Examining a Digital Health Approach for Advancing Schizophrenia Illness Self-management and Provider Engagement

Examining a Digital Health Approach for Advancing Schizophrenia Illness Self-management and Provider Engagement

Examining a Digital Health Approach for Advancing Schizophrenia Illness Self-management and Provider Engagement

The effective treatment of schizophrenia is very challenging due to a number of factors. These include issues such as poor engagement with treatment plans and care providers, limited contacts with providers due to under-resourced health services, and the challenges inherent to schizophrenia symptoms. The outcomes of these problems include frequent, lengthy, and costly hospital readmissions, low quality of life, high levels of distress, and difficulties engaging in valued community roles. Digital Health technologies are a promising model to help address these problems. They are a low cost and accessible form of support and have not been substantively developed or studied for people with schizophrenia spectrum illnesses. In this study, the feasibility of one such technology that is in development will be tested: App4Independence (A4i). A4i provides customized coping prompts, peer-peer networking, and a portal that facilitates better provider engagement. This research will provide critical information in the development of this new technology to address a key problem in the field - how to enhance care in a resource-limited context where provider-patient contacts are brief, infrequent, and rely on in the moment recall and self-advocacy by patients. These findings will lay the groundwork for a larger program of research and software development that will (i) validate the technology across multiple sites and, (ii) catalyze engagement with healthcare systems and caregiver networks to scale-out access to this promising resource.

Problem Statement: Among schizophrenia-spectrum populations, adherence to treatment is poor, community-based supports are limited, and efforts to foster illness self-management have had limited success. These challenges contribute to frequent, lengthy, and costly hospital readmissions and poor functional outcomes. Digital health strategies, in turn, hold considerable promise in the effort to address these problems. Across healthcare domains, digital health is a rapidly growing area due to its potential reach, accessibility, low cost, and implications for the use of data to customize treatments and identify risk trajectories. Despite this promise and for reasons that are not entirely clear, the development and study of digital health strategies for more severe mental health conditions such as schizophrenia is much less developed than other domains of healthcare. Objective: This feasibility trial will examine a digital health platform designed to enhance illness self-management and treatment engagement for individuals with schizophrenia. Technology: The investigators and collaborators have developed and piloted a digital technology called App4Independence (A4i). This platform was designed to (i) help prevent social isolation through behavioral activation prompts and peer-peer strategy sharing, (ii) enhance coping with schizophrenia symptoms through functions that draw on evidence-based strategies (e.g., texted tips derived from cognitive and behavioral therapies) and provide a novel technology that assists with the identification of auditory hallucinations, (iii) enhance treatment adherence through scheduling, text and reminder functions, (iv) track level of wellness/risk and progress on personal goals through both active (self-ratings) and passive (sleep monitoring proxy) metrics, and (v) facilitate communications with care providers through a provider dashboard summarizing platform-collected data gathered between appointments. Partners: This study builds on a partnership between the Centre for Addiction and Mental Health (research capability, mental health service and associated expertise, access to patient populations) and MEMOTEXT, a health technology company with a track record of success in digital health approaches across multiple health conditions and care contexts. Study Design: This single blind, randomized controlled trial examines the feasibility of A4i. Feasibility metrics include study recruitment and retention, rate of technology use, safety, and utility in clinical interactions. Other outcome metrics include symptomatology, treatment adherence, patient-provider alliance, and quality of life. In this trial, study participants will be randomized to either treatment or control conditions, with pre-post outcomes measured over a 6-month period. Implications: This research will provide critical information for the development of this new technology in the larger effort to address a key problem in the schizophrenia field - how to leverage technology to enhance illness self-management and care engagement in resource-limited service contexts. These findings will lay the groundwork for larger trials assessing the impacts of A4i on hospital readmission and functioning - providing essential evidence for commercialization and expanded access to this tool. This work is at the forefront of international efforts to explore and validate digital health approaches for schizophrenia.

Blocked randomization, stratified by gender, will be employed to ensure balance in sample size between treatment and control groups and gender representation. Stratification by study site (CAMH versus community agency) will also be undertaken to determine feasibility questions that may differ as a function of same. REDCap will be employed and will allocate based on the computer-generated randomization list. Allocation concealment will be achieved since the person making the assignment will have no awareness or control over the randomization schedule.

App4Independence (A4i) Experimental: A4i Intervention App4Independence (A4i) The study intervention is the digital health platform A4i. A4i operates on the individual's own phone with or without data. Specific A4i functionality includes: Addressing social isolation and cognitive challenges through personalized prompts, scheduling of activities, and connections to a range of resources. Fostering illness self-management through evidence-informed content. A peer-peer engagement platform that facilitates strategy/tip sharing between users (anonymous and moderated). Daily wellness and goal attainment check-ins. An ambient sound detector with an oscilloscope-type indicator that assists individuals with auditory hallucinations separate hallucinations from real sounds. Passively collected data on phone use as a proxy for sleep. A provider dashboard. Both control and experimental condition participants will be receiving standard outpatient care (TAU).

Treatment as usual participants will be recieving outpatient mental health care through the standard supports (most typically, case management and psychiatric support) that are available in a large, Canadian, urban centre.

Number of individuals successfully recruited into the trial. Higher values are better with a target of 160.

Number of participants retained in the study through to post-intervention evaluation. Higher values are better. The target is retaining 85% of participants recruited.

Objective A4i use metrics will be collected including information on the combined time and frequency of use for each participant. Higher values are better.

Safety/tolerability will be assessed through information gathered via all study-related interactions with significant safety concerns operationalized as one or more critical incidents occurring in which there is evidence of an association between the incident and App use. Lower values are better.

An Research Assistant will contact treatment arm providers and participants to complete a brief, qualitative, semi-structured interview assessing strengths (generally and in clinical interactions) and limitations of A4i and any risks not otherwise reported or observed during study operations.

General symptomatology will be assessed using the 53-item, 5-point likert scale Brief Symptom Inventory. Range 0-212. Lower values are better.

Medication adherence will be measured using the 4-item Brief Adherence Rating Scale with responses obtained by both providers and participants to assess medication adherence. Range 0-100%. Higher values are better.

Provider-Patient Clinical Alliance will be assessed with Scale to Assess the Therapeutic Relationship. This 12-item measure employing a 5-point likert scale has been used extensively in studies of outpatient care for severe mental illness. This measure supports patient and provider versions. Higher values are better. Range 0-48.

The Heinrichs-Carpenter Quality of Life Scale, has 21 items, is well validated for schizophrenia, and captures sense of purpose, motivation, emotional and social interaction, role functioning, and engagement in regular activities. Higher values are better. Range 0-126.

Schizophrenia-specific symptomatology will be assessed with the Positive and Negative Syndrome Scale. Lower values are better. Range 30-210.

Negative symptoms assessed with the Scale for the Assessment of Negative Symptoms. Lower values are better. Range 0-125.

The 5-item, 6-point likert scale Medical Outcomes Study general adherence scale to capture broader adherence to treatment recommendations (again triangulated with provider responses). Higher values are better. Range 5-26.

The percentage of scheduled appointments attended through EMR audit at CAMH or provider report at non-CAMH sites. Higher values are better.

Inclusion Criteria: Participants will be adults, 18 years of age or older, with a chart diagnosis of a DSM-5 schizophrenia spectrum illness confirmed by a structured diagnostic interview (SCID-5)40. All participants will be engaged in outpatient psychiatric treatment. Proficiency in English. Own and use an Android or iOS smartphone. Exclusion Criteria: Lack of capacity with no identified substitute decision maker. Intellectual disability.

The plan is to share study metrics with participant identifiers removed (e.g., age, gender, ethnicity".