ArticlePloS one2025
Bipolar vs. unipolar scaling in dynamic network analyses of Ecological Momentary Assessment data.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Adaptive and Maladaptive Networks Using Ecological Momentary Assessment.Clinical psychology in Europe · 2026Article
- From diagnosis to dynamics: complex systems, transdiagnostics, and networks in forensic psychiatry.Frontiers in psychology · 2026Article
- Article
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8 authors.
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Abstract
This study examined the statistical and clinical benefits of using bipolar versus unipolar scaling in dynamic network analysis of Ecological Momentary Assessment (EMA) data.
methodsForty-seven students completed EMA reports three times daily for five weeks via either unipolar (n = 24) or bipolar (n = 23) scales. The data were analyzed to construct idiographic network models.
resultsThe bipolar scaling group presented significantly lower zero inflation (2.37% vs. 10.31%, U = 2407756, r = 0.75, p < .05) and greater response variability. Network analysis revealed more participants with significant network edges in the bipolar group (69.57% vs. 41.67%, χ²(1) = 12.06, p = .0007). Additionally, the bipolar group had lower odds of zero responses than the unipolar group did (p = .038).
conclusionBipolar scaling enhances EMA data quality by reducing zero inflation and increasing variability, resulting in richer dynamic network models. Further research is needed to confirm these findings in clinical populations.
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