Effect of the School-Based Asthma Care for Teens (SB-ACT) program on asthma morbidity: a 3-arm randomized controlled trial

JOURNAL OF ASTHMA(2022)

引用 6|浏览19
暂无评分
摘要
Urban adolescents with asthma often have inadequate preventive care. We tested the effectiveness of the School-Based Asthma Care for Teens (SB-ACT) program on asthma morbidity and preventive medication adherence. Methods: Subjects/Setting- 12-16yr olds with persistent asthma in Rochester, NY schools. Design- 3-group randomized trial (2014-2019). SB-ACT Intervention- Two core components: 1) Directly observed therapy (DOT) of preventive asthma medications, provided in school for at least 6-8 weeks for the teen to learn proper technique and experience the benefits of daily preventive therapy; 2) 4-6 weeks later, 3 sessions of motivational interviewing (MI) to discuss potential benefits from DOT and enhance motivation to take medication independently. We included 2 comparison groups: 1) DOT-only for 6-8wks, and 2) asthma education (AE) attention control. Masked follow-up assessments were conducted at 3, 5, and 7mos. Outcomes- Mean number of symptom-free days (SFDs)/2 weeks and medication adherence. Analyses- Modified intention-to-treat repeated measures analysis. Results: We enrolled 430 teens (56% Black, 32% Hispanic, 85% Medicaid). There were no group differences at baseline. We found no difference in SFDs at any follow-up timepoint. More teens in the SB-ACT and DOT-only groups reported having a preventive asthma medication at each follow-up (p<.001), and almost daily adherence at 3 and 5-months (p<.001, p=.003) compared to AE. By 7 months there were no significant differences between groups in adherence (p=.49). Conclusion: SB-ACT improved preventive medication availability and short-term adherence but did not impact asthma symptoms. Further work is needed to create developmentally appropriate and effective interventions for this group.
更多
查看译文
关键词
Adherence, adolescents, motivational interviewing, symptoms, schools, urban, directly observed therapy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要