This lecture will be on Friday, April 6th from 3:30-5:30 pm. It will be on Northwestern’s Evanston campus in the Ruan Conference Room in the lower level of Chambers Hall at 600 Foster Street. Following Dr. Gallo’s lecture, we invite you to join us for a reception in the same location. This talk will be able to streamed remotely via BlueJeans.
Adolescent men who have sex with men (AMSM) experience a disproportionate burden of new HIV diagnoses among all young people. Fortunately, carefully designed mHealth interventions exist to reach and engage this key population. Mobile health (mHealth) is a general strategy to use mobile phones and other wireless mental health interventions. However, these interventions often send scripted messages while ignoring the linguistic style of participants or the linguistic context in which the scripted messages are received. Linguistic style and context affect people’s interpersonal satisfaction and engagement, as demonstrated in sociology, couple’s counseling, and psycholinguistics. For instance, married couples with similar linguistic styles report higher marital satisfaction and are less likely to separate. HIV research has largely ignored how mHealth participants’ linguistic style affects engagement and satisfaction to the intervention.
This lecture will describe computational linguistic methods that analyze the linguistic style of AMSM in order to optimize peer-to-peer platforms of HIV prevention programs. Also, these methods can inform ways to tailor scripted messages to the linguistic context of the peer-to-peer conversation in an efficient, scalable, non-obtrusive, and automatic manner. In summary, this lecture will demonstrate examples where computational linguistic methods could improve the implementation of future generation mHealth HIV interventions.
Dr. Carlos Gallo is an ISGMH affiliate faculty member whose research aims to facilitate the implementation of evidence based programs (EBPs) by local agencies, particularly those addressing health inequities in LGBT and ethnic minority populations. Dr. Gallo is interested in developing computational methods that monitor implementation indicators and provide real-time feedback useful for health care providers and funding agencies. He has successfully applied his background in systems engineering and computational linguistics to improving parent-training preventive interventions, such as Familias Unidas and New Beginning Programs. Dr. Gallo’s work has enhanced program delivery, leading to improved outcomes among Hispanic youth in terms of risky sexual behaviors, HIV rates, and drug abuse. Dr. Gallo also developed the first machine-based methods to recognize linguistic patterns of a therapeutic alliance between therapist and family. These linguistic patterns are linked to fidelity of implementation, and demonstrate adherence to EBP protocol. His research provides a foundation for efficiently evaluating the translation of EBPs to real world use, thereby closing the gap between research and practice.