JMIR Mental Health (Nov 2022)

Development of the First Episode Digital Monitoring mHealth Intervention for People With Early Psychosis: Qualitative Interview Study With Clinicians

  • Ana Stefancic,
  • R Tyler Rogers,
  • Sarah Styke,
  • Xiaoyan Xu,
  • Richard Buchsbaum,
  • Ilana Nossel,
  • Leopoldo J Cabassa,
  • T Scott Stroup,
  • David Kimhy

DOI
https://doi.org/10.2196/41482
Journal volume & issue
Vol. 9, no. 11
p. e41482

Abstract

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BackgroundMobile health (mHealth) technologies have been used extensively in psychosis research. In contrast, their integration into real-world clinical care has been limited despite the broad availability of smartphone-based apps targeting mental health care. Most apps developed for treatment of individuals with psychosis have focused primarily on encouraging self-management skills of patients via practicing cognitive behavioral techniques learned during face-to-face clinical sessions (eg, challenging dysfunctional thoughts and relaxation exercises), reminders to engage in health-promoting activities (eg, exercising, sleeping, and socializing), or symptom monitoring. In contrast, few apps have sought to enhance the clinical encounter itself to improve shared decision-making (SDM) and therapeutic relationships with clinicians, which have been linked to positive clinical outcomes. ObjectiveThis qualitative study sought clinicians’ input to develop First Episode Digital Monitoring (FREEDoM), an app-based mHealth intervention. FREEDoM was designed to improve the quality, quantity, and timeliness of clinical and functional data available to clinicians treating patients experiencing first-episode psychosis (FEP) to enhance their therapeutic relationship and increase SDM. MethodsFollowing the app’s initial development, semistructured qualitative interviews were conducted with 11 FEP treatment providers at 3 coordinated specialty care clinics to elicit input on the app’s design, the data report for clinicians, and planned usage procedures. We then generated a summary template and conducted matrix analysis to systematically categorize suggested adaptations to the evidence-based intervention using dimensions of the Framework for Reporting Adaptations and Modifications‐Enhanced (FRAME) and documented the rationale for adopting or rejecting suggestions. ResultsThe clinicians provided 31 suggestions (18 adopted and 13 rejected). Suggestions to add or refine the content were most common (eg, adding questions in the app). Adaptations to context were most often related to plans for implementing the intervention, how the reported data were displayed to clinicians, and with whom the reports were shared. Reasons for suggestions primarily included factors related to health narratives and priorities of the patients (eg, focus on the functional impact of symptoms vs their severity), providers’ clinical judgment (eg, need for clinically relevant information), and organizations’ mission and culture. Reasons for rejecting suggestions included requests for data and procedures beyond the intervention’s scope, concerns regarding dilution of the intervention’s core components, and concerns about increasing patient burden while using the app. ConclusionsFREEDoM focuses on a novel target for the deployment of mHealth technologies in the treatment of FEP patients—the enhancement of SDM and improvement of therapeutic relationships. This study illustrates the use of the FRAME, along with methods and tools for rapid qualitative analysis, to systematically track adaptations to the app as part of its development process. Such adaptations may contribute to enhanced acceptance of the intervention by clinicians and a higher likelihood of integration into clinical care. Trial RegistrationClinicalTrials.gov NCT04248517; https://tinyurl.com/tjuyxvv6