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ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Why We Must Move Beyond the Cycle of Violence: Introducing Escalation Pattern Analysis (EPA)

Authors: Kaiser, Robert;

Why We Must Move Beyond the Cycle of Violence: Introducing Escalation Pattern Analysis (EPA)

Abstract

Lenore Walker’s Cycle of Violence marked an early conceptual milestone in understanding intimate partner violence, yet its explanatory power has been eclipsed by contemporary theoretical developments. The model’s cyclical, incident-bound formulation fails to accommodate the relational, patterned, and structurally embedded nature of coercive control, as articulated by Stark (2007) and subsequent scholars. Moreover, the cycle’s episodic logic is inconsistent with empirical findings on escalation trajectories, lethality markers, and the temporal compression of harm identified in modern femicide research. These limitations position the Cycle of Violence as an important historical artefact rather than a viable analytical framework for present-day scholarship. This paper addresses that theoretical gap by advancing Escalation Pattern Analysis (EPA): a behaviorally anchored, tri-axis model designed specifically to interpret IPV as an evolving trajectory rather than a repetitive loop. EPA uniquely offers an operationalized mechanism, evaluating Frequency, Intensity, and Inhibitory Decline, that precisely tracks escalation over time. This capability enables a structured and quantifiable method for risk assessment and intervention, distinguishing EPA from traditional cycles. By clarifying the nature and stages of escalation, EPA delivers practical and analytical advantages for practitioners aiming to intervene before high-harm or lethal outcomes. Incorporating recent scholarship on coercive control, economic control, stalking, technological abuse, and homicide progression, this paper demonstrates that modern IPV requires models that capture progression and change. EPA provides a distinctive, empirically grounded lens for understanding how abuse transitions from control to high-harm and lethality, setting it apart from earlier models. Keywords: intimate partner violence, coercive control, Escalation Pattern Analysis (EPA), lethality assessment, femicide, risk assessment, patterned abusive behaviors, domestic abuse dynamics

Keywords

Gender-Based Violence/psychology, Domestic Violence, Domestic Violence/prevention & control, Intimate Partner Violence/history, Intimate Partner Violence, FOS: Law, Gender-Based Violence, Criminology, Violence, Risk Assessment, Forensic Psychology, Intimate Partner Violence/psychology, lethality assessment, Domestic Violence/psychology, Forensic Psychology/history, Gender-Based Violence/prevention & control, Sexual violence, Risk assessment, Gender-Based Violence/history, Intimate Partner Violence/prevention & control, Domestic Violence/prevention & control, domestic abuse, FOS: Other medical sciences, Domestic Violence/history, Gender-Based Violence/prevention & control, Intimate Partner Violence/prevention & control

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green