This K24 proposal builds on my strong record of successful mentoring and original investigation to generate research capacity in the area of mobile technologies to improve health (mHealth). I have mentored 21 clinician-scientists, 15 of whom have been awarded NIH funding under K23, K08, R01, R21, R03, Loan Repayment Program, and Minority Supplement mechanisms. Of the 16 clinician-scientists whom I currently mentor, 12 have engaged in mHealth-related research. My responsibilities in the University of Massachusetts (UMass) CTSA-funded mentoring programs, my collaborations with the NIDA-funded P30 Center for Technology and Behavioral Health at Dartmouth Medical School, referrals from NIDA program staff, and other efforts have expanded the scope of my mentoring and ensured a nationwide source of mentees. My patient-oriented research focuses on mHealth approaches to substance abuse treatment and improving medication adherence in persons with HIV. The striking increase in the use of mobile technologies has created great opportunities for delivery of health interventions in natural environments at the time and location they are needed most. Despite the broad reach, multimedia capabilities, and computing power of mobile technologies, several features threaten the acceptability of smartphone-delivered behavioral interventions and detract from their enormous potential as effective health promotion tools. The ultimate goal of this proposal, therefore, is to create mobile technology-driven interventions capable of producing persistent beneficial health effects. The overall research goal of the K24 is to develop new classes of mHealth behavioral interventions through three synergistic research thrusts. The first involves the development of advanced mHealth behavioral interventions that support long-term abstinence, prevent relapse, and promote antiretroviral adherence in HIV+ patients. The second involves development of mobile biosensing methods that can assess the effectiveness of these highly innovative interventions by identifying the onset and duration of drug use episodes. In a third line of investigation, I intend to elucidate the design elements that will maximize the usability and acceptability of novel mHealth behavioral interventions. The overall mentoring objective of this K24 is to develop researchers who not only have the skills to develop, implement, and publish hypothesis driven, patient-oriented mHealth research, but who understand the importance of bringing a multi-method, multi-disciplinary approach to clinical and translational research problems. My mentoring approach emphasizes the importance of tailoring research methods to the nature of the problem of interest, even if that means learning new behavioral science, engineering, and clinical research methods or developing collaborations with investigators from other disciplines familiar with those methods. The proposed research is relevant to the NIH's mission because the lessons learned from this drug abuse- and HIV-related work are directly applicable to the care of patients with other common, intractable, and expensive conditions amenable to behavioral interventions.
This K24 grant will support the training and launching of careers of a strong cadre of rigorously trained new patient oriented drug abuse investigators dedicated to using novel approaches to expand knowledge and develop new avenues for clinical applications of mobile health (mHealth) technologies to promote abstinence, prevent relapse, and support adherence to antiretroviral medications in HIV+ persons.
|Lai, Jeffrey T; Chapman, Brittany P; Boyle, Katherine L et al. (2018) Low-energy Bluetooth for detecting real-world penetrance of bystander naloxone kits: a pilot study. Proc Annu Hawaii Int Conf Syst Sci 2018:3253-3258|
|Broach, John; Hart, Alexander; Griswold, Matthew et al. (2018) Usability and Reliability of Smart Glasses for Secondary Triage During Mass Casualty Incidents. Proc Annu Hawaii Int Conf Syst Sci 2018:1416-1422|
|Carreiro, Stephanie; Chai, Peter R; Carey, Jennifer et al. (2018) mHealth for the Detection and Intervention in Adolescent and Young Adult Substance Use Disorder. Curr Addict Rep 5:110-119|
|Ouchi, Kei; Lindvall, Charlotta; Chai, Peter R et al. (2018) Machine Learning to Predict, Detect, and Intervene Older Adults Vulnerable for Adverse Drug Events in the Emergency Department. J Med Toxicol 14:248-252|
|Chai, Peter R; Carreiro, Stephanie; Carey, Jennifer L et al. (2018) Faculty member writing groups support productivity. Clin Teach :|
|Chai, Peter R; Hayes, Bryan D; Erickson, Timothy B et al. (2018) Novichok agents: a historical, current, and toxicological perspective. Toxicol Commun 2:45-48|
|Griswold, Matthew K; Chai, Peter R; Krotulski, Alex J et al. (2018) Self-identification of nonpharmaceutical fentanyl exposure following heroin overdose. Clin Toxicol (Phila) 56:37-42|
|Chintha, Keerthi Kumar; Indic, Premananda; Chapman, Brittany et al. (2018) Wearable Biosensors to Evaluate Recurrent Opioid Toxicity After Naloxone Administration: A Hilbert Transform Approach. Proc Annu Hawaii Int Conf Syst Sci 2018:3247-3252|
|Chai, Peter Ray; Zhang, Haipeng; Baugh, Christopher W et al. (2018) Internet of Things Buttons for Real-Time Notifications in Hospital Operations: Proposal for Hospital Implementation. J Med Internet Res 20:e251|
|Chai, Peter R; Carreiro, Stephanie; Innes, Brendan J et al. (2017) Oxycodone Ingestion Patterns in Acute Fracture Pain With Digital Pills. Anesth Analg 125:2105-2112|
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