| Summary: | Aim
To present the content development study of support messages to be sent via WhatsApp embedded to smoking cessation healthcare service to increase the individuals’ success rate.
Methods
After the literature review, 178 key messages were gathered supporting smoking cessation. Similar messages related to "preparation" and "action" phases of the Transtheoretical Model were combined and a total of 60 key messages were obtained. Messages have been transformed into graphic images and sending period has also been determined for each message. Graphic messages were sent to field experts and individuals with quitting experience via an online questionnaire. Participants were asked to rate each graphic message in terms of content and appropriateness of sending period on a Likert-type scale (1: Absolutely no - 5: Absolutely yes). Messages with 4.0 and higher average scores were decided appropriate and, others were revised. After the revision, messages were sent back to the both participant groups again and, they were asked to evaluate with the same scale.
Results
A total of 60 messages were developed (seven for pre-quitting and, 53 for quitting phase). All (n=14) participants (seven from expert and seven from quitters group) were responded in the first round and 10 (71.4%) in the second round. The average score of the messages in the first round; 4.4 ± 1.0 in the expert group, 4.6 ± 0.8 in the quitters group and 4.5 ± 0.9 for all participants. The number of messages below the cutoff point were five (8.3%) in the expert and two (3.3%) in the quitters group. The average score of messages in the second round; 4.9 ± 0.3 in the expert group, 4.7 ± 0.6 in the quitters group and 4.8 ± 0.4 for all participants. In this round, all messages’ average scores were found above (> 4.0) the cut-off point.
Conclusions
Study was conducted with a multidisciplinary participation. Sixty messages were created to support quitters according to stages of Transtheoretical model. A consensus developed on these graphic messages among field experts and individuals with quitting experience in terms of content and sending period.
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