Multi-source Mobile Experience Sampling — Multi-informant Ecological Momentary Assessment
Multi-source Mobile Experience Sampling Method · Also known as: multi-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM
Multi-source Mobile Experience Sampling extends the standard ESM design by simultaneously collecting repeated momentary self-reports from two or more linked informant types — such as patient and caregiver, employee and supervisor, or partners in a dyad — via their smartphones. Signals are delivered concurrently across sources, enabling researchers to examine convergences and discrepancies between informants' real-time experiences and to model interpersonal dynamics at the moment they unfold in daily life.
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When to use it
Use multi-source mobile ESM when the research question concerns real-time interpersonal dynamics, perceptual discrepancies between linked informants, or phenomena that are inherently relational — such as dyadic stress transmission, caregiver-patient interaction, or supervisor-employee emotional contagion. It is well-suited to clinical, organizational, relationship, and family research where concurrent multi-informant data are theoretically essential. Do NOT use this design when the phenomenon is adequately captured from a single perspective, when linking informants is logistically impractical or ethically problematic, when participants cannot manage repeated smartphone use throughout the day, or when the analytic team lacks expertise in dyadic multilevel modeling. Single-source ESM is simpler and sufficient for individual-level research questions.
Strengths & limitations
- Captures real-time divergences and convergences between linked informants at the moment experiences occur, eliminating retrospective recall distortion.
- Enables modeling of interpersonal dynamics — how one person's momentary state predicts another's — with fine temporal resolution unavailable in diary or survey designs.
- Separates within-person, between-person, and between-dyad variance, supporting nuanced hypotheses about relational processes.
- Naturalistic setting preserves ecological validity; both informants are assessed in their real daily contexts.
- Simultaneous multi-informant coverage reduces mono-source bias, a pervasive limitation of conventional ESM.
- Coordination burden is substantially higher than single-source ESM; both informants must remain available and compliant throughout the study period.
- Paired compliance is the binding constraint: a missed signal from either informant in a dyad eliminates that observation from dyadic analyses, reducing effective sample size.
- Dyadic multilevel modeling (e.g., APIM, time-lagged cross-level effects) requires specialized statistical expertise and is more complex than standard multilevel analysis.
- Participant burden is doubled relative to single-source ESM; fatigue, reactivity, and attrition risks are higher, particularly in longer protocols.
- Recruiting matched informant pairs introduces additional selection bias and sample size challenges compared to independent participant recruitment.
Frequently asked
How tightly must the two sources' signals be synchronized?
There is no universal rule, but a common recommendation is that matched signals for linked informants fall within the same 30–60 minute window. Tighter windows improve the temporal validity of cross-source comparisons but increase the coordination burden. For phenomena that change rapidly (momentary affect) tighter synchrony is more important than for slower-moving constructs (daily satisfaction).
What is the minimum number of dyads needed?
Simulation studies for dyadic multilevel models suggest that 50 or more dyads with at least 30 valid paired assessments each provides reasonable power for typical within-dyad cross-partner effects. Below 30 dyads, between-dyad variance estimates become unstable regardless of the number of assessments. Power calculators such as those by Bolger and Laurenceau or Arend and Schafer should be consulted during design.
Can I include more than two informant sources?
Yes, but complexity increases rapidly. Three-source designs (e.g., patient, caregiver, and clinician) are manageable if signal schedules are coordinated and the analytic plan specifies which cross-source comparisons are theoretically primary. Coordinating more than three informant types concurrently is rarely practical in field research.
What analytic model handles dyadic ESM data?
The Actor-Partner Interdependence Model (APIM) adapted for intensive longitudinal data is the standard framework. It partitions variance into actor effects (how my own state at time t predicts my outcome at t+1) and partner effects (how my partner's state at time t predicts my outcome at t+1), while controlling for non-independence within dyads. Standard multilevel software (lme4 in R, Mplus) supports these models.
How does this differ from running two separate single-source ESM studies?
The defining feature is linkage: informants are recruited as matched pairs or clusters, signals are synchronized, and the data are analyzed as dyadic units. Running two independent ESM studies on overlapping populations and comparing group averages does not capture within-dyad covariation or interpersonal dynamics — it misses the relational phenomena that multi-source ESM is specifically designed to study.
Sources
- Bolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781
- Iida, M., Shrout, P. E., Laurenceau, J.-P., & Bolger, N. (2012). Using diary methods in psychological research. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA Handbook of Research Methods in Psychology, Vol. 1. American Psychological Association. link ↗
How to cite this page
ScholarGate. (2026, June 3). Multi-source Mobile Experience Sampling Method. ScholarGate. https://scholargate.app/en/survey-methodology/multi-source-mobile-experience-sampling
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Diary MethodSurvey Methodology↔ compare
- Longitudinal Mobile Experience SamplingSurvey Methodology↔ compare
- Mobile Experience SamplingSurvey Methodology↔ compare
- Multi-source Participant ObservationSurvey Methodology↔ compare
- Multilevel ModelingResearch Statistics↔ compare
- Sensor Data CollectionSurvey Methodology↔ compare