Evidence map›Paper›PMID 39989584›Full record

ArticleJournal of family medicine and primary care2025

The use of a smartphone app for self-monitoring by patients with bipolar disorder being treated in a primary care setting.

Omar H Elsayed, John Cecil, Richard Priesmeyer, Gregg Siegel, Phyllis Siegel, Rif S El-Mallakh

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 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. 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

6 authors.

Omar H ElsayedDepartment of Psychiatry and Behavioral Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States.
John CecilRetired, President and Owner, Cecil Clinic, Paduch, Kentucky, United States.
Richard PriesmeyerDepartment of Management and Marketing, St Mary's University, San Antonio, Texas, United States.
Gregg SiegelBiomedical Development Corporation, San Antonio, Texas, United States.
Phyllis SiegelBiomedical Development Corporation, San Antonio, Texas, United States.
Rif S El-MallakhDepartment of Psychiatry and Behavioral Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States.

Funding

Nonlinear Computation Tool to Chart Trajectories of Bipolar DisorderR42MH091997 · NIMH · BIOMEDICAL DEVELOPMENT CORPORATION · PI BOWDEN, CHARLES LEE, PRIESMEYER, RICHARD · 2015 to 2016
$1.5M
NIMH NIH HHS R42 MH091997
6 · The paper itself

Abstract

Background: Self-monitoring and self-management are growing phenomena in the care of chronic illnesses, like bipolar disorder. A significant fraction of patients with bipolar disorder are cared for by primary care providers. The use of smart technology may be effective in this setting. Method: KIOS-Bipolar, a smartphone app that proved superior in a randomized, controlled trial, was beta-tested for two-month periods in 12 patients with bipolar disorder who were under the care of a primary care clinic. Results: Adherence to the app was 100%. Patients experienced improvements in depressive (-41%) and manic (-46%) symptoms and overall instability (-39%). Patients felt that the system was user-friendly with an average system usability score of 80.8 (range 48-100). Five participants (41.8%) gave a system usability score ≥ 90. Discussion: This open trial suggests that utilization of a self-management tool may be a useful adjunct in the treatment of patients with bipolar disorder in the primary care setting.

Indexed as

Appbipolarself-monitoring

Identifiers

PMID39989584
PMCPMC11845010

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.