Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

ABSTRACT: Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic pain are known sequelae of IPV; however, not all those who experience IPV develop chronic pain. To mitigate its development, it is critical to identify the factors that are associated with increased risk of pain after IPV. This proof-of-concept study used machine-learning strategies to predict pain severity and interference in 47 young women, ages 18 to 30, who experienced an incident of IPV (i.e., physical and/or sexual assault) within three months of their baseline assessment. Young women are more likely than men to experience IPV and to subsequently develop posttraumatic stress disorder (PTSD) and chronic pain. Women completed a comprehens

SUBMITTER: Lannon E 

PROVIDER: S-EPMC8320990 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature