Helander Elina, Kaipainen Kirsikka, Korhonen Ilkka, Wansink Brian
Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
J Med Internet Res. 2014 Apr 15;16(4):e109. doi: 10.2196/jmir.3084.
Healthy eating interventions that use behavior change techniques such as self-monitoring and feedback have been associated with stronger effects. Mobile apps can make dietary self-monitoring easy with photography and potentially reach huge populations.
The aim of the study was to assess the factors related to sustained use of a free mobile app ("The Eatery") that promotes healthy eating through photographic dietary self-monitoring and peer feedback.
A retrospective analysis was conducted on the sample of 189,770 people who had downloaded the app and used it at least once between October 2011 and April 2012. Adherence was defined based on frequency and duration of self-monitoring. People who had taken more than one picture were classified as "Users" and people with one or no pictures as "Dropouts". Users who had taken at least 10 pictures and used the app for at least one week were classified as "Actives", Users with 2-9 pictures as "Semi-actives", and Dropouts with one picture as "Non-actives". The associations between adherence, registration time, dietary preferences, and peer feedback were examined. Changes in healthiness ratings over time were analyzed among Actives.
Overall adherence was low-only 2.58% (4895/189,770) used the app actively. The day of week and time of day the app was initially used was associated with adherence, where 20.28% (5237/25,820) of Users had started using the app during the daytime on weekdays, in comparison to 15.34% (24,718/161,113) of Dropouts. Users with strict diets were more likely to be Active (14.31%, 900/6291) than those who had not defined any diet (3.99%, 742/18,590), said they ate everything (9.47%, 3040/32,090), or reported some other diet (11.85%, 213/1798) (χ(2) 3=826.6, P<.001). The average healthiness rating from peers for the first picture was higher for Active users (0.55) than for Semi-actives (0.52) or Non-actives (0.49) (F2,58167=225.9, P<.001). Actives wrote more often a textual description for the first picture than Semi-actives or Non-actives (χ(2) 2=3515.1, P<.001). Feedback beyond ratings was relatively infrequent: 3.83% (15,247/398,228) of pictures received comments and 15.39% (61,299/398,228) received "likes" from other users. Actives were more likely to have at least one comment or one "like" for their pictures than Semi-actives or Non-actives (χ(2) 2=343.6, P<.001, and χ(2) 2=909.6, P<.001, respectively). Only 9.89% (481/4863) of Active users had a positive trend in their average healthiness ratings.
Most people who tried out this free mobile app for dietary self-monitoring did not continue using it actively and those who did may already have been healthy eaters. Hence, the societal impact of such apps may remain small if they fail to reach those who would be most in need of dietary changes. Incorporating additional self-regulation techniques such as goal-setting and intention formation into the app could potentially increase user engagement and promote sustained use.
采用自我监测和反馈等行为改变技术的健康饮食干预措施效果更为显著。移动应用程序可通过拍照让饮食自我监测变得轻松，并有潜力覆盖大量人群。
本研究旨在评估与一款免费移动应用程序（“餐厅”）持续使用相关的因素，该应用程序通过饮食拍照自我监测和同伴反馈来促进健康饮食。
对2011年10月至2012年4月期间下载并至少使用过一次该应用程序的189,770人样本进行回顾性分析。根据自我监测的频率和持续时间来定义依从性。拍摄多张照片的人被归类为“使用者”，拍摄一张或未拍摄照片的人被归类为“退出者”。拍摄至少10张照片且使用该应用程序至少一周的使用者被归类为“活跃使用者”，拍摄2 - 9张照片的使用者为“半活跃使用者”，拍摄一张照片的退出者为“非活跃使用者”。研究了依从性、注册时间、饮食偏好和同伴反馈之间的关联。分析了活跃使用者随时间推移健康评分的变化。
总体依从性较低，只有2.58%（4895/189,770）的人积极使用该应用程序。应用程序最初使用的星期几和时间段与依从性相关，其中20.28%（5237/25,820）的使用者在工作日白天开始使用该应用程序，而退出者中这一比例为15.34%（24,718/161,113）。与未定义任何饮食的人（3.99%，742/18,590）、表示什么都吃的人（9.47%，3040/32,090）或报告其他饮食的人（11.85%，213/1798）相比，饮食严格的使用者更有可能成为活跃使用者（14.31%，900/6291）（χ²(3)=826.6，P<.001）。活跃使用者第一张照片获得同伴的平均健康评分（0.55）高于半活跃使用者（0.52）或非活跃使用者（0.49）（F(2,58167)=225.9，P<.001）。活跃使用者为第一张照片撰写文字描述的频率高于半活跃使用者或非活跃使用者（χ²(2)=3515.1，P<.001）。除评分外的反馈相对较少：3.83%（15,247/398,228）的照片收到评论，15.39%（61,299/398,228）的照片收到其他用户的“点赞”。活跃使用者的照片比半活跃使用者或非活跃使用者更有可能至少收到一条评论或一个“赞”（χ²(2)=343.6，P<.001，以及χ²(2)=909.6，P<.001，分别）。只有9.89%（481/4863）的活跃使用者平均健康评分呈上升趋势。
大多数试用这款免费饮食自我监测移动应用程序的人没有继续积极使用它，而那些积极使用的人可能本来就是健康饮食者。因此，如果此类应用程序无法触及最需要改变饮食的人群，其社会影响可能仍然较小。在应用程序中纳入额外的自我调节技术，如目标设定和意图形成，可能会提高用户参与度并促进持续使用。
