Evidence map›Paper›PMID 38064256›Full record

ArticleJMIR human factors2023

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

Che-Wei Hsu, Daniel Stahl, Elias Mouchlianitis, Emmanuelle Peters, George Vamvakas, Jeroen Keppens, Miles Watson, Nora Schmidt, Pamela Jacobsen, Philip McGuire and 5 more

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 2 countries.

Che-Wei HsuDepartment of Psychological Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.ORCID 0000-0002-3297-3961
Daniel StahlDepartment of Biostatistics and Health Informatics, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0001-7987-6619
Elias MouchlianitisUniversity of East London, London, United Kingdom.ORCID 0000-0003-0329-5492
Emmanuelle PetersDepartment of Psychology, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0003-3327-9223
George VamvakasDepartment of Biostatistics and Health Informatics, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0002-2817-3320
Jeroen KeppensDepartment of Informatics, King's College London, London, United Kingdom.ORCID 0000-0003-3858-7858
Miles WatsonDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0009-0000-3887-7455
Nora SchmidtDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0003-1506-0818
Pamela JacobsenUniversity of Bath, Bath, United Kingdom.ORCID 0000-0001-8847-7775
Philip McGuireDepartment of Psychiatry, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-4381-0532
Sukhi ShergillDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0003-4928-9100
Thomas KabirDepartment of Psychiatry, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-8908-0964
Tia HiraniDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0009-0000-6748-2188
Ziyang YangDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0009-0000-9198-3564
Jenny YiendDepartment of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.ORCID 0000-0002-1967-6292
King's College London · GBUniversity of Oxford · GBNational Health Service · GBUniversity of Bath · GBUniversity of East London · GB

Funding

Medical Research Council MR/V027484/1
6 · The paper itself

Abstract

backgroundParanoia 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").

objectiveThis 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.

methodsWe 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.

resultsAll 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.

conclusionsMaterial 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.

Indexed as

Mobile ApplicationsTelemedicineHumansParanoid DisordersUser-Centered DesignUser-Computer Interfacecognitive bias modificationcontent specificitydelusionsdigital therapeuticmegalomaniamental healthmhealthmobile appmonomaniaobsessionparanoiaparanoidpersecutionpersecution complexpsychosispsychoticuseruser-centered developmentuser-friendly app

Identifiers

PMID38064256
PMCPMC10746980
OpenAlexW4386985882

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.