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 accessAbstract
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.
Integrity signals
Registry
Cites
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.
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?
The cited source says what the claim attributes to it.
In the citing paper
“and can lead to greater reductions in anxiety compared with usual care [8]”
From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [8]
In the citing paper
“Although some trials have shown strong patient engagement in health care settings (59), others have had high dropout rates (60, 61).”
From Banbury forum consensus statement on the path forward for digital mental health treatment (2021) · cites this paper as [59]
In the citing paper
“Patient engagement has been a challenge for some DMHTs. Although some trials have shown strong patient engagement in health care settings (59), others have had high dropout rates (60, 61).”
From Banbury forum consensus statement on the path forward for digital mental health treatment (2021) · cites this paper as [59]
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
The PHQ-9: Validity of a brief depression severity measure
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2001.016009606.x · Cited by 44,910
A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.10.1092 · Cited by 31,765
Posner, K., Brown, G. K., Stanley, B., Brent, D. A., Yershova, K. V., Oquendo, M. A., Currier, G. W., Melvin, G. A., Greenhill, L., Shen, S., et al. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.10111704 · Cited by 5,157
The PHQ-8 as a measure of current depression in the general population
Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B. W., Berry, J. T., & Mokdad, A. H. (2009) · Journal of Affective Disorders · doi:10.1016/j.jad.2008.06.026 · Cited by 5,121
Epidemiology of Adult DSM-5 Major Depressive Disorder and Its Specifiers in the United States
Hasin, D. S., Sarvet, A. L., Meyers, J. L., Saha, T. D., Ruan, W. J., Stohl, M., & Grant, B. F. (2018) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.4602 · Cited by 1,737
Screening for Depression in Adults: US Preventive Services Task Force Recommendation Statement
Siu, A. L., and the US Preventive Services Task Force (USPSTF), Bibbins-Domingo, K., Grossman, D. C., Baumann, L. C., Davidson, K. W., Ebell, M., García, F. A. R., Gillman, M., Herzstein, J., et al. (2016) · JAMA · doi:10.1001/jama.2015.18392 · Cited by 1,407
Collaborative Care for Depression: A Cumulative Meta-analysis and Review of Longer-term Outcomes
Gilbody, S. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.21.2314 · Cited by 1,340
Adherence in Internet Interventions for Anxiety and Depression
Christensen, H., Griffiths, K. M., & Farrer, L. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1194 · Cited by 1,133
Firth, J., Torous, J., Nicholas, J., Carney, R., Pratap, A., Rosenbaum, S., & Sarris, J. (2017) · World Psychiatry · doi:10.1002/wps.20472 · Cited by 1,097
Objective user engagement with mental health apps: systematic search and panel-based usage analysis
Baumel, A., Muench, F., Edan, S., & Kane, J. M. (2019) · Journal of Medical Internet Research · doi:10.2196/14567 · Cited by 965
Andrews, G., Basu, A., Cuijpers, P., Craske, M. G., McEvoy, P., English, C. L., & Newby, J. M. (2018) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2018.01.001 · Cited by 922
A Systematic Review of the Impact of Adherence on the Effectiveness of e-Therapies
Donkin, L., Christensen, H., Naismith, S. L., Neal, B., Hickie, I. B., & Glozier, N. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1772 · Cited by 876
Barlow, D. H., Farchione, T. J., Bullis, J. R., Gallagher, M. W., Murray-Latin, H., Sauer-Zavala, S., Bentley, K. H., Thompson-Hollands, J., Conklin, L. R., Boswell, J. F., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.2164 · Cited by 853
Whitney, D. G., & Peterson, M. D. (2019) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2018.5399 · Cited by 770
Firth, J., Torous, J., Nicholas, J., Carney, R., Rosenbaum, S., & Sarris, J. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.04.046 · Cited by 675
Psychological treatment of generalized anxiety disorder: A meta-analysis
Cuijpers, P., Sijbrandij, M., Koole, S., Huibers, M., Berking, M., & Andersson, G. (2014) · Clinical Psychology Review · doi:10.1016/j.cpr.2014.01.002 · Cited by 527
Ruscio, A. M., Hallion, L. S., Lim, C. C. W., Aguilar-Gaxiola, S., Al-Hamzawi, A., Alonso, J., Andrade, L. H., Borges, G., Bromet, E. J., Bunting, B., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.0056 · Cited by 492
Mohr, D. C., Lyon, A. R., Lattie, E. G., Reddy, M., & Schueller, S. M. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7725 · Cited by 432
Self-citationGilbody, S., Littlewood, E., Hewitt, C., Brierley, G., Tharmanathan, P., Araya, R., Barkham, M., Bower, P., Cooper, C., Gask, L., et al. (2015) · BMJ · doi:10.1136/bmj.h5627 · Cited by 409
Beyond self-report: tools to compare estimated and real-world smartphone use
Andrews, S., Ellis, D. A., Shaw, H., & Piwek, L. (2015) · PLOS ONE · doi:10.1371/journal.pone.0139004 · Cited by 408
McCrone, P., Knapp, M., Proudfoot, J., Ryden, C., Cavanagh, K., Shapiro, D. A., Ilson, S., Gray, J. A., Goldberg, D., Mann, A., et al. (2004) · British Journal of Psychiatry · doi:10.1192/bjp.185.1.55 · Cited by 371
Mohr, D. C., Weingardt, K. R., Reddy, M., & Schueller, S. M. (2017) · Psychiatric Services · doi:10.1176/appi.ps.201600541 · Cited by 365
Self-citationTreatment of Adult Depression in the United States
Olfson, M., Blanco, C., & Marcus, S. C. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.5057 · Cited by 352
Perceived barriers to psychological treatments and their relationship to depression
Mohr, D. C., Ho, J., Duffecy, J., Baron, K. G., Lehman, K. A., Jin, L., & Reifler, D. (2010) · Journal of Clinical Psychology · doi:10.1002/jclp.20659 · Cited by 347
Self-citationIntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety
Mohr, D. C., Tomasino, K. N., Lattie, E. G., Palac, H. L., Kwasny, M. J., Weingardt, K., Karr, C. J., Kaiser, S. M., Rossom, R. C., Bardsley, L. R., et al. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6645 · Cited by 301
Self-citationScreening for Depression in Adult Patients in Primary Care Settings: A Systematic Evidence Review
O’Connor, E., Whitlock, E. P., Beil, T. L., & Gaynes, B. N. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-11-200912010-00007 · Cited by 279
Barriers to psychotherapy among depressed and nondepressed primary care patients
Mohr, D. C., Hart, S. L., Howard, I., Julian, L., Vella, L., Catledge, C., & Feldman, M. D. (2006) · Annals of Behavioral Medicine · doi:10.1207/s15324796abm3203_12 · Cited by 276
Self-citationA Solution-Focused Research Approach to Achieve an Implementable Revolution in Digital Mental Health
Mohr, D. C., Riper, H., & Schueller, S. M. (2018) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.3838 · Cited by 204
Self-citationPham, Q., Graham, G., Carrion, C., Morita, P. P., Seto, E., Stinson, J. N., & Cafazzo, J. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/11941 · Cited by 131
Effectiveness of Online Collaborative Care for Treating Mood and Anxiety Disorders in Primary Care
Rollman, B. L., Belnap, B. H., Abebe, K. Z., Spring, M. B., Rotondi, A. J., Rothenberger, S. D., & Karp, J. F. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.3379 · Cited by 118
Gilbody, S., Brabyn, S., Lovell, K., Kessler, D., Devlin, T., Smith, L., Araya, R., Barkham, M., Bower, P., Cooper, C., et al. (2017) · British Journal of Psychiatry · doi:10.1192/bjp.bp.116.192435 · Cited by 116
Mohr, D. C., Schueller, S. M., Tomasino, K. N., Kaiser, S. M., Alam, N., Karr, C., Vergara, J. L., Gray, E. L., Kwasny, M. J., & Lattie, E. G. (2019) · Journal of Medical Internet Research · doi:10.2196/13609 · Cited by 116
Self-citationCharacteristics of effective psychological treatments of depression: a metaregression analysis
Cuijpers, P. J., van Straten, A., Warmerdam, L., & Smits, N. (2008) · Psychotherapy Research · doi:10.1080/10503300701442027 · Cited by 109
The association between adherence and outcome in an Internet intervention for depression
Fuhr, K., Schröder, J., Berger, T., Moritz, S., Meyer, B., Lutz, W., Hohagen, F., Hautzinger, M., & Klein, J. P. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.12.028 · Cited by 97
Experimental therapeutics for digital mental health.
Graham, A. K., Lattie, E. G., & Mohr, D. C. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.2075 · Cited by 93
Self-citationCollaborative care for anxiety disorders in primary care: a systematic review and meta-analysis
Muntingh, A., Feltz-Cornelis, C. M. V. D., van Marwijk, H., Spinhoven, P., & van Balkom, A. J. L. M. (2016) · BMC Family Practice · doi:10.1186/s12875-016-0466-3 · Cited by 92
Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study
Zhang, R., Nicholas, J., Knapp, A. A., Graham, A. K., Gray, E., Kwasny, M. J., Reddy, M., & Mohr, D. C. (2019) · Journal of Medical Internet Research · doi:10.2196/15644 · Cited by 91
Self-citationMultimodal e-mental health treatment for depression: a feasibility trial
Mohr, D. C., Duffecy, J., Jin, L., Ludman, E. J., Lewis, A., Begale, M., & McCarthy Jr, M. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1370 · Cited by 82
Self-citationIs It Time to Ban the P Value?
KRAEMER, H. C. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.1965 · Cited by 58
Mental Health Apps in Psychiatric Treatment: A Patient Perspective on Real World Technology Usage
Chiauzzi, E., & Newell, A. (2019) · JMIR Mental Health · doi:10.2196/12292 · Cited by 46
Kwasny, M., Schueller, S. M., Lattie, E. G., Gray, E., & Mohr, D. C. (2018) · JMIR Mental Health · doi:10.2196/11572 · Cited by 37
Self-citationGraham, A. K., Greene, C. J., Powell, T., Lieponis, P., Lunsford, A., Peralta, C. D., Orr, L. C., Kaiser, S. M., Alam, N., Berhane, H., et al. (2020) · Translational Behavioral Medicine · doi:10.1093/tbm/ibz140 · Cited by 37
Self-citation
Cited by
Sorted by citations
Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., Carvalho, A. F., Keshavan, M., Linardon, J., & Firth, J. (2021) · World Psychiatry · doi:10.1002/wps.20883 · Cited by 1,199
Borghouts, J., Eikey, E., Mark, G., De Leon, C., Schueller, S. M., Schneider, M., Stadnick, N., Zheng, K., Mukamel, D., & Sorkin, D. H. (2021) · Journal of Medical Internet Research · doi:10.2196/24387 · Cited by 1,069
“Although some DMHIs have been shown to be as effective as traditional mental health services (eg, psychotherapy and pharmacotherapy) in improving mental health conditions such as depression [7] and can lead to greater reductions in anxiety compared with usual care [8], engagement with these technologies remains to be…”
BackgroundThe Economic Burden of Adults with Major Depressive Disorder in the United States (2010 and 2018)
Greenberg, P. E., Fournier, A.-A., Sisitsky, T., Simes, M., Berman, R., Koenigsberg, S. H., & Kessler, R. C. (2021) · PharmacoEconomics · doi:10.1007/s40273-021-01019-4 · Cited by 838
Banbury forum consensus statement on the path forward for digital mental health treatment
Mohr, D. C., Azocar, F., Bertagnolli, A., Choudhury, T., Chrisp, P., Frank, R., Harbin, H., Histon, T., Kaysen, D., Nebeker, C., et al. (2021) · Psychiatric Services · doi:10.1176/appi.ps.202000561 · Cited by 115
Self-citationYeo, G., Reich, S. M., Liaw, N. A., & Chia, E. Y. M. (2023) · Journal of Medical Internet Research · doi:10.2196/51268 · Cited by 143
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.
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2020-09-01
- Volume
- 77
- Issue
- 9
- Pages
- 906
- ISSN
- 2168-622X (ISSN-L)
- 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
- bronze
- doi.org
- 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
