Identification of Behavior Change Techniques and Engagement Strategies to Design a Smartphone App to Reduce Alcohol Consumption Using a Formal Consensus Method.
Identification of Behavior Change Techniques and Engagement Strategies to Design a Smartphone App to Reduce Alcohol Consumption Using a Formal Consensus Method.
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DOI：
10.2196/mhealth.3895
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发表时间：
2015-06-29
影响因子：
5
通讯作者：
Michie S
中科院分区：
文献类型：
--
作者：
Garnett C;Crane D;West R;Brown J;Michie S
与传统的简短干预措施相比，减少过度饮酒的数字干预措施可能具有更广泛的影响范围，并且更具成本效益。然而，目前还没有强有力的证据证明它们吸引用户的能力或有效性。本研究旨在通过使用正式的专家共识方法，将行为改变技术 (BCT) 和参与策略纳入智能手机应用程序中以减少饮酒，从而确定最值得进一步研究的行为改变技术 (BCT) 和参与策略。研究的第一阶段包括三轮德尔菲练习。该研究由 7 名酒精和/或行为改变领域的国际专家共同进行。在第一轮中，专家们确定了最有可能有效减少饮酒的 BCT 以及最有可能吸引用户使用应用程序的策略；这些在第二轮中进行了评级；七名参与者中至少有四名被评为有效的将进入第三轮。使用肯德尔 W 一致性系数对排名进行分析，该系数表明参与者之间达成了共识。第二阶段由一个新的独立专家组（n=43）组成，对第一阶段确定的旅战斗队进行排名。使用斯皮尔曼等级相关系数评估两组排名之间的相关性。 12 个 BCT 被认为可能有效。专家们对其排名有一定程度的一致性（W=.465，χ2 11=35.8，P<.001），平均排名最高的 BCT 是自我监控、目标设定、行动计划和与目标相关的反馈。确定 BCT 的专家组与第二个独立专家组对 BCT 的排名之间存在显着相关性（Spearman 的 rho=.690，P=.01）。针对可能吸引用户的策略生成了 17 个回复。专家们对这些参与策略的排名达成了适度的一致（W=.563，χ2 15=59.2，P<.001），平均排名最高的是易用性、设计（美观、反馈、功能）、设计（根据自己的喜好改变设计的能力、定制信息和独特的智能手机功能）。专家认为，最有潜力纳入智能手机应用程序以减少饮酒的 BCT 包括自我监控、目标设定、行动计划以及与目标相关的反馈。最有可能吸引用户的策略是易用性、设计、设计和信息的定制以及独特的智能手机功能。
Digital interventions to reduce excessive alcohol consumption have the potential to have a broader reach and be more cost-effective than traditional brief interventions. However, there is not yet strong evidence for their ability to engage users or their effectiveness. This study aimed to identify the behavior change techniques (BCTs) and engagement strategies most worthy of further study by inclusion in a smartphone app to reduce alcohol consumption, using formal expert consensus methods. The first phase of the study consisted of a Delphi exercise with three rounds. It was conducted with 7 international experts in the field of alcohol and/or behavior change. In the first round, experts identified BCTs most likely to be effective at reducing alcohol consumption and strategies most likely to engage users with an app; these were rated in the second round; and those rated as effective by at least four out of seven participants were ranked in the third round. The rankings were analyzed using Kendall’s W coefficient of concordance, which indicates consensus between participants. The second phase consisted of a new, independent group of experts (n=43) ranking the BCTs that were identified in the first phase. The correlation between the rankings of the two groups was assessed using Spearman’s rank correlation coefficient. Twelve BCTs were identified as likely to be effective. There was moderate agreement among the experts over their ranking (W=.465, χ2 11=35.8, P<.001) and the BCTs receiving the highest mean rankings were self-monitoring, goal-setting, action planning, and feedback in relation to goals. There was a significant correlation between the ranking of the BCTs by the group of experts who identified them and a second independent group of experts (Spearman’s rho=.690, P=.01). Seventeen responses were generated for strategies likely to engage users. There was moderate agreement among experts on the ranking of these engagement strategies (W=.563, χ2 15=59.2, P<.001) and those with the highest mean rankings were ease of use, design – aesthetic, feedback, function, design – ability to change design to suit own preferences, tailored information, and unique smartphone features. The BCTs with greatest potential to include in a smartphone app to reduce alcohol consumption were judged by experts to be self-monitoring, goal-setting, action planning, and feedback in relation to goals. The strategies most likely to engage users were ease of use, design, tailoring of design and information, and unique smartphone features.