Evidence map›Paper›PMID 35877158›Full record

ArticleJMIR research protocols2022

Developing, Implementing, and Evaluating an Artificial Intelligence-Guided Mental Health Resource Navigation Chatbot for Health Care Workers and Their Families During and Following the COVID-19 Pandemic: Protocol for a Cross-sectional Study.

Jasmine M Noble, Ali Zamani, MohamadAli Gharaat, Dylan Merrick, Nathanial Maeda, Alex Lambe Foster, Isabella Nikolaidis, Rachel Goud, Eleni Stroulia, Vincent I O Agyapong and 6 more

Open 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. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
7.6field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Perspectives on Artificial Intelligence in Nursing in Asia.Asian/Pacific Island nursing journal · 2024
    Article
  10. Article
  11. 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
    Article
  12. Article
  13. Review
  14. 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

16 authors at 4 institutions in 1 country.

Jasmine M NobleDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-5979-136X
Ali ZamaniDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-7320-0976
MohamadAli GharaatDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0003-3342-0549
Dylan MerrickDepartment of Indigenous Studies, University of Saskatchewan, Regina, SK, Canada.ORCID https://orcid.org/0000-0001-7882-3478
Nathanial MaedaRehabilitation Robotics Lab, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-7511-7041
Alex Lambe FosterMood Disorders Society of Canada, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0002-8424-9457
Isabella NikolaidisMood Disorders Society of Canada, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0003-4117-8510
Rachel GoudTemerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-7857-320X
Eleni StrouliaDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-8784-8236
Vincent I O AgyapongDepartment of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0002-2743-0372
Andrew J GreenshawDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-9097-900X
Simon LambertDepartment of Indigenous Studies, University of Saskatchewan, Regina, SK, Canada.ORCID https://orcid.org/0000-0002-7744-6372
Dave GallsonMood Disorders Society of Canada, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0003-4876-1071
Ken PorterMood Disorders Society of Canada, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0001-9802-3021
Debbie TurnerMood Disorders Society of Canada, Ottawa, ON, Canada.ORCID https://orcid.org/0000-0002-6033-2918
Osmar ZaianeDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-0060-5988
University of Alberta · CAUniversity of Saskatchewan · CADalhousie University · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundApproximately 1 in 3 Canadians will experience an addiction or mental health challenge at some point in their lifetime. Unfortunately, there are multiple barriers to accessing mental health care, including system fragmentation, episodic care, long wait times, and insufficient support for health system navigation. In addition, stigma may further reduce an individual's likelihood of seeking support. Digital technologies present new and exciting opportunities to bridge significant gaps in mental health care service provision, reduce barriers pertaining to stigma, and improve health outcomes for patients and mental health system integration and efficiency. Chatbots (ie, software systems that use artificial intelligence to carry out conversations with people) may be explored to support those in need of information or access to services and present the opportunity to address gaps in traditional, fragmented, or episodic mental health system structures on demand with personalized attention. The recent COVID-19 pandemic has exacerbated even further the need for mental health support among Canadians and called attention to the inefficiencies of our system. As health care workers and their families are at an even greater risk of mental illness and psychological distress during the COVID-19 pandemic, this technology will be first piloted with the goal of supporting this vulnerable group.

objectiveThis pilot study seeks to evaluate the effectiveness of the Mental Health Intelligent Information Resource Assistant in supporting health care workers and their families in the Canadian provinces of Alberta and Nova Scotia with the provision of appropriate information on mental health issues, services, and programs based on personalized needs.

methodsThe effectiveness of the technology will be assessed via voluntary follow-up surveys and an analysis of client interactions and engagement with the chatbot. Client satisfaction with the chatbot will also be assessed.

resultsThis project was initiated on April 1, 2021. Ethics approval was granted on August 12, 2021, by the University of Alberta Health Research Board (PRO00109148) and on April 21, 2022, by the Nova Scotia Health Authority Research Ethics Board (1027474). Data collection is anticipated to take place from May 2, 2022, to May 2, 2023. Publication of preliminary results will be sought in spring or summer 2022, with a more comprehensive evaluation completed by spring 2023 following the collection of a larger data set.

conclusionsOur findings can be incorporated into public policy and planning around mental health system navigation by Canadian mental health care providers-from large public health authorities to small community-based, not-for-profit organizations. This may serve to support the development of an additional touch point, or point of entry, for individuals to access the appropriate services or care when they need them, wherever they are. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/33717.

Indexed as

chatbotconversational agenteHealthelectronic health carehealth system navigationmobile phone

Identifiers

PMID35877158
PMCPMC9361145
OpenAlexW4285364236

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.