Associations of Eating Identities With Self-Reported Dietary Behaviors and Body Mass Index.

Objective: To inform dietary interventions, it is important to understand antecedents of recommended (henceforth: healthy) dietary behaviors, beyond dietary beliefs and self-efficacy. We used the validated "Eating Identity Type Inventory" to assess the extent to which participants identified as healthy eaters, meat eaters, emotional eaters or picky eaters. We examined correlations between participants' race/ethnicity and other socio-demographic characteristics and affinity with these eating identities, how affinity with these eating identities correlated with self-reports of dietary beliefs, self-efficacy, dietary behaviors and Body Mass Index (BMI), and how well affinity with these eating identities predicted self-reported dietary behaviors and BMI, as compared to self-reported dietary beliefs and self-efficacy. Methods: In an online survey, a diverse sample of 340 Los Angeles County adults reported eating identities, dietary beliefs, and self-efficacy, dietary behaviors and BMI. Results: Pearson correlations revealed that identifying more as a healthy eater was positively associated with self-reports of being non-Hispanic White, non-Hispanic mixed race, older, and college-educated, while identifying more as a meat eater was positively associated with self-reports of being non-Hispanic Black, younger, and male (α = 0.05). Pearson correlations also showed that healthy eaters had more accurate dietary beliefs and self-efficacy, and emotional eaters had lower self-efficacy (α = 0.05). In linear regressions, identifying more as a healthy eater was associated with self-reporting healthier dietary behaviors and lower BMI, and identifying more as a meat eater and emotional eater was associated with reporting less healthy dietary behaviors and higher BMI, even after accounting for correlations with socio-demographics, dietary beliefs, and self-efficacy (α = 0.05). Conclusions: Our findings highlight the importance of eating identities in understanding dietary behaviors and outcomes, with implications for dietary interventions.

Self-administered Web-Based Tests of Executive Functioning and Perceptual Speed: Measurement Development Study With a Large Probability-Based Survey Panel.

BACKGROUND: Cognitive testing in large population surveys is frequently used to describe cognitive aging and determine the incidence rates, risk factors, and long-term trajectories of the development of cognitive impairment. As these surveys are increasingly administered on internet-based platforms, web-based and self-administered cognitive testing calls for close investigation. OBJECTIVE: Web-based, self-administered versions of 2 age-sensitive cognitive tests, the Stop and Go Switching Task for executive functioning and the Figure Identification test for perceptual speed, were developed and administered to adult participants in the Understanding America Study. We examined differences in cognitive test scores across internet device types and the extent to which the scores were associated with self-reported distractions in everyday environments in which the participants took the tests. In addition, national norms were provided for the US population. METHODS: Data were collected from a probability-based internet panel representative of the US adult population-the Understanding America Study. Participants with access to both a keyboard- and mouse-based device and a touch screen-based device were asked to complete the cognitive tests twice in a randomized order across device types, whereas participants with access to only 1 type of device were asked to complete the tests twice on the same device. At the end of each test, the participants answered questions about interruptions and potential distractions that occurred during the test. RESULTS: Of the 7410 (Stop and Go) and 7216 (Figure Identification) participants who completed the device ownership survey, 6129 (82.71% for Stop and Go) and 6717 (93.08% for Figure Identification) participants completed the first session and correctly responded to at least 70% of the trials. On average, the standardized differences across device types were small, with the absolute value of Cohen d ranging from 0.05 (for the switch score in Stop and Go and the Figure Identification score) to 0.13 (for the nonswitch score in Stop and Go). Poorer cognitive performance was moderately associated with older age (the absolute value of r ranged from 0.32 to 0.61), and this relationship was comparable across device types (the absolute value of Cohen q ranged from 0.01 to 0.17). Approximately 12.72% (779/6123 for Stop and Go) and 12.32% (828/6721 for Figure Identification) of participants were interrupted during the test. Interruptions predicted poorer cognitive performance (P<.01 for all scores). Specific distractions (eg, watching television and listening to music) were inconsistently related to cognitive performance. National norms, calculated as weighted average scores using sampling weights, suggested poorer cognitive performance as age increased. CONCLUSIONS: Cognitive scores assessed by self-administered web-based tests were sensitive to age differences in cognitive performance and were comparable across the keyboard- and touch screen-based internet devices. Distraction in everyday environments, especially when interrupted during the test, may result in a nontrivial bias in cognitive testing.

Comparability of Emotion Dynamics Derived From Ecological Momentary Assessments, Daily Diaries, and the Day Reconstruction Method: Observational Study.

BACKGROUND: Interest in the measurement of the temporal dynamics of people's emotional lives has risen substantially in psychological and medical research. Emotions fluctuate and change over time, and measuring the ebb and flow of people's affective experiences promises enhanced insights into people's health and functioning. Researchers have used a variety of intensive longitudinal assessment (ILA) methods to create measures of emotion dynamics, including ecological momentary assessments (EMAs), end-of-day (EOD) diaries, and the day reconstruction method (DRM). To date, it is unclear whether they can be used interchangeably or whether ostensibly similar emotion dynamics captured by the methods differ in meaningful ways. OBJECTIVE: This study aims to examine the extent to which different ILA methods yield comparable measures of intraindividual emotion dynamics. METHODS: Data from 90 participants aged 50 years or older were collected in a probability-based internet panel, the Understanding America Study, and analyzed. Participants provided positive and negative affect ratings using 3 ILA methods: (1) smartphone-based EMA, administered 6 times per day over 1 week, (2) web-based EOD diaries, administered daily over the same week, and (3) web-based DRM, administered once during that week. We calculated 11 measures of emotion dynamics (addressing mean levels, variability, instability, and inertia separately for positive and negative affect, as well as emotion network density, mixed emotions, and emotional dialecticism) from each ILA method. The analyses examined mean differences and correlations of scores addressing the same emotion dynamic across the ILA methods. We also compared the patterns of intercorrelations among the emotion dynamics and their relationships with health outcomes (general health, pain, and fatigue) across ILA methods. RESULTS: Emotion dynamics derived from EMAs and EOD diaries demonstrated moderate-to-high correspondence for measures of mean emotion levels (ρ≥0.95), variability (ρ≥0.68), instability (ρ≥0.51), mixed emotions (ρ=0.92), and emotional dialecticism (ρ=0.57), and low correspondence for measures of inertia (ρ≥0.17) and emotion network density (ρ=0.36). DRM-derived measures showed correlations with EMAs and EOD diaries that were high for mean emotion levels and mixed emotions (ρ≥0.74), moderate for variability (ρ=0.38-.054), and low to moderate for other measures (ρ=0.03-0.41). Intercorrelations among the emotion dynamics showed high convergence across EMAs and EOD diaries, and moderate convergence between the DRM and EMAs as well as EOD diaries. Emotion dynamics from all 3 ILA methods produced very similar patterns of relationships with health outcomes. CONCLUSIONS: EMAs and EOD diaries provide corresponding information about individual differences in various emotion dynamics, whereas the DRM provides corresponding information about emotion levels and (to a lesser extent) variability, but not about more complex emotion dynamics. Our results caution researchers against viewing these ILA methods as universally interchangeable.