Evidence map›Paper›PMID 39114464›Full record

ReviewmHealth2024

Performance, impact and experiences of using wearable devices for seizure detection in community-based settings: a mixed methods systematic review.

Maxime Sasseville, Eugène Attisso, Marie-Pierre Gagnon, Jean-Marc-Wilfried Supper, Steven Ouellet, Samira Amil, Elie Bou Assi, Dang Khoa Nguyen

Abstract readReview
In one paragraph

Review in mHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Observational
  5. Review
  6. Article
  7. 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

8 authors.

Maxime Sasseville *Faculty of Nursing Sciences, Université Laval, Quebec, Canada.ORCID https://orcid.org/0000-0003-1694-1414
Eugène Attisso *Faculty of Nursing Sciences, Université Laval, Quebec, Canada.ORCID https://orcid.org/0000-0002-0820-0993
Marie-Pierre Gagnon *Faculty of Nursing Sciences, Université Laval, Quebec, Canada.ORCID https://orcid.org/0000-0002-0782-5457
Jean-Marc-Wilfried SupperFaculty of Nursing Sciences, Université Laval, Quebec, Canada.ORCID https://orcid.org/0009-0002-6642-5768
Steven OuelletFaculty of Nursing Sciences, Université Laval, Quebec, Canada.ORCID https://orcid.org/0000-0003-2158-0043
Samira AmilVitam Research Center on Sustainable Health, Quebec, Canada.ORCID https://orcid.org/0000-0002-4024-9762
Elie Bou AssiCentre de Recherche du CHUM (CRCHUM), Department of Neuroscience, Université de Montréal, Montréal, QC, Canada.ORCID https://orcid.org/0000-0001-8248-2565
Dang Khoa NguyenCentre de Recherche du CHUM (CRCHUM), Department of Neuroscience, Université de Montréal, Montréal, QC, Canada.ORCID https://orcid.org/0000-0003-1550-4423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is growing scientific evidence that wearable devices for seizure detection (WDD) perform well in controlled environments. However, their impact on the health and experience of patients with epilepsy (PWE) in community-based settings is less documented. We aimed to synthesize the scientific evidence about the performance of wearable devices used by PWE in community-based settings, and their impact on health outcomes and patient experience. Methods: We performed a mixed methods systematic review. We performed searches in PubMed, Google Scholar, Web of Science and Embase from inception until December 2022. Independent reviewers checked studies published in English for eligibility based on predefined inclusion and exclusion criteria. We collected information about studies, wearable devices, their performance, and their impact on health outcomes and patient experience. We used a narrative method to synthetize separately data for each question. We assessed the quality of included studies with the QUADAS-C and MMAT tools. Results: On a total of 9,595 publications, 10 studies met our eligibility criteria. Study populations included mostly PWE who were young (≤18 years) and/or their caregivers. Participants were living at home in most studies. Accelerometer was the wearable device mostly used for seizure detection. Wearable device performance was high (sensitivity ≥80% and false alarm rate ≤1/day), but some concerns remained due to false alarms according to qualitative studies. There was no significant effect of wearable device on quality of life (QoL) measures and no study reported quantitatively other health outcomes. Qualitative studies reported positive effect of wearable devices on QoL, seizure management and seizure-related injuries. Overall, patients reported that the device, especially the accelerometer, was suitable, but when the device was too visible, they found it uncomfortable. Study quality was low to medium. Conclusions: There is low quality scientific evidence supporting the performance of WDD in a home environment. Although qualitative findings support the positive impacts of wearable devices for patients and caregivers, more quantitative studies are needed to assess their impact on health outcomes such as QoL and seizure-related injuries.

Indexed as

community healthepilepsytechnologyWearable

Identifiers

PMID39114464
PMCPMC11304097

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.