Using Mobile Technology to Enhance Early Psychosis Treatment Delivery
Condition: Psychosis; Clinical High Risk for Psychosis
MeSH terms: Psychotic Disorders; Mental Disorders
Study type: Interventional

Summary: 
      This project tests the feasibility of implementing a smartphone application - Ginger.io - in
      the UC Davis Early Psychosis Program, and investigates whether mobile health technology can
      improve treatment delivery and outcomes in individuals with early psychosis. Ginger.io is a
      smartphone application that utilizes methods of passive data collection (i.e. data gathered
      without active interaction/contribution from the user) to gather communication, movement, and
      interaction data from smartphone devices to model individuals' social, physical, and mental
      health. These models are used to infer health-related outcomes and could inform treatment. By
      implementing the Ginger.io application in the UC Davis Early Psychosis Program with an
      integrated clinical and research infrastructure, the investigators will be able to quickly
      determine its feasibility for use in early psychosis populations, while simultaneously
      developing its ability to systematically capture aspects of relapse and recovery that are
      unique to this patient population.

      Objectives: This project has three principle objectives related to early psychosis care: 1)
      improve treatment delivery, 2) improve patient outcomes, and 3) lower treatment costs. The
      project will target individuals in the early stages of psychotic illness, including
      individuals at high risk for developing a psychotic illness (termed "clinical high risk" or
      CHR) and individuals within three years of their first psychotic episode (termed "first
      episode psychosis" or FEP). The early stages of psychotic illness represent a critical period
      for intervention; early identification of clinical deterioration and subsequent targeted
      intervention is crucial for rapid remission of symptoms and reduced relapse rates. However,
      without the information necessary to identify patients in need of such intervention,
      providers are limited in their ability to respond rapidly. Within the UCD Early Psychosis
      Program, a mobile health application such as Ginger.io has the potential to equip the
      providers and caregivers with valuable insight into a patient's status in real-time without
      the burden of increased appointments and intrusive monitoring, allowing the identification of
      early psychosis patients most in need of outreach, and routing of treatment resources to the
      right patients at the right time.
    

Detailed description: 
      The project comprises two phases. In both phases, patients will use the Ginger.io app on
      their mobile device to complete daily surveys assessing mood and social interactions, and
      weekly surveys assessing symptoms. Patients will also complete monthly gold-standard clinical
      interviews at the UC Davis Early Psychosis Program. Once enrolled, the investigators will ask
      patients to participate for the duration of the study, a total of 14 months across Phase I
      and II.

      Phase I involves the collection of pilot data to assess feasibility and conduct exploratory
      analyses. Participants will include individuals in the earliest stages of psychosis (CHR and
      FEP). The investigators will recruit 60 participants to allow for 15% dropout, aiming to
      obtain complete data on 50 participants. Given the emphasis on feasibility and acceptability
      in Phase I, research staff will monitor patient Dashboards daily and provide clinicians with
      weekly summaries for each patient. Clinicians and patients will provide ratings on
      satisfaction and effect of Ginger.io on treatment at the end of Phase I.

      Specific aims for Phase I are as follows:

      Specific Aim 1: Determine the feasibility and acceptability of Ginger.io in an early
      psychosis population.

      Feasibility will be measured by utilization of the application (i.e. number of enrolled and
      active participants versus total patient population invited). Acceptability will be measured
      with satisfaction survey ratings of Ginger.io by patients and clinicians. Analysis will
      include summary statistics reporting utilization rates and satisfaction ratings. The
      investigators hypothesize high utilization of Ginger.io and low dropout, as well as high
      satisfaction and endorsement of continued use of Ginger.io.

      Specific Aim 2: Identify passive behavior data associated with gold-standard measures of
      clinical symptoms and social functioning.

      The investigators will examine associations between passive and active data collected via
      Ginger.io. The investigators will then validate both the active and passive behavior data by
      examining associations with symptom and social functioning ratings obtained via gold-standard
      clinical interviews conducted at monthly research evaluations. The investigators hypothesize
      patients' passive interaction data will positively associate with active survey data of
      symptoms and social interactions (e.g. increase reports of mood will relate to more
      texts/calls), and that both active and passive data regarding symptoms and social behavior
      will relate to gold-standard clinical measures of symptoms and social functioning.

      Specific Aim 3: Identify Ginger.io data related to key patient outcomes to inform calibration
      of patient status alerts.

      Exploratory analyses using regression models and repeated measure GLMs will examine whether
      the passive and active data from Ginger.io statistically predict key patient outcomes,
      including psychotic symptom flares, increased clinic contact, psychiatric ER visits or
      hospitalizations, and progression from a high risk state to first episode psychosis. The
      investigators hypothesize reductions in phone calls/text messages and/or increases in
      self-reported ratings of basic symptoms will predict psychotic symptom flares, increased
      clinic utilization, psychiatric ER visits and hospitalizations. This analysis will be used to
      calibrate patient status alerts for Phase II that will notify clinicians which patients are
      at risk of symptom exacerbation and relapse.

      Specific Aim 4: Evaluate effect of Ginger.io on key treatment variables. Key variables of
      interest are medication adherence, therapeutic alliance, and insight. All three variables
      will be measured using self-report questionnaires (see Procedures Involved) administered to
      patients at the beginning and end of the project, and as part of the monthly clinical
      interviews, enabling the evaluation of change over time. The investigators hypothesize that,
      following three months of Ginger.io use, patients will report improved medication adherence,
      therapeutic alliance, and insight into their illness.

      Phase II will extend the findings of Phase I through the implementation of Ginger.io in the
      UC Davis Early Psychosis Programs (EDAPT and SacEDAPT) to allow clinicians to directly
      interact with the Dashboard and integrate its information directly into patient care.
      Patients will continue to complete daily and weekly surveys via Ginger.io, and monthly
      clinical assessments with research staff. Additionally, clinicians will monitor patient
      Dashboards on a daily basis and will respond to patient status alerts as they arise (see Aim
      2 below). Phase I participants will be asked to remain in the study through Phase II,
      yielding a more comprehensive longitudinal dataset. Phase II will involve a total of 120
      participants (combined Phase I and newly recruited participants) to account for 15% dropout,
      aiming to obtain data for at least 100 participants.

      Phase II has four specific aims.

      Specific Aim 1: Continue to validate predictive value of Ginger.io data related to key
      patient outcomes.

      This is a direct extension of Aim 3 in Phase I and will be addressed through continued linear
      modeling of passive and active data from Ginger.io to identify and test statistical
      predictors of key patient outcomes. This will facilitate continued calibration of patient
      status alerts used in the Dashboard to notify clinicians when patients are at risk of
      clinical deterioration.

      Specific Aim 2: Evaluate effect of patient status alerts on treatment delivery. Key variables
      of interest include clinician-rated utility of the patient status alerts, clinician choice of
      treatment delivery following an alert, and the action response time following notification of
      an alert. In response to each alert, clinicians will indicate the type of clinical
      intervention they pursued (e.g. "called patient to check in", "scheduled appointment with
      psychiatrist"). All treatment will be clinician-driven and provided in a naturalistic manner,
      and data will be collected on the types of treatments chosen for a given alert. Clinicians
      will also rate the utility (e.g. not useful/useful) of the alert based on information
      gathered during follow-up. Action response time will be recorded via Dashboard interaction.
      Preliminary analyses will be exploratory and will inform continued improvements to the
      Dashboard and calibration of patient status alerts. Summary statistics regarding clinician
      responses, average response time, and utility ratings will be included. The investigators
      hypothesize that clinicians will rate patient status alerts as useful and informative to
      their treatment planning and intervention.

      Specific Aim 3: Analysis of the impact of Ginger.io on cost of care. Key variables of
      interest include cost of outpatient care, and psychiatric ER visits and hospitalizations. To
      evaluate the impact of Ginger.io, the historical average monthly and annual cost of care per
      patient will be compared to the average monthly and annual cost of care during and following
      completion of the project. The investigators hypothesize that implementation of Ginger.io
      will reduce the number and duration of psychiatric ER visits and hospitalizations, thereby
      reducing costs.

      Specific Aim 4: Continued evaluation of feasibility and acceptability of Ginger.io in an
      early psychosis population.

      The investigators will continue to evaluate feasibility and acceptability of Ginger.io in
      both patients and clinicians using satisfaction surveys. The investigators hypothesize that
      patients will continue to endorse high satisfaction rates and continued use of Ginger.io.
      Additionally, the investigators hypothesize that clinicians will report high satisfaction
      rates with the Dashboard and endorse its continued use in clinical care.
    

Intervention name(s): Mobile health application - Ginger.io
Intervention type(s): Other
Intervention description(s): the Ginger.io is a smartphone application allowing for daily surveys assessing mood and social interactions, and weekly surveys assessing symptoms and psychosocial functioning. Collects passive movement and interaction data
Allocation: Non-Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Health Services Research
Keywords: early psychosis; clinical high risk; mobile health