Corrections_Today_Spring_2025_Vol.87_No.1

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attributable to the intervention rather than another factor. In this study, researchers ran domly assigned units rather than individual deputies using a clus tered randomized controlled trial approach. Each month, the CNA team randomly assigned each of the 12 units into six treat ment units where deputies were required to wear body-worn cam eras, and six control units where deputies continued to operate under business-as-usual without body-worn cameras. The team then collected informa tion to examine the intervention’s impact including: (1) surveys of deputies; (2) interviews of jail leaders, deputies, and external jail stakeholders; (3) a focus group with deputies who served on the Special Weapons and Tactics (SWAT) team; (4) observations of jail operations and body-worn camera trainings; (5) review and analysis of jail administrative data, including response to resistance events and resident injuries; and (6) review and analysis of data col lected from stationary cameras and body-worn camera footage.

The dataset included information for each responding deputy and included: – Location of the response-to resistance event. – Shift. – Level of resident resistance, categorized as level 1: passive cal evasive movements), or level 3: aggressive (attacking movements that may cause injury). – Service activity underway at the time of the response-to (verbal or physical refusal to comply), level 2: active (physi resistance, categorized as a cell extraction, escort, event within unit, intake, or other. – Resident injury. – Reason for the use of force, cat egorized as resident assaultive/ combative, resident noncompli ant, or other. – Type of force used, categorized as physical controls (active countermeasures, arm-bar takedowns, close-quarter strikes, empty-hand controls, pressure point controls); restraint controls (emergency restraint chair, handcuffs, hobble restraint, spit-hood); or weapon controls (OC spray, personal weapon, or taser). The study team used the loca tion of the event to determine additional data — including resident sex, security level, and residential capacity — and statis tically compared characteristics of response-to-resistance events between those with body-worn cameras and those without, while also controlling for other factors. 20

Body-worn cameras were as

sociated with a decrease in response-to-resistance events and active resistance from residents, the use of physical controls, and resi dent injuries during those events. CNA researchers determined that there was a statistically significant reduction in response-to-resistance events when body-worn cameras were present. Specifically, there was a 40% decrease in response-to resistance events when a unit had body-worn cameras. – In terms of response-to-resis significantly associated with a 52% reduction in active resis tance from residents during the events. – There was not a significant difference in passive or aggres sive resistance from residents during response-to-resistance events when comparing units with or without body-worn cameras. – There were considerably lower instances of passive (n = 18) and aggressive resistance (n = 12) than active resistance (n = 67), making it more difficult to statistically detect meaningful relationships. – Body-worn cameras were also significantly associated with a 37% reduction in the use of physical controls during response-to-resistance events. – There was not a significant dif ference in the use of restraint controls or weapon controls between units with and with out body-worn cameras during the study period. tance event characteristics: – Body-worn cameras were

Results RTRs and resident injuries

To determine the impact of body-worn cameras on response to-resistance events and resident injuries, CNA researchers analyzed LCADC administrative data per taining to responses to resistance and resident injuries. 18 There were 97 response to resistance events in LCADC over the study period. 19

Corrections Today | Spring 2025

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