Evidence map›Paper›PMID 39175600›Full record

ArticleHealth science reports2024

Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care.

Moustaq Karim Khan Rony, Sharker Md Numan, Fateha Tuj Johra, Khadiza Akter, Fazila Akter, Mitun Debnath, Sujit Mondal, Md Wahiduzzaman, Mousumi Das, Mohammad Ullah and 3 more

Abstract read
In one paragraph

Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 3 pooled it
–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

33 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

13 authors.

Moustaq Karim Khan RonyMaster of Public Health Bangladesh Open University Gazipur Bangladesh.ORCID 0000-0002-6905-0554
Sharker Md NumanSchool of Science and Technology Bangladesh Open University Gazipur Bangladesh.
Fateha Tuj JohraMasters in Disaster Management University of Dhaka Dhaka Bangladesh.ORCID https://orcid.org/0009-0004-0301-6064
Khadiza AkterMaster of Public Health Daffodil International University Dhaka Bangladesh.ORCID https://orcid.org/0009-0001-4258-5321
Fazila AkterDhaka Nursing College affiliated with the University of Dhaka Dhaka Bangladesh.ORCID https://orcid.org/0009-0009-5887-8370
Mitun DebnathMaster of Public Health National Institute of Preventive and Social Medicine Dhaka Bangladesh.ORCID https://orcid.org/0000-0002-8082-1575
Sujit MondalMaster of Science in Nursing National Institute of Advanced Nursing Education and Research Mugda Dhaka Bangladesh.ORCID https://orcid.org/0009-0003-2932-0833
Md WahiduzzamanSchool of Medical Sciences Shahjalal University of Science and Technology Sylhet Bangladesh.ORCID https://orcid.org/0009-0007-4019-5913
Mousumi DasMaster of Public Health Leading University Sylhet Bangladesh.
Mohammad UllahCollege of Nursing International University of Business Agriculture and Technology Dhaka Bangladesh.
Mohammad Habibur RahmanSchool of Science and Technology Bangladesh Open University Gazipur Bangladesh.
Shuvashish Das BalaCollege of Nursing International University of Business Agriculture and Technology Dhaka Bangladesh.ORCID https://orcid.org/0000-0002-7473-0933
Mst Rina ParvinBangladesh Army (AFNS Officer) Combined Military Hospital Dhaka Dhaka Bangladesh.ORCID https://orcid.org/0000-0003-0111-6163

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the ever-increasing integration of artificial intelligence (AI) into health care, it becomes imperative to gain an in-depth understanding of how health care professionals, specifically nurse practitioners, perceive and approach this transformative technology. Objectives: This study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care. Methods: This qualitative research employed a descriptive and phenomenological approach using in-depth interviews. Data were collected through a semi-structured questionnaire with 37 nurse practitioners selected through purposive sampling, specifically Maximum Variation Sampling and Expert Sampling techniques, to ensure diversity in characteristics. Trustworthiness of the research was maintained through member checking and peer debriefing. Thematic analysis was employed to uncover recurring themes and patterns in the data. Results: The thematic analysis revealed nine main themes that encapsulated nurse practitioners' perceptions and attitudes toward AI adoption in health care. These included nurse practitioners' perceptions of AI implementation, attitudes toward AI adoption, patient-centered care and AI, quality of health care delivery and AI, ethical and regulatory aspects of AI, education and training needs, collaboration and interdisciplinary relationships, obstacles in integrating AI, and AI and health care policy. While this study found that nurse practitioners held a wide range of perspectives, with many viewings AI as a tool to enhance patient care. Conclusions: This research provides a valuable contribution to the evolving discourse surrounding AI adoption in health care. The findings underscore the necessity for comprehensive education and training in AI, accompanied by clear and robust ethical and regulatory guidelines to ensure the responsible integration of AI in health care practice. Furthermore, fostering collaboration and interdisciplinary relationships is pivotal for the successful incorporation of AI in health care. Policymakers should also address the challenges and opportunities that AI presents in the health care sector. This study enhances the ongoing conversation on AI adoption in health care by shedding light on the perspectives of nurses, thereby shaping future strategies for AI integration.

Indexed as

artificial intelligenceattitudeshealth carenurse practitionersperceptions

Identifiers

PMID39175600
PMCPMC11339127

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.