Trial reportJMIR mHealth and uHealth2026
Individualized Treatment Effects of a Digital Smoking Cessation Intervention Among Individuals Looking Online for Help: Secondary Analysis of a Randomized Controlled Trial.
Trial report in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Effectiveness of the Components of a Digital Multiple Health Behavior Change Intervention Among Individuals Seeking Help Online (Coach): Factorial Randomized Trial.Journal of medical Internet research · 2026Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Smoking is a leading cause of mortality and morbidity worldwide. Efforts to reduce smoking prevalence have used SMS text message-based interventions, which typically send participants a series of short, informational, motivational, and practical messages over a set period. Evidence highlights the efficacy of using this approach to support smoking cessation, with such trials typically reporting the average treatment effects, in which causal inference is made regarding the average effect of a treatment on a heterogeneous sample. Nonetheless, using this approach to assessing treatment effects means we are unable to account for individual factors that impact the effectiveness of a treatment on outcomes, such as age, gender, and genetics. Objective: This study aimed to estimate the individualized effects of an SMS text message-based smoking cessation intervention to ascertain which individuals benefited the most and least during an effectiveness trial. Methods: Data from a randomized controlled trial including 1012 adults from the Swedish general population were used. The trial assessed the effects of an SMS text message-based intervention, NEXit (Nicotine Exit), that aimed to change behavior by increasing the importance of change, boosting knowledge on how to change, and instilling confidence for change. Outcomes assessed in the trial were prolonged abstinence and point prevalence of smoking cessation. Individualized treatment effects were modeled using baseline factors (demographics, psychosocial variables, and past behavior) to study who benefited the most and least from the intervention. Results: For prolonged abstinence, there was evidence of heterogeneous effects, with those benefiting the most from NEXit being older adults, female participants, individuals with high confidence in their ability to quit, and those who believed that quitting was important. For point prevalence abstinence, older individuals and those reporting high confidence in the ability to quit, the importance of quitting, and knowledge for change benefited the most. For both outcomes, individuals who reported smoking for a longer duration and smoking more at baseline benefited less. Conclusions: The results demonstrate how individuals respond differently to an SMS text message-based smoking cessation intervention. This provides an insight into who benefits the most and least from the intervention in terms of demographics, baseline characteristics, and behaviors. The study highlights which individuals need to be specifically targeted and/or have content developed to suit their individual needs to further reduce the prevalence of smoking.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.