CoChat
Sign Up
Cited by 162Digital Mental Health InterventionsMobile Health and mHealth ApplicationsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

The DOI matches its Crossref record; 42 of the 43 references it cites were found in a registry or an index.

Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial

Open access
Graham, Andrea K., Greene, Carolyn J., Kwasny, Mary J., Kaiser, Susan M., Lieponis, Paul, Powell, Thomas, Mohr, David C.·2020·JAMA Psychiatry
DOI 10.1001/jamapsychiatry.2020.1011PMC PMC7240649
Open this paper in CoChat — free accountOpen PDF

Abstract

Importance: Depression and anxiety are common and disabling. Primary care is the de facto site for treating these mental health problems but is typically underresourced to meet the burden of these demands. Objective: To evaluate the efficacy of a mobile intervention platform, IntelliCare, for addressing depression and anxiety among primary care patients. Design, Setting, and Participants: Two-arm randomized clinical trial at internal medicine clinics at the University of Arkansas for Medical Sciences. Adult primary care patients (N = 146) who screened positive for depression on the Patient Health Questionnaire-8 (PHQ; score ≥ 10) or anxiety on the Generalized Anxiety Disorder-7 (GAD-7; score ≥ 8) were recruited between July 17, 2018, and December 14, 2018. Interventions: The coach-supported platform composed of a suite of apps, was delivered over 8 weeks. Wait list control participants received treatment as usual for 8 weeks, then the mobile platform. Main Outcomes and Measures: Primary outcomes were changes in depression (PHQ-9) and anxiety (GAD-7) during the intervention period. Secondary outcomes were differences in the proportion of patients who achieved recovery (PHQ-9/GAD-7 <5 or 50% improvement from baseline), sustainment of intervention effects during 2-month follow-up, and app use during the intervention period. Results: One hundred forty-six patients were included (119 of 146 were women [81.5%]; mean [SD] age, 42.3 [13.8] years). Of the 146 patients, 122 (83.6%) were diagnosed as having depression and 131 (89.7%) were diagnosed as having anxiety. A greater proportion of intervention vs wait list control participants achieved recovery from depression (n = 38 of 64 [59%] vs n = 18 of 58 [31%]; odds ratio, 3.25; 95% CI, 1.54-6.86) and anxiety (n = 37 of 65 [57%] vs n = 25 of 66 [38%]; odds ratio, 2.17; 95% CI, 1.08-4.36). Sustained effects were observed for depression (slope, 0.01; 95% CI, -0.09 to 0.10; P = .92) and anxiety scores (slope, 0.02; 95% CI, -0.08 to 0.12; P = .67) during follow-up. App use was high, with a median of 93 and 98 sessions among participants with depression and anxiety, respectively. Conclusions and Relevance: In this trial, a mobile intervention app was effective for depression and anxiety among primary care patients. Findings also support designing digital mental health interventions as platforms containing simple, brief apps that can be bundled by users to meet their needs. Trial Registration: ClinicalTrials.gov Identifier: NCT03500536.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamapsychiatry.2020.1011

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 43 references

Cited by

Sorted by citations

Items 101–162 of 162

Related

See all

Metadata

Authors
Graham, A. K., Greene, C. J., Kwasny, M. J., Kaiser, S. M., Lieponis, P., Powell, T., & Mohr, D. C.
Affiliations
  • Northwestern University (US)
  • University of Arkansas for Medical Sciences (US)
  • Actualize Therapy, Inc, Chicago, Illinois
Corresponding author
Mohr, David C.
ORCID
Venue
JAMA Psychiatry
Publisher
American Medical Association (AMA)
Published
2020-09-01
Volume
77
Issue
9
Pages
906
ISSN
2168-622X (ISSN-L)
DOI
10.1001/jamapsychiatry.2020.1011
PMC
PMC7240649
OpenAlex
W3027708473
Cited by
162
References
43
Citations by year
2026: 22 · 2025: 41 · 2024: 20 · 2023: 28 · 2022: 17 · 2021: 31 · 2020: 3
FWCI
17.86
Type
journal article
Language
en
Open access
Locations
  • JAMA Psychiatry (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (U54TR001629, UL1TR001422)
  • National Institute of Mental Health (P50MH119029, R44MH114725)
  • National Institute of Diabetes and Digestive and Kidney Diseases (K01DK116925)
  • National Center for Advancing Translational Sciences
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords
depression, anxiety, mobile health intervention, primary care, recovery from depression, sustained treatment effects, app use, PHQ-9, GAD-7, internal medicine clinic, digital mental health, waitlist control
MeSH terms
Internet-Based Intervention, Adult, Anxiety Disorders, Depressive Disorder, Female, Follow-Up Studies, Humans, Male, Middle Aged, Outcome and Process Assessment, Health Care, Patient Education as Topic, Primary Health Care, Psychotherapy, Telephone, Telemedicine, Text Messaging, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review