This project will use a smartphone technology to improve medication prescribing for individuals with FEP. We will collect real-time symptom and functioning data via smartphones to provide prescribers and other clinical team members with clinically relevant and time-sensitive information that will inform and promote shared decision making (SDM) and personalized interventions. The result will be a time-sensitive, data-driven, collaborative process to optimize medication regimens in order to maximize benefits, minimize harms, and promote adherence.

Comprehensive early treatment of individuals experiencing schizophrenia has the potential to alter the course of illness and improve long-term outcomes. Psychotropic medications are a critical component of early treatment strategies. First-episode psychosis (FEP) is a critical time to optimize prescribing but evidence suggests that prescribing for this population is suboptimal.

A contributing factor to these difficulties is thought to be the lack of accurate information about the effects of medications on symptoms, their side effects, as well as their behavioral, cognitive, and emotional correlates. At medication management appointments, prescribers typically rely on patients' recollection of how they were doing over periods of weeks. Such retrospective assessments are problematic as they are vulnerable to the influence of memory difficulties, cognitive biases including recency effects and frequency illusions, and reframing. Recent advances in smartphone technologies (mobile Health; mHealth) may help to overcome many of the limitations of retrospective assessments.

This pilot study will be a collaboration with OnTrackNY, an innovative coordinated specialty care (CSC) program for individuals aged 16-30 who are experiencing FEP. OnTrackNY originated as part of the NIMH Recovery After an Initial Schizophrenia Episode (RAISE) Implementation and Evaluatoin Study. The initial phase of this project will use input from stakeholders including patients, front-line providers, clinical leaders, and members of the research team to adapt and refine the mHealth intervention to improve feasibility and clinical utility. A pilot study at 3 OnTrackNY sites will then examine its feasibility and effectiveness by comparing the management and outcomes of 60 patients randomly assigned to the mHealth application or usual care.

Inclusion Criteria:

• Male or female OnTrackNY participants, ages 16 to 30, of any race/ethnicity
• Able and willing to give informed consent and participate in the intervention
• Participating in OnTrackNY for less than 1 year because this group may be more in need of medication adjustments and will be less likely to graduate from the program before 6 months of participation.

Exclusion Criteria:

• Suicidal at baseline with C-SSRS score 4 or 5.
• PANSS baseline score of 5 (moderately severe) or greater on the Conceptual Disorganization item (P2)

Raw data will be made available for research to investigators working under a Federal Wide Assurance who meet security measures and data use agreement criteria associated with public repositories including the National Database for Clinical Trials related to Mental Illness (NDCT). Data will include baseline demographic data, and baseline and post raw data derived from functioning and symptom measures.

A list of all data expected to be collected in the project will be submitted within 6 months of award. Subsequently, descriptive and raw data will be submitted on a semi-annual basis. Unpublished de-identified data will be submitted prior to study completion and will be shared within one year after project completion, or when the data are published, whichever is earlier.

Data in NIH repositories may be accessed through the NIH Data Access Committee which reviews data access and submission requests.