The Effect of Training on Participant Adherence With a Reporting Time Frame for Momentary Subjective Experiences in Ecological Momentary Assessment: Cognitive Interview Study
Bibliographic record
Abstract
BACKGROUND: Ecological momentary assessment (EMA) has the potential to minimize recall bias by having people report on their experiences in the moment (momentary model) or over short periods (coverage model). This potential hinges on the assumption that participants provide their ratings based on the reporting time frame instructions prescribed in the EMA items. However, it is unclear what time frames participants actually use when answering the EMA questions and whether participant training improves participants' adherence to the reporting instructions. OBJECTIVE: This study aims to investigate the reporting time frames participants used when answering EMA questions and whether participant training improves participants' adherence to the EMA reporting timeframe instructions. METHODS: Telephone-based cognitive interviews were used to investigate the research questions. In a 2×2 factorial design, participants (n=100) were assigned to receive either basic or enhanced EMA training and randomized to rate their experiences using a momentary (at the moment you were called) or a coverage (since the last phone call) model. Participants received five calls over the course of a day to provide ratings; after each rating, participants were immediately interviewed about the time frame they used to answer the EMA questions. A total of 2 raters independently coded the momentary interview responses into time frame categories (Cohen κ=0.64, 95% CI 0.55-0.73). RESULTS: =16.6; P<.001) in which the enhanced training condition yielded more reports within the intended reporting time frames for momentary EMA reports. Cognitive interview data from the coverage model did not lend themselves to reliable coding and were not analyzed. CONCLUSIONS: The results of this study provide the first evidence about adherence to EMA instructions to reporting periods and that enhanced participant training improves adherence to the time frame specified in momentary EMA studies.
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 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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".