Pascal Küng
Postdoctoral Researcher @ UZH

Pascal Küng.

Investigating dyadic data, intensive longitudinal designs, and the dynamics of daily health behavior change.

Selected Work Publications Methods Demo
Simulation System Dyadic Behavior Concordance
Active Loop
P₁
Partner A
Concordance +0.48
P₂
Partner B
REALTIME EMA STREAMS day_t
Activity A Activity B
LOG FEED 14:02:18
> INITIALIZING CORE LOOP...
> SIMULATING DAILY EMAS...
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Research Focus

Methodological rigour meeting empirical questions.

Modeling interpersonal processes and relational dynamics in close relationships. I investigate how partners mutually influence each other's health behaviors over time.

APIMActor-Partner EffectsInterdependenceCouples Research
Actor A (X₁)Outcome A (Y₁)Actor B (X₂)Outcome B (Y₂)Actor EffectActor EffectPartner Effects

Capturing life as it is lived. Using Ecological Momentary Assessment (EMA) and daily diaries to study within-person micro-processes and health behavior changes in real time.

EMA / Daily DiariesWithin-Person dynamicsMultilevel ModelingTime-Series
Time (Days)YFluctuations (Within-Person)Mean (Between-Person)

Bridging the gap between conceptual models and statistical evidence. Translating psychological theories of social control and autonomy into precise, interpretable empirical tests.

MeasurementInterpretationConstruct ValidityBayesian Models
SocialControlSelf-ReportPartner-ReportAccelerometerloading (λ)λ₁λ₃
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Highlighted Research

Interdependent processes in daily health behavior change.

Core Topic

Social Control in Couples

Investigating how health-related social control interacts with individual factors like the preference for self-reliance. Using daily diary data and dyadic EMA designs to understand behavioral trajectories and affective reactance.

View social control publications →

R Package

wbCorr Package

A dedicated methodological package designed to cleanly estimate bivariate within-person and between-person correlations in clustered, repeated-measures datasets.

View on GitHub
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Scholarly Directory

Publications & research outputs.

2026First Author

Does preference for self-reliance moderate associations of health-related social control with physical activity and smoking cessation? Two intensive longitudinal studies.

Read Paper→

Küng, P., Bierbauer, W., Berli, C., Höhener, P. S., Lüscher, J., Bermudez, T., Banik, A., Łuszczyńska, A., & Scholz, U.

British Journal of Health Psychology•31(2), e70082
#IntensiveLongitudinal#SocialControl#Moderation#PhysicalActivity
2026First Author

Daily associations of three types of social control with physical activity, reactance, and mood in romantic couples: A dyadic intensive longitudinal study.

Read Paper→

Küng, P., Höhener, P. S., Allen, J. M., Tobias, R., & Scholz, U.

Psychology & Health•1–25
#DyadicData#EMA/DailyDiary#Reactance#PhysicalActivity
2025First Author

Health-related social control in overweight romantic couples: Daily associations with physical activity and affect for targets and agents.

Read Paper→

Küng, P., Berli, C., Höhener, P. S., Tobias, R., & Scholz, U.

Annals of Behavioral Medicine•59(1), kaae093
#SocialControl#DyadicData#EMA/DailyDiary#OverweightCouples
2025Software

Tutorial: Distinguishable and exchangeable dyads -- Bayesian multilevel modelling

Code / Link→

Küng, P.

Zenodo Tutorial•Version 2.0.1
#BayesianMLM#DyadicData#Tutorial#R/brms
2023Software

wbCorr: Bivariate within- and between-cluster correlations

Code / Link→

Küng, P.

R Package•Version 0.1.22
#RPackage#Methodology#Correlation#ClusteredData
2026Co-Authored

Effectiveness of smartphone-based dyadic interventions to increase physical activity in romantic couples: Microrandomized trial.

Read Paper→

Höhener, P. S., Tobias, R., Allen, J. M., Küng, P., & Scholz, U.

JMIR mHealth and uHealth•14, e67136
#mHealth#Micro-randomizedTrial#DyadicIntervention#PhysicalActivity
2025Co-Authored

Investigating the association between companionship and behavior concordance: A dyadic panel study.

Read Paper→

Höhener, P. S., Lüscher, J., Tobias, R., Küng, P., & Scholz, U.

Personal Relationships•32(2), e70005
#Companionship#Concordance#DyadicPanelStudy#Relationships
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Methods Intuition

Visualizing multilevel models.

In intensive longitudinal and dyadic designs, mapping individual intercepts and slopes makes abstract equations intuitive. Play with the parameters or drag the nodes directly in the graph to see their impact in real time.

Parameters

Fixed Effects Line (Drag Handles)
10 Simulated Individuals (u_i)
Yij=(6.0+u0i)+(0.20+u1i)XijY_{ij} = (\color{#4E94F8}{6.0} + u_{0i}) + (\color{#E25C5C}{0.20} + u_{1i})X_{ij}
u0i∼N(0,σu02),u1i∼N(0,σu12)u_{0i} \sim N(0, \sigma^2_{u0}), \quad u_{1i} \sim N(0, \sigma^2_{u1})
σu0=1.0,σu1=0.15,Cor(u0i,u1i)=−0.40\sigma_{u0} = \color{#93C5FD}{1.0}, \quad \sigma_{u1} = \color{#FCA5A5}{0.15}, \quad \text{Cor}(u_{0i}, u_{1i}) = \color{#C59E5D}{-0.40}
💡 Hover over an individual's gray line to see their unique formula realization
46810DAY (X)Y0510β₀ + β₁X
💡 Drag plot nodes to change intercept & slope
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Get in touch

Let's
connect.

Interested in collaboration, methodology advisory, or longitudinal research discussions? My inbox is always open.

Email Me →
GitHub ORCID

© 2026 Pascal Küng. All rights reserved.

Google Scholar / Publications GitHub Repository