{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:34:41Z","timestamp":1787027681269,"version":"build-2736575974"},"reference-count":71,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T00:00:00Z","timestamp":1766620800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behavioral Sciences"],"abstract":"<jats:p>Police crime reports are a critical but often underutilized source of information for understanding intimate partner violence (IPV). They provide systematic, population-level data on when, where, and how IPV incidents occur, complementing surveys and clinical studies. This study provides a descriptive analysis of IPV crime reports in Los Angeles (January 2020\u2013December 2023) and models temporal trends using Seasonal Autoregressive Integrated Moving Average (SARIMA). Results showed that a total of 74,776 IPV-related incidents were reported to the LAPD in the four-year period, averaging 51.22 incidents per day (SD = 10.84). Most incidents occurred in residential settings (71.9%), followed by public spaces (18.2%) and transportation settings (6.5%). Females accounted for the majority of incidents (77.35%) compared to males (22.65%), and Physical IPV was the most frequently reported subtype (77.0%). Of these Physical IPV reports, most incidents did not involve a weapon (83.82%), while the use of firearms, bladed weapons, blunt objects, and improvised implements was relatively uncommon. Temporal modeling using SARIMA indicated that month-to-month variation was dominated by stable seasonal and autoregressive dynamics, with no evidence of a distinct pandemic-specific shift in call volume. By integrating descriptive and temporal analyses, the study offers actionable insights for public health, law enforcement, and community organizations working to prevent and respond to IPV.<\/jats:p>","DOI":"10.3390\/bs16010048","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T02:07:58Z","timestamp":1766714878000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Understanding Intimate Partner Violence Through Police Crime Data: Descriptive and Temporal Insights"],"prefix":"10.3390","volume":"16","author":[{"given":"Charmayne Mary Lee","family":"Hughes","sequence":"first","affiliation":[{"name":"Age-Appropriate Human-Machine Systems, Institute of Psychology and Ergonomics, Technische Universit\u00e4t Berlin, Fasanenstra\u00dfe 1, 10623 Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1177\/1088767912471341","article-title":"Fatal and non-fatal intimate partner violence: What separates the men from the women for victimizations reported to police?","volume":"18","author":"Addington","year":"2014","journal-title":"Homicide Studies"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Transactions on Automation Control"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Allen, E. 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