54 claims on pp. 8–94 (fact 40, statement 3, evidence 11).
The 2023 report examined 173 acts of mass violence in public and semi-public spaces across the United States over a five-year period.
examined 173 acts of mass violence perpetrated in public and semi-public spaces across the United States over a five-year period
In NTAC's 2023 Mass Attacks in Public Spaces: 2016-2020 study (173 attacks), businesses were the most frequent type of location impacted by mass violence, including restaurants, bars, banks, office spaces, warehouses, and hospitals.
One key finding from the study was that businesses were the most frequent type of location impacted by acts of mass violence
The 50 analyzed incidents are a subset of a population of 173 mass attacks described in NTAC's 2023 report.
The 50 incidents analyzed in this study are a subset from a population of 173 mass attacks
Included incidents harmed three or more people, not counting the attacker(s), and occurred in public or semi-public workplaces.
These incidents resulted in harm to three or more people, not including the attacker(s)
The incidents were perpetrated in public or semi-public workplaces, including restaurants, bars, retail outlets, service centers, manufacturing and distribution facilities, healthcare settings, educational institutions, and military installations.
were perpetrated in public or semi-public workplaces, including restaurants, bars, retail outlets, service centers, manufacturing and distribution facilities, healthcare settings, educational institutions, and military installations
The study uses open sources to examine 50 mass violence incidents on the premises of a business or other work location, covering attacks and attackers' backgrounds and behavioral histories.
describes key findings of research using open sources examining 50 incidents of mass violence which occurred on the premises of a business or other work location
The section presents findings on the characteristics of the attacks and on the backgrounds and behavioral histories of the attackers.
We present findings on the characteristics of the attacks and the backgrounds and behavioral histories of the attackers.
The report examines 50 attacks. These were the attacks analyzed across the study.
Across the 50 attacks examined
Across the 50 attacks examined, 128 people were injured.
128 people were injured
Across the 50 attacks examined, 119 people were killed.
119 were killed
Table 1 lists the location types impacted by the attacks, with n and percentage for each type (retail/services 14, 28%; restaurants/bars 10, 20%; manufacturing/distribution 10, 20%; healthcare 7, 14%; and others).
Sample (N = 50) · incidents (attacks) in the study
Table 1: Locations Impacted
Retail and service outlets were the most frequently impacted location type (n = 14, 28%), including grocery stores, hotels, salons, banks, law firms, and technology companies.
Sample (n = 14 of 50) · incidents (attacks) in the study
Retail and service outlets were the most frequently impacted location type (n = 14, 28%)
Restaurants and bars were among the commonly impacted location types (n = 10, 20%).
Sample (n = 10 of 50) · incidents (attacks) in the study
Restaurants/Bars | 10 | 20%
Manufacturing and distribution sites were among the commonly impacted location types (n = 10, 20%).
Sample (n = 10 of 50) · incidents (attacks) in the study
Manufacturing/Distribution | 10 | 20%
Healthcare settings were among the commonly impacted location types (n = 7, 14%).
Sample (n = 7 of 50) · incidents (attacks) in the study
Healthcare | 7 | 14%
Location-type totals exceed 50 because 3 attacks took place in more than one location type.
Total will exceed 50 as 3 attacks took place in more than one location type.
A 45-year-old gunman fatally shot four people across three locations after confronting his wife over divorce papers, including her coworkers and divorce attorney. He then held police off in a three-hour standoff and was shot by law enforcement, dying later of his injuries.
A 45-year-old gunman fatally shot four individuals in a shooting spree across three locations.
After fleeing police, the attacker positioned a rifle at his apartment window and fired at responding officers, killing one.
Afterward, the attacker fled from police, drove to his apartment, positioned a rifle at his window, and fired at responding law enforcement, killing one officer.
A three-hour standoff followed, during which the attacker repeatedly called dispatch demanding reform in how assets are divided during divorce.
A three-hour long standoff ensued, and the attacker called dispatch multiple times, demanding reform in how assets are divided during divorce.
Many different types of workplaces were impacted by these incidents of mass violence, as shown in Table 1.
Many different types of workplaces were impacted by these incidents of mass violence, as illustrated in Table 1.
Table 1 reports that retail and services locations were impacted in 14 attacks (28%).
Sample (n = 14 of 50) · incidents (attacks) in the study
Retail/Services | 14 | 28%
Table 1 reports that open spaces were impacted in 4 attacks (8%).
Sample (n = 4 of 50) · incidents (attacks) in the study
Open Spaces | 4 | 8%
Table 1 reports that residential community locations were impacted in 2 attacks (4%).
Sample (n = 2 of 50) · incidents (attacks) in the study
Residential Community | 2 | 4%
Table 1 reports that non-profit services locations were impacted in 2 attacks (4%).
Sample (n = 2 of 50) · incidents (attacks) in the study
Non-profit Services | 2 | 4%
Table 1 reports that government locations were impacted in 2 attacks (4%).
Sample (n = 2 of 50) · incidents (attacks) in the study
Government | 2 | 4%
Table 1 reports that an education location was impacted in 1 attack (2%).
Sample (n = 1 of 50) · incidents (attacks) in the study
Education | 1 | 2%
Table 1 reports that a military location was impacted in 1 attack (2%).
Sample (n = 1 of 50) · incidents (attacks) in the study
Military | 1 | 2%
A 39-year-old man stabbed a counselor and other employees at a mental health center after the center had determined that morning he was not appropriate for its treatment program. He was subdued by a client until police arrived.
A 39-year-old man entered a mental health treatment center.
Table 3 illustrates how the attacks were resolved, broken down by whether attackers stopped on their own, law enforcement intervened, bystanders intervened, or the attack was otherwise ended.
Table 3 illustrates how attacks were resolved.
The attacker drew a concealed knife in a room with a female counselor, stabbed her repeatedly, then slashed and stabbed other employees.
When placed in a room with a female counselor, the man drew a knife concealed under his waistband and began to stab her repeatedly before exiting the room and slashing and stabbing numerous other employees.
Before the cemetery attack, the attacker rigged his apartment, garage, and an adjacent residence with a series of incendiary devices, which were detected before they could detonate.
Prior to the attack at the cemetery, the attacker rigged his apartment, garage, and an adjacent residence with a series of incendiary devices, which were detected before they could detonate.
The attack took place on the day of the hospital's residency program graduation.
The attack date coincided with the hospital's residency program graduation.
All triggering events occurred within one month of the attack, ranging from 2.5 hours to 2-4 weeks before the incident.
These triggering events all occurred within one month of the attack, ranging from 2.5 hours to 2-4 weeks prior to the incident
Each of these attackers carried out their attack alone.
Each of these attackers carried out their attack alone
A 37-year-old man called an impromptu meeting at his manufacturing workplace, shot five coworkers (three killed), then drove to two more locations and shot a business owner he knew.
On October 18, 2017, a 37-year-old man gathered coworkers around him by calling an impromptu meeting at the manufacturing facility where he worked
The attacker drew a semiautomatic pistol and shot five colleagues in the head, killing three and injuring two.
He then drew a semiautomatic pistol and shot five of his colleagues in the head, killing three and injuring two others.
After the shooting, the attacker drove to two more locations: a former workplace, where he likely targeted his former boss who was not there, and another location, where he shot and injured a business owner he knew.
including a former workplace where he likely targeted his former boss who was not there, and another location where he shot and injured a business owner he knew
The attacker began working at the manufacturing facility about four months before the attack.
The attacker began working at the manufacturing facility about four months before the attack.
A majority of incidents in healthcare settings involve assaults by patients or visitors against nurses and emergency department staff.
A majority of incidents in healthcare settings involve assaults perpetrated by patients or visitors against nurses and staff of emergency departments.
Data Table 1 (Incident Data) reports weapons, location types, motives, total casualties (injured and killed), and resolution for all attacks (n = 50) and for current or former employees (n = 22), customers, clients, patients, and visitors (n = 19), and romantic partners and relatives (n = 9). The column ns printed are 50 | 22 | 19 | 9.
APPENDICES: DATA TABLE 1
Data Table 1 column headers give all attacks as n = 50 / 29%, current or former employees as n = 22 / 13%, customers, clients, patients, and visitors as n = 19 / 11%, and romantic partners and relatives as n = 9 / 5%.
Sample (n = 50 of 173) · mass attacks (2016-2020) in the NTAC 2023 population from which the 50 workplace incidents were drawn
| INCIDENT DATA | All Attacks<br>n = 50 / 29% | Current or Former Employees<br>n = 22 / 13% | Customers, Clients, Patients, and Visitors<br>n = 19 / 11% | Romantic Partners and Relatives<br>n = 9 / 5% |
Why inferred table header: the column headers are printed in the table; the <br> marks the line break inside each printed header cell and is not printed text
Data Table 1 reports businesses as the location type in 86% of all attacks (n = 50), 95% of attacks by current or former employees (n = 22), 74% by customers, clients, patients, and visitors (n = 19), and 89% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Businesses | 86% | 95% | 74% | 89%
Data Table 1 reports restaurants/bars (a business sub-type) as the location in 20% of all attacks (n = 50), 5% of attacks by current or former employees (n = 22), 37% by customers, clients, patients, and visitors (n = 19), and 22% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Restaurants/Bars | 20% | 5% | 37% | 22%
Data Table 1 reports retail (a business sub-type) as the location in 6% of all attacks (n = 50), 9% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 11% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Retail | 6% | 9% | 0% | 11%
Data Table 1 reports services (a business sub-type) as the location in 22% of all attacks (n = 50), 23% of attacks by current or former employees (n = 22), 21% by customers, clients, patients, and visitors (n = 19), and 22% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Services | 22% | 23% | 21% | 22%
Data Table 1 reports manufacturing/distribution (a business sub-type) as the location in 20% of all attacks (n = 50), 45% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 0% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Manufacturing/Distribution | 20% | 45% | 0% | 0%
Data Table 1 reports healthcare (a business sub-type) as the location in 14% of all attacks (n = 50), 9% of attacks by current or former employees (n = 22), 16% by customers, clients, patients, and visitors (n = 19), and 22% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Healthcare | 14% | 9% | 16% | 22%
Data Table 1 reports government/military (a business sub-type) as the location in 6% of all attacks (n = 50), 9% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 11% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Government/Military | 6% | 9% | 0% | 11%
Data Table 1 reports government (a sub-row of government/military) as the location in 4% of all attacks (n = 50), 5% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 11% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Government | 4% | 5% | 0% | 11%
Data Table 1 reports military (a sub-row of government/military) as the location in 2% of all attacks (n = 50), 5% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 0% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Military | 2% | 5% | 0% | 0%
Data Table 1 reports a residential community as the location in 4% of all attacks (n = 50), 0% of attacks by current or former employees (n = 22), 11% by customers, clients, patients, and visitors (n = 19), and 0% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Residential Community | 4% | 0% | 11% | 0%
Data Table 1 reports open space as the location in 8% of all attacks (n = 50), 9% of attacks by current or former employees (n = 22), 5% by customers, clients, patients, and visitors (n = 19), and 11% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Open Space | 8% | 9% | 5% | 11%
Data Table 1 reports a school as the location in 2% of all attacks (n = 50), 0% of attacks by current or former employees (n = 22), 0% by customers, clients, patients, and visitors (n = 19), and 11% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
School | 2% | 0% | 0% | 11%
Data Table 1 reports non-profit services as the location in 4% of all attacks (n = 50), 0% of attacks by current or former employees (n = 22), 11% by customers, clients, patients, and visitors (n = 19), and 0% by romantic partners and relatives (n = 9).
Sample (N = 50 | 22 | 19 | 9 by column) · Data Table 1 columns: all attacks 50 | employees 22 | customers, clients, patients, visitors 19 | partners and relatives 9
Non-profit Services | 4% | 0% | 11% | 0%
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