Mark Savill

Knowledge derived from personal experience of mental health service use, by way of individuals with lived and living experience, is increasingly incorporated into mental health programs. Yet organizational readiness to support meaningful integration often lags behind intent. This paper offers a case analysis of the first 2 years of a Lived Experience Integration (LEI) Team embedded within a statewide early psychosis training and technical assistance network. Using Organizational Readiness for Change as a conceptual framework, this paper describes how leadership from people with lived experience contributed to training development, consultation, advisory structures, and workforce design, while navigating evolving infrastructure and the relational and interpretive demands of lived experience roles. Practical lessons are highlighted for building readiness to support durable lived experience integration in complex service systems. Lived Experience or Public Contribution: This manuscript describes work that was initiated and led with substantial involvement from individuals with lived experience of psychosis‐spectrum conditions and mental health service use. Lived experience‐identified contributors built the LEI Team under discussion, participated in consultation and training activities, advised on organizational tensions described in this case analysis, and were fully responsible for the conceptualization and writing of this manuscript.

Time between the onset of psychosis and the start of treatment significantly influences outcomes. Rapid access to care is essential, yet barriers such as stigma, difficulties with navigating the mental health system, and financial constraints prolong this process. This mixed-methods study aimed to assess how these barriers affect participation in early psychosis services. A directed content analysis of telephone log data was conducted from intake assessments at an early psychosis clinic. Stepwise logistic regression and analyses of variance were used to evaluate the impact of barriers on assessment completion and time from referral to assessment. Of 1,048 individuals screened for early psychosis services, 201 completed a telephone assessment. Individuals who dropped out had a higher proportion of barriers overall than did those who completed the assessment (p<0.01). Greater than 50% of interactions included at least one barrier, with logistical issues being the most common. Increased barriers were correlated with longer assessments and lower completion rates. Adults and Hispanic participants reported more barriers, compared with adolescents and non-Hispanic individuals, respectively. Significant contributors to nonengagement included unknown gender, public insurance, and various barriers. Identifiable barriers to intake assessment were frequently reported by clients and were associated with higher intake noncompletion and a longer assessment process. Efforts to address logistical barriers may represent an essential step in improving the linkage process and reducing the duration of untreated psychosis.

Background: The Early Psychosis Intervention Network of California project, a learning health care network of California early psychosis intervention (EPI) programs, prioritized incorporation of community partner feedback while designing its eHealth app, Beehive. Though eHealth apps can support learning health care network data collection aims, low user acceptance or adoption can pose barriers to successful implementation. Adopting user-centered design (UCD) approaches, such as incorporation of user feedback, prototyping, iterative design, and continuous evaluation, can mitigate these potential barriers. Objective: We aimed to use UCD during development of a data collection and data visualization web-based and tablet app, Beehive, to promote engagement with Beehive as part of standard EPI care across a diverse user-base. Methods: Our UCD approach included incorporation of user feedback, prototyping, iterative design, and continuous evaluation. This started with user journey mapping to create storyboards, which were then presented in UCD workshops with service users, their support persons, and EPI providers. We incorporated feedback from these workshops into the alpha version of Beehive, which was also presented in a UCD workshop. Feedback was again incorporated into the beta version of Beehive. We provided Beehive training to 4 EPI programs who then piloted Beehive’s beta version. During piloting, service users, their support persons, and EPI program providers completed Beehive surveys at enrollment and every 6 months after treatment initiation. To examine preliminary user acceptance and adoption during the piloting phase, we assessed rates of participant enrollment and survey completion, with a particular focus on completion of a prioritized survey: the Modified Colorado Symptom Index. Results: UCD workshop feedback resulted in the creation of new workflows and interface changes in Beehive to improve the user experience. During piloting, 48 service users, 42 support persons, and 72 EPI program providers enrolled in Beehive. Data were available for 88% (n=42) of service users, including self-reported data for 79% (n=38), collateral-reported data for 42% (n=20), and clinician-entered data for 17% (n=8). The Modified Colorado Symptom Index was completed by 54% (n=26) of service users (total score: mean 24.16, SD 16.81). In addition, 35 service users had a support person who could complete the Modified Colorado Symptom Index, and 56% (n=19) of support persons completed it (mean 26.71, SD 14.43). Conclusions: Implementing UCD principles while developing the Beehive app resulted in early workflow changes and produced an app that was acceptable and feasible for collection of self-reported clinical outcomes data from service users. Additional support is needed to increase collateral-reported and clinician-entered data.

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PsychiatryOnline.org is the platform for all American Psychiatric Association Publishing journals, DSM, and bestselling textbooks, as well as APA Practice Guidelines, and continuing medical education.

Despite the substantial capacity of qualitative and mixed methods research to advance healthcare and interventions knowledge, most large-scale health intervention trials exclusively use quantitative methods. The authors argue that qualitative research can optimize investments in these studies. As researchers within the Early Psychosis Intervention Network (EPINET), the authors highlight examples of how qualitative research has enhanced this national initiative, organizing them with a Learning Health System (LHS) framework to demonstrate the ways qualitative research can increase value at each phase of a health trial. They emphasize the critical need for integrating qualitative research from the beginning of health trials, ensuring its influence in decision-making, creating infrastructure to support it, and promoting meaningful representation within research teams. By illustrating the advantages of qualitative research in EPINET, they advocate for sustained commitment to qualitative research in health trials to maximize value in client and provider experience, cost, and population health.

BACKGROUND The Early Psychosis Intervention Network of California project, a learning health care network of California early psychosis intervention (EPI) programs, prioritized incorporation of community partner feedback while designing its eHealth app, Beehive. Though eHealth apps can support learning health care network data collection aims, low user acceptance or adoption can pose barriers to successful implementation. Adopting user-centered design (UCD) approaches, such as incorporation of user feedback, prototyping, iterative design, and continuous evaluation, can mitigate these potential barriers. OBJECTIVE We aimed to use UCD during development of a data collection and data visualization web-based and tablet app, Beehive, to promote engagement with Beehive as part of standard EPI care across a diverse user-base. METHODS Our UCD approach included incorporation of user feedback, prototyping, iterative design, and continuous evaluation. This started with user journey mapping to create storyboards, which were then presented in UCD workshops with service users, their support persons, and EPI providers. We incorporated feedback from these workshops into the alpha version of Beehive, which was also presented in a UCD workshop. Feedback was again incorporated into the beta version of Beehive. We provided Beehive training to 4 EPI programs who then piloted Beehive’s beta version. During piloting, service users, their support persons, and EPI program providers completed Beehive surveys at enrollment and every 6 months after treatment initiation. To examine preliminary user acceptance and adoption during the piloting phase, we assessed rates of participant enrollment and survey completion, with a particular focus on completion of a prioritized survey: the Modified Colorado Symptom Index. RESULTS UCD workshop feedback resulted in the creation of new workflows and interface changes in Beehive to improve the user experience. During piloting, 48 service users, 42 support persons, and 72 EPI program providers enrolled in Beehive. Data were available for 88% (n=42) of service users, including self-reported data for 79% (n=38), collateral-reported data for 42% (n=20), and clinician-entered data for 17% (n=8). The Modified Colorado Symptom Index was completed by 54% (n=26) of service users (total score: mean 24.16, SD 16.81). In addition, 35 service users had a support person who could complete the Modified Colorado Symptom Index, and 56% (n=19) of support persons completed it (mean 26.71, SD 14.43). CONCLUSIONS Implementing UCD principles while developing the Beehive app resulted in early workflow changes and produced an app that was acceptable and feasible for collection of self-reported clinical outcomes data from service users. Additional support is needed to increase collateral-reported and clinician-entered data.

Background: Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust. Objective: First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities. Methods: We conducted an exploratory, qualitative, and focus group–based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities. Results: In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1% (421/478) of clients who reviewed the video agreeing to share data. Conclusions: Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners’ priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates.

BACKGROUND Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust. OBJECTIVE First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities. METHODS We conducted an exploratory, qualitative, and focus group–based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities. RESULTS In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1% (421/478) of clients who reviewed the video agreeing to share data. CONCLUSIONS Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners’ priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates.

Aim: Duration of untreated psychosis, or the time between onset of psychosis symptoms and accurate diagnosis and treatment, is a significant predictor of both initial treatment response and long‐term outcomes. As such, efforts to improve rapid identification are key. Because early signs of psychosis commonly emerge in adolescence, schools have the potential to play an important role in the identification of psychosis‐spectrum disorders.Methods: To illustrate the potential role of schools in this effort, the current paper describes implementation of a psychosis screening tool as part of a larger study focused on reducing the duration of untreated psychosis in Sacramento, CA.Results: Clinical considerations related to screening for psychosis in schools, including ethical concerns, logistics, screening population and stigma are addressed. Implementation strategies to address these concerns are suggested.Conclusions: Early psychosis screening in the school system could improve early identification, reduce stigma and may represent an important further step towards an integrative system of mental health.