Evidence map›Paper›PMID 40773747›Full record

ArticleJMIR human factors2025

A Digital Mental Health Intervention for Paranoia (the STOP App): Qualitative Study on User Acceptability.

Laura Eid, Alexandra Kenny, Rayan Taher, Pamela Jacobsen, Che Wei Hsu, Jenny Yiend

Abstract read
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Laura EidDepartment of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom.ORCID 0009-0006-3252-9330
Alexandra KennyMcPin Foundation, London, United Kingdom.ORCID 0000-0002-0162-9009
Rayan TaherDepartment of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom.ORCID 0000-0001-8592-527X
Pamela JacobsenDepartment of Psychology, University of Bath, Bath, United Kingdom.ORCID 0000-0001-8847-7775
Che Wei HsuSocial Services (Counselling Specialty), College of Community Development and Personal Wellbeing, Otago Polytechnic, Dunedin, New Zealand.ORCID 0000-0002-3297-3961
Jenny YiendDepartment of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, United Kingdom.ORCID 0000-0002-1967-6292

Funding

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

Abstract

backgroundCognitive bias modification for interpretation (CBM-I) is a technique to modify interpretation and is used to reduce unhelpful negative biases. CBM-I has been extensively studied in anxiety disorders where interpretation bias has been shown to play a causal role in maintaining the condition. Successful Treatment of Paranoia (STOP) is a CBM-I smartphone app targeting interpretation bias in paranoia. It has been developed following research on the feasibility and acceptability of a computerized version. This qualitative study extended that research by investigating the acceptability of STOP in individuals with paranoia. The study design and implementation were informed by the Evidence Standards Framework for Digital Health Technologies (DHTs) published by the UK National Institute for Health and Care Excellence (NICE).

objectiveThe aim of the study was to involve service users in the design, development, and testing of STOP and understand the degree of satisfaction with the product. We aimed to establish the extent to which STOP met the NICE minimum and best practice standards for DHTs, specifically its acceptability to intended end users.

methodsIn total, 12 participants experiencing mild to moderate levels of paranoia were recruited to complete 6 weekly sessions of STOP before being invited to a feedback interview to share their experiences. Interview questions revolved around the acceptability of the app, its perceived usefulness, and barriers to the intervention, as well as practicality and views on the use of a digital intervention in principle. Interviews were coded and analyzed using the framework analysis method, combining both deductive and inductive approaches.

resultsFramework analysis yielded 6 themes: independent use and personal fit; digital versus traditional approaches; user reactions and emotional impact; impact on thinking, awareness, and well-being; design, engagement, and usability; and intervention relevance and practical fit.

conclusionsSTOP was found to be a broadly acceptable intervention and was positively received by most participants. The study findings are in line with the NICE Evidence Standards Framework for DHTs, as intended end users were involved in the development, design, and testing of STOP and were mostly satisfied with it. These findings will contribute to the further iterative development of this intervention that targets interpretation bias in paranoia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-024-08570-3.

Indexed as

Cognitive Behavioral TherapyMobile ApplicationsParanoid DisordersPatient Acceptance of Health CareUser-Centered DesignAdultDigital HealthFeasibility StudiesFemaleHumansInterviews as TopicMaleMiddle AgedQualitative ResearchSmartphonecognitive bias modificationdigital health technologiesframework analysisinterpretation biasparanoiaqualitative

Identifiers

PMID40773747
PMCPMC12371281

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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.