Ecological Momentary Assessment in Schizophrenia

Ecological Momentary Assessment (EMA) has transformed the study of schizophrenia by enabling repeated, real-time monitoring of symptoms, behaviour and emotional states in naturalistic settings. By prompting participants to record experiences at multiple intervals each day via smartphones or wearable devices, EMA mitigates retrospective recall bias and captures the dynamic fluctuations of psychotic symptoms, negative affect and social functioning. This method has been deployed to quantify real-world activity levels, chart daily time use and characterise momentary mood and cognition. Coupled with passive sensor data—such as GPS, accelerometry and heart‐rate monitoring—it forms the basis of digital phenotyping, offering an unobtrusive window into daily life. EMA paradigms have yielded fresh insights into negative symptoms, anhedonia and psychosocial functioning, and have informed the design of personalised ecological momentary interventions. Challenges remain in maintaining adherence over extended monitoring periods, addressing data privacy concerns and integrating heterogeneous data streams into clinical decision-making. Nonetheless, the global significance of EMA lies in its capacity to deliver fine-grained, ecologically valid measures of how individuals with schizophrenia navigate everyday contexts, opening avenues for tailored treatment strategies and remote monitoring of treatment response.

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Ecological Momentary Assessment in Schizophrenia publication trend

The graph below shows the total number of articles in ecological momentary assessment in schizophrenia across all publications each year (not limited to Nature Index journals).

Technical terms

Ecological Momentary Assessment (EMA): A methodology involving repeated self-reports of mood, symptoms and context in real time within an individual’s natural environment.

Experience Sampling Method (ESM): A subtype of EMA that uses scheduled prompts to elicit participants’ reports of activities, thoughts and feelings at multiple times each day.

Digital phenotyping: The continuous collection of behavioural and physiological data via personal devices (smartphones, wearables) to characterise mental health states and functional patterns.

Positivity offset: The tendency to experience a predominance of positive over negative affect in low-arousal or neutral contexts, reduction of which is associated with negative symptoms in schizophrenia.

Passive monitoring: The unobtrusive capture of sensor-derived data (e.g., GPS location, accelerometry, physiological signals) without active input from the participant.

References

1. Comparing Adherence to the Experience Sampling Method Among Patients With Schizophrenia Spectrum Disorder and Unaffected Individuals: Observational Study From the Multicentric DiAPAson Project. Journal of Medical Internet Research (2023).
2. Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study. JMIR mHealth and uHealth (2025).
3. The positivity offset theory of anhedonia in schizophrenia: evidence for a deficit in daily life using digital phenotyping. Psychological Medicine (2023).
4. An ecological momentary intervention incorporating personalised feedback to improve symptoms and social functioning in schizophrenia spectrum disorders. Psychiatry Research (2019).