Occurrence of and Reasons for "Missing Events" in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies.

BACKGROUND: Establishing a methodology for assessing nutritional behavior comprehensively and accurately poses a great challenge. Mobile technologies such as mobile image-based food recording apps enable eating events to be assessed in the moment in real time, thereby reducing memory biases inherent in retrospective food records. However, users might find it challenging to take images of the food they consume at every eating event over an extended period, which might lead to incomplete records of eating events (missing events). OBJECTIVE: Analyzing data from 3 studies that used mobile image-based food recording apps and varied in their technical enrichment, this study aims to assess how often eating events (meals and snacks) were missed over a period of 8 days in a naturalistic setting by comparing the number of recorded events with the number of normative expected events, over time, and with recollections of missing events. METHODS: Participants in 3 event-based Ecological Momentary Assessment (EMA) studies using mobile image-based dietary assessments were asked to record all eating events (study 1, N=38, 1070 eating events; study 2, N=35, 934 eating events; study 3, N=110, 3469 eating events). Study 1 used a basic app; study 2 included 1 fixed reminder and the possibility to add meals after the actual eating events occurred instead of in the moment (addendum); and study 3 included 2 fixed reminders, an addendum feature, and the option to record skipped meals. The number of recalled missed events and their reasons were assessed by semistructured interviews after the EMA period (studies 1 and 2) and daily questionnaires (study 3). RESULTS: Overall, 183 participants reported 5473 eating events. Although the momentary adherence rate as indexed by a comparison with normative expected events was generally high across all 3 studies, a differential pattern of results emerged with a higher rate of logged meals in the more technically intensive study 3. Multilevel models for the logging trajectories of reported meals in all 3 studies showed a significant, albeit small, decline over time (b=-.11 to -.14, Ps<.001, pseudo-R²=0.04-0.06), mainly because of a drop in reported snacks between days 1 and 2. Intraclass coefficients indicated that 38% or less of the observed variance was because of individual differences. The most common reasons for missing events were competing activities and technical issues, whereas situational barriers were less important. CONCLUSIONS: Three different indicators (normative, time stability, and recalled missing events) consistently indicated missing events. However, given the intensive nature of diet EMA protocols, the effect sizes were rather small and the logging trajectories over time were remarkably stable. Moreover, the individual's actual state and context seemed to exert a greater influence on adherence rates than stable individual differences, which emphasizes the need for a more nuanced understanding of the factors that affect momentary adherence.

Do We Know What We Enjoy? Accuracy of Forecasted Eating Happiness.

Forecasting how we will react in the future is important in every area of our lives. However, people often demonstrate an "impact bias" which leads them to inaccurately forecast their affective reactions to distinct and outstanding future events. The present study examined forecasting accuracy for a day-to-day repetitive experience for which people have a wealth of past experiences (eating happiness), along with dispositional expectations toward eating ("foodiness"). Seventy-three participants (67.12% women, M age = 41.85 years) used a smartphone-based ecological momentary assessment to assess their food intake and eating happiness over 14 days. Eating happiness experienced in-the-moment showed considerable inter-and intra-individual variation, ICC = 0.47. Comparing forecasted and in-the-moment eating happiness revealed a significant discrepancy whose magnitude was affected by dispositional expectations and the variability of the experience. The results demonstrate that biased forecasts are a general phenomenon prevalent both in outstanding and well-known experiences, while also emphasizing the importance of inter-individual differences for a detailed understanding of affective forecasting.