Testing a Machine Learning–Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial
BackgroundIndividuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interventions. Computer-tailored health communication, which is focused on finding the most relevant messages for an individual, has b...
Saved in:
| Main Authors: | Ariana Kamberi, Benjamin Weitz, Julie Flahive, Julianna Eve, Reem Najjar, Tara Liaghat, Daniel Ford, Peter Lindenauer, Sharina Person, Thomas K Houston, Megan E Gauvey-Kern, Jackie Lobien, Rajani S Sadasivam |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-04-01
|
| Series: | JMIR Research Protocols |
| Online Access: | https://www.researchprotocols.org/2025/1/e63693 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Protocol for iSISTAQUIT: Implementation phase of the supporting indigenous smokers to assist quitting project.
by: Gillian Sandra Gould Judean, et al.
Published: (2022-01-01) -
The views and experiences of smokers who quit smoking unassisted. A systematic review of the qualitative evidence.
by: Andrea L Smith, et al.
Published: (2015-01-01) -
E-cigarette and cannabis use among current and recently quit smokers: Co-use and Co-cessation
by: Deanna M. Halliday, et al.
Published: (2025-06-01) -
Adaptation of the quiet quitting scale for teachers to Turkish culture: An empirical psychometric investigation
by: Alper Uslukaya, et al.
Published: (2024-09-01) -
Increasing Danger in Business After the Pandemic: Adaptation of the Quiet Quitting Scale to Turkish
by: Tayfun Arar, et al.
Published: (2024-12-01)