Evidence map›Paper›PMID 39093108›Full record

ArticleWork (Reading, Mass.)2024

Ethical considerations in telehealth and artificial intelligence for work related musculoskeletal disorders: A scoping review.

Adnan Karaibrahimoglu, Fuat İnce, Gholamreza Hassanzadeh, Ali Alizadeh, Kian Bagheri, Irem Yucel, Ardalan Shariat

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Work (Reading, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  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

7 authors.

Adnan KaraibrahimogluDepartment of Biostatistics and Medical Informatics, Faculty of Medicine, Süleyman Demirel University, Isparta, Turkiye.
Fuat İnceDepartment of History of Medicine and Ethics, Faculty of Medicine, Süleyman Demirel University, Isparta, Turkiye.
Gholamreza HassanzadehDepartment of Digital Health, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Ali AlizadehDepartment of Digital Health, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Kian BagheriDepartment of Medicine, Campbell University School of Osteopathic Medicine, Lillington, NC, USA.
Irem YucelDepartment of Statistics, Faculty of Science, Süleyman Demirel University, Isparta, Turkiye.
Ardalan ShariatDepartment of Digital Health, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to perform tasks that typically require human intelligence. The integration of AI and telehealth applications in healthcare raises ethical concerns such as bias, transparency, data privacy, and accountability for errors. Several studies have assessed this topic, particularly with regard to musculoskeletal disorders, which will be the focus of this manuscript.

objectiveWe will examine key ethical concepts including informed consent, data protection, confidentiality, physician malpractice, liability, and telemedicine regulations.

methodsEthical issues pertaining to the topic were explored through a review paper. The primary objective of this scoping review was to map and synthesize the existing literature concerning ethical considerations in telehealth and AI for work-related musculoskeletal disorders.

resultsResearch demonstrates that medication effectiveness, patient and physician satisfaction, and accessibility costs are higher with telemedicine and AI methods compared to in-person approaches, particularly for work-related musculoskeletal disorders. Therefore, addressing ethical issues, including patient data privacy and security, is crucial in this field. By considering these factors, the adoption of emerging AI and telemedicine applications, especially for work-related musculoskeletal disorders, is likely to increase.

conclusionAI and telemedicine offer significant advantages, particularly in addressing work-related musculoskeletal disorders. However, ethical and legal issues surrounding their practice require standardized rules to ensure equitable access, quality care, sustainable costs, professional liability, patient privacy, data protection, and confidentiality. Further practical research studies are needed to address these considerations more effectively.

Indexed as

Artificial IntelligenceConfidentialityMusculoskeletal DiseasesTelemedicineHumansInformed ConsentOccupational Diseasesartificial intelligencedigital healthEthicsmHealthmusculoskeletal diseasetelehealthtelemedicine

Identifiers

PMID39093108
PMCPMC11612935

What OpenQuestion holds

Textmetadata
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.