Evidence map›Paper›PMID 35314423›Full record

ArticleJMIR research protocols2022

Delivery of a Mental Health Intervention for Chronic Pain Through an Artificial Intelligence-Enabled App (Wysa): Protocol for a Prospective Pilot Study.

Megha Gupta, Tanya Malik, Chaitali Sinha

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07167056 (Artificial Intelligence-Powered Support For Quality Of Life Improvement In Patients With Cancer), which is not on this map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.9field-weighted citation impact, top 6% 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.

NCT07167056 narecruitingnot on this mapstarted 2025, after this paper: background citation

Artificial Intelligence-Powered Support For Quality Of Life Improvement In Patients With Cancer

TypeinterventionalSponsorCase Comprehensive Cancer CenterRan2025 to 2027Enrolled60ConditionsCancerArmsStandard of Care Psychotherapy, WYSA App
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
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  3. Digital Psychiatry with Chatbot: Recent Advances and Limitations.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2025
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  8. An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2023
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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

3 authors.

Megha GuptaWysa Inc, Boston, MA, United States.ORCID https://orcid.org/0000-0001-6047-2825
Tanya MalikWysa Inc, Boston, MA, United States.ORCID https://orcid.org/0000-0001-7508-0330
Chaitali SinhaWysa Inc, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8919-7134

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with chronic pain often experience coexisting, long-term and debilitating mental health comorbidities such as depression and anxiety. Artificial intelligence-supported cognitive behavioral therapy (AI-CBT) interventions could offer cost-effective, accessible, and potentially effective resources to address this problem. However, there is not enough research conducted about the efficacy of AI-CBT interventions for chronic pain.

objectiveThis prospective cohort study aims to examine the efficacy and use of an AI-CBT intervention for chronic pain (Wysa for Chronic Pain app, Wysa Inc) using a conversational agent (with no human intervention). To the best of our knowledge, this is the first such study for chronic pain using a fully-automated, free-text-based conversational agent.

methodsParticipants with self-reported chronic pain (n=500) will be recruited online on a rolling basis from April 2022 through posts on US-based internet communities within this prospective cohort. Informed consent is received from participants within the app, and the Wysa for Chronic Pain intervention is delivered remotely for 8 weeks. Outcome measures including a numeric pain rating scale and Patient-Reported Outcomes Measurement Information System-Pain Interference, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-9 questionnaires administered to test the effectiveness of the intervention on reducing levels of pain interference, depression, and anxiety. The therapeutic alliance created with the conversational agent will be assessed through the Working Alliance Inventory-Short Revised instrument. Retention and use statistics will be observed for adherence and engagement.

resultsThe study will open for recruitment in April 2022, and data collection is expected to be completed by August 2022. The results for the primary outcomes are expected to be published by late 2022.

conclusionsMental health conversational agents driven by artificial intelligence could be effective in helping patients with chronic pain learn to self-manage their pain and common comorbidities like depression and anxiety. The Wysa for Chronic Pain app is one such digital intervention that can potentially serve as a solution to the problems of affordability and scalability associated with interventions that include a human therapist. This prospective study examines the efficacy of the app as a treatment solution for chronic pain. It aims to inform future practices and digital mental health interventions for individuals with chronic pain. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/36910.

Indexed as

AI-enabled mental health assistantanxietyartificial intelligencechatbotchronic painconversational agentdepressiondigital healthdigital health interventionhealth care costmental healthmental health conversational agent

Identifiers

PMID35314423
PMCPMC9015778
OpenAlexW4221042235

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.