Mobile Phone App for Self-Monitoring of Eating Rhythm: Field Experiment (Preprint)

Abstract

BACKGROUND Temporal aspects of eating are an integral part of healthy eating, and regular eating has been associated with good diet quality and more successful weight control. Unfortunately, irregular eating is becoming more common. Self-monitoring of behavior has been found to be an efficient behavioral change technique, but the solution should be simple enough to ensure long-lasting adherence. OBJECTIVE This study aimed to explore the influence of self-monitoring of daily eating pattern with mobile phone app on eating rhythm, eating behavior tendencies, and the underlying motives and attitudes related to eating. METHODS A mobile phone app, Button, was developed for effortless self-monitoring of eating rhythm. The feasibility of the app was tested in a 30-day intervention. The participants (N=74) recorded their eating occasions during the intervention by pressing a button in the app widget. RESULTS The average interval between meals increased (96 [SD 24] min during the first 10 days vs 109.1[SD 36.4] during the last 10 days) and the number of daily eating occasions decreased (4.9 [SD 0.9] during the first 10 days vs 4.4 [SD 0.9] during the last 10 days). The tendencies for cognitive restraint, emotional eating, and uncontrolled eating increased. Eating-related attitudes and motives remained largely unchanged. CONCLUSIONS These results indicate that a simple self-monitoring tool is able to draw a user’s attention to eating and is a potential tool to aid people to change their eating rhythm.

Characteristics of smartphone-based dietary assessment tools: A systematic review

“…Only two studies (1.6%) explicitly stated that they did not provide any incentive for participation. Out of the 123 included studies, three used two different dietary assessment tools (25,38,39), one study used four different dietary assessment tools (40), and the remaining studies only used one dietary assessment tool each. Accordingly, this systematic review reports on a total of 129 dietary assessment tools that were used by between 1 and 1027 participants (M = (n = 2) for Symbian OS, and 0.8% (n = 1) were not restricted regarding operating systems.…”

“…A classification system to categorise food intake was used in 36 dietary assessment tools (27.9%). Six studies asked participants to classify the food into general categories such as meals vs snacks (67,111,112), light vs heavy (113,114), healthy vs unhealthy meals, or the participants feeling content vs not content (38). The majority however asked for a classification based on a list of food groups (40,42,49,50,108,(115)(116)(117)(118)(119)(120)(121)(122)(123)(124)(125)(126)) that varied in the number of categories presented.…”

Characteristics of smartphone-based dietary assessment tools: a systematic review

“…Out of the 123 included studies, three used two different dietary assessment tools (33,46,47), one study used four different dietary assessment tools (48) (n = 2) for Symbian OS, and 0.8% (n = 1) were not restricted regarding operating systems.…”

“…A classification system to categorise food intake was used in 36 dietary assessment tools (27.9%). Six studies asked participants to classify the food into general categories such as meals vs snacks (74,118,119), light vs heavy (120,121), healthy vs unhealthy meals, or the participants feeling content vs not content (46). However, the majority asked for a classification based on a list of food groups (20,48,50,57,115,(122)(123)(124)(125)(126)(127)(128)(129)(130)(131)(132)(133)) that varied in the number of categories presented.…”