E0 ConsensusModerate confidencePEM not requiredSystematic-ReviewPeer-reviewedReviewed
Methodological Strategies for Ecological Momentary Assessment to Evaluate Mood and Stress in Adult Patients Using Mobile Phones: Systematic Review.
Yang, Yong Sook, Ryu, Gi Wook, Choi, Mona · JMIR mHealth and uHealth · 2019 · DOI
Quick Summary
This review looked at research studies that used smartphones to track mood and stress in patients with various chronic illnesses, including ME/CFS. Researchers used apps or text-based systems to send prompts at random times throughout the day, asking patients to report how they were feeling in that moment. The review found that this method is practical and feasible for understanding how symptoms and emotions change during daily life.
Why It Matters
For ME/CFS patients, EMA methods offer a way to capture real-time changes in mood and stress in daily life without requiring clinical visits, which can be difficult for those with severe fatigue. Understanding how psychological factors fluctuate alongside ME/CFS symptoms could help identify triggers and patterns that might guide treatment approaches. This methodology review demonstrates that smartphones are a feasible tool for collecting this data from ME/CFS populations.
Observed Findings
- 92% of included studies used signal contingency (triggered measurement prompts) as their assessment strategy.
- 67% of studies employed random or semirandom interval alarms to trigger momentary measurements.
- 58% of studies used dedicated mobile apps installed directly on phones, while 25% used web-based survey links and 17% used interactive voice-response systems.
- One of the 12 reviewed studies involved patients with chronic fatigue syndrome.
Inferred Conclusions
- EMA via mobile phones is a feasible and effective method for measuring momentary mood and stress in adult patient populations.
- Smartphones are an accessible platform for collecting real-time psychological data because phones are ubiquitous and familiar to most adults.
- Researchers should consider random/semirandom signaling and direct app installation as preferred methodological approaches for EMA implementation.
Remaining Questions
- What is the typical adherence rate and participant dropout rate for smartphone-based EMA studies in chronic disease populations?
- How do different technical implementations (apps vs. web-based vs. voice response) compare in terms of data quality, burden, and patient retention?
- What is the optimal frequency and timing of assessment prompts to balance data richness with participant burden in ME/CFS specifically?
What This Study Does Not Prove
This review does not prove that EMA findings change clinical outcomes or improve patient care; it only describes methodological options. The review also does not establish whether smartphone-based mood tracking is superior to other assessment methods, nor does it demonstrate adherence rates or sustained engagement with these tools in any specific patient population. No causal relationships between stress/mood and disease progression are established.
Tags
Method Flag:Mixed CohortWeak Case DefinitionPEM Not Defined
Symptom:Fatigue
Metadata
- DOI
- 10.2196/11215
- PMID
- 30932866
- Review status
- Editor reviewed
- Evidence level
- Higher-level evidence type — systematic reviews, meta-analyses, guidelines, or major syntheses (study type, not a quality guarantee)
- Last updated
- 12 April 2026
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
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