Projects from Collaboration with CMU, CiTech, and CBMHT
Collaborative Interactive Fanfiction as a Novel Medium for Transformative Personal Expression and Social Support for Transgender Youth
Geoff Kaufman, PhD of Carnegie Mellon University's Human-Computer Interaction Institute
Chinmay Kulkarni, PhD of Carnegie Mellon University's Human-Computer Interaction Institute
César Escobar-Viera, MD, PhD of the University of Pittsburgh's Center for Research on Media, Technology, and Health
Transgender youth are at an increased risk of depression and other negative health issues due to prejudice and homophobia pervasive in the world today. Social isolation can worsen these symptoms, so by creating an intervention that both combats isolation and reinforces positive self-affirmations, the investigators hope to support transgender youth using creative methods. Fanfiction, a type of writing that interests many transgender youth, takes preexisting characters and plotlines from popular media like TV shows or books and writes new content. With this concept in mind, the researchers hope to develop an intervention that makes fanfiction interactive for the user to share struggles and experiences and receive advice from near-peer mentors to increase community connection and minimize negative mental health risks in transgender youth.
imHere4U: An Online Suicide Prevention Intervention for Cyberbullied Adolescents
Candice Biernesser, PhD, LCSW of the University of Pittsburgh's Pitt Cyber Institute
Robert Kraut, PhD of Carnegie Mellon University's Human-Computer Interaction Institute
Brian Thoma, PhD of the University of Pittsburgh's Department of Psychiatry
Suicide is the 2nd leading cause of death in adolescents, and bullying increases the risk of suicidal ideation. Cyberbullying as well is becoming a more menacing threat as the use of technology continues to skyrocket during the COVID-19 pandemic, diminishing teens' ability to escape the bullies or meaningfully confide in teachers and friends. Only 11% of adolescents actually report cyberbullying, thus worsening the risk of suicide. imHere4U aims to decrease the mental toll of cyberbullying by providing immediate intervention through use of an existing algorithm that can detect signs of cyberbullying on social media. Researchers hypothesize that offering support immediately after a cyberbullying incident will decrease adolescents' risk of suicidal ideation and further negative effects.
Co-designing Effective Human–Algorithm Collaborations for Suicide Risk Assessment with Clinicians, Teens, and Families
Ken Holstein, PhD of Carnegie Mellon University's Human-Computer Interaction Institute
Neal Ryan, MD of the University of Pittsburgh's Department of Psychiatry
Jamie Zelazny, PhD, MPH, RN of the University of Pittsburgh's School of Nursing
The risk of adolescent suicide is gaining recognition, especially during the COVID-19 pandemic where teens may feel isolated from peers and school educators and counselors are not as able to check for signs of suicidality. A growing body of research focuses on the development of predictive suicide risk algorithms and decision support tools to aid clinicians in identifying cases that may otherwise go undetected and untreated. However, clinicians, families, and other stakeholders have typically had limited input regarding how these algorithmic tools should be designed and used in practice. The researchers plan to conduct iterative, participatory design workshops to engage stakeholders in collaboratively re-envisioning the roles of algorithmic decision supports in clinical suicide risk assessment. Workshop participants will help shape the design of new interfaces to facilitate decision-making and communication around algorithmic predictions. This research aims to inform ongoing efforts to develop such technologies (at UPMC and beyond) with the goal of supporting more effective and ethical implementations in practice.
Pilots from Frontline Behavioral Health Innovation Contest
Augemented Reality Exposure Therapy for Treatment of Needlephobia
Augmented reality exposure therapy to treating needle phobia. The study would design and evaluate an augmented mini reality game that would make exposure therapy for needles more approachable, engaging, & less scary for children, increasing likelihood of successful injection.
Angelina Gradian, MS, LPC
ETUDES PARTNERS: Dmitriy Babichenko, PhD, Jen Silk, PhD
Young Adult College Health Transition: A Guide to Autonomy, Healthy Bodies, and Healthy Minds
Utilize a video platform for teens age 16 yo+ to prepare for college transition mentally and physically. A series of short videos would be available to all teens to promote a healthy lifestyle, recognize mental health issues before college, explain importance of seeking help early, and learn how to recognize crisis in others. This has the potential expand to videos on specific topics and can be utilized globally. Focus is on autonomy and the understanding that mental and physical health are one in the same.
Dawn Gotkiewicz, MD
Barbara Giannini, LPC
ETUDES PARTNER : Tina Goldstein, PhD
Mindfulness Based Intervention to Promote Mental Health Wellbeing Amongst Latino Youth Community
Augment in-person group therapy with online/social networking group with incorporation of CBT to reinforce community connectedness among an emerging community that may have limited access to in-person treatment in their area.
Claudia Ardiles, MSEd, LPC
ETUDES PARTNERS: César Escobar-Viera, MD, PhD, Patricia Documét, PhD
Utility of a Single Session Intervention to Improve Acceptance of Further Psychotherapeutic Interventions and Instill Hopefulness for Depressed and / or Anxious Youth and their Caretakers
A 30-minute computerized intervention to promote “growth orientation” (belief that a person can change) has been shown to decrease depression and anxiety. We want to learn if this intervention can also lead to increased engagement in services.
Sheree Shaffer, DNP, FNP-BC, PMH, CNS-BS
Suzanne Reitz, MD
Jessica Schleider, PhD
ETUDES PARTNER: David Brent
ETUDES Pilot Projects
Developing and Assessing the Acceptability of a Social Media—Delivered Intervention to Optimize Social Media use and Reduce Social Isolation Among Rural Sexual and Gender Minority Youth
César Escobar-Viera, MD, PhD of the University of Pittsburgh's Center for Research on Media, Technology, and Health. A Pilot Contest winner.
Lesbian, gay, bisexual, transgender, and queer/questioning youth (LGBTQY) are at 2–3 times higher risk of social isolation and depression than their non-LGBTQ-identifying peers. These risks are much higher for rural LGBTQY outcomes than urban LGBTQY. Of 6 million LGBTQY in the United States, about 2 million live in rural areas with a lack of diversity and resources, which can increase social isolation and thus risk of depression. To fill the need for community, LGBTQY reach out to social media to connect with others like them or seek support. However, social media can also lead to feelings of rejection, discrimination, and other negative experiences, potentially increasing social isolation and depression risk. Dr. Escobar-Viera’s study aims to diminish the risk of social isolation among LGBTQY by delivering a psycho-educational intervention online that informs teens of how to more positively engage with social media.
Feasibility and Utility of Passive Mobile Technologies for Monitoring Symptoms and Treatment Progress in Depressed and/or Suicidal Youth
Lori Scott, PhD of the University of Pittsburgh's Department of Psychiatry. A Pilot Contest winner.
Suicide is a leading cause of death among American youth. In spite of decades of suicide research, known suicide risk factors fail to accurately predict which individuals will attempt or die by suicide. Sensors embedded in personal smartphones can passively assess changes in sleep, physical activity, and social engagement, which can predict fluctuations in psychiatric symptoms such as depression and mania. However, the use of these tools to understand teens is not yet adequately studied. Dr. Scott’s research study aims to use these passive mobile sensors to provide information on a real-time basis in hopes to significantly advance care for youth at risk for suicide. To monitor these changes, Dr. Scott will examine whether emotional regulation skills practiced through use of the BRITE app result in significant changes in these objective markers of behavior and physiology over time. The proposed work will serve as a foundation for future research efforts to develop and test novel risk monitoring and real-time intervention tools.
Multiplayer RPG as depression isolation intervention
Dmitriy Babichenko, PhD of the University of Pittsburgh's School of Computing and Information
Numerous studies have revealed that children and adolescents with pediatric-onset chronic diseases (POCD), as well as their caregivers, are at an increased risk for depression and anxiety, with serious direct and indirect negative effects on treatment adherence, family functioning, and health-related quality of life. Additionally, living with a chronic disease can place adolescents at higher risk for poor educational, vocational, and social outcomes and lead to isolation from peers. Regular participation in social activities with peers is particularly crucial in adolescence where it can provide a critical key component for developing healthy psychological development. Moreover, support from peers can also play a significant role in helping young people with POCD cope with the illness and with its “inherent psychosocial and lifestyle changes”. In order to address some of the issues inherent to social isolation and lack of peer support, the MASKS study proposes a novel method of engaging adolescents with POCD through role-playing game (RPG) communities.
MoodRing
Ana Radovic, MD of the University of Pittsburgh's Department of Adolescent and Young Adult Medicine
The MoodRing study works to adapt machine algorithms, which were developed for passive sensing in college-aged youth to adolescents with depression, to help detect and monitor depression symptoms. Personal sensor data from smartphones tracks sleep, and a provided activity tracker tracks heart rate variabilty. Data will be taken from 55 adolescents with depressive symptoms and compared with weekly online surveys for 24 weeks to understand whether depressive symptoms can be predicted in adolescents by using this passive sensing technique. Frequent passive monitoring with the potential to detect depression could help adolescents notice their symptoms and employ early self-management interventions, while also alerting parents and clincians of any worsening symptoms and ultimately avoid crisis situaitions.
An Open Pilot Study of Transdiagnostic Sleep and Circadian Intervention (TranS-C) for Youth At-Risk for Suicide
Adriane Soehner, PhD of the University of Pittsburgh's Department of Psychiatry
Tina Goldstein, PhD of the University of Pittsburgh's Department of Psychiatry
Peter Franzen, PhD of the University of Pittsburgh's Department of Psychiatry
Sleep and circadian difficulties have been identified as important warning signs of suicidality in adolescents. However, of yet no interventions exist that aim to treat sleep disturbances in adolescents at-risk for suicide. The researchers have developed a unique Transdiagnostic Sleep and Circadian Intervention (TranS-C) that aims to decrease sleep and circadian difficulties common in adolescence to in turn mitigate risk of suicide. The intervention combines sleep diaries and patient-reported symptoms with data from actigraphs worn while asleep to then inform a personalized treatment plan developed with the parents and the teen. The researchers expect that the intervention will calm sleep disturbances and significantly reduce suicidality.
Guide2BRITE AFSP
Stephanie Stepp, PhD of the University of Pittsburgh's Department of Psychiatry
The overall goal of this study aims to develop and test BRITEPath, an app-supported intervention to guide pediatric primary care clinicians in effectively treating depressed and suicidal adolescents in primary care. We have developed the three components of the BRITEPath intervention: (1) Guide2BRITE, an electronic guide for primary care clinicians providing step-by-step instructions in the onboarding of the safety plan, emotion regulation, and distress tolerance skills for (2) the BRITE app, a personalized and interactive safety plan and self-monitoring tool for the adolescent, and (3) the clinician dashboard, BRITEBoard, to track adolescents' app use, distress ratings, and treatment progress as well as to promote communication and collaboration among primary care clinicians. We will conduct an open trial to examine the feasibility and initial outcomes of BRITEPath in primary care among 40 adolescents and young adults aged 12-26.
Data Mining of the Electronic Health Record to Identify Youth with Depression and Suicidality
This study, headed by Drs. Rich Tsui and Neal Ryan, aims to use machine learning (ML) and natural language processing (NLP) of pediatric health records to identify youth at risk for depression. Current recommendations are to screen youth once a year for depression with the Patient Health Questionnaire-9 (PHQ-9) to identify youth with depression who may otherwise go undetected and untreated. The investigators believe that the use of ML and NLP of pediatric electronic health records (EHR) may aid in the identification of youth at risk for depression and suicidal ideation or behavior. If the investigators can demonstrate that youth who will screen positive for depression and/or suicidal ideation can be accurately identified by data already contained in their EHRs, it will allow the providers to anticipate which patients are likely to screen positive and proactively allocate additional time for intervention. Moreover, theremay be patients who have previously been in treatment or are currently undergoing treatment for depression who may require closer scrutiny (e.g., more frequent monitoring) that such an algorithm has the potential to accurately identify.Qualitative Study to Inform the Implementation of a Predictive Suicide Risk Algorithm
Jamie Zelazny, PhD, MPH, RN of the University of Pittsburgh's School of Nursing
With the increasing risk of adolescent suicide, there is extensive research being conducted on how to better detect and predict suicidality. Recently, natural language processing (NLP) and machine learning algorithms have shown promise for predicting suicidal risk in UPMC patients from their health records. This study aims to investigate the best implementation methods of this algorithm. Qualitative interviews will be conducted with clinicians, families, attorneys, and bioethicists to assess the feasability and efficacy of the algorithm as well as any ethical, legal, and medical issues that could arise. The researchers hope that once the algorithm's potential is evaluated, it can be put into practice to better predict and protect against adolescent suicidality.