Assessing Day-to-Day Emotion Dynamics Within the Whole Family: Protocol for a Family-Wide Ecological Momentary Assessment Study (The Family and Child Emotion Study)
Bibliographic record
Abstract
BACKGROUND: Families play a pivotal role in shaping children's emotional development through emotion socialization. However, most research has focused on individual or dyadic relationships, such as those between parents and children, overlooking the more complex dynamics that emerge when multiple family members interact simultaneously. This limited perspective fails to capture the full scope of the interconnected emotional processes within family units. A contributing factor to this gap is the limited availability of models suited for capturing and analyzing complex, family-level data. OBJECTIVE: The Family and Child Emotion Study aims to address this gap by examining family-wide emotion dynamics across all family members-including parents and children-as they naturally unfold in daily life. METHODS: This protocol uses a pre-post design and a 7-day ecological momentary assessment period combined with ambulatory monitoring of heart rate and electrodermal activity within whole family units to examine interactions among mothers, fathers, and siblings, providing a comprehensive understanding of family-wide emotion processes. Data will be analyzed using a network analytical approach, specifically multilevel vector autoregressive modeling, to investigate dynamic emotional processes within and between family members. RESULTS: Funding was received in April 2020. Data collection began in September 2022 and will continue until March 2026. As of May 2025, the Family and Child Emotion Study has collected data from 48 eligible families. Data analyses will begin after March 2026, with results expected to be published in Fall 2027. CONCLUSIONS: This study introduces an innovative approach for examining emotion dynamics within whole-family systems in naturalistic settings, offering practical guidance for collecting and analyzing complex, multilevel, and nested data. The primary aim is to investigate how family emotion networks contribute to children's emotional functioning and development. A secondary aim is to explore key factors, such as parental psychological functioning and child emotion regulation abilities, that may shape these networks. This protocol serves as a valuable framework for future researchers exploring family-wide emotion dynamics. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77364.
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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 | 0.024 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.015 |
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".