J. Med. Internet Res. - Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study.

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Resumo

CKGROUND: 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.OBJECTIVE: 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.METHODS: 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.RESULTS: 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) ((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 ((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 ((2) 2=343.6, P<.001, and (2) 2=909.6, P<.001, respectively). Only 9.89% (481/4863) of Active users had a positive trend in their average healthiness ratings.CONCLUSIONS: 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.

Resumo Limpo

ckground healthi eat intervent use behavior chang techniqu selfmonitor feedback associ stronger effect mobil app can make dietari selfmonitor easi photographi potenti reach huge populationsobject aim studi assess factor relat sustain use free mobil app eateri promot healthi eat photograph dietari selfmonitor peer feedbackmethod retrospect analysi conduct sampl peopl download app use least octob april adher defin base frequenc durat selfmonitor peopl taken one pictur classifi user peopl one pictur dropout user taken least pictur use app least one week classifi activ user pictur semiact dropout one pictur nonact associ adher registr time dietari prefer peer feedback examin chang healthi rate time analyz among activesresult overal adher lowon use app activ day week time day app initi use associ adher user start use app daytim weekday comparison dropout user strict diet like activ defin diet said ate everyth report diet p averag healthi rate peer first pictur higher activ user semiact nonact f p activ wrote often textual descript first pictur semiact nonact p feedback beyond rate relat infrequ pictur receiv comment receiv like user activ like least one comment one like pictur semiact nonact p p respect activ user posit trend averag healthi ratingsconclus peopl tri free mobil app dietari selfmonitor continu use activ may alreadi healthi eater henc societ impact app may remain small fail reach need dietari chang incorpor addit selfregul techniqu goalset intent format app potenti increas user engag promot sustain use

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