19
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Submit your digital health research with an established publisher
      - celebrating 25 years of open access

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Mobile 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.

          Objective

          This 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.

          Methods

          Following 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.

          Results

          The 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.

          Conclusions

          FREEDoM 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 Registration

          ClinicalTrials.gov NCT04248517; https://tinyurl.com/tjuyxvv6

          Related collections

          Most cited references54

          • Record: found
          • Abstract: found
          • Article: not found

          Outcomes for Implementation Research: Conceptual Distinctions, Measurement Challenges, and Research Agenda

          An unresolved issue in the field of implementation research is how to conceptualize and evaluate successful implementation. This paper advances the concept of “implementation outcomes” distinct from service system and clinical treatment outcomes. This paper proposes a heuristic, working “taxonomy” of eight conceptually distinct implementation outcomes—acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability—along with their nominal definitions. We propose a two-pronged agenda for research on implementation outcomes. Conceptualizing and measuring implementation outcomes will advance understanding of implementation processes, enhance efficiency in implementation research, and pave the way for studies of the comparative effectiveness of implementation strategies.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The FRAME: an expanded framework for reporting adaptations and modifications to evidence-based interventions

            Background This paper describes the process and results of a refinement of a framework to characterize modifications to interventions. The original version did not fully capture several aspects of modification and adaptation that may be important to document and report. Additionally, the earlier framework did not include a way to differentiate cultural adaptation from adaptations made for other reasons. Reporting additional elements will allow for a more precise understanding of modifications, the process of modifying or adapting, and the relationship between different forms of modification and subsequent health and implementation outcomes. Discussion We employed a multifaceted approach to develop the updated FRAME involving coding documents identified through a literature review, rapid coding of qualitative interviews, and a refinement process informed by multiple stakeholders. The updated FRAME expands upon Stirman et al.’s original framework by adding components of modification to report: (1) when and how in the implementation process the modification was made, (2) whether the modification was planned/proactive (i.e., an adaptation) or unplanned/reactive, (3) who determined that the modification should be made, (4) what is modified, (5) at what level of delivery the modification is made, (6) type or nature of context or content-level modifications, (7) the extent to which the modification is fidelity-consistent, and (8) the reasons for the modification, including (a) the intent or goal of the modification (e.g., to reduce costs) and (b) contextual factors that influenced the decision. Methods of using the framework to assess modifications are outlined, along with their strengths and weaknesses, and considerations for research to validate these measurement strategies. Conclusion The updated FRAME includes consideration of when and how modifications occurred, whether it was planned or unplanned, relationship to fidelity, and reasons and goals for modification. This tool that can be used to support research on the timing, nature, goals and reasons for, and impact of modifications to evidence-based interventions.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Comparison of rapid vs in-depth qualitative analytic methods from a process evaluation of academic detailing in the Veterans Health Administration

              Background It is challenging to conduct and quickly disseminate findings from in-depth qualitative analyses, which can impede timely implementation of interventions because of its time-consuming methods. To better understand tradeoffs between the need for actionable results and scientific rigor, we present our method for conducting a framework-guided rapid analysis (RA) and a comparison of these findings to an in-depth analysis of interview transcripts. Methods Set within the context of an evaluation of a successful academic detailing (AD) program for opioid prescribing in the Veterans Health Administration, we developed interview guides informed by the Consolidated Framework for Implementation Research (CFIR) and interviewed 10 academic detailers (clinical pharmacists) and 20 primary care providers to elicit detail about successful features of the program. For the RA, verbatim transcripts were summarized using a structured template (based on CFIR); summaries were subsequently consolidated into matrices by participant type to identify aspects of the program that worked well and ways to facilitate implementation elsewhere. For comparison purposes, we later conducted an in-depth analysis of the transcripts. We described our RA approach and qualitatively compared the RA and deductive in-depth analysis with respect to consistency of themes and resource intensity. Results Integrating the CFIR throughout the RA and in-depth analysis was helpful for providing structure and consistency across both analyses. Findings from the two analyses were consistent. The most frequently coded constructs from the in-depth analysis aligned well with themes from the RA, and the latter methods were sufficient and appropriate for addressing the primary evaluation goals. Our approach to RA was less resource-intensive than the in-depth analysis, allowing for timely dissemination of findings to our operations partner that could be integrated into ongoing implementation. Conclusions In-depth analyses can be resource-intensive. If consistent with project needs (e.g., to quickly produce information to inform ongoing implementation or to comply with a policy mandate), it is reasonable to consider using RA, especially when faced with resource constraints. Our RA provided valid findings in a short timeframe, enabling identification of actionable suggestions for our operations partner. Electronic supplementary material The online version of this article (10.1186/s13012-019-0853-y) contains supplementary material, which is available to authorized users.
                Bookmark

                Author and article information

                Contributors
                Journal
                JMIR Ment Health
                JMIR Ment Health
                JMH
                JMIR Mental Health
                JMIR Publications (Toronto, Canada )
                2368-7959
                November 2022
                4 November 2022
                : 9
                : 11
                : e41482
                Affiliations
                [1 ] Department of Psychiatry Vagelos College of Physicians and Surgeons Columbia University New York, NY United States
                [2 ] Division of Behavioral Health Services and Policy Research New York State Psychiatric Institute New York, NY United States
                [3 ] Department of Biostatistics Mailman School of Public Health Columbia University New York, NY United States
                [4 ] Brown School of Social Work Washington University in St Louis St Louis, MO United States
                [5 ] Department of Psychiatry Icahn School of Medicine New York, NY United States
                [6 ] New York Mental Illness Research Education and Clinical Center The James J Peters Veteran's Affairs Medical Center Bronx, NY United States
                Author notes
                Corresponding Author: David Kimhy david.kimhy@ 123456mssm.edu
                Author information
                https://orcid.org/0000-0002-1573-1565
                https://orcid.org/0000-0001-5976-2921
                https://orcid.org/0000-0002-3737-7640
                https://orcid.org/0000-0002-6963-4189
                https://orcid.org/0000-0001-7844-2114
                https://orcid.org/0000-0002-6797-0103
                https://orcid.org/0000-0002-1872-4141
                https://orcid.org/0000-0002-3123-0672
                https://orcid.org/0000-0001-7735-9378
                Article
                v9i11e41482
                10.2196/41482
                9675009
                36331539
                8be20937-3de6-4d70-97f2-07a664dcc36f
                ©Ana Stefancic, R Tyler Rogers, Sarah Styke, Xiaoyan Xu, Richard Buchsbaum, Ilana Nossel, Leopoldo J Cabassa, T Scott Stroup, David Kimhy. Originally published in JMIR Mental Health (https://mental.jmir.org), 04.11.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.

                History
                : 25 August 2022
                : 31 August 2022
                : 16 September 2022
                : 19 September 2022
                Categories
                Original Paper
                Original Paper

                first-episode psychosis,early psychosis,coordinated specialty care,mental health treatment,shared decision-making,mobile health,smartphone apps,qualitative,digital psychiatry,mobile phone

                Comments

                Comment on this article