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

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.


Background and objectives 2a
Scientific background and explanation of rationale Computer-tailored health communication (CTHC) is an effective intervention to help people who smoke to quit because it selects the best messages for an individual using computer algorithms.Delivering CTHC messages by tailored to contextual information about a participant (mood) as part of just-in-time interventions can help optimize the effectiveness of smoking cessation messaging.2b Specific objectives or hypotheses The research question proposed: "According to a mood state, which messages increase motivation to quit, message receptivity, and perceived message relevance?"

Trial design 3a
Description of trial design (such as parallel, factorial) including allocation ratio This study was a cross-sectional, randomized, parallel 3-armed design.Participants were randomly assigned to one of three mood arms in a one-time study.3b Important changes to methods after trial commencement (such as eligibility criteria), with reasons No change from the standard CONSORT item.

Participants 4a
Eligibility criteria for participants Participants were eligible for the study if they currently smoked cigarettes (smoked at least 5 cigarettes a day and have smoked this amount for at least 1 year) and lived in the United States.4b Settings and locations where the data were collected We used Prolific, a web-based crowdsourcing survey platform, for data collection.Interventions 5 The interventions for each group with sufficient details to allow replication, including how and when they were actually administered Each group consisted of 30 mood-induction pictures from the International Affective Picture System selected for each of the mood condition (positive, negative, and neutral mood).Mood manipulation was checked using the PANAS self-report scale items.Then, participants were shown 30 smoking cessation messages in random order that were selected from a panel of health experts and former smokers in a prior study.

Outcomes 6a
Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed The primary outcomes were motivation to quit, message receptivity, and perceived relevance.Motivation to quit outcomes was assessed pre-test and post-test using a single question item.Message receptivity was assessed post-test using 10 items from the message receptivity scale assessing the extent to which the message was appealing, spoke to them, said something important to them, convincing, would motivate persons to prevent smoking, confusing, promote behaviors that are difficult, did not like the messages, and contradicts what they know about smoking.Perceived relevance was assessed post-test using 3 items from the perceived relevance scale assessing the extent to which the message was relevant to their life, grasped their attention, and said something important.6b Any changes to trial outcomes after the trial commenced, with reasons No change from the standard CONSORT item.Sample size 7a How sample size was determined This pilot study was conducted to get a more accurate estimate of the sample sizes needed for a larger, representative sample in the future.Therefore, we did not perform a power analysis for this study.7b When applicable, explanation of any interim analyses and stopping guidelines Preliminary analysis was conducted using paired t-tests to assess pre-test and post-test differences in the primary outcome measure motivation to quit.Randomisation: Sequence generation 8a Method used to generate the random allocation sequence We used Qualtrics' pre-programmed, computer-generated feature to generate the random allocation sequence.8b Type of randomisation; details of any restriction (such as blocking and block size) It was a simple randomization.Allocation concealment mechanism 9 Mechanism used to implement the random allocation sequence (such as sequentially numbered containers), describing any steps taken to conceal the sequence until interventions were assigned Eligible participants were randomized in a 1:1:1 allocation to one of three arms using the Qualtrics' preprogrammed computer-generated random allocation feature.Implementation 10 Who generated the random allocation sequence, who enrolled participants, and who assigned participants to interventions We used Qualtrics' pre-programmed, computer-generated feature to generate the random allocation.We used Prolific for participant recruitment and used Qualtrics' randomization feature to randomly assign the intervention arm.Blinding 11a If done, who was blinded after assignment to interventions (for example, participants, care providers, those assessing outcomes) and how All participants were blinded after the intervention assignment.11b If relevant, description of the similarity of interventions All interventions (mood-induction pictures) were presented in the same format, size, and number (n=30), and in random order.Statistical methods 12a Statistical methods used to compare groups for primary and secondary outcomes We used 1-way ANOVA tests to estimate the association between the intervention and primary outcomes.12b Methods for additional analyses, such as subgroup analyses and adjusted analyses When the overall ANOVA tests were statistically significant, we tested for the pairwise comparison of each arm on the primary outcomes controlling for cigarettes per day, pre-test quitting motivation, age, gender, race, ethnicity, relationship status, self-perceived health, and financial stress.

Results
Participant flow (a diagram is strongly recommended) 13a For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analysed for the primary outcome

Outcomes and estimation
17a For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval) We report the statistical significance 17b For binary outcomes, presentation of both absolute and relative effect sizes is recommended Binary outcomes were not included in analyses.

Ancillary analyses 18
Results of any other analyses performed, including subgroup analyses and adjusted analyses, distinguishing pre-specified from exploratory Ancillary analyses were not performed.Harms 19 All important harms or unintended effects in each group (for specific guidance see CONSORT for harms) Participants were informed about the risks involving feeling psychological discomfort with answering questions about tobacco use and experiencing negative feelings for those assigned to the negative mood arm, and a possibility of breach of confidentiality.

Allocation Analysis Flow diagram of the parallel 3-group randomized trial.
Limitations 20Trial limitations, addressing sources of potential bias, imprecision, and, if relevant, multiplicity of analyses There are limitations involving sample, which consists of largely non-Hispanic White, and use of convenience sampling.Additionally, there is a limitation with cross-sectional design and self-report bias.We strongly recommend reading this statement in conjunction with the CONSORT 2010 Explanation and Elaboration for important clarifications on all the items.If relevant, we also recommend reading CONSORT extensions for cluster randomised trials, non-inferiority and equivalence trials, non-pharmacological treatments, herbal interventions, and pragmatic trials.Additional extensions are forthcoming: for those and for up-to-date references relevant to this checklist, see www.consort-statement.org.
The study was funded by iDAPT P50 Implementation Science Center in Cancer Control (MPI: RSS, EMS).Data analysis and manuscript preparation were additionally supported by R00DA046563(PI: EMS) via National *