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      User-Centered Development of STOP (Successful Treatment for Paranoia): Material Development and Usability Testing for a Digital Therapeutic for Paranoia

      research-article
      , PhD 1 , 2 , , PhD 3 , , PhD 4 , , PhD 5 , 6 , , MSc 3 , , PhD 7 , , MSc 2 , , MSc 2 , , PhD 8 , , MD 9 , , MD 2 , , PhD 9 , , MSc 2 , , MSc 2 , , PhD 2 ,
      (Reviewer), (Reviewer)
      JMIR Human Factors
      JMIR Publications
      cognitive bias modification, paranoia, content specificity, mental health, mobile app, mhealth, digital therapeutic, user-centered development, user, user-friendly app, paranoid, persecution, persecution complex, delusions, obsession, megalomania, monomania, psychosis, psychotic

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          Abstract

          Background

          Paranoia is a highly debilitating mental health condition. One novel intervention for paranoia is cognitive bias modification for paranoia (CBM-pa). CBM-pa comes from a class of interventions that focus on manipulating interpretation bias. Here, we aimed to develop and evaluate new therapy content for CBM-pa for later use in a self-administered digital therapeutic for paranoia called STOP (“Successful Treatment of Paranoia”).

          Objective

          This study aimed to (1) take a user-centered approach with input from living experts, clinicians, and academics to create and evaluate paranoia-relevant item content to be used in STOP and (2) engage with living experts and the design team from a digital health care solutions company to cocreate and pilot-test the STOP mobile app prototype.

          Methods

          We invited 18 people with living or lived experiences of paranoia to create text exemplars of personal, everyday emotionally ambiguous scenarios that could provoke paranoid thoughts. Researchers then adapted 240 suitable exemplars into corresponding intervention items in the format commonly used for CBM training and created 240 control items for the purpose of testing STOP. Each item included newly developed, visually enriching graphics content to increase the engagement and realism of the basic text scenarios. All items were then evaluated for their paranoia severity and readability by living experts (n=8) and clinicians (n=7) and for their item length by the research team. Items were evenly distributed into six 40-item sessions based on these evaluations. Finalized items were presented in the STOP mobile app, which was co-designed with a digital health care solutions company, living or lived experts, and the academic team; user acceptance was evaluated across 2 pilot tests involving living or lived experts.

          Results

          All materials reached predefined acceptable thresholds on all rating criteria: paranoia severity (intervention items: ≥1; control items: ≤1, readability: ≥3, and length of the scenarios), and there was no systematic difference between the intervention and control group materials overall or between individual sessions within each group. For item graphics, we also found no systematic differences in users’ ratings of complexity ( P=.68), attractiveness ( P=.15), and interest ( P=.14) between intervention and control group materials. User acceptance testing of the mobile app found that it is easy to use and navigate, interactive, and helpful.

          Conclusions

          Material development for any new digital therapeutic requires an iterative and rigorous process of testing involving multiple contributing groups. Appropriate user-centered development can create user-friendly mobile health apps, which may improve face validity and have a greater chance of being engaging and acceptable to the target end users.

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          Most cited references50

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          Cognitive approaches to emotion and emotional disorders.

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            Efficacy of cognitive bias modification interventions in anxiety and depression: meta-analysis.

            Cognitive bias modification (CBM) interventions are strongly advocated in research and clinical practice.
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              Psychological interventions for psychosis: a meta-analysis of comparative outcome studies.

              Meta-analyses have demonstrated the efficacy of various interventions for psychosis, and a small number of studies have compared such interventions. The aim of this study was to provide further insight into the relative efficacy of psychological interventions for psychosis. Forty-eight outcome trials comparing psychological interventions for psychosis were identified. The comparisons included 3,295 participants. Categorization of interventions resulted in six interventions being compared against other interventions pooled. Hedges' g was calculated for all comparisons. Risk of bias was assessed using four items of the Cochrane risk of bias tool, and sensitivity analyses were conducted. Researcher allegiance was assessed, and sensitivity analyses were conducted for robust significant findings. Cognitive-behavioral therapy (CBT) was significantly more efficacious than other interventions pooled in reducing positive symptoms (g=0.16). This finding was robust in all sensitivity analyses for risk of bias but lost significance in sensitivity analyses for researcher allegiance, which suffered from low power. Social skills training was significantly more efficacious in reducing negative symptoms (g=0.27). This finding was robust in sensitivity analyses for risk of bias and researcher allegiance. Significant findings for CBT, social skills training, and cognitive remediation for overall symptoms were not robust after sensitivity analyses. CBT was significantly more efficacious when compared directly with befriending for overall symptoms (g=0.42) and supportive counseling for positive symptoms (g=0.23). There are small but reliable differences in efficacy between psychological interventions for psychosis, and they occur in a pattern consistent with the specific factors of particular interventions.
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                Author and article information

                Contributors
                Journal
                JMIR Hum Factors
                JMIR Hum Factors
                JMIR Human Factors
                JMIR Human Factors
                JMIR Publications (Toronto, Canada )
                2292-9495
                2023
                8 December 2023
                : 10
                : e45453
                Affiliations
                [1 ] Department of Psychological Medicine Dunedin School of Medicine University of Otago Dunedin New Zealand
                [2 ] Department of Psychosis Studies King's College London Institute of Psychiatry, Psychology & Neuroscience London United Kingdom
                [3 ] Department of Biostatistics and Health Informatics King's College London, Institute of Psychiatry, Psychology & Neuroscience London United Kingdom
                [4 ] University of East London London United Kingdom
                [5 ] Department of Psychology King's College London Institute of Psychiatry, Psychology & Neuroscience London United Kingdom
                [6 ] South London and Maudsley National Health Service Foundation Trust London United Kingdom
                [7 ] Department of Informatics King's College London London United Kingdom
                [8 ] University of Bath Bath United Kingdom
                [9 ] Department of Psychiatry University of Oxford Oxford United Kingdom
                Author notes
                Corresponding Author: Jenny Yiend jenny.yiend@ 123456kcl.ac.uk
                Author information
                https://orcid.org/0000-0002-3297-3961
                https://orcid.org/0000-0001-7987-6619
                https://orcid.org/0000-0003-0329-5492
                https://orcid.org/0000-0003-3327-9223
                https://orcid.org/0000-0002-2817-3320
                https://orcid.org/0000-0003-3858-7858
                https://orcid.org/0009-0000-3887-7455
                https://orcid.org/0000-0003-1506-0818
                https://orcid.org/0000-0001-8847-7775
                https://orcid.org/0000-0003-4381-0532
                https://orcid.org/0000-0003-4928-9100
                https://orcid.org/0000-0001-8908-0964
                https://orcid.org/0009-0000-6748-2188
                https://orcid.org/0009-0000-9198-3564
                https://orcid.org/0000-0002-1967-6292
                Article
                v10i1e45453
                10.2196/45453
                10746980
                38064256
                343d31b0-4b7d-436e-9b00-84aa04860fae
                ©Che-Wei Hsu, Daniel Stahl, Elias Mouchlianitis, Emmanuelle Peters, George Vamvakas, Jeroen Keppens, Miles Watson, Nora Schmidt, Pamela Jacobsen, Philip McGuire, Sukhi Shergill, Thomas Kabir, Tia Hirani, Ziyang Yang, Jenny Yiend. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 08.12.2023.

                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 Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included.

                History
                : 1 January 2023
                : 1 May 2023
                : 13 June 2023
                : 23 September 2023
                Categories
                Original Paper
                Original Paper

                cognitive bias modification,paranoia,content specificity,mental health,mobile app,mhealth,digital therapeutic,user-centered development,user,user-friendly app,paranoid,persecution,persecution complex,delusions,obsession,megalomania,monomania,psychosis,psychotic

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