Evidence map›Paper›PMID 38851123›Full record

ArticleEpilepsy & behavior : E&B2024

User experience of a seizure risk forecasting app: A mixed methods investigation.

Rachel E Stirling, Ewan S Nurse, Daniel Payne, Jodie Naim-Feil, Honor Coleman, Dean R Freestone, Mark P Richarson, Benjamin H Brinkmann, Wendyl J D'Souza, David B Grayden and 2 more

Abstract read
In one paragraph

Article in Epilepsy & behavior : E&B, 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. Rhythms in Longitudinal Thalamic Recordings are Linked to Seizure Risk.medRxiv : the preprint server for health sciences · 2025
    Article
  4. Article
  5. Article
  6. Seizure prediction and forecasting: a scoping review.Current opinion in neurology · 2025
    Article
  7. 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

12 authors.

Rachel E StirlingDepartment of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Graeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia. Electronic address: rachel.stirling@unimelb.edu.au.
Ewan S NurseGraeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Seer Medical, Melbourne, Victoria, Australia; Department of Medicine, St Vincent's Hospital Melbourne, The University of Melbourne, Australia. Electronic address: ewan@seermedical.com.
Daniel PayneSeer Medical, Melbourne, Victoria, Australia. Electronic address: daniel@seermedical.com.
Jodie Naim-FeilDepartment of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Graeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia. Electronic address: jodie.feil@unimelb.edu.au.
Honor ColemanMelbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia; Epilepsy Research Centre, Department of Medicine (Austin Health), University of Melbourne, Victoria, Melbourne, Australia; Department of Neuroscience, Faculty of Medicine, Nursing & Health Science, Monash University, Melbourne, Australia. Electronic address: honor.coleman@unimelb.edu.au.
Dean R FreestoneSeer Medical, Melbourne, Victoria, Australia. Electronic address: deanrf@unimelb.edu.au.
Mark P RicharsonDivision of Neuroscience, King's College London, London, UK. Electronic address: mark.richardson@kcl.ac.uk.
Benjamin H BrinkmannDepartment of Neurology, Mayo Foundation, Rochester, MN, United States. Electronic address: brinkmann.benjamin@mayo.edu.
Wendyl J D'SouzaDepartment of Medicine, St Vincent's Hospital Melbourne, The University of Melbourne, Australia. Electronic address: wendyl1@icloud.com.
David B GraydenDepartment of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Graeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Department of Medicine, St Vincent's Hospital Melbourne, The University of Melbourne, Australia. Electronic address: grayden@unimelb.edu.au.
Mark J CookGraeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Seer Medical, Melbourne, Victoria, Australia; Department of Medicine, St Vincent's Hospital Melbourne, The University of Melbourne, Australia. Electronic address: markcook@unimelb.edu.au.
Philippa J KarolyDepartment of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia; Graeme Clark Institute of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia. Electronic address: karolyp@unimelb.edu.au.

Funding

Optimizing Pharmacotherapy with Noninvasive Wearable Sensors and Subscalp EEGUH3NS123066 · NINDS · MAYO CLINIC ROCHESTER · PI Benjamin H Brinkmann, Gregory A Worrell · 2025 to 2026
$1.4M
Optimizing Pharmacotherapy with Noninvasive Wearable Sensors and Subscalp EEGUG3NS123066 · NINDS · MAYO CLINIC ROCHESTER · PI BRINKMANN, BENJAMIN H, WORRELL, GREGORY A · 2022 to 2024
$1.2M
NINDS NIH HHS UG3 NS123066NINDS NIH HHS UH3 NS123066
6 · The paper itself

Abstract

objectiveOver recent years, there has been a growing interest in exploring the utility of seizure risk forecasting, particularly how it could improve quality of life for people living with epilepsy. This study reports on user experiences and perspectives of a seizure risk forecaster app, as well as the potential impact on mood and adjustment to epilepsy.

methodsActive app users were asked to complete a survey (baseline and 3-month follow-up) to assess perspectives on the forecast feature as well as mood and adjustment. Post-hoc, nine neutral forecast users (neither agreed nor disagreed it was useful) completed semi-structured interviews, to gain further insight into their perspectives of epilepsy management and seizure forecasting. Non-parametric statistical tests and inductive thematic analyses were used to analyse the quantitative and qualitative data, respectively.

resultsSurveys were completed by 111 users. Responders consisted of "app users" (n = 58), and "app and forecast users" (n = 53). Of the "app and forecast users", 40 % believed the forecast was accurate enough to be useful in monitoring for seizure risk, and 60 % adopted it for purposes like scheduling activities and helping mental state. Feeling more in control was the most common response to both high and low risk forecasted states. In-depth interviews revealed five broad themes, of which 'frustrations with lack of direction' (regarding their current epilepsy management approach), 'benefits of increased self-knowledge' and 'current and anticipated usefulness of forecasting' were the most common. SIGNIFICANCE: Preliminary results suggest that seizure risk forecasting can be a useful tool for people with epilepsy to make lifestyle changes, such as scheduling daily events, and experience greater feelings of control. These improvements may be attributed, at least partly, to the improvements in self-knowledge experienced through forecast use.

Indexed as

SeizuresAdolescentAdultAgedEpilepsyFemaleFollow-Up StudiesForecastingHumansMaleMiddle AgedMobile ApplicationsQuality of LifeRiskSurveys and QuestionnairesYoung AdultCommunity surveyMood questionnairesNon-invasive wearablesPatient experienceSeizure forecasting devices

Identifiers

PMID38851123
PMCPMC13529357

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.