Evidence map›Paper›PMID 41939740›Full record

ArticleFrontiers in medicine2026

Sociotechnical-systems analysis of IoT-AI convergence in cosmetic health.

Abdulrahman Makhseed, Husain Arian, Ali Shuaib

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Abdulrahman MakhseedDepartment of Plastic Surgery, Jaber Al-Ahmad Hospital, Ministry of Health, Kuwait City, Kuwait.
Husain ArianDepartment of Plastic Surgery, Jahra Hospital, Ministry of Health, Al Jahra, Kuwait.
Ali ShuaibBiomedical Engineering Unit, Department of Physiology, College of Medicine, Kuwait University, Kuwait City, Kuwait.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The convergence of Internet of Things (IoT) devices and artificial intelligence (AI) in cosmetic health offers significant potential for preventive healthcare and personalized beauty-health integration. Despite market growth, implementation of IoT-AI technologies remains fragmented due to misalignment between technical capabilities and social systems. This perspective article uses sociotechnical-system analysis to examine implementation challenges in digital beauty-health initiatives. The analysis revealed that devices prioritized technical accuracy over integration with user routines, applications achieved consumer adoption while creating workflow challenges for healthcare systems, and algorithms exhibited performance disparities across populations. Studies on sociotechnical systems in healthcare demonstrate that successful implementation requires joint optimization across technical infrastructure, social systems, organizational contexts, and environmental factors. We propose establishing relevant sociotechnical standards, validating integration through diverse trials, and achieving healthcare alignment to this end. The priority areas include UV monitoring, skin barrier assessment, and AI-driven personalization. Without coordinated action addressing accuracy, workflow integration, and algorithmic fairness, cosmetic IoT-AI risks amplifying existing disparities rather than democratizing personalized cosmetic health.

Indexed as

artificial intelligence (AI)cosmetic healthdigital healthInternet of Things (IoT)personalized beautypreventive healthcaresociotechnical systems

Identifiers

PMID41939740
PMCPMC13046524

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.