Effectiveness of Text Messaging in Encouraging Smoking Cessation among Non-Communicable Disease Patients: A Randomized Controlled Trial.


Journal

Asian Pacific journal of cancer prevention : APJCP
ISSN: 2476-762X
Titre abrégé: Asian Pac J Cancer Prev
Pays: Thailand
ID NLM: 101130625

Informations de publication

Date de publication:
01 Jul 2024
Historique:
received: 23 03 2024
medline: 28 7 2024
pubmed: 28 7 2024
entrez: 28 7 2024
Statut: epublish

Résumé

To assess the impact of a text-messaging intervention on smoking cessation among patients with non-communicable diseases. A total of 200 participants were randomly assigned to either a text-messaging intervention group or a control group. The 7-day point prevalence of smoking cessation and exhaled carbon monoxide (CO) levels were measured at baseline, 6 weeks, and 18 weeks. Mixed linear regression was employed to examine the interaction effect of exhaled CO between the intervention group and follow-up time. The 7-day point prevalence of smoking cessation increased by 16.16% (95% CI: 10.98, 21.33) at the 6-week follow-up and by 15.46% (95% CI: 10.68, 21.33) at the 18-week follow-up. In the intervention group, exhaled CO was significantly lower compared to the control group at 6 weeks (mean difference: -5.79; 95% CI: -7.26, -4.32) and at 18 weeks (mean difference: -4.19; 95% CI: -5.67, -2.71). The text-messaging intervention proved effective in increasing the prevalence of smoking cessation and reducing carbon monoxide levels among non-communicable disease patients.

Identifiants

pubmed: 39068584
doi: 10.31557/APJCP.2024.25.7.2493
pii:
doi:

Substances chimiques

Carbon Monoxide 7U1EE4V452

Types de publication

Journal Article Randomized Controlled Trial

Langues

eng

Sous-ensembles de citation

IM

Pagination

2493-2498

Auteurs

Odd Saksiri (O)

PhD in Health Science Program, Faculty of Medicine, Mahasarakham University, Thailand.

Nirun Intarut (N)

Department of Health Systems Science,, Faculty of Medicine, Mahasarakham University, Muang, Mahasarakham, Thailand.

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Classifications MeSH