Ecological Momentary Assessment of Weight-Related Behaviors in the Home Environment of Children From Low-Income and Racially and Ethnically Diverse Households: Development and Usability Study
Bibliographic record
Abstract
BACKGROUND: Ecological momentary assessment (EMA) is an innovative tool for capturing in-the-moment health behaviors as people go about their daily lives. EMA is an ideal tool to measure weight-related behaviors, such as parental feeding practices, stress, and dietary intake, as these occur on a daily basis and vary across time and context. A recent systematic review recommended standardized reporting of EMA design for studies that address weight-related behaviors. OBJECTIVE: To answer the call for reporting study designs using EMA, this paper describes in detail the EMA design of the Family Matters study and how it was adapted over time to improve functionality and meet the needs of a racially, ethnically, and socioeconomically diverse sample. METHODS: Family Matters is an incremental, 2-phased, mixed methods study, conducted with a racially and ethnically diverse, immigrant and refugee sample from largely low-income households, designed to examine risk and protective factors for child weight and weight-related behaviors in the home environment. The Family Matters study intentionally recruited White, Black, Hmong, Latino, Native American, and Somali parents with young children. Parents in phase 1 of the study completed 8 days of EMA on their smartphones, which included signal-contingent surveys (eg, asking about the parent's stress at the time of the survey), event-contingent surveys (eg, descriptions of the meal the child ate), and end-of-day surveys (eg, overall assessment of the child's day). RESULTS: A detailed description of EMA strategies, protocols, and methods used in phase 1 of the Family Matters study is provided. Compliance with EMA surveys and participants' time spent completing EMA surveys are presented and stratified by race and ethnicity. In addition, lessons learned while conducting phase 1 EMA are shared to document how EMA methods were improved and expanded upon for phase 2 of the Family Matters study. CONCLUSIONS: The results from this study provided an important next step in identifying best practices for EMA use in assessing weight-related behaviors in the home environment. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30525.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".