Methodological Strategies for Ecological Momentary Assessment to Evaluate Mood and Stress in Adult Patients Using Mobile Phones: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Ecological momentary assessment (EMA) has utility for measuring psychological properties in daily life. EMA has also allowed researchers to collect data on diverse experiences and symptoms from various subjects. OBJECTIVE: The aim of this study was to review methodological strategies and useful related information for EMA using mobile phones to capture changes of mood and stress in adult patients seeking health care. METHODS: We searched PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, the Cochrane Library, PsycINFO, and Web of Science. This review included studies published in peer-reviewed journals in English between January 2008 and November 2017 that used basic- or advanced-feature mobile phones to measure momentary mood or stress in adult patients seeking health care in outpatient departments. We excluded studies of smoking and substance addictions and studies of mental disorder patients who had been diagnosed by physicians. RESULTS: We reviewed 12 selected articles that used EMA via mobile phones to measure momentary mood and stress and other related variables from various patients with chronic fatigue syndrome, breast cancer, migraine, HIV, tinnitus, temporomandibular disorder, end-stage kidney disease, and traumatic brain injury. Most of the selected studies (11/12, 92%) used signal contingency and in 8 of the 12 studies (67%) alarms were sent at random or semirandom intervals to prompt the momentary measurement. Out of 12 studies, 7 (58%) used specific apps directly installed on mobile phones, 3 (25%) used mobile phones to link to Web-based survey programs, and 2 (17%) used an interactive voice-response system. CONCLUSIONS: This study provides researchers with useful information regarding methodological details for utilizing EMA to measure mood and stress in adult patients. This review shows that EMA methods could be effective and reasonable for measuring momentary mood and stress, given that basic- and advanced-feature mobile phones are ubiquitous, familiar, and easy to approach. Therefore, researchers could adopt and utilize EMA methods using mobile phones to measure psychological health outcomes, such as mood and stress, in adult patients.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".