PDF(Pubmed)
Abstract：
UNASSIGNED: Determining how individuals engage with digital health interventions over time is crucial to understand and optimize intervention outcomes.
UNASSIGNED: To identify the engagement trajectories with a mobile chat-based smoking cessation intervention and examine its association with biochemically validated abstinence.
UNASSIGNED: A secondary analysis of a pragmatic, cluster randomized clinical trial conducted in Hong Kong with 6-month follow-up. From June 18 to September 30, 2017, 624 adult daily smokers were recruited from 34 community sites randomized to the intervention group. Data were analyzed from March 6 to October 30, 2023.
UNASSIGNED: Chat-based cessation support delivered by a live counselor via a mobile instant messaging app for 3 months from baseline.
UNASSIGNED: Group-based trajectory modeling was used to identify engagement trajectories using the participants\' weekly responses to the messages from the counselor over the 3-month intervention period. The outcome measures were biochemically validated tobacco abstinence at 3-month (end of treatment) and 6-month follow-ups. Covariates included sex, age, educational level, nicotine dependence, past quit attempt, and intention to quit at baseline.
UNASSIGNED: Of 624 participants included in the analysis, 479 were male (76.8%), and the mean (SD) age was 42.1 (16.2) years. Four distinct engagement trajectories were identified: low engagement group (447 [71.6%]), where participants maintained very low engagement throughout; rapid-declining group (86 [13.8%]), where participants began with moderate engagement and rapidly decreased to a low level; gradual-declining group (58 [9.3%]), where participants had high initial engagement and gradually decreased to a moderate level; and high engagement group (58 [5.3%]), where participants maintained high engagement throughout. Compared with the low engagement group, the 6-month validated abstinence rates were significantly higher in the rapid-declining group (adjusted relative risk [ARR], 3.30; 95% CI, 1.39-7.81), gradual-declining group (ARR, 5.17; 95% CI, 2.21-12.11), and high engagement group (ARR, 4.98; 95% CI, 1.82-13.60). The corresponding ARRs (95% CI) of 3-month validated abstinence were 4.03 (95% CI, 1.53-10.59), 5.25 (95% CI, 1.98-13.88), and 9.23 (95% CI, 3.29-25.86).
UNASSIGNED: The findings of this study suggest that higher levels of engagement with the chat-based smoking cessation intervention were associated with greater biochemically validated tobacco abstinence. Improving engagement with digital interventions may increase intervention benefits.
UNASSIGNED: ClinicalTrials.gov Identifier: NCT03182790.
UNASSIGNED: To identify the engagement trajectories with a mobile chat-based smoking cessation intervention and examine its association with biochemically validated abstinence.
UNASSIGNED: A secondary analysis of a pragmatic, cluster randomized clinical trial conducted in Hong Kong with 6-month follow-up. From June 18 to September 30, 2017, 624 adult daily smokers were recruited from 34 community sites randomized to the intervention group. Data were analyzed from March 6 to October 30, 2023.
UNASSIGNED: Chat-based cessation support delivered by a live counselor via a mobile instant messaging app for 3 months from baseline.
UNASSIGNED: Group-based trajectory modeling was used to identify engagement trajectories using the participants\' weekly responses to the messages from the counselor over the 3-month intervention period. The outcome measures were biochemically validated tobacco abstinence at 3-month (end of treatment) and 6-month follow-ups. Covariates included sex, age, educational level, nicotine dependence, past quit attempt, and intention to quit at baseline.
UNASSIGNED: Of 624 participants included in the analysis, 479 were male (76.8%), and the mean (SD) age was 42.1 (16.2) years. Four distinct engagement trajectories were identified: low engagement group (447 [71.6%]), where participants maintained very low engagement throughout; rapid-declining group (86 [13.8%]), where participants began with moderate engagement and rapidly decreased to a low level; gradual-declining group (58 [9.3%]), where participants had high initial engagement and gradually decreased to a moderate level; and high engagement group (58 [5.3%]), where participants maintained high engagement throughout. Compared with the low engagement group, the 6-month validated abstinence rates were significantly higher in the rapid-declining group (adjusted relative risk [ARR], 3.30; 95% CI, 1.39-7.81), gradual-declining group (ARR, 5.17; 95% CI, 2.21-12.11), and high engagement group (ARR, 4.98; 95% CI, 1.82-13.60). The corresponding ARRs (95% CI) of 3-month validated abstinence were 4.03 (95% CI, 1.53-10.59), 5.25 (95% CI, 1.98-13.88), and 9.23 (95% CI, 3.29-25.86).
UNASSIGNED: The findings of this study suggest that higher levels of engagement with the chat-based smoking cessation intervention were associated with greater biochemically validated tobacco abstinence. Improving engagement with digital interventions may increase intervention benefits.
UNASSIGNED: ClinicalTrials.gov Identifier: NCT03182790.
摘要：
■随着时间的推移，确定个人如何参与数字健康干预对于理解和优化干预结果至关重要。
■通过基于移动聊天的戒烟干预来确定参与轨迹，并检查其与生化验证的禁欲的关联。
■对语用的二次分析，整群随机临床试验在香港进行,随访6个月.从2017年6月18日至9月30日，从34个社区地点招募了624名成人每日吸烟者，随机分配到干预组。对2023年3月6日至10月30日的数据进行了分析。
■由现场辅导员通过移动即时消息应用程序提供的基于聊天的戒烟支持，从基线开始3个月。
■使用基于组的轨迹建模来识别参与轨迹，使用参与者在3个月的干预期内每周对辅导员消息的响应。结果指标是在3个月（治疗结束）和6个月随访时进行生化验证的戒烟。协变量包括性别，年龄,教育水平,尼古丁依赖,过去的戒烟尝试，并打算在基线时退出。
■在分析中包括的624名参与者中，479人是男性（76.8%），平均（SD）年龄为42.1（16.2）岁。确定了四个不同的参与轨迹：低参与组(447[71.6%])，参与者在整个过程中保持非常低的参与度；快速下降的群体(86[13.8%])，参与者从适度的参与度开始，并迅速下降到较低水平；逐渐下降的群体(58[9.3%])，参与者初始参与度高，并逐渐下降到中等水平；和高参与度组(58[5.3%])，参与者在整个过程中保持高度参与度。与低参与度群体相比，在快速下降的组中，6个月验证的禁欲率显着更高（调整后的相对风险[ARR]，3.30；95%CI，1.39-7.81），逐渐下降组(ARR，5.17；95%CI，2.21-12.11)，和高参与度小组(ARR，4.98；95%CI，1.82-13.60）。3个月验证禁欲的相应ARR（95％CI）为4.03（95％CI，1.53-10.59），5.25（95%CI，1.98-13.88），和9.23（95%CI，3.29-25.86）。
■这项研究的结果表明，参与基于聊天的戒烟干预的更高水平与更高的生化验证的戒烟相关。改善对数字干预的参与可能会增加干预效益。
■ClinicalTrials.gov标识符：NCT03182790。
■通过基于移动聊天的戒烟干预来确定参与轨迹，并检查其与生化验证的禁欲的关联。
■对语用的二次分析，整群随机临床试验在香港进行,随访6个月.从2017年6月18日至9月30日，从34个社区地点招募了624名成人每日吸烟者，随机分配到干预组。对2023年3月6日至10月30日的数据进行了分析。
■由现场辅导员通过移动即时消息应用程序提供的基于聊天的戒烟支持，从基线开始3个月。
■使用基于组的轨迹建模来识别参与轨迹，使用参与者在3个月的干预期内每周对辅导员消息的响应。结果指标是在3个月（治疗结束）和6个月随访时进行生化验证的戒烟。协变量包括性别，年龄,教育水平,尼古丁依赖,过去的戒烟尝试，并打算在基线时退出。
■在分析中包括的624名参与者中，479人是男性（76.8%），平均（SD）年龄为42.1（16.2）岁。确定了四个不同的参与轨迹：低参与组(447[71.6%])，参与者在整个过程中保持非常低的参与度；快速下降的群体(86[13.8%])，参与者从适度的参与度开始，并迅速下降到较低水平；逐渐下降的群体(58[9.3%])，参与者初始参与度高，并逐渐下降到中等水平；和高参与度组(58[5.3%])，参与者在整个过程中保持高度参与度。与低参与度群体相比，在快速下降的组中，6个月验证的禁欲率显着更高（调整后的相对风险[ARR]，3.30；95%CI，1.39-7.81），逐渐下降组(ARR，5.17；95%CI，2.21-12.11)，和高参与度小组(ARR，4.98；95%CI，1.82-13.60）。3个月验证禁欲的相应ARR（95％CI）为4.03（95％CI，1.53-10.59），5.25（95%CI，1.98-13.88），和9.23（95%CI，3.29-25.86）。
■这项研究的结果表明，参与基于聊天的戒烟干预的更高水平与更高的生化验证的戒烟相关。改善对数字干预的参与可能会增加干预效益。
■ClinicalTrials.gov标识符：NCT03182790。
