Every major U.S. airline has experienced a violent inflight assault on one of their flight attendants. The problem is becoming more widespread, but industry leaders have few coping strategies. The first step toward addressing the issue is understanding the various aspects of the event, including the actions of other passengers (bystanders) who may witness the assault. There is ample literature on bystander reactions to similar events such as bullying, medical emergencies, injuries, and violent attacks, but none dedicated to a flight attendant assault or passenger reactions to it.
At the core of bystander action is the bystander effect, which postulates the inhibiting effect that others have on a person's behavior. Overcoming the inhibition involves a five-step cognitive process. Researchers have modeled and positively applied the process, known as the bystander intervention model, to various helping scenarios (bullying, sexual assault, organ donating, and environmental conservatism) but have thus far left flight attendant assaults unresearched.
The research used partial-least-squares structural equation modeling to expand the understanding of passenger-bystanders and the bystander intervention model by evaluating its applicability to a flight attendant assault and identifying predictors of its steps. Data was collected from adult American air travelers to assess the relevance and strength of the relationships between model steps, their predictors, and a passenger’s likelihood to intervene during an assault. Most outer models showed moderately strong reliability and validity, although step three of the bystander intervention model was removed for having low discriminant validity. The remaining steps showed significant ability to predict their following steps, and only the expectation of a positive outcome was a nonsignificant predictor. However, the resulting disjointedness of the model constrains assigning its relevance to a flight attendant assault. Also included was an evaluation of differences between males and females for those outer models found to be at least partially measurement invariant. This evaluation showed mixed results, attesting to the complexities of the gender variable in bystander studies. The findings broaden the research application of the bystander intervention model and allow practitioners to develop mitigation strategies.
","abstract_html":"<p>Every major U.S. airline has experienced a violent inflight assault on one of their flight attendants. The problem is becoming more widespread, but industry leaders have few coping strategies. The first step toward addressing the issue is understanding the various aspects of the event, including the actions of other passengers (bystanders) who may witness the assault. There is ample literature on bystander reactions to similar events such as bullying, medical emergencies, injuries, and violent attacks, but none dedicated to a flight attendant assault or passenger reactions to it.</p> <p>At the core of bystander action is the bystander effect, which postulates the inhibiting effect that others have on a person's behavior. Overcoming the inhibition involves a five-step cognitive process. Researchers have modeled and positively applied the process, known as the bystander intervention model, to various helping scenarios (bullying, sexual assault, organ donating, and environmental conservatism) but have thus far left flight attendant assaults unresearched.</p> <p>The research used partial-least-squares structural equation modeling to expand the understanding of passenger-bystanders and the bystander intervention model by evaluating its applicability to a flight attendant assault and identifying predictors of its steps. Data was collected from adult American air travelers to assess the relevance and strength of the relationships between model steps, their predictors, and a passenger’s likelihood to intervene during an assault. Most outer models showed moderately strong reliability and validity, although step three of the bystander intervention model was removed for having low discriminant validity. The remaining steps showed significant ability to predict their following steps, and only the expectation of a positive outcome was a nonsignificant predictor. However, the resulting disjointedness of the model constrains assigning its relevance to a flight attendant assault. Also included was an evaluation of differences between males and females for those outer models found to be at least partially measurement invariant. This evaluation showed mixed results, attesting to the complexities of the gender variable in bystander studies. The findings broaden the research application of the bystander intervention model and allow practitioners to develop mitigation strategies.</p>","abstract_has_math":false,"creators":["Pettit, Michael"],"institution":null,"degree_name":"Doctor of Philosophy in Aviation","degree_level":"Dissertation - Open Access","degree_discipline":"College of Aviation","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-04-01T07:00:00Z","date_published":"2024-04-01T07:00:00Z","updated_at":"2026-07-27T19:25:29Z","subjects":["flight attendant","air rage","bystander","bystander intervention model","inflight assault","airline","passenger","structural equation modeling","PLS-SEM","Aviation Safety and Security","Behavior and Behavior Mechanisms"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/804","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Pettit, Michael"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Aviation"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy in Aviation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["flight attendant","air rage","bystander","bystander intervention model","inflight assault","airline","passenger","structural equation modeling","PLS-SEM","Aviation Safety and Security","Behavior and Behavior Mechanisms"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/804"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Every major U.S. airline has experienced a violent inflight assault on one of their flight attendants. The problem is becoming more widespread, but industry leaders have few coping strategies. The first step toward addressing the issue is understanding the various aspects of the event, including the actions of other passengers (bystanders) who may witness the assault. There is ample literature on bystander reactions to similar events such as bullying, medical emergencies, injuries, and violent attacks, but none dedicated to a flight attendant assault or passenger reactions to it.
At the core of bystander action is the bystander effect, which postulates the inhibiting effect that others have on a person's behavior. Overcoming the inhibition involves a five-step cognitive process. Researchers have modeled and positively applied the process, known as the bystander intervention model, to various helping scenarios (bullying, sexual assault, organ donating, and environmental conservatism) but have thus far left flight attendant assaults unresearched.
The research used partial-least-squares structural equation modeling to expand the understanding of passenger-bystanders and the bystander intervention model by evaluating its applicability to a flight attendant assault and identifying predictors of its steps. Data was collected from adult American air travelers to assess the relevance and strength of the relationships between model steps, their predictors, and a passenger’s likelihood to intervene during an assault. Most outer models showed moderately strong reliability and validity, although step three of the bystander intervention model was removed for having low discriminant validity. The remaining steps showed significant ability to predict their following steps, and only the expectation of a positive outcome was a nonsignificant predictor. However, the resulting disjointedness of the model constrains assigning its relevance to a flight attendant assault. Also included was an evaluation of differences between males and females for those outer models found to be at least partially measurement invariant. This evaluation showed mixed results, attesting to the complexities of the gender variable in bystander studies. The findings broaden the research application of the bystander intervention model and allow practitioners to develop mitigation strategies.
"]},{"key":"dc:title","label":"Title","values":["Passenger Traits That Predict the Bystander Intervention Model Steps During an Inflight Assault on a Flight Attendant"]}]}],"canonical_facts":{"dc:creator":["Pettit, Michael"],"dc:description.abstract":["Every major U.S. airline has experienced a violent inflight assault on one of their flight attendants. The problem is becoming more widespread, but industry leaders have few coping strategies. The first step toward addressing the issue is understanding the various aspects of the event, including the actions of other passengers (bystanders) who may witness the assault. There is ample literature on bystander reactions to similar events such as bullying, medical emergencies, injuries, and violent attacks, but none dedicated to a flight attendant assault or passenger reactions to it.
At the core of bystander action is the bystander effect, which postulates the inhibiting effect that others have on a person's behavior. Overcoming the inhibition involves a five-step cognitive process. Researchers have modeled and positively applied the process, known as the bystander intervention model, to various helping scenarios (bullying, sexual assault, organ donating, and environmental conservatism) but have thus far left flight attendant assaults unresearched.
The research used partial-least-squares structural equation modeling to expand the understanding of passenger-bystanders and the bystander intervention model by evaluating its applicability to a flight attendant assault and identifying predictors of its steps. Data was collected from adult American air travelers to assess the relevance and strength of the relationships between model steps, their predictors, and a passenger’s likelihood to intervene during an assault. Most outer models showed moderately strong reliability and validity, although step three of the bystander intervention model was removed for having low discriminant validity. The remaining steps showed significant ability to predict their following steps, and only the expectation of a positive outcome was a nonsignificant predictor. However, the resulting disjointedness of the model constrains assigning its relevance to a flight attendant assault. Also included was an evaluation of differences between males and females for those outer models found to be at least partially measurement invariant. This evaluation showed mixed results, attesting to the complexities of the gender variable in bystander studies. The findings broaden the research application of the bystander intervention model and allow practitioners to develop mitigation strategies.
"],"dc:identifier":["https://commons.erau.edu/edt/804"],"dc:subject":["flight attendant","air rage","bystander","bystander intervention model","inflight assault","airline","passenger","structural equation modeling","PLS-SEM","Aviation Safety and Security","Behavior and Behavior Mechanisms"],"dc:title":["Passenger Traits That Predict the Bystander Intervention Model Steps During an Inflight Assault on a Flight Attendant"],"thesis:degree_discipline":["College of Aviation"],"thesis:degree_level":["Dissertation - Open Access"],"thesis:degree_name":["Doctor of Philosophy in Aviation"]},"updated_at":"2026-07-27T19:25:29Z"}