Evidence map›Paper›PMID 40276421›Full record

ReviewCureus2025

What Clinicians Should Tell Patients About Wearable Devices and Data Privacy: A Narrative Review.

Joseph V Pergolizzi, Jo Ann K LeQuang, Salah N El-Tallawy, Giustino Varrassi

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Joseph V PergolizziPain Medicine, NEMA Research, Inc., Naples, USA.
Jo Ann K LeQuangScientific Communications, NEMA Research, Inc., Naples, USA.
Salah N El-TallawyAnesthesia and Pain Management, Faculty of Medicine, Minia University, Minia, EGY.
Giustino VarrassiPain Medicine, Fondazione Paolo Procacci, Rome, ITA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent growth of wearable medical device technology in fitness trackers, smartwatches, smartphone apps, and patient monitoring systems has created people-generated health data (PGHD) that may benefit medical science with large amounts of continuous real-world data. The prevalence of these devices speaks to their broad popularity and user-friendliness and may lead us one day to a more fully "connected healthcare system." Meanwhile, data security, confidentiality, and privacy issues have emerged in these hackable systems. Despite the promise of anonymized data, data can sometimes be re-identified. However, even without that step, data breaches may reveal information (name, address, date of birth, social security number, and so on) sufficient for identity theft. Clinicians are often asked about the utility and value of wearable devices or monitors. Still, most are unaware that data from these systems may be transmitted, stored, and even sold without the user's specific knowledge. Despite the confidentiality of medical information, cybersecurity surrounding wearables and monitors remains relatively lax, making them comparatively easy targets for cyber villains. It is also important that efforts be made to make PGHD more secure since medical data may be of great value to telehealth applications and AI-physician assistants. Clinicians should actively inform patients about the risks and benefits of wearables and similar devices.

Indexed as

cybersecurityethical implicationshealth appmobile health apppatient data privacysmart health wearablewearable deviceswearable technology

Identifiers

PMID40276421
PMCPMC12020962

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.