The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
mHealth for mental health: Integrating smartphone technology in behavioral healthcare.
Abstract
The rapid growth in the use of smartphones has opened a new world of opportunities for use in behavioral health care. Mobile phone software applications (apps) are available for a variety of useful tasks to include symptom assessment, psychoeducation, resource location, and tracking of treatment progress. The latest two-way communication functionality of smartphones also brings new capabilities for telemental health. There is very little information available, however, regarding the integration of smartphone and other mobile technology into care. In this paper, we provide an overview of smartphone use in behavioral health care and discuss options for integrating mobile technology into clinical practice. We also discuss limitations, practical issues, and recommendations.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Recent studies have shown that those who received Web-based CBTi had improved sleep outcomes [22-26].”
From Tamper-Resistant Mobile Health Using Blockchain Technology. (2017) · cites this paper as [22]
In the citing paper
“Luxton et al. demonstrated the efficacy of predictive analytics in identifying mental health crises early, which is crucial for timely intervention [49]. For healthcare workers, predictive analytics can identify those at high risk of mental health issues before they manifest, enabling proactive intervention.”
From Mental Health in Healthcare Workers Post-COVID-19: A Latin American Review and Insights into Personalized Management Strategies (2024) · cites this paper as [49]
In the citing paper
“Smartphone, or mobile, apps may present a versatile and personalized platform for the delivery of a dedicated MBI for populations experiencing a concussion [28].”
In the citing paper
“However, many of the recent advances in smartphones have enabled the use of automated sensors and in-built cameras. 50”
From Effectiveness of mobile technologies delivering Ecological Momentary Interventions for stress and anxiety: A systematic review (2016) · cites this paper as [50]
In the citing paper
“Web-based programs delivered through smartphones are increasingly used to support the self-management of various health disorders; however, research on smartphone interventions for patients with chronic pain is limited [17].”
In the citing paper
“Furthermore, there is the possibility of loss, theft, or malfunction of the mobile device [5], or cybercriminals specifically targeting health information [207], all of which could result in the loss of sensitive data.”
From Smartphone Apps for the Treatment of Mental Disorders: Systematic Review (2020) · cites this paper as [5]
In the citing paper
“Among the advantages of using smartphones rather than the traditional personal computer s are their small size and mobility, making self-management support available to the user in most situations [17].”
Citations
Cites
Ellison, N. B., Steinfield, C., & Lampe, C. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00367.x · Cited by 9,939
McHugh, R. K., & Barlow, D. H. (2010) · American Psychologist · doi:10.1037/a0018121 · Cited by 909
Papastergiou, M. (2009) · Comput. Educ. · doi:10.1016/j.compedu.2009.04.001 · Cited by 598
Palermo, T. M., Eccleston, C., Lewandowski, A. S., de C. Williams, A. C., & Morley, S. (2010) · Pain · doi:10.1016/j.pain.2009.10.004 · Cited by 489
Pope, K. S., & Vásquez, M. J. T. (2011) · doi:10.1002/9781118001875.app1 · Cited by 431
Keenan, T. A. (1964) · Communications of the ACM · doi:10.1145/364005.364020 · Cited by 413
College Smoking-Cessation Using Cell Phone Text Messaging
Obermayer, J. L., Riley, W. T., Asif, O., & Jean-Mary, J. (2004) · Journal of American College Health · doi:10.3200/jach.53.2.71-78 · Cited by 321
Happy Ending: a randomized controlled trial of a digital multi‐media smoking cessation intervention
Brendryen, H., & Kraft, P. (2008) · Addiction · doi:10.1111/j.1360-0443.2007.02119.x · Cited by 292
Biofeedback Treatment for Headache Disorders: A Comprehensive Efficacy Review
Nestoriuc, Y., Martin, A., Rief, W., & Andrasik, F. (2008) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-008-9060-3 · Cited by 273
Mobile Interventions for Severe Mental Illness: Design and Preliminary Data From Three Approaches
Depp, C. A., Mausbach, B., Granholm, E., Cardenas, V., Ben-Zeev, D., Patterson, T. L., Lebowitz, B. D., & Jeste, D. V. (2010) · Journal of Nervous & Mental Disease · doi:10.1097/nmd.0b013e3181f49ea3 · Cited by 265 · cited 1×
“Podcasts are becoming a very popular way for individuals to obtain behavioral health information (Dingfelder, 2010).”
Background
Flagged first, then by citations
Cited by
Sorted by citations
Smartphones for smarter delivery of mental health programs: A systematic review
Donker, T., Petrie, K., Proudfoot, J., Clarke, J., Birch, M.-R., & Christensen, H. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2791 · Cited by 1,136
“Technical problems and factors related to telecommunication can arise (eg, battery failures, reliability and sustainability of connections [11]), and issues of data security, patient privacy, and the identification and timely management of crises and risk of harm must be carefully considered when integrating smartphon…”
BackgroundTrull, T. J., & Ebner-Priemer, U. (2013) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-050212-185510 · Cited by 761
mHealth: A Mechanism to Deliver More Accessible, More Effective Mental Health Care
Price, M., Yuen, E. K., Goetter, E. M., Herbert, J. D., Forman, E. M., Acierno, R., & Ruggiero, K. J. (2014) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.1855 · Cited by 488
Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia
Ben-Zeev, D., Brenner, C. J., Begale, M., Duffecy, J., Mohr, D. C., & Mueser, K. T. (2014) · Schizophrenia Bulletin · doi:10.1093/schbul/sbu033 · Cited by 493
Ben-Zeev, D., Scherer, E. A., Wang, R., Xie, H., & Campbell, A. T. (2015) · Psychiatric Rehabilitation Journal · doi:10.1037/prj0000130 · Cited by 429
Metadata
- Authors
- Luxton, D. D., McCann, R. A., Bush, N. E., Mishkind, M. C., & Reger, G. M.
- Venue
- Professional Psychology: Research and Practice
- Published
- 2011-12
- Volume
- 42
- Issue
- 6
- Pages
- 505-512
- ISSN
- 0735-7028 (ISSN-L)
- 1939-1323
- OpenAlex
- W2064721329
- Cited by
- 809
- References
- 38
- Citations by year
- 2026: 24 · 2025: 21 · 2024: 29 · 2023: 45 · 2022: 43 · 2021: 59 · 2020: 69 · 2019: 99 · 2018: 86 · 2017: 86 · 2016: 77 · 2015: 70 · 2014: 58 · 2013: 27 · 2012: 16
- FWCI
- 44.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Professional Psychology Research and Practice (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health, mobile application, behavioral health services, telemental health, mobile technology integration, symptom assessment, psychoeducation, clinical practice integration
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
