Evidence map›Paper›PMID 38161825›Full record

ArticleCureus2023

Factors Affecting the Adoption of Artificial Intelligence-Enabled Virtual Assistants for Leukemia Self-Management.

Turki Alanzi, Reham Almahdi, Danya Alghanim, Lamyaa Almusmili, Amani Saleh, Sarah Alanazi, Kienaz Alshobaki, Renad Attar, Abdulaziz Al Qunais, Haneen Alzahrani and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

15 authors.

Turki AlanziDepartment of Health Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, SAU.
Reham AlmahdiCollege of Medicine, Al Baha University, Al Baha, SAU.
Danya AlghanimCollege of Medicine and Surgery, Royal College of Surgeons in Ireland, Dublin, IRL.
Lamyaa AlmusmiliCollege of Pharmacy, Jazan University, Jazan, SAU.
Amani SalehFaculty of Pharmacy, Ibnsina National College of Medical Studies, Jeddah, SAU.
Sarah AlanaziDepartment of Pharmacy, Almoosa Specialist Hospital, Al Mubarraz, SAU.
Kienaz AlshobakiCollege of Medicine, King Abdulaziz University, Jeddah, SAU.
Renad AttarCollege of Medicine, King Abdulaziz University, Jeddah, SAU.
Abdulaziz Al QunaisCollege of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, SAU.
Haneen AlzahraniDepartment of Hematology, Armed Forces Hospital at King Abdulaziz Airbase Dhahran, Dhahran, SAU.
Rawan AlshehriCollege of Medicine, Taif University, Taif, SAU.
Amenah SulailCollege of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, SAU.
Ali AlblwiCollege of Medicine, King Abdulaziz University, Jeddah, SAU.
Nawaf AlanziDepartment of Blood Bank, Regional Laboratory and Blood Banks Arar, Arar, SAU.
Nouf AlanziDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Jouf, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aim and purposeThe purpose of this study is to analyze the various influencing factors affecting the adoption of artificial intelligence (AI)-enabled virtual assistants (VAs) for self-management of leukemia.

methodsA cross-sectional survey design is adopted in this study. The questionnaire included eight factors (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of AI-enabled virtual assistants. A total of 397 leukemia patients participated in the online survey.

resultsPerformance expectancy (μ = 3.14), effort expectancy (μ = 3.05), and personal innovativeness (μ = 3.14) were identified to be the major influencing factors of AI adoption. Statistically significant differences (p < .05) were observed between the gender-based and age groups of the participants in relation to the various factors. In addition, perceived privacy risks were negatively correlated with all other factors.

conclusionAlthough there are negative factors such as privacy risks and ethical issues in AI adoption, perceived effectiveness and ease of use among individuals are leading to greater adoption of AI-enabled VAs.

Indexed as

artificial intelligencebenefitscancerchallengesleukemiatechnology acceptancevirtual assistants

Identifiers

PMID38161825
PMCPMC10757561

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.