Psychometric validation of the pictorial ecological momentary well-being instrument
Bibliographic record
Abstract
OBJECTIVES: With the growing interest in Ecological Momentary Assessment (EMA) in mental health research, the need for precise and reliable measurement tools has become a pressing issue. However, few candidate instruments have been validated in intensive longitudinal data collection contexts. The present study provides an example of the psychometric validation of measurement instruments designed for EMA, by assessing the psychometric properties of Ecological Momentary Well-being Instrument (EMoWI), the first scale specifically designed to measure momentary well-being. STUDY DESIGN AND SETTING: Participants from the COvid-19 HEalth and Social InteractiOn in Neighborhoods (COHESION) cohort, a general population sample of Canadian adults, who participated in the September 2022 EMA wave, were included. Prompts including the 8 EMoWI items were sent to participants three times a day, over 10 consecutive days. Based on recent recommendations, we combined Classical Test and Item Response theories to assess content, structural, and construct validity, as well as reliability of EMoWI in an intensive longitudinal data collection context. RESULTS: Two Hundred Ninety adults aged between 19 and 80 were included, representing a total of 7974 prompts over 10 days. Variance decomposition analysis confirmed significant variability in momentary well-being at both the participant and day levels. Multilevel confirmatory factor analysis supported a single factor hypothesis (root mean square error of approximation = 0.074). Internal consistency was high, both at the within- and between-variance level (MacDonald's ω = 0.814 and 0.938, respectively) and we demonstrated longitudinal measurement invariance over time. Variations in mean momentary well-being across subgroups were consistent with our predefined hypotheses, supporting construct validity of EMoWI. CONCLUSION: We demonstrated the validity and reliability of EMoWI to measure momentary well-being in intensive longitudinal studies. These results will enhance the accuracy of findings related to well-being in EMA studies and inform the development of evidence-based mental health ecological momentary interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".