MoSHI-Led Projects
Active:
Remote Oncology Symptom Assessment (ROSA)
PI: Carissa Low
Funding: NCI R37CA242545
Objective: (1) To develop a system to use mobile sensing to passively monitor patient-reported symptom burden during chemotherapy and (2) to evaluate the feasibility of using this system to generate automated clinical alerts.
Sensing Activity and Gait in Elderly Survivors (SAGES)
PIs: Carissa Low & Grace Campbell
Funding: Pitt Pepper Center Pilot & Duquesne Faculty Development Award
Objective: To examine the association between continuous mobile sensor data features and commonly used measures of physical function in cancer survivors aged 65 and older.
Musculoskeletal Oncology Virtual Evaluation Study (MOVES)
PIs: Kurt Weiss & Carissa Low
Funding: Shadyside Hospital Foundation
Objective: (1) To use mobile technology to assess pain, physical functioning, sleep, and depression as well as objective physical mobility patterns before and after intramedullary nailing procedures for metastatic bone disease and (2) to evaluate the potential clinical benefits of giving orthopedic oncology providers access to an online dashboard visualizing sensor and patient-reported data.
Completed:
Detecting Activity to Support Healing (DASH)
PI: Carissa Low
Funding: NCI K07CA204380
Objective: To refine and test a novel technology-supported intervention to reduce sedentary behavior before and after abdominal cancer surgery.
Results:
- Low CA, Danko M, Durica KC, Kunta AR, Mulukutla R, Ren Y, Bartlett DL, Bovbjerg DH, Dey AK, Jakicic JM. A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Usability and Feasibility Study. JMIR Perioper Med 2020;3(1):e17292
- Low CA, Danko M, Durica KC, Vega J, Li M, Kunta AR, Mulukutla R, Ren Y, Sereika SM, Bartlett DL, Bovbjerg DH, Dey AK, Jakicic JM. A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Pilot Randomized Trial. JMIR Preprints. 26/07/2022:41425
Computational Modeling of Behavioral Rhythms to Predict Readmissions
PIs: Anind Dey & Carissa Low
Funding: Pittsburgh Health Data Alliance
Objective: To develop computational models using passively-sensed behavioral data collected before and after pancreatic cancer surgery to predict real-time readmission risk.
Results:
- Qian C, Leelaprachakul P, Landers M, Low C, Dey AK, Doryab A. Prediction of Hospital Readmission from Longitudinal Mobile Data Streams. Sensors. 2021; 21(22):7510
- Low CA, Li M, Vega J, Durica KC, Ferreira D, Tam V, Hogg M, Zeh III H, Doryab A, Dey AK. Digital Biomarkers of Symptom Burden Self-Reported by Perioperative Patients Undergoing Pancreatic Surgery: Prospective Longitudinal Study. JMIR Cancer 2021;7(2):e27975
Collaborative Projects:
Capturing Habits and Everyday Experiences with Alcohol in Real-time Study (CHEEARS)
PI: Aidan Wright
Funding: NIAAA R01AA026879
Objective: To apply machine learning to data collected from daily surveys and passive smartphone sensors in young adult risky drinkers to develop personalized models of problematic alcohol use.
Predicting recurrences in bipolar illness (PROMPT-BD)
PI: Boris Birmaher
Funding: NIMH R01MH126991
Objective: To use passive sensing of sleep, activity, and sociability to improve prediction of mood recurrences in youth with bipolar illness.
Connectomic Phenotyping of the Mood Switch in Bipolar Disorder (BDLONG)
PI: Danella Hafeman
Funding: NARSAD
Objective: To use passive smartphone sensing to predict changes between euthymia, mania, and depression in teenagers and young adults with rapid cycling bipolar disorder.
Targeting Stress Study (TSS)
PI: Emily Lindsay
Funding: NCCIH K01AT011232
Objective: To refine a smartphone-based mindfulness intervention for adults with a history of early life adversity.
Predicting alcohol use events in people with AUD using mobile sensors: Towards automated telehealth treatment
PI: Walter Roberts, Yale University
Funding: Alkermes Pathways Research Award
Objective:To develop predictive models of alcohol use events in adults with severe alcohol use disorder using physiological, behavioral, and environmental sensing.
Mobile technology to track activity during vestibular rehabilitation
PI: Brooke Klatt
Funding: SHRS Dean’s Research and Development Award
Objective: To characterize associations between activity and impairments before and after vestibular rehabilitation.
The Impact of Social Media Use on Precursors of Adolescent Suicide Risk: A Prospective Study
PI: Jessica Hamilton, Rutgers University
Funding: NIMH K01MH121584
Objective: To harness smartphone technology to examine whether social media use patterns predict sleep disruption, depressive symptoms, and suicidal ideation in adolescents.