Exploring emotions beyond the laboratory: A review of emotional and physiological ecological momentary assessment methods in children and youth
Bibliographic record
Abstract
Recent advancements in methodologies such as ecological momentary assessment (EMA) and ambulatory physiology devices have enhanced our ability to measure emotions experienced in daily life. Despite the feasibility of EMA for assessing children's and youth's emotional self-reports, the feasibility of combining it with physiological measurements in a real-life context has yet to be established. Our scoping review evaluates the feasibility and usability of implementing emotional and physiological EMA in children and youth. Due to the complexities of physiological EMA data, this review also synthesized existing methodological and statistical practices of existing studies. Following the PRISMA-ScR guidelines, we searched and screened PsycINFO, PubMed, and Web of Science electronic databases for studies that assessed children's and youth's subjective emotions and cardiac or electrodermal physiological responses outside the laboratory. Our initial search resulted in 4174 studies, 13 of which were included in our review. Findings showed significant variability in the feasibility of physiological EMA, with physiology device wear-time averaging 58.77% of study periods and data loss due to quality issues ranging from 0.2% to 77% across signals. Compliance for emotional EMA was approximately 60% of study periods when combined with physiological EMA. The review points to a lack of standardized procedures in physiological EMA and suggests a need for guidelines in designing, processing, and analyzing such data collected in real-life contexts. We offer recommendations to enhance participant engagement and develop standard practices for employing physiological EMA with children and youth for emotion, developmental, and psychophysiology researchers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".