Beyond the Individual: A 25-year Systematic Review of the Actor–Partner Interdependence Model in Longitudinal Dyadic Research Across Disciplines and Contexts

The Actor-Partner Interdependence Model (APIM) has become a foundational framework for analyzing dyadic data, but systematic reviews synthesizing how longitudinal APIM has been applied across disciplines and populations are limited. This systematic review examined 73 longitudinal APIM studies published between 2008 and 2025, analyzing methodological practices, analytical strategies, and population diversity. Studies were included if they used APIM as the primary framework, reported both actor and partner effects, included a minimum of 70 dyads, and employed longitudinal designs exceeding one year. Data were extracted on study characteristics, sample demographics, APIM variants, statistical approaches, and methodological transparency indicators. Results revealed a fivefold increase in publications after 2016, with applications spanning psychology (37.0%), family science (31.5%), and gerontology (12.3%). However, substantial gaps emerged in three areas. First, geographic and population concentration was evident: 58.9% of studies originated from North America, 86.3% examined couple dyads, and 75.3% utilized secondary data from established panels. Second, methodological transparency showed inconsistency: only 17.8% reported power analyses, 24.7% did not report missing data strategies, and 35.6% failed to document model constraints. Third, universal self-report reliance with minimal multi-method assessment (16.4%) limits distinguishing genuine interpersonal influence from shared method variance. Despite these gaps, nearly all studies were hypothesis-driven, typically articulating a priori expectations regarding actor and partner pathways, and researchers increasingly acknowledged limitations regarding power (37.0%) and self-report reliance (65.8%). Future advances require integrating a priori power analysis using dyadic-specific tools, employing multi-method designs, diversifying populations beyond Western heterosexual couples, and enhancing reporting transparency through preregistration and comprehensive model specification.