Additional Resources:

Program Profile: Police Body-Worn Cameras (Rialto, Calif.)

Evidence Rating: Promising - One study Promising - One study

Date: This profile was posted on November 28, 2016

Program Summary

This program equips individual police officers with body-worn cameras to record police encounters during shifts. The program aims to reduce use-of-force incidents and citizen complaints by increasing mutual accountability. The program is rated Promising. There was a significant reduction in police use-of-force, but no significant difference in citizens’ complaints.

This program’s rating is based on evidence that includes at least one high-quality randomized controlled trial.

Program Description

Program Goals/Program Components
Video surveillance technology, already in use by law enforcement in the form of CCTV, has been adapted to be worn by frontline police officers in order to assist in the gathering of evidence and to record police encounters with the public. This involves equipping an officer with an audiovisual-recording apparatus (i.e., a body-worn camera), which is small enough to be worn by police officers without encumbering them in the conduct of regular police work, and developing a system to store and review the data gathered by the device. Advances in the field of miniaturization have led to the development of small yet robust devices that can be worn on the chest, collar, or shoulder, or mounted on glasses or a helmet. These cameras operate as mobile CCTV units, and record police activity and encounters while officers are out in the field.
There are a number of reasons for police to use body-worn cameras. One is to help in the gathering of evidence and accurate reporting of events. Another objective is to encourage mutual accountability during difficult police–citizen encounters. The objective of having police use body-worn cameras is to reduce the number of use-of-force incidents and reduce the number of complaints from the community by monitoring all police–citizen encounters.
One jurisdiction that has adopted the use of body-worn cameras is Rialto, California. The Rialto Police Department serves a population of approximately 100,000 residents, and employs 115 sworn police officers and 42 non-sworn staff. The devices used in Rialto are small enough to fit into the officers’ shirt pockets; they also provide high-definition color video and audio, are water resistant, and have a battery life greater than 12 hours. Police are instructed to use these cameras for every police interaction with the public, except in cases of sexual assault of a minor or when dealing with police informants. The devices are visible to the citizens who are interacting with the officers. All the data are automatically uploaded, collated, and inventoried in a web-based, video-management system at the end of each shift.
Program Theory
The theoretical foundation for the use of body-worn cameras and their effects on reducing problem behaviors is rooted in deterrence theory and social surveillance. With regard to deterrence theory, as the certainty of detection or apprehension for wrongdoing is perceived to increase, the incidence of such behavior should decrease. Body-worn cameras should therefore increase people’s perceptions of the risk of detection or apprehension because their actions will be caught on camera (this applies to the behavior of both suspects and police).
Additionally, with social surveillance, research suggests that people will adhere to social norms and change their conduct when they are aware that someone else is watching. When people are aware that their actions are being monitored, they are more likely to behave in a socially acceptable manner in an effort to avoid the negative outcomes associated with being caught breaking rules. The body-worn cameras may have a “self-awareness effect”, which could impact both suspects and police. Suspects would be less likely to act aggressively in a situation, and police officers would be less likely to react with excessive or unnecessary force ((Ariel, Farrar, and Sutherland 2015).

Evaluation Outcomes

top border
Study 1
Use-of-Force Incidents
During the study period Ariel, Farrar, and Sutherland (2015) recorded a total of 25 incidents of police use-of-force, with 17 occurring during the control shifts and only 8 during the experimental shifts. The mean rate of use-of-force was 0.33 incidents per 1,000 police–public contacts in the experimental condition, compared with a rate of 0.78 per 1,000 contacts in the control condition (a significant difference). 
Although the use-of-force rate was significantly lower for the experimental condition, the probability of an incident was very low in both conditions. Overall, use-of-force rate was significantly reduced by more than half for the entire department, compared with previous years.
Citizen Complaints
There were only three citizen complaints during the study period, with one of those occurring for a control shift and the other two relating to an experimental shift (no statistical difference).
While the low number of incidences led to no significant differences between the groups, the results showed that the department-wide numbers of citizen complaints were reduced tenfold, compared with previous years.
bottom border

Evaluation Methodology

top border
Study 1
Ariel, Farrar, and Sutherland (2015) conducted a randomized experiment on the effects of police body-worn cameras on use-of-force incidents and citizen complaints against the police in the city of Rialto, in San Bernardino County, California. Covering 28.5 square miles, the Rialto Police Department serves a population of approximately 100,000 residents, and employs 115 sworn police officers and 42 non-sworn staff. The department handles roughly 3,000 property and 500 violent crimes per year; it handled about six to seven homicides per year in the period from 2009 to 2011, which is almost 50 percent higher than the national per capita homicide rate. 
Every frontline officer in the Rialto Police Department took part in the experiment (n = 54), although the study authors  used shifts as the unit of analysis and randomization. Each 12-hour shift consisted of roughly 10 armed frontline officers patrolling the streets of Rialto, responding to calls for service, and interacting with the public. 
Beginning in February 2012, and lasting a year, the study consisted of randomly assigning all shifts on a weekly basis to either an experimental or control condition. In the experimental shifts, officers were required to wear a high-definition, video- recording apparatus fitted to their collar, which would record all of their activities during the shift. Although the device would be visible to citizens interacting with the officers, the police also informed anyone they interacted with that they were being videotaped. A total of 988 shifts were randomly assigned during the 1-year study, resulting in 489 experimental shifts and 499 control shifts, which were patrol shifts “as usual”. The researchers measured the contacts between the police and the public in every shift for all non-casual encounters (calls for service, collecting evidence and statements, formally advising individuals, etc.), which allowed them to compute incident rates per 1,000 police–public encounters. 
The devices used in the experimental condition were small enough to fit into the officers’ shirt pockets, and provided high- definition color video and audio, were water resistant, and had a battery life greater than 12 hours. The officers were instructed to use the devices for every police interaction with the public, except for those involving cases of sexual assault of a minor or when dealing with police informants. All the data was automatically uploaded, collated, and inventoried in a web-based, video-management system at the end of each shift, and was available to the researchers. 
One of the two outcomes of interest was use-of-force. The Rialto Police Department uses a standardized tracking system that records instances of use-of-force that are beyond basic control and compliance holds, including the use of pepper spray, a baton, a Taser, a canine bite, or a firearm. For the purposes of this study, the researchers operationalized use-of-force as whether or not force was used during a given shift. Use-of-force was counted only as instances of force, and not the degree of force used, the length of that use, or who instigated the use-of-force. 
The second outcome of interest was citizen complaints against officers. These data were tracked by the Rialto Police Department through software that records citizens’ complaints of alleged police misconduct or poor performance. The researchers used these data to count the number of complaints of any type filed against officers. 
Poisson regression models were used to assess the differences between the experimental and treatment shifts in terms of use-of-force and citizen complaints. The authors acknowledged some limitations of the study, including the Hawthorne and John Henry effects. The Hawthorne effect refers to how individuals change their behavior in response to their awareness of being observed, while the John Henry effect refers to the degree to which comparison subjects change their behavior when they become aware that their performance is being compared with a treatment condition. Given that a frontline police officer may have been involved in both experimental and treatment shifts over the study period, both these effects may be at work in reporting mechanisms. However, the researchers also looked at the overall effect that their experiment had on the Rialto Police Department, by examining the previous years’ reports for both use-of-force and citizen complaints.
bottom border


top border
The total cost of the body-worn cameras for the Rialto Police Department was around $90,000. This included 70 complete video camera units and mounts, charging/docking stations, video management and data upload and tracking system, and training for the trainers/technicians and officers (Note: For further information on program costs, see Supplementary Material in Ariel, Farrar, and Sutherland 2015 ).
bottom border

Other Information (Including Subgroup Findings)

top border
Ariel and colleagues (2016) conducted subgroup analyses to examine the effect of officers’ discretion on activating body- worn cameras. They found that when officers in the experimental condition followed the study protocol (i.e., they did not use discretion to decide when and where the cameras were turned on or off) use-of-force rates were 37 percent lower, compared with the control condition. When officers in the experimental condition did not follow the study protocol (i.e., they chose when to turn the cameras on or off), use-of-force rates were 71 percent higher, compared with the control condition. This suggests body-worn cameras can reduce use-of-force rates when police officers’ discretion to turn the cameras on or off is minimized (Ariel et al. 2016).
bottom border

Evidence-Base (Studies Reviewed)

top border
These sources were used in the development of the program profile:

Study 1
Ariel, Barak, William A. Farrar, and Alex Sutherland. 2015. “The Effect of Police Body-Worn Cameras on Use of Force and Citizens’ Complaints Against the Police: A Randomized Controlled Trial.” Journal of Quantitative Criminology 31:509–35.

bottom border

Additional References

top border
These sources were used in the development of the program profile:

Ariel, Barak, Alex Sutherland, Darren Henstock, Josh Young, Paul Drover, Jayne Sykes, Simon Megicks, and Ryan Henderson. 2016. “Increases in Police Use of Force in the Presence of Body-Worn Cameras are Driven by Officer Discretion: A Protocol-Based Subgroup Analysis of Ten Randomized Experiments.” Journal of Experimental Criminology 12(3):453–63.

bottom border

Program Snapshot

Geography: Suburban, Urban

Setting (Delivery): Other Community Setting

Program Type: Community and Problem Oriented Policing, Violence Prevention, General deterrence

Current Program Status: Active

Program Developer:
Barak Ariel
Institute of Criminology, Faculty of Law, Hebrew University, Mount Scopus
Jerusalem 91905
Phone: 44.7838.776585