recently, CTHC interventions have been tested using contextual information such as participants' current stress or location to adapt message selection. However, mood has not yet been used in CTCH interventions and may increase their effectiveness.

Objective: This study aims to examine the association of mood and smoking cessation message effectiveness among adults who currently smoke cigarettes.

Methods: In January 2022, we recruited a web-based convenience sample of adults who smoke cigarettes (N=615; mean age 41.13 y). Participants were randomized to 1 of 3 mood conditions (positive, negative, or neutral) and viewed pictures selected from the International Affective Picture System to induce an emotional state within the assigned condition. Participants then viewed smoking cessation messages with topics covering five themes: (1) financial costs or rewards, (2) health, (3) quality of life, (4) challenges of quitting, and (5) motivation or reasons to quit. Following each message, participants completed questions on 3 constructs: message receptivity, perceived relevance, and their motivation to quit. The process was repeated 30 times. We used 1-way ANOVA to estimate the association of the mood condition on these constructs, controlling for demographics, cigarettes per day, and motivation to quit measured during the pretest. We also estimated the association between mood and outcomes for each of the 5 smoking message theme categories.

Results: There was an overall statistically significant effect of the mood condition on the motivation to quit outcome (P=.02) but not on the message receptivity (P=.16) and perceived relevance (P=.86) outcomes. Participants in the positive mood condition reported significantly greater motivation to quit compared with those in the negative mood condition (P=.005). Participants in the positive mood condition reported higher motivation to quit after viewing smoking cessation messages in the financial (P=.03), health (P=.01), quality of life (P=.04), and challenges of quitting (P=.03) theme categories. We also compared each mood condition and found that participants in the positive mood condition reported significantly greater motivation to quit after seeing messages in the financial (P=.01), health (P=.003), quality of life (P=.01), and challenges of quitting (P=.01) theme categories than those in the negative mood condition.

Conclusions: Our findings suggest that considering mood may be important for future CTHC interventions. Because those in the positive mood state at the time of message exposure were more likely to have greater quitting motivations, smoking cessation CTHC interventions may consider strategies to help improve participants' mood when delivering these messages. For those in neutral and negative mood states, focusing on certain message themes (health and motivation to quit) may be more effective than other message themes.

Keywords: adult; cessation; computer-tailored health communication; digital intervention; effectiveness; innovation; mood; motivation; smoking; smoking cessation messages; text mining.