Evidence map›Paper›PMID 38640476›Full record

ArticleJMIR formative research2024

AI-Led Mental Health Support (Wysa) for Health Care Workers During COVID-19: Service Evaluation.

Christel Lynne Chang, Chaitali Sinha, Madhavi Roy, John Chee Meng Wong

Registry-linked trialAbstract read
In one paragraph

Article in JMIR formative research, 2024. 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Artificial Intelligence in and Beyond Healthcare Psychology.Journal of clinical psychology in medical settings · 2025
    Review
  4. Article
  5. Article
  6. Review
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

4 authors.

Christel Lynne ChangYeo Boon Khim Mind Science Centre, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0003-0725-9675
Chaitali SinhaWysa Inc, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8919-7134
Madhavi RoyWysa Inc, Boston, MA, United States.ORCID https://orcid.org/0000-0003-2413-9763
John Chee Meng WongYeo Boon Khim Mind Science Centre, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0002-5580-6234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe impact that the COVID-19 pandemic has had on health care workers' mental health, in particular, cannot be ignored. Not only did the pandemic exacerbate mental health challenges through elevated stress, anxiety, risk of infection, and social isolation, but regulations to minimize infection additionally hindered the conduct of traditional in-person mental health care.

objectiveThis study explores the feasibility of using Wysa, an artificial intelligence-led mental health app, among health care workers.

methodsA national tertiary health care cluster in Singapore piloted the use of Wysa among its own health care workers to support the management of their mental well-being during the pandemic (July 2020-June 2022). The adoption of this digital mental health intervention circumvented the limitations of in-person contact and enabled large-scale access to evidence-based care. Rates and patterns of user engagement were evaluated.

resultsOverall, the opportunity to use Wysa was well-received. Out of the 527 staff who were onboarded in the app, 80.1% (422/527) completed a minimum of 2 sessions. On average, users completed 10.9 sessions over 3.80 weeks. The interventions most used were for sleep and anxiety, with a strong repeat-use rate. In this sample, 46.2% (73/158) of health care workers reported symptoms of anxiety (Generalized Anxiety Disorder Assessment-7 [GAD-7]), and 15.2% (24/158) were likely to have symptoms of depression (Patient Health Questionnaire-2 [PHQ-2]).

conclusionsBased on the present findings, Wysa appears to strongly engage those with none to moderate symptoms of anxiety. This evaluation demonstrates the viability of implementing Wysa as a standard practice among this sample of health care workers, which may support the use of similar digital interventions across other communities.

Indexed as

AIappapplicationartificial intelligenceCOVID-19digitalhealth care workersmental healthpandemicWysa

Identifiers

PMID38640476
PMCPMC11034576

What OpenQuestion holds

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LicenceCC BY
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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.