Department of Medicine, University of Pennyslvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America.
Penn Medicine Nudge Unit, University of Pennyslvania, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2020 Oct 14;15(10):e0239288. doi: 10.1371/journal.pone.0239288. eCollection 2020.
Participants often vary in their response to behavioral interventions, but methods to identify groups of participants that are more likely to respond are lacking. In this secondary analysis of a randomized clinical trial, we used baseline characteristics to group participants into distinct behavioral phenotypes and evaluated differential responses to a physical activity intervention. Latent class analysis was used to segment participants based on baseline participant data including demographics, validated measures of psychosocial variables, and physical activity behavior. The trial included 602 adults from 40 U.S. states with body mass index ≥25 who were randomized to control or one of three gamification interventions (supportive, collaborative, or competitive) to increase physical activity. Daily step counts were monitored using a wearable device for a 24-week intervention with 12 weeks of follow-up. The model segmented participants into three classes named for key defining traits: Class 1, extroverted and motivated; Class 2, less active and less social; Class 3, less motivated and at-risk. Adjusted regression models were used to test for differences in intervention response relative to control within each behavioral phenotype. In Class 1, only participants in the competitive arm increased their mean daily steps during the intervention (adjusted difference, 945; 95% CI, 352-1537; P = .002), but it was not sustained during follow-up. In Class 2, participants in all three gamification arms significantly increased their mean daily steps compared to control during the intervention (supportive arm adjusted difference 1172; 95% CI, 363-1980; P = .005; collaborative arm adjusted difference 1119; 95% CI, 319-1919; P = .006; competitive arm adjusted difference 1179; 95% CI, 400-1957; P = .003) and all three had sustained impact during follow-up. In Class 3, none of the interventions had a significant effect on physical activity. Three behavioral phenotypes were identified, each with a different response to the interventions. This approach could be used to better target behavioral interventions to participants that are more likely to respond to them.
参与者对行为干预的反应常常存在差异，但缺乏识别更有可能产生反应的参与者群体的方法。在这项随机临床试验的二次分析中，我们使用基线特征将参与者分为不同的行为表型，并评估了对体育活动干预的不同反应。潜在类别分析用于根据基线参与者数据（包括人口统计学数据、经过验证的心理社会变量测量值和体育活动行为）对参与者进行细分。该试验纳入了来自美国 40 个州的 602 名 BMI≥25 的成年人，他们被随机分配到对照组或三种游戏化干预组（支持性、协作性或竞争性）之一，以增加体育活动。使用可穿戴设备监测 24 周干预和 12 周随访期间的日常步数。该模型将参与者分为三个类，分别以关键定义特征命名：第 1 类，外向且积极；第 2 类，活动量较少且社交较少；第 3 类，积极性较低且处于风险中。使用调整后的回归模型测试每个行为表型内相对于对照组的干预反应差异。在第 1 类中，只有竞争组的参与者在干预期间增加了他们的平均每日步数（调整差异，945；95%CI，352-1537；P=.002），但在随访期间没有持续增加。在第 2 类中，所有三种游戏化干预组的参与者在干预期间与对照组相比，平均每日步数均显著增加（支持组调整差异 1172；95%CI，363-1980；P=.005；协作组调整差异 1119；95%CI，319-1919；P=.006；竞争组调整差异 1179；95%CI，400-1957；P=.003），并且所有三组在随访期间均有持续影响。在第 3 类中，没有一种干预对体育活动有显著影响。确定了三种行为表型，每种表型对干预的反应都不同。这种方法可以用于更好地针对更有可能对干预措施产生反应的参与者进行行为干预。
